Machine learning methods in predicting the student academic motivation
Academic motivation is closely related to academic performance. For educators, it is equally important to detect early students with a lack of academic motivation as it is to detect those with a high level of academic motivation. In endeavouring to develop a classification model for predicting stude...
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| Format: | Article |
| Language: | English |
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Croatian Operational Research Society
2017-01-01
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| Series: | Croatian Operational Research Review |
| Online Access: | http://hrcak.srce.hr/file/285562 |
| _version_ | 1819153805972865024 |
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| author | Ivana Đurđević Babić |
| author_facet | Ivana Đurđević Babić |
| author_sort | Ivana Đurđević Babić |
| collection | DOAJ |
| description | Academic motivation is closely related to academic performance. For educators, it is equally important to detect early students with a lack of academic motivation as it is to detect those with a high level of academic motivation. In endeavouring to develop a classification model for predicting student academic motivation based on their behaviour in learning management system (LMS) courses, this paper intends to establish links between the predicted student academic motivation and their behaviour in the LMS course. Students from all years at the Faculty of Education in Osijek participated in this research. Three machine learning classifiers (neural networks, decision trees, and support vector machines) were used. To establish whether a significant difference in the performance of models exists, a t-test of the difference in proportions was used. Although, all classifiers were successful, the neural network model was shown to be the most successful in detecting the student academic motivation based on their behaviour in LMS course. |
| first_indexed | 2024-12-22T15:11:02Z |
| format | Article |
| id | doaj.art-99c2a35323bb4fa487b0330477f46f45 |
| institution | Directory Open Access Journal |
| issn | 1848-0225 1848-9931 |
| language | English |
| last_indexed | 2024-12-22T15:11:02Z |
| publishDate | 2017-01-01 |
| publisher | Croatian Operational Research Society |
| record_format | Article |
| series | Croatian Operational Research Review |
| spelling | doaj.art-99c2a35323bb4fa487b0330477f46f452022-12-21T18:21:52ZengCroatian Operational Research SocietyCroatian Operational Research Review1848-02251848-99312017-01-018244346110.17535/crorr.2017.0028193542Machine learning methods in predicting the student academic motivationIvana Đurđević Babić0Faculty of Education, University of Osijek, Cara Hadrijana 10, 31 000 Osijek, CroatiaAcademic motivation is closely related to academic performance. For educators, it is equally important to detect early students with a lack of academic motivation as it is to detect those with a high level of academic motivation. In endeavouring to develop a classification model for predicting student academic motivation based on their behaviour in learning management system (LMS) courses, this paper intends to establish links between the predicted student academic motivation and their behaviour in the LMS course. Students from all years at the Faculty of Education in Osijek participated in this research. Three machine learning classifiers (neural networks, decision trees, and support vector machines) were used. To establish whether a significant difference in the performance of models exists, a t-test of the difference in proportions was used. Although, all classifiers were successful, the neural network model was shown to be the most successful in detecting the student academic motivation based on their behaviour in LMS course.http://hrcak.srce.hr/file/285562 |
| spellingShingle | Ivana Đurđević Babić Machine learning methods in predicting the student academic motivation Croatian Operational Research Review |
| title | Machine learning methods in predicting the student academic motivation |
| title_full | Machine learning methods in predicting the student academic motivation |
| title_fullStr | Machine learning methods in predicting the student academic motivation |
| title_full_unstemmed | Machine learning methods in predicting the student academic motivation |
| title_short | Machine learning methods in predicting the student academic motivation |
| title_sort | machine learning methods in predicting the student academic motivation |
| url | http://hrcak.srce.hr/file/285562 |
| work_keys_str_mv | AT ivanađurđevicbabic machinelearningmethodsinpredictingthestudentacademicmotivation |