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A Personalized Course Recommender System for Undergraduate Students

Thi-Hai-Yen Vuong 1, Thi-Thu Trinh 2, Hong-Duyen Ha 2, Xuan-Hieu Phan 2, and Thi-Oanh Tran 3
1. School of Information Science, Japan Advanced Institute of Science and Technology, Ishikawa, Japan
2. University of Engineering and Technology, Vietnam National University Hanoi, Vietnam
3. International School, Vietnam National University Hanoi, Vietnam
Abstract—In this paper, we describe a web-based course recommender system which has a variety of functions for supporting students in academic fields. The system’s goal is to help students manage their own study progress in a more effective way. With this system, students would achieve better performance, find it easy to select courses without wondering which will give them high score or which are better for their future job or career path. The core functionalities of the system are partly based on recommendation methods. The first task is the prediction of student performance to help them estimate their performances on selected courses. These predicted results help students choose courses that are appropriate for them to get higher scores. Second, the system will automatically build a study strategy for next two years or even entirely four academic years based on their ability and related information. Our system also provides students a general view of their learning status: profile, grades, taken courses, credits, important school news, time table, etc. By using these functionalities, students will have a guidance and an up-to-date studying path to follow, as well as efficiently complete their school work.
 
Index Terms—student performance prediction, recommender system, study strategy

Cite: Thi-Hai-Yen Vuong, Thi-Thu Trinh, Hong-Duyen Ha, Xuan-Hieu Phan, and Thi-Oanh Tran, "A Personalized Course Recommender System for Undergraduate Students," International Journal of Learning and Teaching, Vol. 5, No. 3, pp. 181-190, September 2019. doi: 10.18178/ijlt.5.3.181-190
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