Towards predictive models for e-learning

Many organizations view e-learning as a useful organizational component to face current competitive challenges. However, results have not shown up the expected benefits. This research aims at identifying alternative ways to promote learning-centred design, in order to build more cost-effective and satisfying technology-enhanced learning experiences. Though further research is needed to confirm results, this exploratory research sheds some light on this issue by means of using a holistic, bottom-up Usability-Evaluation framework, method and supporting tool-kit, that made possible to cluster students, based upon their motivation-to-elearn, and identify their specific technical and non-technical improvement areas. This kind of results helps contextualize the learning experience by supporting the early identification of troublesome areas and the definition of intervention strategies by student clusters. By so doing, TEL development teams can help student performance and satisfaction, and continuously improve pedagogical practice and system adaptability. In this manner, this research sets up a workable way towards predictive modelling.