Elicitation of latent learning needs through learning goals recommendation

Authors:
Nicola Capuano;Matteo Gaeta;Pierluigi Ritrovato;Saverio Salerno
Affiliations:
Centro di Ricerca in Matematica Pura ed Applicata, Fisciano SA, Italy;University of Salerno, Fisciano SA, Italy;University of Salerno, Fisciano SA, Italy;University of Salerno, Fisciano SA, Italy
Venue:
Computers in Human Behavior
Year:
2014

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Abstract

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.