Using Cognitive Categories for an Interactive Diagnostic Learner Model of Historical Text Comprehension

In this contribution we present a Learner Model (LM) of Historical Text Comprehension (HTC), which infers the cognitive profile of learner’s global comprehension concerning the recognition or not of the three fundamental cognitive categories: action, state and event. Moreover the LM infers the profile descriptor, which displays the learner’s learning difficulties. The diagnostic module of the LM, which has been presented in our previous work, imitates human diagnosis using Fuzzy logic and Case-Based Reasoning techniques of artificial intelligence. Based on the diagnostic results the model activates the learner in an interactive diagnostic dialogue. The LM is externally explicit and open to discussion and helps learners to become conscious of the quality of their answers, reflect back to claims about their reasoning and some times change their reasoning.