Using decision trees for improving AEH courses

Abstract

Adaptive educational hypermedia systems (AEHS) seek to make easier the learning process for each student by providing each one (potentially) different educative contents, customized according to the student’s needs and preferences. One of the main concerns with AEHS is to test and decide whether adaptation strategies are beneficial for all the students or, on the contrary, some of them would benefit from different decisions of the adaptation engine. Data-mining (DM) techniques can provide support to deal with this issue; specifically, this chapter proposes the use of DM techniques for detecting potential problems of adaptation in AEHS. © 2010 by Taylor & Francis Group, LLC.