Gigi Johnson: (1) Co-learning is Messy. It needs time, patience, confusion, re-forming, re-norming, re-storming, etc. Things go awry and part of norms needs to be how to realign. (2) Co-learning is a VERY different experience from traditional teacher-led learning in terms of time and completion. It is frustrating, so many people will lurk or just step in and out, the latter of which is very different from what is acceptable in traditonal learning. Online learning programs are painted with the brush now of an “unacceptable” 50% average non-completion rate. Stanford’s MOOC AI class, which started out with +100,000 people, had 12% finish.  If only 12% or 50% of my traditional class finished, I’d have a hard time getting next quarter’s classes approved!

The second point is similar to the earlier Anti-pattern “Misunderstanding Power (Laws)“.  People have to join in order to try, and when joining is low-cost, and completion low-benefit, it is not surprising that many people will “dissipate” as the course progresses.

The “messiness” of co-learning is interesting because it points to a sort of “internal dissipation”, as contributors bring their multiple different backgrounds, interests, and communication styles to bear.  In Tomlinson et al., we observed:

More authors means more content, but also more words thrown away. Many of the words written by authors were deleted during the ongoing editing process. The sheer mass of deleted words might raise the question of whether authoring a paper in such a massively distributed fashion is efficient.

If we were to describe this situation in traditional subject/object terms, we would say that peer production has a “low signal to noise ratio”.  However, it may be more appropriate (and constructive) to think of meanings as co-constructed as the process runs, and of messiness (or meaninglessness) as symptomatic, not of peer production itself, but of deficiencies or infelicities in shared meaning-making and “integrating” features.