Abstract
Education is an important determinant of nation that succeed, nowadays, artificial intelligence algorithms have been applying practically in all field of science. As a result, learning analytics was born, referring to artificial intelligence techniques used in the field of education. The aim of this work is to build a machine learning models that can predict the student grade retention in K-9 grade. This work, first, applies six supervised artificial intelligence techniques, and validate them within four scenarios according the normalization and balancing of data in a second step, finally, these models was validated according to four recognized measures in order to choose the one that fit very well. The final purpose of our work is to contribute to the education field, we achieve this by providing some new idea where we have applied machine learning algorithms in grade retention research issue.
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Ibourk, A., Ouaadi, I. (2022). An Exploration of Student Grade Retention Prediction Using Machine Learning Algorithms. In: Fakir, M., Baslam, M., El Ayachi, R. (eds) Business Intelligence. CBI 2022. Lecture Notes in Business Information Processing, vol 449. Springer, Cham. https://doi.org/10.1007/978-3-031-06458-6_8
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