An Artificial Intelligence Approach to Monitor Student Performance and Devise Preventive Measures

Autor/inn/en	Khan, Ijaz; Ahmad, Abdul Rahim; Jabeur, Nafaa; Mahdi, Mohammed Najah
Titel	An Artificial Intelligence Approach to Monitor Student Performance and Devise Preventive Measures
Quelle	In: Smart Learning Environments, 8 (2021), Artikel 17 (18 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Khan, Ijaz)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2196-7091
DOI	10.1186/s40561-021-00161-y
Schlagwörter	Artificial Intelligence; Academic Achievement; Progress Monitoring; Data Collection; Prevention; At Risk Students; Prediction; Models + Suchen Sie Ihr Suchwort? Künstliche Intelligenz; Schulleistung; Data capture; Datensammlung; Prävention; Vorbeugung; Vorhersage; Analogiemodell
Abstract	A major problem an instructor experiences is the systematic monitoring of students' academic progress in a course. The moment the students, with unsatisfactory academic progress, are identified the instructor can take measures to offer additional support to the struggling students. The fact is that the modern-day educational institutes tend to collect enormous amount of data concerning their students from various sources, however, the institutes are craving novel procedures to utilize the data to magnify their prestige and improve the education quality. This research evaluates the effectiveness of machine learning algorithms to monitor students' academic progress and informs the instructor about the students at the risk of ending up with unsatisfactory result in a course. In addition, the prediction model is transformed into a clear shape to make it easy for the instructor to prepare the necessary precautionary procedures. We developed a set of prediction models with distinct machine learning algorithms. Decision tree triumph over other models and thus is further transformed into easily explicable format. The final output of the research turns into a set of supportive measures to carefully monitor students' performance from the very start of the course and a set of preventive measures to offer additional attention to the struggling students. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01