Gary Woodill

Learning Techologies: Motion Capture

Gary Woodill — Fri, 13 Jun 2008 03:29:21 +0000

Motion capture technology promises to speed up the process of developing animated avatars for immersive learning. Existing motion capture software works by tracking the path of a large number of visible markers placed all over the body. Because of the complexity of tracking so many points, motion capture software often gets confused and errors are produced. A new approach using marker-less software from a lab at Stanford University, promises to reduce the error rate, and does not need the actor to wear tight clothing. In fact, capturing the movement of clothing, such as the ruffle of a skirt, leads to more realistic animations. A downloadable paper and video, both entitled Performance Capture from Sparse Multiview Video, describes this new approach.

Multiple Metaphors for Learning

Gary Woodill — Tue, 10 Jun 2008 18:48:02 +0000

A recent article by Jacob Vakkayil in the academic journal Learning Inquiry (Vol. 2, 2008, pp. 13-27) is a good review of the various metaphors that surround the concept of learning. Each metaphor gives us some insight, and taken together they show what a complex concept learning really is. No one metaphor is “correct”, but each represents a different understanding. This makes subscribing to only one or a limited set of these metaphors a dangerous practice. As Lakoff and Johnson outlined in their book Metaphors We Live By, much of our understanding and communications are founded on base metaphors that are combined to achieve complex abstract concepts. Each metaphor has implications as to how we view knowledge and the processes of teaching.

Jacob Vakkayil is oriented towards organizational learning in this article, so his examples are particularly relevant to people in corporate training. The eight metaphors that he lists (with my comments) are:

Learning as transfer - implications: knowledge is portable stuff that can be passed around and the learner is a container
Learning as corrective change - implications: observable behaviors can be changed and the instructor needs to have objectives in terms of the desired end behaviors from the learner
Learning as computing - implications: the mind is a computer that processes large quantities of data and the learning is a process of reprogramming mental structures, scripts and algorithms
Learning as building connections - implications: the human brain is like a neural network where learning is the strengthening or weakening of pathways of neurons
Learning as self-organization - implications: humans are self-organizing adaptive systems that continuously produces its own components and organization in the context of being embodied, and embedded in a culture and history. Learning is the emergence of new knowledge based on all these contextual factors
Learning as propogation - implications: cultural ideas (”memes”) are transmitted through humans who act as hosts and transmitters of these ideas. Humans are robots under the evolutionary influence of both genes and memes.
Learning as coordination - implications: knowledge is distributed and doesn’t reside within any individual. It is partially held by each learner, and is found in collective artifacts made through collaboration
Learning as participation - implications: learning is also distributed, but is found in the social interaction among individual learners. Learning is always associated with a community, and happens through joint action

Each metaphor offers unique perspectives and, at the same time, limits understanding in various ways. Disagreements within the learning industry and its critics may be a result of each group talking past each other while using different metaphors. Change can happens through the introduction of “disrputive” metaphors that challenges old thinking and bridges the gap between conflicting metaphors.

This article is very useful for clarifying some of the dominant metaphors for learning in use today. An online copy of the article can be found here.

Post-biological intelligence

Gary Woodill — Mon, 09 Jun 2008 14:28:42 +0000

An article by Stephen J. Dick, NASA’s chief historian, (New Scientist, May 31, 2008) on the search for extraterrestrial intelligence (SETI) suggests that we view intelligence as the “smart” actions other biological creatures like us would carry out. He contends that our searches for extraterrestrial intelligence ignore the likelihood that intelligence in the universe has evolved “beyond biology”, towards what we currently call artificial intelligence (AI). If this has happened on other worlds, the process of cultural evolution has probably taken these societies in very different directions than ours. We may be dealing with cosmic snobs! Dick writes, “the intelligence principle renders it unlikely that post-biologicals would wish to communicate with embryonic biologicals such as humans, so we might be reduced to intercepting their communications.” Of course our current ideas of artificial intelligence may also be too primitive as a metaphor for post-biological intelligence, and “the differences between our minds and players may be so great that communication is impossible.” Dick expands on these themes in two books, The Biological Universe (Cambridge University Press, 1996), and The Living Universe (Rutgers University Press, 2004).

Slick Podcasts for Corporate Trainers

Gary Woodill — Tue, 06 May 2008 15:39:59 +0000

When I look at the literature on emerging learning technologies, I find that for the most part it is being produced and used by people in schools and universities. This is especially true for the latest technologies known as Web 2.0. Corporate training on the web still seems to be instructor led and course based with lots of multiple-choice tests.

So it is exciting to find examples that break out of this model. The Cascadia chapter of the American Society for Training and Development (ASTD) in Oregon and Southwest Washington has produced a slick set of podcasts for corporate trainers that rival professional radio shows. The half-hour podcasts consist of introductory music, conversations, interviews, and news about the chapter. In the latest episode, I was interviewed by chapter members Aaron Munter and Christine Martell about future trends in learning technologies. There are over 50 other podcasts available, produced by volunteer Richard Watson. The hosts are chatty and fun, and the interviews are informative and fast-paced. Try them, I think you’ll like what you hear.

Learning to Be Funny

Gary Woodill — Fri, 14 Mar 2008 16:11:32 +0000

A great comedian appears to be spontaneous, giving, and having a great time. In truth, most comedy acts are delivered by highly insecure people using carefully contrived and rehearsed material that has often taken years to develop. This is the lesson from watching Jerry Seinfeld in the documentary film Comedian, and from reading Steve Martin recent autobiography Born Standing Up: a comic’s life (New York: Scribner, 2007). In Comedian, Jerry Seinfeld is shown developing a new stand-up comedy routine by trying out new ”bits” at small clubs over a period of a year. After a year he has an hour or so of new material to deliver as a coherent “show”. We see him with his peer group, other comedians who are doing the same thing as Jerry. They give him feedback, share stories, and generally support each other, even though they are in a highly competitive business

Steve Martin’s route to fame and fortune is even more tortuous. He sums up the journey as follows: “I did stand-up comedy for eighteen years. Ten of those years were spent learning, four years were spent refining, and four were spent in wild success.” At the end of Martin’s success was burn-out, mental exhaustion, and a need to walk away to start a different career in film and writing.

Much of the learning being promoted in corporate training and the new learning technologies is based on memorizing things - what some have called surface learning. Deep learning requires years to acquire, engaged immersion in the world and lots of hard work.

Tools and Technologies to Support Collaborative Learning

Gary Woodill — Tue, 19 Feb 2008 16:15:56 +0000

I have just finished a report called Computer Supported Collaborative Learning: Tools and Technologies in which I try to enumerate all the different information technologies that can be used to support collaborative learning. In trying to make sense of the myriad of software packages available, I divided them into environments, networks, and tools.

I then divided each category into 6 sub-categories as follows:

Environments for Collaborative Learning
- Shared Computer Resources in Classrooms and Workplaces
- Online Collaborative Workspaces
- Web Conferencing Software with Collaboration Features
- Knowledge Collectives
- Collective Immersive Environments
- Collaborative Augmented Reality
Networks for Collaborative Learning
- Personal and FOAF Networks
- Group Forming Networks
- Social Mobile Networks
- Peer Sharing and Production Networks
- Community Computing Grids
- Self-Organizing Mesh Networks
Tools for Collaborative Learning
- Communications Tools
- Collaborative Process Tools
- Presence Tools
- Social Markup Tools - Annotation, Bookmarking, and Rating
- Project and Team Management Software
- Community Management Tools

I was able to find examples of technologies for collaborative learning in all of the above sub-categores. All classification systems are arbitrary, but my starting point for this one was the 2005 report from the Institute for the Future on Technologies of Cooperation, especially the concept map of the technologies on page 15.

5 Surprising Things about Computer Supported Collaborative Learning

Gary Woodill — Thu, 10 Jan 2008 02:38:35 +0000

In his 1999 book Collective Intelligence Pierre LÃ©vy observes that â€œno one knows everything, everyone knows something, all knowledge resides in humanity.â€ I thought I knew something about the field of Computer Supported Collaborative Learning (CSCL) because I’d been teaching a graduate class at the University of Toronto in the mid-1980s when Marlene Scardamelia and Carl Bereiter started a collaborative learning project with grade school children called CSILE. I saw the demos and read the theory, even though I was not directly involved with the project. CSILE was one of the earliest examples of purpose built environments to facilitate collaborative learning. (The CSCL label goes back to a conference in Italy in 1989 and is now the generic term that is used most in the field).

I’ve just finished a new research report on the application of CSCL in Training and Development (due out shortly), and realized that I really didn’t understand the concept of CSCL as deeply as I thought I knew it. In preparing this report, I encountered at least 5 surprisingÂ things about this topic that I want to share:

1. CSCL remains an academic field, still mostly centered on schools and universities. Of the more than 500 references to collaborative learning that I found, only about 20 dealt with corporate training and development. That doesn’t mean that collaborative learning doesn’t take place in training settings, but that almost all the research on CSCL has been about its application in school and post-secondary settings.

2. A parallel field of study, called Computer Supported Cooperative Work (CSCW), which also started in the 1980s, has developed very little research on learning or training. The surprising thing here is that both CSCL and CSCW each have their own books, journals, and conferences, but don’t seem to have ever seriously connected with each other. There are a few articles on learning in the CSCW literature, but mostly it is about office automation and cooperative work processes. I’d not even heard about CSCW until I undertook this research.

3. I was intrigued by the idea from Gerry Stahl at Drexel University that individual learning is mostly the result of group learning. In his recent book Group Cognition, Stahl concludes that individual learning may automatically take place within collaborative interactions. â€œIt may be that group learning often supplies an essential basis for individual learning, providing not only the cultural background, the motivational support and the interactional location but also an effective mechanism for ensuring individual learningâ€ (p. 274). This idea definitely needs more exploration, as does the distinction made by Stahl between individual learning and group cognition.

4. Most research on collaborative learning argues that it doesn’t happen just by putting people together in a room or a network, but requires a great deal of structure and intervention to make productive collaborative learning happen. While instructors do move away from direct presentation of materials to learners, theirÂ position in CSCL systems include scripting of roles and procedures for learners, and many other interventions including:

Modeling to illustrate performance standards and verbalize invisible processes
Coaching to observe and supervise students, thereby guiding them toward expert performance
Scaffolding and fading to support what learners cannot yet do and gradually removing that support as confidence is displayed
Questioning to request a verbal response from learners while supporting them with mental functions they cannot produce alone
Encouraging student articulation of their reasoning and problem-solving processes
Pushing student exploration and application of their problem-solving skills
Fostering student reflection and self-awareness (e.g., through performance replays)
Providing cognitive task structuring by explaining and organizing the task
Managing instruction with performance feedback and positive reinforcement
Using direct instruction to provide clarity, needed content, or missing information

This list, adapted from Bonk and Cunningham (1998), shows that the versions of CSCL being advocated in the literature have a much stronger role for instructors than I expected in my initial conceptualization of collaborative learning.Â

5. In addition to the need for intervention and structure, the literature shows a long list of issues that need to be dealt with in order to have successful collaborative learning. These include the development of trust among participants, motivating participants to engage with others, having participants learn methods of argumentation, creating an organizational memory as a repository of group ideas, leadership within the group, change management, creation of “presence” for online environments, lack of technical standards, and little agreement on how to assess the results of collaborative learning.

I’m not sure that computer supported collaborative learning needs to be that complicated, but that is what the literature is suggesting.

Ten Learning Technologies to Transform Training in 2008

Gary Woodill — Thu, 03 Jan 2008 15:06:23 +0000

During the past 2 months I have given workshops on emerging learning technologies in 6 locations in Canada and the United States. Most workshops were attended by 10 to 20 people, most of whom had developed at least one online course for their organization, but who were looking for what was coming next. Interestingly, only about 10% of the workshop participants were under 35. I know that because I would ask who had a Facebook account. Invariably, it was the one or two people in the group who were youngerÂ ”digital natives” who volunteered to show the group their Facebook account.

The rest of the group had heard of blogs and wikis, but had usually never tried them, not even to enter a comment into a blog. But, they were there because they knew they were being left behind. The workshop time was used to introduce group members to about 10 technologies emerging in corporate training, with a chance to actually try them out.

So whatÂ ten learning technologies should be the focus of my 2008 workshops and webinars? Here is my list (but I would love to hear yours):

1. Technologies of collaboration - wikis and teamspace software will grow in use in non-academic organizations, and the field ofÂ ”computer supported collaborative learning” (CSCL), now mostly found in schools and universities,Â will develop outside of academic settings, including corporate training.

2. Learning Games for Business - This field is old news to die-hard gamers, but just being discovered by most people in corporate training. Most of the participants inÂ our workshops and conference in September tried a training game for the first time. Games are being used both for training and for recruitment of a new generation of employees.

3. Distributed Computing Technologies - I introduce “mashups” and Service Oriented Architecture (SOA) to workshop participants because this is a fundamental shift in how we view “websites”. Instead of sites, we need to think of a group of agents harvesting and gathering content and applications from many locations, and delivering it as a dynamic personal mix based on a user’s profile and needs.

4. Embedded Learning Technologies - computing power is already almost everywhere, from toilet seats to cell phones. I show the “hug shirt” (it vibrates and squeezes you in response to a friend’s phone message) as an example of the convergence of affective computing, wearable computing, mobile computing, hapticsÂ and teledildonics. One person at last year’s ASTD conference asked me if a “kick in the ass pants” was being developed. Hmm…

5. Multisensory input devices - Computing is mostly a visual and auditory experience. The use of touch (”haptics”) is rapidly becoming more common, led by the interace for Apple’s iPhone and Microsoft Surface technology. Watch for levers, gloves and places to put your finger in new training applications this year. While haptics will lead the way, technologies for the senses of taste and smell are not that far behind.

6. Rollout Flexible Screens for Mobile Devices - the ability to reach employees with information as they need it through mobile devices is very attractive to many training departments, but is held back by the small screens and keyboards. The introduction of flexible rollout screens (”digital paper”), with touch capabilities (”digital ink”), gesture recognition,Â and speech recognition for mobile devicesÂ may break that logjam. I know that this has been forecast for the past ten years, but now that it is in the Economist, it must really be happening.

7. Social Bookmarking and Automatic Synthesis of Tags - As people add tags to just about everything, a new set of technologies that gathers related tags and makes something out of them will construct some amazing synthetic worlds. Already the millions of photographs on Flickr.com are being used to develop 3D models of buildings and landscapes, through such applications as Photosynth.

8. Personalization Technologies - software for automatically constructing personal profiles beased on e-mail, web use trails, and user input is now available and is being used in recommender systems (e.g., Amazon), dynamic museum exhibits and information systems that change for each user, and adaptive tutoring systems. Watch for training to become more personalized.

9. Visualization of Complexity - computer data systems can continuously compile huge amounts of information. The problem is what to do with it. Because of our strong visual processing abilities, transforming large and complex data sets into pictures may be the best way for us to grasp its meaning. See www.visualcomplexity.com for lots of examples.

10. Location-basedÂ Augmented RealityÂ - the Global Positioning System (GPS) will track where you are through cell phones and other GPS devices, while vast amounts of data stored in Geographic Information Systems and applications such as Google Earth will drive augmented reality applications to add to your experience of any location on the globe. This information will be superimposed on the world as you move through it.

Those are my 10 learning teachnologies with great potential to shake up training in the coming year. Let me know what you think.

Mesh Networks Bring Broadband to Rural Areas

Gary Woodill — Wed, 21 Nov 2007 05:14:32 +0000

In late August I moved to a country house looking over 23 mile long Rice Lake, 10 km North of Cobourg, Ontario, Canada. The only problem was the fact that the area did not have high-speed internet, a must for someone working from home doing research.

Â Consequently, I had to suffer through 6 weeks of a “dialup” internet connection, and had to go to town just to be able to download large files. What a pain!

We tend to forget that millions of people still get their internet through less than adequate pipes, at a time when the sizes of files that people want to see and download continue to go up. For me, using dialup was equivalent to regressing back about 10 years, in terms of speed of access to what has become an essential service.

Â I investigated using a satellite hook-up, but, while faster than dialup, it has delays as your antenna communicates with the satellite. And, it is only relatively fast in downloading, remaining painfully slow for uploading files.

Help came in the form of a new point-to-point wireless “mesh network”Â that usesÂ radio-based repeater stations with a line of site range of about 15 miles. The particular technology used in my village is from Tranzeo, and my provider is Airnet, which bounces a digital signal in from Cobourg to a group of towers and rooftops along the lake and other rural areas of Northumberland County. For those who are more technically minded, Tranzeo has a white paper that illustrates the network setup with lots of diagrams and tables.

Here is a photo of the radio/antenna that is just outside my office window. My experience of the service is that this is the fastest internet connection that I have used to date. While the weather can cause problems, in general it is a great technology that brings high speed internet to areas that the big providers won’t touch.

For me, it brings me back up to speed…

Guess Who’s Coming to Santa Clara…

Gary Woodill — Tue, 07 Aug 2007 18:24:15 +0000

The Innovations in Learning Conference in September in Santa Clara is the first conference that Brandon Hall Research has organized, and so we are very interested in which groups in the training field will be represented there. Based on an analysis of the first 200 delegates to register, here is a breakdown of the demographics of the group, based on their type of job within their organizations:

Executives â€“ CEO/President, CLO, VP, Partner or Chair â€“ 10%

Directors, Managers and Coordinators â€“ 47%

Programmers or Developers â€“ 13%

Instructional Designers â€“ 10%

Trainers â€“ 6%

Consultants â€“ 5%

HR Staff â€“ 3%

Other â€“ 6%

In terms of geography:

Delegates from the USA â€“ 85%

Delegates from Canada â€“ 10%

Delegates from other countries â€“ 5%

To me that indicates that decision makers, both executives and middle management, of American companies are interested in what is happening in the field of emerging learning technologies. This is also born out by the fact that as many delegates have signed up for my pre-conference workshop on Twenty Technologies to Transform Training as have signed up for the other four pre-conference workshops combined.Â