Motivational Diagnosis in ITSs: Collaborative, Reflective Self-Report

Authors:
Katerina Avramides;Benedict Du Boulay
Affiliations:
IDEAS lab, Department of Informatics, University of Sussex, Falmer, Brighton BN1 9QJ, K.Avramides@sussex.ac.uk;IDEAS lab, Department of Informatics, University of Sussex, Falmer, Brighton BN1 9QJ, K.Avramides@sussex.ac.uk
Venue:
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
Year:
2009

Citing 4
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Abstract

A central challenge in the design of motivationally intelligent tutoring systems lies in defining and diagnosing a learner's motivational state: in particular, in distinguishing between the learner's motivational and affective states. We discuss existing AIED approaches and outline an alternative approach that incorporates reflective peer collaboration. The paper raises questions about the basis for the design of motivationally intelligent tutoring systems.