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Improving the Behavior of Intelligent Tutoring Agents with Data Mining
May/June 2009 (vol. 24 no. 3)
pp. 46-53
ASCII Text
x 
 
Roger Nkambou, Philippe Fournier-Viger, Engelbert Mephu Nguifo, "Improving the Behavior of Intelligent Tutoring Agents with Data Mining," IEEE Intelligent Systems, vol. 24, no. 3, pp. 46-53, May/June, 2009.
 
 
BibTex
x
 
@article{ 10.1109/MIS.2009.59,
author = {Roger Nkambou and Philippe Fournier-Viger and Engelbert Mephu Nguifo},
title = {Improving the Behavior of Intelligent Tutoring Agents with Data Mining},
journal ={IEEE Intelligent Systems},
volume = {24},
number = {3},
issn = {1541-1672},
year = {2009},
pages = {46-53},
doi = {http://doi.ieeecomputersociety.org/10.1109/MIS.2009.59},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - MGZN
JO - IEEE Intelligent Systems
TI - Improving the Behavior of Intelligent Tutoring Agents with Data Mining
IS - 3
SN - 1541-1672
SP46
EP53
EPD - 46-53
A1 - Roger Nkambou,
A1 - Philippe Fournier-Viger,
A1 - Engelbert Mephu Nguifo,
PY - 2009
KW - data mining
KW - intelligent agent
KW - intelligent tutoring systems
KW - cognitive agent
KW - knowledge acquisition
KW - knowledge discovery
VL - 24
JA - IEEE Intelligent Systems
ER -
 
Roger Nkambou, University of Quebec
Philippe Fournier-Viger, University of Quebec
Engelbert Mephu Nguifo, Université Blaise- Pascal, Clermont-Ferrand II
This article presents a novel framework for adapting the behavior of intelligent agents. The framework consists of an extended sequential pattern mining algorithm that, in combination with association rule discovery techniques, is used to extract temporal patterns and relationships from the behavior of human agents executing a procedural task. The proposed framework has been integrated within the CanadarmTutor, an intelligent tutoring agent aimed at helping students solve procedural problems that involve moving a robotic arm in a complex virtual environment. We present the results of an evaluation that demonstrates the benefits of this integration to agents acting in ill-defined domains.

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Index Terms:
data mining, intelligent agent, intelligent tutoring systems, cognitive agent, knowledge acquisition, knowledge discovery
Citation:
Roger Nkambou, Philippe Fournier-Viger, Engelbert Mephu Nguifo, "Improving the Behavior of Intelligent Tutoring Agents with Data Mining," IEEE Intelligent Systems, vol. 24, no. 3, pp. 46-53, May-June 2009, doi:10.1109/MIS.2009.59
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