Predictive Model to Identify College Students with High Dropout Rates
Decreasing student attrition rates is one of the main objectives of most higher education institutions. However, to achieve this goal, universities need to accurately identify and focus their efforts on students most likely to quit their studies before they graduate. This has given rise to a need to...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Universidad Autónoma de Baja California
2023-05-01
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| Series: | Revista Electrónica de Investigación Educativa |
| Subjects: | |
| Online Access: | https://redie.uabc.mx/redie/article/view/5398 |
| _version_ | 1797833311701172224 |
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| author | Jhoan Keider Hoyos Osorio Genaro Daza Santacoloma |
| author_facet | Jhoan Keider Hoyos Osorio Genaro Daza Santacoloma |
| author_sort | Jhoan Keider Hoyos Osorio |
| collection | DOAJ |
| description | Decreasing student attrition rates is one of the main objectives of most higher education institutions. However, to achieve this goal, universities need to accurately identify and focus their efforts on students most likely to quit their studies before they graduate. This has given rise to a need to implement forecasting models to predict which students will eventually drop out. In this paper, we present an early warning system to automatically identify first-semester students at high risk of dropping out. The system is based on a machine learning model trained from historical data on first-semester students. The results show that the system can predict “at-risk” students with a sensitivity of 61.97%, which allows early intervention for those students, thereby reducing the student attrition rate. |
| first_indexed | 2024-04-09T14:21:11Z |
| format | Article |
| id | doaj.art-ebfaf1ae3acc4f58bb6a2a10bb8c1bd5 |
| institution | Directory Open Access Journal |
| issn | 1607-4041 |
| language | English |
| last_indexed | 2024-04-09T14:21:11Z |
| publishDate | 2023-05-01 |
| publisher | Universidad Autónoma de Baja California |
| record_format | Article |
| series | Revista Electrónica de Investigación Educativa |
| spelling | doaj.art-ebfaf1ae3acc4f58bb6a2a10bb8c1bd52023-05-04T19:33:25ZengUniversidad Autónoma de Baja CaliforniaRevista Electrónica de Investigación Educativa1607-40412023-05-012511010.24320/redie.2023.25.e13.5398Predictive Model to Identify College Students with High Dropout Rates Jhoan Keider Hoyos Osorio0https://orcid.org/0000-0002-7169-7963Genaro Daza Santacoloma 1https://orcid.org/0000-0002-1429-5925Universidad Tecnológica de Pereira, Colombia Universidad Tecnológica de Pereira, ColombiaDecreasing student attrition rates is one of the main objectives of most higher education institutions. However, to achieve this goal, universities need to accurately identify and focus their efforts on students most likely to quit their studies before they graduate. This has given rise to a need to implement forecasting models to predict which students will eventually drop out. In this paper, we present an early warning system to automatically identify first-semester students at high risk of dropping out. The system is based on a machine learning model trained from historical data on first-semester students. The results show that the system can predict “at-risk” students with a sensitivity of 61.97%, which allows early intervention for those students, thereby reducing the student attrition rate.https://redie.uabc.mx/redie/article/view/5398dropping outcollege studentsforecastingregression analysis |
| spellingShingle | Jhoan Keider Hoyos Osorio Genaro Daza Santacoloma Predictive Model to Identify College Students with High Dropout Rates Revista Electrónica de Investigación Educativa dropping out college students forecasting regression analysis |
| title | Predictive Model to Identify College Students with High Dropout Rates |
| title_full | Predictive Model to Identify College Students with High Dropout Rates |
| title_fullStr | Predictive Model to Identify College Students with High Dropout Rates |
| title_full_unstemmed | Predictive Model to Identify College Students with High Dropout Rates |
| title_short | Predictive Model to Identify College Students with High Dropout Rates |
| title_sort | predictive model to identify college students with high dropout rates |
| topic | dropping out college students forecasting regression analysis |
| url | https://redie.uabc.mx/redie/article/view/5398 |
| work_keys_str_mv | AT jhoankeiderhoyososorio predictivemodeltoidentifycollegestudentswithhighdropoutrates AT genarodazasantacoloma predictivemodeltoidentifycollegestudentswithhighdropoutrates |