An artificial intelligence approach to monitor student performance and devise preventive measures
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...
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Springer
2023
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| _version_ | 1833411519765807104 |
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| author | Khan I. Ahmad A.R. Jabeur N. Mahdi M.N. |
| author2 | 58061521900 |
| author_facet | 58061521900 Khan I. Ahmad A.R. Jabeur N. Mahdi M.N. |
| author_sort | Khan I. |
| building | UNITEN Library |
| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | 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. � 2021, The Author(s). |
| format | Article |
| id | my.uniten.dspace-25881 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2023 |
| publisher | Springer |
| record_format | dspace |
| spelling | my.uniten.dspace-258812023-05-29T17:05:24Z An artificial intelligence approach to monitor student performance and devise preventive measures Khan I. Ahmad A.R. Jabeur N. Mahdi M.N. 58061521900 35589598800 6505727698 56727803900 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. � 2021, The Author(s). Final 2023-05-29T09:05:24Z 2023-05-29T09:05:24Z 2021 Article 10.1186/s40561-021-00161-y 2-s2.0-85114501475 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114501475&doi=10.1186%2fs40561-021-00161-y&partnerID=40&md5=c57ce71f62d6094a3bfd9f3196600e0b https://irepository.uniten.edu.my/handle/123456789/25881 8 1 17 All Open Access, Gold Springer Scopus |
| spellingShingle | Khan I. Ahmad A.R. Jabeur N. Mahdi M.N. An artificial intelligence approach to monitor student performance and devise preventive measures |
| title | An artificial intelligence approach to monitor student performance and devise preventive measures |
| title_full | An artificial intelligence approach to monitor student performance and devise preventive measures |
| title_fullStr | An artificial intelligence approach to monitor student performance and devise preventive measures |
| title_full_unstemmed | An artificial intelligence approach to monitor student performance and devise preventive measures |
| title_short | An artificial intelligence approach to monitor student performance and devise preventive measures |
| title_sort | artificial intelligence approach to monitor student performance and devise preventive measures |
| url_provider | http://dspace.uniten.edu.my/ |