29 October 2010

Learning in Learning Networks (2)

In a previous post I concluded that the non-formal learning that is a prime characteristic of Learning Networks may well be an internally inconsistent notion. Either non-formality points to the absence of the structuring that teachers provide and then the question arises of whether non-formal learning is learning at all; or teachers are allowed in to develop learning content and learning tasks, provide assistance, etc., but then non-formal learning starts to coincide with formal learning. The problem can be resolved by looking more carefully at the dichotomy of formal and non-formal. The key is to differentiate between learning as an activity and the contexts in which this takes place. To make sure this distinction is crystal clear, I conceive of learning as an activity people undertake to update or extend their range of beliefs and abilities. In order to learn, they need a context, an environment, that provides them with the right kind of stimuli to learn. The problem arises because we tend to think that teachers should be part of that environment as only they can ensure that learning is effective, efficient and satisfactory.

To make my point, I use of a distinction that Suzanne Verdonschot in her thesis called Learning to innovate uses; she synthesizes the ideas of a variety of other authors to arrive at this distinction. Suzanne distinguishes three kinds of learning:
  1. learning that prepares one for the workplace (training or acquisition learning)
  2. learning that helps one better to perform at the workplace (learning sensu stricto or participation learning
  3. learning that is needed to resolve novel problems (productive or creative learning)
Her context is one of learning at the workplace, but that does not detract from a more general usefulness. Since Learning Networks target professional development, her distinction is certainly useful for the present discussion.

Training (acquisition learning) is associated with clear-cut tasks that need to be fulfilled and with carefully described competences that one needs to acquire to fulfill those tasks. Competence gaps that people have with respect to a particular job situation can therefore easily be identified, and instructional-design-type methods can be deployed to design learning content and tasks that help people to fill these gaps. Such environments are rather schoollike in that there is an important role for teachers who design and develop the learning environment. Such an approach, moreover, is possible, because of the relative immutability of the situation: the work tasks are known, the competences needed to carry them out also, so learning tasks and content may be developed in advance and will remain useful for some time to come. If anything, this kind of learning may be described as formal, even though it still differs from the archetypal school-based learning by children and adolescents. (Parenthetically, children and adolescents learn not merely to prepare for the workplace, enculturation and socialisation are important other functions.)

Learning in a narrow sense (participation learning) is what one does on the job. Although the tasks to be carried out do not change fundamentally, there's always room for improvement; procedures may be optimized, services may be fine-tuned, products may be enhanced. A social setting with colleagues is crucial for this kind of learning to occur. Communities of practice is a term that comes to mind immediately and the example of maintenance personnel that John Seely Brown and Paul Duguid give in their book The Social Life of Information (p. 99 et seq.) quite well illustrates this kind of learning. It cannot be planned ahead nor does it lend itself to competence-gap-type of analyses as it is not known beforehand what needs to be learned. Although it is still individuals who learn, it is the community which provides their learning environment. The structuring comes about through the way their work is organized, such as through the early-morning dispatch meetings with a cup of coffee that Brown and Duguid mention. This kind of learning takes place in non-formal context, as there are no curricula, no lecture time-tables, no teachers, only colleagues who may occasionally act as teachers.

The third kind of learning is yet different. It can best be described as 'working and thereby learning'. Were in the previous kinds at least the work tasks stable, we now even do away with that assumption. Indeed, the work tasks are the problem as they have to be replaced by other ones in order to create novel products, services or procedures. Clearly, the kind of learning that talks competences is no use here. To be sure, competences matter, but learning tasks to acquire those cannot be defined. One doesn't know the prospective work tasks, let alone the learning tasks (and associated competences). (The only exception may be meta-competences such as being able to solve problems, to collaborate and communicate, to guide one's own learning, etc.) This kind of learning is described as productive or creative learning as at its heart lies the need to produce or create new knowledge. Although it is social in nature, the notion of a community of practice does not apply. Such communities consist of relatively stable groups of people, where creative learning requires inputs from new people, even though one may not yet know from whom! Productive learning thus thrives on a networked approach, one in which a great many people with a great many different backgrounds are available for collaboration. The network forms a valuable source upon which one can draw for learning creatively and productively and thus be innovative. The idSpace project, discussed in a previous post, was about this kind of learning. Clearly, this is the kind of learning that George Siemens with his connectivist view targets: even though learning is not equivalent to making and breaking of connections, making and breaking them amounts to creating a learning environment for oneself. Clearly also, this kind of learning demands non-formal contexts.

Back to Learning Networks. As argued, they encompass quite naturally productive learning. In so far as a Learning Network consists of an ensemble of relatively stable, established communities of practice, it also supports participation learning. Either way, Learning Networks are non-formal learning environments. Now back to the original problem of how to design a Learning Network as an environment that still allows one to learn efficiently, effectively and satisfactorily. This problem still stands. Suzanne Verdonschot's thesis is one long attempt to develop design principles for productive learning environments. She lists 11 of them but concludes that they 'do not have a prescriptive function, [... but] present various perspectives that offer the designer starting points for the design of interventions.' (ibid. p. 240). This is much better than nothing, but can of course not be equated with the tried and tested principles of instructional design. So, the logical problem of being inconsistent when talking about non-formal learning in Learning Networks has been resolved, but a practical problem has come in its place, and not a simple one at that!

15 September 2010

Limited data retention through selective data degradation

The social web can only thrive if its participants are willing to share personal data, data about themselves, with each other. So, you have an account with some social network (Twitter, del.ico.us, LinkedIn, etc) in order to allow others to read your Tweets, peruse your presentations or, quite generally, find out who you are and what you do. With the advent of the semantic web, of systems that can make inferences on the basis of the data that are fed to them, this is all the more true. Individual users profit from the services that the web offers to them, often for free; the service providers profit, mainly from the advertisements that accompany their services. Although there are other business models, this is the prevailing one, it seems.

So far so good then. But what if service providers sell the data they have acquired in the course of their business to other providers; or worse even, what if these data end up in the hand of others because of clumsiness (a stolen USB stick, a lost laptop) or criminal intent (hacking servers, bribing personel)? Admittedly, you may decide to shut down your Facebook account or give up Twittering, but this freedom of choice is absent for many services. What about your loyalty card with your favourite grocery store, which not only registers your purchasing behaviour but also gives you access to sizeable discounts; or your public transportation travel pass, a system recently introduced in The Netherlands, which allows you to travel throughout the country with one card but registers routes and start and end times in its database; or a road use system installed in your car which helps prevent traffic congestions but does so by logging your car's GPS track data in its central database? In each of these examples - and many more can easily be given - data about a person are logged into a database and it is not transparent to the data providing individual what the associated privacy risks are.

In 1981 the states that jointly form the European Council signed a ‘Convention for the Protection of Individuals with regard to Automatic Processing of Personal Data’. Among other things, it stipulates that no more data may be stored than needed for a particular, identified purpose, and that those data may not be kept for longer than strictly needed. The lack of transparency compels the individual to simply trust the database manager to abide by these rules. Experience teaches us that often this trust is misguided, even if we ignore cases of intentional theft and accidental loss of data. The issue of whom to trust with what data is a complex one. It touches upon the closely related questions of what data to collect and whom to allow to access them. The other day, I read a PhD thesis that sheds an interesting light on the first one of these questions (Harold J.W. van Heerde (2010) Privacy-aware data management by means of data degradation; making private data less sensitive over time. Universiteit Twente).

Ignoring for now the possibility to grant differential access rights, someone can decide to make her particular personal data available or decide not to do so. A LinkedIn profile may contain a photo but need not. Something similar goes for the data that are collected through someone's public transport travel pass. If one uses the pass, route and time data will be collected and stored. Could a user still decide to remove or replace her photo, the storage of travel data is fully beyond her control. The point to note here is that the decisions are all-or-none decisions. Someone’s photo is there or it isn’t, travel data or logged or aren’t. There is no middle ground. Van Heerde shows that a sensible middle ground does exist. He introduces a limited retention principle, meaning that data degrade over time. So, the public transportation database may remain fully intact for a month to allow sending out bills. The data may subsequently be degraded to the level of the route and day of the week someone has travelled to allow sending out special offers. This level of detail is maintained, say, for a year. After one year only the cumulative frequency of use or routes per day of the week, decoupled from the individual, are still available. This still allows the statistical analysis of travel data, for planning purposes for instance. Data degradation allows for a more subtle marriage of the interests of the individual (new, better, cheaper services) with those of the service provider (a more efficient and effective business). Of course, there are all sorts of theoretical and practical problems to be dealt with. Van Heerde discusses many of them, he also suggests how to solve them. For me, the importance of his contribution is his description of how one may come one step closer to heeding the European Council's admonition only to store just enough data for just long enough. This is in the interest of both web service users (aren't we all) and web service providers.

23 July 2010

Learning in Learning Networks

With a group of people at the Centre for Learning Sciences and Technologies at the Open Universiteit (Netherlands), I am doing research on so-called Learning Networks. Networked Learning or Learning (in) Networks is a popular catch phrase these days. As long ago as 1995 Linda Harasim and colleagues already dubbed their book Learning Networks: A field guide to teaching and learning online, and this May the fifth Networked Learning Conference was held in the city of Aalborg in Denmark. Inevitably the notion of a Learning Network harbours a great many different opinions on what it actually is. For Harasim cs, any form of learning and teaching for which networks (the Internet) were used, fitted the bill. The visitors of the Networked Learning Conference seemed very much interested in pedagogies for networked learning and in positioning networked learning properly with respect to such theories as Engeström's version of Activity Theory. And of course, ours is yet a different take. I don't necessarily see this is a problem: conceptual growth besides theory development is the hallmark of a growing and evolving scientific field.

For us, Learning Networks are online, social networks that have been designed to facilitate non-formal learning. Here, in line with what is customary, non-formal learning is like formal learning intentional (in contract with informal or accidental learning). However, it differs from formal learning in that it rigorously puts the demands of the learner centre stage. Therefore, it does not necessarily rely on such institutions as curricula, experts in the capacity of teachers, cohorts, schools as buildings or institutions, etc. So far, so good.

This definition of a Learning Network may seem rather weak. After all, it only specifies that the network should be designed in a particular way, not how that should be done. In terms of the how, it only determines that it should not contain such ingredients as cohorts as curricula. Yet, we feel this definition is an apt one as it serves as a workable starting point for empirical research into the how question. What network constellations work in the sense of allowing non-formal learners to learn, and what not?

There is a large variety research questions that we try to solve (see publications). A particularly important set relates to the role competences and competence taxonomies should play, for instance for inventorying someone's prior competences or for charting out someone's learning objectives. Since Learning Networks are online networks, another set of questions is related to appropriate software tools that should help the inhabitants of the Learning Network to learn collectively. The assumption is that being united in such an online network is an important asset, something that helps learning. However, a typical learner may only be acquainted with a few of his peers, if any. So what, in a social-network analytical terms, is a good mix of weakly and strongly linked people, and how can such a mix arise?

These questions are all about how to dress up, to tool the Learning Network. But there is one question that precedes all these: how do individual people learn in a Learning Network, how do they acquire the competences they need? In a recent paper on Connectivism in the Enterprise, George Siemens defines learning as 'the process of forming and pruning connections through social and technological networks'. Although I obviously have no quarrel with the network part, it cannot be that learning only is a matter of forming and pruning links. Ultimately, it is individuals who learn or do not learn. Networks may play a part in that, indeed I argue they should, but it is individuals who decide to make or break links and their decisions hang on what fosters their learning, which is different than being their learning. So, how can people be helped to learn in a Learning Network?

If anything, formal learning is teacher led. This means that teachers develop activities, in which their students engage with their help, through which the students learn; they organise the times and the order of engagements. A lot has been written about this by people such as Robert Gagné (nine events of instruction), Dave Merrill (first principles of instruction) and Jeroen van Merriënboer (4 components instructional design model), to mention a few. All have in common that they prescribe how what it is that needs to be learned should be 'packaged' so as to opimise learning effectiveness (what you learn), learning efficiency (at what costs you learn) and perhaps learner satisfaction.

Non-formal learning, on the other hand, is learner led. So students themselves should somehow organise their own learning. But how are we to understand that? As argued, making and breaking of links with fellow-learners may contribute to learning, it cannot be learning. Merely consuming content cannot be equated with learning either. After all, we do not lock up our students in a library for a few years, wish them all the best, and have them sit in on exam at the end. The various instructional principles and theories we have developed, including those just mentioned, indicate that there are more sensible ways to learn than being flooded with content. Put differently, if learners themselves develop learning activities, decide what learning activities to engage in, when and with whom to do so, how can they be sure they do so most effectively, efficiently and satisfactorily? This is the design question. Also, where do these learning activities come from in the first place? This is the library with books or an online network with content resources is not the same as a collection of learning activities. Perhaps teachers should develop learning activities according to sound instructional design principles and subsequently make them available to learners, for instance as open educational resources. This is the development question. But if teachers interfere in both the developing of learning activities and their structured provision, one could well argue that non-formal learning is teacher led after all. According to that argument, non-formal learning is an internally inconsistent notion: either it isn't learning or it is formal (teacher-led) learning in disguise!

I have no ready-made answer, I do have a couple of ideas. I'll discuss those in a next installment. Meanwhile, suggestions are welcome.


Note added after publication: In a follow-up post, I further develop the argument, solving the apparent logical problem of internal inconsistency, but replacing it with a practical one.

19 May 2010

idSpace project successfully completed

idSpace is an EU FP7 project that started April 1st, 2008, ran for two years and just got its (informal) final ok from the EU reviewers. This is both something cheerful and something sad. Cheerful because we got the official recognition for a job well done. Sad because there's no denying now anymore that the project really is over and that we're really out of funds to continue our R&D and software development work. What was the project about? To quote from its website, The ultimate goal of the idSpace project was to build ... the idSpace environment that should come to the aid of distributed teams of innovators who want to collaborate on product design, thereby making use of earlier results achieved by themselves or even others. So what it tries to do is not so much to make people more creative per se, but to provide them with a software platform in which they can achieve their creative potentials to the full. The environment does so by offering the innovators a choice of (as yet only a few) scenarios for sharing ideas and related knowledge, a module for entering ideas and connecting them in graphs, a variety of context-sensitive recommendations on for instance relevant new group members and helpful resources. Admittedly, this all sounds a bit complicated and you do indeed need a knowledgeable moderator to steer the whole collaborative innovation process, but we are convinced there's a lot of potential here. The platform really still is a prototype, so it needs improvement in many respects. But even in its present state it is quite useable. To help users and to satisfy the curiosity of prospective users, an extensive online user guide and a series of tutorials have been created. So far so good. But how can the potential we believe the platform has be unleashed? How can its further development be financed and how can further R&D work, that provides the input for future improvements, be guaranteed? So far we've been able to come up with a rather predictable answer: new project applications. However, even though this may in principle finance R&D work, new proposals require novel lines of enquiry, while we really only want to continue along the already familiar lines. Also, the platform itself needs to prove its usefulness in actual practice, for which its useability needs to be maximised first, something for which R&D proposals typically do not pay. We need to be more imaginative, more creative, if you like. How about turning this into an open source project so that others can contribute to the platform development too? How about tapping into regional innovation funds? How about even obtaining private funding? Or, to add a wild suggestion, how about asking for funds at such sites as Kickstarter (see the Diaspora project, an attempt to build an open Facebook version, for how easily funds can be raised if the cause is right). Many options, no firm answers, but certainly exciting opportunities. And of course, all suggestions are welcome!