Abstract
Using data mining technology to collect and analyze a large number of learning data generated during the learning process of learners, discover learners’ learning characteristics and problems, so that teachers can adopt reasonable intervention measures to learners to improve learners’ learning effects. This article aims to study the student performance prediction and learning intervention system model based on machine learning. Based on the analysis of the educational data mining process and performance prediction algorithms, the student performance prediction model and learning are constructed by comparing the performance of four different algorithms. The experimental results show that special attention should be paid to the historical information of students in the study of student behavior and study performance prediction.
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Kong, Y. (2022). Student Performance Prediction and Learning Intervention System Model Based on Machine Learning. In: Xu, Z., Alrabaee, S., Loyola-González, O., Zhang, X., Cahyani, N.D.W., Ab Rahman, N.H. (eds) Cyber Security Intelligence and Analytics. CSIA 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 123. Springer, Cham. https://doi.org/10.1007/978-3-030-96908-0_107
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DOI: https://doi.org/10.1007/978-3-030-96908-0_107
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