Stitching Together the Fragments of a MOOC
I read with interest George Siemens’ recent article on ‘Activating Latent Knowledge Capacity‘ and in particular:
The one draw back to networked learning is that while we have managed to advance conversation on the fragmentation of learning so that it is not a cohesive whole created solely by the instructor, we have not yet advanced the process of centring or stitching together fragmented parts into cohesive wholes for individuals.
This has certainly been my experience of networked learning and is particularly true of the mammoth xMOOCs where huge clunky forums can be so overwhelming that a majority of participants just keep away. In connectivist MOOCs, participants are encouraged to use their own blogs and social media for interaction but there’s still a need for ‘defragmentation’ – a means of signposting MOOC activity in one place in ways that are meaningful to the individual. There are of course RSS readers but these focus on the aggregation of blog posts rather than active discussion and interaction between participants. MOOCs sometimes pull together participant blog postings into a single ‘blog hub’ but the resulting presence of duplicate posts can be confusing, particularly if discussion about the same post is fragmented with comments appearing on the hub independently of other comments on the original post.
Interaction between the participants of a MOOC can centre around social media such as Google Plus, Facebook or even Twitter and a dedicated Facebook Group page can be very effective in tracking current activity. In this case, the most recently active threads appear first, often with relevant images and the non-active ones gradually fall into obscurity. This can result in timely and fast-moving forum discussions although the various threads are unlikely to carry the more substantive contributions typical of blog posts. Over-dependence on social media is not without a price. Participants who are not registered for some services will be excluded and there is the inevitable manipulation of users and their data for commercial purposes.
Setting aside the practical problems of implementation, what considerations should apply to the design of a ‘MOOC defragmenter’?
- Give primacy to personal web space – First and foremost participant web spaces should be recognised and scanned as the major source of data. Currently, most participants are unlikely to have their own web spaces but setting up a personal blog has never been more straightforward. The trend towards establishing a digital presence on the open web is set to continue as the benefits of controlling one’s own data and digital identity become more widely recognised. Innovation such as ‘Domain of my Own‘ demonstrates that owning and managing one’s own slice of the web is not just for the geeks.
- Signpost current activity – Create a concise overall view of current MOOC activity on a single page. Focus on the wood rather than the trees. Activity could be signposted by direct links to participant spaces with older material dropping down in classic Facebook style. Little manipulation of content or additional material is envisaged so that participants are encouraged to move on to whatever fragment of the MOOC they find of particular interest.
- Openness Rules! – Clear information about rules, settings and any other uses made of participant data should be freely stated and available. Selecting output from a miscellany of inputs necessarily involves a set of rules that are designed to bring together and output MOOC fragments as a cohesive whole. Rules, however, can be manipulated, commercial advertising being the obvious example. Data could also be collected for academic research or other purposes. MOOCs are complex systems and the rules governing effective defragmention are also likely to be complex. Some rules may be misunderstood, unacceptable or even detrimental to the interests of some participants.
Returning to the practical, I have experimented with a ‘MOOC Comment Scraper‘ that generates brief summaries of WordPress and Blogger comments and posts by scanning the RSS feeds of participant blogs. The latest version was well tested during the excellent Rhizo14 MOOC and considered to be a useful facility by many participants (see MOOC Comment Scraper Output – #rhizo14 ). Further development has now resulted in a ‘Comment Collector’ where output items are ordered according to the date of a post’s latest comment rather than the date of the post itself. An example output was derived from a real MOOC (nonsense text replaces real). The presentation could be enhanced in a number of ways but as an amateur programmer I’m unlikely to produce a really comprehensive MOOC defragmenter! All the same, I’d be pleased to find another MOOC for a field test.