Abstract
Course selection is a crucial task which may affect greatly on student performance. Because of poor performances, numerous students have been receiving formal warnings and expulsions from universities. Clearly, a good strategy for study progress which can come from course recommendation methods really holds an important role to obtain a good study performance. In addition, early warnings that release on challenging courses enable students to prepare better for such courses. The current course recommendation systems are usually conducted from marks prediction and factor analysis on marks of courses based on advancements of machine learning approaches. In this study, we propose a course recommender system by using deep learning techniques with MultiLayer Perceptron and pre-processing methods. The prediction tasks are performed on approximately four million of mark records at Can Tho University, Vietnam to provide recommendations on course selection to students. The proposed method reveals promising results and is expected to apply in practical cases.
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Notes
- 1.
Can Tho University, 2020. Management Information System, accessed on 12/5/2020. Available from https://htql.ctu.edu.vn/.
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Dien, T.T., Hoai-Sang, L., Thanh-Hai, N., Thai-Nghe, N. (2020). Course Recommendation with Deep Learning Approach. In: Dang, T.K., Küng, J., Takizawa, M., Chung, T.M. (eds) Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications. FDSE 2020. Communications in Computer and Information Science, vol 1306. Springer, Singapore. https://doi.org/10.1007/978-981-33-4370-2_5
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