We want to support this reflection process through contextualized capturing of learning experiences during everyday work activities, e.g., through mobile apps and sensors capturing affective state and allowing individual to annotate their experiences on entirely personal level. Aggregated experiences can be shared with others to support a group reflection process, the results of which should feed into an organizational reflection and improvement process.

We invite contributions from the areas of psychology, sociology, computer science, CSCW, economics, among others.

The kick-off took place in Røros, a small town in the mountains of Norway, which is a World Cultural Heritage because it has been shaped by its several hundred years of copper mining. It is a beautiful location, but for most of us this has also represented a new personal record in terms of temperature. We had a small tour to the “smelte” in the evening at –34°C, and even during the day, the temperatures were around -24°C.

Here is now the video on YouTube:

• Lack of societal awareness about the problems that demand for AAL solutions (we will not be able to deliver care in the same way as today as there will be many more older people than now). This leads to a lack of political support.
• Lack of awareness by the immediate carers about the possibilities, availability, and cost/benefits of AAL solutions and potentially threatening change of the role of the carer
• Too high a pace of innovation, which leads to hesistant investments
• Immaturity of the technology as to practical usability and cost effectiveness
• Lack of direct end customer approach (start with the more prosperous as early adopters)

Probably it is a mixture of all of it, but I found particularly the first one convincing as it changes the perspective: we now longer ask what added-value this technology can deliver in addition to care services and informal carers, but we ask how can we keep up a similar level of care for a much larger number of older people with fewer younger carers.

This week we were at the Professional Training Facts 2009 in Stuttgart (see here for a summary of MATURE activities at this event). This was a great opportunity to think and discuss about topics around competence development in company. One trend I have spotted was the increasing importance of indicators for competence development and the incorporation of those indicators into management instruments like management-by-objectives. At first sight, this always seems to be a good idea to “professionalize” the learning element in a company by making it measurable. This originates in the assumption that “you cannot manage what you cannot measure”, which is probably true when you want to manage things. The approach promises transparency and can be a step towards calculating an ROI for learning. The big problem, however, does not lie in the approach of defining indicators and measuring them, but rather in the concrete indicators themselves. These indicators do not naturally naturally derive from the topic at hand, but are actually always bound to a notion of an ideal state; they contain the statement: you should have a high score in this indicator – this would be the best option. This is not bad as such, but this fact is rarely reflected, especially because this ideal state is actually context-dependent. It can be different for large vs. small organizations, for innovation-focused vs. efficiency-focused organizations, for service vs. production etc. What happens is that somebody defines (probably with good reasons) a certain set of indicators, and other simply take those indicators and apply them without questioning their value for their context.

What does this have to do with knowledge and knowledge maturing? This has three aspects:

• This “ideal state” conception as such is a body of knowledge, and it has to be carefully examine if the underlying knowledge about the ideal state is has reached a level of maturity that allows for a standardization in which you usually simply take things and apply them (like, e.g., for many financial indicators). Or if we are on a lower level of maturity and have to develop from there our own answer to the question “what is the ideal state”. In this learning and maturing process we have to learn about the contextual factors that differentiate us from others. And even if we take and apply standardized things, we should allow and encourage questioning usefulness at any time.
• Indicators are not only about measuring, they are about management and guidance. They aim at changing the behaviour by explicitly or implictly encouraging to become “better”. Even if we know sufficiently about the ideal state, do we know enough how a certain set of indicators (potentially tied together with a complex formula) influences the behaviour? Is our knowledge about that mature enough to make them the basis for formalized instruments (like reward schemes, but also career decisions)? Can we differentiate between correlations and causal relationships? Can we separate external factors? Or should be modest enough to consider them what they are: indicators that measure something, but not the wealth of reality, and use them as a reflection instrument – and in the end maybe come to the conclusion that they measure nothing of interest.
• We are currently researching indicators for knowledge maturing both in the empirical and the technical-conceptual strand of the MATURE project. We should be aware that indicators always derive from a concept of ideal state, which is difficult to envision as a whole. So we will base those indicators based on our pre-conceptions (which has a lot to do with our value systems) – and we should carefully reflect on this problem.

As a conclusion: measuring can be very helpful for many aspects, also on the soft side, but we should understanding the development and application of such measuring instruments as a collaborative learning process which should involve many. Then this process and its result can be also a good guidance instrument.

Here is also the position paper.

One of my main points was that we need to look at the use cases and their specific requirements as many of the misunderstandings come from the implicit assumption of a certain use case. Our initial analysis of use cases is reported here:

Simone Braun, Christine Kunzmann, Andreas Schmidt
People Tagging & Ontology Maturing: Towards Collaborative Competence Management
In: David Randall and Pascal Salembier (eds.): From CSCW to Web2.0: European Developments in Collaborative Design Selected Papers from COOP08, Computer Supported Cooperative Work vol. , Springer, 2010

Some use cases, like people finding, only rely on very weak notions of interests, while others – like career planning and rewarding schemes – rely on sound competency definitions. This is very important to understand – because all of them tend to speak of competencies. This also helps to understand why in some cases >700 competencies are appropriate, and in others 20 might be sufficient.

For a general conceptual model, I have pointed out the following challenges:

• Competencies are cultural abstractions
• Competency definitions are implicitly contextualized and a certain degree of ambiguity will always remain.
• Competency definitions are purpose-driven conceptualizations
• Competencies are time-dependent conceptualizations

I am in the lucky situation that this is just the starting point for my further work. Within the MATURE project, I can continue my research on knowledge maturing and on competency-oriented approaches. Additionally, it has turned out that the context management approach is ideal also for the domain of ambient-assisted living (AAL), which has been shown in SOPRANO, and will continue in UniversAAL. Context-aware system behaviour in context of adaptive user interfaces has been the subject in AGENT-DYSL and will continue to be explored in the upcoming myUI.

• In the upcoming AAL project universAAL (an Integrating Project – IP) we aim to develop our SOPRANO Ambient middleware (soon to be release as openAAL – an open source middleware for ambient assisted living) to become part of a reference architecture and open source implementation of a universal AAL infrastructure, together with a promising consortium of 18 partners.
• Within myUI (a STREP), we aim at “synergistic user modeling”, i.e., device-independent capturing of the user’s context so that we can more easily engineer adaptive user interfaces for various devices, particularly for users with special needs, like the elderly, but also others.

I am already looking forward to those projects, which will probably start in the first quarter 2010, although this will again mean an increased number of travels (which I could successfully reduce in 2009).

On the other side, the event hosted the kick-off event for the Special Interest Group on Professional Learning (www.sig-protel.eu), which tries to increase the visibility of the topic on a European level, first by better networking among the concerned European research projects like MATURE, APOSDLE, ROLE, and others. In the discussion, it has turned out that despite the ambiguity of the term, professional learning seems to be umbrella term for KM and workplace learning. This SIG is a promising sign for a maturing community.

This year, Christine and I were giving a talk on integrating motivational aspects into the design of informal learning support, which reported on our findings on how to integrating motivational measures into tools for informal learning (the paper is available from here). Christine has done most of the work in ethnographic studies and their analysis. Currently, together with our colleague Athanasios, they are struggling to integrate their ideas into the four demonstrators of MATURE Year 2 demonstrators.