Data-driven and human-controlled intelligent recommender agents for digitalized education

Murillo, Francis, 2018

Art der Arbeit Master Thesis
Auftraggebende
Betreuende Dozierende Witschel, Hans Friedrich
Keywords
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In the environment of e-learning many approaches for recommender systems have been proposed. They are based on data or human driven knowledge, which have different advantages and disadvantages. To combine these two approaches, the data of three elearning courses was analysed. The data-based knowledge was combined with human knowledge of the corresponding course lecturers. The combined knowledge was represented in a Bayesian network to generate recommendations for students attendingthese e-learning courses. A prototype was implemented to simulate one of these coursesand to propose recommendations to test persons for an evaluation.
Studiengang: Business Information Systems (Master)
Vertraulichkeit: öffentlich
Art der Arbeit
Master Thesis
Autorinnen und Autoren
Murillo, Francis
Betreuende Dozierende
Witschel, Hans Friedrich
Publikationsjahr
2018
Sprache der Arbeit
Englisch
Vertraulichkeit
öffentlich
Studiengang
Business Information Systems (Master)
Standort Studiengang
Olten