CourseQ: the impact of visual and interactive course recommendation in university environments

Shin’ichi Konomi,Yuta Taniguchi,Min Lu,Boxuan Ma

doi:10.1186/s41039-021-00167-7

Shin’ichi Konomi, Yuta Taniguchi + Show 2 more

Open Access

https://doi.org/10.1186/s41039-021-00167-7

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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.

Highlights

Recommendation systems are increasingly used in many everyday services; they exploit very large information spaces to personalize many aspects of our digital lives and to help alleviate the problem of information overload in a variety of domains
Compared to our previous work, here we present a detailed description of the design choices made in the development of our interface and more comprehensive analysis of results to investigate the impact of visualization and interaction on the course recommendation system, and the key factors that influence the success of such a system
Discussion we link the results of the questionnaire to the interaction patterns of different users; we discuss the implication for the design of future interactive course recommendation systems

Summary

Introduction

Recommendation systems are increasingly used in many everyday services; they exploit very large information spaces to personalize many aspects of our digital lives and to help alleviate the problem of information overload in a variety of domains. Course recommendation systems can make learning environments more adaptive and effective by alleviating certain types of information overlord (Ma et al 2020). The course recommendation in universities, is different from the conventional movie recommendation or music recommendation because of the unique characteristics of educational settings such as course enrollment. Some students may have general interests without a clear idea of what they want to study For those students, course recommendations that help to explore various candidate courses can be extremely important. The students who have clear learning goals would prefer narrowed-down results according to their goals and interests. They would appreciate specific and accurate results

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