RESULTANT FORCE: Which results matter? That's the thought-provoking question in this Will Richardson response to Nicholas Carr's MOOC-hailing article in MIT's Technology Review. For what it's worth Carr's article presents a fairly neutral view of the online learning phenomena. (That in itself is amazing considering this is the guy who built a career around books including: "The Shallows: What the Internet is Doing to Our Brains," and "Does IT Matter?")
What really gets Richardson fired up is the notion that the only results worth mentioning (and the ones used to support MOOC effectiveness) are limited to "competencies or tests or grades." He predicts a dire end for the teaching profession if stories of authentic face-to-face learning don't scale as effectively as online learning platforms.
We're a bit more optimistic. Machine learning algorithms are great for predicting misconceptions in number theory, but have yet to mimic the magic of the most transformative teachers -- that is, the ability to co-create a culture and learning environment that engages and motivates the learner. If intelligent tutoring systems and the like can improve test scores in schools where these teachers are most needed -- where barriers to learning are social and testing cycles reinforce academic inferiority -- then by all means, let's MOOC it out.
Still there's no denying Richardson's logical conclusion: "Simply pushing back against these types of innovations by attacking their lack of humanity will not work." Here are a few more pointed questions for the edtech entrepreneurial community: