Abstract
In recent years, universities have been offering a rising number of courses, creating not only greater flexibility of choice, but simultaneously more complexity for students in their course selection. Therefore, this paper seeks to identify key aspects that should be considered when designing a course recommender system (CRS) in the higher education context. To achieve this, students’ selection criteria and processes were analyzed and condensed into requirements. Based upon these, a prototype was implemented and evaluated via think-aloud user tests. The results of this study indicate that a multidimensional approach shall be taken to optimize the user experience. As our main contribution, we identify six guidelines for the design of an effective CRS.
This research was conducted as part of the projects “Developing Digital Cultures for Teaching (DiKuLe)” and “Learning from Learners (VoLL-KI)” and was financed by “Stiftung Innovation in der Hochschullehre” as well as “Künstliche Intelligenz in der Hochschulbildung (Artificial Intelligence in Higher Education)”.
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Ochs, M., Hirmer, T., Past, K., Henrich, A. (2023). Design-Focused Development of a Course Recommender System for Digital Study Planning. In: Abelló, A., et al. New Trends in Database and Information Systems. ADBIS 2023. Communications in Computer and Information Science, vol 1850. Springer, Cham. https://doi.org/10.1007/978-3-031-42941-5_50
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