Elicitation of latent learning needs through learning goals recommendation

•We designed a hybrid recommender system able to suggest learning goals to learners.•We defined a methodology for providing recommendations.•The learning goals are suggested considering learners’ knowledge.•We integrated the recommender system into an existing learning platform (IWT).•The integration allow us to improve the IWT adaptive learning courses generation.

The aim of a recommender system is to estimate the relevance of a set of objects belonging to a given domain, starting from the information available about users and objects. Adaptive e-learning systems are able to automatically generate personalized learning experiences starting from a learner profile and a set of target learning goals. Starting form research results of these fields we defined a methodology and developed a software prototype able to recommend learning goals and to generate learning experiences for learners using an adaptive e-learning system. The prototype has been integrated within IWT: an existing commercial solution for personalized e-learning and experimented in a graduate computer science course.