Adaptive mobile learning environments and evaluation: CoMoLE and geses

Abstract

This article presents the basis and experience with two systems that support the creation and evaluation of adaptive mobile learning environments. In this type of environment, dynamically generated by CoMoLE, the most suitable activities to be carried out by each student are recommended, so that s/he can benefit from spare time. The interface to support activity accomplishment is adapted by selecting the most suitable contents and tools for each student. To this end, student features, needs, previous interactions and context are considered. However, evaluating whether the recommendations and adaptation fit the student’s needs is complex. With the purpose of evaluating adaptive learning systems, the method GeSES was designed. GeSES uses Data Mining techniques to extract information about potential problems. It has been used to evaluate a CoMoLE-based learning 
environment and the results obtained are presented in this article.