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Title:
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GENERATING GLOBAL MODEL TO PREDICT STUDENTS' DROPOUT IN MOROCCAN HIGHER EDUCATIONAL INSTITUTIONS USING CLUSTERING |
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Author(s):
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Khalid Oqaidi, Sarah Aouhassi and Khalifa Mansouri |
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ISBN:
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978-989-8704-39-9 |
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Editors:
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Miguel Baptista Nunes and Pedro Isaias |
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Year:
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2022 |
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Edition:
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Single |
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Keywords:
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Students' Dropout, Higher Education, Machine Learning Prediction, Clustering |
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Type:
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Short Paper |
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First Page:
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159 |
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Last Page:
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164 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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The dropout of students is one of the major obstacles that ruin the improvement of higher education quality. To facilitate the study of students' dropout in Moroccan universities, this paper aims to establish a clustering approach model based on machine learning algorithms to determine Moroccan universities categories. Our objective in this article is to present a theoretical model capable of identifying higher education institutions that are similar in the dropout phenomenon. To avoid making Educational Data Mining Analysis on each higher educational programs predict students' performance, with such a classification we can reduce the number of studies to be done on one institution in each category of universities. |
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