Diagnostic and learning interaction system for historical text comprehension

Abstract

In this contribution we present a Learner Model (LM) of Historical Text Comprehension (HTC), which activates the learner in interactive diagnostic and learning dialogues. The LM infers the learner's cognitive profile and profile descriptor, which reveal his global comprehension of the historical text and his learning difficulties. The Fuzzy Case-Based Reasoning diagnostic module of the LM has been presented in our previous work. Based on the diagnostic results the LM generates the appropriate dialogue and activates the learner in a learning interaction. Preliminary experiment showed that the externally explicit and open to discussion LM helps learners to become conscious of the quality of their answers, to reflect back to claims about their reasoning and some times change their reasoning.