You are required to read and agree to the below before accessing a full-text version of an article in the IDE article repository.

The full-text document you are about to access is subject to national and international copyright laws. In most cases (but not necessarily all) the consequence is that personal use is allowed given that the copyright owner is duly acknowledged and respected. All other use (typically) require an explicit permission (often in writing) by the copyright owner.

For the reports in this repository we specifically note that

  • the use of articles under IEEE copyright is governed by the IEEE copyright policy (available at http://www.ieee.org/web/publications/rights/copyrightpolicy.html)
  • the use of articles under ACM copyright is governed by the ACM copyright policy (available at http://www.acm.org/pubs/copyright_policy/)
  • technical reports and other articles issued by M‰lardalen University is free for personal use. For other use, the explicit consent of the authors is required
  • in other cases, please contact the copyright owner for detailed information

By accepting I agree to acknowledge and respect the rights of the copyright owner of the document I am about to access.

If you are in doubt, feel free to contact webmaster@ide.mdh.se

Case-Based Reasoning to Improve Adaptability of Intelligent Tutoring Systems

Fulltext:


Authors:

Peter Funk, Owen Conlan

Publication Type:

Conference/Workshop Paper

Venue:

Workshop on Case-Based Reasoning for Education and Training, CBRET2002

Publisher:

Robert Gordon University


Abstract

Educational Adaptive Hypermedia Systems and Intelligent Tutoring Systems (ITS) are capable of producing personalized learning courses that are tailored to various learning preferences and characteristics of the learner. In the past ITS traditionally have embedded experts’ knowledge in the structure of its content and applied appropriate design models. However, such systems have continually been criticized for believing that this is sufficient for effective learn-ing to occur [Stauffer 96]. For a tutor who develops such a system there may be many permutations of narrative, concepts and content that may be combined to produce the learner courses. However, the more levels of personalization the system can provide the greater likelihood exists that the system may produce an unexpected or undesired effect. As a tutor it can be difficult to monitor the suit-ability of the personalized course offerings on an individual learner basis. This paper provides a high level overview of a technique for predicting/monitoring personalized course suitability and increasing the quality of delivered courses using CBR in combination with other techniques, e.g. filtering techniques.

Bibtex

@inproceedings{Funk351,
author = {Peter Funk and Owen Conlan},
title = {Case-Based Reasoning to Improve Adaptability of Intelligent Tutoring Systems},
pages = {15--23},
month = {September},
year = {2002},
booktitle = {Workshop on Case-Based Reasoning for Education and Training, CBRET2002},
publisher = {Robert Gordon University},
url = {http://www.es.mdh.se/publications/351-}
}