Authors:
Kerstin Wagner
1
;
Agathe Merceron
1
;
Petra Sauer
1
and
Niels Pinkwart
2
Affiliations:
1
Berliner Hochschule für Technik, Berlin, Germany
;
2
Deutsches Forschungszentrum für Künstliche Intelligenz, Berlin, Germany
Keyword(s):
Course Recommender System, Survey, Mann-Whitney U Test, Wilcoxon Signed-Rank Test, Benjamini-Hochberg Procedure.
Abstract:
In this work, we present a survey of a course recommender conducted among students and its results. The course recommender system, published in our previours work (Wagner et al., 2023), is based on the nearest neighbors algorithm and aims to support students in their course enrollment; it targets above all students who did not pass all mandatory courses as indicated in the study handbook in their first or second semester at university. The primary objective of the survey was to evaluate the perceived quality of explanations and recommendations based on two presentation variants (a ranked list of courses and a set of courses), as well as the general trust in such systems. The survey included quantitative measures and demographic information from the students, so that different subgroups could be evaluated. The results indicate that students tend to trust recommender systems and that they tend to understand the explanations. No clear winner emerges between the presentation of the cours
es as a set and as a ranked list. The survey data explorations are available at: https://kwbln.github.io/csedu24.
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