دورية أكاديمية
Predicting First-Time-in-College Students' Degree Completion Outcomes
| العنوان: | Predicting First-Time-in-College Students' Degree Completion Outcomes |
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| اللغة: | English |
| المؤلفون: | Demeter, Elise (ORCID |
| المصدر: | Higher Education: The International Journal of Higher Education Research. Sep 2022 84(3):589-609. |
| الإتاحة: | Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/ |
| Peer Reviewed: | Y |
| Page Count: | 21 |
| تاريخ النشر: | 2022 |
| نوع الوثيقة: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Undergraduate Students, Prediction, Graduation Rate, Time to Degree, Outcomes of Education, Student Characteristics |
| DOI: | 10.1007/s10734-021-00790-9 |
| تدمد: | 0018-1560 1573-174X |
| مستخلص: | About one-third of college students drop out before finishing their degree. The majority of those remaining will take longer than 4 years to complete their degree at "4-year" institutions. This problem emphasizes the need to identify students who may benefit from support to encourage timely graduation. Here we empirically develop machine learning algorithms, specifically Random Forest, to accurately predict if and when first-time-in-college undergraduates will graduate based on admissions, academic, and financial aid records two to six semesters after matriculation. Credit hours earned, college and high school grade point averages, estimated family (financial) contribution, and enrollment and grades in required gateway courses within a student's major were all important predictors of graduation outcome. We predicted students' graduation outcomes with an overall accuracy of 79%. Applying the machine learning algorithms to currently enrolled students allowed identification of those who could benefit from added support. Identified students included many who may be missed by established university protocols, such as students with high financial need who are making adequate but not strong degree progress. |
| Abstractor: | As Provided |
| Entry Date: | 2022 |
| رقم الأكسشن: | EJ1346177 |
| قاعدة البيانات: | ERIC |
Find this article in full text from Springer Verlag. 
Full Text Finder | تدمد: | 0018-1560 1573-174X |
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| DOI: | 10.1007/s10734-021-00790-9 |