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Book Chapter
Stereotypes, Student Models and Scrutability
Book Series
Lecture Notes in Computer Science
Publisher
Springer Berlin / Heidelberg
ISSN
0302-9743 (Print) 1611-3349 (Online)
Volume
Volume 1839/2000
Book
Intelligent Tutoring Systems
DOI
10.1007/3-540-45108-0
Copyright
2000
ISBN
978-3-540-67655-3
DOI
10.1007/3-540-45108-0_5
Pages
19-30
Subject Collection
Computer Science
SpringerLink Date
Saturday, January 01, 2000
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Stereotypes, Student Models and Scrutability
Judy Kay
7
(7)
Basser Dept of Computer Science Madsen F09, University of Sydney, Australia, 2006
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.
Judy
Kay
Email:
judy@cs.usyd.edu.au
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