Decision Models in the Design of Adaptive Educational Hypermedia Systems

Abstract

Several efforts have been reported in literature aiming to support the Adaptation Model (AM) design in Adaptive Educational Hypermedia Systems (AEHS) with either guidance for the direct definition of adaptation rules or semi-automated mechanisms that generate the AM through the implicit definition of such rules. The main drawback of the direct definition of adaptation rules is that there can be cases during the run-time execution of AEHS where no adaptation decision can be made, due to insufficiency and/or inconsistency of the pre-defined adaptation rule sets. The goal of the semi-automated, decision-based approaches is to generate a continuous decision function that estimates the desired AEHS response, aiming to overcome the above mentioned problem. However, such approaches still miss a commonly accepted framework for evaluating their performance. In this chapter, we review the design approaches for the definition of the AM in AEHS and discuss a set of performance evaluation metrics proposed by the literature for validating the use of decision-based approaches.