دورية أكاديمية
Grade Expectations: How Well Can Past Performance Predict Future Grades?
| العنوان: | Grade Expectations: How Well Can Past Performance Predict Future Grades? |
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| اللغة: | English |
| المؤلفون: | Wyness, Gill (ORCID |
| المصدر: | Education Economics. 2023 31(4):397-418. |
| الإتاحة: | Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals |
| Peer Reviewed: | Y |
| Page Count: | 22 |
| تاريخ النشر: | 2023 |
| نوع الوثيقة: | Journal Articles Reports - Research |
| Education Level: | Secondary Education |
| Descriptors: | Foreign Countries, Prediction, Grades (Scholastic), Expectation, Teacher Attitudes, Bias, Accuracy, Academic Achievement, Artificial Intelligence, Models, High Achievement, Low Income Students, Secondary School Students, Exit Examinations |
| مصطلحات جغرافية: | United Kingdom |
| DOI: | 10.1080/09645292.2022.2113861 |
| تدمد: | 0964-5292 1469-5782 |
| مستخلص: | Students in the UK apply to university with teacher-predicted examination grades, rather than actual results. These predictions have been shown to be inaccurate, and to favour certain groups, leading to concerns about teacher bias. We ask whether it is possible to improve on the accuracy of teachers' predictions by predicting pupil achievement using prior attainment data and machine learning techniques. While our models do lead to a quantitative improvement on teacher predictions, substantial inaccuracies remain. Our models also underpredict high-achieving state school pupils and low socio-economic status pupils, suggesting they have more volatile education trajectories. This raises questions about the use of predictions in the UK system. |
| Abstractor: | As Provided |
| Entry Date: | 2023 |
| رقم الأكسشن: | EJ1394220 |
| قاعدة البيانات: | ERIC |
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Full Text Finder | تدمد: | 0964-5292 1469-5782 |
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| DOI: | 10.1080/09645292.2022.2113861 |