The number of information systems using adaptation rules is increasing
quickly. These systems are usually focused on implement nice and complex
functionality for adaptation of contents, links or presentation, so software
engineering methodologies for the description of rules are required. In
addition, the distributed service oriented Internet philosophy presents the
challenge of combining different rules from independent Internet sources.
Moreover, easy authoring, rule reuse and collaborative design should be
enabled. This paper presents the AR (Adaptation Rules) model, a new software
engineering model for the description of rules for adaptation. These rules
can be composed as a set of smaller atomic, reusable, parametric,
interchangeable and interoperable rules, with clear restrictions in their
combinations. Our model enables the distribution of rules as well as rule
reuse and collaboration among rule creators. We illustrate our approach with
the application of this model to a hinting adaptive e-learning system that
generates exercises with hints, which can be adapted based on defined rules.
Advantages of the AR model are confirmed with an evaluation that has been
done with teachers and learning analytics experts for adaptive e-learning.
Prediction of Learner’s Performance in Adaptive E-Learning System using Learning Analytics