A case-based reasoning approach to provide adaptive feedback in microworlds

This paper presents a case-based reasoning (CBR) approach to provide adaptive support in microworlds. Interaction in microworlds is complex and unstructured, making the analysis of student behaviour difficult and the provision of computer-based feedback challenging. Our approach starts with the ellicitation of expected solutions to microworld tasks (both valid and common mistakes) to generate a case base. This is used to evaluate the actions of students and provide adapted feedback