Providing adaptive support for meta-cognitive skills to improve learning.
Kasia Müldner, Cristina Conati · 2005
We describe a computational framework designed to provide adaptive support for learning from problem solving activities that make worked-out examples avail-able. This framework targets several meta-cognitive skills required to learn effectively in this type of instruc-tional setting, including explanation-based-learning-of-correctness and min-analogy. The generated interven-tions are based on an assessment of a student’s knowl-edge and meta-cognitive skills provided by the frame-work’s student model, and thus are tailored to that stu-dent’s needs.