This post is about the methodology of Adaptive Personalized Learning. It represents my comments on Michael Feldstein’s post that Pearson Releases a Significant Learning Design Aid.
It is not a secret, but rather a commonly forgotten or ignored fact, that scientific knowledge has a hierarchical structure in contrast to amorphous/messy heuristics, practices, pragmatic principles, rules, etc. A few of general interdisciplinary sciences, such as Systems, Control, Activity Theories, are on the top of this hierarchy. They generalize objects, models, and methods of more specific exact sciences and soft humanities, both located below in the hierarchy. In turn, humanities include the learning sciences. In contrast to exact sciences (with well-defined objects, models, and methods), some humanities and all the learning sciences have an ill-defined, ill-observable, and ill-controllable object, the learning process. As a result, models and methods of learning sciences are often represented with amorphous/messy heuristics, best practices, principles, rules, etc. This is what Michael’s post is about. It is pretty challenging to analyze, understand and explain this mess to others who has the different mess in their minds. Michael’s talent is required.
The common problem is that we do not see a forest behind the trees. We are constructors without an architect. But according to the science hierarchy that forest, big picture, general models, methods, and methodology exist on the top level and can be found in such multidisciplinary theories as Systems, Control, Activity Theories.
It is not just an idea. In my R&D, I successfully used many interdisciplinary theories as a basis for developing general models and methods of cost-effective Intelligent Tutoring, Adaptive Learning Systems, and Platforms. According to the general-specific hierarchy, all Pearson’s specific principles can be implemented within our general content-independent platform.