Optimization of Markov chain modeling in predicting college student retention
College student retention is one of the most important metrics in higher education. With institutions across the US facing decreasing enrollment, developing a reliable retention prediction method is crucial. In recent years, the use of the Markov chain model in forecasting student enrollment and pro...
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| Format: | Article |
| Language: | English |
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University of South Florida (USF) M3 Publishing
2024-12-01
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| Series: | Journal of Global Education and Research |
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| Online Access: | https://digitalcommons.usf.edu/jger/vol8/iss3/6 |
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| author | Kien Nguyen |
| author_facet | Kien Nguyen |
| author_sort | Kien Nguyen |
| collection | DOAJ |
| description | College student retention is one of the most important metrics in higher education. With institutions across the US facing decreasing enrollment, developing a reliable retention prediction method is crucial. In recent years, the use of the Markov chain model in forecasting student enrollment and progression has become more common, but there is little work on its application in student retention. One key factor in determining this model's effectiveness is what parameters should be used in the student population’s segmentation or grouping. This study presents a rigorous algorithm, coupled with a prediction model, capable of selecting parameters that provide the most accurate results for term-to-term retention prediction using the Markov chain analysis. This is a pioneering attempt to optimize the Markov chain for retention prediction. Results are verified against an enrollment dataset from a public institution. With high accuracy, flexibility, and interpretability, the coupled algorithm model is an effective tool for institutional planning. Future iterations will focus on adding behavioral data and integrating the model with advanced deep learning methods to predict the detailed status of returning students, such as full-time equivalent and class level. |
| format | Article |
| id | doaj-art-975b14aae03c4ad8a69f45fdf1cb43a6 |
| institution | OA Journals |
| issn | 2577-509X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | University of South Florida (USF) M3 Publishing |
| record_format | Article |
| series | Journal of Global Education and Research |
| spelling | doaj-art-975b14aae03c4ad8a69f45fdf1cb43a62025-08-20T01:52:19ZengUniversity of South Florida (USF) M3 PublishingJournal of Global Education and Research2577-509X2024-12-018310.5038/2577-509X.8.3.1360Optimization of Markov chain modeling in predicting college student retentionKien Nguyen0University of North CarolinaCollege student retention is one of the most important metrics in higher education. With institutions across the US facing decreasing enrollment, developing a reliable retention prediction method is crucial. In recent years, the use of the Markov chain model in forecasting student enrollment and progression has become more common, but there is little work on its application in student retention. One key factor in determining this model's effectiveness is what parameters should be used in the student population’s segmentation or grouping. This study presents a rigorous algorithm, coupled with a prediction model, capable of selecting parameters that provide the most accurate results for term-to-term retention prediction using the Markov chain analysis. This is a pioneering attempt to optimize the Markov chain for retention prediction. Results are verified against an enrollment dataset from a public institution. With high accuracy, flexibility, and interpretability, the coupled algorithm model is an effective tool for institutional planning. Future iterations will focus on adding behavioral data and integrating the model with advanced deep learning methods to predict the detailed status of returning students, such as full-time equivalent and class level.https://digitalcommons.usf.edu/jger/vol8/iss3/6college retention studystatistical modelingoptimization algorithmstudent retention |
| spellingShingle | Kien Nguyen Optimization of Markov chain modeling in predicting college student retention Journal of Global Education and Research college retention study statistical modeling optimization algorithm student retention |
| title | Optimization of Markov chain modeling in predicting college student retention |
| title_full | Optimization of Markov chain modeling in predicting college student retention |
| title_fullStr | Optimization of Markov chain modeling in predicting college student retention |
| title_full_unstemmed | Optimization of Markov chain modeling in predicting college student retention |
| title_short | Optimization of Markov chain modeling in predicting college student retention |
| title_sort | optimization of markov chain modeling in predicting college student retention |
| topic | college retention study statistical modeling optimization algorithm student retention |
| url | https://digitalcommons.usf.edu/jger/vol8/iss3/6 |
| work_keys_str_mv | AT kiennguyen optimizationofmarkovchainmodelinginpredictingcollegestudentretention |