Stereotypes, Student Models and Scrutability

  • Judy Kay
Conference paper

DOI: 10.1007/3-540-45108-0_5

Volume 1839 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Kay J. (2000) Stereotypes, Student Models and Scrutability. In: Gauthier G., Frasson C., VanLehn K. (eds) Intelligent Tutoring Systems. ITS 2000. Lecture Notes in Computer Science, vol 1839. Springer, Berlin, Heidelberg

Abstract

Stereotypes are widely used in both Intelligent Teaching Systems and in a range of other teaching and advisory software. Yet the notion of stereotype is very loose. This paper gives a working definition of stereotypes for student modelling. The paper shows the role of stereotypes in classic approaches to student modelling via overlay, differential and buggy models.

A scrutable student model enables learners to scrutinise their models to determine what the system believes about them and how it determined those beliefs. The paper explores the ways that scrutable stereotypes can provide a foundation for learners to tune their student models and explore the impact of the student model. Linking this to existing work, the paper notes how scrutable stereotypes might support reflection and metacognition as well as efficient, learner-controlled student modelling.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Judy Kay
    • 1
  1. 1.Basser Dept of Computer Science Madsen F09University of SydneyAustralia