An adaptive learning system tries to evaluate what a student knows and present that student with new material and/or problems to solve that are just at the edge, or just beyond the edge, of the student’s demonstrated knowledge and understanding. The adaptive learning system then supports (or scaffolds) learning at this point. Such an approach is depicted below.

learning trajectoryv2.jpg

The three key regions of “understanding” are highlighted: a region where the student knows the content being presented, a region where the student could understand, with help, and a region that is well beyond the student’s current understanding. It is not productive for the student to work with material he already understands, the region shown on the left. This is likely to lead to boredom and disinterest. It is also not productive for the student to be presented with material well beyond his understanding, as depicted by the region on the right. This will lead to frustration. What an adaptive learning system tries to do is keep the student working with material just beyond what he knows, in a region where some support and feedback could lead the student to learning and new insights. This is adaptivity as Vygotsky imagined it. It is also important for students to use what they know to help them learn more.

 

Essentially, this is like “bootstrapping” new knowledge from existing knowledge. From a cognitive science perspective, this involves using long-term memory, what a learner already knows, to incorporate and associate new concepts and knowledge from short-term, working memory (Sweller, Van Merriënboer, & Paas, 1998). We have long known that working memory is relatively small (Miller, 1956) and thus can be easily taxed to the point of blocking new knowledge from transferring to long-term memory. A key to adaptive learning is to maintain low stress on working memory, so the student can easily and actively extend her long-term network of associations and strengthen her understanding of partially understood concepts. Again, by keeping the student’s learning trajectory towards the middle of the above image, working memory is less taxed and the important associations and meanings that extend long-term memory are given the opportunity to develop. Furthermore, by extending long-term memory and associations, the student may also be able to apply learned concepts to new contexts of the student’s demonstrated knowledge and understanding.

 

Excerpted from Adaptive Online learning: The Present and Future of Education by Dr. Bruce McLaren, Carnegie Mellon University, United States.