Paper Info
Title
Developing a Bayes-net based student model for an External Representation Selection Tutor
Abstract
This paper describes the process by which we are constructing an intelligent tutoring system (ERST) designed to improve learners' external representation (ER) selection accuracy on a range of database query tasks. This paper describes how ERST's student model is being constructed-it is a Bayesian network seeded with data from experimental studies. The studies examined the effects of students' background knowledge-of-external representations (KER) upon performance and their preferences for particular information display forms across a range of database query types.
Year
Venue
Keywords
2005
AIED
selection accuracy,background knowledge-of-external representation,bayesian network,particular information display form,external representation,student model,database query task,intelligent tutoring system,experimental study,database query type,external representation selection
Field
DocType
Volume
TUTOR,Database query,Intelligent tutoring system,Computer science,Bayesian network,Artificial intelligence,Information display,Machine learning
Conference
125
ISSN
ISBN
Citations 
0922-6389
1-58603-530-4
0
PageRank 
References 
Authors
0.34
4
2
Name
Order
Citations
PageRank
Beate Grawemeyer118417.60
Richard Cox200.34