Leading Learning

Studying Innovation with Mary Byers

Jackie Harman — Tue, 19 Oct 2021 10:36:31 +0000

This podcast series is our attempt to offer a theoretical learning business MBA program, and we invite you to play along. Imagine you’re in business school and about to hear a guest lecture by Mary Byers, a speaker, facilitator, consultant, and author of several books, including Race for Relevance: Five Radical Changes for Associations. She’s also host of the Successful Associations Today Podcast. Her work centers on helping organizations remain relevant in a rapidly changing environment, and her main area of interest is innovation and evolution in all things—organizationally, educationally, and otherwise.

In this third episode in our seven-part learning business MBA series, Celisa talks with Mary about what it takes to succeed as a learning business and her related thoughts around innovation and continuous evolution. They discuss the idea of shrinking to grow, why organizations need a digital-first mindset, and the importance of a go-forward strategy.

To tune in, listen below. To make sure you catch all future episodes, be sure to subscribe via RSS, Apple Podcasts , Spotify, Stitcher Radio, iHeartRadio, PodBean, or any podcatcher service you may use (e.g., Overcast). And, if you like the podcast, be sure to give it a tweet.

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[00:31] – Intro and background info about Mary

What it Takes to Succeed as a Learning Business

[02:04] – What do those leading and working in a learning business need to know or be able to do to be successful?

Mary mentions three things:

Be committed to continuous evolution. Complacency leads to irrelevance.
Be comfortable launching small pilots and recalibrating if necessary. Flexible organizations are successful organizations.
Be comfortable dancing with uncertainty. We dance with uncertainty all the time, and the more we lean into that and acknowledge it, the more realistically we’ll approach our work.

[04:11] – Out of the skills, knowledge, and behaviors you just mentioned, where do you typically see learning businesses struggle, and where are they more open to embracing that attitude or mindset?

Where we struggle is in keeping the pedal to the metal on continuous evolution and being comfortable with small pilots and recalibrating when necessary. We also struggle in the area of risk tolerance.

We can’t move our educational efforts forward if we do the same things in the same way. So much has changed. Whether you’re talking about in-person learning, online learning, or a combination of the two, we just have to be more aggressive overall, period.
Mary Byers

Where we often excel—and these aren’t things that actually help us—is in protecting the status quo, in meeting deadlines, and doing the comfortable things. We need to get comfortable with discomfort, especially going forward in the educational arena.

[05:53] – When you think about the skills and behaviors that it takes for organizations to succeed, is there a hierarchy? If so, which ones are the most important?

The willingness to experiment is one of the most important, but that comes along with risk and no guarantees. Because we’re not comfortable with uncertainty, there’s tension between those two things. Many cultures don’t support this aspect of innovation and reward consistent performance instead.

[06:38] – How do you see organizations helping their internal team get the needed skills, knowledge, behaviors, and mindset to succeed?

The ones that are doing it well are being very intentional and deliberate about having conversations related to needed skill sets. Mary suggests each team member should have a personal learning roadmap for two reasons:

If you’re an educational organization and you believe in continuing education, you should walk the talk and make sure your employees are engaged in continuous education.
It’s a way to be intentional and deliberate and to have a plan each year for what we need to learn, how to do it, and where to get the necessary resources.

Complacency leads to irrelevance…. A lot of times we think of employees as serving our learners externally, but we also need to think about employees as learners internally as well.
Mary Byers

Sponsor: Cadmium

[10:02] – If you’re looking for a partner to help you make continuous learning a reality, check out our sponsor for this series.

The COVID-19 pandemic catalyzed the merging of events and education for organizations across the globe. Organizations have realized that synergizing their education and events strategies produces immeasurable benefits, but they need a technology solution that facilitates that merge.

Cadmium is focused on providing a full suite of technology solutions enabling organizations to meet the changing environment head on. From a host of event technologies to integrated learning management and content creation tools, Cadmium offers everything an organization needs to generate revenue and drive engagement.

Learn more, and request a demo to see how Cadmium can help your learning business at gocadmium.com.

Role of Data in Organizational Decision-Making

[11:02] – This is a concept that you talk about in your book Race for Relevance. What is the role you see data playing to help organizations make decisions?

As we’re talking about experimenting and innovation, if we are using data, we are taking less risk because we’re not just guessing. We’re using what we know to be true to help identify new opportunities such as potential new topics that people are interested in for their own learning.

Data is important because it can help you meet learner needs more efficiently. It can create efficiencies internally as well. However, data isn’t always sexy, and Mary thinks that’s one of the reasons it’s underutilized. The second reason is we aren’t set up to capture data, and, even if we have the data, we don’t always use it. Also, sometimes we have data that we don’t even know we have.

To look at data effectively, you need people who are skilled enough to be able to interpret it and help you make sense of it. They need to help you identify trends that the data is showing you and help you make decisions based on what you know to be true rather than what you think or hope to be true.

Understanding Cost

[14:49] – How should organizations go about understanding the cost of the programs that it offers?

It is not enough to look at the direct cost; we have to consider overhead and staff time as well. But many organizations are not set up to track this, so it isn’t easy. Sometimes we don’t give ourselves the freedom and flexibility to step back and assess staff time, even at a very simple level. Therefore, many organizations think they’re making money on a product or program, but, if they accounted for overhead and staff time, they’d find they really aren’t profitable. We have to be more deliberate and intentional about tracking our costs so that we get a true picture of whether we’re making money, breaking even, or actually losing money on some of our offerings.

Volume Doesn’t Equal Value

[16:28] – Would you talk a bit about the arguments that you see for an organization having a narrower product and service line?

The Pareto Principle (also known as the 80/20 rule) tells us that 80 percent of value comes from 20 percent of programs. For a learning business, this means that a few of its programs are going to be the most popular and likely provide the most revenue. This means that you could lean into 20 percent of your programs and probably be more profitable right off the bat.

We’re very slow to retire programs, and that leads to educational clutter…. We need to think about regularly, purposely abandoning less popular or dated courses.
Mary Byers

Besides retiring less popular and dated courses, Mary recommends leaders consider the following to increase both revenue and impact for learners:

Have a strong search function so that prospective learners can find what they’re looking for quickly and easily (without having to hunt through layers and years of programming).
Consider creating packages so that if a learner buys one thing, they can get other related material for one fee.
Think about learning pathways or learning journeys so that once learners have started with an area of interest, you’re able to recommend what they can do next.

The bottom line is to not make your learners work to learn with you. Help them access your programs, services, and curricula.

[20:28] – One of the ideas from Race for Relevance deals with opportunity cost. When you pursue more than you should, that means you don’t have bandwidth or resources to pursue something else.

If you’re busy doing one thing, you can’t be doing another—and if the “another” could hold more value for your audience, that is a sad way to use resources. We want to be using resources, like time, at the highest and best use, not only for your curriculum developers but also for your learners. You also want to make sure there’s a good match between what you’re offering and what learners desire.

Regarding sunk cost, a lot of the times we won’t abandon, sunset , or retire a program because we have a high level of sunk cost in them, and we want to keep going to turn a profit. That’s why experimenting is so important. If you put a small piece of learning out there, and nobody’s interested, you don’t have to build it out. You can go on to find the next piece of learning that somebody would be interested in. That approach keeps your sunk costs low, making it easier to abandon a program when needed.

A Digital-First Mindset

[22:08] – How you would describe a digital-first mindset, and what would that look like in the context of a learning business?

Mary defines a digital-first mindset as embracing technology in order to deliver what learners want, when they want it, and how they want it. And that doesn’t mean only in a virtual environment. A digital-first mindset is understands that technology also plays a role even when you’re meeting in person. A digital-first mindset requires a close relationship with your audience, constantly asking them, listening to them, and inviting input.

Many organizations are behind in building a robust technology framework. That may be due to lack of money or lack of expertise, or it could be as simple as they’re intimidated. The reality is that none of us has time to embrace or create a digital-first mindset while we’re doing the work of today’s business. We have to have two-horizons thinking—short-term, immediate deadlines and long-term deadlines focused on the infrastructure and technology needed to support the learning business’s mission and learners.

When we hold hybrid events, we need to consider the needs of the two audiences. There are certainly places where they intersect, but we have to be cognizant of what our goal is and then work backwards to figure out how to best meet that. We need to be thinking not just about the online experience but how technology can support the in-person experience as well.

Check out our related article “Hybrid vs. Blended Learning: The Difference and Why It Matters.”

Advice for Learning Businesses

[25:34] – What advice do you have for a learning business that is looking to grow and to move up to the next level?

Mary encourages thinking about three things:

Don’t wait to determine and articulate your strategy. Put it in writing, share it with your team, and make that the focus of your longer-horizon thinking because the decisions and actions you take today will determine where you’re going to be in the future.

Watch the video to see what Mary says is a secondary benefit of strategic planning.

Be prepared to invest and invest regularly. Investment involves not just money but also time and expertise. Areas and efforts that are under-resourced or inadequately resourced often fail.
Consider finding collaborative partners. In many cases, the expertise we need to grow exponentially isn’t necessarily on staff, but a collaborative partner (whether a vendor or another organization) has it. Collaboration is the new currency.

[29:40] – Mary adds that sometimes the data from an early experiment isn’t mature enough to be helpful. She tells people not to pull the plug too soon, especially if you’re launching something new that’s never been tried before. Also, the more you do it, the more you can get testimonials, social proof, and social media working so you can promote the new initiative, and then momentum may take off. Although there is a time to retire, sunset, and purposely abandon, it’s not always right after your first attempt trying something new.

[31:07] – Mary encourages listeners to think about developing a go-forward strategy.

We hear a lot about going back to “normal,” going back and just doing things the way that we used to.… But I’m encouraging anytime you hear the words “go back” out of your mouth to gently switch that and change it to “go forward” because “go forward” is positive and optimistic and forward-looking and forward-thinking. Those words “go forward” just have power and momentum and energy in them. And that’s what all learning organizations need to have. They need to be looking further down the horizon than anybody else is.
Mary Byers

[32:15] – Wrap-up

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The Strategy and Marketing Episode

Jackie Harman — Tue, 12 Oct 2021 09:29:27 +0000

Both marketing and strategy are fundamental to the health and success of a learning business, which is why we’re addressing them in the context of the learning business MBA. Of course, the learning business MBA doesn’t exist yet. Rather, we’re using it as shorthand for the key skills, knowledge, and behaviors needed by those working in market-facing learning businesses so they can ensure their organizations survive and thrive. While a single podcast series won’t allow us to do the work of a true advanced graduate degree, we can cover some key areas, give you ideas to ponder, and offer tools to try in your learning business.

In this second installment in our seven-part series on the learning business MBA, we focus on two fundamental areas of knowledge for those leading and working in learning businesses: strategy and marketing. We offer definitions of each and share related resources and tools to help you grow your learning business in each of these areas.

Listen to the Show

Access the Transcript

Download a PDF transcript of this episode’s audio.

Read the Show Notes

[00:25] – Intro

Defining Strategy: A Framework for Decisions

[01:28] – Strategy drives—or should drive—essentially all that happens in a learning business. When it comes to defining strategy and understanding what it is, we may not have a clear and common understanding. Our go-to definition of strategy is based on the work of Benjamin B. Tregoe and John W. Zimmerman in a book from 1980 called Top Management Strategy. They define strategy as a “framework which guides those choices that determine the nature and direction of an organization.”

There are thousands of decisions, some big, some small, when it comes to running a learning business: How do we define our target market? What products and services should we offer? How should we price them? What technology should we use?

We like that Tregoe and Zimmerman think of strategy as a framework that guides your decisions. Strategy assumes there is something you’re trying to do and that you have a general approach to how you’re going to do it. Strategy should guide how you behave, particularly with respect to the market in which you operate. It should also guide how you allocate resources. Strategy has to lead to action.

We also like the Tregoe and Zimmerman definition because it’s short and sweet, which makes it easier to remember and therefore more actionable. The definition can remind you and your team about what you should be doing with strategy: setting the organization’s direction and making choices.

Three Essential Components of Strategy

[03:51] – That focus on action is something that really comes across in a 2011 book on strategy that we highly recommend: Good Strategy/Bad Strategy: The Difference and Why It Matters by Richard Rumelt.

Rumelt breaks strategy down into three essential components: diagnosis, guiding policy, and coherent actions.

A diagnosis involves gathering critical information about your learning business’s current situation, identifying the key challenges represented by the situation, and identifying the most compelling opportunities that would result from tackling one or more of the key challenges and lead you to a future where your learning business is successful and thriving.

A guiding policy is a general approach to overcoming the challenges identified and making significant progress. A guiding policy describes the trajectory, or general path, for how to achieve a desired future state. A critical part of a good policy is that it reflects some advantage or strength your organization has that will appeal to your audience and won’t be easy for others to copy.

Coherent actions are the set of major, coordinated steps you will take to support the guiding policy. They don’t describe every action you will take, but they do indicate your major initial actions, the big projects and areas of focus, and indicate the general categories of action that will be important going forward.

The tricky thing about strategy is that it’s deceptively simple, and the best strategy usually comes from some insight, and insight isn’t easy. You have to diagnose the situation accurately and honestly to have a shot at a good strategy—and that’s much harder than many organizations appreciate.

We appreciate Rumelt’s title Good Strategy/Bad Strategy: The Difference and Why It Matters because it suggests it can be hard to tell good strategy from bad strategy. They can look alike, and it can take some work to see the difference. Because the best strategies are usually simple that can lead to imposters who mimic the simplicity of real, good strategy. But when it comes to strategy, imitation isn’t effective. You can’t copy and paste and expect to thrive.

Strategy should not be confused with best practices. You can’t copy a brilliant strategy from another organization. Strategy needs to be organic, born out of out your learning business’s unique set of circumstances, taking advantage of your strengths while addressing your weaknesses and with an awareness of competition and change in your market. And, most importantly, strategy should be proactive, not reactive, and following someone else’s strategy, even a good one, keeps you in a reactive, let’s-see-what-they-do mindset rather than looking out to the future and proactively shaping that future and your learning business’s role in it.
Jeff Cobb

Sponsor: Cadmium

[07:59] – Your choice of learning technologies should be driven by strategy. If you’re looking for a strategic technology partner, please check out our sponsor for this series.

Learn more, and request a demo to see how Cadmium can help your learning business at gocadmium.com.

Blue Ocean Strategy

[09:02] – Being proactive, not doing whatever everyone else is doing, looking for your learning business’s unique positioning jibes perfectly with another of our favorite strategy resources: Blue Ocean Strategy. This is the work of Chan Kim and Renée Mauborgne, both professors at INSEAD, one of the world’s leading graduate business schools.

In 2005, they published Blue Ocean Strategy based on over a decade-long study they had made of key strategic moves spanning more than 100 years and 30 industries. In 2017, they published a follow-up, Blue Ocean Shift, based on another decade of research and real-world examples of organizations that have implemented blue ocean strategy.

Blue Ocean Strategy challenges the tenets of competitive strategy, which was the dominant school of strategy when the book was published. Kim and Mauborgne called for a shift from focusing on competition to a focus on creating new market space, which would make the competition irrelevant. Their view was that cutthroat competition results in a bloody red ocean of rivals fighting over a shrinking profit pool. Lasting success, they argued, comes from creating “blue oceans”—untapped new market spaces ripe for growth.

Tied up in that challenge to competitive strategy was a challenge to the conventional wisdom that an organization has to choose between either being low cost or differentiating to add more value. The blue ocean strategy approach is that you can differentiate and add value while also delivering at low cost—so it’s a win-win for the organization and its customers.

With the traditional competitive view of strategy, an organization begins by analyzing the industry and competitors and then carves out a distinctive position in the existing industry where they outperform the competition by building a competitive advantage. With this approach an organization’s strategic options are circumscribed; they’re limited by the environment. Blue ocean strategists recognize that while market and industry conditions exist, they were created by organizations. And, just as organizations created those market and industry conditions, organizations can shape them and even create new industries and markets.

Strategy Canvas

[13:41] – Like Rumelt, Chan and Mauborgne focus on execution. They don’t leave strategy at the theoretical level. They offer tried and true tools to help identify strategy, and these are tools that we have first-hand experience using in the context of learning businesses. Here we’ll touch on one we’ve used in our consulting work called the strategy canvas.

The strategy canvas serves two purposes:

The strategy canvas captures the current state of play in your known market space and allows you to clearly see the factors that the industry competes on and lets you see clearly where the competition currently invests and where your organization invests.
Once you have your current-state, as-is strategy canvas drawn, it prompts you to begin rethinking your position, to think about what you could do differently to stand out from other players, as shown on the strategy canvas. The strategy canvas is both a diagnostic tool and an action framework.

The strategy canvas does all this in a simple picture. The example strategy canvas below looks at factors organizations typically compete on in the continuing education (CE) market (convenience, speaker, quality of content, price, etc.) and shows how one particular organization (the dotted blue line) diverges from the industry focus (the solid pink line).

The strategy canvas focuses you on the competitive factors in your market—i.e., the factors on which organizations tend to compete in order to win customers. Price is almost always a factor, and it certainly is a factor in the continuing education and professional development market. Other factors in that market include things like the reputation of the presenters or instructors, location, and amenities like food in the case of face-to-face events. It can include things like the availability of credit or the amount of access learners will get to the instructor or another expert for help.

The strategy canvas helps plot out the competitive factors by rating (from low to high) the level of emphasis that different competitors place on those factors and the level of emphasis that your organization places on them by comparison. This gives you a really useful visual of where things currently stand in the market, and, just as importantly, it starts giving you ideas for how you might change your approach to the market by increasing or reducing, maybe even eliminating, your emphasis on certain factors and possibly adding new factors that no one seems to be competing on at this point.

Blue Ocean Strategy offers more tools. In addition to the strategy canvas, we also really like the four actions framework and the six paths. See our break-down of the six paths in the context of a learning business.

Check out our related episode Blue Ocean Strategy for Your Learning Business.

Defining Marketing: The 4 Ps

[17:25] – Marketing is a perfect follow-on to our discussion of strategy because the two are intertwined. Strategy will help a learning business determine what to do in the market, and a deep and meaningful understanding of the market will influence strategy. We’ll start with being clear about what we mean by marketing.

The American Marketing Association definition states: “Marketing is the activity, set of institutions, and processes for creating, communicating, delivering, and exchanging offerings that have value for customers, clients, partners, and society at large.” This definition makes it clear that marketing is broad—it’s not just advertising or other types of promotion—and it’s ongoing.

We also like its mention of value. Marketing is about identifying what a particular audience values, building products and services that provide some or all of that value, making the audience aware of the offerings, and then delivering the products and services—and thereby the value. And, of course, creating value is generally at the core of strategy.

In marketing classes and textbooks—the kind you might find in an MBA—the 4Ps of marketing are often covered: product, place, price, and promotion.

Product

[19:38] – Product is most fundamentally about identifying and creating an offering that meets the needs of your audience and that will result in the outcomes you aim to achieve for your learners and as a business. In other words, the product P is about creating something that clearly delivers the desired learning outcomes, that people will buy, and that—as a result—will generate revenue for your learning business.

While product, as part of the marketing mix, addresses obvious areas like features and benefits and the quality level of the offering, it also includes less obvious elements like branding, how you name it and package it, what sort of services and levels of services you provide to support it, and any guarantees you plan to provide. Beyond that, the product P also includes making decisions about how and when to update and revise the product over time to meet market needs. But most people don’t tend to think of these areas as “marketing.”

With elements like features and benefits for a learning product, for example, it’s easy to think that these are purely the domain of the subject matter experts and instructional designers and developers. But we know that the biggest issue learning businesses face is that they create products and then no one buys them—and that’s because they have not applied the marketing perspective to the product. They haven’t gotten the kind of market insight they need to be confident that whatever they create will actually resonate with a fundamental desire or need in their target audience.

That brings us to the tool we’d like to offer to help with the product P: the Market Insight Matrix^TM.

The Market Insight Matrix^TM

[21:28] – This is a tool we developed and have used with consulting clients. The matrix can help your organization manage a rigorous and practical market assessment process, through three stages and three types of activities, to identify learning products that will address market needs.

The three stages are idea generation, idea verification, and idea testing.

Idea generation: The higher the quality of the ideas you come up with initially, the easier and more effective the subsequent parts of the market assessment process will be. You want diverse input at this stage. Don’t rely only on the input of a small group or team. You also need input from staff and volunteers, important customers, and influencers in your market.

Idea verification: Many organizations effectively stop at the idea generation stage. They come up with a few good ideas, prioritize one or two of them—often based on the thinking of a small number of people in the organization—and then begin building a product. A better approach is to take the ideas generated in stage 1 and verify them by looking at what Web searches, customers’ and prospects’ discussions in social media, and surveys and polls can tell you.

Idea testing: To test the idea, put the concept—or even a version of the product—into the marketplace and see if you can get people to take action. Will they sign up for future notifications via a landing page? Can you pre-sell the product and thereby ensure purchases from the get-go?

The stages are one key part of the process. The next part is the types of activities you should engage in across these stages.

[23:20] – The three types of market assessment activities covered by the matrix are tracking, listening, and asking.

Tracking: Tracking focuses primarily on historical, quantitative data. What can you tell—based on a variety of tools like Google Analytics, Google Trends, and data from your e-commerce and learning management systems—about the behavior of your customers in the recent past? What content has been of interest? Where have they found it?
Listening: Listening focuses on observing what your learners are saying and doing. What are they saying as they interact with each other, your organization and its offerings, and even your competitors and their offerings? You can find out by monitoring social media, conducting user testing, and mining evaluations.
Asking: Asking involves you engaging directly with stakeholders and requesting their input on specific questions. This is the path of traditional tools like surveys and focus groups but also includes activities like pre-selling and crowdfunding.

The matrix combines the three stages and the three activity types, with the goal of ensuring you have a process that generates diverse input and doesn’t rely too heavily on any one source.

Place

[26:11] – The second P is place, and it addresses the question, “How will customers purchase and access the offering?” Place may get overlooked or undervalued because people aren’t intuitively sure what “place” means in the context of marketing, but, even when it’s clear that we’re talking about distribution, learning businesses don’t necessarily consider all the nuances and possibilities.

Deciding to distribute a course online, for example, is an example of addressing place. But you can go beyond that decision to consider whether the distribution will be only through your own learning management system and only through a single, standard interface or whether you will support distribution through branded sub-portals or even allow organizations to license the content for use on their own LMS. You can do the same thing with place-based offerings. For example, you might give organizations or subject matter experts the right to deliver one of your workshops internally. You can even consider franchising entire educational events or event models—similar to what TED has done with TEDx.

The main takeaway with place is that most organizations simply stick with tried and true channels for getting their products and services to market. But this is an area where pushing yourself to think a little outside the box can open up big opportunities. Probably the most basic one that applies to a majority of learning businesses is to think beyond selling to individual learners and develop approaches to institutional selling—that is, selling in bulk to corporate, government, and other organizational buyers of training and education.
Celisa Steele

Effectively executing on institutional selling can radically transform a learning business’ prospects.

The Value Ramp^TM

[28:27] – We’ll add another interpretation of the place P in the context of a learning business, and that’s thinking about an offering’s place on your Value Ramp. This is another tool we’ve developed and used in our consulting work, and it has you think about where a particular product or service sits in relationship to your other offerings.

One key idea that underlies the Value Ramp is that there is a relationship between price and value when it comes to selling just about any product of service. Provide more value in the eyes of the potential purchaser, and you can and should charge more. (Note that “in the eyes of the potential purchaser” is critical.)

Another key idea behind the Value Ramp is that to get to a higher place and price, you need momentum. In today’s markets, a corollary to this point is that demonstrating value early and often is one of the surest ways to build significant value. More and more, this means providing significant value before you ever charge a dime—which is why content marketing is so important.

That’s why both a product’s place on your Value Ramp and where it’s available to your audience matters. Some significant portion of the value you offer needs to be free so that people who don’t know you can discover you and see the value you provide without hitting a barrier like a paywall.

See our related episode 8 Tips for Optimizing Your Value Ramp™.

Price

[30:10] – That brings us to the third P, price. It’s one of the marketing Ps that does not tend to get ignored—pricing is a fact of life for learning businesses. If you’re marketing and selling learning products and services, then those come with a price tag. But what to put on the price tag can be tricky because a lot of organizations don’t know how to approach pricing.

We’re proponents of value-based pricing. That doesn’t mean that a learning business shouldn’t know the costs (both direct and indirect, hard and soft) that go into making and offering a learning product or service. Often organizations know the direct and hard costs, but many don’t have a good sense of indirect or soft costs, like staff time. Even if not precise, even if just an educated guess, having some sense of the staff time and effort required to create, manage, and deliver an offering is so important to understanding the financial performance of a learning product or service.

Understanding costs is important, but we don’t believe in cost-plus pricing—costs plus 20 percent, for example. We also don’t believe in pricing that’s pegged to your competition. And we don’t recommend trying to beat competition on price.

Definitely do your market research, but don’t settle for just matching competitor pricing. You want to beat competition by offering something better, something of higher value, or, better yet, something that’s different.
Jeff Cobb

Value-based pricing is the concept that the price you charge reflects the value that you believe—and that your prospect is reasonably going to believe—you’re going to create for them with the product or service that you’re offering. If you embrace value-based pricing, then it will begin to influence decisions you make about the features and quality of a product, the packaging and branding, how it will be distributed, what level of exclusivity will be associated with it, etc. All those factors drive value perception—and impact underlying costs. As a result, they directly impact your decisions about price.

Those decisions include asking and answering questions like these:

What will our pricing strategy be?
Are we going for market penetration or expansion with low pricing?
Do we price this as a premium offering?
Do all customers get the same price?
Are there discounts?
What are the criteria for the discounts?
Do we offer payment terms?

It’s important to stress just what a powerful lever price is. Price impacts perception—just assigning a higher price to a product and doing nothing else can raise its perceived value. And a lower price can suggest lower value. Price also has a big impact on revenue. Raising prices is more powerful than cutting costs or increasing sales volume when it comes to generating higher net revenue. The opposite is also true. It’s very difficult to make up for the net revenue losses that occur as the result of a price decrease.

Resources for Pricing Learning Products

[34:09] – In terms of a tool for pricing, we’ll mention that the Value Ramp can also be used here. You’ll want your Value Ramp to tell a logical story of increasing value and increasing price, so consider that when plotting your offerings.

Because we know how key pricing is for learning business, we have a lot of information about pricing learning products that can help you get thinking about your approach to pricing.

To learn more, check out the pricing resources below:

Also check out our related episode How to Price Educational Products – 10 Tips from 20 Years of Experience.

Promotion

[34:47] – The final P is promotion. This is the P that most people equate with marketing, which may be why a lot of learning business professionals say they don’t like marketing—they don’t like the idea of promoting or selling, even if they appreciate how important they are. It’s also likely that many learning business professionals don’t appreciate the full range of possibilities for promotion.

It’s easy to think of promotion as overtly selling, whether that means advertising or sending an e-mail campaign that pitches a specific offering. Those are part of promotion—and they are often very important parts—but a lot of what goes into promotion these days is much more subtle. There’s the concept of a promotional mix, and that’s going to include not just things like advertising, brochures, and mailings, but also content marketing, search engine marketing, and social media marketing, just to name a few of the possibilities.

Those suggest some skills for learning business MBA students to dig into: SEO (search engine optimization), copywriting, and the use of social media for conversion.

To learn more about the 4Ps, listen to our related episode The 4 Ps of Marketing Your Learning Business.

AIDA Formula

[36:07] – The tool we’re offering to help you with the promotion P is the AIDA formula. AIDA is an acronym:

Attention
Interest
Desire
Action

Those are the four stages that prospective customers move through in a typical buying process—from initial awareness to some interest to the desire to do something to making an actual purchase. The goal of anyone promoting a product or service is to help prospects move through these stages so that they will be converted and buy or register for the course or turn over their e-mail to get that resource.

AIDA reminds us that no matter how much we want a customer or prospect to take action, to click the Buy button, we first have to get their attention—and getting their attention is no small matter. Then we have to create an interest in what we’re offering. Then we have to take that interest and get them to desire, and then and only then might they take action.

To learn more about AIDA, listen to our related episode The 4-Part Formula for Selling Education.

[37:56] – Wrap-up

We’d also appreciate if you give us a rating on Apple Podcasts by going to https://www.leadinglearning.com/apple.

We personally appreciate your rating and review, but more importantly reviews and ratings play a big role in helping the podcast show up when people search for content on leading a learning business.

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Other Episodes in This Series:

Learning to Get Down to Business

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Virtual Events Are Here to Stay: The Future of Associations

Guest Contributor — Thu, 07 Oct 2021 12:51:22 +0000

by Jake Fabbri of Fonteva

The safety regulations of the pandemic required many of us to adapt to remote work and digital engagements, which included virtual meetings and conferences. After a year and a half of working from home, we have become more accustomed to virtual events—so much so that associations will keep them around even in a post-pandemic world.

For some associations, in-person conferences, large gatherings, or major events require a great deal of logistical coordination that could be lessened by going virtual. As a result, leaders could put more effort into planning compelling and effective content rather than organizing accommodations or venue planning.

Despite the benefits of virtual events, there is still the worry about keeping your members engaged. It’s true that we tend to be less focused when meeting through a screen, but there are strategies you can implement to improve engagement and take your virtual gatherings to the next level.

In this guide, we’ll review the benefits and challenges of virtual events, plus tips that can help you get the most out of your programs, even if they’re happening online. When you’re running your virtual event, be sure to do the following:

Make your events interactive.
Stay organized.
Create independent opportunities for virtual events.

It’s likely that virtual is a key part of the future of events for many organizations and associations. Optimizing your engagement strategy now shows your members that just because you’re changing your processes doesn’t mean that quality will decrease. In fact, it might even improve.

Benefits of Virtual Events

Virtual events have tons of benefits for convenience and time efficiency. According to this Boardable guide to virtual meetings, meeting remotely can save up to 40 minutes of commute time. Those extra minutes mean more time for new ideas, problem-solving, and task completion.

Virtual events also create new opportunities that might not have been possible in-person. For example, you can record events to easily reference later. The wide array of tools available for virtual events can also increase productivity and help gatherings run smoothly. Here are some of the key benefits of virtual events:

Convenience: When you meet virtually, your members can connect anywhere, at any time (as long as they have wifi). Your members will appreciate the flexibility that virtual meetings offer, and you might even see an increase in attendance because it’s much easier for members to log on than commute.
More efficiency: Because virtual events tend to be shorter, they are also more productive. Although you might spend less time catching up with small talk, you can get down to business more quickly. This way, you truly maximize your time during events.
Greater diversity: In the past, attendance at association events might have been limited by each member’s ability to travel, pay for accommodations, or take time off work. With virtual events, you can have greater geographical, financial, and social diversity. More diversity ensures a wider variety of ideas because everyone brings something different to the table.

Although we might not have anticipated the surprising increase of virtual events over the past year and a half, there are apparent benefits to this sudden pivot. For these reasons, making virtual events a standard in your association makes sense. However, there are also some drawbacks to virtual events that are worth considering.

Challenges of Virtual Events

Did you know that virtual attendees typically only watch 68 percent of an event that is 20 minutes or longer? Keeping your audience engaged is one of the largest overarching challenges of virtual events.

That’s because the lack of apparent body language, constantly having to look at ourselves, and the inability to move around all contribute to lower focus. If you do make a permanent pivot to virtual events, navigating reduced engagement will need to be one of your top priorities.

Here are some of the primary challenges of virtual events:

Reliance on technology: How many times has someone started speaking in a meeting, only for their connection to freeze? This hiccup can make gathering online very frustrating. For virtual events to run smoothly, all your members need access to a reliable computer and wifi, and you need some tech-savvy team members. Prepare your staff members so they know how to troubleshoot if a technical issue does come up.
Less rapport: Meeting virtually means that you lose the small talk that often contributes to strong working relationships between members. Because you won’t bump into colleagues in the hallway or have a chance to grab a meal together after a conference, it’s more difficult to build as much rapport with fellow members.
Reduced focus: As we mentioned, meeting virtually can also negatively impact member engagement and focus. For this reason, virtual events might require a bit more planning to keep everyone involved.

3 Virtual Event Tips

Although you might be hesitant to continue virtual events post-COVID, there are several ways that you can overcome the challenges and reap the benefits of virtual events. Let’s look at three tips for making the most out of your virtual events.

1. Make Events Interactive

It’s clear that keeping your virtual member engagement high will pose a critical challenge to your association’s leadership. However, you can significantly increase your audience’s engagement by adding interactive elements to your virtual events.

Interactive elements can help your audience feel like they are contributing to your event or have more of a say in discussions. Some interactive elements you could incorporate into your virtual events include the following:

Breakout rooms: Putting members into smaller discussion groups can encourage deeper conversation and more active speakers. While some members might feel intimidated to share their ideas in a large group, intimate breakout rooms can help to get the conversation flowing.
Chat function: Encouraging members to share their thoughts through your virtual conferencing platform’s chat function is a great way to stimulate conversation and allow for a continuous flow of ideas.
Acknowledgement of specific members: In smaller member meetings, the discussion leader should call on specific members. It’s likely that they have something on their minds. Calling on a member demonstrates that you value their input, and it has the added benefit of encouraging participation from everyone.
Polls: Many virtual conferencing tools have poll capabilities so you can quickly vote on a decision. Sending out a poll is a fun and easy way for members to contribute and settle on decisions quickly.

Incorporating these interactive elements can be especially helpful if you’re organizing a large, multi-day event such as a virtual conference. Because a conference requires much more focus, frequent opportunities for interaction can help sustain your members’ level of engagement throughout the day. Interactive engagement can go a long way in keeping your members involved during virtual events. Brainstorm some ideas with your team for how you can get your members to participate.

2. Stay Organized

One of the best ways to ensure a seamless virtual experience is through ample planning and organization. Whether you’re planning a small meet-and-greet or a major conference, being intentional about staying organized can help events of all sizes run more smoothly.

With virtual events, it can be harder for members to get a sense of how the event will go or what exactly they should expect. Setting clear expectations before an event can help your members go into it feeling prepared and excited.

Here are some tips for keeping your virtual events organized:

Create an agenda. Outline how the event will go, what you plan to cover, and what sort of activities you have in store for your members. Send out your agenda before the event begins so that members have a chance to review it.
Test any technology in advance. If you’re going to be adding interactive elements to your event, it’s a good idea to do a test run before the actual event. This way, you won’t have to troubleshoot while your audience waits.
Send relevant information ahead of time. Just as you want to send your agenda ahead of time, you should also attach any relevant materials you’ll be referencing so your members can adequately prepare.

If you’re managing a large association, keeping track of all the necessary details might seem overwhelming. Investing in software specifically designed to manage your members and upcoming events can be an excellent tool to streamline time-consuming administrative tasks. This Fonteva guide about association management software can help you get started.

3. Create Independent Opportunities for Virtual Events

To encourage more participation among your members, consider creating independent opportunities for virtual events. If you have a large association, it might be less feasible for you to meet regularly, so give your members the opportunity to keep in touch with your association.

Your members might even prefer these independent events so that they can engage on their own time and to the extent that they wish. Not sure what these independent opportunities might look like? Here are some examples:

E-learning courses: Give your members access to relevant e-learning courses that could supplement future events.
Webinars: Offer to send recordings of Webinars or meetings to your members so they can watch even if they couldn’t make it to the live event.
Podcast or book recommendations: Have your members suggest podcasts or books that might be of interest to others.
Community involvement: Encourage your members to involve their personal networks with your association, whether it’s through applying to your organization, joining a volunteer program, or simply spreading the word.

Even if you aren’t directly communicating with your members, these types of activities can keep them engaged with your organization. Plus, working independently might even help them come up with new ideas to share at the next event.

Although virtual events do have some extra logistical and engagement challenges, they can be a great option to bring together community members from far and wide. With the right tools and an emphasis on keeping everyone focused, you can ensure that you get the all of the benefits of virtual events.

About the Author

With over two decades of experience marketing association technology, Fonteva CMO Jake Fabbri has developed a deep understanding of the unique needs of associations and the challenges technology can solve. Jake’s marketing expertise has been honed by demonstrated excellence in the areas of lead generation, content marketing, marketing automation, and events.

The post Virtual Events Are Here to Stay: The Future of Associations appeared first on Leading Learning.

Learning to Get Down to Business

Jackie Harman — Tue, 05 Oct 2021 11:02:47 +0000

Chances are, if you’re in the learning business, you probably didn’t go to school knowing this is where your career would take you. Some of you may a have strong background on the learning or education side, while others may have it on the business side—but likely, you don’t have an equally strong background when it comes to both, and it may be difficult to combine the two.

And because we want you to have the core skills and knowledge needed to run a successful learning business, we’re focusing our newest series on the learning business MBA.

In this first installment in our seven-part series, we discuss the idea behind the learning business MBA and the related skills it requires. We also pull in perspectives from Josh Goldman—who we credit for giving us the term for the learning business MBA—and Arianne Urena and Cristyn Johnson.

Listen to the Show

Access the Transcript

Download a PDF transcript of this episode’s audio.

Read the Show Notes

What Is the Learning Business MBA?

[00:29] – We’ll credit the term to Josh Goldman, who now serves as the senior director of consulting at Tagoras, the parent company of Leading Learning, which we co-founded. He was not part of the team here when he first used the term. He was at a CPA society then, and he reached out to us because he was in charge of putting together programming for a gathering of the educators from the CPA world.

The idea of an MBA (a master’s in business administration) emerged and having that be a theme for a day of education. Of course, we weren’t going to accomplish a true MBA in a day, but the idea was that we could focus on the business side of providing lifelong learning and continuing education in a one-day session with these educators. We had a chance to talk with Josh much more recently than that initial conversation about this idea of an MBA for learning leaders.

[03:27] – Josh shares what he remembers about the original of the learning business MBA.

As I looked across the landscape, I realized that the market was changing. There were a lot of competitive forces at play, and I needed a skill set that I hadn’t earned either formally through formal training and education or informally via on-the-job learning…. As I advanced in my career and worked with different audiences and in increasingly complex associations, I recognized I personally was lacking some of the explicit knowledge, skills that you would find inside of a traditional MBA program…. And so the market was changing needs, and I felt at that time that that collective audience—all of those learning leaders across a number of CPA associations and myself—could use something like a learning MBA that helped us focus on some of those more business-focused or corporate-focused knowledge and skill sets.
Josh Goldman

Josh speaks based on his personal background working in associations, but we don’t think what he’s describing is unique to people working in the association world. People who wind up in the learning business probably do so accidentally more often than not. Even if you come to a commercial training firm that might be focused on the adult lifelong learning market, chances are you didn’t go to school thinking that’s where you were going to end up. So you may be lacking some of those skills. Also, it can feel a little bit distasteful to some to combine learning and education with business.

Perhaps there is some tension inherent in how we describe our audience. We talk about learning businesses. Learning is an innate impetus—all humans learn—and so it seems learning should be wide open, freely available. Business, on the other hand, is about competition and profit and charging for access. So it can feel distasteful for people who really buy into the learning mission of a learning business to think of it as a business.

Some people who end up in a learning business come a learning or education background. Others (probably fewer) land in a learning business with business skills and acumen, and they might be unfamiliar with the learning side of things and feel at a loss when it comes to understanding what goes into making an effective learning experience, which, of course, is what a learning business provides.

[06:45] – Back to the question, “What is the learning business MBA?”

The learning business MBA is shorthand for getting at the core skills and knowledge needed to run a successful learning business. Just as the traditional master’s of business administration focuses on key areas that are important for the successful operations of a business, the learning business MBA does the same thing. It identifies the core skills and knowledge in specific areas that are necessary for one particular type of business, for a learning business, and what it takes for that to be successful. The main difference is that the learning business MBA focuses on learning businesses that serve learners and help them learn, and so learning is so important to their profitability.

One of the things we’ll aim to do over the course of this series is to enumerate some of those skills and knowledge areas required for running a successful learning business, dig into them a bit, and have conversations with people who can help to illuminate them in the context of a learning business.

Another model is something like the altMBA that Seth Godin introduced a number of years ago. The altMBA and executive MBAs play off the idea of the full-blown MBA and focus on offering content to people who are already in the work world and are going to be able to put what they learn to work in the context of their day-to-day jobs. While obviously this podcast series is not going to be any sort of true MBA, we hope to MBA-type skills, knowledge, insights, and conversations with people from a business perspective that you will be able to put to work in your learning business.

What Would the Course of Study Cover in the Learning Business MBA?

[09:38] – Let’s talk about what would we study in the learning business MBA. What are the skills and knowledge learning businesses need to be successful? It’s going to vary from program to program, but there are some core areas you find in most MBA programs—things like accounting, finance, strategy, management, marketing, and communications. These aren’t unique to learning businesses, but they are definitely important to learning businesses.

When talking about skills he wanted and felt lacking in years ago, Josh mentioned product development, pricing, market assessment, and risk assessment. Those are arguably more specific domains—subdomains you could call them, under some of those broader categories.

There are some domains that are unique to learning businesses, the main one being an understanding of how adults learn efficiently and effectively.

An understanding of how learning happens is, of course, key to developing and delivering products that are going to help a learning business in its arguably most fundamental goal.
Celisa Steele

The business elements are really built all around developing and delivering effective, efficient learning products and services. Fortunately, we’ve got good resources to help you understand how learning happens. We just completed a great series on learning science for learning businesses, which we recommend particularly if your background is more in business than in learning. Depending on your role in a learning business, you’re going to go deeper or shallower in some areas.

Sponsor: Cadmium

[12:49] – The effective use of learning technology is a core skill of successful learning businesses. If you’re looking for a technology partner, please check out our sponsor for this series.

Learn more, and request a demo to see how Cadmium can help your learning business at gocadmium.com.

The Most Important Skills for the Learning Business MBA

[13:43] – What are the most important skill sets for those leading and working in learning businesses? The answer to that will change depending on the nature of the organization, the people involved, and the situation. It’s hard to generalize too much, but anybody working in a learning business needs to have at least a good grasp of the fundamentals.

You need to know how to work with a spreadsheet. You need to understand things like the four Ps of marketing and why they matter and have some basic understanding of how to develop strategy. In addition to these sort of concrete core skills around business, anybody working in the learning business—and maybe this applies to any business—has to be skilled in critical thinking.

Critical thinking has aspects of judgment and aspects of what we’ve written and talked about before as metalearning. It’s the ability to step back and make sense of what’s going on and figure out how to find the value and how to move forward, whether we’re talking about big organizational decisions or just small day-to-day decisions.

We’ve already said there can be this sort of cognitive dissonance between the idea of business on the one hand, where you’ve got competition and profit, and learning and education on the other hand, where people often have a sense of purity about that. You have to be able to look at those two areas and recognize the ways that maybe they legitimately are in opposition but also recognize the ways in which they overlap—and overlap very strongly when your business is learning—and be able to figure out what to do with that. That’s one area where that kind of critical thinking judgment really applies.
Jeff Cobb

Another area where critical thinking applies is around trends and buzzwords. You have to be able to step back, make some sense of the situation, and come to judgments that are going to result in value for the business and for the learners that you aim to serve. Critical thinking is going to help you no matter where your organization is.

There are also perennial issues that we see come up that you have to have skills to address.

[17:43] – When we asked Josh what he sees as the most important skills for those leading and working in learning businesses he offered two.

Understand the current and potential customers, beyond a surface-level understanding. Know their motivations, the decision criteria they use, and why they’re working with you versus working with others.
Know how to translate and transition that understanding into how you position the value you credibly bring to the market.

We also spoke with Arianne Urena, who has served on the Elevate LMS team at CommPartners and is now part of Cadmium, and she focused in on the same two areas as Josh: homing in on the needs and wants of the learners and then ensuring that your offerings are accessible and that the value is shown.

To understand the audience, a learning business needs to “get” market research and market analysis. Then to translate that understanding into products and services, a learning business has to understand product development and the pricing and promotion aspects of marketing.

To learn more, check out our related episode, The 4 Ps of Marketing Your Learning Business.

[21:24] – Critical thinking and judgment are needed because there are so many cut-and-paste things you can do around things like market assessment and understanding your audience. Those can be useful, but, if you can’t really apply that judgment to both crafting those instruments and then analyzing and evaluating what you get out of them, then you’re not going to get very far. You have to understanding your audience, and apply judgment and critical thinking to then make the decisions that are going to create the value that you need to create as a learning business.

Is your approach going to be market-focused or product-focused? What Josh and Arianne are talking about is that market-focused approach—really understanding that market and then giving them what they need and want. But there’s an alternative to that.

There’s leading the market, leading your audience, giving them what you can see they need, even if they haven’t fully recognized that. Deciding between a market focus and a product focus gets back to the critical thinking skill. It also ties very clearly to strategy. There are choices, decisions to make, and it takes critical thinking to decide which strategic approach you’re going to follow and execute on.

Deciding between a market focus and a product focus is a strategic question, and our talk of strategy reminds us of something that Cristyn Johnson, who focuses on training and development for clients and staff at Cadmium, said when we spoke with her. We asked her what she thinks those leading and working in a learning business need to know or be able to do in order to be successful, and she talked about planning, which is an important aspect of strategy.

Cristyn says it may seem like a no-brainer, but you need to create a plan to achieve the learning goals that you’re looking to achieve, and the plan should have a mix of short-term and long-term goals and objectives. During this planning process, she recommends thinking about the things that you have control over that can really help you achieve your goals.

Cristyn also likes to reiterate that an engaged learner is much more likely to not only retain the information that you’re giving them, but they’re also more likely to return, to come back and purchase again—and they’re also more likely to tell their friends and colleagues about the amazing experience that they had.

Cristyn adds that you should strive to foster an environment of learning both internally within your organization and externally with your learners. A learning mindset goes a long way for everybody embracing it.

It’s hard to have a successful learning business if you haven’t really thought about the learning culture in which you are working, the different constituents that make up that culture—not just your internal culture at the learning business—but more broadly, that universe of your learners and the different providers and subject matter experts, and really understanding the context in which you’re working as a learning business. Growing a learning culture is a fundamental skill for any learning business looking to thrive.

[27:36] – Wrap-up

Reflection Question

We’ll offer a reflection question for you to ponder:

If you were putting together a learning business MBA, what subjects and skills would you include? What was missing from the topics we touched on today?

We’d also appreciate if you give us a rating on Apple Podcasts by going to https://www.leadinglearning.com/apple.

We personally appreciate your rating and review, but more importantly reviews and ratings play a big role in helping the podcast show up when people search for content on leading a learning business.

Finally, consider following us and sharing the good word about Leading Learning. You can find us on Twitter, Facebook, and LinkedIn.

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Why Strategic Training Matters for Capacity Building

Guest Contributor — Thu, 26 Aug 2021 16:26:45 +0000

by Matt Hugg of Nonprofit.Courses

How many times have you heard someone say, “I went to school…the School of Hard Knocks”?

This humorous nod at non-traditional education can be a proud declaration or a depressing admission. Either way, the subject would probably have rather not gone through it.

Then there’s “on-the-job” learning. That’s like the School of Hard Knocks except the learner figures things out as they go along because they can see those hard knocks coming.

Nonprofit staff and volunteers tend to do a lot of on-the-job learning while serving a lot of people who attended the School of Hard Knocks.

You could be thinking, “There’s nothing wrong with either of these learning methods.” And you’re right. There are a lot of valuable, practical lessons in both. And you’re not likely to forget them, even though you might want to.

The problem is that they’re both highly inefficient and, worse, entirely random. You never know what lessons you’ll end up with either—and some of those lessons could be entirely wrong. The point is, there’s no surefire way to build capacity in any organization through learn-as-you-go education. What you need is systematic training for capacity building.

Consider the following questions as you develop your ongoing training programs.

In what areas does your team need strategic training?

Effective training for capacity building all begins with knowing why you’re there in the first place. In nonprofits, it’s called a mission. In a nonprofit, everything circles back to the mission—whether that’s saving the whales, eliminating homelessness, providing youth with unique educational opportunities, or one of the millions of other causes. If someone’s role is not mission-connected, you have to question why they’re doing it.

Yet it’s easy to lose track of the mission when you’re in the thick of an accounting audit or a human resources review. This is why dedication to mission is often a major job requirement for any nonprofit position. It’s also why learning about your mission is the bedrock of any nonprofit training program.

Start with a review of your history.

Every organization—business, nonprofit, or government—has a heroic origin story. One person saw or experienced something that couldn’t be lived with and came up with a solution. Maybe that solution was national independence. Maybe it was a better widget. Maybe it was giving local kids something to do after school.

Whatever it was, they started working on it, gathered others around, and began making their vision—a world where that problem was solved—into a reality. Whether you offer this story via a video, podcast, or a beautifully written story, everyone needs to know how you started—and most importantly—why you’re still there.

Consider why your organization is critical to its beneficiaries.

The key to understanding why your organization still exists is to get into the heads of those you serve. This is one of the most neglected parts of any capacity-building strategy, but you could also argue that it’s the most important part. Whether you call the people you serve clients, patients, students, constituents, or customers, you will not flourish as an organization if you don’t thoroughly understand your mission recipient’s needs.

The problem is that it’s easy to trick yourself. Were you once a beneficiary yourself? How long ago was that? Perhaps you’ve been serving your mission for what seems like a lifetime, so of course you understand those you serve. You come at it with some arrogance when you think, “They don’t know what they need, but I do.” Nonprofits fall into this trap all the time.

Sometimes you can walk in their shoes. An organization that aids people with spinal cord injuries encourages their staff to spend at least one day a year doing their job from a wheelchair. A nonprofit that works with the homeless offers staff an experience where they live on their city’s streets for 24 hours.

Whether you can directly feel the pain of those you serve, you can certainly study it and look for opportunities to learn about it—either directly or indirectly. As an organization, ongoing learning about those you serve needs to be a top priority.

How can you improve your capacity building training?

The above is an important baseline training strategy for strengthening organizational infrastructure. It’s exactly the leverage you need for deeper staff (and, for nonprofits, volunteer) engagement with their function in your organization.

But, to run an effective operation, your training needs to go further, to cover program-specific topics that allow your team to better fulfill their role. That’s where real change and real capacity building starts. Here are ten tips.

1. Create a training culture that works.

If there is a training culture at all in an organization, it often doesn’t work. In a lot of nonprofits, “training” is a euphemism for “paid vacation.” The staff member is allotted a sum of money for what’s expected to be a conference, usually far away. Some attendees faithfully go to sessions, but a lot seem to find local shopping more interesting and attend only the most compelling presentations.

The key is to avoid this by taking a strategic approach to training that your team is actually excited to participate in. And, really, learning – just like capacity building – is an ongoing process rather than a one-time event.

2. Pay for staff training.

More and more, nonprofits and businesses are zeroing out their training budgets with the idea that either “we hire people who know the job, so we don’t need to train” or “if we train them, they’ll use it to find a new job and someone else will benefit.”

However, the opposite is true in both cases. While you certainly look for candidates with the best skills, nobody can come ready with every skill that’s required. And, if they are that good, they’ll use their training to create networks for you and your organization to get more knowledge and better people.

And that “they’ll leave” argument? Again, the opposite is true. Don’t train, and they’ll leave. Every employee and volunteer wants to grow. If you help them grow, they’ll become loyal, stay longer, and your organization will benefit—both from what they learned and from increased staff retention.

3. Encourage teaching.

Encouraging a culture of teaching at your organization benefits more than just the learners involved. Teaching not only gives status to the instructor, but it forces the instructor to learn as well—even if only to avoid embarrassment.

Okay, that’s a bit cynical. But teaching is a great way to engage veteran staff on a meaningful level. Whether they teach your own staff through internal programs or others at outside venues, their instruction means you (and your eager learners) benefit from what they know.

4. Make ongoing learning essential.

Nothing stays the same. What anyone learned when they started a job could be different six months later. This is especially important and true for disciplines that have life-and-death consequences, such as medical and social service professions.

If clients know they are not getting the most current service methods, they’ll look to other organizations to fulfill their needs. Plus, as an organization, you risk liability issues if your staff training isn’t up to date.

5. Incentivize education.

If your staff is overworked and, at a nonprofit, likely underpaid, they’re not likely to participate in training if there’s no reward for doing so.

So how can you incentivize your training program? Perhaps you create a sophisticated system of badges and recognitions with rewards in time off, pay, or other goodies. However, you might also take sincere interest in what the trainee learned. Either way, it’s important for your staff to know that there is a reason beyond “knowledge for knowledge’s sake” in putting in the effort to get trained.

6. Make training fun.

Yes, it’s a cliché. But, yes, it’s important. Nobody likes to be talked at all day. No, you don’t need jugglers and clowns.

Instead, check out the resources at the Association for Talent Development (formerly known as the Association for Training and Development). As professional trainers, they’ll tell you that physicality, audience engagement, and gamification can do more than entertain—they can get information into the brains of the audience members effectively.

7. Train in short bites.

The human brain takes information in like pouring water into a jug with a funnel. You need the right speed and the right amount to get it all in. Too much, too fast, and some will spill over. The best training with the least spillage happens in short bites over time.

8. Put training to work as soon as possible.

A tremendous amount of the value anyone gets from training is lost because it is simply forgotten. Why? The time between its introduction and its use, if ever, is way too long.

The first question anyone should ask when it comes to training is “how and when will you use this?” This is not to suggest that all training must have a practical, immediate application. Sometimes you need long-term theoretical education to put practical knowledge into context. If that’s the case, no problem. Just know that going in.

9. Educate on the cutting edge and the basics.

Technology has a way of making us think that some things are brand-new when really what’s new is the gadget and not the basic methodology.

For example, someone introduced to crowdfunding may think that it’s a great new way to raise money. Really, crowdfunding is a teched-up version of the old neighborhood campaigns—except the community isn’t just the six houses adjacent to yours but all of your Facebook friends.

If you know the basics, then you can not only recognize the latest and greatest for what it is, you can apply lessons from the old way to make the new way even better.

10. Assign a training partner.

A training partner isn’t necessarily a guru in the trainee’s discipline, although they certainly can be. It could also be their boss, although that can put an unwelcome power dynamic into the relationship.

A training partner discusses available training opportunities, encourages training to occur, expresses genuine interest in what their partner learned, and helps them talk through how it will be used.

If you think your nonprofit needs capacity building—whether you define that as generating more revenue, building a stronger board, instituting better financial controls, more effectively carrying out your programs, or all of the above and more—hiring new staff and expecting them to learn on the job won’t get you there. At best, it may fill your short-term need. But it will never build a sustainable organization.

To build a sustainable organization, you need systematic training that accounts for how, why, and when people learn and motivates them to do so. That’s how you leverage training to meet the most important responsibility a nonprofit or any organization can have: fulfilling your mission.

About the Author

Matt Hugg is an author and instructor in nonprofit management in the US and abroad. He is president and founder of Nonprofit.Courses, an on-demand, e-learning educational resource for nonprofit leaders, staff, board members, and volunteers, with thousands of courses in nearly every aspect of nonprofit work.

He’s the author of The Guide to Nonprofit Consulting and Philander Family Values: Fun Scenarios for Practical Fundraising Education for Boards, Staff, and Volunteers and a contributing author to The Healthcare Nonprofit: Keys to Effective Management.

Over his 30-year career, Hugg has held positions at the Boy Scouts of America, Lebanon Valley College, the University of Cincinnati, Ursinus College, and the University of the Arts. In these positions, Matt raised thousands of gifts from individuals, foundations, corporations, and government entities and worked with hundreds of volunteers on boards and fundraising committees, in addition to his organizational leadership responsibilities. Matt teaches fundraising, philanthropy, and marketing in graduate programs at Eastern University, the University of Pennsylvania, Juniata College, and Thomas Edison State University via the Web and in-person in the United States, Africa, Asia, and Europe and is a popular conference speaker. He has a BS from Juniata College and an MA in Philanthropy and Development from St. Mary’s University of Minnesota. Matt has served on the board of the Greater Philadelphia Chapter of the Association of Fundraising Professionals, the Nonprofit Career Network of Philadelphia, and several nonprofits.

The post Why Strategic Training Matters for Capacity Building appeared first on Leading Learning.

Taking Action with Learning Science

Jackie Harman — Tue, 24 Aug 2021 12:24:47 +0000

This is the last installment in our seven-episode series on learning science’s role in a learning business, and we’ve covered a variety of interesting topics. But we want learning science to be more than interesting. We want you to apply it so you can elevate the success and impact of your learning business, as well as the success and impact of the learners you serve.

In this episode, we revisit comments from the interviewees in the series about the one tenet or aspect of learning science they wished was better understood by those designing and delivering learning for adult lifelong learners. We connect their perspectives and uncover the common theme: actionability. And, to help your learning business take the important step of applying learning science, we offer a framework we developed—the MIDDLE ME learning product lifecycle—to get you started.

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Read the Show Notes

Perspectives on Key Tenets of Learning Science

[00:27] – We spoke with Megan Sumeracki for the episode that focused on behavioral and cognitive psychology. She explained that we’re actually really bad at putting ourselves in the future context related to what we’re learning and assessing how well we’d do in that context.

We’re bad judges of our own learning. That is a significant finding. It shows that we can’t just ask learners if they’re getting it and if they’ll be able to do it when the time comes. We need to get them to try to do and see. That’s when we’ll know—and they’ll know—whether or not they’ve really learned it.
Celisa Steele

[04:04] – We asked learning designer and technologist Myra Roldan what aspect of learning science she wishes those designing and delivering adult lifelong learning better understood. Her comments connect with Megan’s. Myra explained that a lot of instruction focuses on theory and understanding concept, but instruction tends to fall flat on the hands-on, application piece.

What both Megan and Myra homed in on is cause and effect—or at least a logical consequence. If learners aren’t good judges of knowing if they’ve learned something, you need to give them opportunities for for trying things out. Those hands-on opportunities allow them to not only learn but to also get some feedback about their learning.

By doing something, learners often produce something that an instructor can evaluate and provide feedback on too. There’s a lot of work to be done in helping instructors and subject matter experts learn how to scaffold hands-on, application opportunities well.

Not just any doing will have good results—learners need doing and application that are spot-on, relevant, and align with how they will use whatever they are learning in the future.

That can sound obvious and easy, but we know from our own experience that when you’re trying to design something impactful in a limited amount of time, it can be hard to determine appropriate opportunities for doing and application. It requires work over time, and learning businesses should help their subject matter experts in understanding the importance of practice and scaffolding application opportunities.

[07:14] – The aspect of learning science Ruth Colvin Clark wishes learning designers better understood is the fundamentals of the mental processes and a better appreciation of the limits and strength of working memory.

This is one I’ve been guilty of, time and time again, and always have to pay attention to. So many subject matter experts, so many presenters, teachers, facilitators are guilty of this. Just stuffing too much into a learning experience, not taking the time to cut down to what’s truly essential and what’s truly reasonable for a learner to process…. Less content really can be a beautiful thing.
Jeff Cobb

[09:35] – The limitations of working memory that Ruth brought up are also an argument for microlearning, which Brenda McLaughlin, CEO at SelfStudy, raised in regards to designing effective learning experiences. She thinks we need more normalcy and systems around creating smaller interactions with education so that we’re not always thinking in terms of mapping to a course but of mapping to a competency or skill.

Brenda’s comments remind us of Cathy Moore’s take that we really need a mindset shift to get away from content-heavy learning options and offerings that can then favor more doing because there’s less emphasis on content. Microlearning embraces the less-is-more approach, and Brenda points out that, to realize its full potential, it isn’t just chunking longer content; it’s truly a different approach.

[12:04] – We asked evaluation experts Rob Brinkerhoff and Daniela Schroeter to pick one aspect of effective evaluation they wished was more broadly understood by those charged with looking at the impact of learning programs.

Daniela emphasized that there has to be a focus on performance—what the learning is about, what you want to get out of it, and if it’s actually being used.

Rob stressed that that an evaluation must be actionable. You need to know what the return on investment of the evaluation is, and it has to be actionable because, if you can’t do anything with it, there’s no point. We struggle with this ourselves, and it’s not easy territory, but the Success Case Method is one approach that can be used.

Listen to Mark Nilles speak at the Leading Learning Symposium about how he’s made use of the method to evaluate training programs.

Mark Nilles presenting on the Success Case Method

Sponsor: SelfStudy

[15:17] – If you’re looking for a technology partner to help you optimize the learning experiences you offer, check out our sponsor for this series.

SelfStudy is a learning optimization technology company. Grounded in effective learning science and fueled by artificial intelligence and natural language processing, the SelfStudy platform delivers personalized content to anyone who needs to learn either on the go or at their desk. Each user is at the center of their own unique experience, focusing on what they need to learn next.

For organizations, SelfStudy is a complete enterprise solution offering tools to instantly auto-create highly personalized, adaptive learning programs, the ability to fully integrate with your existing LMS or CMS, and the analytics you need to see your members, users, and content in new ways with deeper insights. SelfStudy is your partner for longitudinal assessment, continuing education, professional development, and certification.

Learn more and request a demo to see SelfStudy auto-create questions based on your content at selfstudy.com.

The MIDDLE ME Learning Product Lifecycle

[16:29] – We’d like to offer a framework we developed that can help you think about where and how learning science might play a more strategic, thoughtful, and intentional role in your learning business: the MIDDLE ME learning product life cycle.

The MIDDLE ME learning product life cycle has four phases:

Market interface (MI): understanding what your learners need and want and communicating with them about the value you have to offer
Design & development (DD): creating what your learners need and want
Learning experience (LE): the learners interacting with what you’ve created
Measurement & evaluation (ME): looking at the impact of learners interacting with what you’ve created

The MIDDLE ME framework can help you focus efforts among your stakeholders: the staff that you have who are charged with providing the learning that you offer, the volunteers, facilitators, the subject matter experts, and the learners. The framework can help give you insight into what’s going on at different points for each of those key stakeholder groups.

[18:32] – Here’s how learning science might fit in in each phase of MIDDLE ME:

Market interface (MI) is all about knowing and connecting with your audience: learners, customers, and your potential learners and customers. Here’s where learner needs assessment and/or market assessment come into play. Your internal team/staff will need to be engaged to conduct the assessments. Once you have the results of those assessments, you need to share them with your designers and developers.
Design and development (DD) is where you plan and create the products and services that your learners need and want. This is where you cut and chunk to help with the limitations of working memory. You scaffold practice so that learners aren’t passive or getting theory only, but they engage and try things. The main stakeholder group involved here are those people doing the design and development of your learning experiences.
The learning experience (LE) phase is where learners interact with what you’ve designed and developed based on your market interface. Mostly, you have to make sure that the good design and development work of the previous phase doesn’t get thwarted. This is also where feedback and practice happen. Stakeholders here are the learners and those supporting them in the moment.
In the measurement and evaluation (ME) phase, we look at the impact of learners interacting with what we designed and developed. We measure and evaluate our products and services and look to draw business insights. As we heard from Rob Brinkerhoff and Daniela Schroeter, this is where you can look for evidence of the impact of the learning experience, and, in particular, you might look for success cases and failures and analyze those. This is valuable in multiple ways—marketing potential, improving offerings, proving value, and more.

We’re providing this MIDDLE ME model as a tool because it can be a simple framework for helping you put learning science into action. Providing education and learning experiences for your adult lifelong learners is really at the core of being in a learning business.

To thrive in the learning business, what you deliver has to be effective. It has to get the learners to where they’re supposed to go, and that’s what applying learning science can make happen for your learning business.
Jeff Cobb

Evidence-Based Practice Requires Evidence

[24:41] – Learning science, as a science, is grounded in evidence. That evidence-based approach is consistent with how we tend to approach life and work—we strive to try and test and study what’s working or not working and why.

We hope you’ll choose at least one action to take in at least one of the four phases of the MIDDLE ME model and then look at the results. Use the evidence you gather to grow and improve your learning business in general and your offerings in particular. Get out and do/try/measure something so you can get some evidence that will allow you to test ideas and hypotheses and make informed decisions throughout MIDDLE ME.

Learning science has the potential to help you across the board with the reach, revenue, and impact of your learning business. It’ll help you as an organization be more successful. It’s going to help your learners be more successful. It’s going to help the field, profession, or industry that they’re working in do better. Then, of course, those served by the learners are going to fare better as well. It really is a win-win-win-win when a learning business can really leverage learning science.
Celisa Steele

[26:19] – Wrap-up

This is the last episode in the seven-part series on the role of learning science in a learning business. We hope you’ve enjoyed the series, and we’d love to hear your feedback and suggestions for the future. You can leave a comment at below or e-mail us at leadinglearning@tagoras.com.

We’ll resume releasing episodes of the Leading Learning Podcast with a new series starting in October 2021, which means you have some time to experiment with infusing learning science more intentionally in your learning business before the next new series airs.

To make sure you don’t miss the remaining episodes in the series, we encourage you to subscribe via RSS, Apple Podcasts,Spotify, Stitcher Radio, iHeartRadio, PodBean, or any podcatcher service you may use (e.g., Overcast). Subscribing also helps us get some data on the impact of the podcast.

Recommendations offer evidence of the podcast’s impact, so please take a minute to rate and review the Leading Learning Podcast at https://www.leadinglearning.com/apple.

We personally appreciate your rating and review, but more importantly reviews and ratings play a big role in helping the podcast show up when people search for content on leading a learning business.

We encourage you to learn more about the series sponsor at selfstudy.com.

Finally, consider following us and sharing the good word about Leading Learning. You can find us on Twitter, Facebook, and LinkedIn.

[28:21] – Sign-off

Other Episodes in This Series:

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The post Taking Action with Learning Science appeared first on Leading Learning.

Evidence-Based Evaluation with Rob Brinkerhoff and Daniela Schroeter

Jackie Harman — Tue, 17 Aug 2021 10:26:39 +0000

Learning science uses evidence-based practice to support learning, and evaluation plays a critical role in providing that evidence by revealing its true impact.

To help us unpack how evaluations should inform decisions about learning, we spoke with Dr. Robert Brinkerhoff and Dr. Daniela Schroeter, co-directors of the Brinkerhoff Evaluation Institute (BEI).

Rob is an internationally recognized expert with four decades of experience in evaluation and learning effectiveness and he’s the author of several books including, The Success Case Method and Telling Training’s Story. He’s also the creator of the Success Case Method, a highly regarded and carefully crafted impact evaluation approach to determining how well educational and training programs work.

Daniela has a PhD in interdisciplinary evaluation and has spent the past 15 years providing evaluation and capacity building to a wide range of private, public, and nonprofit organizations around the globe. In addition to co-directing BEI, Daniela is an associate professor at Western Michigan University.

In this sixth installment in our seven-part series on learning science’s role in a learning business, we talk with Rob and Daniela about how to effectively leverage evaluations to maximize outcomes from learning. We also discuss the Success Case Method, the value in using evidence-based stories to demonstrate the impact of an offering, and why evaluation must lead to actionability.

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Download a PDF transcript of this episode’s audio.

Read the Show Notes

[00:19] – Intro and background info about Rob and Daniela.

Flaws of Traditional Evaluation Methods

[02:13] – What do you see as the primary flaws or shortcomings of traditional typical evaluation methods?

There’s currently an emphasis on evidence-based practice focusing on quantitative outcome data and sophisticated methodologies. Those are challenging because they’re often not practical and don’t allow you to adapt a learning intervention while you’re still implementing it.

There’s also too much emphasis on comparison groups and singular outcomes rather than looking at the intervention as a whole and the unique environments of each individual learner. Evaluations shouldn’t focus on the end point, but rather they should be used from the beginning to continuously improve the program, the impacts from it, and to leverage learning and maximize outcomes from learning.

Success Case Method

[04:03] – Can you briefly introduce the Success Case Method?

Rob describes how he got the idea for the Success Case Method when he realized the need for an evaluation method that focuses on the success of something when it was actually used, not just on average. This is because the average always underestimates the good.

The Success Case Method identifies the most successful users—and not so successful users—of the initiative being evaluated. It then answers questions to identify what needs to be done to make more people perform as well as the few best people.

The Success Case Method (image from www.monicawabuke.com)

[08:13] – Would you talk a little bit about some of the purposes that the Success Case Method can be used for?

The Success Case Method can be used to:

Improve learning interventions and maximize the outcomes from the learning.
Pilot programs to find out what works well and for whom.
Market to downstream audiences. Once we know what is working and for whom, we can leverage that information to push the learning to new audiences.
Help program deliverers tell the story. Often learning providers want share outcomes that are the result of a learning experience, and a success case story provides information that can be shared.
Teach participants and their supervisors about the value of the learning that they’re participating in.

Too many times we’ve seen evaluation studies that are hard to interpret, hard to understand. They use a lot of statistics and a lot of jargon. And what really compels people is stories…. That sort of evidence really compels action and drives emotional response and buy-in.
Rob Brinkerhoff

Rob stresses the importance of stories. There are fictional stories, and there are evidence-based stories. We need to look for the truth of a program. Almost always there are successes, and it’s important to leverage those.

Value in Impact Evaluation: Past and Future

[11:46] – Do you think impact evaluation should always have a future-facing aspect, where you’re looking to improve? Or do you see value in a purely historical look at a particular course’s impact in the past?

There’s value in summative, endpoint evaluation and being able to provide evidence that a particular program is working and making a difference. We can learn a lot from history. Being able to learn about programs that didn’t work and why is valuable, but, even with that, there’s a future orientation. It can provide information that helps you defend why you want to continue with a program.

All evaluation should be used for learning at one point or another. While our method directly tries to focus on current learning and what we can learn now for future learning interventions…there’s also a longer-term effect in doing historical evaluation because, without looking back at the past, we cannot innovate in the future.
Daniela Schroeter

[13:56] – How do you respond to people who get tripped up trying to show direct causation between an educational offering and specific results?

Learning is never the sole cause for anything other than paying the bill for having participated in it. Any change in human performance or behavior is driven by a complex nexus of causes. It’s not important to show that the training is the sole cause of an improvement or change, but it’s critical to show that the training made a worthy and necessary contribution to an individual’s success.

As a methodology, the Success Case Method gets away from looking at the average. Instead, it looks at outliers and the best an intervention can do when it works well, as well as why it doesn’t work for people at the very bottom.

Too many valuable babies get thrown out in the bathwater of statistical reporting. We want to be sure that we understand, when it did work, why did it work? And, when it didn’t work, why didn’t it work? Because that’s the real leverageable information that we can do something useful with.
Rob Brinkerhoff

Causation is really a question for knowledge generation when we want to build a research base, and that’s very important—that’s what academia does. For learning providers, the primary interest is how to leverage an intervention and make it better for the people who are using the learning, rather than generating academic contributions.

It’s also important to understand that a judicial context factored into the creation of the Success Case Method. When saying the Success Case Method produces “evidence that would stand up in court,” it literally means it has to be testimony that can be corroborated with evidence.

Sponsor: SelfStudy

[17:41] – If you’re looking for a technology partner whose platform development is informed by evidence-based practice, check out our sponsor for this series.

Learn more and request a demo to see SelfStudy auto-create questions based on your content at selfstudy.com.

Defining Success for Effective Evaluation

[18:49] – In Telling Training’s Story, you define success as “the achievement of a positive impact on the organization through the application of some skill or knowledge acquired in training.” In the case of learning businesses, how might you define success?

The root definition of success is that you learn something that makes a difference. It’s not whether you learned something or not; it’s whether you made use of it for some worthy purpose in your life. If it isn’t making a difference to people, then it doesn’t have value.

Many learning interventions don’t necessarily teach a new skill. Then the question becomes, “What is this current learning doing to reinforce, change, or provide for greater success?”

Each individual learner may have a unique context and experience, so a cookie-cutter evaluation approach doesn’t work. It’s useful for the learning provider to understand what the biggest challenges for people are in different contexts. This also allows people who are asked to sign up for a certain learning experience to make good decisions about what works and why.

One exception to this is people who sign up for a course only to get a certificate. This isn’t a good candidate for the Success Case Method if the only motivation for people is to show participation and they don’t care if they ever use it.

The Evolution of Evaluation

[23:05] – How have you seen evaluation practices change? Do you think there’s a better or broader understanding of effective evaluation now than there used to be?

There’s a lot of change and innovation going on in evaluation and there’s more interest now in practicality. There’s more need for useful information, and Rob and Daniela are trying to maximize the value of evaluation for the people who want a program evaluated. It’s about empowering people to engage in evaluative activity so they can maximize the learning from their programs.

Academically speaking, there’s a lot going on with transformative evaluation methods that try to engage marginalized groups and support sociocultural developments.

Also, there’s more interest in getting evidence for more savvy consumers. There’s a trend toward making evaluation more of a partnering activity, working more in tandem toward the common goal of doing something good for that program and helping it be more successful. Partnering in that way is more fulfilling for the program side and for the evaluation side.

[25:43] – Are there areas of evaluation that you would love to know more about? Anything you’re keeping an eye on to see how it evolves or what we learn about it in the years ahead?

As an evaluation scholar, Daniela keeps up to date with the evaluation literature and new developments in evaluation theory, methodology, and practice. In terms of the Success Case Method, she looks forward to better understanding how it works in different evaluation contexts. While the Success Case Method has traditionally been marked as a methods-oriented approach to evaluation, she considers it more of a user- or consumer-oriented approach and a transformative type of evaluation that can engage stakeholders.

Rob adds that, because their evaluation work is conducted as a business, they have to always keep an eye on the competition, making sure they maintain a competitive advantage in their approach. They’re constantly looking at who’s doing what in evaluation and how they can learn from them to get better.

Transformative Evaluation

[27:46] – Can you explain what you mean by the term transformative evaluation?

Transformative evaluation approaches take marginalized groups into account. For example, feminist, culturally responsive, and LBGTQ evaluation approaches exist. Transformative evaluation brings in the perspective of groups that are often on the edge of a learning intervention. It directly engages with those individuals and brings their issues to the center of the evaluation. It’s not just the program, but it’s how we engage the learner or the marginalized group in the program to maximize the benefits for disenfranchised people.

We want to know if we’ve needle moved for those people in the organization who are especially vulnerable. We can then focus on that group because that’s where the gold is buried. When you look at a broader statistic that takes everybody into account—those who aren’t being affected by these practices anyway—you wash out this impact.

[30:05] – What role do you see evaluation playing in the realm of diversity, equity, and inclusion?

The role evaluation should play in DEI is helping get the truth out—getting evidence and bringing it to people who otherwise would not be aware of it.

It’s hugely important to get the story told of the marginal groups that are being impacted by lack of diversity and inclusion so that people who don’t understand their experience can learn some more about the truth of their experience. Evaluation is searching for the truth. And we need to then get that truth to the people who can do something valuable with that understanding.
Rob Brinkerhoff

DEI also means engaging the right people to ask the right questions and to use the right ways of communicating findings.

Understand This About Effective Evaluation

[31:29] – If you had to pick one aspect of effective evaluation, what do you wish was more broadly understood and implemented by those tasked with looking at the impact of learning programs?

Rob says the one criterion an evaluation should meet is actionability. As a learning business, you need to know the return on investment of the evaluation, and it has to be actionable.

Daniela thinks there needs to be a focus on performance—what the learning is about, what you want to get out of it, and if it’s actually being used.

How the Success Case Method Has Evolved

[32:59] – How has the Success Case Method evolved over the years?

With the introduction of technology, it’s changed a lot. Evaluation studies can be done for less money because we can be much more efficient. For example, survey software has eliminated the need to mail surveys. More conceptually, there’s more demand for value and actionable performance from evaluators, and we’re more adaptable than we used to be.

On a broad level, evaluation is very much the same, but the way things are being done is very different—for example, how reports are being written, the way things are communicated, the way the surveys are implemented, turnaround times, how interviews are being conducted, etc. You can engage more people in a more efficient way, which impacts the way methodologies are implemented.

There’s also a shift towards technology-based digital platforms for delivering learning journeys. Rob and Daniela have had to become savvy about how the expectations for impact and value differ when dealing with virtual training. You can harvest success stories earlier on and produce knowledge—and integrate it back—much faster. The findings are much more immediate and actionable.

[37:00] – Is there anything else you’d like to say before we say goodbye?

Rob says evaluation is common sense applied. Don’t be afraid of it. It’s not rocket science. He would like people to keep in mind the tagline for BEI. Evaluation is for making it work. When it works, notice and nurture. When it doesn’t work, notice and change. That in a nutshell is evaluation.

Daniela emphasizes that evaluation is not about making people feel bad about themselves or making programs look bad. Evaluation is about learning, innovating, and getting to better learners, better learning programs, and better organizations.

[38:24] – Wrap-Up

Dr. Robert O. Brinkerhoff and Dr. Daniela Schroeter co-direct the Brinkerhoff Evaluation Institute. Rob developed the Success Case Method, an impact evaluation approach used by BEI to help determine how well learning programs work. Daniela is also associate professor of public administration at Western Michigan University, and Rob currently serves as head of impact and evaluation at Promote International. Be sure to check out “Using Evaluation to Build Organizational Performance and Learning Capability,” co-written by Rob. You can also connect with Daniela and Rob on LinkedIn.

To make sure you don’t miss the remaining episodes in the series, we encourage you to subscribe via RSS, Apple Podcasts,Spotify, Stitcher Radio, iHeartRadio, PodBean, or any podcatcher service you may use (e.g., Overcast). Subscribing also helps us get some data on the impact of the podcast.

We’d also appreciate if you give us a rating on Apple Podcasts by going to https://www.leadinglearning.com/apple.

We personally appreciate your rating and review, but more importantly reviews and ratings play a big role in helping the podcast show up when people search for content on leading a learning business.

Finally, consider following us and sharing the good word about Leading Learning. You can find us on Twitter, Facebook, and LinkedIn.

[40:22] – Sign-off

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Webinar Pricing and Sponsorship Data

Jeff Cobb — Mon, 16 Aug 2021 13:56:46 +0000

This data comes from the most recent round of our Webinar survey that was conducted in July 2021. There were 180 qualified responses to the survey.

Participation in the survey was diverse. Respondents represented a wide range of professions and industries as well as a range of organization types – from trade and professional associations, to for profit corporations and entrepreneurs, to educational institutions, to charitable organizations.

We’ll stress that this is in no way a guide to setting Webinar registration or sponsorship fees or a suggestion for how you should price your registration fees and sponsorships. What is viable will vary greatly by the field or industry served and the nature of the audience. That said, these figure do at least provide a high level point of reference as you consider what will work for your specific audience.

Here are the questions about Webinar pricing data we asked of organizations that sell and/or accept sponsorships for Webinars they offer.

Highest Webinar Pricing

Question: What is the highest amount (in U.S. dollars) your organization charges for a Webinar? Please enter a whole number–no commas, decimals, or dollar signs.

Average (out of 96 responses): $142.47

Question: What is the typical length (in minutes) of one of the Webinars for which your organization charges this highest amount? (For example, enter 60 for a one-hour Webinar.) Please enter a whole number–no commas or decimals.

Average (out of 96 responses): 114.26 minutes

This works out to approximately $1.25 per minute. So, at the high end, a one hour Webinar would run around $75, on average, for an individual registration.

Lowest Webinar Pricing

Question: Excluding any free Webinars you may offer what is the lowest amount (in U.S. dollars) your organization charges for a Webinar? Please enter a whole number–no commas, decimals, or dollar signs.

Average (out of 76 responses): $48.02

Question: What is the typical length (in minutes) of one of the Webinars for which your organization charges this lowest amount? (For example, enter 60 for a one-hour Webinar.) Please enter a whole number–no commas or decimals.

Average (out of 76 responses): 72.29 minutes

This works out to approximately $.66 per minute. So, on the low end, a one hour Webinar would run about $40, on average, for an individual registration.

This is a relatively small sample, but these figures might nonetheless be of some help if you are in the midst of figuring out your Webinar price points.

I’ll emphasize though, that we never advocate setting prices based purely on what the market trends are. These are simply a point of reference. They tell you something about what market expectations may be, but your overall product strategy should focus on how you differentiate your product – and, by extension, your price – from the market. If you want to explore pricing in greater depth, I recommend the following posts:

Pricing Online Learning (Article | Blog Post)
A discussion of some of the fundamental principles of pricing as they apply to sales of e-learning products and services.
3 Axioms of Pricing for Your Education Products (Video)
A brief overview of some essential concepts that it pays to have in mind when developing a pricing strategy.
Effective Pricing Practices for Your Educational Offerings (Video)
Video of one of the Content Pods™ at the 2015 Leading Learning Symposium

Finally, I’ll note my strong bias that Webinars – at least when they are called “Webinars” – are best used for content marketing, and as a result, best offered for free. If you want to sell it, don’t call it a Webinar.

Webinar Sponsorship Fees

As noted, with this round of the Webinar pricing data survey we also asked about fees that organizations charge for sponsorship of Webinars.

Single Level Sponsorship

This group indicated that they only offer a single level of sponsorship per Webinar.

Question: What is the typical fee (in U.S. dollars) your organization charges for sponsoring a single Webinar?

Average (out of 39 responses): $5,640

Multi-Level Sponsorship

This group indicated they offer multiple levels of sponsorship for a single Webinar.

Question: What are the typical fees (in U.S. dollars) your organization charges for sponsoring a Webinar? Please begin with your lowest level sponsorship in the Level 1 box and enter as many subsequent levels after that as are applicable to your organization.

Because the number of levels varied among 39 respondents, we’re reporting the high and low average for the range. At the low and high end these averages broke down as follows:

Low end: $2,400
High end: $11,000

What you are actually able to charge for sponsorship will, of course, vary based on the size of your audience, the nature – and, in particular, the price point – of products and services that tend to be purchased by your audience, and the benefits you offer to sponsors. We asked respondents about the benefits they provide with sponsorship.

Question: Which of the following benefits do sponsors receive? Check all that apply. (If you offer multiple levels of sponsorship, please indicate all benefits that would apply at the highest level.)

We offered the following response options:

Logo or text link from your Web site to sponsors’ Web site
Opportunity to insert “qualifying questions” poll in Webinar
List of registrants for sponsored Webinars
Opportunity to speak or present during the Webinar
Complimentary Webinar registrations for sponsors stakeholders (e.g., customers, employees, etc.)
Guaranteed number of mentions in organizational e-mail communications
Guaranteed number of mentions in organizational print publications
Other (please specify)

Here’s how the responses broke down:

Jeff

Practice and Feedback: Evidence-Based Tools for Learning

Jackie Harman — Tue, 10 Aug 2021 10:48:59 +0000

Practice and feedback are essential to effective learning, yet all too often they aren’t given the time and attention they deserve by learning businesses. Practice and feedback are powerful tools for moving a learning experience away from pure theory and content and towards deeper learning and application in the real world.

In this fifth episode in our seven-part series on learning science’s role in a learning business, we feature key insights related to practice and feedback from conversations with learning design experts Myra Roldan, Ruth Colvin Clark, Patti Shank, Michael Allen, and Cathy Moore. We connect their perspectives to highlight the importance of practice and feedback as evidence-based tools and critical components of designing effective learning experiences.

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Read the Show Notes

[00:21] – To help us explore practice and feedback and what learning science knows about their ability to support learning, we went back to the Leading Learning Podcast archives and found some choice sound bites from Cathy Moore, Michael Allen, and Patti Shank. We also pull in perspectives from Ruth Colvin Clark and Myra Roldan, who were featured in the previous episode in this series about content design.

Myra Roldan

We start with technologist and learning professional Myra Roldan.

A Tenet of Effective Learning

[02:38] – What one aspect or tenet of effective learning do you wish was more broadly understood and supported by those designing and providing learning to adults?

A lot of instruction that you see out there in the world, whether it’s in higher education, workforce development programs, even these free e-learning courses or paid courses that you can take, they really focus on theory. So helping you to understand a concept. Where they fall flat is on this whole concept of hands-on.
Myra Roldan

Myra has a framework that she and her team developed around this concept of application—taking something from theory and being able to apply it in a real-world setting. Every educational initiative she’s evaluated over the years has fallen flat on the application piece, which is really important.

CRAP

[04:20] – There are many models, frameworks, approaches to designing learning, including ADDIE, SAM, and design thinking. Which of those do you tend to find useful, and which would you recommend to others to help them ensure they’re designing effective learning?

ADDIE and SAM are process-driven guidelines and not really a framework for creating learning itself. Myra thinks that design thinking has applications everywhere, but you need to look at whatever solution you’re creating as a product. You need to be able to step out of your comfort zone and work with a group to understand and develop an understanding of who your audience is and what their obstacles are to find solutions for delivering creative learning.

The methodology Myra and her team developed for application and a focus on mastery is called CRAP: concrete, repetition (or representation), abstraction, and practice. You do something concrete, then you repeat a process in a different modality, next you learn the theory about it (abstraction), and, finally, you practice and go through it again.

[07:29] – Myra’s comments drive home the importance of designing practice into a course or other learning experience. Practice is one of the four pillars of the methodology that she and her colleagues have developed for designing learning, and it’s something that we’ve certainly talked a lot about over the years. It’s not enough simply to tell learners that they need to practice. You have to scaffold the practice, you have to build in the opportunities, and you have to set aside time for them to do it.

Ruth Colvin Clark

Ruth Colvin Clark is one of the leading translators of academic research on learning science into practical advice for practitioners. We asked for her advice on how learning businesses might give practice and feedback a substantial role in their learning offerings.

Making Practice and Feedback Part of Your Offerings

[08:33] – We know that practice and feedback are critical to learning and to improving, but they are also areas that get ignored. What suggestions do you have for organizations to make practice and feedback a more serious part of their learning offerings?

Ruth agrees that practice and feedback are two critical areas that often shortchanged. The main reason she’s seen for this is people’s limited time. No matter how complex the knowledge and skills, providers often cram lots of content into a limited time frame, but practice and feedback take time.

I always used to hear, “We have to cover the material.” …That means sometimes just dumping out a lot of information and not really giving people the opportunity to apply that and to see how that, those knowledge and skills, can actually work in their job tasks…. [M]y motto would be “Maybe do less, but do it well.”
Ruth Colvin Clark

Ruth suggests the following:

Evaluate outcomes to see if you’re learners are applying knowledge. The vast majority of evaluation in most learning settings is the student rating sheet at the end, which can be misleading. (See our related episode “Rethinking a Dangerous Art Form with Dr. Will Thalheimer.”)
Set standards regarding engagement. After every new topic or chunk of information build in a change for learners to use the knowledge and skills in job-relevant ways.

Learner Engagement

[11:40] – How do you define learner engagement?

Ruth uses the technical term “generative learning.” What techniques are you using to help learners mentally process knowledge and skills? These techniques fall into two major categories: overt techniques, which are behavioral and involve some overt action from the learner, and covert techniques, which involve learners’ mental effort.

[14:16] – Are overt or covert approaches to engaging learners more beneficial in terms of helping with learning transfer?

Ruth says providers want to provide both overt and covert opportunities, but the advantage to behavioral (overt) engagement is you can give feedback because the learner has taken some action. Since covert engagement goes on in learners’ heads, it’s not as easy to provide feedback because you don’t really know what they’ve processed.

[15:19] – Do you have suggestions or ideas for how one can design to help cultivate engagement among learners?

Ruth suggests using self-explanation questions. Research shows that learners who self-initiate their own self-explanation questions are more successful. This would be a technique to teach learners, and it would providers can insert self-explanation questions to encourage learners to put in the effort. To learn more, check out “Why You Should Add Self-Explanation Questions to Multiple-Choice Questions” by Karl Kapp.

Sponsor: SelfStudy

[18:00] – If you’re looking for a technology partner whose platform development is informed by evidence-based practice, check out our sponsor for this series.

Learn more and request a demo to see SelfStudy auto-create questions based on your content at selfstudy.com.

Patti Shank

[19:14] – Patti Shank is the author of the three books in the Deeper Learning series: Write and Organize for Deeper Learning, Practice and Feedback for Deeper Learning, and Manage Memory for Deeper Learning. Below are some highlights from our conversation with her in a previous episode of the podcast:

Focusing on Content at the Expense of Practice and Feedback

Patti says we spend too much time throwing content at people and, as a result, make it harder for them to learn.

Practice is one of those essential and deep elements that is needed for proficiency…. We worry about developing content for people. We don’t worry as much about developing adequate and accurate practice at the level of proficiency they’re at so that we can move them up…. [W]e deliver far too little practice for any level of proficiency—in fact no proficiency…. And we generally deliver the wrong types of feedback to help people become more proficient. And so we actually create problems for proficiency rather than creating proficiency when we do this wrong.
Patti Shank

Patti disagrees with those who dismiss this kind of discussion as not applicable or “academic stuff.” The research may be academic, and it may be hard to understand, but understanding practice and feedback and other nuances of how learning happens is how we get people to where they need to go—faster and with better results.

Types of Feedback

[21:42] – What types of feedback would be helpful in supporting learners to learn?

Patti frames her discussion about feedback (and how nuanced it is) by limiting it to people who have less prior knowledge in the area being taught and by limiting it to electronic feedback (as opposed to one-on-one feedback). She shares research related to three types of feedback:

KR (knowledge of results) tells learners whether they got the answer right or wrong.
KCR (knowledge of correct results) tells learners not only whether they got it right or wrong but also what the correct answer is.
Elaborative feedback explains why, and there’s a whole host of things that can go into this.

The research shows (though, again, this is very nuanced and so doesn’t apply to every situation) that the best feedback for most people is knowledge of correct answer (KCR). The knowledge of results (KR) is not helpful. For people who are brand-new, the research shows that they can’t handle a lot of elaborative feedback.

KCR is also more effective when showing the feedback in the guise of how the questions were originally presented to the learners. Patti discusses the implications of this related to choosing a multiple-choice question system. For more advanced learners, the most helpful feedback is different than for learners with less prior knowledge.

See “Mastering Deeper Learning, Part 2: Feedback” by Dr. Patti Shank for a good summary of how to handle feedback differently at the different ends of the skill and expertise continuum.

How skill and prior knowledge of the topic impact feedback (image from elearningindustry.com)

Key Takeaways from Patti

[26:15] – We’ve already heard time constraints cited as a big reason why practice and feedback get short shrift. Another big reason is because practice and feedback can be tricky to do well. Patti’s comments show just how truly nuanced feedback is—or how nuanced it should be. A blanket policy of always including elaborative feedback in an e-learning course might actually do learners a disservice if they’re new learners.

Patti’s comments also relate to Myra Roldan’s emphasis on knowing your audience, knowing your customers. Understanding what they already know is going to be key to providing appropriate feedback. The distinction between beginning and more advanced learners is very important—it can be hard for a learning business to navigate, especially if it’s trying to serve a wide audience.

To learn more about feedback, check out Leading Learning Podcast episode 209, “The Art and Science of Effective Feedback.”

In discussing feedback, Patti spoke indirectly about multiple-choice questions. She’s a fan of well-written multiple-choice questions and believes they can be done well, and she’s dedicated time and energy to outlining the best ways to use multiple-choice questions effectively for learning.

Michael Allen

Multiple-choice questions are something e-learning industry pioneer Michael Allen brought up when we spoke with him in a previous podcast episode.

Activity and Feedback in the CCAF Design Model

[28:31] – Michael shared there are almost always four components to an effective learning experience, and those are encapsulated in the CCAF Design Model he developed:

Context
Challenge
Activity
Feedback

CCAF Design Model (image from alleninteractions.com)

Regarding activity, multiple-choice questions are not what most of us do in real life, and so they often don’t accurately measure what you know. Michael suggests that we instead have people take action or respond with a gesture to tell you what they would do in the face of the challenge. If they can’t do it, then they should ask for support or clarification. If they don’t know they can’t do it and try and fail, then developers and teachers know what instruction to give learners because they’ve seen how they fail.

Related to feedback and what makes the most difference, Michael says it’s not about hearing if you’re right or wrong.

To me, the feedback that makes the most difference is…the feedback that shows me the consequences of what I did. So, if I did things well, I want to see the happy outcomes. If I didn’t do things well, I want to see the consequences of not doing things well because it’s going to help motivate me to learn what I need to and avoid those consequences.
Michael Allen

Cathy Moore

[32:20] – Cathy Moore is another voice we pulled from the archives because her Action Mapping model is very much in keeping with cutting content in favor of increased practice.

Action Mapping

Here’s how Cathy describes the model.

[Action Mapping] is a model that helps us avoid doing information dumps to create more activity-centered training. It starts with the question, “What measurable improvement do we want to see in the organization as a result of this training?” In the case of an association, it would be, “What measurable improvement do our learners want to see in the performance of their organization or in their personal lives?” When you start with that, you can then list what it is that people actually need to do on the job to achieve this change. You avoid jumping immediately to what they need to know and instead list what they need to do—and you ask what makes it hard to do. This leads to things such as practice activities rather than information presentations. In those activities you can link, or provide optionally, the information learners may need. The result is a very activity-focused experience, and the learners have the freedom to pull as much information as they need rather than everybody having to sit through the same information presentation.
Cathy Moore

What Is Action Mapping? (slideshow from blog.cathy-moore.com)

Why Practice Activities Aren’t the Norm

[34:02] – Why don’t we see more practice activities in learning products?

Cathy explains that the focus on content is a cultural issue.

Education, as most of us experience it, is delivery of information and then testing to see if that information has survived in the memory…. And I think in the world of professional continuing education, that’s really entrenched because we are focusing on certificates or hours that people spend in class rather than what can they do. So it’s a mindset shift—and it’s a scary mindset shift because we’re so familiar with the information-delivery-and-testing model.
Cathy Moore

[35:24] – In this episode, we heard from Myra Roldan, Ruth Colvin Clark, Patti Shank, Michael Allen, and Cathy Moore. All of them are learning designers whose work is well grounded in learning science, and all of them believe practice and feedback to be critical aspects of effective learning.

Follow-Up Assignment

For this episode, we want to offer not a resource but an assignment. A resource is more content. An assignment is a practice opportunity.

Choose one or more of your learning offerings to audit. Try to find a product that’s representative in some way, maybe not of all that you offer but of a particular product line or a format type.
In the offering or line of offerings that you choose, ask:
1. What feedback and practice opportunities do you offer your learners?
2. Did you devote the same time and energy to those practice and feedback opportunities as you devoted to content development?
3. Did you use evidence-based approaches to building in practice and providing feedback?
4. Based on your informal audit, what changes would you make to how you design and develop offerings in the future?

We’d also appreciate if you give us a rating on Apple Podcasts by going to https://www.leadinglearning.com/apple.

We personally appreciate your rating and review, but more importantly reviews and ratings play a big role in helping the podcast show up when people search for content on leading a learning business.

Finally, consider following us and sharing the good word about Leading Learning. You can find us on Twitter, Facebook, and LinkedIn.

[37:43] – Sign-off

Other Episodes in This Series:

Episodes on Related Topics:

The post Practice and Feedback: Evidence-Based Tools for Learning appeared first on Leading Learning.

Designing Content Scientifically with Ruth Colvin Clark and Myra Roldan

Jackie Harman — Tue, 03 Aug 2021 12:31:46 +0000

Both Ruth Colvin Clark and Myra Roldan are evidence-based learning designers who combine a nuanced understanding of learning theory with years of hands-on experience developing solutions.

Ruth is principal and president of Clark Training & Consulting and has spent her career as an instructional psychologist, working with diverse organizations. She’s the author of many articles and books, including Evidence-Based Training Methods, and she co-authored e-Learning and the Science of Instruction.

Myra Roldan is a technologist and learning professional who currently serves as chief cloudification officer at Amazon Web Services. She does a bit of everything, from research and data analytics, to implementing new technologies, to creating full-blown learning experiences. Much of her personal work is focused on increasing access and opportunity for underserved groups, including women and minorities, so they can get jobs that will earn them a livable income.

In this fourth episode in our seven-part series on learning science’s role in a learning business, we speak with Ruth and Myra individually to get their perspective and expertise on designing effective learning experiences. We cover a variety of topics including research-based principles and their implications on learning, tips for working with subject matter experts to ensure learning objectives are met, how to avoid cognitive overload, and the importance of knowing your audience.

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Read the Show Notes

[00:28] – Intro/preview of episode.

Part 1: Ruth Colvin Clark

[01:44] – Background information about Ruth.

The Value of Evidence-Based Practice

[02:19] – You’ve done a lot of work to bridge the gap between academic research on instructional methods and then practitioner application of that research. How do you explain the value of evidence-based practice?

A lot of money is invested in learning events, and there is limited time to deliver training events, so you need to maximize the value of that training. One of the best ways to do that and to get a return on investment is to draw on instructional methods that have actually been empirically researched and proven.

[03:23] – How would you describe the value for the learners in participating in learning that is developed according to evidence-based practices?

Learners can get more value from a well-designed and empirically based set of instructional methods. Often in traditional types of training, the learners are passive; learners be more engaged by appropriate instructional methods.

[04:14] – Do you see more practitioners making sure that their decisions and designs are backed up by solid research than you did a decade or two ago?

The answer is yes and no. In the 1990s, evidence-based medicine emerged. As a result, practitioners involved in training the allied health sciences and in medical schools began to attend more to evidence-based learning. That gave evidenced-based practice a boost in that professional arena. However, in many cases, organizations have high turnover in training and limited learning professionals to provide guidance.

In some ways we’ve moved forward, but we still have large gaps and probably an ongoing challenge with promoting and disseminating the concepts of evidence-based learning.
Ruth Colvin Clark

Keeping Up with Learning Science

[05:30] – How do you personally keep up with new research and developments in learning science and the implications on learning design?

Every month, Ruth checks several journals (mostly academic) that publish fundamental research. There are 10 to 20 themes that she monitors and then files to reference when she’s preparing a chapter or a book. Most practitioners don’t have time to find and read original academic research, so she’s hoping to fill a gap by doing that reading for learners and summarizing the information.

[06:38] – What advice do you have for learning businesses looking to stay on top of learning science and learning-related research?

Ruth recommends that people look at books, online conferences, Web sites, and discussion forums on LinkedIn that are grounded with evidence-based practice.

She also suggests checking out businesses that help in making these kinds of translations, such as the International Society for Performance Improvement (ISPI ) and the Learning Development Accelerator.

Designing for E-learning Versus Other Modes

[08:02] – You co-authored (with Richard Mayer), e‑Learning and the Science of Instruction. How different is it to design effective learning for different modes? What are the salient differences when designing for e-learning versus classroom instruction, for example?

For all media, there is a common body of research and guidelines that apply, whether you’re in the classroom or whether you are designing for e-learning.

As for differences, one of the main differences in e-learning is learner control. For learners using asynchronous e-learning, they can usually go at their own pace and go back and review something. However, in the classroom, typically learners have to go at the instructor’s pace. Also, with technology, it’s a little easier make use of simulations or immersive virtual reality. The classroom has great opportunities for social presence.

All media have strengths and weaknesses, and perhaps sometimes the best solution is a blended solution, where you combine some asynchronous e-learning with some synchronous classroom-led training.

[10:07] – Is there a gold standard in terms of mode?

Research over the past 20 years or so has shown that e-learning has steadily grown in terms of the proportion of its use, but there, of course, continue to be examples of classroom training. Ruth thinks we should try to blend the best of all worlds and involve classroom as well as e-learning. Note the term “classroom” doesn’t always have to be the physical classroom since we now have technology for virtual classrooms too.

Sponsor: SelfStudy

[11:53] – If you’re looking for a technology partner to help you effectively engage learners online, check out our sponsor for this series.

Learn more and request a demo to see SelfStudy auto-create questions based on your content at selfstudy.com.

The Coherence Principle

[13:01] – What is the coherence principle? Any suggestions for how to avoid the pitfall of adding extra material?

A lot of times the information and the skills and knowledge that we are charged with creating learning around are not the most stimulating or exciting. Yet we’re all used to being immersed in high-intensity media, games, etc., so it’s tempting to try to spice up or elaborate on content. Below are some common dimensions that can make it harder for learners to learn:

Graphics
Often a simpler graphic is better, easier to produce, and ultimately more effective instructionally compared to a high-end graphical interface.
Stories
Stories are often memorable, but, if they are not directly related to learning outcomes, they can become distractions and disrupt learning.
Subject matter experts
Because they know so much, SMEs often want to provide everything there is to know about a certain topic. Instructional professionals need to narrow down “need to know” versus “nice to know.”

Coherence Principle (image from waterbearlearning.com)

[14:34] – Do you have any suggestions for how to work with subject matter experts to whittle away the non-essential and get to the core content?

Give the SMEs the learning objective, and then ask if the story (or other content they’re suggesting) supports those objectives.
Have groups of people review the material.
Act as an editor yourself, and cut out extraneous materials.

The Redundancy Principle

[15:50] – Would you tell us about the redundancy principle?

The redundancy principle refers to a situation when you have a screen or slide with a graphic of moderate to high complexity and you use text and an audio narration of that text to explain the graphic. This is redundant because the graphic goes into the visual center of a learner’s brain, and the on-screen text is competing with that limited visual resource. It can also be out of sync with what the learner’s natural reading rate is. All of this creates a higher cognitive load.

Redundancy Principle (image from waterbearlearning.com)

Strategies for Chunking and Segmenting Learning

[18:17] – What advice you have for how to effectively chunk or segment learning?

A huge advantage of asynchronous e-learning is that learners can control their own pace. This makes it possible for them to also segment what you have provided. It’s much more difficult to do this for something instructor-paced.

Keep your target audience in mind. If your learners are experienced in the content being taught, then the chunking principle is not quite so crucial because they themselves can manage greater amounts of instructional content. However, when you have novice learners, you should employ a variety of techniques to chunk and segment. For example, use a lot of white space. You can include just one or two words on the screen and use narration to elaborate on it. For complex graphics, you can build them gradually, explaining key points as the build happens.

I always would recommend err on the side of having shorter amounts of content or slides or screens in a topic. I myself, even in my pleasure reading, I’m more and more drawn to books that have short chapters. I just find it a whole lot easier and more enjoyable to read and review it. I think in learning, when you have relatively short little topics, you feel a sense of achievement, and you don’t feel so overwhelmed by the long, lengthy lesson.
Ruth Colvin Clark

Outlining and Storyboarding

[20:40] – Are outlining and segmenting related concepts in getting clear on the content you’re covering?

Outlining is one very powerful tool, and it’s a good place to start because it’s a relatively straightforward technique. Start with the learning objectives, next the content, and then use the outline to decide how to break it down into modules, lessons, or other divisions.

Storyboarding is another useful tool. Start with the outline, and then sketch out storyboards to decide where to show a graphic, etc. Start at a high level first, and then break out more detail.

[21:33] – A reader can look at the table of contents in e-Learning and the Science of Instruction, and it serves as a review session because it lists all the topics and subtopics.

That was an evidence-based technique. If you start a lesson or a chapter with a quick outline, that serves as an advance organizer and it helps with the reading or the learning process.

A Tenet of Effective Learning

[22:05] – What aspect of effective learning do you wish was more broadly understood and supported by those designing and providing learning to adults?

One of the major understandings that would help learning designers and providers is to appreciate the limits and strengths of working memory. We have two memories: working memory and long-term memory. Leveraging these two memories effectively leads to a lot of the instructional techniques already discussed. Understanding the fundamentals of the mental processes involved in learning and how to accommodate those would be a useful design understanding.

[23:37] – Is there anything else that you’d like to share?

The more we can promote evidence-based practice, the better off we, as a profession, will be, and the more we will grow. Also, keep in mind that research evolves, and hopefully we will continue to have people disseminating that evolving information for practitioners.

Part 2: Myra Roldan

[24:41] – Background information about Myra (who we heard from in our last episode on market assessment and needs assessment).

Working with SMEs to Incorporate Learning Design

[25:38] – What advice you have for working with SMEs who don’t necessarily know anything about effective learning design?

Subject matter experts don’t need learning design experience—that’s your job, as a learning provider and designer. Myra suggests doing the following when working with subject matter experts:

Ask good questions, such as, “What does someone who is new need [to the field, profession, industry, role, etc.] to know?” or “What are the [X number of] things that someone who is new needs to master first?” Then break those steps and points down.
Value the expertise of SMEs, but also help them narrow the content down to very specific areas.
Take control of and guide the conversation. Start by asking questions such as, “If I didn’t know anything about this or if I was new, what things do I need to know in order to be productive immediately?”
Have some back-up subject matter experts you can go to in case the one you’re working with doesn’t have the bandwidth to give you the time you need.

[28:11] – Are there other specific techniques, tactics, or questions that you like to use when engaging subject matter experts to help you get at that most essential content?

It varies from subject matter expert to subject matter expert, but, overall, Myra suggests:

Educate SMEs, and help them put themselves back in the shoes of a beginner.
Build trust with them.
Make them feel like they are the subject matter experts, and that you’re trying to gather nuggets of knowledge from them.
Let them know you value their time and the expertise they bring to the table.

Common Mistakes in Learning Design

[29:48] – What’s one of the common mistakes that you see in designing learning for adults?

One of the most common mistakes Myra sees is huge learning solutions that are drowned in theory and scenarios with too much information.

You end up throwing your learners into cognitive overload, where they don’t have sufficient time to actually process the information that they’re being given…. We tend to throw everything at people and then expect them to know what they’re doing. And we all know that there is a forgetting curve…. Even though we know that, we see learning being designed as so dense and thick…. And you get bored. You get lost. You don’t know what you’re supposed to be learning, and it’s not engaging. To avoid that, you should take a step back and put yourself in the shoes of the learner.
Myra Roldan

Design thinking can help. Ask yourself, “What are the obstacles that learners encounter when they’re using our solutions? And how does it impact their daily operations? How much work do they have to do on a daily basis, and how do we help lower the cognitive load?”

The Impact of New Technology on Instructional Design

[31:27] – What’s the impact of new and evolving technology on instructional design? Does new tech change how we design learning—or how we should design learning?

Myra explains that it does, and it doesn’t. You do need additional skills to work with the new technologies. But instead of learning how to create or program in the new technology, you should learn how to design for it—which is very different. It’s understanding how the tech works, but you’re not going to build it. To build, bring in an expert who knows how to program in that technology.

A main issue with a new technology is the cost. A lot of organizations want to integrate new technologies without really considering the cost of development and maintenance and the feasibility of integration into a learning space. Myra recommends that you do a feasibility study before you decide to use any of these new technologies.

Listen to Myra below where she shares how virtual reality has evolved and how it’s transforming the way we live, work, and learn.

Learning Science and DEI

[35:14] – What role do you see for learning science and learning design in the realm of diversity, equity, and inclusion?

Myra thinks learning science and learning design play very significant roles in diversity, equity, inclusion. Learning design is about how you’re going to help someone learn and what obstacles learners encounter and have to overcome to gain access to a specific training option.

When you think about learning science, you have machine learning, personalization, and AI. But how do you ensure that people are able to gain access?

I think where we fail is that we’re always trying to build new and shiny, the latest and greatest, but then we’re…widening the gap—the equity gap, the gender gap, the access gap, the opportunity gap gets wider when we start to integrate these new and exciting technologies that may not be accessible to someone who doesn’t have access to a computer and Internet.
Myra Roldan

Keeping Up with Learning Science

[37:43] – What do you do personally to keep up with new research and new developments in learning science and the implications that those might have on how you design?

Myra spends a lot of time doing labor market research to understand the competencies that employers are looking for in new employees. She also focuses on new tech developments. She doesn’t do a lot of research around learning science and learning design because she feels it’s too narrow of a perspective. Instead, she likes to reach out into other realms and explore what’s going on in psychology, technology, behavioral therapies, and other fields to see if there are things learning professionals should be looking at that are being applied effectively.

Advice for Incorporating Learning Science

[40:26] – What advice do you have for a learning business that’s looking to make good use of learning science in their offerings?

Myra’s number one advice is to know your audience. Don’t build a solution looking for a problem. Understand the problems that people are grappling with, and then align yourself to create solutions that will solve those problems. You want to build solutions around the needs of your audience.

[41:52] – Wrap-up

Ruth Colvin Clark founded Clark Consulting & Training and has written many articles and books, including Evidence-Based Training Methods and e-Learning and the Science of Instruction, that focus on translating research into practical guidelines for creating adult learning.

Ruth is generous with her translation work, and so you can find a number of free, one-page summaries she’s done of academic articles and their implications on the Learning Development Accelerator site. For example, she’s done one on the role of emotions in learning. Her short summaries may be sufficient, but she always provides the full citation, so you can also dig into the original research too.

Myra Roldan is a technologist, a learning professional, and chief cloudification officer at Amazon Web Services. You can connect with Myra on LinkedIn and at myraroldan.tk, where she has some free micro courses available on topics including using slides as a virtual background in Zoom, and she posts information there when she teaches courses that are accessible to the general public.

We’d also appreciate if you give us a rating on Apple Podcasts by going to https://www.leadinglearning.com/apple.

We personally appreciate your rating and review, but more importantly reviews and ratings play a big role in helping the podcast show up when people search for content on leading a learning business.

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[44:19] – Sign-off

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Needs, Wants, and Learning Science

Jackie Harman — Tue, 27 Jul 2021 11:21:24 +0000

Learner needs are important—but, in the context of learning businesses, learner wants are just as important. Correctly satisfying these needs and wants requires figuring out what to offer—not by assuming or guessing what’s needed in the market but by following processes and systems that yield the data to prove it.

In this third installment in our seven-part series focused on learning science for learning businesses, we explain why performing market and needs assessments are critical steps in effectively applying learning science because, to be able to apply learning science to specific content, we have to know what that content is. We also discuss the Market Insight Matrix, a tool we created that treats assessment as a process rather than an event.

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Market Assessment Versus Needs Assessment

[00:21] – Market assessments and needs assessments are related but different.

A needs assessment is a process for identifying gaps between current conditions and desired conditions and then addressing those gaps. In the case of learning businesses, those needs are usually tied to content that individuals need in order to know or do something.

A market assessment (sometimes called a market analysis) analyzes a learning business’s assets and activities to determine strengths and weaknesses and a learning business should do to best position its brand to take advantage of its market and audience.

We think of market assessment as more organizationally focused and needs assessment as more learner-focused or product-focused. A market assessment is about understanding the profession, field, or industry your learning business serves; knowing the other options learners in that space have; and determining how you can best support excellence in that profession, field, or industry through the products and services that you offer.

A needs assessment is about understanding learner needs and learning gaps so you can design and offer specific learning opportunities that will help close those gaps. Needs assessment and market assessment overlap, of course. You need to understand how your learners perceive their needs and therefore how they’re going to perceive your products and make sure that you’re developing the right products and positioning them in the right way in the market.

We also think of market assessment as addressing the question of “What will people buy?” and needs assessment as addressing the question “What positive impact will we create for the learner?” The two questions are—or at least should be—completely related, but learning businesses often emphasize one over the other, focusing, for example, on what they think learners need versus what will actually sell or vice versa.

When you are focused on what learner needs, you are going to ask questions about the challenges and opportunities the learners—or their employers—are currently facing; work to identify the specific knowledge, skills, attitudes, and behaviors needed to address those challenges and opportunities; and then determine the learning experiences that will help produce the needed knowledge, skills, attitudes, and behaviors.

When you are focused on market assessment, you are concerned about how large the market is, the other options learners have in the market, what their buying behaviors are, how price-sensitive they are, and how aware they are of your offerings.

Perception matters in both cases. You have to understand how members of the audience you aim to reach perceive their context and their specific needs. You’ll either need to align with those perceptions or determine ways that you can influence those perceptions to attract learners to the experiences you offer.

You do the market assessment and needs assessment to understand the current situation and perception. That doesn’t mean you have to accept that status quo as the “right” or only way to do things. You can work to influence and change perceptions. That’s arguably a harder tack to take, but it’s also one that can really stand you out from competitors, and it’s a tack that can really allow you to influence and change the field, profession, or industry you serve for the better.
Celisa Steele

With those descriptions in mind, let’s turn to the relationship between these kinds of assessment and learning science. Why do we include market and needs assessments in a discussion of learning science?

Assessment’s Relationship with Learning Science

[04:54] – To answer that question, let’s revisit at how we defined learning science in episode one of this series. Learning science is an interdisciplinary field devoted to better understanding how learning happens and then applying that understanding to creating and improving instructional methods, curricula, learning environments, and more. The curricula, learning environments, and materials that get developed involve specific content.

In order to apply learning science in context—i.e., in order to apply learning science to specific content—we have to know what that content is. Market assessment and needs assessment are how we determine what that content is. Just as learning science focuses on getting verifiable evidence of which learning approaches work best, these kinds of assessments allow us to determine the content not by assuming or guessing what’s needed in the market but by following processes and systems that help us ensure the content is what learners need.

The idea of systems and processes is critical because, ideally, you want to leave as little of this to chance as you can. That’s a key reason we’re talking about market and needs assessment as part of a conversation about learning science: There are scientific ways to go about them.
Jeff Cobb

That may seem obvious, but we often see situations where learning businesses have not been scientific, where they have not really followed systems and processes to assess their market and learner needs. But the lack of system or process is at the root of the whole “We built it, and they didn’t come” problem we hear about so often.

We keep using the word process because assessment should be something that takes place over time. That doesn’t mean there’s not value in taking snapshots in time, like you would with a typical needs assessment survey, for example. It just means you shouldn’t rely solely on that—you need to have methods in place of observing and engaging with prospective learners over time to get a truer sense of their situation, their challenges and problems, and how they behave.

In addition to treating assessment as a process rather than a snapshot in time, you should also bring a scientific mindset to it. Treat your ideas about market and learner needs as theories, and you are always searching for evidence to prove or disprove those theories. That’s the essence of the scientific method.

Market Insight Matrix

[7:40] – We have developed a tool for supporting this approach called the Market Insight Matrix. The matrix that lays out market assessment according to three stages and three types of activity.

The Market Insight Matrix lays out three stages in market assessment:

Idea generation
The higher the quality of the ideas you come up with initially, the easier and more effective the subsequent parts of the market assessment will be. You want diverse input at this stage. Don’t rely only on the input of your education committee. You also need input from staff and volunteers, important customers, and influencers in your market.
Idea verification
In our experience, many organizations effectively stop at the idea generation stage. They come up with a few good ideas, prioritize one or two of them—often based on the thinking of a small number of people in the organization—and then begin building a product. A better approach is to take the ideas generated in stage 1 and verify them by looking at what Web searches, customers’ and prospects’ discussions in social media, and surveys and polls can tell you.
Idea testing
To test the idea, put the concept—or even a version of the product (maybe a minimum viable product)—into the market place and see if you can get people to take action. Will they sign up for future notifications via a landing page? Can you pre-sell the product and thereby ensure purchases from the get-go?

[09:33] – The stages are one key part of the process. The next part is the types of activities you should engage in across these stages. These fall into three main categories:

Tracking focuses primarily on historical, quantitative data. What can you tell—based on a variety of tools like Google Analytics, Google Trends, and data from your e-commerce and learning management systems—about the behavior of your members and customers in the recent past? What content has been of interest? Where have they found it?
Listening is another activity. Listening focuses on observing what your members and customers are saying and doing. What are they saying as they interact with each other, your organization and its offerings, even your competitors and their offerings? You can find out by monitoring social media, conducting user testing, or mining evaluations.
Asking involves you engaging directly with stakeholders and requesting their input on specific questions. This is the path of traditional tools like surveys and focus groups but also includes activities like pre-selling and crowdfunding.

One of the asking activities you can use to assess your market is the tried-and-true focus group. Here are 5 Tips to Focus Your Use of Focus Groups.

Combine the three stages and the three activity types, and we get the Market Insight Matrix. You can use the matrix for identifying and then implementing the specific ways in which you will engage in market assessment over time. It’s a simple tool, but it brings a lot more clarity—and more rigor—to the process.

The key to the kind of assessment approach we’re advocating here—and it’s equally true of market assessment and learner needs assessment—is putting yourself in a position to gather, analyze, and then leverage valuable data about your learners.

Thinking about assessment—and particularly assessment as an ongoing process versus a one-off or even periodic event—reminds us comments Brenda McLaughlin, the CEO of SelfStudy, said when we spoke with her. She talked about blending learning and assessment and how constantly reinforcing strengths and filling gaps and weaknesses with the materials available. This is a natural next step in assessment, moving from a more general needs assessment, which guides content design and development, to specific-to-the-individual, specific-to-the-content assessments that happen in the moment.

When that happens, assessment really then is a process. It gets baked into the process rather than being something separate and discrete, and it’s certainly not a one-off event in that context. And that kind of attention to assessment helps learners fill gaps and reinforce strengths.
Celisa Steele

Sponsor: SelfStudy

[15:26] – SelfStudy, our sponsor for this series, is harnessing artificial intelligence to help organizations assess and address learners’ needs in real time.

Learn more and request a demo to see SelfStudy auto-create questions based on your content at selfstudy.com.

Needs and Wants

[16:41] – Learner needs are important—but, in the context of learning businesses, learner wants are just as important. Your learners most likely have other options and choices, so offering what they need along with what they want increases the chances that they’ll opt for you out of the sea choices available to them.

That jibes with the comments Megan Sumeracki made in episode 273 when talking about captive audiences (like high school students) versus the adults served by learning businesses who have usually have choices about what learning to engage in or not. She pointed out that enjoyment, which might lead to higher engagement and motivation, might be more important in non-captive situations, meaning learner needs (which would dictate content) can be married with learner wants (are learners enjoying the learning?) to create an extra potent offering. Ideally, learning businesses give learners both what they need and what they want.

It can be easy to get overly focused on what we feel learners should be doing or achieving (what usually corresponds with what we mean by “needs”), but it’s also really critical to understand what they actually want to be doing when it comes to learning.

An important twist on that is that asking learners directly about what they want can often result in misleading or invalid data. Learning businesses tend to be fond of asking prospective learners about their preferences, but it’s hard to do that in a way that doesn’t influence the answer. Plus, in many cases, learners don’t have enough experience to say—and, even if they do, preferences are generally a poor predictor of behavior. Our view is that you need to ask about behaviors, not preferences, to get at what learners want.

For example, instead of asking if they would prefer a self-paced online course or an instructor-led Webinar series, ask if they have taken a self-paced online course before or participated in an instructor-led Webinar series. That helps you get at behavior rather than preference.

That’s an approach we talked about in more detail in a past episode titled “Give the Learners What They Want,” where we talked about four key areas of gathering and assessing data. Assessing behavior rather than preferences is one of them, but we also discuss the following areas:

Understanding your demand dynamics
Often your greatest evidence for what your customers will want in the future is what they have already been buying or what they have been looking for—and, to the extent you can determine, why?
Identifying key value factors
It’s important to know the factors prospective customers weigh when making purchase decisions. You’ll want to get a clear read on which variables significantly raise or lower value in the eyes of your learners. These might be things like presenter’s reputation or the results that past participants have attributed to their participation in a course.
Gauging commitment and conversion, not interest
Frequently learning businesses will ask prospective customers whether they are interested in a particular offering. A lot of times what happens is that people say they are interested, but then very few sign up when the course—or whatever the product is—is actually offered. We offer some ideas of how to get at commitment and how to convert in that “Give the Learners What They Want” episode.

[21:50] – To add some perspective, we spoke with Myra Roldan, a seasoned technologist and learning professional, who we’ll hear more from later in this series. She talked about the importance of understanding your audience and provided some concrete examples of how knowing your specific audience can and should inform choices about the design, development, and delivery of offerings. Knowing your audience comes from the kinds of intelligence and insight you can get from market assessments and needs assessments.

Myra’s comments get not just at content but also the format and the importance of really understanding what’s going to be appealing to and possible for your your learners. You want to use the right methods to achieve the desired learning outcomes, but those methods can come in a variety of formats and media.

[24:52] – Wrap-up

Remember to check out the Market Insight Matrix, a free resource that may prove helpful if you’re looking for a do-it-yourself tool to help you with market assessment.

We’d also appreciate if you give us a rating on Apple Podcasts by going to https://www.leadinglearning.com/apple.

We personally appreciate your rating and review, but more importantly reviews and ratings play a big role in helping the podcast show up when people search for content on leading a learning business.

Finally, consider following us and sharing the good word about Leading Learning. You can find us on Twitter, Facebook, and LinkedIn.

[26:07] – Sign-off

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Effective Learning with Learning Scientist Megan Sumeracki

Jackie Harman — Tue, 20 Jul 2021 12:07:59 +0000

Dr. Megan Sumeracki is an associate professor of psychology at Rhode Island College and co-founder of The Learning Scientists, a group of cognitive psychological scientists aiming to make scientific research on learning more accessible to students, teachers, and other educators. Her area of expertise is in human learning and memory, and in applying the science of learning in different contexts.

In this second episode in our series on learning science’s role in a learning business, Jeff talks with Megan about key ideas related to cognitive psychology, what they mean for learning providers, and tips for creating effective learning experiences that incorporate the science of learning. Specifically, they explore the concept of retrieval practice, ways to implement it, and the powerful impact it can have on learning.

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A Tenet of Effective Learning

[02:00] – What is one tenet of effective learning, supported by good research and science, do you wish was more broadly understood and supported by those designing and providing learning to adults?

Megan explains how learning strategies that make us feel like we’re learning efficiently might not produce long-term, durable learning, but strategies that feel more difficult and make us think we’re not learning as well actually produce long-term durable learning. Our own assessment of how we’re doing in the moment can’t be trusted.

For example, repeatedly reading content will make it feel familiar, and we think we won’t forget it in the future. Putting the content away and trying to produce it from memory (retrieval practice) is a better strategy for producing long-term, durable learning, though. It feels difficult, which tricks us into thinking we’re not learning the content as well.

Advice for Incorporating Learning Science

[05:47] – What advice do you have for a learning business looking to make good use of learning science in their offerings?

Megan recommends incorporating retrieval practice and spacing:

Retrieval practice
Retrieval practice can be a quiz, a test, chatting about the content, or asking participants to bring to mind something and then having a few share.

Spacing
Spacing can be tricky because professional development sessions tend to be condensed to one to a few days, but any way that you can spread the information out over time will be helpful. Possibilities include pre-conference reading, post-conference reminders for retrieval, and meeting virtually over time rather than physically.

Sponsor: SelfStudy

[09:59] – If you’re looking for a partner to help you create and deliver learning experiences using tools grounded in learning science, check out our sponsor for this series.

Learn more and request a demo to see SelfStudy auto-create questions based on your content at selfstudy.com.

Learning Scientists’ Understanding of Adult Learning

[11:12] – How would you describe where we are with learning science right now? How well do learning scientists truly understand how adults learn at this point?

On one hand, Megan thinks we understand adult learning pretty well. In the last couple of decades, we have made leaps and bounds. Some strategies (like spacing) have been around as long as the field has been around, but we’ve learned a lot more recently about their durability and the ways that we can implement them.

The broader dissemination of information and trying to have conversations with those who are in the business of learning is new. Also, she says the field hasn’t done a great job in the past of communicating the science effectively.

There are areas where they don’t know as much and where there are still many open questions. A good scientist is going to acknowledge that and isn’t going to try to create a one-size-fits-all approach to learning. Rather, Megan recommends being open to flexible guiding principles and then working to figure out what’s going to be the best approach in a specific context.

Megan says It’s actually quite difficult to predict exactly how a specific adult is going to learn specific content because there are so many variables at play. General rules of thumb exist, and those work well across the board—but there’s still a lot to learn.

The General Public’s Understanding of Learning

[13:57] – What’s your perspective on how broadly dispersed the knowledge about learning science is? Have you seen the reach of that knowledge expand during the time that you’ve been working as a learning scientist?

Megan shares that she and her former colleague Yana Weinstein-Jones originally created The Learning Scientists because they were disappointed in the avenues typically used to disseminate research—the research wasn’t getting read because of accessibility.

It’s unreasonable to expect those who are in these real, boots-on-the-ground learning contexts to gain access to these things, read it, and figure out how it applies in their settings…. The Learning Scientists project really was about trying to make learning more accessible and the science of learning more accessible.
Dr. Megan Sumeracki

Cognitive Versus Behavioral Psychology

[17:39] – What is cognitive psychology, and where do you focus? How is cognitive psychology different from behavioral psychology when it comes to learning?

Megan explains behavioral and cognitive psychology:

Behavioral Psychology

Behaviorism was a reaction to early schools of thought that focused on introspection and thinking about thinking and not a lot of observable behavior.
Behaviorists don’t deny that mental processes are going on but think that, rather than study those processes directly, we can understand them by looking at at behavior.
Behaviorists wanted to be taken more seriously as a science so they looked to see what they could verify in observable behavior.
Behaviorists tend to believe humans are born as a blank slate, and that it’s really all nurture as opposed to nature.

Cognitive Psychology

Cognitive psychology says we can’t ignore the things that are going on in our minds, and so we do need to study mental processes while also studying observable behavior.
Cognitive psychology studies our perceptual systems. For example, how do we see and then recognize a chair as a chair, and how is it that when we see a new chair that we’ve never seen before, we don’t have trouble identifying that that thing is a chair and placing it in that category?
Cognitive psychology also includes the study of memory, learning, problem solving, and understanding knowledge representations.

Megan focuses on applying cognitive psychology to educational settings and, along with others, engages in a lab-to-classroom model. They start in the lab, where they can maintain control, and then move closer to real environments. Finally, they go into the actual environments (e.g., classrooms) and look to see whether or not the processes that they had people engaging in are causing learning.

Memory and Learning

[23:21] – How do you describe memory’s relationship to learning and memory’s role in learning?

When she teaches her learning course, Megan often asks students what the difference between learning and memory is. Their response is that learning is the process of getting the memory. She admits she doesn’t know the answer to her own question because we often talk in spatial metaphors—we’re trying to get things into our head, or, if we can’t remember something, we’re trying to find a memory, and we might search for it.

While there has to be some remnant of the past, that doesn’t mean it has a single, specific location in the brain. Rather, networks and systems are involved neurologically. Humans can show evidence of learning without realizing it. It’s a lot more complicated than we think, but Megan agrees that learning is a process of acquiring information that we are able to use in the future. But whether or not we can use it in the future and how much we’re actually able to produce consciously is only part of the story.

Retrieval Practice

[25:45] – What is retrieval practice, and what are some examples of it?

Essentially, retrieval practice is simply bringing information to mind and then hopefully producing it in some way. You technically don’t have to overtly produce it in order to bring it to mind. You can just consciously bring it to your mind, and Megan has some research suggesting that covert retrieval (bringing it to mind without producing it) might be just as effective as overt retrieval, but that’s with very simple materials.

Research with more complex materials (like what you would learn in an actual context) suggests it’s difficult for us to only mentally articulate it for retrieval. In that context, producing the material by writing it, drawing it, or saying it is helpful.

Retrieval helps us learn in multiple ways, and, from a practical perspective, Megan says it doesn’t really matter which way or ways we target—they all sort of pile on together.

Some ways retrieval practice is beneficial include the following:

Retrieval practice produces a feedback about what you know and what you don’t know, and that feedback might allow you to then learn.
Retrieval practice allows you to study more effectively and efficiently. You can allocate resources more judiciously; you can review things that you might not have reviewed had you not realized you couldn’t remember it.
Retrieval practice gives an instructor information about what the individuals who are trying to learn know (or don’t), which enables the instructor to then provide more targeted instruction.
Retrieval practice also provides a direct effect—bringing information to mind produces learning in and of itself.

One way to engage in retrieval practice in educational settings is to give frequent low-stakes tests or quizzes (the low-stakes aspect helps with test anxiety). Retrieval practice can also be drawing what you remember or sketching a concept map. Also, having learners explain content to one another in small groups without the aid of the material right in front of them is another approach to retrieval practice.

Listen to Dr. Megan Sumeracki share what retrieval practice and hiding broccoli in brownies have to do with one another. To learn more, see the related blog post, Retrieval Practice: Hiding Broccoli in the Brownies.

[30:28] – What are ways to support retrieval in recorded presentations?

To increase retrieval opportunities and effectiveness in an asynchronous setting, Megan recommends something like, “Pause this video and think about X.” Explicitly talk about retrieval and the importance of it. Then to motivate learners to do the retrieval work, ask them to bring their responses to the next synchronous session or ask them to type into the chat (where applicable). Without a prompt to show evidence of the retrieval work, learners may just think about it in their head for a second, and that’s where covert retrieval doesn’t work as well.

It also may be helpful to send out text messages after a learning experience with reminders to practice retrieval; such an approach also provides some spacing. Giving learners prompting questions and having them talk through them in breakout rooms can also be effective. Although Megan notes that collaborative retrieval is tricky because everyone has their own retrieval structure; collaborative retrieval is an area where cognitive science still has a lot of room to grow.

Megan also inserts quiz questions in her videos that students have to answer, and they get immediate feedback about whether their answer was right or wrong. Another useful aspect of retrieval practice opportunities is that they break up content and help learners stay engaged, maintain attention, and stay focused.

[35:22] – It sounds like there’s an element of retrieval that’s effective even without feedback. For example, if I’m musician playing the piano and hit a wrong note, then that’s some feedback telling me I need to go back and practice that again. Before I actually get to the point of playing at the piano, is there something happening in terms of retrieval that’s contributing to learning, even before I get any sort of feedback from the instrument?

When you produce information, you have a certain level of confidence, and that confidence could drive how well you think you’re doing. You can think you’re doing really well, or you can think you’re not, but that level of confidence does not necessarily correspond to accuracy. You can be confidently wrong.

Practicing retrieval helps even when you don’t get the corrective feedback. However, adding corrective feedback can make it particularly effective, and, if you consistently retrieve the wrong information, you strengthen that, which is not helpful for learning.

Further Explorations in Learning Science

[39:44] – What interests you in what we don’t about learning science? What question would you love to see answered?

Megan shares that she’s become very interested in motivation as a result of the COVID-19 pandemic teaching that she has been doing. She’s also interested in intrinsic and extrinsic interest, something she says the field knows about, but she personally wants to learn more about. She’s also interested in individual differences and how they can shape the way an individual learns in specific contexts.

Learning styles are still popular among a number of individuals, and it’s an extremely pervasive myth that matching instruction to an individual’s learning style is going to help them learn. That’s not true. Individuals do have preferences. You might prefer to listen to a podcast or watch a video over reading something. You might prefer online versus in-person, or you might prefer in-person versus online, but that doesn’t necessarily mean that’s the way you’re going to learn better.

What matters is the processes that you are engaging with, and certain materials tend to be better…. So those individual differences don’t seem to matter in terms of learning. I do think that anybody can learn online or in person. We just have to make sure that the processes that they are engaging in online or in person are top-notch.
Dr. Megan Sumeracki

Megan is interested in those individual differences and how they affect how we learn. She says cognitive psychologists who are experimentalists don’t tend to look at individual differences as often as some other areas of psychology, but she thinks they should be doing more of that.

Motivation

[43:00] – Do you have any tips or tricks to increase motivation to learn in adult learning settings?

Megan elaborates on the concept of metacognition, which is the idea of knowing what you know and determining how well you’re learning in a particular context. There’s some research (not published yet) looking at interest and how it affects learning and your metacognitive judgments of how well you’re learning. The researchers found that having a greater self-reported interest in the material led to increased judgments of learning—so they thought that they were learning it better—but it did not affect actual learning. (The research deals with “captive” learners, i.e., those who don’t have a choice about being there versus participating in a similar offering.)

They engaged in X amount of time of some specific learning strategy. So it didn’t matter whether they were interested or not in terms of actual learning because they all engaged in retrieval practice at a certain level. So it’s actually kind of good news. You don’t have to be overly interested. As long as you know that you have to learn the content, even if you’re not interested in it, if you can buckle down and use the science of learning to say, “Here’s the strategy that’s going to be effective,” it will be effective.
Dr. Megan Sumeracki

The good news is learners don’t have to love every minute of a course or experience in order to learn. But, if the audience isn’t captive, and they have a choice, how do we increase interest and motivation? Megan admits she’s doesn’t know the answer, although maybe somebody else in the field does. She suggests asking participants if they enjoyed the experience and what they enjoyed so you determine what they found engaging, which might be a key to motivating others. However, she cautions not to mistake enjoyment for learning.

[46:42] – Wrap-Up

Megan Sumeracki is co-founder of The Learning Scientists, which she manages with three other smart, motivated women who love science and data: Carolina Kuepper Tetzel, Cindy Nebel, and Althea Need Kaminske. We encourage you to learn more about her and her colleagues’ work at learningscientists.org and on Twitter as @AceThatTest. On The Learning Scientists Web site, you’ll find a blog, a podcast, and downloadable materials that can help expand your team’s, your facilitators’, your learners’, and your own understanding of effective learning strategies.

In particular, we’ll call out a blog post by Megan called “Elaboration As Self-Explanation.” The post comes from a particular experience with high school teachers, but the benefits of self-explanation—and the tactics for encouraging it—apply to adult lifelong learners as well. And don’t forget to check out their resources on six strategies for effective learning that we highlighted in the previous episode.

We’d also appreciate if you give us a rating on Apple Podcasts by going to https://www.leadinglearning.com/apple.

We personally appreciate your rating and review, but more importantly reviews and ratings play a big role in helping the podcast show up when people search for content on leading a learning business.

Finally, consider following us and sharing the good word about Leading Learning. You can find us on Twitter, Facebook, and LinkedIn.

[48:48] – Sign-off

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Learning Science for Learning Impact

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Learning Science for Learning Impact

Jackie Harman — Tue, 13 Jul 2021 12:19:37 +0000

Jeff Cobb and Celisa Steele

For any organization offering learning, learning science is important. But it’s arguably even more important for learning businesses because of the far-reaching impact that can be achieved from effectively applying it.

In this first installment in our “Learning Science for Learning Businesses” new seven-part series, we take a broad look at the science of learning, including related practical insights and key areas of influence for learning businesses. We also preview the specific areas of learning science that we’ll address later in the series and their related implications for creating a thriving learning business.

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What Is Learning Science?

[00:20] – Saying we’re focusing on learning science invites the obvious but important question “What is learning science?”

The science of learning is an interdisciplinary field devoted to better understanding how learning happens and then applying that understanding to creating and improving instructional methods, curricula, formal and informal learning environments, and more.

In some ways, learning science is a new field in the sense that we’ve become much more conscious of it in the last couple of decades or so, particularly with advances in neuroscience and even in psychology. Implicitly, the whole science of learning has been there for a very long time, but it has the feel of something new, and we felt we really needed to dig into it because it is so important to modern learning and being a modern learning business.

There’s even an association for this: the International Society of the Learning Sciences. One thing to emphasize is the field’s foundation in evidence-based approaches. The science part of the science of learning is that it relies on experiments and studies of what actually works or doesn’t, what actually improves learning or doesn’t.

That evidence-based approach is probably one of the reasons we’re so fascinated with it because that’s consistent with our own bias and how we like to approach learning, how we like to approach business, probably how we like to approach life in general. There’s always just a lot of intuition out there. Intuition can be a good thing, but it often proves to not be our friend. You really do have to test things and figure out what’s actually going to work. Go with your intuitions, obviously trust them to a certain extent, but always verify; always go for that evidence-based approach.

The rigor of the science part of learning science means it can be a bit slow—structuring the studies, writing them up, getting them peer reviewed and published takes time. Even once a study is published about, say, the role of learning objectives in learning, it can be dense. Given rise to a cadre of folks devoted to translating academic research for the practitioners—the designers and teachers and facilitators who are the ones who actually need to know the stuff if learning science is actually going to result in more effective products and experiences.

That cadre of research-to-practice translators includes folks like Will Thalheimer, Patti Shank, Connie Malamed, co-author of Make It Stick: The Science of Successful Learning, Peter C. Brown, and others we’ve had on the podcast in the past.

It also includes folks like Ruth Colvin Clark, whom we’ll talk with for this series, which is exciting as we’ve been big fans of her work for years, especially e-Learning and the Science of Instruction.

Another translator we talk with in this series is Megan Sumeracki, co-founder of The Learning Scientists, who are cognitive psychologists interested in the science of learning. Their vision is to make scientific research on learning more accessible to students, teachers, and other educators.

Learning science has clear implications for those providing learning—and that’s why we have these translators doing the work to bridge academic research with real-world application. For any organization offering learning, learning science is important, but it’s arguably even more important for learning businesses.

There’s widespread recognition now that lifelong learning is so important (see our related episode, The Mainstreaming of Lifelong Learning).

Providing education and learning experiences to adult lifelong learners is obviously at the core of being in a learning business. But, to thrive in that business, you must have impact. You have to move the dial for the learners you’re serving. That’s what learning science helps to guarantee, and it’s just so critical for learning businesses.
Jeff Cobb

See our related episode, One Word: Impact.

Sponsor: SelfStudy

[07:49] – If you’re looking for a partner to help you create and deliver learning experiences using tools grounded in learning science, check out our sponsor for this series.

Learn more and request a demo to see SelfStudy auto-create questions based on your content at selfstudy.com.

Practical Insights from the Science of Learning

[09:10] – To help convey the potential impact of learning science on learning design and the success of learning businesses and their learners, below are some of the practical insights that have come from the science of learning.

Working memory, cognitive load, and long-term memory. We all have a limited amount of cognitive space to use to engage with and process new information and ideas. That space—typically referred to as working memory—can only hold a few items at any one time. We have to design to focus learners’ working memory on what’s relevant and necessary to learn—so the learner isn’t squandering finite cognitive resources on irrelevant stuff. While we do know that that learning needs to be effortful to stick, that’s not the kind of effort that you want people to make. You don’t want them to have to deal with overload. You want to ease that path to moving that information, the new knowledge that they’re acquiring, from short-term memory, working memory, into long-term.

To learn more, check out our interview with Dr. Patti Shank, author of Manage Memory for Deeper Learning (*see transcript for specific excerpt referenced).

[14:10] –

Effort and spacing. Combining these is so important. Spacing is the idea that you don’t encounter content or practice something just once, rather you do it repeatedly over time with some space in between. We think a lot of learning scientists/learning theorists would agree that it’s one of the most powerful ways to make sure that learning sticks.

To learn more, check out our interview with Peter C. Brown, co-author of Make it Stick: The Science of Successful Learning (*see transcript for specific excerpt referenced).

Brenda McLaughlin, CEO of SelfStudy also shares how they see a growing understanding in the market of the benefits of some of these science-based practices such as personalization, spacing, and repetition.

[18:40] – The interesting thing is that a lot of the big takeaways from learning science aren’t new discoveries—personalization, spacing and repetition and effort, the role of memory. None of that’s new. The Ebbinghaus forgetting curve—which shows that we forget the vast majority of what we “learn”—has been around since the 1880s.

Ebbinghaus Forgetting Curve (image from inkling.com)

Our understanding, of course, is deepening now, and it’s becoming more nuanced. Also, the pandemic was a sort of petri dish in this past year because we had to scramble so quickly to get online and figure out how to make learning effective in an environment that many organizations hadn’t focused on as much as they should have before.

Key Areas of Learning Science’s Influence

[20:17] – Learning science plays a direct role in a learning business’s portfolio of products. And portfolio is one of the 5 domains we identified in the Learning Business Maturity Model^TM. Having a good understanding of learning science plays into a learning business’s capacity too—having staff who and technology that understand and make use of learning science is great. And good learning science will help with marketing, and it can—and arguably should—factor into a learning business’s strategy, and having leadership tuned in is key too. But the most direct role is in portfolio.

Learning Business Maturity Model^TM

In this series we want to look at some of the key aspects of learning science, and we’ll pull in other experts and draw on conversations for perspective. We’ll focus on:

Behavioral and cognitive psychology
Needs assessment
Content
Feedback and practice
Evaluation

[25:05] – Of course, all of this is important in general. But getting it right is really at the core of being an effective learning business, being a learning business that’s going to be able to not just survive but thrive in the current world.

Learning science will also help your learning business:

Stand out in a crowded marketplace
Improve reach, revenue, and impact
Have an impact on the learning businesses ecosystem

[28:15] – Wrap-up

Highlighted Resources:

A wealth of resources exists for keeping up with evidence-based practice ideas. We’ll share some specific ones over the course of this series but to avoid overwhelming you we’ll just highlight two now:

For a more in-depth resource, we suggest Make It Stick: The Science of Successful Learning.
For a quicker-hits resource, and one that’s freely and immediately available, check out Six Strategies for Effective Learning from The Learning Scientists.

As you look at those six strategies, think about which your learning business might benefit from using more?

Impact is as important for podcasting as it is for learning. We’d also appreciate if you give us a rating on Apple Podcasts by going to https://www.leadinglearning.com/apple.

We personally appreciate your rating and review, but more importantly reviews and ratings play a big role in helping the podcast show up when people search for content on leading a learning business.

Finally, consider following us and sharing the good word about Leading Learning. You can find us on Twitter, Facebook, and LinkedIn.

[32:30] – Sign off

Episodes on Related Topics:

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Digital Transformation: It’s All About Culture

Guest Contributor — Mon, 12 Jul 2021 12:47:58 +0000

Editorial Note: We’ve written about the importance of learning culture and suggested that fostering a learning culture requires a different perspective on learning and—by extension—what’s needed to support effective learning. It also requires re-thinking significantly how the stakeholders in your learning business interact, the assumptions they bring to the table, and how new perspectives translate into new strategies. The transformation of learning is, of course, very often a part of larger digital transformation efforts, and research by our colleagues Maddie Grant and Elizabeth Engel highlights just how important culture is to digital transformation. In their research and in this guest post, Maddie and Elizabeth address the relationship between digital transformation and culture in the context of associations—important players in the learning business—and many of their conclusions apply to learning business broadly.

***

Organizations of all types—for-profit and tax-exempt—have been talking about digital transformation for many years, yet association efforts continue to lag.

Why is that?

In The No BS Guide to Digital Transformation: How Intentional Culture Change Can Propel Associations Forward, we posit that it’s all about culture.

The main challenge associations face in digital transformation initiatives is that digital transformation is an iterative process that includes both technologies and culture. Associations focus on creating more value for our members and for the professions and industries we serve, which means we need to continuously change the way we work. And that means we need to be on the lookout for the tools and technologies that will enable us to change.

Which sounds if not easy then at least simple.

So why aren’t we doing it?

Our research revealed that, while there is still work to be done on the technology front, it’s not technology that’s holding our industry back; it’s culture and, more specifically, culture change. This is why a lot of the copious digital transformation advice that exists doesn’t quite hit the mark for associations. For-profit culture is fundamentally different than association culture.

What do we mean by that?

First, a member is more than just a customer. Your members are invested in your association in a way that “members” of Costco are not. Your board of directors has a very different role to play in the governance of your association than that of a for-profit board. Additionally, your board members are users (or beneficiaries) of your association in a way that for-profit board members, even those who are customers of the organizations whose boards they sit on, are not. For-profits don’t have anything analogous to chapters or affiliates. This all complicates culture work–there are a lot more stakeholders who are a lot more invested in associations than for-profits.

But internal association culture can be a challenge as well. Your association may claim values like collaboration and innovation. But is that really true? Maybe your collaboration is a little awkward—your internal departments are siloed and don’t generally share what they’re working on freely and effectively. So how will you suddenly start sharing data openly on a new platform?

Maybe your commitment to innovation is a little more talk than walk—you say you’re forward-thinking, but people get punished for taking a risk, at least if it doesn’t pan out. So how are you going to get comfortable experimenting? You need to get your culture ready for this work if you want it to succeed.

As Maddie is fond of remarking, digital transformation comes down to culture change + vendor selection.

From the technology perspective, that means you don’t want a mobile strategy or a data analytics strategy or a social strategy—you need a well-thought-out organizational strategy that includes these things. The tech of transformation (AI, cloud, data analytics, Internet of Things, mobile, social, Web) is not the end—it’s the means to the end of accomplishing your larger organizational goals in a coordinated and member-centric way.

But it’s the culture part that gets really tricky. How do you change your culture so it enables digital transformation rather than blocking it?

Digital transformation success starts at the top, with a specific mandate from your C suite, answering the “why” of digital transformation in a clear and compelling way. Your leaders, both staff and elected, must also provide strong, consistent support and resources, including budget. You also need an organization-wide commitment to identifying and, as necessary, adjusting your culture patterns—patterns that define what is valued inside your culture, which then drives behavior.

Where do you start?

Learning about what digital transformation is (and isn’t), why it matters, what barriers are unique to associations, what advantages our industry has—that’s all interesting and useful.

But how do you actually accomplish digital transformation in your association?

We have you covered:

Assess where you are now.
Secure leadership support and a funding commitment.
Identify strategic areas where digital tech could make a difference.
Review your legacy systems and processes.
Recruit your team.
Get comfortable with experimenting.
Improve your culture management.

Then—and only then—chose your tech investments, and make it happen. In other words, to be successful, digital transformation must start with culture change and proceed to technologies, not the other way around.

For more on how to do all that, download the full white paper for free at https://bit.ly/3y4O6dy.

***

You can also join Maddie, Elizabeth, and the team from the Construction Specifications Institute (one of their case studies) for their first Webinar on the project Friday, July 16, at 1 pm ET. Find details and register at https://propelnow.co/events/digital-transformation-live-webinar.

About the Authors

Elizabeth Weaver Engel, M.A., CAE, is Chief Strategist at Spark Consulting. For more than twenty years, Elizabeth has helped associations grow in membership, marketing, communications, public presence, and especially revenue, which is what Spark is all about. She speaks and writes frequently on a variety of topics in association management. When she’s not helping associations grow, Elizabeth loves to dance, listen to live music, cook, and garden.

Maddie Grant, CAE, co-founder at PROPEL, is an expert culture designer and digital strategist who focuses on helping organizations prosper through culture change. She has specific expertise in digital transformation and generational differences in the workplace. She has explored the evolution of culture in the digital age through her books, including Humanize: How People-Centric Organizations Succeed in a Social World (2011), When Millennials Take Over: Preparing for the Ridiculously Optimistic Future of Business (2015), and the Non-Obvious Guide to Employee Engagement (2019). Find Maddie at propelnow.co.

The post Digital Transformation: It’s All About Culture appeared first on Leading Learning.

Effectively Training a Global Audience: What Works?

Guest Contributor — Thu, 17 Jun 2021 11:25:00 +0000

by Amy Morrisey of Artisan E-Learning

We work with a lot of different associations at Artisan E-Learning. We’ve noticed when associations are new to e-learning, it’s common for them to underestimate the complexity and number of moving parts involved in a project. It’s helpful to have an understanding of e-learning course creation, from coordinating subject matter experts (SMEs) and writing scripts to using rapid authoring tools, when creating a successful learning experience.

Now, if it’s already a complicated process to create e-learning courses in your native language, what happens when you add one, two, three, or more languages into the mix? If you’re not careful, you might end up with a chaotic process and a less-than-effective course.

Training a global audience comes with a unique set of challenges. Let’s walk through a few obstacles when training your global association audience and how you can create e-learning courses that overcome them.

What obstacles occur with e-learning for global audiences?

Learner engagement is the “holy grail” of e-learning—if a learner isn’t paying attention, they’re not going to learn much at all. But, for a learner to pay attention, two things need to happen.

First, the learner has to see the content as meaningful in light of achieving their goals. Second, they need to be able to easily access all the content and resources necessary to understand the information.

These are baseline requirements for a learner to “opt in” to your content. But for international learners, roadblocks in your course itself can prevent them from fulfilling those basic requirements. Here are a few obstacles an international learner might encounter:

Language barriers
Only slightly under 5 percent of the world population are English speakers. Do you know how many of your members speak English as a second, third, or fourth language? Say you have an association member who does speak English, but it’s their second language. While they may be able to complete a course written in English, it may be significantly more difficult than if it was written in their native language.
Cultural differences
Imagine you were raised in Japan, where you learned to bow when you meet someone in a professional setting and to avoid putting your hands in your pockets out of courtesy. Now you’re completing a course created by an association based in the United States of America, and the characters refer to their superiors by their first name, speaking casually, and certainly not bowing. Courses that fail to adapt to the culture of their learners present a barrier for understanding and are less engaging.
Regional differences
Say you’re an association member who was born and raised in Egypt. You’re taking a course and two characters have this exchange:

Thomas: This deal is going south. We need to pull the plug.
Sandra: My back-of-the-napkin math says we don’t.

This course is clearly written for North Americans, and you feel disconnected. Regional differences extend beyond casual phrases—available resources, currency, and modes of transportation can all be impacted by region.
Time zones
Let’s say your association is located in the Eastern Time Zone in the United States. If you host a live training session at 4 pm, members located in the same time zone will be able to participate fairly easily. Your London-based members, however, will need to stay up until 9 pm to participate, Beijing-based members will be tuning in at 4 am—you get the idea. Learners shouldn’t need to be night owls or early birds to take a course.

These obstacles don’t mean it’s impossible to create effective e-learning courses for your association’s global audience.

It just means that you, along with any e-learning content development partners you work with, need to effectively translate and localize content you create to remove these barriers to understanding.

Let’s explore this more in the next section.

So, you want to use translated and localized e-learning courses. What does that really mean?

What do we mean by translate and localize?

There are some misconceptions about translating e-learning courses for global audiences—the main one being that the process is as simple as copying and pasting your course into a translation service and calling it a day.

When you add localization to the e-learning translation equation, you adjust the course to represent the target culture as well. This means factoring in aspects such as the following:

Dialects
For example, the French spoken in France is much different than the French spoken in Cameroon.
Idioms, metaphors, and similes
While an English speaker might understand what “cold turkey” means, translating the phrase literally into other languages doesn’t work.
Narrators and accents
If your narrators have US American accents but provide instruction in other languages, there will be a disconnect.
Culture
This includes the visuals shown throughout the course, speaking and nonspeaking characters included, and the cultural norms assumed (like the bowing already mentioned).

Adapting your courses for language and culture has benefits beyond making the course more relatable and accessible for global learners. It shows your association is committed to your diversity, equity, and inclusion (DEI) efforts and providing a diverse and equitable learning experience to all.

How can you create effective e-learning for global learners?

Let’s walk through an example course to demonstrate how you can create effective e-learning for global learners. At Artisan E-Learning, we were tasked with creating a course for JLG Industries that provided technical training in several languages.

We translated the course into the target languages, which included non-Western languages such as Japanese. Because the course itself focused on technical training to help learners understand how to operate large machinery, the visuals were fairly similar regardless of the region or culture they were shown in. But remember—that doesn’t mean we can just translate the text and call it a day!

Here are a few additional steps we took to make sure this course was useful for all learners:

Used visual and interactive elements
We used synchronized animations, sliders, and motion paths to solidify the concepts and supplement the translated copy. If the text translation didn’t make sense to the global learner, the visual provided clarification.

Prioritized mobile-friendliness
Learners could access the content regardless of where they were located or what their office set-up was like—a desktop computer in an office or a makeshift workspace on a train.
Empowered global learners to practice concepts in the course
With drag-and-drop elements and simulations, global learners could practice the skills in JLG’s translated course before incorporating them into their day-to-day lives.

Earlier in this piece, we discussed how translating courses involves adjusting not just the language but the cultural aspects as well. The JLG course shows that the structure and format of the course can also create a more effective course for a global and remote audience.

Effectively training a global audience requires more than copying and pasting the text from your courses into a translation service. While translation is an important part of the process, it’s just one step in creating an effective e-learning course across languages.

Language, culture, and format all play a role in creating effective training for a global audience. We recommend keeping all these elements in mind when adjusting your courses and, even better, working with an e-learning content development team to make sure none of these aspects fall to the wayside.

About the Author

Amy Morrisey is the president of Artisan E-Learning and serves as sales & marketing manager. Amy started with Artisan as a contract writer/instructional designer. She was our production manager for four years and helped the team to double its capacity. As president, she stays focused on maintaining the high standards our clients have grown to expect. She believes that staying close to our clients, our people, and our work is a smart way to do that. One of her favorite things to do in the e-learning world is jump in with a client to write a storyboard that is creative and application-based. Before working with Artisan, Amy spent 17 years in corporate training and development, predominantly teaching leadership development and coaching teams and executives. She currently serves on the board of ATD Detroit.

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3 Tips to Empower Member Organizations with E-learning

Guest Contributor — Thu, 03 Jun 2021 14:12:05 +0000

by Amber Winter of Web Courseworks

Trade associations need to provide experiences that are valuable for both their member organizations as a whole and the individual learners that are part of those organizations. It’s easy to see why trade associations face challenges such as high administrative cost, struggles to increase membership, and low non-dues revenue.

It’s your association’s responsibility to lead your member organizations with e-learning that prepares them for the future of your industry. But how can you use your e-learning programming to truly set member organizations up for success?

At Web Courseworks, we specialize in software solutions for professional, healthcare, and trade associations. Drawing on our experience helping trade associations elevate their learning businesses, we’ve outlined the following three tips to help you set member organizations up for success with e-learning:

Invest in an intuitive LMS made for extended enterprises.
Make purchasing courses an easy decision for institutions.
Work with an e-learning consultant to map a path for growth.

Whether you work at a trade association, a nonprofit with regional membership groups or chapters, or a corporation working with many partners, there are unique challenges with providing training for member organizations versus individual learners.

Let’s discuss what you can do as a learning business to overcome them and set your team and member organizations up for success.

1. Invest in an intuitive LMS made for extended enterprises.

Overcoming the challenges that come with implementing an e-learning program for your member organizations can be tough if you don’t have the right tools. If you’re facing major hurdles delivering your e-learning program, it may be a good time to upgrade and invest in an extended enterprise learning management system (LMS).

Upgrade your LMS, and minimize your team’s administrative burden with key features and functionalities:

Co-branded sub-portals
With individual member portals, you can brand each portal and provide a unique experience for each member organization. You can segment reporting to understand performance and participation across your organization as a whole as well as within each individual member organization. Further, you can maintain the privacy of each organization and automate your reports for simplified data analysis.
Intuitive navigation
When your LMS is easy to navigate, it saves your team time and energy that they can then dedicate to what really matters: providing a superior experience for member organizations. Designed with your members in mind, a learning management system’s responsive design can ensure the best and most engaging learning experiences for all, regardless of the device used.
Built-in features for virtual events
While you can invest in a separate virtual conference platform, some LMSes can function as an e-learning and virtual event solution. This means you only need to invest in and manage one solution as you continue hosting virtual and hybrid events in the future.
Built-in marketing and advertising
This includes the ability to promote upcoming events and e-learning opportunities, upsell courses with additional offerings like downloadable resources, and cross-sell products by allowing members to compare courses, all from directly in your LMS.
Integrations with your other software solutions
According to the team at Fonteva, the ideal association management software can host member profiles, reports, accounting tools, and other features that are essential for daily operations. If you choose an LMS that can integrate directly with your AMS, the data in your LMS will be included in your main database’s reports. This allows you to see a full picture of member activity and make informed decisions about the future of your learning business.

An enterprise LMS with these capabilities will reduce the time and energy that your LMS administrator needs to dedicate to ensuring the system runs smoothly. This will benefit your staff, member organizations, and the individual members navigating it.

2. Make purchasing courses an easy decision for member organizations.

When it comes to increasing membership and non-dues revenue, there are a few steps that you can take to increase the value perception of your materials and make investing in your learning business an easy decision for member organizations:

Empower learners to submit their own external learning.
In your LMS, allow learners to track credits earned in your system and outside of it. When they’re able to create a comprehensive portfolio of achievements, individuals in your member organizations will be incentivized to continue engaging. The impact of this will be that member organizations will increase their investment in your programming.
Provide course recommendations and learning paths.
Pay attention to the courses that individual member organizations invest in, and provide recommendations for similar courses they may be interested in. For example, let’s say a member organization registered members for basic sales training courses. You could then recommend courses on cold calling and outreach.
Enable bulk purchasing and registrations.
With this, leaders at your member organizations can purchase course seats and register multiple individuals at once. This type of pay-per-user e-learning pricing model removes much of the administrative burden from your member organizations and makes it incredibly easy for them to invest in your courses.

Benefits like these make investing in e-learning convenient and can help point your member organizations in the right direction when it comes to identifying the courses they should invest in. The ability to provide these benefits will depend on the LMS you use to deliver e-learning programming to member organizations.

3. Work with an e-learning consultant to map a path for growth.

Administering e-learning to member organizations can mean providing courses for large numbers of individuals. That means the needs of your e-learning program may outpace the capacity or expertise of your team.

In that instance, it’s helpful to partner with an e-learning consultant to formulate a strategy to elevate your programming. This graphic, pulled from Web Courseworks’ guide to e-learning consultants, highlights some of the services a consultant may provide:

As indicated by that graphic, an experienced e-learning consultant brings many attributes to the table. Let’s take a slightly deeper look at each of those common services. An e-learning consultant may be able to help with some or all of the following:

Formulating a strategy for growing your learning business and guiding your team through carrying out that strategy
Sourcing the ideal learning technology to meet your needs, whether a learning management system, course authoring tools, or something else
Creating a content development strategy, from researching the courses that would best appeal to your members to managing subject matter experts (SMEs) during the authoring process
Converting your existing materials into a new format, such as revising courses that used Adobe Flash elements (the Flash Player reached end of life in 2020) or preparing live training materials like recorded lectures into digital formats
Administering your LMS, including troubleshooting any tech challenges that arise and assisting end users who call with questions about how to access their training
Measuring the efficacy of your e-learning program, generating reports, conducting analysis to understand areas of improvement, and making data-driven decisions
Planning virtual or hybrid events from the ground up or transitioning in-person events to the digital space using virtual conference software

The idea is that e-learning consultants provide solutions tailored to your organization’s exact needs—so, if you’re struggling with one of these challenges, they can formulate a roadmap to help you surpass it.

When choosing a consultant, it’s crucial to choose the right one for your organization. To do that, ask yourself the following:

Is the consultant a good personality fit for my team?
Does the consultant have experience in the industry that my association operates in?
Can the consultant provide examples of past work, and are those examples proving success?

These questions will help you choose a consultant who will be an effective partner to surpass the obstacles in your path now and formulate a path for growth well into the future. Whether decreasing administrative burden, increasing membership, or raising non-dues revenue, a consultant can build out your e-learning strategy.

Setting member organizations up for success in the future using your association’s e-learning programming can be a challenge—but not one that you can’t overcome.

To recap, upgrading your current LMS to a more intuitive system that’s made for extended enterprises will drastically decrease the administrative burden on your team and create a more pleasant experience for members navigating it.

Further, increasing the perceived value of your e-learning programming will make the choice to purchase courses an easy one. This can have a direct impact on the amount of non-dues revenue your learning business generates.

And, last but not least, working with the right e-learning consultant can help your team choose technology, implement it seamlessly, overcome any unforeseen obstacles, quickly pivot to a new strategy, and more.

With these tips, you’ll be off to a great start when it comes to setting your member organizations up for success with your learning programs.

About the Author

Amber Winter is the director of Sales & Marketing at Web Courseworks. She’s committed to helping association executives realize the potential of their education programs and turn them into high-performing revenue generators. Amber was named one of Madison, Wisconsin’s 40 under 40 and the number 1 LMS salesperson by Talented Learning.

The post 3 Tips to Empower Member Organizations with E-learning appeared first on Leading Learning.

Pursuing Learning Culture and Learning Ecosystem

Jeff Cobb — Thu, 27 May 2021 13:11:28 +0000

The terms learning culture (or, alternatively, culture of learning) and learning ecosystem have been relatively trendy in the corporate learning and development world for many years, but our experience has been that they are used much less frequently in the world of learning businesses. We’re seeing some signs that may be changing, and it’s a change that’s needed.

Why?

We’ve made the point before that learning is not an event; it’s a process. But that process is neither linear nor isolated. Even our most clearly defined learning experiences happen in interaction with other people and our environment and are influenced by countless other processes that may be unfolding on our lives.

And, of course, most of our learning experiences are not clearly defined. They emerge organically from the sum of our day-to-day experiences.

Most of the focus of learning businesses historically has been on what might be described as “point in time” solutions – classes, courses, conference sessions that are mere blips on the overall context of a learner’s life and career. Blips that appear and fade away quite rapidly, often leaving little, if any, trace behind.

If we’re going really support lifelong learning, if we are going to position ourselves in the career business, rather than the education or events business, if we are, in fact, going to lead learning in the fields and industries we serve, then we must understand and address each learner’s need in context, over time. And we must understand that we have some ability to not just to react to context, but also to influence and shape it.

As our series on the frontiers of learntech made clear, technology has opened new possibilities for serving learners in this way. The sheer increase in our ability to reach and connect with learners has changed the learning landscape permanently, and the emergence of artificial intelligence and possibilities for personalization will also leave an indelible mark.

But simply implementing better technology isn’t going to carry us into the future of learning. The key is in our relationships with and to our learners – and learning culture and learning ecosystem are at the heart of those relationships.

Let’s take a closer look at each.

What is a Learning Culture?

Culture, broadly speaking, may be defined as a cohesive, integrated, and persistent pattern of knowledge, belief, and behavior exhibited by a group of human beings.

Learning may be defined as “the lifelong process of transforming information and experience into knowledge, skills, behaviors, and attitudes.”

Learning is the the lifelong process of transforming information and experience into knowledge, skills, behaviors, and attitudes
Mission to Learn

Combining the two definitions, a learning culture is one in which the process of learning drives the pattern of culture. Learning is among the highest values of the group of people involved, and learning, because it inherently leads to change, enables and drives the evolution of the culture.

Put somewhat differently, a learning culture is a culture that clearly values and prioritizes learning, rewards the pursuit of learning, and is therefore able to change, adapt, and evolve as circumstances require.

For learning business, this culture is not confined to a single organization, but rather extends out to the broader community, field, or industry the business services. (That said, as prerequisite to supporting the broader culture, the business should have a strong internal learning culture. Modeling the desired outcomes is crucial, and it is difficult to model what you have not fully appreciated and integrated into your own practices.)

Dynamics of Learning Culture

It is important to recognize that while education and training can be important elements of a learning culture, there is nothing about “learning culture” per se that requires formal education and training experiences. Living itself is learning. Participants in a learning culture recognize this equivalence, whether consciously or not, and this recognition shapes their mindset with respect to both life and learning.

Too much of a focus on training and education can actually impede a learning culture if training and education experiences – and, typically, the credit associated with them – evolve to act as a proxy for true learning. Simply putting in the time or “checking the box” for a formal, structured educational activity may be perceived as learning when, in reality, little is gained from the experience, whether because it is not truly relevant to the learner, the learner is not motivated, or myriad other reasons.

Finally, a true learning culture is never fixed or static; it is emergent, representing the continuing accumulation of interactions within the culture – i.e., the patterns. Because this is the case, learning culture cannot be prescribed, it can only be influenced and fostered. Equally important, learning culture, by its very nature, requires social interaction and community. Those seeking to influence and foster a learning community must be meaningful participants in these interactions and community wherever they arise.

What is a Learning Ecosystem?

An ecosystem in nature is a community of living beings interacting with each other and their environment. When healthy, it is characterized by balance and an innate understanding that no single part of the system is more important than another and that changes in one part of the ecosystem may impact multiple other parts of the ecosystem directly or indirectly.

Ecosystem is an apt metaphor to apply to learning given that learning is also fundamentally about interactions among human beings and between human beings and their environment or context. We have the ability to shape and influence a learning ecosystem through decisions about the people involved, the substance of the learning experiences offered, and the tools and technologies used to support and connect the two. From this perspective, a learning ecosystem is comprised of people, content, technology, and the processes and strategies that unite them.

The whole of a learning ecosystem, however, is greater than the sum of its parts. Learning culture emerges from a learning ecosystem while simultaneously influencing and impacting the ecosystem. Just as culture is dynamic and evolving, the ecosystem, too, is dynamic and evolving. The two concepts are inseparable from each other: two side of the same coin or, borrowing from the poet William Butler Yeats, as hard to distinguish as the dancer and the dance.

O body swayed to music, O brightening glance,
How can we know the dancer from the dance?
William Butler Years, Among School Children

That said, while firm control of culture and ecosystem is impossible, decisions made about an ecosystem – the components, the processes, the strategy – do impact its health and, by extension, the health and efficacy of the learning culture. As in nature, too much of an emphasis on any one factor – a delivery method or approach to learning, for example – may negatively impact the whole. Learning ecosystem decisions should always be made with the desired outcomes – including the desired learning culture – in mind.

A learning ecosystem is comprised of people, content, technology, and the processes and strategies that unite them. Download this image as a PDF.

Start With a Shift In Mindset

Of course, very few learning businesses start from a blank slate with respect to either ecosystem or culture. There are already elements of each in place, both within the business and within the broader community, field, or industry it serves. The challenge and the opportunity are to make the effort to assess current culture and ecosystem, to establish a vision for the future state of culture and ecosystem, and consciously set about the work of influencing each in a positive direction, one that will elevate the range, relevance, and quality of learning experiences available to each individual learner.

For most learning businesses, this will require a significant shift in mindset across the stakeholder base – often meaning not only staff, board members, and volunteers (where relevant), but also learners themselves. In the world of adult lifelong learning, we tend to be very validation-centric, viewing primarily those experiences associated with continuing education, certification, and other forms of “credit” as valid learning experiences. This bias is usually unconscious, but it confuses education and learning to the detriment of learning.

As an initial step toward prioritizing learning ecosystem and learning culture, the bias needs to be made conscious – again, across the stakeholder base – and organizations need to make a much more conscious effort to support less formal opportunities as well as opportunities that are not “one size fits all” as so many continuing education and professional development opportunities essentially are currently.

None of this is to say that there is not a place for traditional formal approaches. Rather, it is a call for a significant shift in emphasis and a recognition that, while formal education certainly can and should play a key role in supporting a learning culture, excessive focus on it can make it difficult to realize the potential of other, less formal elements as well as to personalize experiences to the needs of individual learners.

For most organizations, gathering the right group of people – usually a combination of staff, key volunteers (if relevant), and some representative learners – and asking the question, “How else – beyond what we have traditionally done – could we foster and support learning for the people we serve?” is a simple, but powerful first step toward shifting mindset and identifying the opportunities that a focus on learning ecosystem and learning culture represent.

How else – beyond what we have traditionally done – could we foster and support learning for the people we serve?

If you are interested in successfully navigating and leading the future of learning in your community, field, or industry, it’s a gathering I highly encourage you to start scheduling today.

The post Pursuing Learning Culture and Learning Ecosystem appeared first on Leading Learning.

Making Learntech’s Promise Real

Jackie Harman — Tue, 18 May 2021 12:45:59 +0000

Jeff Cobb and Celisa Steele

As we close out our seven-part series on the frontiers of learntech, we want to help you make sense of what the wide-ranging topics that emerged mean for the future of your learning business.

Through the interviews with Ashish Rangnekar, Sam Sannandeji, Sae Schatz, and Donald Clark and our own reflective episodes, we’ve had the chance to touch on many different aspects of learntech. We covered everything from specific types of learntech, to the growing importance of data, the increasing need for organizations to have an integrated learning ecosystem in place, the essential role of standards in making such an ecosystem work, and, at long last, truly delivering on the promise of personalized learning.

We also explored related philosophical and ethical concerns such as the accelerating pace of change, equity in access to learning technology, and the potential bias in the data and design of technologies.

In this final episode in the series, we offer five suggested actions for how to make the promise of the frontiers of learntech a reality for your learning business: develop a data strategy, grow a learning ecosystem, conduct a feasibility study for extended reality, build a governance structure, and regularly reassess which learntech holds the most promise.

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[00:32] – An overview of the first six episodes in our series on the frontiers of learntech:

The Challenge and Overview of Five Suggested Actions

[02:42] – There are incredible technologies being developed, and their promise for the future is huge—more effective learning, more efficient learning, learning that’s more broadly and equitably distributed, learning that responds to a specific learner’s needs in a particular situation at a particular time. Making sure those promises pan out is the challenge. What can a learning business do now to make those promises comes true? That’s what we want to address in this episode.

A lot has to happen to get from here to the frontiers of learntech, where those promises of more equitable, accessible, effective, and personalized learning exist, where they are well-executed realities rather than just possibilities. To help with the journey, we’ll offer five suggested actions.

The suggested actions are numbered, but the order isn’t important—these aren’t sequential—and you might not pursue all five actions or all five at once. These are the kinds of actions that might make it into your roadmap for how to make the promise of the frontiers of learntech a reality for your learning business.

1. Develop a Data Strategy

[04:20] – When we asked interviewees for their advice for learning businesses trying to figure out what to do with learntech, what to invest in, what to focus limited time and other resources on, data came up again and again.

When Donald and Sae answered that question, they mentioned data, as did both Celeste Martinell and Joe Miller, VP of customer success and VP of learning design and strategy at BenchPrep, respectively.

Celeste recommends focusing on the richness of the data that you’ll get from your learntech partner or partners. Joe stresses the importance of having a vision and how data as part of an overall approach helps you move from vision to roadmap. Both Celeste and Joe get at some of the areas and key questions you’ll want your data strategy to address, including what data you have and what insights that data can yield.

[08:00] – A good data strategy will:

Account for all four of the levels of data use that Donald Clark describes in Artificial Intelligence for Learning: describe, analyze, predict, prescribe. The strategy should describe what data you have from what sources, but you have to analyze that data, and then be clear about what you’re trying to use the data to predict and prescribe. The strategy part of a data strategy is about using data to help your learning business meet its goals.
Address questions you’re trying to answer, based on what’s strategically important for your learning business. Part of using the data to meet your goals will be about formulating the questions you want your data to help you answer.
Think throughout your organization, not just your learntech data as you document your data sources. For a fuller picture of your learners, you’ll want to marry data from your learning management system with data from your association management system or customer relationship database and other sources.
Think outside your organization. There are likely data sources that you don’t own but that can give you insight into learners and prospective learners. For example, the Bureau of Labor Statistics and the Bureau of the Census. There are also thinktanks and nonprofits that conduct original research and make it freely available—Georgetown University’s Center on Education and the Workforce and the Pew Research Center, for example. There are also likely data sources specific to the industry, profession, or field you serve. Take time to do the legwork to figure out what’s available and how you might be able to layer that broader data with your internal data for an even deeper understanding of the market you serve.
Use marketing as a bellwether for learning. Marketing is strong in the area of mining various data sources and using that to drive conversion.
Include standards in your data strategy. Which standards are you following now? Which standards should you use? The more consistent and uniform your data, the easier it will be to analyze and interpret. The importance of data standards was a key takeaway from our conversation with Sae. Competencies and frameworks can also be part of thinking about standards. If you have data you can tag and track against a competency framework, that’s likely to also help you track and interpret data about what your learners need, what they’re accessing, and where they’re struggling.

[13:02] – If you’re looking for a learntech partner to play a meaningful role in your data strategy, check out our sponsor for this series.

BenchPrep is a pioneer in the modern learning space, digitally transforming professional learning for corporations, credentialing bodies, associations, and training companies for over a decade. With an award-winning, learner-centric, cloud-based platform, BenchPrep enables learning organizations to deliver the best digital experience to drive learning outcomes and increase revenue.

The platform’s omni channel delivery incorporates personalized learning pathways, robust instructional design principles, gamification, and near real-time analytics that allow organizations across all industries to achieve their goals. More than 6 million learners have used BenchPrep’s platform to attain academic and professional success. BenchPrep publishes regular content sharing the latest in e-learning trends.

To download BenchPrep’s latest e-books, case studies, white papers, and more go to www.benchprep.com/resources.

2. Grow a Learning Ecosystem

[14:18] – Learning ecosystems came up in our conversation with Sae, as well as standards and competencies. Sae co-edited ADL’s e-book Modernizing Learning: Building the Future Learning Ecosystem, and the first chapter offers a definition of learning ecosystem:

We use the phrase ‘future learning ecosystem’ to describe this new tapestry of learning. At the highest level, the future learning ecosystem reflects a transformation—away from disconnected, episodic experiences and towards a curated continuum of lifelong learning, tailored to individuals, and delivered across diverse locations, media, and periods of time. Improved measures and analyses help optimize this system-of-systems and drive continuous adaptation and optimization across it. Its technological foundation is an ‘internet for learning’ that not only allows ubiquitous access to learning, it also provides pathways for optimizing individual and workforce development at an unprecedented pace.
excerpt from Modernizing Learning, co-edited by Sae Schatz and J.J. Walcutt

A learning ecosystem is aligned with the fact that learning is a process, not an event. Learning is, to use the terms from the ADL e-book, not “disconnected, episodic experiences” but “a curated continuum of lifelong learning, tailored to individuals, and delivered across diverse locations, media, and periods of time.”

We like to think that it’s not just a move away from disconnection but a move towards connection. In nature, an ecosystem is a community—living beings interacting with each other and their environment. When healthy, an ecosystem is balanced. No single part of the system is more important than another, and changes in one part of the ecosystem may impact other parts of the ecosystem.

Learning is fundamentally about interactions among human beings and between human beings and their environment. Learning businesses have the ability to shape and influence a learning ecosystem through decisions about the people involved (the learners, the facilitators, the designers), the content offered (the courses, the publications, the community discussions), and the technologies used to support and connect the people and the content.

In short, a learning ecosystem is comprised of five parts: people, content, technology, and the processes and strategies that unite them. But the whole of a learning ecosystem is greater than the sum of those five parts. Learning culture emerges from a learning ecosystem while simultaneously influencing and impacting the ecosystem. Just as culture is dynamic and evolving, the ecosystem too is dynamic and evolving.

The two concepts are inseparable, two side of the same coin, or, to borrow from William Butler Yeats, as hard to distinguish as the dancer and the dance. Arbitrary or overly simple lines of distinction may do more harm than good. Too much emphasis on any one factor—a delivery method or approach to learning or a particular piece of learntech, for example—may negatively impact the whole.

This reminds us of something Ashish said when we asked him his advice for learning businesses when it comes to choosing learntech. He offered three considerations:

What’s your goal?
What are the changes/triggers driving the goal?
What is the solution? What is the learntech that will help you with your goal?

He’s making sure the tools and technologies don’t get overemphasized and recognizes that learntech are just one part of a learning ecosystem.

3. Conduct a Feasibility Study for XR

[19:16] – This is a little narrower in focus than the first two actions we’ve mentioned. Keep in mind that all five suggested actions aren’t necessarily for every organization or for every organization to pursue now. We feel that given the potential for extended reality—whether augmented or virtual or mixed—to make a training or learning environment more closely match the real-world contexts in which learners need to apply knowledge and skills, it’s worth learning businesses getting clearer on what would be involved.

We’re not suggesting you go build XR, not even a prototype. This is a pre-prototype phase, where you look at what would be involved, do a cost-benefit analysis, and try to understand the potential return on investment, the features needed or desired, which type of XR might fit best, and what tools and technology investments would be needed.

A feasibility study approach is in keeping with Sam’s advice on AR and VR. He made a point of saying a side-project, skunk-works prototype often doesn’t give an organization a good entrée into XR. Often it’s more helpful to go in, eyes open, with a goal in mind for the use of XR and a feasibility study backing up trying out XR.

Or a feasibility study that shows that XR doesn’t make sense, at least at this point. Even if the outcome of a feasibility study is to not pursue XR now, the work done to put together the assumptions about costs, value, development time, and uses can likely be updated and revisited, plugging in new numbers, so you can periodically reassess the validity of XR, VR, or AR. The feasibility study route will also help organizations avoid getting sidetracked by the flashy, latest shiny thing, which Sam also warned against.

It would also be helpful if organizations keep the SAMR Model—a framework created by Dr. Ruben Puentedura that categorizes four different degrees of technology integration in learning experiences—in mind (as referenced in our conversation with Sae).

SAMR Model (image from from schoology.com)

It seems likely, though not necessarily always true, that to justify the time and cost of an XR solution for a training problem or a learning situation, you’re going to want to get into the transformation phases of SAMR. You’re likely going to want to consider modification or redefinition in your XR feasibility study, so that it’s not a cut and paste from how you’re doing things currently, but an exploration of what you might be able to help learners with that you can’t currently.

4. Build a Governance Structure

[24:03] – Your learning business needs some people to be thinking about learntech, not only from a technical standpoint, but also with the goal of understanding the implications of the technologies.

Those implications will run the gamut from budgetary considerations—what will building and maintaining a learntech stack cost?—to ethical and philosophical decisions around learners’ privacy and rights when it comes to what personal data is collected and how it’s used. It might also touch on issues of potential bias in the use of artificial intelligence and other automated technologies.

A governance structure could be charged with determining when interpretability and when explainability is needed around your learning business’s use of AI, machine learning, and other tech automation. We give credit to Christopher Penn of Marketing Over Coffee for the explainability versus interpretability tradeoff, which we talked about in episode 268, but, as a reminder, interpretability is the decompilation of a technology into its source code.

To use an analogy, interpretability is looking over the recipe and verifying the ingredients. Explainability is like tasting the cake rather than looking over the cake recipe. You’ll know how it tastes, and you can probably figure out most of the ingredients. Tasting is a faster, easier, less expensive way to verify the results—but it’s not as rigorous or complete as interpretability. When stakes are low, explainability (just tasting the cake) is often adequate. When stakes are higher, interpretability (reviewing the recipe) may be needed. The time and expense may be justified in that case.

If you have a governance structure in place, you have a group who can debate the tradeoffs and ultimately make decisions about things like when interpretability is needed versus just explainability. Think in advance about the implications of your learntech so you’re better equipped to deal with any issues that arise.

A governance structure could also be involved in considering which standards for data and technology a learning business should adopt and use and what the implications for that might be.

5. Regularly Reassess Which Learntech Holds the Most Promise

[27:11] – We return to a question we asked in the first episode of this series.

Out of what’s on the frontiers of learntech, what holds the most promise for significant positive impact on your learners and your learning business in the near future? Ask that question now. And ask it again next month. And three months out, and six months, and a year from now. Regularly check in on the frontiers of learntech so you can use learning technology effectively to grow the reach, revenue, and impact of your learning business.
Celisa Steele

When we spoke with Ashish, he said we’re in the second inning of a nine-inning ballgame. So there’s lots more to come—plenty of time for more developments and innovations. We need to regularly check in on our understanding of what’s coming.

When we talked with Joe, he recommended looking at how other industries are using technology to see the potential for learntech. Keep an eye on fintech, retail tech, and martech. Look for inspiration outside the learning space.

As you look at what others are doing with tech and as you engage and re-engage with the question of what holds the most promise for your learners and your learning business, your answer will likely suggest additional actions for you to take, beyond the five suggested here. And, if you do anything of the things we suggest, you will, over time, establish a good foundation to refer to when checking back in on this question—the data will help, feasibility studies will help, having governance in place will help, as will having a learning culture and growing a learning ecosystem.

[30:16] – Wrap-up

This is the last episode in the seven-part series on the frontiers of learntech. We hope you’ve enjoyed the series, and we’d love to hear your feedback and suggestions for the future. You can leave a comment below or e-mail us at leadinglearning@tagoras.com.

We’ll resume releasing episodes of the Leading Learning Podcast with a new series starting in July 2021.

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Personal recommendations are critical in today’s noisy world, so please take a minute to rate the Leading Learning Podcast on Apple Podcasts. We personally appreciate your rating and review, but more importantly reviews and ratings play a big role in helping the podcast show up when people search for content on leading a learning business.

We encourage you to learn more about the sponsor for this series by visiting benchprep.com/resources.

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[33:06] – Sign-off

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Digital Transformation with Ashish Rangnekar

Jackie Harman — Tue, 11 May 2021 11:21:01 +0000

Ashish Rangnekar

Ashish Rangnekar, a self-described lifelong learner, is co-founder and CEO of BenchPrep, where he’s focused on helping organizations digitally transform their learning offerings in the new digital world order. BenchPrep elevates and empowers learning businesses through their full-stack learning platform, aimed at delivering the best digital experience to drive outcomes and increase revenue.

In this penultimate episode in our series on the frontiers of learning technology, Jeff talks with Ashish about why the learntech market is slated to experience unprecedented growth and transformation, related trends, and potential implications for learning businesses and society.

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[00:36] – Intro and background info about Ashish.

A Transformative Time for Learntech

[01:44] – There’s a lot of investor interest in learntech right now. What’s different now compared to past surges in learntech investment? What’s the opportunity that investors see now, especially in the adult lifelong learning market?

This is an amazing and transformative time for learning technology companies and the entire industry. Music streaming has seen tremendous growth in the past ten years (from less than 5 percent of music revenue to more than 80 percent today). The education and training industry will see a similar trend, with more and more moving to digital delivery.

Three macro shifts happened in society, leading to this enormous potential for growth in learntech:

The Fourth Industrial Revolution has brought massive transformation to society, driven by technology, and fundamentally changed the way we live, work and relate to one another. As this revolution unfolds, every professional, irrespective of the industry, and every organization will have to retrain how they work and operate.
Lifelong learning has become an economic reality. Because of the Fourth Industrial Revolution change we are seeing, companies like Amazon and AT&T are spending more than a billion dollars on upskilling and reskilling. So much learning is happening beyond the traditional degree programs and higher ed with a focus on lifelong learning.
We have entered an era of digital-first, digital-all, digital-only learning.

Seventy percent of learning happens on the job (experiential). Twenty percent is peer-to-peer. Ten percent is formal. What we have seen in the last couple of decades is most of the digital or the technology was focused on that ten percent of formal educational programs. Finally, we’re seeing that digital is driving all of it—not just formal, but social and experiential as well. And that shift has opened up the market 10X.
Ashish Rangnekar

All these things were already happening, but the pandemic accelerated everything by at least five years. The potential in the next ten years is once in a lifetime, so it’s not surprising there’s been a lot of investor interest.

The Frontiers of Learning Technology

[07:11] – When you think about the phrase “frontiers of learning technology” what comes to mind?

Ashish thinks of Andy Grove, ex-CEO of Intel and author of Only the Paranoid Survive: How to Exploit the Crisis Points That Challenge Every Company, and his 10X change concept. It’s a moment that signifies change so big, that all bets are off. The frontiers of learntech are the technologies, concepts, business models, and organizations that are leading a 10X change.

Image source: https://thekeypoint.org

The Near Future of Learntech

[08:26] – Which trends in learntech have the most potential for significant positive impact in the next three years or so?

Data is an area where we’ve only started to scratch the surface and that can drive 10X change.

Our collective ability to leverage data, I think, can truly transform our ability to drive learning and business outcomes. And not just there. I think if we leverage, collect, analyze, and deploy the right data models, it can bring equity and access to learning like never, never before.
Ashish Rangnekar

As things go digital, it’s easier to collect data. It has become cheap to collect and store data over the last ten years. The technology has made it possible to truly collect and store every click and response for every single learning activity.

We are still in the first phase of a transformation where everyone is focused on data collection, and we need to quickly get into the second phase of deploying insights gleaned from the data back into the learning models. As we start doing that, it’s going to become cheaper to create content, we’ll be able to drive learning outcomes more quickly, and we’ll be able to innovate faster because we will know exactly where to innovate.

Many technology developments are happening in artificial intelligence (AI), machine learning, and data storage, and those developments will have a massive impact in the next three years.

Over-Hyped Trends in Learntech

[11:10] – Which trend or trends in learntech do you think might be over-hyped, shiny objects distracting us from what really matters?

Ashish thinks that many of these technologies, which others may consider hype, are just a matter of prioritization and time. Organizations need to understand if they are ready for a particular technology or not. Whether something is a shiny object and a distraction depends on the specific learning organization and their goals.

Gartner’s Hype Cycle looks at where specific technologies (personalization, AI, machine learning, immersive technology, virtual events, etc.) are in the cycle of commercialization. The cycle covers five main phases (e.g., the peak of inflated expectations or the slope of enlightenment), and Ashish makes the point that how valuable (or not) a technology is depends a lot on the specific learning business and what its needs are.

Image source: https://www.gartner.com

The Near Future of Learntech

[14:06] – How would you characterize learntech in the near future? Is there going to be disruptive innovation, incremental innovation, or something else?

When it comes to innovation and change, we overestimate the time that it takes for true disruption, and we underestimate the time it takes for something that is next to us. Ashish is betting on net-net overall disruptive innovation—something he wouldn’t have thought pre-pandemic. However, the disruptive innovation will happen through step change.

Many learning businesses fully understand they are going to have to make big changes in their learning technology stack, the way they operate, and even their business models. However, in some cases, the technology itself hasn’t fully caught up, and that commercialization is going to take time. An example is video conferencing. We haven’t seen true innovation at scale in video conferencing yet, but, during the pandemic, everyone moved online, and that level of scale and commercialization is going to yield innovation over the coming 18 to 24 months.

The More Distant Future of Learntech

[17:28] – What might learntech look like in the more distant future?

The impact of learning and learning outcomes are very important. Ashish would like to see more of a focus on impact and outcomes than the learning process. He’d also like to see more innovation around peer-to-peer social learning. Social learning is an area where technology can make a big difference in the way we learn from each other.

Learning at the core is a very social activity. We learn way more from each other—talking to each other, watching each other—than anything else…. But I don’t think it has reached the scale that it needs to in the digital world.
Ashish Rangnekar

Social learning is decentralized, in small bits and pieces and in multiple computing sites. Rather than being tethered to one particular instructor, provider, or course, Ashish hopes to see continued decentralization, where we learn from every single interaction in every facet our lives.

Sponsor: BenchPrep

[20:45] – If you’re looking for a partner to help with your organization’s digital transformation, check out BenchPrep, our sponsor for this series.

To download BenchPrep’s latest e-books, case studies, white papers, and more go to www.benchprep.com/resources.

Getting Learntech Right

[22:07] – If we get learning technology right as society, what’s the good that we might see?

At the highest level, if we get it right, we truly elevate human potential. Ashish admits that’s a philosophical perspective, but it is the impact of learning and training, as he sees it.

I truly believe that every human wants to learn and do better in life. And learning is an enabler towards that. People learn, people go through training so that they can get a better job. They want a better job so that they can maybe potentially earn better, take care of their family. And all of this starts with actually helping them in their learning outcomes…. Technology, which is a true enabler of that, can make the difference. So that’s what’s at stake. We can truly elevate human potential and have an impact at a macro scale if we can get learning technology right.
Ashish Rangnekar

Getting Learntech Wrong

[25:01] – If we get it wrong, what are the dangers that learning technology might bring?

Ashish sees three areas of concern in getting learntech wrong:

Allowing the power of AI and data to lead us in a direction we don’t want to go
The enormous consolidation of power (which we’ve already seen with companies like Facebook, Google, and Amazon)
Society and learning businesses becoming pessimistic about the impact and slow to adopt learntech

If organizations are not diligent about how to leverage and deploy learning technology—or if they do it in a suboptimal way—then we’ll see suboptimal or unintended results. We could leave hundreds of millions of people behind because learning technology couldn’t scale to provide them with the equity and access. And that would lead to whole new set of economic and social problems.

Advice for Learning Businesses

[28:28] – What advice do you have for a learning business looking to effectively use learning technology and trying to decide what to focus on and invest in?

Associations and learning businesses are at a critical point, with a lot of opportunity ahead. This transformation is only beginning, so learning businesses need to think long term.

Ashish offers three major considerations for learning executives to think through related to the effective use of learntech:

Identify your goal. Are you trying to optimize what you have or trying to digitally transform? Those are two different goals, leading to different processes and outcomes. Thinking long term, learning businesses have to go through this digital transformation, and sooner is better than later. Technology companies have to transform every five years.
Identify the triggers by understanding the 10X changes around you. What is happening around your learning business that is driving change? This is where the 10X moment comes in. A learning business might want to transform, but it’s not just an inside-out transformation; it’s also outside-in.
When it comes to the solution, it’s not about one tool or platform; it’s about a technology stack. Platform providers and vendors are part of a solution—they are the enablers, but not the solution. Start with the entire technology stack, and work backwards to figure out what learning platform, learning technology, vendor, learning management system, etc.

[33:45] – Wrap-up

Ashish Rangnekar is co-founder and CEO of BenchPrep. BenchPrep offers a learning operating system—a full-stack learning platform that organizations can use to build and grow their learning business. Ashish is passionate about learning and would be happy to talk lifelong learning, professional development, learning technology, and anything in between with podcast listeners.

We’d also appreciate if you give us a rating on Apple Podcasts by going to https://www.leadinglearning.com/apple. We personally appreciate your rating and review, but more importantly reviews and ratings play a big role in helping the podcast show up when people search for content on leading a learning business.

We encourage you to learn more about the sponsor for this series by visiting benchprep.com/resources.

Finally, consider following us and sharing the good word about Leading Learning. You can find us on Twitter, Facebook, and LinkedIn.

[35:28] – Sign-off

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6 Instructional Design Approaches to Capitalize on in 2021

Guest Contributor — Thu, 06 May 2021 12:26:26 +0000

by Salma Torres of Skyepack

For continuing education, professional development, and lifelong learning providers, it’s vital to consider not only the content of educational courses but also the way in which material is presented. Effective, thoughtful instructional design prioritizes the learner at every step to maximize value from your offerings.

The COVID-19 pandemic threw a wrench in many learning businesses’ operations and activities, forcing offerings to shift to the virtual sph ere. Organizations have had to quickly adapt to the virtual learning environment if they hadn’t already. During such a chaotic time, returning to well-researched, effective instructional design approaches can maximize the effectiveness of your offerings.

At Skyepack, we know how important instructional design is. As we’ve designed custom digital courses over the years, we’ve learned some of the most effective instructional design approaches that any association, training company, or other learning business can implement. In this guide, we’ll discuss six approaches:

Content curation
Microlearning
Personalized learning
Video
Mobile learning
Measurement and analytics

With these tried and true ways to convey information and skills to learners, you’ll provide effective, engaging, and powerful learning experiences. Let’s dive in.

1. Content Curation

Providing engaging content to the learners your serve can be tough. One way to ensure you’re prioritizing the learner from the very beginning is by curating your own custom courses.

Every learning business is different, and your learners have their own unique needs. To best meet those needs and provide a customized, comprehensive learning experience, draw information from several sources to compile the best possible course for your audience. Instead of borrowing a training course from another organization or using the same materials your organization has used for years, create your course with materials from:

Open educational resources (OER)
Past curricula
Instructor-created materials

With a curriculum designed particularly for your audience, you’ll be sure to engage your association’s members and other learners.

2. Microlearning

Over the past few decades, there has been increasing competition for our attention—iPhones, tablets, computers, and televisions are ubiquitous, providing instant entertainment at every turn.

With our attention in such high demand, it can be difficult for learners to sit down for hours at a time to digest a self-guided digital course. With this format, learners are not likely to remain engaged and retain all of the valuable information your course has to offer.

There is a research-backed strategy for maximizing information retention and keeping learners engaged: microlearning. Microlearning is an instructional design tactic that involves bite-sized lessons that cover a smaller amount of material than normal lessons or units usually contain.

Research shows that microlearning can make the transfer of knowledge and information 17 percent more efficient than traditional learning and can lead to 50 percent more audience engagement.

The time span of microlearning lessons can vary—they may be as short as a minute (the time it takes to answer a couple of quiz questions) or as long as fifteen minutes or more. Regardless, the learning objective for a microlearning lesson is generally much narrower in scope than a traditional lesson.

3. Personalized Learning

Personalized learning is an instructional design approach that can take more than one form. In general, any strategy that increases the level of customization to a given learner is a way to personalize the learning experience.

As learning technology has advanced, digital learning platforms have made use of artificial intelligence-powered algorithms. Some of these algorithms are capable of customizing content in real time in response to learners’ engagement with a course or examination.

The digital Graduate Record Examinations, or GRE, is one example. The test presents questions based on the test-taker’s past answers, creating an experience tailored to the individual taking the test. Such experiences are commonly referred to as “adaptive” because they adapt based on the learner’s interactions. Depending on the learning management system (LMS) or content delivery platform through which you administer your offerings, adaptive learning options may be possible to implement.

Another, lower-tech way to implement personalized learning is to allow learners to choose how they would like to proceed in a given course. For example, you could provide a list of activity options and ask each learner to select the activities they would like to complete. Personalized learning provides a higher-value learning experience to each member of your audience.

4. Video

With the prevalence of video-supporting technology in 2021, using video in an e-learning scenario is no longer an up-and-coming trend in the development and delivery of online courses but the norm. Video provides a convenient way to deliver large amounts of information in an accessible way by:

Illustrating topics or examples visually
Catering to different types of learners
Providing information in a shorter amount of time

Producing videos for educational purposes is easier and more affordable than ever before. It’s possible to produce high-quality videos with excellent editing, sound, and writing without breaking the bank, making video production a feasible option for your courses. To maximize the impact of this instructional design approach, use a content delivery platform that allows you to embed video directly in your digital course materials, providing learners with periodic breaks from reading.

5. Mobile Learning

As of 2021, 56 percent of all Web traffic comes from users on mobile devices, rather than desktops or laptops. Smartphones are so prevalent—and so capable—these days that many learners appreciate the opportunity to learn directly from their cell phones.

Mobile learning has several key benefits, including:

Convenience. As described in the Web Courseworks guide to association software, a mobile-supported content delivery platform enables your learners to access content from anywhere they can connect to the Internet. This prioritizes the learner’s experience by accommodating audience members who may be especially busy and/or those who prefer self-guided learning.

Microlearning suitability. A mobile device is the perfect platform to deliver those small chunks of material discussed earlier. Not only are short lessons better suited to learning on-the-go, but the smaller screen size on mobile devices is more conducive to delivering shorter lessons.

Interactivity. Mobile learning allows for all types of media delivery, assuming you have a content delivery platform that supports them. Your learners can use mobile devices to view images or presentations, listen to audio files, watch videos, and complete quizzes and drag-and-drop activities with their touch screens. This provides a more engaging learning experience for your audience.

Mobile learning provides convenience and interactivity that hard-copy materials and even long-form digital materials can’t match.

6. Measurement and Analytics

The most reliable way to cater to your specific audience is to continuously collect feedback from your learners about the efficacy of your courses. As we outline in our guide to curriculum development, this is an essential step to ensure you are continuously building and improving on your course materials.

Today, there are many ways to improve on your courses, including:

Tracking engagement data. Many content delivery platforms offer tracking and reporting that can shed light on how your learners engage with content. For example, you may want to track completion rate to see what percentage of learners have made it through the entire course. Alternatively, you might track the length of time learners spend in a session to get an idea of how your learners are using your materials.
Requesting feedback. Solicit feedback directly from your learners to hear their thoughts and input about your course. Post-course surveys are a great way to collect this information. You might ask your learners questions about the organization of the course’s topics, the usefulness of certain approaches/activities, and their favorite/least favorite aspects of the course.

As data analysis tools become more powerful, instructors, facilitators, and instructional designers can draw more useful insights from data about learners, their preferences, and their behaviors. Every time a learner interacts with an LMS or content delivery platfo rm, another data point is generated and collected, joining a wealth of other data points. When analyzed, this can provide information to guide a learning business’s future course development efforts. Data from surveys can be similarly analyzed to extract insights and trends about your learners’ opinions and experiences.

As you administer courses to your members, volunteers, or other lifelong learners, keep in mind the importance of strategic instructional design. A combination of the approaches discussed here is likely to provide the best results and most engaging learning experience for your audience.

About the Author

Salma Torres is an instructional editor and content curator at Skyepack. Salma graduated with a BA in English from Texas A&M University. With her background as a research scholar, she became a person who is continually learning and excited for new knowledge. Her passion for reading and writing helps her continue to create quality content for online learners. When she isn’t creating course content, she can be found traveling around the world, reading, watching the latest movie, or learning something new.

The post 6 Instructional Design Approaches to Capitalize on in 2021 appeared first on Leading Learning.

LMS vs LXP vs LRS vs LRS – The Core Four Learntech Platforms

Celisa Steele — Tue, 04 May 2021 14:11:55 +0000

As the learning landscape and market have evolved, the technology platforms most closely associated with learning—including learning management systems—have evolved too, and new platforms have emerged. In our executive briefing Conquering the Confusion: The Role of the LMS in the Evolving Learntech Landscape, we examine why and how learntech has evolved, consider how different types of technologies fit into the learning product lifecycle, and help you choose the right mix of technologies.

The Four Learntech Ls: LMS, LCMS, LRS, and LXP

This post provides an excerpt from the briefing in which we focus on the “core four” learning platform technologies: learning management systems, learning experience platforms, learning record stores, and learning content management systems.

Understanding the fundamental purpose and capabilities of each is essential to understanding how the most established of them—the learning management system—fits in your overall learntech ecosystem.

Learning Management Systems (LMS)

Most learning businesses are familiar with learning management systems, even if they are one of the few not using one. The most common piece of learntech, an LMS is software for delivering educational experiences to learners, with an emphasis on pushing out content designed by the organization that owns the LMS—e.g., your catalog of online courses.

Traditionally, learning management systems have excelled at a basic but essential set of tasks for managing learners, providing them with access to learning content, and tracking completion status— often for the purpose of maintaining compliance or awarding credit. Learners interact directly with an LMS via a user interface (UI).

An LMS enables you to enroll learners in courses; it enables your learners to launch and access those courses; and it enables you to track learners’ activity, scores, and completion of courses. An LMS provides basic testing and generates reports.

In today’s context, most learning businesses are not satisfied with that basic LMS functionality alone—and that demand for more has led to significant expansion of the features and functionalities most modern learning management systems offer. What else an LMS does varies from platform to platform, but learning management systems catering to learning businesses (versus corporate L&D) tend to also emphasize discoverability (empowering learners to find the content they want by searching the catalog, for example) and e-commerce.

See also:

Understand LMS in 10 Minutes or Less

Learning Content Management Systems (LCMS)

A learning content management system (LCMS) allows an organization to author and import learning content objects into the platform, edit them, assemble them into learning experiences, and repurpose them into other, different learning experiences. Not as common as LMSes, learning content management systems supplement LMS functionality in the Design & Development phase of the learning product lifecycle. They can be of particular value when collaborative authoring, extensive re-use of individual learning objects, or the ability to manage different versions of learning content are critical to your operations.

Learners do not directly interact with an LCMS—the LCMS UI is for administrators and course authors. Learners interact with the products that come from an LCMS through the UI of another platform, like an LMS or LXP.

While LMSes and LCMSes are distinct types of platforms, some vendors blend the two offerings into a single, unified platform. When that is the case, understanding the origin of the platform can be instructive. Content authoring and management tools built into a system intended primarily for content delivery and tracking will typically be less sophisticated than those featured in an LCMS. The functionality to launch and track learning content and manage learners in a system designed for authoring and assembling content will typically be less robust than in an LMS.

Learning Record Stores (LRS)

Learning record stores (LRSes)—servers that receive, store, and provide access to xAPI statements—are newer entrants on the learntech scene. The Experience API (application programming interface), also known as Tin Can and xAPI for short, is a specification that makes it possible to collect data about a wide range of experiences a learner has, both online and offline.

The appeal of xAPI is that it allows learning businesses and learners greater flexibility in what data is tracked and captured when compared to older standards (like SCORM) and their almost exclusive focus on online courses. xAPI statements, structured as “[actor] [verb] [object],” allow offline activities as well as non-traditional online activities to be recorded. xAPI also opens the door to allowing learners to play a larger role in determining which of their actions get counted as learning activities. Their actions need not be limited to the completion of administrator-created courses but can also include a wide range of less formal activities—for example, watching a how-to video on YouTube, participating in a mentoring or coaching session, or writing a blog post.

Learners typically do not interact directly with an LRS—the LRS is a behind- the-scenes repository of learning records (those “[actor] [verb] [object]” xAPI statements) that might be accessed by learning businesses to better understand their learners’ needs, understand their current skills and knowledge, to award credit, and more. Given their behind-the-scenes nature, LRSes are usually used in tandem with other learntech, like an LMS or LXP, and some LMS and LXP providers have built learning record stores into their systems.

Learning Experience Platforms (LXP)

The learning experience platform (LXP) is one of the newest flavors of learntech. Focused on overcoming some of the perceived shortcomings of traditional LMSes, LXPs put the learner at the forefront. The learner interacts directly with an LXP via a user interface (UI), and LXPs emphasize the user experience (UX).

Drawing on personalization, discovery, and playlist models now common in non-learning applications such as Netflix and Spotify, LXPs allow learners to explore and then access educational experiences, with an emphasis on learner- discovered content. Whereas LMSes evolved out of a top-down model where the organization and its administrators know best what a learner needs, LXPs empower learners to follow their interests when deciding what learning experiences to engage in.

To allow for meaningful learner-driven decisions, LXPs typically draw on large repositories of content, which often means drawing on catalogs of content from outside the learning business. Additionally, most major LXPs leverage artificial intelligence to recommend content to learners based on behaviors and interests.

See also:

LMS vs LXP: The difference and why you should care

The Evolving Role of the LMS

While it is true there is no single, across-the-board, right answer for which system or systems a learning business needs, it is also true that the LMS will likely remain a part of the core learning business technology stack for years to come.

An LMS on its own serves essential needs that most learning businesses have and are likely to have for the foreseeable future. These include the abilities to manage users, push out education that the learning business can ensure aligns with requirements set by regulatory and credentialing bodies, and validate completion of structured learning experiences in accordance with these requirements or requirements set by the learning business itself.

Given that a rapidly growing number of learning management systems are incorporating options for supporting social learning, gamified learning, and access to external course catalogs, many learning businesses may find that the newer, more modern breed of LMS is sufficient for supporting the essential components of the MI DD LE ME lifecycle. These platforms—particularly to the extent that they incorporate marketing and e-commerce tools—are evolving into what might be described as holistic operating systems for learning businesses.

But even the most comprehensive LMS may not meet all of a learning business’s strategic needs.

For example, if an organization develops its learning content through a distributed, collaborative process, if it needs strong capabilities for re-using learning objects across different learning experiences (so the same interactive exercise could appear in multiple courses), or if it wants greater confidence that the content it creates can be used across multiple platforms, then it may make sense to use an LMS in combination with an LCMS.

If a learning business sees strategic value in being able to support and track learning experiences that take place outside of the LMS, particularly informal experiences, then using an LRS in tandem with the LMS may be valuable. An xAPI-compliant LMS can push learning data to an LRS which, in turn, can capture data generated from learner activities that happen on the Web, on mobile devices, in classroom settings, or other places. The LRS then becomes a valuable source for reporting beyond what the LMS alone can provide.

While there may be instances in which an LXP can replace an LMS, most LXP vendors currently promote use of an LXP in tandem with an LMS. When it comes to providing a Netflix-like, highly personalized learning experience, LXPs have a clear lead at this point. At the same time, they typically do not have the same capabilities for handling structured content and learning activities that LMSes do. In the current market, a number of LXPs and LMSes have announced partnerships to help provide organizations with the best of both worlds. Over time, our expectation is that LMSes will incorporate more LXP capabilities natively, and vice-versa. In the meantime, though, the LMS remains the starting point for most learning businesses.

Get the Full Briefing

As noted, this is an excerpt from our Conquering the Confusion executive briefing in which we discuss the role of the LMS in the current learning technology landscape. We encourage you to get the full briefing.

The post LMS vs LXP vs LRS vs LRS – The Core Four Learntech Platforms appeared first on Leading Learning.

Finding XR’s Sweet Spot with Sam Sannandeji

Jackie Harman — Tue, 04 May 2021 12:40:56 +0000

Sam Sannandeji

Recognized as a leader in extended reality (XR) learning, Sam Sannandeji is founder and CEO of Modest Tree, a Canadian company providing immersive software to empower non-technical people to create and maintain their own augmented reality and virtual reality training. He brings both a technical, hands-on expertise of how XR works with an understanding of the needs and pain points immersive technologies can successfully address.

In this fifth installment in our seven-part series on the frontiers of learning technology, Celisa talks with Sam about the future of XR, its potential dangers and opportunities, and related advice for learning businesses on how to make practical use of augmented or virtual reality.

Listen to the Show

Access the Transcript

Download a PDF transcript of this episode’s audio.

Read the Show Notes

[00:21] – Intro and background info about Sam

The Frontiers of Learning Technology

[01:23]- When you hear the phrase “frontiers of learntech,” what comes to mind?

The groups or the industries of people who are trying to change the scope of the platform as it exists. As the training is evolving, our consumption of it is evolving as well. Our attention span is lowering so we need things to be flashier. Being on the frontiers of learntech hopefully means our training continues to evolve to meet those needs.

Defining AR, VR and XR

[02:08] – Can you briefly define AR, VR, and XR?

XR is the variable of X. Once you put the X in there, it could be whatever you want—mixed reality, augmented reality, extended reality, etc.
VR takes someone into a virtual world, immersing them in that environment and closing off the existing world.
AR is often wearable, and we use it to augment our existing reality.

Over-Hyped Trends in Learntech

[03:39] – Which trend or trends in learntech do you think might be the over-hyped, shiny objects that are maybe distracting us from what really matters?

The shiny objects are the new headset or new device that’s coming out. We get distracted by these because of the marketing. Sam says 90 percent of the time, we don’t get what’s actually promised. You don’t need to spend thousands of dollars or be part of a special group to get access to a new device. Rather, wait until it becomes something that all consumers can pick up at the store.

People are getting distracted from the fact that VR is great when you use it for the purpose of building muscle memory and for creating immersive learning environments. For Sam, the focus of learntech is about how to evolve from the old way of doing things in training using these technologies. Not to get derailed by a shiny object like a new headset, but rather focusing on the main concept of the method of delivery of the content.

The Near Future of Learntech

[05:47] – Which trends in learntech have the most potential for significant positive impact in the next three years or so?

Sam hopes the trends related to devices or equipment become mainstream and affordable. He’s seen increased usability in trends like VR, particularly because of the current state of the world not being able to meet face-to-face.

The new technology and evolving game technology related to the training and learning has become very valuable. If that continues and the hardware also follows along, Sam says the trend will continue. We will be at a point where everybody can have that headset, they’re okay with this new method of delivery, and can now comfortably use it.

The Near Future of XR

[07:12] – How would you characterize the future of XR in the next three years or so?

For XR, it always comes down to the lower technology that’s underneath it. We’ve seen huge leaps in the graphical powers of computers lately with some of the new graphic cards coming out. We’ve seen some new leaps in the chip sets for the phones that are coming out that are allowing us to push the boundaries for XR technologies as well.

We’re still trying to figure out what that sweet spot is between AR and VR and MR—or whatever the different X for the R is. We’re trying to still figure out which is the one that people are going to like.
Sam Sannandeji

Until we get mainstream usability out of it, the hardware cost is going to be key. Sam doesn’t think we’re going to make that huge leap in three years, but he does see it in the next five years or six years if we get to a point that there is a standard in the industry of VR headsets.

For example, phones are all pretty standard now. The hardware is different but interface-wise they are similar. The technology related to XR needs to do the same from a usability perspective. The gaming industry is pushing it forward a bit but there still is yet to be that standard headset. For example, everyone in the industry has different preferences for these. There need to be more standards and uniformity so that there can be broader adoption.

Sponsor: BenchPrep

[10:12] – If you’re looking for a partner to help you explore the frontiers of learning technology, check out our sponsor for this series.

The platform’s omni-channel delivery incorporates personalized learning pathways, robust instructional design principles, gamification, and near real-time analytics that allow organizations across all industries to achieve their goals. More than 6 million learners have used BenchPrep’s platform to attain academic and professional success. BenchPrep publishes regular content sharing the latest in e-learning trends.

To download BenchPrep’s latest e-books, case studies, white papers, and more go to www.benchprep.com/resources.

The More Distant Future of XR

[11:21] – What might XR look like out in the distant future?

With technology, Sam describes the three-release lifecycle:

The first one is usually the device or the hardware. It’s often innovative and seems amazing, but it’s not accessible and/or has glitches and usability problems.
Next, the second one comes out. It’s improved upon with better technology and the price goes down.
Then the third release comes out and that’s usually the one that makes things a lot easier for the users. It’s closer to mainstream as possible, which is where we need it to be.

Right now, in many cases, we’re in that second phase. Going back to that standard, Sam predicts we’ll have a breakthrough in the next ten years. In fact, there’s technology right now where contact lenses have chips in them for augmented reality. But the question is whether people will put that in their eyes—will they trust it? There’s also the lack of information about spending 20 hours in VR and whether or not we’re even okay having that AR headset or sunglasses that gives us information.

In the next 10 years as the graphics, hardware, and chips grow—and with 5G being introduced, which allows us to get the information we need a lot faster—then it seems that we are moving in the direction of making it mainstream.

Getting Learntech Right

[13:33] – If we collectively get it right, what do you think is the good that we might see from learntech in general? Or if you want to focus on XR, AR or VR—in the near future, what would it look like to get it right?

Sam doesn’t think we should look at it and say “if” we get it right, we should just get it right. The new workforce coming in has a different way of thinking and they were educated differently than older generations. We need to keep their attention.

The retention rate drops if the learntech is not there to evolve the type of training we’re doing. What we need to do is collectively try to improve the methods of learning as much as we can to the direction that it has the highest retention rate.
Sam Sannandeji

Based on existing data and research, Sam retention rates are not high—but the retention rate is a lot higher than just sitting behind the monitor when you introduce XR. When you get the engagement up, you get the retention up. We end up not only improving the training as we’re going because the old days of manually building these teachings might not be the best option.

Learn more about Xplorer 2.0 (below), Modest Tree’s latest software iteration, which is another milestone in the continued evolution of AR, VR, and XR technology viability for enterprise use.

We might also want to look into doing data-driven teachings and data-driven training for when it comes to that. Then use the data we get from the end case—the learners—to improve that learning.

Getting Learntech Wrong

[16:44] – If we get it wrong, what are the dangers that might come from XR or, more broadly, learntech if you’d like?

We have a problem right now where people are always looking at their phones. Imagine instead of having a phone in your hand, you’re spending 10 hours on a headset, talking to everybody virtually. Sam points out how this can be beneficial for people, particularly introverts who maybe don’t like to engage as much. VR and XR make that very easy to do. For example, he says gaming allows for that [ability not to engage], but it’s also bad that you might get used to living in that XR world and lose social skills.

The other part is that we become too reliant on it. For example, with cars, all the augmented reality (the heads-up displays) and sensors that are going in. They’re reflecting your speed and a bunch of other information into the front windshield, so you don’t have to look down or even be aware of it. This can actually cause us to become really bad drivers because we’re relying on all this technology to help us.

There are certain skillsets that we’re going to lose in the process. It’s a learning balance, that, as a unit, we have to work together to not lose some of those skillsets that we gained…It’s how much do you want to stick to the legacy information we have or the knowledge we have versus the technology moving us forward?
Sam Sannandeji

Technology to Address Problems and Opportunities

[20:01] – Are there problems or opportunities that we need technology to address? What can’t we do without XR?

Organizations are usually concerned with two things: how they can make more money, or how they can save money. If talking about educational institutions such as schools and universities, it’s how can we teach better and how can the students learn better? It’s all about making what we have better, even though we’re okay with what we have.

Sam asks how can we take less time—because time is something we can’t get back—to get something accomplished and get the knowledge base back? For example, if you are putting together a piece of IKEA furniture using the manual it will take a certain amount of time. But consider how XR or augmented technology feeding you information through glasses as you’re putting it together makes that process faster and more streamlined. It’s not that we can’t do things without XR, it’s how can we use it to amplify our processes and the way we do things.

One of the risks we face is that the new workforce coming in has no interest in our old way of doing things. Sam says they aren’t very comfortable sitting in a class, spending five days looking at slides They want a virtual world to practice the skill or practice being in certain situations using the teacher’s guidance to learn. Also, there’s no cost of destroying real equipment.

Advice for Learning Businesses

[23:49] – What advice do you have for a learning business looking to get started in XR, trying to decide what to focus on and what to invest in the near term?

Don’t get caught up in the flashiness of things. A lot of companies make the mistake of seeing something in AR and VR and immediately getting the device.
Don’t fall into judging the effectiveness of XR based on a prototype. Use your old data to help your new methods of delivery so you’re not building things from scratch. Instead of doing a prototype project, try to have a data-driven focus on trying to expand it from one prototype.
Don’t fall into the traps of press releases and marketing videos that show something amazing that was rendered rather than the real-life product.

[26:05] – Are there particular ingredients or factors that you think contribute to organizations’ successful use of XR?

The big challenge Sam sees many organizations have is that they treat XR technology as the same old way of doing training. The problem with that is—because you’re getting into that third dimension with XR—it’s no longer two-dimensional. If you’re talking AI and about 3D, data-driven content, it’s about trying to build something holistic where you can have a full-feature product that is useful day-to-day and can grow. This requires an entire team of people because the key to being able to launch a successful product requires the maintainability of code.

Writing code is like fruit. If you don’t maintain it, it rots…Building XR technology or immersive training is the same way. If you’re not constantly updating it, it rots, and it becomes useless.
Sam Sannandeji

You need a dedicated team from design, to development, to maintenance that are working all together to maintain that dataset and content. If you don’t want to create a team and have the overhead of 20 people doing that for you, Sam recommends partnering up with a company who can.

[29:08] – Are there practical tips or suggestions about how to make practical use of AR or VR specifically for learning and education? Or pitfalls to avoid?

Find the actual pain that you’re trying to solve and be clear on your desired outcome. Then find how you want to solve it, through what technology, and what the outcome is for it. Once you have that, you have your ROI, and now you can quantify it.

[31:43] – Wrap-Up

Sam Sannandeji is founder and CEO of Modest Tree. Based in Nova Scotia, the company provides immersive software for enterprise digitization. Sam is passionate about educating others about the practical possibilities of XR. You can connect with him on Twitter and LinkedIn.

We encourage you to learn more about the sponsor for this series by visiting benchprep.com/resources.

Finally, consider following us and sharing the good word about Leading Learning. You can find us on Twitter, Facebook, and LinkedIn.

[33:20] – Sign off

Other Episodes in This Series:

Episodes on Related Topics:

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Bias and Equity in Learntech

Jackie Harman — Tue, 27 Apr 2021 11:58:08 +0000

Jeff Cobb & Celisa Steele

This marks the halfway point in our series on the frontiers of learntech. Our hope is that you have already begun to consider the implications this explosion in learning technology will have on your learning business. And when it comes to implications we want to focus on some of the major themes that emerged from our earlier conversations with Donald Clark and Sae Schatz—particularly those related to bias and equity.

Bias and artificial intelligence or, more specifically, bias in AI is not a new concern. But it’s one that’s been garnering more and more attention in recent years, and it feels appropriate to focus on it now because of the rise in social justice movements we’ve experienced in the United States.

In this fourth episode of the series, we explore the potential harm of bias in AI drawing on research from Joy Buolamwini and Cathy O’Neil, both featured in the documentary Coded Bias, available on Netflix. We also discuss the difference between interpretability and explainability when it comes to understanding AI and why looking for bias in data is equally important to looking for bias in AI processes.

Listen to the Show

Access the Transcript

Download a PDF transcript of this episode’s audio.

Read the Show Notes

[00:18] – A summary of what we’ve covered up to this point in the series and a preview of what’s to come in our conversations with Sam Sannandeji, founder and CEO of Modest Tree, and Ashish Rangnekar, co-founder and CEO of BenchPrep.

Harm from Bias

We recently watched Coded Bias, a 2020 documentary available on Netflix. The film investigates bias in algorithms and features the work of MIT Media Lab researcher Joy Buolamwini, who uncovered flaws in facial recognition technology. The technology was really good at recognizing the faces of white men, less good with the faces of women and people of color. Because of her work, Google and other tech companies have worked to improve their AI, and it’s gotten better at recognizing faces of all types.

Joy founded the Algorithmic Justice League, which “combines art and research to illuminate the social implications and harms of artificial intelligence. AJL’s mission is to raise public awareness about the impacts of AI, equip advocates with empirical research to bolster campaigns, build the voice and choice of most impacted communities, and galvanize researchers, policymakers, and industry practitioners to mitigate AI bias and harms.”

Watch Joy Buolamwini’s TED Talk below about the need for accountability in coding and how she’s fighting bias in algorithms.

Cathy O’Neil is also featured in the Coded Bias documentary. Cathy wrote Weapons of Math Destruction: How Big Data Increases Inequity and Threatens Democracy (2016). In the documentary, Joy and Cathy focus on the use of AI in policing, surveillance, credit and lending decisions, insurance, advertising, and more. In the film Cathy O’Neil says, “People are suffering algorithmic harm.”

Both Cathy and Joy are focused on the harm. Harm is in the quote from Cathy, and the mission of AJL also mentions harm. They have real concerns—and there is real reason for their concerns. Lost opportunities in accessing money through lending, greater likelihood of being stopped by police, higher interest rates, etc. There’s enough harm and enough real instances of harm that many are clamoring for legislation and regulation and standards. In fact, as we’re recording, the European Commission is expected to unveil a proposal on artificial intelligence regulations in the European Union.

One concern covered in Coded Bias involved a teacher in Houston who had won numerous teaching awards over many years, but he received a poor evaluation when the district implemented an algorithmic approach to assessing teachers. He and other teachers sued, and part of their argument (they won the case) was that they didn’t know why they’d gotten the poor evaluation—the algorithm was a black box that they couldn’t question, and so they couldn’t contest the result because the premises for the result weren’t known.

Black Boxes, Explainability, and Interpretability

[05:45] – The black box argument is interesting. As a society, we use a lot of technology we don’t understand—for example, our laptops, smartphones, and Google Search. We have a pretty crude understanding of how all those work, but we aren’t likely to want give any of them up.

We recently came across a really helpful distinction from Christopher Penn in a Marketing Over Coffee podcast episode. He says when we want to understand how software arrived at a particular outcome, we choose between explainability and interpretability. “Interpretability is the decompilation of the model into its source code. We look at the raw source code used to create the model to understand the decisions made along the way,” per Penn. “Explainability is the post-hoc explanation of what the model did, of what outcome we got, and whether that outcome is the intended one or not.”

Christopher uses an analogy to make explainability and interpretability more digestible. Explainability is tasting a cake—we can taste it and get a general idea of what went into making it. We might not get 100% of the ingredients right—is that vanilla extract or almond extract?—but it’s a fast, easy way of testing. Interpretability, though, is looking over the recipe for the cake. We look at the list of ingredients and the steps, and that allows us to verify that the recipe makes sense and the ingredients are good. This is a more rigorous way of validating results, so it makes sense in high-stakes situations—if someone has a severe allergy, if harm could come from eating the cake, then we want interpretability not just explainability.

But if the stakes aren’t very high, explainability usually is the go-to. Interpretability is costly, and it’s often operationally difficult to do a thorough review. “For more complex systems like neural networks, interpretability is a massive, expensive undertaking. It slows down systems like crazy, and in the most complex models, we might never fully unravel all the details. Interpretability also reveals the secret sauce, to the extent there is any, in the process,” says Christopher. So AI software makers don’t really want interpretability—at least not publicly available interpretability.

But, if you’re the teacher in Houston whose job is suddenly in jeopardy, you want interpretability, not just explainability. Or if you’re not getting job interviews because of AI screening or you can’t get access to a loan because of your zip code. There’s a power differential that comes into play—and this is mentioned in Coded Bias.

Cathy O’Neil makes the point that it’s very hard for an individual to push back against large-scale AI-driven decisions because a lot of them are invisible and are happening in a black box. Many people concerned about bias in AI are focused at this point on simply making the issue known, calling our attention to these often invisible systems, and raising awareness of the potential for misuse, whether that misuse is intentional or incidental.

Weighing Benefits and Risks

[09:39] – In our conversation with Donald Clark earlier in the series, he said he feels like the bias-in-AI discussions lean too hard to the harm side. He makes the point that calling out bias in AI is problematic because the alternatives aren’t bias-free. In the case of learning, human teachers and facilitators are rife with bias. So eliminating AI does not eliminate bias.

We think Donald and Joy agree on this point. Joy says in the documentary, “The past dwells within our algorithms.” They both acknowledge that past and current biases are reflected in AI and its algorithms. Donald just wants to make sure that the baby doesn’t get chucked with the bathwater. Because there’s bias everywhere and because the current educational system isn’t working—he calls the current educational systems “far too expensive, clumsy, and slow”—he sees hope in AI. AI can be taught and audited, probably more effectively than humans, so over time hopefully we catch and remove biases. In the meantime we have to act carefully, though, since AI can scale bias.

AI has the potential to do much more harm than a single biased teacher, but it also has the ability to do great good. If we can scale unbiased AI, it can help learning be the great equalizer it’s often been held up to be in the past.
Jeff Cobb

Though, as Donald points out, learning is often not an equalizer but something exclusive. Learning is not cheap enough or fast enough to be equally useful and accessible to all. On the Pollyanna-to-Doomsday spectrum, it seems we’re somewhere in the middle. Artificial intelligence feels like a both/and at this point—it has dystopian and utopian possibilities.

Rating the Risk of AI

[11:53] – Tied up in Donald’s baby-and-bathwater comment is an idea of the risk involved. Donald used cars as an example. Tens of thousands of people die in car crashes in the U.S. every year, but we still drive cars. We’re not talking about banning the use of cars. We’ve collectively concluded that the good outweighs the bad. The same is likely true for AI—we won’t ban it, but what rules and regulations, what speed limits do we need in place to make it as safe as possible?

We’d argue that AI for personalizing learning is at the lower end of the risk scale, especially if the AI is not a gatekeeper giving access to content to some and keeping others out but is more of the guide on the side, recommending and trying to help learners find relevant and useful content.

In our conversation with Sae Schatz, she homed in on the fact that we can’t be satisfied when we can say everyone has Internet and a computer—i.e., the tools for access aren’t enough. For equity in learning, everyone needs access to high-quality opportunities and experiences—and that’s something that AI can help with, if done right. If not, we run the risk of exacerbating existing inequalities and of creating what Sae called “hidden haves and have-nots.”

In his book Artificial Intelligence for Learning, Donald Clark points out the risk in AI for learning. He writes, “The danger is that AI could deliver narrow, deterministic, prescribed pathways, not allowing the learner to breathe and expand their horizons, and apply critical thought.” So, “We need to be careful that the learner retains the curiosity and critical thinking necessary to become an autonomous learner.” But he also points out, “The degree to which human agency is included in AI-driven systems is a design issue.”

So it comes down to human designers. Do we design AI as a guide and nudge with lots room to still explore or even ignore recommendations? Or do we make it a gatekeeper with tight control over access to learning resources? As long as AI is a guide and not a gatekeeper, the risk of getting AI wrong feels minimal, and the potential for getting right seems huge.

Sponsor: BenchPrep

[14:53] – If you’re looking for a partner to help you realize the possibilities of learning technology, check out our sponsor for this series.

To download BenchPrep’s latest e-books, case studies, white papers, and more go to www.benchprep.com/resources.

Data As Dangerous As AI

[16:12] – In Coded Bias, Joy Buolamwini says, “The past dwells within our algorithms.” The good and the bad of our past are on display in the algorithms and in AI. The past is there because AI needs data to focus. That means the datasets used to teach AI can be troublesome—gaps in the data or over-representation by particular groups can skew results. So even if the algorithm is unbiased, the data might be biased. We have to look for and audit for bias in the data and in the AI processes.

If you think about the term systemic racism and the fact that learntech is made up of systems, like learning management systems, you see the potential bias and injustice in learntech.

We’re struck by how everyone we’ve talked to for this series has emphasized the importance of data. Data is the lifeblood that makes AI, personalization, recommendations, and more work. When we spoke with her, Celeste Martinell, vice president of customer success at BenchPrep emphasized the essential importance of data in learning going forward.

Data was a topic we spent time on in episode 265, and it was a refrain that both Donald and Sae returned to again and again. Sae mentioned the conventional wisdom summed up in the cliché that data is the new oil. Oil is arguably a 20th-century point of comparison—a more 21st-century view might argue data is new solar or the new wind. But the point is that data is necessary for powering and enabling other types of activity.

Donald Clark outlines four levels of use of data in his book Artificial Intelligence for Learning: describe, analyze, predict, and prescribe. The levels move up in terms of difficulty. Using data to describe who completed which course and when is relatively easier than getting to the fourth level, prescribe, where we use data to help us understand not what’s happened but what should happen. What should this learner study? Prescribing gets into recommendations and true personalization.

AI plays a significant role in marketing today, and AI in marketing is pretty good at getting beyond the lower levels (describe and analyze) and into the upper levels (predict and prescribe). We feel like many learning businesses are still in the describe and analyze levels with their learning, even while marketing is further along. We know our listeners have to market their learning offerings, so marketing’s use of AI is important and relevant in its own right but also because what happens with martech is often a bellwether for what happens with learntech.

This fits with Donald Clark’s assertion that consumer tech drives learntech. It’s also a point that Joe Miller, vice president of learning design and strategy at BenchPrep, made when we spoke to him. He likes to look at what the other “x” techs are doing—fintech or retail tech for example. Looking at how they’re approaching problems and opportunities can be instructive for organizations looking to get the most out of their learntech.

[20:34] – Wrap-Up

Reflection Questions

Below are two questions to explore and re-evaluate as your learning business gets into AI and increased automation in its use of learntech.

How risky are the ways in which you use or plan to use artificial intelligence and automation? More risky ways would be tied to when the technology is a gatekeeper, allowing access to some and keeping others out. Less risky ways would be where these technologies make suggestions and recommendations to learners that can be acted on or ignored.
For each of your uses of automation and AI, is the technology interpretable or explainable? And does that match the risk? For riskier uses that might be tied to job promotion, salary increases, etc., you’ll want to lean towards the interpretability side, being able to check out the cake recipe, so to speak.

We encourage you to learn more about the sponsor for this series by visiting benchprep.com/resources.

Finally, consider following us and sharing the good word about Leading Learning. You can find us on Twitter, Facebook, and LinkedIn.

[23:10] – Sign-off

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The Future Learning Ecosystem with Sae Schatz

Jackie Harman — Tue, 20 Apr 2021 12:30:31 +0000

Sae Schatz

Throughout her career, Sae Schatz has been deeply immersed in the application and advancement of learntech. She currently serves as director of the Advanced Distributed Learning (ADL) Initiative, a government program for science, technology, and policy related to distributed learning. She’s also an editor of and contributor to the e-book Modernizing Learning: Building the Future Learning Ecosystem.

Prior to joining ADL, Sae worked as an assistant professor and an applied human-systems scientist, with an emphasis on human cognition and learning, instructional technologies, adaptive systems, human performance assessment, and modeling and simulation.

In this third episode in our seven-part series on the frontiers of learning technology, Jeff talks with Sae about ADL’s “building the future learning ecosystem” initiative and the key ideas behind it. They also discuss the role of Total Learning Architecture (TLA), data, the future of learntech, and suggestions for learning businesses to capitalize on these new technologies.

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[00:29] – Intro and background info about Sae Schatz

[01:31] – About ADL, the work it does, and Sae’s role

Sae shares that the Advanced Distributed Learning (ADL) Initiative was created in the late 1990s to encourage the use of online learning, across the government and society and, in particular, defense.

Originally, a lot of the work focused on what we now see as “traditional” e-learning—learning management systems and SCORM (Shareable Content Object Reference Model), for example.

They also do a lot of work with digital learning interoperability, data, emerging platforms, and the learning science for different modalities.

The Evolution of xAPI and cmi5

[02:58] – How are xAPI or cmi5 evolving? What other specifications are you working on?

Besides xAPI (the Experience Application Programming Interface) and cmi5, Sae says the ADL is working on other interoperability specifications, dealing with learning content metadata, learner records, and competencies. These are all ways to be able to put building blocks together.

She notes we have been talking about these emerging concepts for years: lifelong learning (see Chris Dede’s discussion on the 60-Year Curriculum), ubiquitous learning across all different kinds of platforms, augmented reality, virtual reality, extended reality, data-driven learning, AI-driven personalization, learning analytics, and competency-based learning.

The question really becomes how do we take all these amazing puzzle pieces and put them together? And that’s really where all of these different interoperability specifications come into play. Think of that sort of like Lego blocks. The reason that Legos work is because you have the exact same little connections in the same sizes in the same places. But the blocks themselves can be all different shapes and formats, and you can build your own little castle, however you want it to be. The art is in the way that they’re interoperable.
Sae Schatz

Frontiers of Learning Technology: Building the Future Learning Ecosystem

[05:45] – When you think about the phrase “frontiers of learning technology,” what comes to mind?

Sae shares the ADL is very focused right now on building “the future learning ecosystem”—the K-to-gray, technology-enabled, data-driven, heterogeneous system of systems. Imagine a technology-enabled lifelong continuum of learning that’s driven by data, that’s personalized, and that incorporates good-quality learning science.

The ADL recently published the (free and downloadable) e-book Modernizing Learning: Building the Future Learning Ecosystem, which talks about the rationale and then defines a roadmap across technology, data, and data issues like privacy and security, learning science, and organizational dynamics.

[07:33] – How do we make progress towards building this future of learning ecosystem?

Sae explains that won’t get there all at once; it has to be a journey. But we don’t have to get all the way to the end to begin to realize some benefits.

She shares three steps to making progress:

Data interoperability. Currently we have learning islands that are pretty siloed. One particular course doesn’t know who you are or what courses that you took beforehand.

We don’t have a way to have that relay race, where we’re passing the baton of data, of information about the learner from place to place to place. Instead of having these learning islands, we want to connect them up. We want to get to that modular open systems architecture, that interoperability.
Sae Schatz

Semantic interoperability. This helps us get a common currency across the different islands, and it’s where competency-based learning comes into play, so can all work off a common, machine-readable list of the different knowledge, skills, abilities, and job requirements.

Upskill learning professionals. We’re not living on our own little island anymore; instead we have this whole world we need to navigate. We need to have learning engineers—people who understand technology, learning data, learning analytics, learning science for learning at scale, lifelong learning, and all of these other capabilities to use our toolset to the best effect.

Total Learning Architecture (TLA)

[11:25] – Would you tell us about the Total Learning Architecture (TLA) concept?

TLA is about data interoperability and the enabling infrastructure to make this big vision work. Specifically, TLA is a set of IT and data specifications and standards for learning technologies. TLA is open and standards-based, so anyone can implement it in their systems. It’s the blueprint detailing where those little circles on the Lego blocks go.

The Total Learning Architecture incorporates four data standards.

Getting good-quality, granular runtime data out of your learning management system, simulator, electronic grade book, etc. (using xAPI)
Knowing and defining what the learner is doing (the course, video, simulation, etc.)
Defining a learner’s education, experience, and employment history (the three Es of their life) to know their capabilities
Identifying competencies (as a common currency)

Sae acknowledges this sounds simple, but, when you think about how to connect hundreds of systems, ensure security and privacy are maintained, abstract information, etc., it becomes complicated quickly. That’s what TLA is meant to help with. TLA is a blueprint of IT and data specifications for learning technologies to build out the ecosystem. It’s also the reference implementation and prototype to make sure everything works correctly and that the business rules are correct.

[15:40] – How does an organization start moving towards Total Learning Architecture?

ADL has produced a system administrator guide that lays out specific steps to implement.

Sae recommends the following to start:

Get good runtime data out of your training, education, and other learning and development systems. We need to do a good job of measuring what individuals are doing, what they’re learning, and what their performance looks like. Using xAPI to do this puts things into an interoperable format.

Start connecting different training and education opportunities together. For example, if you have a learning management system, a microlearning app for smartphones, and videos, connect those so you’re getting rich data across your own learning islands. Also, implement metadata that describes what those different experiences are. ADL is currently working with the IEEE Learning Technology Standards Committee on the P2881 standard for learning metadata.

TLA Capability Maturity Model (image from https://adlnet.gov)

Sponsor: BenchPrep

[18:20] – If you’re looking for options for your learning ecosystem, check out our sponsor for this series.

To download BenchPrep’s latest e-books, case studies, white papers, and more go to www.benchprep.com/resources.

The Near Future of Learntech

[19:47] – Which trends in learntech have the most potential for significant positive impact in the next three years or so?

Sae says it’s not about the technology; it’s about how we use the technology. We need to figure out how to creatively—using good-quality, evidence-based learning science—make the best use of what we have.

She’s a big fan of Ruben Puentedura’s Substitution, Augmentation, Modification, and Redefinition Model (SAMR) Model. The first stage is simply replacing the old way with new technology.

SAMR Model (image from from schoology.com)

The More Distant Future of Learntech

[22:29] – What might learntech look like in the more distant future?

Sae sees so much possibility with learntech and doesn’t think it’s going to happen in a too-distant future—it will certainly happen in our lifetimes.

Going back to the idea of learning ecosystems, she explains there is a childhood-through-lifelong-learning continuum that is technology-enabled with many different platforms. All the platforms collect data about your performance and what you’re experiencing so they’re able to then create individual profiles and truly personalize learning and development.

This would integrate education and employment, as well as other experiences that shape you as a person (being a parent, climbing a mountain) and may get to some soft skills and other important competencies that are hard to measure. And competency-based learning comes into play, so the organizations and the learners themselves are able to see what the learners can do.

We’ll have humans and AI working together helping to complete tasks. This will ensure we have truly effective learning, not that you’ve spent an hour in a course or four years getting a degree to show you are qualified. Rather, this will be based on your performance and where you need to go in your nonlinear journey.

Sae also imagines this is tied into the workforce, so that it’s an integrated system, and we’re able to connect a person’s capabilities with certain jobs. The better matchmaking will help us solve unemployment and underemployment and fill gaps.

Ideally, we would have a meritocracy, helping to elevate people and give them a clear pathway forward. She imagines the systems all driven by data where individuals, organizations, and society can leverage high-quality data about individuals to better inform learning, development, employment, and lifelong planning.

Getting Learntech Right

[27:02] – If we get learning technology right as society, what’s the good that we might see? And what are some of the things we need to do to make sure that we get learntech right?

Today every single individual is being asked to do a broader range of things and, typically, at higher levels of sophistication.

The pace of change is just constant. The technology you are using today, the landscape, the world today will probably be completely different in five years. So we need to be constantly learning, unlearning, relearning. And the only way we can cope with this increased breadth, depth, and pace is to have this flexible learning ecosystem around us to help us get to this constant learning and development that we’re going to need.
Sae Schatz

She says we need to make sure that we’re doing a better job of capitalizing on our talent. Right now we do a pretty bad job of measuring our human capital and personnel readiness. We can do a much better job if we can identify individuals’ capabilities, where our gaps are, and what our jobs or tasks are and then make sure we put the right person in the right place at the right time, giving that person the right development experiences when needed. We can start to move towards more of a meritocracy for job placement instead of relying on propinquity or social advantage. We can start to do a better job with matchmaking for the people with the jobs.

Sae notes this isn’t just her vision. The Chamber of Commerce has an initiative to build a nationwide talent pipeline. They’re bringing together businesses and government organizations and working on the foundational data standards—those Lego block blueprints—so we can make this happen.

Learn more about the Chamber of Commerce’s initiative in this video.

Getting Learntech Wrong

[31:15] – If we get it wrong, what are the dangers that learning technology might bring?

Sae stresses this is a really important thing for us to be asking because there are some major pitfalls, and, if we’re not careful, we could cause damage.

Below are some ideas to consider to avoid getting learntech wrong:

Information overload, disconnected experiences (lack of semantic coherence) lead to cognitive biases.
Incomplete, degraded, or otherwise untrustworthy information is problematic.
Equity is important. We need to make sure that we have high-quality learning experiences driven by high-quality learning data available to everyone.

Advice for Learning Businesses

[34:33] – What advice do you have for a learning business looking to effectively use learning technology and trying to decide what to focus on and invest in in the near term?

Start with your data, and make sure you are capitalizing on it. Data is the new gold. Find the common standards that are being used across industry, academia, and government. You can use the standards they’re working on at ADL or standards from other organizations such as the Chamber of Commerce and IEEE organizations.
Shift to a competency-based learning approach. This allows for a meritocracy, and it’s more motivating for people. You’re better able to align the training and education with the actual jobs or the outcomes you need, and it provides a common currency across different data systems. Just as with the data standards, you don’t have to invent this on your own because so much of this already exists. For example, the Department of Labor’s O*NET (Occupational Information Network) has competency frameworks.
Upskill your learning facilitators. Facilitators means your designers, developers, and deliverers—the people who work across your learning franchise. Help them learn how to embrace learning data, learning analytics, improved assessment, and learning technologies to get the most out of them. This will help you get the most from individual learning, learning at scale, and eventually from the lifelong learning ecosystem.

[37:59] – Wrap-up

Sae Schatz is the director of the Advanced Distributed Learning Initiative and editor of the e-book Modernizing Learning: Building the Future Learning Ecosystem. We encourage you to visit the ADL Initiative’s Web site, as they make a wealth of resources available to help you as you think about your organization’s learning technology needs.

Connect with Sae on LinkedIn or Twitter.

We encourage you to learn more about the sponsor for this series by visiting benchprep.com/resources.

Finally, consider following us and sharing the good word about Leading Learning. You can find us on Twitter, Facebook, and LinkedIn.

[39:56] – Sign-off

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AI, Data, and Optimism with Donald Clark

Jackie Harman — Tue, 13 Apr 2021 13:34:23 +0000

Donald Clark

With an unmatched passion, knowledge, and optimism related to advances in learntech, Donald Clark has over three decades of experience at the intersection of technology and learning. He is CEO of WildFire, an AI content creation company, and a professor, researcher, speaker, and learntech blogger (he’s written a series of posts on 100 learning theorists who have shaped the world of learning). He’s also author of the book Artificial Intelligence for Learning. (Listen to the audio at the end of the episode for a special discount offer on the book for Leading Learning Podcast listeners.)

In episode two of our seven-part series exploring the frontiers of learning technology, Celisa talks with Donald about the important role of artificial intelligence and data in shaping the learntech landscape. They also discuss related trends, what’s on the horizon, and key ideas learning businesses and society need to consider to ensure effective and positive applications of learntech, now and in the future.

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Read the Show Notes

[00:24] – Intro and background info about Donald Clark

The Frontiers of Learning Technology

[03:18] – When you think of the phrase “frontiers of learning technology,” what comes to mind?

Donald shares that because he’s tended to always to work on the leading edge of technology, and, for him, “frontiers of learning technology” means two things: artificial intelligence and data.

Really everything we do online is mediated by AI and data.
Donald Clark

The whole online world is supported and mediated by AI except in learning, which is why he’s focused on AI in learning for the past four to five years. Not only has he built and invested in companies that focus on AI in learning, but he wrote Artificial Intelligence for Learning, which lays out the landscape around this really radical shift in technology.

He highlights several big shifts in technology, the biggest one being writing, which shaped and created the culture of our species, along with the alphabet and then printing. He explains that these are all learning technologies and multipliers of culture. The computer came along in the 1970s, and then the Internet itself, another event some would argue was as big as writing. Now the big paradigm shift is to AI and data, which start to mimic teaching and learning in a much more sophisticated way.

Over-Hyped Trends in Learntech

[05:15] – When you think about trends, do any fall in the camp of the over-hyped or dead-ends, things distracting us from other technology that might actually help with learning?

Donald thinks there are certainly some things that are more niche than general. He likes to look at the consumer technology that influences learning technology universally, and AI and data fit the bill—as do writing, computers, and social media.

But there are some niche things that people claim to be universal, such as Google Glass. He says virtual reality (VR) is not a dead-end, but it is a niche product currently and we don’t quite know where it’s going to end up. He also thinks augmented reality (AR) is over-hyped. There are trends whose efficacy in learning are somewhat exaggerated.

Another trend he thinks is exaggerated is gamification. Donald says it could be useful, but only in a Pavlovian badging sense. Badges are another trend he thinks is over-hyped.

Trends with Significant Potential for Learning

[07:08] – Which trends have significant potential for learning?

Donald likes to think about that question by considering which technologies reflect good learning theories and how we really learn. Some technologies fit learning; some don’t. The ones that really fit—and this is why he thinks AI and data are so important—are the ones that shape the interfaces, make learning easier, and avoid cognitive overload. For example, voice interface AI (such as with Google Alexa) has given us text-to-speech and speech-to-text that makes these interfaces almost frictionless.

The brain has evolved to where we don’t really learn how to speak or understand what people are saying—it comes effortlessly. But we did have to learn how to read and write. Our big fingers on tiny touch screens are a poor way of interfacing with anything. AI should make learning smoother and easier. We want to get to the learning, not worry about the interface.

The algorithmic side of AI, fueled by data, is allowing us to personalize learning, which is very important. This is the big shift in pedagogy that he thinks is afforded by AI. AI can be sensitive to what learners are finding difficult at a precise moment and help.

We vector through learning differently. We’re all in a different learning journey, even when you’re sitting in a classroom with 30 people. You’re all sort of going at different speeds, different things going on in your head, different types of difficulties. So this personalization of learning is terribly important.
Donald Clark

AI for Personalization of Learning

[09:14] – Where are we in the application of AI to personalize learning? Do you have examples of where AI is being used successfully to support learning interactions?

Donald points out that we tend to think about AI as present and future tense, but it’s already been around for a couple of decades. For example, we all use Google, and Google is pure AI. It gives us what we’re interested in at the exact moment of need. He doesn’t just mean Google Search; he means the searchability of the content. Nobody doing PhD research would want to trade Google Scholar to return to wandering down shelves, looking for bits of paper in journals. AI makes research more efficient.

AI is already touching adaptive learning, which is increasingly being adopted.

There’s also the recommendation engine side of AI, which tries to determine where learners are on their learning journey in order to suggest appropriate content, as well as provide learning support through chatbots or the like. All this is enabled by AI. AI is also being used for anti-plagiarism, and there’s even the creation of online learning content using AI (such as what WildFire does).

I think we’re at this embryonic stage where the sophistication of AI is bringing sophistication to technology-based learning to get us out of a really, what was a necessary stage, which was almost multimedia production. Lots of videos, thinly punctuated by multiple-choice questions…. What it needs to do is become more like a teacher. Be more sensitive to you as a learner, be more adaptive, more responsive,to be able to tackle your needs at exactly that moment. And you can only do that by using data. This is terribly important. I need to know about you as an individual, where you are exactly, how you got there, the context you’re in, butI also need aggregated data from all the other learners that are taking this course so that I can bring that to bear,right at that moment of need.
Donald Clark

The Near Future of Learntech

[12:40] – How would you characterize learntech in the near future? Are we going to have breakthroughs? Is it going to be disruptive innovation, more incremental innovation, something else? How would you describe what you think is going to come in the next three years or so?

Donald predicts in the next three years we’ll have a hybrid phase, as we move from one paradigm to another. Netflix gives you an AI-mediated, tiled, personalized menu. Nobody has to learn the Netflix menu—it scrolls to the right across a topic and in-depth for new topics. It’s almost an effortless interface. But Netflix exists alongside broadcast television, which isn’t disappearing anytime soon (although it will diminish as the new streaming service comes into mode).

The best contrast might be between traditional VLEs (virtual learning environments) or LMSes (learning management systems), which will continue for some time because they manage and store stuff (though rather crudely) with the SCORM standard. But he thinks they are going to be replaced to a very large degree—and quite quickly—by LXPs (learning experience platforms). LXPs will enable AI- and data-driven learning journeys that are much more sophisticated, respond to the learner, and deliver personalized learning.

The More Distant Future of Learntech

[14:11] – In the more distant future, what do you see as the direction for learntech?

The shift is starting now. For example, there are now $3 million deals on LXPs, and that wouldn’t have happened just a few years ago, but it’s now happening with the larger global companies.

He admits that looking further out is always dangerous because the further you go out the probability drops off dramatically of you being correct. But he says the AI- and data-driven approach is irreversible. It’s is the technology of the age, and the idea that we’ll go back to a client-server model is plainly ridiculous.

There are some really interesting developments that he thinks don’t get enough attention when thinking five to ten years out. First, and this may be within the three-year horizon, is Starlink. The underlying technology for online delivery, especially AI and data, is bandwidth, is the Internet itself. The promise here (likely within a year or two) is that high bandwidth 5G will be available anywhere on planet Earth at a reasonable price because the prices will fall with volume. Donald thinks that will be revolutionary in our ability to deliver technology-based learning to anyone, anywhere, anytime.

Donald notes the great thing about having high bandwidth anywhere is it allows the use of personalization and AI and data in a way previously impossible because streaming is data-hungry. Also, the use of AI needs high bandwidth because you don’t want latency; the experience should be smooth.

Another area further out that Donald finds fascinating is the work by Neuralink and others. We have to be careful with these invasive and noninvasive techniques around the brain. He’s highly suspicious of the value of the noninvasive techniques, where you put a little helmet on and have a light flashing on your forehead, because what it’s measuring is EEG (electroencephalogram), which is a messy signal. He finds claims that we’ll be able to tell whether learners are paying attention or not farfetched.

However, the invasive techniques are starting to get interesting. We already have the Utah Array, and there are 150,000 people with that in their heads, helping them to move their arms and legs.

See below for an example from Neuralink, which shows a monkey playing a simple video game after getting implants of the new technology.

Donald says we know that putting fibers in the brain to stimulate portions of the brain works, but the interesting possibility is the ability to read and write to the brain. When you’ve got tiny fibers—a fraction of the width of a human hair—and you can put them in without bleeding, then you can start reading data, and you need AI to interpret that data accurately.

Writing data back to the brain begins to get into the realm of science fiction because we’re nowhere near this practically, but imagine sometime in the future if where we could pay $50 to learn Spanish.

But he points out there’s a bigger prize at stake here, which Neuralink is focused on: solving mental illness problems. For example, using technology to get rid of depression. So this isn’t just about toys, gimmicks, or gadgets. Rather, there are some real possibilities the technologies will afford us.

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Getting Learntech Right

[22:03] – If we get learning technology right as society, what’s the good that we might see coming from learntech? And what are some of the things that we need to do to make sure that we get it right?

There are people, especially in academia who say they’re involved in AI and ethics, but it’s not really ethics, according to Donald. Ethics is the study of moral principles, good and bad. But what they’re doing, he says, is more like activism. They’re looking for bias, gender issues, or racism around AI. They’re looking for the flaws, and that’s not really ethics because they’re discounting the other side, the good side. Ethics takes a more balanced view of what’s good and bad.

Donald thinks there are big moral issues here. Higher education in particular produces massive inequalities, and it’s become a generator of inequalities. The future technology-driven world offers a chance to balance things out and get education to everyone cheaply.

We cannot go on charging people tens of thousands of dollars a day for a little certificate at the end that’s really a sorting mechanism. Of course, it has value. Of course, people learn things at college, but about 80 percent of it is signaling. In other words, it’s giving employers a signal that you stuck at it a little bit, that you come from a certain class and background, and so on. I think that’s unacceptable now because it’s led to such inequalities and such a fractious world that I think it’s no longer sustainable. So I think we have to make learning cheaper, faster, better, more accessible globally.
Donald Clark

Donald thinks globally is an important word if we’re going to solve climate change and get around the economic issues that we face today. The current system doesn’t work—it’s far too expensive, clumsy, and slow. We have to begin to rebalance system.

Donald doesn’t believe lifelong learning has anything to do with going back to college. Hardly any adult who went through college wants to go back, and hardly any of them do because that’s not what lifelong learning is about. Lifelong learning is about become an autonomous learner, being curious, and learning on your own.

Getting Learntech Wrong

[26:57] – What are the dangers we’re up against if we don’t approach learning technology in the right way? Any thoughts around what actions might lead us to get learntech wrong?

Donald thinks we’re already getting it wrong, particularly when it comes to cost, with $1.8 trillion in federal debt around student loans and people are struggling to pay that money back because they’re un- or underemployed. Academics fly everywhere at the drop of a hat to to to a conference, and, if we think that’s acceptable in terms of climate change, then we have to think again.

He says we’re now in sort of disaster avoidance mode, with economic issues and climate change. Technology promises a greener world. We went through an amazing experiment during COVID, where almost everybody on the planet had to do online learning (and he doesn’t buy the idea that kids were traumatized by it).

Donald suggests we need to look forward to a blend between the online and offline, with learning but also with work. We may spend two to four days a week working at home with the days in an office—or maybe wholly at home. Everything will be blended in the future. We’re now doing blended eating (with food getting delivered to our doors in COVID times) and blended entertainment (watching more movies than ever through Netflix).

Donald thinks the technology has shown we can help solve the climate change issue. And technological innovation is ultimately perhaps our only hope with climate change, and that’s a result of education and learning.

Donald is optimist. He thinks technology is a force for good, and that’s why he gets disappointed when he sees armies of people on social media looking for little bits of bias in algorithms when we know human beings are packed full of bias. Donald says we’re all racist and sexist, and it’s very difficult to get rid of that bias. But at least we can work towards improving these other systems to reduce the levels of bias. The danger is that we throw the baby out with the bathwater—and the bath. We throw the whole lot out because we think there’s some bias or unfairness in an algorithmic system that actually exists in the human system anyway.

See our related episodes that deal with bias: Diversity and Disruption with Shilpa Alimchandani and Getting Conscious About Bias with Howard Ross and Shilpa Alimchandani.

Donald thinks China perhaps will leap ahead because they don’t have the same view of these issues. He says Europe tends to be stuck in the middle here, with less innovation and loads of regulation. Americans have innovation on their side with some of the great tech innovations coming from the US (and he thinks this will continue to be the case).

Technology to Address Learning-Related Problems and Opportunities

[31:33] – Are there learning-related problems or opportunities that we need technology to address? Are there things we can’t solve without learning technology or technology more broadly?

Almost everyone with learning difficulties has been helped by AI and data, and Donald thinks we have a chance of tackling the difficulties every individual has in learning. This has already happened in the world of accessibility. For people with hearing and visual impairment, it’s been AI that’s led the way with text-to-speech and speech-to-text systems.

Mathematics and language learning are areas of catastrophic failure for most people. We can use technology to help solve failure and get people through obstacles.

I think once we pay attention to the learning theory and match that with the technology we can massively accelerate learning for the good of all, for the good of everyone.
Donald Clark

Advice for Learning Businesses

[34:05] – What advice do you have for a learning business looking to effectively use learning technology and trying to decide what to focus on, what to invest in, and where to put their resources?

Donald recommends learning businesses look at AI and data with more vigor. Remember that learning is a process, not an event. Nobody learns anything by just sitting in a lecture or a one-off course, online or offline. Almost all learning is asynchronous and after the event. We know how people learn, and, more importantly, we know a lot about how people forget and fail. If we start addressing those issues using the technology, we will accelerate learning and have a much higher degrees of success.

Donald only invests in AI- and data-based learning companies now because that’s the future. We live in the age of algorithms, AI, and data. And if your learning business is not thinking about using those, then another organization will come along that is.

AI- and data-driven companies are growing, with the biggest ones being either American or Chinese. Google, Facebook, Microsoft, and Apple are all really AI companies. If you ask any of the CEOs of those companies what the underlying technology is that they use and develop, they would say AI. Donald says these companies are now starting to dabble in education and learning.

He also adds that we’re looking at hybrid AI-with-human models coming along. That’s happening already in adaptive learning, in learning experience platforms (LXPs).

Consumer Technology with the Most Potential for Learning

[37:25] – What consumer technology do you see having the most potential for learning?

Donald clarifies that when he refers to AI, it’s not one thing—it is many, many things. Text-to-speech/speech-to-text is one species of AI that relies on natural language processing (NLP).

Then there are the big models, such as GPT-3, that generate online learning content automatically. He’s built a system that does that. You just send him a video, a PowerPoint, text, etc., and he cuts and pastes it into the system that then generates online learning content, not multiple-choice questions, but questions that can be interrogative. So it will ask a learner a question, she types a short paragraph, and AI interpret that paragraph semantically and meaningfully. These little bits of AI are moving ahead on a broad front and allowing us to do things we could never do with technology before.

Donald Clark explains WildFire’s AI content creation tool.

Donald thinks AI will have big cultural and economic impact because it’s a massive multiplier. You can scale it, and it extends cognition in a way that other technology doesn’t. For example, video is a very poor medium for learning (unless the goal is emotional impact or to cause an attitudinal shift). AI is replacing some teaching tasks, and that’s why it’s more important. It can scale, and it allows us to enable pedagogies like spaced practice, interleaving, all the things we know will work, but never had the chance to apply.

AI comes from consumer technology. If you buy something on Amazon or go on Netflix, the reason they have these personalized screens is they’re trying to target what you want. That’s what we need in learning. AI melds hardware and software together in a very powerful fashion. Donald thinks there’s a huge amount of good to come from this in the learning and education sphere.

Donald points out that we don’t regard things like writing, printing, or books as technology, but they were in their day. What we tend to do is historically declassify or discount the technology from before we were born. We don’t see a dishwasher as a piece of technology now, but it was. He predicts we’ll see the current e-learning, LMSes, MOOCs, and so on as old hat very soon because of this newer age of algorithms, data, and AI.

AI As Comprehension Without Competence

[41:05] – I’ve heard you describe AI as comprehension without competence. Would you talk a little bit about what the implications of that might mean when applying AI in the service of learning?

When describing AI to people in the education and learning profession Donald stresses the importance of truly understanding what it is. He describes AI as an idiot savant. It’s incredibly smart at very precise things but incredibly stupid at general intelligence.

But AI doesn’t have to be a form of human intelligence to be effective. It’s terribly important in terms of the application of AI that we don’t over anthropomorphize.

The future of AI is not going to be little robot teachers. It’s not going to be robot teachers, full stop. It’s such a great fallacy this. It’s going to be more like Google. It’s going to be online. It’s going to be from Starlink. It’s going to be on whatever devices we carry around with us, coming into our glasses, AR, whatever. It’s going to be online stuff. Incredibly smart because of the hidden force of AI behind the scenes. It will be invisible, and that’s the point.
Donald Clark

AI shouldn’t replace the human brain because the human brain is a terrible, messy organ. It’s inattentive and gets easily distracted, emotional, and depressed. It forgets almost everything, gets dementia, Alzheimer’s, etc. We can’t network from other brains or upload or download. Computers can do a lot of that stuff, so we can take a load off ourselves by using this technology.

AI has a long way to go before being human, but it doesn’t have to be human to be effective.

A Shift to LXPs

[43:49] – LXPS are getting a lot of attention these days, the Netflix-like learning being very attractive. What are your thoughts on the differences that LXPs represent versus other learning technologies, like LMSes? What’s driving the shift?

Donald thinks what’s driving the shift is the idea that you spend a lot of money just storing and managing stuff on an LMS, which is really mimicking the old course structure. Learning is a process, not an event. With LXPs, we flip that model and look at how people actually learn. We learn in a fragmented and informal fashion. He references the 1991 book Electronic Performance Support Systems by Gloria Gery, which talks about unintentional learning and how most of learning just happens to us.

He says LXPs are more dynamic. They use AI for recommending and predicting the future and automating processes. They push stuff to learners, but also allow learners to pull stuff.

There are other species of push that are more dynamic and process-like. For example, Donald talks about spaced practice, which works superbly well. But how many of us use it? Almost nobody. But now we have the technology where the algorithms can personalize spaced practice, just as Duolingo does with a language. Duolingo is worth $1.5 billion and has 100 million learners in their sy,stem and that’s because it uses this type of tech. It’s adaptive. It’s an LXP-type system that will send notifications to you. If you go away for the weekend and stop learning Spanish, it knows you’re going to forget some so it takes, you back a little bit. Donald asserts this type of smart technology will shape the future of learning—it already is.

LXPs are data-driven, often using a learning record store (LRS) to fuel the LXP.

When we look into the future, we need to have an ethical concern and focus then on what really matters—and that’s people and their needs in terms of accessibility and cost. Donald points out that everything has become too expensive, making it far too elitist. We need to make sure that people can afford learning, that it’s available, most likely for free.

All the learning he does is free—for example, listening to podcasts. Some 60 percent of all Americans listen regularly to podcasts, and Donald says nobody could have predicted that, which is what’s so exciting.

This interview is taking place on different parts of the planet, and then we publish it, and anybody can hear it for free. When Starlink comes along, anybody, literally anywhere on planet Earth, can listen to that podcast for free. Donald notes that we’ve gotten pessimistic about technology; we need to have more optimism.

[49:35] – Wrap-up

Donald Clark is CEO of WildFire, an AI content creation company, and author of Artificial Intelligence for Learning, which is recommended reading if you want to better understand how AI can support learning. We’re pleased to be able to offer Leading Learning Podcast listeners a 20-percent discount with free delivery in the US. (Listen to the audio to get the discount code.)

We also encourage you to take time to peruse Donald’s blog. There you’ll find insights and reflections on learntech, including the series on 100 learning theorists.

We encourage you to learn more about the sponsor for this series by visiting benchprep.com/resources.

Finally, consider following us and sharing the good word about Leading Learning. You can find us on Twitter, Facebook, and LinkedIn.

[51:52] – Sign-off

Other Episodes in This Series:

Learntech: The Next Generation

Episodes on Related Topics:

The post AI, Data, and Optimism with Donald Clark appeared first on Leading Learning.

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