Rule discovery in Web-based educational systems using Grammar-Based Genetic Programming

This paper describes the use of data mining methods in an e-learning system for providing feedback to courseware authors. The discovered information is presented in the form of prediction rules since these are highly comprehensible and they show important relationships among the presented data. The rules will be used to improve courseware, particularly Adaptive Systems for Web-based Education (ASWE). We propose to use evolutionary algorithms as the rule discovery methods, concretely Grammar-Based Genetic Programming (GBGP) with multi-objective optimization techniques. We have developed a specific tool named EPRules (Education Prediction Rules) to facilitate and simplify the knowledge discovery process for usage data in web-based education systems.