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

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Title: CourseQ: The Impact of Visual and Interactive Course Recommendation in University Environments
Language: English
Authors: Ma, Boxuan (ORCID 0000-0002-1566-880X), Lu, Min, Taniguchi, Yuta, Konomi, Shin'ichi
Source: Research and Practice in Technology Enhanced Learning. 2021 16.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: N
Page Count: 24
Publication Date: 2021
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Universities, College Students, Course Selection (Students), Visualization, Interaction, Computer Interfaces, Educational Technology
DOI: 10.1186/s41039-021-00167-7
ISSN: 1793-7078
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.
Abstractor: As Provided
Entry Date: 2021
Accession Number: EJ1300544
Database: ERIC
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  Data: <searchLink fieldCode="AR" term="%22Ma%2C+Boxuan%22">Ma, Boxuan</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-1566-880X">0000-0002-1566-880X</externalLink>)<br /><searchLink fieldCode="AR" term="%22Lu%2C+Min%22">Lu, Min</searchLink><br /><searchLink fieldCode="AR" term="%22Taniguchi%2C+Yuta%22">Taniguchi, Yuta</searchLink><br /><searchLink fieldCode="AR" term="%22Konomi%2C+Shin'ichi%22">Konomi, Shin'ichi</searchLink>
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  Data: 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.
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      – SubjectFull: College Students
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      – SubjectFull: Course Selection (Students)
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