Design, in the abstractI 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 designsThere 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!