The development of a predictive model for students’ final grades using machine learning techniques
As per research, utilizing predictive analytics in education can be very beneficial. It can help educators improve students' performance by analyzing historical data through various approaches such as data mining and machine learning. However, there is a scarcity of studies on using machine lea...
| Päätekijät: | , , |
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| Aineistotyyppi: | Artikkeli |
| Kieli: | English |
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Penerbit UMP
2023
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| Aiheet: | |
| Linkit: | http://umpir.ump.edu.my/id/eprint/40003/1/The%20development%20of%20apredictive%20model%20for%20students.pdf |
| _version_ | 1825815401806692352 |
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| author | N. H., A. Rahman Sahimel Azwal, Sulaiman Nor Azuana, Ramli |
| author_facet | N. H., A. Rahman Sahimel Azwal, Sulaiman Nor Azuana, Ramli |
| author_sort | N. H., A. Rahman |
| collection | UMP |
| description | As per research, utilizing predictive analytics in education can be very beneficial. It can help educators improve students' performance by analyzing historical data through various approaches such as data mining and machine learning. However, there is a scarcity of studies on using machine learning and predictive analytics to enhance student performance in Malaysian higher education. This study used the records of 450 students enrolled in the Business Statistics course at Universiti Islam Pahang Sultan Ahmad Shah (UnIPSAS) from 2013, obtained from UnIPSAS's Learning Management System. The aim was to develop the best predictive model for forecasting students' final grades based on their performance levels, using machine learning techniques such as Decision Tree, k-Nearest Neighbor, and Naïve Bayes. The final model was developed using Python software. The results showed a strong negative correlation between the students' carry marks and their final grades, with an r-value of -0.8. Naïve Bayes was found to be the best model, with an AUC score of 0.79. |
| first_indexed | 2024-03-06T13:12:56Z |
| format | Article |
| id | UMPir40003 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T13:12:56Z |
| publishDate | 2023 |
| publisher | Penerbit UMP |
| record_format | dspace |
| spelling | UMPir400032024-01-15T04:04:37Z http://umpir.ump.edu.my/id/eprint/40003/ The development of a predictive model for students’ final grades using machine learning techniques N. H., A. Rahman Sahimel Azwal, Sulaiman Nor Azuana, Ramli QA Mathematics As per research, utilizing predictive analytics in education can be very beneficial. It can help educators improve students' performance by analyzing historical data through various approaches such as data mining and machine learning. However, there is a scarcity of studies on using machine learning and predictive analytics to enhance student performance in Malaysian higher education. This study used the records of 450 students enrolled in the Business Statistics course at Universiti Islam Pahang Sultan Ahmad Shah (UnIPSAS) from 2013, obtained from UnIPSAS's Learning Management System. The aim was to develop the best predictive model for forecasting students' final grades based on their performance levels, using machine learning techniques such as Decision Tree, k-Nearest Neighbor, and Naïve Bayes. The final model was developed using Python software. The results showed a strong negative correlation between the students' carry marks and their final grades, with an r-value of -0.8. Naïve Bayes was found to be the best model, with an AUC score of 0.79. Penerbit UMP 2023-04 Article PeerReviewed pdf en cc_by_4 http://umpir.ump.edu.my/id/eprint/40003/1/The%20development%20of%20apredictive%20model%20for%20students.pdf N. H., A. Rahman and Sahimel Azwal, Sulaiman and Nor Azuana, Ramli (2023) The development of a predictive model for students’ final grades using machine learning techniques. Data Analytics and Applied Mathematics (DAAM), 4 (1). pp. 40-48. ISSN 2773-4854. (Published) https://doi.org/10.15282/daam.v4i1.9591 https://doi.org/10.15282/daam.v4i1.9591 |
| spellingShingle | QA Mathematics N. H., A. Rahman Sahimel Azwal, Sulaiman Nor Azuana, Ramli The development of a predictive model for students’ final grades using machine learning techniques |
| title | The development of a predictive model for students’ final grades using machine learning techniques |
| title_full | The development of a predictive model for students’ final grades using machine learning techniques |
| title_fullStr | The development of a predictive model for students’ final grades using machine learning techniques |
| title_full_unstemmed | The development of a predictive model for students’ final grades using machine learning techniques |
| title_short | The development of a predictive model for students’ final grades using machine learning techniques |
| title_sort | development of a predictive model for students final grades using machine learning techniques |
| topic | QA Mathematics |
| url | http://umpir.ump.edu.my/id/eprint/40003/1/The%20development%20of%20apredictive%20model%20for%20students.pdf |
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