An Efficient Student Model Based on Student Performance and Metadata

Arndt Faulhaber, Erica Melis

In: Nikos Avouris , Nikos Fakotatis , Constantine D. Spyropoulos , Malik Ghallab (Hrsg.). Proceedings of 18th European Conference on Artificial Intelligence. European Conference on Artificial Intelligence (ECAI-08) 18th July 21-25 Patras Greece Seiten 276-280 Frontiers in Artificial Intelligence and Applications (FAIA) 178 IOS Press 2008.


This paper describes a new student model technology that combines evidences and knowledge about pedagogical and domain structure. Its structure is generated from the metadata available in the content representation of the adaptive webbased learning platform ActiveMath (or other contents). The evidences are processed with Item Response Theory and Transferable Belief Model uncertainty methodologies. We summarize evaluation results for this student model. (pdf, 56 KB )

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence