Abstract
Predicting the academic results and preparing the study plan are crucial concerns for students to improve their academic performance. The existing literature mainly focused to predict the academic results and how best the teacher can design a specific course for improving the student’s academic performance. However, the process of recommending study plan for a specific student based on his/her predicted results is not well investigated. Therefore, the objective of this study is to propose artificial intelligence (AI)-based models to predict the academic results and recommend study plan accordingly to improve the student’s performance. As outcomes, this study proposed two models based on sophisticated deep learning algorithms and artificial neural networks namely, result prediction and recommending study planner. The proposed result prediction and study-planner models showed the accuracy of 97.02% and 99.8%, respectively, on training datasets, and also 92.94% and 87.65%, respectively, on test datasets. A Web-based system for predicting results and recommending study plan is also developed based on the proposed models.
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Roy, A., Rahman, M.R., Islam, M.N., Saimon, N.I., Alfaz, M., Jaber, AAS. (2022). A Deep Learning Approach to Predict Academic Result and Recommend Study Plan for Improving Student’s Academic Performance. In: Karuppusamy, P., Perikos, I., García Márquez, F.P. (eds) Ubiquitous Intelligent Systems. Smart Innovation, Systems and Technologies, vol 243. Springer, Singapore. https://doi.org/10.1007/978-981-16-3675-2_19
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