Abstract
This paper proposes a recommendation engine for educational contents in the organizational context of a user. The novelty in this paper lies in creating a context model for a user incorporating the role and the tasks assigned to him, and its application to recommendation problem. The recommendations are made on the basis of the estimated gap that exists between an employee’s current knowledge level and the skill-set required in his job-context. A probabilistic reasoning framework is used for recommendations, to account for the inexact specifications of user competencies and requirements of the job context.
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Saraswat, N., Ghosh, H., Agrawal, M., Narayanan, U. (2015). Contextual Recommendation of Educational Contents. In: Conati, C., Heffernan, N., Mitrovic, A., Verdejo, M. (eds) Artificial Intelligence in Education. AIED 2015. Lecture Notes in Computer Science(), vol 9112. Springer, Cham. https://doi.org/10.1007/978-3-319-19773-9_44
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DOI: https://doi.org/10.1007/978-3-319-19773-9_44
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