About formal and informal (non-formal) learning

Discussions abound about how to properly differentiate formal and informal learning. To make things even more complicated, some throw in the notion of non-formal learning as a further refinement. On the one hand, the distinction has been made loosely to differentiate between learning in schools (formal) and all the other learning (informal). As long as you don't think to deeply, this works. However, now that some want to start theorizing about informal learning (workplace learning, professional learning, ...) and environments are claimed to be developed for it (such as MOOCs), too loose a definition won't do anymore. I will make a suggestion here for a sharp distinction that is simple to apply yet allows us to continue most of the conversations about formal and informal learning that we have engaged in.

Although my intention is to make things simpler, I want add one more term before tackling the formal and informal divide. I want to distinguish between learning that is intentional and learning that isn't. The latter kind I call accidental learning, it is the kind of learning we cannot refrain from doing even though we do not set out explicitly to learn something. It refers to for instance making a mental map of a route you are walking in an unknown city or to picking up some interesting tidbit while overhearing a conversation. It is the kind of learning that made us as a species successful (in terms of sheer numbers, not necessarily in any other sense). Formal and informal learning are both intentional because people explicitly want to learn something and make a conscious effort to do so. Eraut (2004, Informal learning in the workplace) calls this implicit learning.

Now on to the formal. Formal learning is all learning that involves a (social) contract between a learner and an (educational) institution. This could be a school (if it is about pupils and students) or a training institute (if it is about professionals). The contract implies that the learner hands over her responsibility for her learning trajectory to another party. That party employs people (teachers) and has all sort of policies in place (curricula, assessment routines, remediation rules, etc.) to honour the contract. Crucially, the contract only means that the institution will make a sincere effort to let the contractee (student) learn, it gives no guarantees about learning outcomes in terms of diplomas, etc. Finally, it is a social contract as other parties tend to be involved, such as governments who take an interest in providing an initial education for  their young people and lifelong learning opportunities for the labour force; or a company or association of companies in a particular sector which wants to provide training opportunities to its employees. Informal learning now is defined by exclusion: all intentional learning that is not formal is informal. From this it already follows that informal learning comes in many kinds, some of which will resemble formal learning more than others. However, it is the absence of a contract - implicit as at schools or explicit as often with training - that makes the difference.

Informal learning thus includes learning that professionals do at their workplace, that students do at university next to their curriculum-based lecture sessions, that ordinary people do when surfing the web for information on a medical condition, that ... I'm not sure it makes sense to subdivide informal learning, but time will tell. Oh, and non-formal learning is synonymous with informal learning, at least for the time being.

Strictly distinguishing formal from informal learning implies that I disagree with Eraut (2004) who maintains that all dichotomies are signs of lazy thinking; many are but certainly not all. It also follows that I disagree with the 2003 report by Colley, Hodkinson & Malcom  (Informality and formality in learning: a report for the Learning and Skills Research Centre), who see formal and informal as attributes of situations. This too would result in a continuum of informal and formal. However, I do agree with them that the distinction does not extend to theories of learning or kinds of knowledge. The formal-informal dichotomy is about learning situations or settings, in which either the responsibility for one's learning trajectory is contractually handed over to others or isn't. The way people learn (learning theories) and what it is they learn (conceptions of knowledge) are independent of this. The benefit of this way of differentiating formal from informal learning is that it does not affect our theories nor our epistemologies, we may keep theorizing about learning irrespective of the setting. So we may remain seeing learning as a mix of knowledge acquisition through transfer and through participation, even though emphases may differ.

Some consequences. Is Connectivism about formal or about informal learning? Assuming that we exactly know what Connectivism is and in so far it is a learning theory, it would be equally applicable to formal and informal learning. And, indeed, we see that Connectivism is embraced by teachers who want to set up PLEs for the students, or help them do so. In connectivist terms, the PLE is what they have learnt. But equally, cMOOCS are being set up by George Siemens and Steven Downs where people from all over the world learn together without any institutional ties. How about xMOOCs, are they then environments for formal learning? My guess would be that they are, although the ties between the student and the institution (Coursera, Udacity, MIT, ...) are very loose indeed. From this it follows that the even broader category of networked learning suits both formal and informal learning, although the way it is implemented in a particular situation of course differs between both learning settings.

Comments added after publication:

• I wrote a follow-up post in which I also react to the comments by Jay and Nick. (September 6, 2012)
• "But Eric Roberts, professor of computer science [at Stanford] and a frequent critic of online learning, said there might not be as much enthusiasm [for online learning] as has been suggested, and he said he feared the innovations could "change the nature of the social contract" of the university." From meeting notes at Stanford on online learning. What is relevant in the present context of course is the mentioning of a social contract. (October 28, 2012)

Setup for a small online course, some lessons learnt

This spring, I taught an online course for some 10 doctoral students, most in Switzerland, some as far away as Mozambique. The topic was technologies for informal learning, and it was part of a larger series, called Cross-FIELD (cross-fertilization between formal and informal Learning through Digital technologies) and set up by three  universities in Switzerland. But that is not what I want to write about. The format of the course is, though. When asked to do this, the request was to give an online seminar on informal learning, but I thought it would be a little more exciting if I were to make things more social, more multi-way interactive than is customary in a seminar. After all, when learning about informal learning it would be nice to experience it to some extent as well. I here want to share some thoughts about how effective this format has been in my opinion.

How as the course set up? 

First and foremost, I wanted to make sure the students would not just consume, but also produce something. Being doctors of philosophy in the making, I felt writing a short (1500 words) essay would be most appropriate as a means to close off the course. The choice of a subject was only constrained in two ways: a) informal learning had someone to feature in it, b) they could either write a conceptual paper or write a persona and discuss what informal learning meant for that fictitious person. This way, I could also ensure the experience would be maximally useful for their doctoral work. Since the group was small, I could afford to read the essays and provide feedback to them. And, of course, I hoped to also learn something myself along the way.

Second, I wanted them to have discussions, with me and among the group members. Informal learning being a concept with mostly negative definitions (i.e. anything that is not formal learning) - which according to all the books on proper definition is to be avoided, and concept formation being one of the hallmarks of scientific progress, I felt budding academics needed to engage in discussions about the topic. This way they could get a feel for how to discuss conceptual matters and, hopefully, both learn how complex the question is and how you go about contributing to such a conceptual discussion. So, I ended up having three online seminars in the course as a whole, at weekly intervals. The first seminar was devoted to the pedagogical challenges of informal learning. As a preparation, I gave them some stuff to read: a chapter from a planned book as well as a blog post of mine. The second online seminar was set up similarly (including a new blog post) and covered the technological challenges of informal learning.  In the third and final one the students had to discuss the topic that they wanted to write about, so their peers could comment on their plans. To help them prepare, I wrote a blog post with some general recommendations, for instance about design as a research method. After that third session I wrote a final blog post with some suggestions on how to profit from your peers during the writing process.

Being an online course, the events were structured via my blog posts. Each one had some housekeeping, there also was a welcome post in the very beginning which headed of the course. E-mail was used throughout, I even set up Google group to make it easier to send out alerts to everyone (url for the Flasmeeting for instance). However, I tried to limit the use of email to inevitable personal messages only ('can't make it to the next semiar'). All online seminars lasted  60 - 90 minutes. I used Flashmeeting as a technical infrastructure. For who doesn't know this, it is similar to Adobe Connect; people take turns to speak, the routing is done by a moderator, the conversation can be recorded, you can also exchange files and use chat as a back channel. I set up a private group in Mendeley, in which I shared the papers I wanted them to read and papers I recommened them to read. I also pointed them to a public group in Mendeley on networked learning, which I moderate and where they could find more general background literature. I urged students to Twitter about their experiences during the four weeks that the course lasted and in particular in the final writing week, using a specific hashtag. And, finally, I suggested they use Google docs, for their writing, so they could read each others' works in progress. I toyed with the idea of also giving my comments on the Google doc version of their papers, but ultimately decided against that as my comments would then be public. The students deserved to receive these in private, which would also allow me to be more  frank in my commenting.

Did it work?

Some things did work, others didn't. Going over the technologies I used (marked in italics in the previous paragraph), technically everything worked with the exception of Flashmeeting on one occasion; but this was entirely due to a scheduling mistake of mine. The blog posts and emails served their communicative functions, although I would have like some more comments on the posts. The same goes for the seminars. They worked but I would have liked them to be a little more interactive. The Mendeley groups were used, Twitter was hardly used. Some did use Google docs for their writing, others did not.

So, were the students better equipped sensibly to discuss informal learning? I don't know about the 'better', having no comparison really. But some said so and the quality of their papers was generally speaking good. Allowing them to either conduct a conceptual discussion or write a persona, was a good decision in retrospect as it accommodated the more theoretically and more practically inclined students. This no doubt contributed to the quality of the papers and, of course, allowed them to profit from the seminar in a way that suited their individual PhD projects best (a key tenet of informal learning, make it relevant for yourself).

Did I succeed in making things interactive? Not to the extent that I would have liked to. The reason for this is likely to be in part the unfamiliarity of some with the technologies I exposed them to, in part the lack of a structure that forced them to use these. My idea was that the tools I exposed them to are the tools of informal learning; so using them in the course would give the students first-hand experience of their use. As I said, I was only partly successful in this. I don't think using other tools (say, Google hangouts for Flashmeeting) would have made much of a difference. Possibly, if I had used additional tools, such as Scoop.it to curate their own informal learning topic, more interactions would have occurred. Following each others' topic with it is easy and has an immediate pay-of in the form of rescoops. ( A confession, while the course was running, the thought came up to use Scoop.it, but I had little experience with it myself, so I decided to go and immediately curate a topic on Networked Learning myself).

In conclusion, I am reasonably satisfied. But I remain in doubt whether, on a next occasion, to further structure the course and make more specific demands on the students (the usual teacher's response) or to look for a better, more inviting set of tools (the proper way of non-formal learning). Although, as a researcher of informal learning in social networks, I really should have no doubt.

On two kinds of MOOCs

There are two kinds of massive, open online courses around (MOOCs), the Downes-Siemens kind and the kind that mostly (uniquely still?) universities in the USA offer. The archetypal example of the former is PLENK10, a course on personal learning environments networks and knowledge, which ran in September 2010. An example of the latter is the Introduction to AI course, taught by Stanford professor Sebastian Thrun and Google's Director of Research Peter Norvig. Sui Fai John Mak makes a serious attempt in a recent blog post entitled What are MOOCs all about to make sense of the differences between these two kinds. He differentiates between them in the following way (my emphases):

Downes-Siemens type:
1. Those MOOCs based on a connectivist approach – with learning focusing on the learning process, with network construction and navigation, where connections, interactivity, diversity, openness, autonomy are emphasized.  ...

US Universities type:
2. Those MOOCs based on an instructivist – behavioral/cognitivist (blended with constructivist) approach – with learning focusing on the learning outcomes and thus are basically content based, where learners are guided by the main instructors, and are also assessed based on either the machine based assessment tools or peer assessment.


So, in his analysis, the key difference is one of a different underpinning by learning theories, connectivist versus instructivist. Although this certainly is a correct way to differentiate between the two, I don't believe this goes to the heart of the matter. In my view, the key difference between the two kinds of MOOCs is one of underlying of ideology. The education-theoretical stance merely follows from that.

For Downes and Siemens openness is key to their ideology, they want to change education as we know it by being totally open in an attempt to empower the learner vis-à- vis the powerful institutions that schools and in particular universities are. Their view is very much in line with the ideology that underpins the open universities of the world, which arose in the seventies and eighties as a means to emancipate and liberate those who for some reason had not been educated to the full extent of their capabilities. The online character of their MOO-Courses is what gives the openness unprecedented opportunities, massiveness is not an intended effect but rather a collateral one (and their courses are  not massive at the scale that the other type is).

The other kind of MOOC embraces a simple business ideology, and as such is almost the antithesis to the first kind. Its proponents emphasize the aspect of massiveness, which allows them to stretch the benefits that result from economies of scale maximally. Although emancipation etc. may be a result, for example in areas where educational opportunities are hard to come by, it is not really the intended result. What they ultimately aim for is recruiting excellent students from the masses these courses serve. Openness, then, is not a goal in itself but a means to the end of massiveness. The online character of these MOOCs is the only way to achieve massiveness at vanishingly small costs for each additional student.

Is there anything wrong with this state of affairs? Yes and no. To start with the no, it is quite all right that people attempt to innovate education, for we need to do so to sustain our knowledge-hungry societies. And indeed both kinds of MOOCs qualify as educational innovations. However, we should not mistake them for what they are. Calling the two kinds of MOOCs by the same name doesn't help to spot the large differences that exist between them. And it certainly doesn't help to uncover their antithetical ideological underpinnings. Pinpointing those is important for the learners, so they know what they are getting themselves involved in. But it matters even more to educational institutions when they consider adopting either kind of MOOC. The ultimate question is whether you see education as a means to prepare people for the knowledge society we live in or as a way to get a head-start in the competition for the talented. So ultimately, it is about the kind of university you want to be.

Note: after finishing this post, I came across a blog, which discusses business models for MOOCs. It says Udacity has suggested that it might double as a headhunter for companies that might like to hire some of its more impressive students. That is exactly the kind of difference I am referring to.

On another kind of blended learning

This is a short note on two forms of blended learning. The first one is generally accepted, but seems to be mostly more cost effective. The other one seems to be interesting from a pedagogical point of view mainly.

There's little point in reviewing extensively what blended learning customarily refers to, but it seems that it predominantly means the mixing of different learning environments, in particular an environment for formal, face-to-face teaching with an environment for formal e-learning. The former is an environment in which the teacher is personally present, which implies that students need to be present as well, at a certain place and time, in order to be taught in the classroom, lecture theatre or hotel room hired for training purposes.The later environment is an online environment that students access through their computer, (smart) phone, tablet, from wherever they want and whenever they want. Note that I've said nothing yet about pedagogy and that is deliberate.

The characterisation is primarily one of logistics; blended learning in the sense of mixing learning environments is attractive because of its promise to save costs or be more convenient, not because it offers a superior pedagogy. The fact that people can access the learning environment also from home, allows one to let students study at home, and thus saves the reservation of a classroom  or the rent for a hotel suite. The decreased costs predominately come about through the diminished involvement of the teacher, thus benefitting the school or company. Note, though, that this concerns the course's runtime. For students to be able to learn independently, sitting in front of their computer, teachers need to make significant investments upfront. Clearly, this only makes sense at an institutional level if the numbers of students to be expected is large enough to recoup these costs through the deminishing costs of teaching face to face. Blended learning in this sense not only benefits the institution but also the student. The benefit is in increased agency, as now they are able to decide where en when to study. This would suggest that one resort to e-learning fully, however, that would significantly diminish the amount of control a school or company can exert or the directness of access a student has with his or her teachers, which would presumably affect learning effectiveness. In sum, blending of learning environments affords one to optimize learning efficiency (costs) and effectiveness in formal learning contexts.

The second form of blended learning would be mixing bouts of formal learning with bouts of informal learning. Thus learners engage in a training session of some kind but also learn informally (or as some prefer to call it non-formally), in their contacts with their peers, be they school mates or work mates. Whereas blended learning in the first sense seems to be generally accepted as a sensible form of learning, this does not seem to be the case for the second form of blending. And yet it makes a lot of sense also to consider this a form of blending. The emphasis is not now on logistics. The formal part could be situated in a face-to-face environment or in an online environment, whichever suits best. Even blending in the above sense may be considered. The informal part may refer to presence situations, in the classroom or on the shop floor, or to online experiences, for instance in online social networks.

This kind of blending, I surmise, offers a superior pedagogy, one that should ensure that the formal and informal learning bouts that someone experiences become wedded to each other and constitute a single learning experience; a pedagogy also that should warrant that learning is gauged in terms of progress made towards the achievement of personal learning goals and not measured only in terms of progress on a scale defined by others. The notion of a personal learning network by taking a decidedly personal perspective is an attempt to do so. The TRAILER project's attempts to incorporate informal learning experiences in e-portfolios, is another one. Through extending their personal learning network or by expanding their e-portfolios, students profit from this kind of blending. But so do the companies that embrace this kind of blended learning. The increasing awareness of the relevance of informal learning at the workplace, makes this kind of blending of the formal with the informal imperative. There is room for training at the workplace, but for knowledge workers in their pursuit of solving wicked, ill-structured, authentic problems this doesn't suffice. As these problems are unique or at least uniquely dependent on their specific setting, training simple is non-existent. Such knowledge workers are in need of fellow experts, with complementary expertise, from whom they can learn and together with whom they can develop the new knowledge that is needed to solve their problems. For them, blending in the first sense offers no solace, but blending in the second sense should. They could make use of bouts of (individual) formal training to efficiently come up to speed with a particular topic they are unfamiliar with; they should use informal bouts of collective learning to then solve the problem at hand. It is the maturity of the field or discipline a question refers to that is decisive: only for mature fields it makes sense to develop a formal training (for more on this, see Maier & Schmidt, 2007). Viewed this way, blended learning in this second sense is the bread and butter of workplace learning (cf. Littlejohn, 2012). Obviously, at least from my point of view, a learning network is the type of learning environment in which this kind of blended learning finds a natural home.

Littlejohn, A. (2012). change11 position paper; connected knowledge, collective learningejohn.com. Little by Littlejohn, blog. Retrieved May 29, 2012, from http://littlebylittlejohn.com/change11-position-paper


Maier, R. & Schmidt, A. (2007) Characterizing Knowledge Maturing: A Conceptual Process Model for Integrating E-Learning and Knowledge Management. In N. Gronau (Ed.), 4th Conference Professional Knowledge Management Experiences and Visions WM 07 Potsdam (Vol. 1, pp. 325-334). GITO. Retrieved from http://www.andreas-p-schmidt.de/publications/Maier_Schmidt_KnowledgeMaturing_WM07.pdf

Maintaining your OLI - a possible solution

To summarize briefly a previous post and article on online identities or OLIs, they should be as complete as possible to improve the quality of online networked learning, and, at the same time, they should be mimimal because of the risks involved with privacy loss.

Differential access

As a learner, you need to grant others access to your data. These others are providers of learning services. They include the delivery of personalized content, help with finding peers with whom you could collaborate on a project, suggestions for peers or paid experts who would tutor you, etc. Only through access to your data these providers can offer to you personal learning opportunities. The fewer data, the more generic their proposal, the more data, the more specific their proposal. And clearly, since personalized learning opportunities allow you to learn more effectively, efficiently and perhaps even satisfactorily, it is in your interest to provide those data. However, not everyone out there has the best of intentions. To avoid misuse of your data (to imagine what could happen, only think of the way your email address is exploited for sending you spam), you should provide nobody access to your data (see earlier post), but this would of course defeat the purpose of collecting data on you in the first place. The way out of this dilemma is that you provide differential access to your data, i.e. some parties whom you trust are allowed to see and do more than others whom you don't trust this much. This solution has a few problems.

Encryption

First, to increase data security, data need to be encrypted, not only when in transfer but also on the server that keeps them. If not, anybody who happens to spot the URL at which particular data reside could access them. A simple, one-key encryption schema, moreover, is not safe enough. Loss of the key leads to providing access to all your data to whomever happens to find that key. And loss is actually quite probable as any party who needs to access your data, needs to possess that single key. The solution is a public-private encryption scheme. In such a scheme one key is made publicly available, the other one is kept private; also, one key is used to encrypt, the other one to decrypt. If I encrypt some message with my private key, anybody who has my public key (and that is in principle everybody, since I publish the key on, say, my website) can verify that this was my message and nobody else's (authenticating). If I encrypt some message with the intended receiver's public key, I can be sure that only s/he can decipher my message, thus ensuring the message's secrecy. Only the intender receiver and nobody else can see this message. So, I could encrypt a subset of my data with the public key of some education provider A, thus ensuring that it is only they who have access to those data. If they loose my data by accident, I know it is they who are responsible for this. The same I could do for some company B, which provides assessments, or C, which is a job mediator, etc. The upshot is that public-private key encryption allows me to provide differential access to my data.

Access policies

However, the system as described is unmanageable. There are so many data about us out there, that it would rapidly overtax individual data owners to identify, store and provide access to their data, let alone keep a record of who has rights to what data. In the above, I mentioned three parties A, B and C with whom I might want to share data. In actual fact, that number is much larger and indeed incorporates companies (or individuals) I am not even acquainted with. The solution to this manageability problem is to specify sets of access policies for sets of providers. So for instance, a policy for public universities, one for private education providers, one for prospective employers, one for government agencies, etc. These policies would then have to be coupled to a public-private key pair that is related to my policy on the one hand and to the public and private key pairs of the institutions that constitute a set (otherwise I would have to start negotiating with them to issue a pair to me, which with all the users who address them would make things unimaginable for them). Also, my policies are likely to evolve over time, including some data in the data set and excluding other, including new providers in the set, excluding particular old ones. This updating should be easy to do, making use of the same public -private key pair, lest I need start negotiating again with all the educational providers that are, will be, and will not be anymore covered by my policies. These are quite complicated issues.

The above situation was the starting point of a recently published  (October, 2011) piece of PhD research carried out by Luan Ibraimi at the University of Twente, Netherlands (Cryptographically Enforced Distributed Data Access Control). Please consult the original publication to see that the story is a bit more complicated than I portray it here. For those interested, the thesis of course describes in detail how these access policies may indeed be implemented

Making it work

With the technology in place to provide differential access, we're not there yet, though. The solution as described demands the collaboration of all online (educational) service providers and all parties who store personal data. These are often the same parties, although they all provide only some services and all have access to parts of your data profile. Sticking to education, the education providers need to make their public keys available and be willing to access your data through their private keys if they want to make you an offer. As it is in their interest to do so, you are a prospective customer, they would probably be willing to do so. But the story is different for those parties who already have access to you data, whether education providers (the university or school you study) or others (Facebook, LinkedIn, Google, ...). Their making your data available to others implies helping the competition! This barrier can only be taken by disallowing them to make use of your data, even if they reside on their server. That can only be done by routinely encrypting all personal data. For that they need to use your public key to ensure that you and only you can decrypt them again. It does not take a gigantic leap of the imagination to understand that these parties will not do so unless forced to do so by law or consumer pressure (see my post on Privacy and your online identity).

Regulation

There is not one single solution to this problem. Data should always be anonymised if possible. For statistical analyses it is, for personal recommendation of course it isn't. They should also be allowed automatically to degrade, the degree of which could perhaps be coupled to particular policies (cf. Harold van Heerde). However, these measures are only supportive. Any comprehensive solution as described above, is predicated on regulation. That is, online service providers who keep personal data should be forced i) to put them squarely under the user's control as for instance the Electronic Frontier Foundation argues. This includes the rights to remove data and alter them, ii) to routinely encrypt those data with the user's public key. The former brings ownership back to where it belongs, the latter allows data owners to exert ownership, for instance along the lines discussed above. Together, this would solve the problem I raised in my previous post on the topic of online learner identities. Data are brought back under their owner's control and although they remain fragmented, the differential access policies actually allow you to treat them as one large body of data.

The kind of regulation that is needed may come about voluntarily, through a process of consensus formation of all interested parties as in the creation of standards. Given the huge commercial interests I am not optimistic that this will succeed. Perhaps things could start this way, for instance at CEN/ISSS, but ultimately legislation will be needed, for instance as part of EU Commissioner Neelie Kroese's efforts for a Digital Agenda for Europe. Finally, this proposal restricts itself to creating the right conditions for users' differential control of their online data. It would clearly not be a good idea to give governmental institutions control of data themselves. They are no less a party with interests as is any company. The role of the government should be restricted to drafting legislation and enforcing it. As this is going to be long in the works, private initiatives, such as that by the QIY foundation, which operate along the lines sketched, are very welcome.

Update

After I published this text, I found out that the Leibniz Centre for Information Science at Dagstuhl, Germany had organized a Perspectives Workshop on the somewhat wider topic of Online Privacy. The abstracts of the talks have become available, but unfortunately the full manifesto hasn't yet. Nevertheless, as a Perspectives workshop is intended to be an agenda-setting meeting of experts, it illustrates the significance of the topic. 

Full reference: Fischer-hübner, S., Hoofnagle, C., Rannenberg, K., Waidner, M., Krontiris, I., & Marhöfer, M. (2011). Online Privacy : Towards Informational Self-Determination on the Internet Edited by Executive Summary. Dagstuhl Manifestos, 1(1001), 1-15. doi:dx.doi.org/10.4230/DagMan.1.1.1

week 4 writing the paper

Now that you have a topic to write on, I would like to point out how maximally you could profit from each other while writing. There are various systems for collaborative writing, see this website for an overview, what we (or rather, I think you) need here is a tool that allows the collection and identification of comments by your course mates. So, it should be private and also free, and there's no need for a powerful editing toolset. Google docs is a tool that fulfills these demands, but so would Zoho for example. I suggest we use Google docs. < br> Second, make use of Mendeley. The web application will suggest papers that are relevant to your topic if you have filled out your profile and, it is my impression, the better the more papers you have in your collection of publications. Finally, sending out Tweets to your followers with specific questions for suggestions, also is a means to collect feedback.

week 3 picking a paper topic, some thoughts about design

In the previous two weeks we have discussed the pedagogical and technological challenges that anyone with a wish to design a networked learning environment has to face. Now I will go a bit more into the idea of what it means to design a learning environment and do some suggestions for topics of papers. Remember, the papers are to be 1000 to 1500 words (exclusive of references) and should be written using Google docs. That way, they can easily be shared and commented upon.

Design, in the abstract

I defined learning networks as online social networks designed to foster non-formal learning. Technically, this definition is a functional definition in that it tells you what a learning network should do, not how it does it (that would be a causal definition). The good thing about functional definitions is that you do not have to change them every time a new tool comes around. The bad thing of course is that it tells you nothing about what tools you may use. We further unpacked the definition though to conclude that any design that fosters learning should address the pedagogical challenge of adhering to particular pedagogical principles, such as those of self-directed (guided) learning and social learning. Second, we realized that fostering learning for personal learning environments makes different demands on tools than does fostering learning in managed learning environments. And finally, this resulted in the discussion of a number of services that the tools should provide.

There is quite a complicated story to tell about the role of design research in scientific inquiry. Some argue that it is not genuine research as it only allows you to test overall designs and thus never get to understand the exact role some factor, say group size, plays in for example learning effectiveness. Others will argue that these factors or so mutually dependent anyway that testing them one by one is silly at best as it doesn't help, misleading at worst as it suggests answers that are plain wrong. This is the argument for the contextual nature of educational theorizing. This is not to place to argue this out (but see Collins et al. 2004: Design Research, Theoretical and Methodological Issues), the game we have decided to play was not so much to get into the theoretical underpinnings of non-formal networked learning, but rather in ways to make it work. That leads automatically to a design-based approach (see Diana Laurillard's book Teaching as a Design Science, which was published just this March).

Choosing for a design-based approach does not imply that theoretical underpinnings do not matter, they do if only to tell sensible designs apart from designs that are known not to work. However, Theoretical underpinnings (almost) always underdetermine a design. That is, completing a design almost always requires knowledge, often of a practical nature, that is simply not known and not easy to come by either. In such cases, a designer needs to make decisions based on informed guesses. A design that then proves to work reinforces the believe in the correctness of the guess, a design that doesn't questions that believe. Some of this is illustrated in a presentation of mine, still work in progress though.

Concrete designs 

There still are a lot of unknowns that have to be filled in. I surmise that those can only be filled in in the context of a concrete problem, a concrete demand for a learning network to be developed. Lacking those, there is a technique, borrowed from computer science, one may use to come as close as possible to such a demand. It is called writing personas. According to Tina Calabria in her Introduction to personas and how to create them (KM Column, March 2004, see private Mendeley group): 'Personas are archetypal users [...] that represent the needs of larger groups of users, in terms of their goals and personal characteristics. They act as "stand-ins" for real users and help guide decisions about functionality and design.' The eight use-cases we discussed in Chapter 1 of Sloep et al. are not detailed enough yet to serve as personas, they do however come close to what is intended. Particularly the second set of organizational use cases don't fit the description of a persona as they are not written in terms of persons but of institutions. However, replacing them with the description of a manager tasked with setting up a learning network would do the trick. So writing one or more personas, either as archetypal users of a PLE or as archetypal managers of an MLE, should help to arrive at a concrete design.

Furthermore, the web is replete with suggestions for how to design learning networks. I will single out two recent, illuminating examples. First, this blog post by @Ignatia Webs gives a list of standard social network tools that may be employed to build a personal learning network, much in the way we try to use such tools for the present course. Second, for the more technically inclined, this post in the Google App Developers Blog shows how you can do such a thing using Google apps. Parenthetically, both are posts in a Scoop.it topic on networked learning I set up, where other, related topics can be found too.

Topics for papers

I suggest there are two kinds of papers that you can decide to write. If you have a practical nature, write a persona, if need be, inspired by the use cases of Chapter 1, and develop a design for a learning network. The design should be somewhat detailed, that is, it should be clear whether it is a PLE or an MLE, service categories should be discussed and argued for and, to the extent possible, they should be illustrated by tools, existing ones or ones that still have to be built if you can't find any. The paper should finish with a brief discussion of the extent to which you expect your design to foster non-formal, networked learning.

Alternatively, you could write a conceptual paper, if reflecting is something you feel more comfortable with. Then you should discuss any of the assumptions I made throughout the blog posts for this course (or any of the other, on online identities and pedagogical issues), whether explicitly revealed as an assumption or as one that has remained hidden and you managed to uncover. Actually, I would prefer you to tackle the latter, as this could point to flaws in my argument, things overseen or conveniently forgotten. But the choice is yours. Topics for a conceptual paper could refer to the distinction between formal and non-formal (informal), to the distinction between personal and managed learning environments, to the wisdom of using a functional (rather than a causal definition), to the sensibility of the definition anyway,to the need for personal identity management, etc.

I will evaluate your paper, whether orientated on a practical design or conceptual, purely on the strength of its arguments. Factual mistakes and oversights I find less problematic, unless they of course betray a fundamental ignorance of the topic, one that could have been easily remedied by checking only a little bit of the literature. Even if I may not like your design or the conclusion of your conceptual stance, if it is coherently and persuasively argued for, I will value it highly. If you wonder about my reasons for that, I firmly believe that facts without carefully crafted arguments around them will not advance the state of (educational) science. Being a doctoral student, it is the right time to learn how to do this. Oh yes, and connect your topic to your research topic if you can. Success!

week 2 technological challenges

In the post for week 1 and during the ensuing online conference meeting, it was discussed how formal and non-formal learning are different. Also, it was pointed out how networked learning would offer a learning environment that is suited for non-formal learning. After all, networked learning environments are designed with the express purpose to serve non-formal learners. To be sure, this is not to say that other solutions may not exist, but networked learning is a sure candidate.


Environments for networked learning (learning networks) are online social networks. For such networks to flourish and function, tools are needed, that is technological artefacts. At the very simplest level, such technologies are a website with a web address (URL) that one can go to to meet others, one's social network partners. At a more sophisticated level, such tools should foster learning. They could for example induce a network structure which is best for learning, they could allow people to get to know each other, they could help to get answers from the network on content related questions, they could provide means for assessing oneself, etc. These tools may exist already, may consist of existing tools transformed to serve educational purposes, or they could have been custom-built. What tools to use and how to use them is not an easy matter to decide on.

Of personal and managed learning networks

As described in the Design of Learning Networks from an organizational perspective - Chapter 8 from Sloep et al., to be retrieved from the private Mendeley group - one should distinguish between two kinds of learning networks. Managed Learning Networks (MLN) are created to serve some organization's goal, unlike Personal (private) Learning Networks (PLN) which only serve the intersection (average, if you like) of the various individual goals that the network participants have. MLNs are sponsored by an organization, which sets up a network, for instance because it wants its personnel to share the knowledge they individually have with each other, perhaps even use it to create new, to the company strategic bits of knowledge. Organizations exist because they are a means to work more productively or more efficiently than a collection of individuals could. Organizations are successful because its products (goods or services) are better produced by dividing the labour of their production over various people each with their own special area of expertise. It thus makes eminent sense that organizations want to optimize this process of producing through a division of labour, by making sure people learn from each other. And therefore, organizations will tend to coerce their employees into participating in the network they have set up, they will spend money on setting up the network and on making it successful, for instance by telling employees what to do in the network. The second set of use cases discussed in Chapter 1 of Sloep et al. illustrate this quite well.

PLNs are different from MLNs in many ways. First, they exist because there are people who share some broad interest, not because some management wants them to. The first set of use case of Chapter 1 of Sloep et al.  describes them best. As indicated, there is no organization with an interest of its own that can act as a sponsor of the network. There are only the users and their interests. It is they and they alone who should see benefit in networked interaction. There is no greater good, although there will be a division of labour based on the various areas of expertise that the network participants represent. But there is no grand scheme, no organizational structure that has been set up to produce some service or product more effectively or more efficiently. There are only the interests of the individual users. This of course also implies that PLNs arise from the bottom up, solely on the initiative of the users; not, as in MLNs from the top-down, on the initiative of the management. PLNs have no official management, although users may adopt managerial (admin) roles. If they do so, it happens purely because of their merits. (Note: it is quite illuminating to look at the open source software movement and how in there networks emerge; a good overview is offered by Steven Weber, 2004:  The Success of Open Source).

Motivation

There is another important difference between MLNs and PLNs that should be highlighted. From the perspective of the users' motivation to actively participate in a network, PLN users do so because they themselves want to. They are predominantly if not purely intrinsically motivated. If they loose their motivation, they will no longer participate and their is nobody who will, indeed could force them to do otherwise. In MLNs however, users may be motivated intrinsically, but their main motivation will be extrinsic, 'because my boss wants me too', 'because it is part of my job'. Either kind of motivation has its own problems that one should be aware of when designing tools for a network. Intrinsic motivation is powerful, but costly. People only have so much of it to spend and are therefore economical with it. This implies that PLNs are difficult to get started as in the beginning there is so little to prove that one should be motivated to participate (a kind of cold start problem). MLNs with their organizational sponsors do not have this start up issue. They are typically launched with a bang (party, event) and, certainly in the beginning, carefully moderated to generate traffic between users. This is often accompanied by the obligation 'to go there and do things'. The obligation is either translated in incentives to participate (bonus points, a good assessment, etc.) or in punishment (negative points, a negative assessment by management). The problem with this is that the networks stops functioning when moderation is withdrawn ('the network should now function by itself'). Also, people will tend to 'play the system' to get the rewards or avoid punishment without actually contributing to its greater goal (think of people who buy 'levels' in online games to move up the respect ladder quickly without having put in the effort). This situation is inherent in the two kinds of networks, one can only be aware of it and, for a PLN, try to avoid the cold start problem and, for an MLN, strive for more intrinsically motivated participants. The right choice of tools is also critical for this.

Technologies, tools and services

There is no point in going over a long list of existing tools as these tools will come and go as well as change and evolve rapidly. However, function categories of tools are more persistent. The following list of five only covers the most obvious needs that learning network tooling should address.

1. content service - a service that points to written resources, such as texts, papers, presentations, collections of links, etc.
2. peer-support service - a service that connects a help seeker with a potential help provider; if networks become large (from about a hundred people up) one cannot know everyone anymore and participants have to rely on software that matches their needs to the expertise and capabilities of others in the network; peer support covers content-related questions (not the trivial who, where, when, but the non-trivial why and how questions), queries for mentoring, for moral support, etc.
3. coalition-formation service - a service that helps participants set up teams of collaborators, to write a paper, to investigate an issue, to study a topic, etc.
4. online identity service - a service that collects online user data and allows recommender algorithms to do their work
5. portfolio service  - a service that allows users to collect their achievements, show case them and perhaps even have them certified. 

Such services have to be implemented in concrete tools. To name but a few examples of content services, Wikipedia is a collection of lemmas as in an encyclopedia, Merlot is a repository of in a learning objects, Mendeley and dSpace.ou.nl are collections of scientific papers, Delicious is a collection of presentations, iTunesU is a collection of usually rich lectures, etc.  Peer support could be provided through Google's Aardvark service (acquired by Google in 2010, subsequently pulled from the market; cf. for details on its functioning Horowitz & Kamvar, 2012: Searching the Village:Models and Methods for Social Search), through LinkedIn or Facebook groups. I know of no publicly available coalition formation services, but that could only betray my ignorance. However, in the course of our research we have built a dedicated peer-support tool (cf Van Rosmalen, 2008: Supporting the tutor in the design and support of adaptive e-learning; SIKS Dissertation Series No. 2008-07) and coalition formation tools are subject of active research (cf. Sie et al., 2011: What’s in it for me? Recommendation of Peers in Networked Innovation). Online identity services do not exist yet, unless one counts Google Profiles as such (They are tricky, see two of my blog posts on privacy and on the problem). Portfolio services have been around for quite some time, but they have been usurped by formal education. An interesting new development are Mozilla's Open Badges.

Questions

The present discussion and the Chapter referred to, should all act as a starting point for Friday's seminar and, later on, the paper that is to be written. The following questions may be seen as starting points for the discussion.

1. Are there other services than the four listed in the above?
2. May Facebook, LinkedIn or indeed Mendeley or Academia.eu be classified as learning networks?
3. Do you know of existing, publicly available tools that could be used to provide valuable services to a learning network?
4. If Facebook were to be used as the infrastructure for a learning network, does its goal of making money through advertisements stand in the way of its function of a learning network. 
5. How do portfolios differ from Mozilla's open badges?
6. Although our group is too small to count as a learning network (if anything, it is a community of learners), yet consider the tools that we have been using. Are they adequate? If not, what should be replaced, what is missing?

Note: the post has been updated, with the addition of links and a few changes in the wording

week 1 pedagogical challenges

Put succinctly, this Cross Field course is an attempt to come to an understanding of informal learning in the age of the Internet. This is quite a daunting task, something which is a key research area for many, including my own research programme on networked learning at the Open University of The Netherlands. However, even if we should not hope to achieve a final understanding, we can certainly make headway towards a better understanding of this question and suggestions for possible answers to it. We will do this by investigating the pedagogical challenges in week 1 and the technological challenges in week 2 that this kind of learning poses. 
To inventory the pedagogical challenges, I will here first discuss briefly the distinction between formal, informal and non-formal, which also touches upon lifelong learning. Then we will look into the specific demands this group of learners make and how their learning may be supported. Finally, I'll list a few questions that may be used to inspire your writing of the short paper in weeks 3 and 4.

Formal, informal, non-formal learning

Figure 1 Forms versus contexts of learning

The term 'informal' learning is problematic in that it is used in different ways by different people. Without attempting to define it once and forever, the following distinctions are useful. By formal learning, I mean the kind of learning we do at schools; learning organized mostly by an accredited institution, with a curriculum, exams, formal entrance requirements and a formal diploma if one passes the exam. Accidental learning is the very opposite of this. It happens because as a biological species we are 'wired' to learn, we cannot not learn. Learning, for example, is not only a topic in text books of psychology but also in text biology books on physiology and behaviour. The crucial  distinction between the two forms is that formal learning is intentional and accidental learning is unintentional. In formal learning, people set out to learn something, learn on purpose; in accidental learning people (and animals) just learn, willy-nilly. The intentionality is also a characteristic of non-formal learning, but the lack of exams, curricula, etc. it shares with accidental learning (even though ways may be sought to somehow give credit for what people have learnt non-formally). Informal learning is sometimes used to label accidental learning, sometimes to describe non-formal learning. This is where the confusion comes in. I will use it here as a synonym of non-formal learning only.

Next to distinguishing these forms of learning, one may distinguish two contexts: initial learning, that is meant to prepare mostly young people for the workplace and life in general, and post-intital learning, which is for people who have passed the initial phase and need to keep learning to stay abreast of new developments, specifically in our fast-paced knowledge society. The need to have the often compulsory phase of initial education followed by a further phase of post-initial education, is often indicated by saying that people need to learn throughout their entire life, that is, participate in lifelong learning. As a short hand, post-initial learners who learn non-formally are often called lifelong learners (see Figure 1). And although this is not entirely correct (if lifelong learning spans the whole lifecycle, it should also incorporate initial education), it is a common usage to which I will conform.

Now for the punch line. In my view, the methods that are used in the context of initial learning, that is a formal learning setting with lecture halls, curricula, etc., are unfit for post-initial education. They are unfit because of the specific demands post-initial learners (lifelong learners) make on learning settings. Therefore, here we will focus on designing learning environments for the lower middle cell of Figure 1, on non-formal learning for post-initial education. Indeed, it is quite possible that whatever insights a focus on this cell produces, may be used profitably to innovate the upper middle cell on non-formal learning for initial education. That would probably be most welcome, as it is something which is next to nonexistent at present. That is, universities, schools, etc. do no seek to help their students learn non-formally nor do they attempt to somehow give students credit for the non-formal learning they have done.

Demands of post-initial learners

See private Mendeley group Chapter 1 of Sloep et al. (2011), Backgrounds and Reasons, here in a quick English translation, discusses a number of use cases, situations of people who may want to engage in lifelong learning (non-formal learning for post-initial education). Generalizing from these use cases, three kinds of demands may be distinguished, which I have called logistic, content-related and methodical demands. Logistic demands are about designing your educational environment in such a way that people may learn at their individual place, time and pace. Typical classrooms are anathema to this. They force learners to come to a lecture hall, at particular class hours, and every time a particular subject is discussed. Thus place, time and pace are heavily constrained. Second, it is the teacher or rather teaching staff who determines the topics that are being taught (content). This of course is derived from the curriculum, which in turn may have to conform to national standards, etc. Nevertheless, a lifelong learner has very specific needs and demands of his or her own. Those may but need not coincide to what is on offer as part of an existing curriculum. Third, people, particularly experienced learners have their own preference for how they want to learn (method); by themselves or with others, driven by tasks set by teachers or just following an erratic trace of their, starting with some realistic problem or by assimilating theoretical backgrounds first, using a classical handbook or drawing on Internet resources, etc. Again, in formal learning it is a teacher who determines this for an entire class, which may not guarantee the best form for each and every individual, but at least something which is acceptably good. However, for lifelong learners with a lot of learning experience who follow their own interests anyway, this won't do.

Figure 2 Demands and Freedoms 

Interestingly this tripartite demands' division corresponds with the classification of eight freedoms offered by networked learning that Terry Anderson and Jon Dron discuss (see Figure 2). Location, time and pace correspond with logistic demands; subject with content demands; and sociability, approach and technology with methodical demands. That leaves delegability, which is a bit of a difficult one. What it for example refers to is the ability of networked (lifelong) learners to have a choice in what people they may choose to work with, to act as peers, etc. It goes beyond choosing in that it not only allows one to pick form a given list (of peers or content items) but to also assemble the list. 

Designing an appropriate learning environment

The upshot of the above discussion is that designing a learning environment in which lifelong learners are capable of learning non-formally is a tall order. One cannot rely on the usual ingredient of learning environments for formal learning as those stand in the way of the freedoms these learning need (demands they make on such an environment). So teachers cannot play the role of experts who determine the content to be studied, unless one is willing to give each student a personal teachers (well, a few students per teacher), and this is of course unaffordable. This not just goes for the role of teachers as experts who pick content, but also for teachers as tutors, who provide help with questions.

To cater for these kinds of situations, one often speaks of self-guided learning: it is the student who guides him or herself. That sounds interesting but really just begs the question: how should students then guide themselves? How should they pick the right content, how should they find people who can help them with hard questions, and, even, how can they overcome difficult periods of lowered motivation?

Without getting ahead of the story, it is technology that admittedly cannot answer those questions to the full, but should at least help to find those answers more easily, perhaps more adequately also. But this is the topic of week 2.

Questions

The present discussion and the papers referred to in it, should all act as starting points for Friday's seminar and, later on, the paper that is to be written. The following questions may be distilled from the above.

1. Are the dimensions of forms and contexts of learning independent of each other (as they should in a good classification)?
2. Are there other forms than formal, non-formal and accidental? Ditto for  initial and post-initial (exhaustiveness also is a demand of good classification).
3. Is the classification portrayed by Figure 1 useful?
4. Are the 8 freedoms independent, is there no overlap?
5. Are there other freedoms that are relevant?
6. Do these freedoms indeed cover the kinds of demands you would expect lifelong learners to have?
7. Is is correct, productive, sensible to speak in terms of designing a learning environment for non-formal learning as I did?
8. What is wrong with characterizes these learning as self-guided, after all, that is what they need to do?
9. Why does it make sense to rely on technology to support self-guidedness and meet the demands for the eight kinds of freedoms? or is this a silly question?

Welcome to the Online Seminar series of the Cross Fields course Doctoral School on informal learning

Welcome

Welcome all to the Online Seminar of the Cross Fields course Doctoral School on informal learning! In the weeks to come, I will share specifically with the students of this course some of my ideas about informal learning, or non-formal learning, as I prefer to call it. More about this at a later stage in the course, though. To show my cards immediately, I am convinced that informal learning stands to profit immensely from a networked approach. That is, I believe that the usual ways in which we educate and train people, using schools, curricula, exams, etc. are ill suited for non-formal learners; and this is particularly so for advanced and lifelong learners. This has always been the case, but it was difficult to act upon it due to all sorts of practical constraints. However, at present, with the advent of the Internet, the information web (1.0) and particularly the social web (2.), we have the tools at hand to create entirely different and in my view much richer and more effective learning environments, learning environments also that can cater for the needs of non-formal learners. This may to some extent be an unproven assumption, but that should not detain us from trying to build such environments and experiment with them. I call them Learning Networks and in this course we will try to come to grips with what they are, what pedagogical principles could underpin them and what technological tools could sustain them. We will be exploring these questions in a learning environment that itself in many ways resembles a Learning Network. That is, we will not just talk the talk of non-formal, networked learning, but also walk its walk, even though four weeks hardly suffice to do so!

In these four weeks we will first address the issue of the pedagogical challenges of non-formal learning (week 1), then its technological challenges (week 2). In both weeks you will be asked to read a blogpost of mine (for details, see below) and provide extensive comments on the questions/topics for discussion I identify in it. Of course, when doing so, you will identify topics and issues yourself and these should be the basis of comments too. The blog merely forms the starting for collective reflections by you, which should help you make sense of such notions as non-formal learning and networked learning. In addition to the blogpost I will recommend one or two papers for further reading. I urge you to read these as they provide a different or more elaborate angle on the topic of the blogpost. The recommended papers will sit in a private Mendeley reading list (it is recommended that you get a Mendeley account). There also is an extensive, public list on Mendeley with background materials on networked learning. Apart from commenting on the blogpost, I urge you to send out tweets, for instance when reading the blogpost or the papers, using the group hashtag #XfieldDS (requires a Twitter account, which I urge you to get). These tweets will be automatically collected and fed back to you (probably using HootSuit), so you have a sense of how the group feels and thinks about how things are going. Each week is closed off by an online seminar, in which we can discuss things in real time. The tool to be used - Flashmeeting - allows turn taking when speaking, but a chat is always available as a back channel. So even if someone speaks, all others can comment immediately. Both the audio and chat will be recorded so that they are available after the session.

Are the first two weeks mainly devoted to consumptive learning, even though admittedly commenting and tweeting are productive forms of learning, the final two weeks are devoted to productive learning mainly. That is, you will be asked to pick a topic for a short paper (week 3) and write a short essay about it (week 4). The essay should have a length of about a 1000 to 1500 words excluding references (really not so much, if you consider that the above already amounts to almost 600 words!). At the end of week 3, a Flashmeeting is scheduled, but it will be an unsupervised one. That is, you as students should organise and moderate it yourselves, I only have reserved a slot. Furthermore, you should all start writing in your individual Googledoc. document, so that others can easily read it, comment on it and also see its revision history. Also, I urge you to keep tweeting at #XfieldDS to maintain that sense of collaborative learning. Share your thoughts, questions, moments of elation and despair. The papers are due Monday, May the 21st. I will then read them and give feedback to you on them. They also form the basis of the assessment of your performance in the course, for which the executive director of the Doctoral School of course carries the final responsibility. As far as I am concerned, your grasp of the theoretical issues of non-formal and networked learning matter, but no less does your attitude of actively trying to figure out how networked learning can be made to work in an environment like the present one.

After the course's ending, when I send you my feedback, I intend to also to ask you to fill out a short questionnaire with questions about the course topic and the technical infrastructure used. Below I have summarized the course schedule for your benefit.

Course schedule

week 1: April 23-30

• study load: 3 hours
• topic: pedagogical challenges of non-formal learning 
• reading material: blogpost at http://pbsloep.blogger.com called week 1, pedagogical challenge; one or two papers referred to in the blog's text and located in the groups private Mendeley reading list
• interaction: comments on the blog; tweets to #XfieldDS; 1 hour long seminar on April 27 at 3.30 pm led by me using flashmeeting at  http://fm.ea-tel.eu/fm/ce50cf-29823
• background material: public Mendeley group on networked learning

week 2: April 30 - May 7

• study load: 3 hours
• topic: technological challenges of informal learning
• reading material: blogpost at http://pbsloep.blogger.com called week 2,  technological challenges; one or two papers referred to in the blog's text 
• and located in the groups private Mendeley reading list
• interaction: comments on the blog; tweets to #XfieldDS; 1 hour long seminar on May 4 at 3.30 pm led by me using flashmeeting at  http://fm.ea-tel.eu/fm/aa1cb1-29824 
• background material: public Mendeley group on networked learning

week 3: May 7 - 14

• study load: 4 hours
• topic: picking a topic for the paper, 1000 to 1500 words excluding references; start writing using Google docs
• reading material: blogpost at http://pbsloep.blogger.com called week 3, picking a paper topic 
• interaction: tweets to #XfieldDS, keeping each other posted about your progress; joint Flashmeeting, in which every student should spend maximally 5 minutes to explain her/his paper topic. May 11 from 2.00 pm to 3.00 pm at  http://fm.ea-tel.eu/fm/e17a45-298http://fm.ea-tel.eu/fm/e17a45-2982525 Please note, changed starting time.
• background material: public Mendeley group on networked learning

week 4: May 14 -21

• study load: 5 hours 
• topic: finishing the paper
• reading material: blogpost at http://pbsloep.blogger.com with some trips and tricks called week 4, writing the paper 
• interaction: none as this is work done best alone, but the usual channel of tweets to #XfieldDS is available 
• background material: public Mendeley group on networked learning
• paper is due Monday, May 21, at midnight

Finally, please note that not all posts have been written yet, I will do so as the course unfolds. Second, I am using my regular blog for this course, so you will also see posts in this blog that are not course bound. Ignore them, but feel free to peruse them though.

Acknowledgement This blog has been written as part of a course in the online Cross Field programme (CROSS-FertilizatIon betwEen formal and informal Learning through Digital technologies). The doctoral programme is lead by Prof. Lorenzo Cantoni (Università della Svizzera italians), involves Prof. Dieter Euler (University of S. Gallen) and Prof. Pierre Dillenbourg (EPFL) and is managed by Dr. Isabella Rega, its executive director.

Maintaining your OLI - the problem

Earlier, I argued that online learner identities (OLIs) are pivotal in a learning ecology that is personal in that it takes the learner as its starting point and is social in that it puts this starting point at the centre of an online network of people with kindred interests (see more on this Berlanga and Sloep, 2011, Towards a Digital Learner Identity). Such an ecology thrives on the services with which it is populated. Such services come in different kinds, but these are the main categories:

• social services - they are services that intelligently match a learner with others in his or her social network; other learners come in a variety of roles, such as fellow learner, team buddy, coach, mentor, tutor, supporter, supervisor, assessor, etc., basically all the different roles teachers in ordinary formal education adopt, and a few more

• content services - they are services that match a learner's learning objectives or needs with content that could help fulfill those needs; such content will often be in the form of (preferably openly accessible) documents (explicit knowledge), but could also be in the form of implicit knowledge, only accessible by approaching the people who bear this knowledge.

The people in your social network are good candidates to fulfill the various roles in your learning ecology. And your search behaviour speaks to the things you want to learn as do, say, your blogs and wikipedia entries; they also reveal your level of expertise. Presumably, the more detailed the data about your network, about your search behaviour, your posts, tweets, etc., that is, the richer the description of your OLI, the better the social and learning services would be able to facilitate your learning. So, learning benefits from a rich OLI description.

Providing such a rich description, however, poses a privacy risk. The risk may be as grave as to result in identity theft, that is,  in somebody intentionally posing as some other person whose personal data have been stolen with the intention to harm that individual; or the risk may be moderate as when two similar but different individuals accidentally, without harmful intentions become mixed up. So the individual learner is faced with a dilemma. She should reveal everything about herself as this improves the learning experience, but she should reveal nothing at all to lower the risks involved with privacy loss. How can this dilemma be tackled? The answer is that a learner should be able to provide differential access rights to her OLI data: different groups of people get different rights. Thus, people whom one has grown to trust are provided with more rights that complete strangers. Also perhaps, people affiliated with a well-known educational institution are endowed with more rights. Etc. In this conception, controlling one's privacy is equivalent to controlling the access rights to one's data. In a next installment I will explain a schema for how this could in principle be achieved technically. However, and this is the topic of the present post, implementing any such solution which puts a user in control of her OLI data, is hard if not impossible to achieve in the current social web.

First, in the current social web data are provided freely. Web users provide them in exchange for the services that social web sites provide. So Google allows people to carry out searches, in return for the searcher's consent to Google to collect and compile a user profile, which furthers their commercial interests. And something similar goes for Facebook, Twitter, etc.  Although in principle you may decide not to agree with such schemes, in practice this is no more an option than disconnecting yourself from the electricity grid. If you want to search, you use Google, if you want to make online friends, you use Facebook, if you want to microblog, you use Twitter; etc. Second, the data are fragmented as they are scattered over various sites. This nature makes controlling them harder as you need to visit multiple sites. Moreover, sites such as Google, Facebook, etc. are walled gardens, they do not let your data escape, again because those data are the very foundation upon which their business rests. So, they are not just fragmented but your data are also deliberately kept out of your control. Clearly, in the face of this, no individual person really stands much of a chance to control his or her personal data, that is, ultimately also his or her privacy (see my earlier post on this issue).

Interestingly, even scarily if you think about it, the issue of privacy does not seem to bother the majority of the Internet users. The discussion on privacy occasionally flares up, for instance when privacy settings turn out to reveal more than previously as a consequence of a license update (Facebook) or when location data on private wifi networks turn out to have been collected and stored (Google). But the big picture of the massive amounts of data that already have been collected and stored, are used on a regular basis, fails to upset people. Wrongly so, as I have argued.

[adapted and updated December 29, 2011

Why we need the Internet to stay a Commons

Thanks to Sir Tim Berners-Lee's vision we have the hyperlinked online network that we call the Web, in which we share information and ever more engage socially with each other. Thanks to the American Department of Defence the Web runs on a distributed logical infrastructure, which gives it the character of a commons: something we use and own collectively, without a central authority to govern or dictate what goes on. This character has been under threat from two sides. The Media Industries who see their business model of 'selling culture in containers' jeopardized. They focus their grievances on the peer-to-peer networks in which content is freely shared. However, independent artists of all kinds who sell their creative products directly to their fans and customers, will in the long run be even more of a threat as they cut out the middleman that the Media Industry is. This is the real game changing event as for the first time it is feasible to also cater for the long tale of people's interests. The second threat comes from governments, which are naturally inclined to fear loss of control and use national security arguments to clamp down on an Open Net. The recent measures that various governments took to make life hard for the WikiLeaks site bear witness to this.

For good measure, I should rapidly add that existing intellectual property rights need to be respected, also on the Internet; and attempts to overthrow governments, threaten its institutions or plan terrorist attacks should be nipped in the buds, anywhere, so also on the Internet. However, this is not an all-or-nothing argument. Rather, of each measure taken benefits and drawbacks should be weighted against each other. Thus, enforcing the old model of selling music, films, books in containers that one pays for or attempting to impart such a model on Internet transactions (Digital Rights Management!) stifles innovation. It keeps transaction costs high and it disallows artists and independent small producers and publishers their seat at the table. Also, imparting too much government control on the Internet brings in its wake the Kafkaesque dangers of intransparant data aggregation, data exclusion and data distortion I discussed in my previous post.

Arguments more detailed than the ones I have given can be found in a recent paper by Yochai Benkler entitled WikiLeaks and the protect-ip Act: A New Public-Private Threat to the Internet Commons.  He also reveals how governments and the Media Industry indeed have joined forces in their attack on the openness of the Internet. According to him, an Open Internet, one which embraces the idea of a commons is not faultless but it offers numerous and large benefits. One of those is its support for democracy and freedom: a democracy only thrives if the populace is well educated and divergent opinions are allowed to be aired; another benefit is its support for innovation and welfare: creativity thrives in heterogeneous environments, where many people gather freely and talk openly, with whom they like, when they like. In a recent 15 minutes interview Benkler reiterates this all very succinctly and eloquently.


Finally, Internet as a Commons is also crucial for the innovation of education. In a world that needs people to be better educated and needs more of them, it is imperative to experiment with different models of learning and teaching. Even though there will always be room for formal learning as in schools and universities, this cannot be the whole story (see Tony Bates' recent blog on this). Experiments with forms of informal learning or combinations of both formal and informal learning are badly needed (see also this recent report on the Future of Learning). To the extent that these are networked - and I have argued in many blogs and papers they should be - only the Internet as a Commons offers enough room for experimentation. Open Educational Resources are a key element but run of course counter to the interests of the Media Industries. Individuals as the sole owners of their profiling data are essential (see my previous post), but runs counter to the interest of governments (who want privileged access) and the Social Media Industry (who want ownership themselves or at least give people a hard time themselves to exert ownership). Long-tail education offers unprecedented opportunities for personalization and customization, but only thrives if providers of such educational opportunities have few hurdles to take, that is, on a web that is as little regulated as feasible. The easiest and ultimately most rewarding way to do this, I believe, is to defend the current character of the Internet as a Commons, surely against attacks such as described by Benkler in his paper and interview.

Privacy and your online learner identity

This post is prompted by an article I happened to read in the Chronicle of Higher Education of May 15th, 2011 entitled Why privacy matters even if you have nothing to hide, written by Daniel Solove, a professor of law at George Washington University. It is a prequel to a book called Nothing to Hide. My interest in it stems from an article Adriana Berlanga and I wrote about online learner identities. The question we address there is how best to balance the need to know as much as you can about a lifelong learner to be able to offer him or her the best possible learning arrangements (in an online learning environment) with the justified worry that yielding all those data may easily invade that person's privacy.

Fundamental to our argument is the observation, made by many, that the online realm or cyberspace becomes ever more a place where we lead our social lives, also our live as a (lifelong) learner and worker. Consequently, we need to build online identities, which we dubbed a online learner identity in so far as that identity should allow us to 'live' in networked environments geared for learning and professional development (Learning Networks, if you like). However, since these identities are fragmented across the various social networking sites out there (Facebook, Google, Ning, LinkedIn, ...) it is difficult for an individual user to build, let alone maintain, such an identity. One needs to repeatedly update various sites and, even harder, one needs to imagine what the big picture of oneself is that emerges this way. So technical solutions may be attempted that allow data to be automatically exchanged between those sites. Perhaps a kind of dashboard that aggregates data from various sources is a good idea. (This assumes the hosting parties would allow that, which does not go without saying as sharing with such a dashboard site lowers traffic and thus is not in their interest.) Also, a learning perspective is needed to dictate what data the dashboard should collect. Past education, for instance, seems more important than the kinds of movies one likes.

However, there is another issue that is inextricably linked to these technical and learning-theoretical issue. It is whether we as users of such a dashboard do indeed want to aggregate our existing fragmented identities. It does not go without saying that we do. Facebook, for instance, once was a fun site only but increasingly has earned itself a bad reputation for revealing ever more data about its users without asking them explicitly beforehand. And every service Google offers us for free betrays Google's hunger for our (profiling) data. This should not come as a surprise, of course. Somebody should foot the bill for the services provided to us. It turns out that we ourselves do so by giving up our data for free, allowing the Facebooks and Googles of this world to make money through targeted advertising and selling of profiling data to third parties. But we need at least ask the question if this is the way we want it, for Facebook and Google but also for dashboard-like services that ostensibly only have the best intentions. At face value, this question is about privacy issues. Solove's paper shines an illuminating light on helping us understand it that way.

His point of departure is the often voiced argument that if you have nothing to hide, it is ok for the government to know anything there is to know about you. The counterargument is that this constitutes an invasion of your privacy. Parenthetically, in the discussion that follows the article someone rightly points out that privacy is a Human Right (number 12) granted to you by birth and that invasions thereof are a privilege that needs to be granted through proper argument, even by governments. However, to make the counterargument stick we need to understand what privacy is. Solove attempts to delineate the notion by using two metaphors, a quite ingenious move in my view. Some aspects of privacy are addressed by George Orwell in his Nineteen Eighty-Four novel, by describing the omnipresent state which watches and stores in huge databases our every step. This is the surveillance aspect of privacy. The other metaphor is discussed by Franz Kafka in his Der Prozess (The Trial). This is about someone who has to stand trial but has no idea what he is accused of nor is he allowed to have access to the accusations and the reasoning behind it. This aspect of privacy Solove calls information processing, it addresses the government as a bureaucracy, which lacks transparency and refuses to be accountable for what it does with those data. He then argues: the problems [with privacy invasions] are not just Orwellian but Kafkaesque. Government information-gathering programs are problematic even if no information that people want to hide is uncovered. In The Trial, the problem is not inhibited behavior but rather a suffocating powerlessness and vulnerability created by the court system's use of personal data and its denial to the protagonist of any knowledge of or participation in the process. The harms are bureaucratic ones—indifference, error, abuse, frustration, and lack of transparency and accountability.

So, one should not so much worry about the mere storage of data, that which George Orwell denounced, but about the subsequent processing of them in opaque ways, that which worried Franz Kafka so much. To unpack the processing, data aggregation is one way of data processing, 'the fusion of small bits of seemingly innocuous data'. Aggregation may be objected to since the picture of someone that emerges after aggregation is not apparent in the constituting bits. The whole is more than the sum of its parts, sums this up nicely. Exclusion, preventing people 'from having knowledge about how information about them is being used' and barring them 'from accessing and correcting errors in that data', is another way. Exclusion goes to the heart of the Kafka objection. Job applicants whose application was turned down because they were unable to remove online pictures taken of them taken in a moment of weakness understand the harm exclusion can do full well. This problem is exacerbated when secondary use of those data is made, as the route from misuse to the data source is now even harder to trace. Distortion is a third kind of data processing, meaning that, necessarily, stored data only show part of a personality, which may lead to a distorted picture of that person. When first impressions matter, as in job interviews, distortion can do much harm.

In the case of a learner's online identity, Adriana and I argued against the fragmentation of someone's identity across the various social media sites in existence. This is a variation of the distortion argument. Even if we admit that people may have good reasons to maintain several, separate online identities (one for work, one or more for your leisure activities), what such an identity should look like should be under the identified person's control and only his or her control. After all, only that person can oversee the degree and kind of allowable distortion. Thus, the practical argument we leveled against fragmentation proves to have a privacy aspect as well. This brings us to the exclusion argument. People need to have access to the data stored about them to correct those data, extend them, prune them, etc. In our paper, we offered a practical argument for this, arguing that people should be able to build an online identity qua learner that suits their learning and professional development best. This argument too turns out to have a privacy twist to it, being that control over one's data is a matter of principle (privacy) and not only convenience. And finally, the defragmentation that we argued for of course is a form of aggregation. However interesting the technical challenges may be to overcome defragmentation and however useful it may be from a learning perspective, doing so inevitably also impacts our privacy. That is the key value of Solove's argument.

Solove thus exposes the nothing-to-hide argument as too simplistic. Privacy is multifaceted, nothing to hide only addresses the data surveillance aspect of it, not the data processing aspect. Data processing itself is complex, encompassing such things as aggregation, exclusion and distortion. Any one of these impinges on efforts to arrive at the consolidated online learner identity we argued for in our paper. Solove, in focusing on debunking the nothing-to-hide argument, does not offer any solutions on how someone's privacy may be safeguarded against the aggregation, exclusion and distortion of their data. But perhaps this cannot be discussed in general terms, perhaps it can only be understood in the concrete case of, for instance, building a consolidated digital identity for learners. If so, his refined understanding of what privacy is about should help us do so. It should help us to reap the benefits of online learning while giving due attention to the privacy challenges that come in its wake.

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October 22, 2012. Note added after publication: It has come to my attention that there is an EU funded, 7th framework project that goes by the name of Trusted architecture for securely shared services (TAS3). I quote from their summary: TAS3 will develop and implement an architecture with trusted services to manage and process distributed personal information. [...] TAS3 will focus an instantiation of this architecture in the employability and e-health sector allowing users and service providers in these two sectors to manage the lifelong generated personal employability and e-health information of the individuals involved. This sounds like an architecture that should also work for online learner identities, even though TAS3 will focus on data in offline databases and we are more interested in online databases (behind social media interfaces). Second, the EIfEL team has published a blog post with the intriguing title: To create a trustworthy Internet respectful of our privacy, shouldn't we simply make our personal data public? Without going into detail, their solution is to spread your personal data over various sites, but anonymously. You as the owner keep a bundle of private keys through which you can grant access to those data in a piecemeal fashion. This way, you can allow whoever you want to access and disallow everybody else access. Quite ingenious, although I am not sure Facebook and Google would like the idea of only having uninformative bits and pieces of your personal profile data hidden behind an alias. Even so, Google just said are considering allowing aliases on their Google+ service.