Paper Info
Title
Evaluating a Probabilistic Model for Affective Behavior in an Intelligent Tutoring System
Abstract
We have developed an affective behavior model (ABM) for intelligent tutoring systems, so the tutor considers the affective state as well as the pedagogical state of the student. The ABM first establishes the affective state based on the OCC cognitive model of emotions, represented as a dynamic Bayesian network. Then, the tutor selects the best tutorial action according to the pedagogical and affective state of the student. For this it uses a dynamic decision network that was designed based on the opinions of a group of experienced teachers. The ABM has been integrated to an intelligent tutor for mobile robotics. A pilot study with a group of 20 students shows that the affective and tutorial actions selected by the tutor are in general in agreement with the students’ expectations.
Year
DOI
Venue
2008
10.1109/ICALT.2008.287
ICALT
Keywords
Field
DocType
affective behavior model,pedagogical state,experienced teacher,tutorial action,affective behavior,intelligent tutoring system,probabilistic model,dynamic bayesian network,intelligent tutor,affective state,occ cognitive model,dynamic decision network,action selection,robots,artificial intelligence,mobile robot,animation,bayesian methods,behavior modeling,cognitive model,intelligent systems,mobile robots,utility theory,decision theory,mobile communication,appraisal,feedback
TUTOR,Intelligent tutoring system,Intelligent decision support system,Computer science,Human–computer interaction,Decision theory,Animation,Artificial intelligence,Cognitive model,Affect (psychology),Multimedia,Dynamic Bayesian network
Conference
ISBN
Citations 
PageRank 
978-0-7695-3167-0
2
0.40
References 
Authors
3
4
Name
Order
Citations
PageRank
Yasmín Hernández1256.13
Gustavo Arroyo-Figueroa217022.16
L. Enrique Sucar31016118.72
Arroyo-Figueroa, G.420.40