دورية أكاديمية
Pass/Fail Prediction in Programming Courses
| العنوان: | Pass/Fail Prediction in Programming Courses |
|---|---|
| اللغة: | English |
| المؤلفون: | Van Petegem, Charlotte (ORCID |
| المصدر: | Journal of Educational Computing Research. Mar 2023 61(1):68-95. |
| الإتاحة: | SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com |
| Peer Reviewed: | Y |
| Page Count: | 28 |
| تاريخ النشر: | 2023 |
| نوع الوثيقة: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Pass Fail Grading, At Risk Students, Introductory Courses, Programming, Computer Science Education, College Students, Identification, Algorithms, Prediction, Accuracy, Artificial Intelligence, College Environment, Metadata |
| DOI: | 10.1177/07356331221085595 |
| تدمد: | 0735-6331 1541-4140 |
| مستخلص: | We present a privacy-friendly early-detection framework to identify students at risk of failing in introductory programming courses at university. The framework was validated for two different courses with annual editions taken by higher education students (N = 2 080) and was found to be highly accurate and robust against variation in course structures, teaching and learning styles, programming exercises and classification algorithms. By using interpretable machine learning techniques, the framework also provides insight into what aspects of practising programming skills promote or inhibit learning or have no or minor effect on the learning process. Findings showed that the framework was capable of predicting students' future success already early on in the semester. |
| Abstractor: | As Provided |
| Entry Date: | 2023 |
| رقم الأكسشن: | EJ1365536 |
| قاعدة البيانات: | ERIC |
Full Text Finder | تدمد: | 0735-6331 1541-4140 |
|---|---|
| DOI: | 10.1177/07356331221085595 |