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ERIC Number: ED639750
Record Type: Non-Journal
Publication Date: 2022
Pages: 6
Abstractor: As Provided
ISBN: N/A
ISSN: N/A
EISSN: N/A
Generating Global Model to Predict Students' Dropout in Moroccan Higher Educational Institutions Using Clustering
Khalid Oqaidi; Sarah Aouhassi; Khalifa Mansouri
International Association for Development of the Information Society, Paper presented at the International Association for Development of the Information Society (IADIS) International Conference: e-Learning 2022, Part of the Multi Conference on Computer Science and Information Systems (MCCSIS 2022) (16th, Lisbon, Portugal, Jul 19-22, 2022)
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. [For the full proceedings, see ED639633.]
International Association for the Development of the Information Society. e-mail: secretariat@iadis.org; Web site: http://www.iadisportal.org
Publication Type: Speeches/Meeting Papers; Reports - Descriptive
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Morocco
Grant or Contract Numbers: N/A