Engagement and Deeper Learning

One of the many books I’m currently reading (ok, I just got started on it) is Conrad and Donaldson’s Engaging the Online Learner. On p. 3 they quote Weigel, Deep Learning for a Digital Age (p. 5), and I think the quote is worth posting here, though I will give a fuller quotation:
> The familiar debate over process versus content loses relevance in a constructivist perspective. Content is the medium for knowledge
> construction and the springboard for learning. But merely possessing information does little to advance the goals of education. Learning,
> from the standpoint of constructivism, takes place when students act on content, when they shape and form it. Content is the clay of
> knowledge construction; learning takes place when it is fashioned into something meaningful. Creativity, critical analysis, and skillful
> performance are inextricably linked to the process of creating more viable and coherent knowledge structures.
Conrad and Donaldson draw on Weigel to make the point that in the online environment instructors must be especially intentional at designing and implementing learning activities (particularly collaborative activities) that move learners away from merely stuffing their short-term memory full of the course content long enough to regurgitate it on the exam and toward deeper knowledge and understanding (cf. my post, "Deeper Knowledge & Understanding" on the North Institute Web site)—a point that applies to the traditional classroom, too.

Weigel defines deep learning as "learning that promotes the development of conditionalized knowledge and metacognition through communities of inquiry" (Deep Learning for a Digital Age, 5). Conditionalized knowledge is knowledge that specifies contexts in which it is useful (Deep Learning for a Digital Age, 5); this kind of knowledge can only be gained when students have the opportunity to unpack discipline-specific theories, formulate models and methods, and put them to use. This is where critical thinking, creativity, and skillful performance converge.