CourseQ: The Impact of Visual and Interactive Course Recommendation in University Environments

Autor/inn/en	Ma, Boxuan; Lu, Min; Taniguchi, Yuta; Konomi, Shin'ichi
Titel	CourseQ: The Impact of Visual and Interactive Course Recommendation in University Environments
Quelle	In: Research and Practice in Technology Enhanced Learning, 16 (2021), Artikel 18 (24 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Ma, Boxuan)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1793-7078
DOI	10.1186/s41039-021-00167-7
Schlagwörter	Universities; College Students; Course Selection (Students); Visualization; Interaction; Computer Interfaces; Educational Technology + Suchen Sie Ihr Suchwort? University; Universität; Collegestudent; Course selection; Student; Students; Kurswahl; Visualisation; Visualisierung; Interaktion; Unterrichtsmedien
Abstract	The abundance of courses available in a university often overwhelms students as they must select courses that are relevant to their academic interests and satisfy their requirements. A large number of existing studies in course recommendation systems focus on the accuracy of prediction to show students the most relevant courses with little consideration on interactivity and user perception. However, recent work has highlighted the importance of user-perceived aspects of recommendation systems, such as transparency, controllability, and user satisfaction. This paper introduces CourseQ, an interactive course recommendation system that allows students to explore courses by using a novel visual interface so as to improve transparency and user satisfaction of course recommendations. We describe the design concepts, interactions, and algorithm of the proposed system. A within-subject user study (N=32) was conducted to evaluate our system compared to a baseline interface without the proposed interactive visualization. The evaluation results show that our system improves many user-centric metrics including user acceptance and understanding of the recommendation results. Furthermore, our analysis of user interaction behaviors in the system indicates that CourseQ could help different users with their course-seeking tasks. Our results and discussions highlight the impact of visual and interactive features in course recommendation systems and inform the design of future recommendation systems for higher education. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01