  Every teacher understands that different students benefit from different
activities. Recent advances in data processing allow us to detect and use
behavioral variability for adapting to a student. This approach allows us to
optimize learning process but does not focus on understanding it. Conversely,
classical findings in educational sciences allow us to understand the learner
but are hard to embed in a large scale adaptive system. In this study we design
and build a framework to investigate when the two approaches coincide.
