Development of a Module Recommendation System using profession-related Data

Which module should I choose? A question that is central to students who can select parts of their curriculum themselves.

Räz, David, 2023

Art der Arbeit Master Thesis
Betreuende Dozierende Hinkelmann, Knut, Spahic, Maja
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Advisory about modules and support in academic planning can help in answering this question. This work investigates the relevance of course selection and its aspects and proposes a technical solution—a knowledge-based recommender system. This system, grounded in an ontology framework, aims to bridge the gap between students profession-related aspects, and the modules available.
The module descriptions for the case did not have information about the skills or knowledge taught. Using a large language model to match this domain-specific data of module descriptions with profession-related data proposed a considerable solution. Therefore, it was also used to classify modules in technical or non-technical modules. The information from the matching process was integrated into the ontology, and relations between modules and professions were established.
This artifact was developed using the case of the business school of the FHNW. The approach, however, is generic and can be used by other universities as well. With querying or reasoning, the modules can be recommended based on the entered job. The artifact was eventually evaluated using two different approaches, evaluating its technical development as well as assessing its clarity, comprehensibility, user-friendliness, recommendations, and benefits.
Studiengang: Business Information Systems (Master)
Vertraulichkeit: öffentlich
Art der Arbeit
Master Thesis
Autorinnen und Autoren
Räz, David
Betreuende Dozierende
Hinkelmann, Knut, Spahic, Maja
Sprache der Arbeit
Business Information Systems (Master)
Standort Studiengang