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.