Abstract

Abstract. There is a strong argument in Artificial Intelligence in Education which advocates that computer-based learning systems need to adapt to the needs of learners if they are to provide for effective personalised instruction (Self, 1999a). Diagnosing a learner's cognitive capacity is a crucial issue in building adaptive systems. We have explored an interactive open learner modelling (IOLM) approach which conceives diagnosis as an interactive process involving both a computer system and a learner that discuss and together construct the learner model. This paper outlines the architecture of an interactive open learner modelling system and illustrates the method in a terminological domain. We discuss an evaluative study of an IOLM demonstrator – a system called STyLE-OLM. The results from the study demonstrate potential benefits of the method for improving the quality of the learner model and providing a means for fostering reflective thinking. We argue that IOLM is a fruitful approach which may be employed in intelligent learning environments both for obtaining a better model of a learner’s cognitive state and engaging learners in reflective activities.

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