By Topic

Fuzzy user modeling for adaptation in educational hypermedia

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Kavcic, A. ; Fac. of Comput. & Inf. Sci., Univ. of Ljubljana, Slovenia

Education is a dominating application area for adaptive hypermedia. Web-based adaptive educational systems incorporate complex intelligent tutoring techniques, which enable the system to recognize an individual user and their needs, and consequently adapt the instructional sequence. The personalization is done through the user model, which collects information about the user. Since the description of user knowledge and features also involves imprecision and vagueness, a user model has to be designed that is able to deal with this uncertainty. This paper presents a way of describing the uncertainty of user knowledge, which is used for user knowledge modeling in an adaptive educational system. The system builds on the concept domain model. A fuzzy user model is proposed to deal with vagueness in the user's knowledge description. The model uses fuzzy sets for knowledge representation and linguistic rules for model updating. The data from the fuzzy user model form the basis for the system adaptation, which implements various navigation support techniques. The evaluation of the presented educational system has shown that the system and its adaptation techniques provide a valuable, easy-to-use tool, which positively affects user knowledge acquisition and, therefore, leads to better learning results.

Published in:

Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on  (Volume:34 ,  Issue: 4 )