|
Published Articles >> Table of Contents >> Abstract
IEEE/WIC International Conference on Intelligent Agent Technology (IAT'03)
p. 614
Web Course Self-Adaptation
Mohammed A. Razek, Université de Montréal, Canada
Claude Frasson, Université de Montréal, Canada
Marc Kaltenbach, Bishop's University
Full Article Text:
 
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IAT.2003.1241157
Send link to a friend
| Abstract |
|
This paper describes the methodology of an intelligent
agent for building a self-adaptive course on the Web. An
important task, therefore, is to combine adaptability with
the learner-driven course in order to get a self-adaptive
mechanism. For this, we have suggested a new structure
for a web course. Based on this structure, we have
suggested a new method to evaluate the granularity level
of each segment on the course. This method evaluates the
segment that a learner most prefers. To achieve this goal,
we design and implement an agent called a confidence
agent. Our experiment to evaluate our adaptation method
shows that our approach greatly improves the domain
model, and presents a course better related to the learner’s
needs.
|
 Additional Information
|
Citation:
Mohammed A. Razek, Claude Frasson, Marc Kaltenbach,
"Web Course Self-Adaptation,"
iat,
p. 614,
IEEE/WIC International Conference on Intelligent Agent Technology (IAT'03),
2003
|
|
