Academic Journal
How Can Valid and Reliable Automatic Formative Assessment Predict the Acquisition of Learning Outcomes?
| العنوان: | How Can Valid and Reliable Automatic Formative Assessment Predict the Acquisition of Learning Outcomes? |
|---|---|
| اللغة: | English |
| المؤلفون: | Blaženka Divjak (ORCID |
| المصدر: | Journal of Computer Assisted Learning. 2024 40(6):2616-2632. |
| الاتاحة: | Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us |
| Peer Reviewed: | Y |
| Page Count: | 17 |
| تاريخ النشر: | 2024 |
| نوع الوثيقة: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Automation, Formative Evaluation, Test Validity, Test Reliability, Predictor Variables, Outcomes of Education, College Mathematics, Longitudinal Studies |
| DOI: | 10.1111/jcal.12953 |
| تدمد: | 0266-4909 1365-2729 |
| مستخلص: | Background: Sound learning design should be based on the constructive alignment of intended learning outcomes (LOs), teaching and learning activities and formative and summative assessment. Assessment validity strongly relies on its alignment with LOs. Valid and reliable formative assessment can be analysed as a predictor of students' academic performance, but the question is how significant its predictive power is, and what other elements can affect predictions. Objectives: Our aim was to investigate the predictive power of formative assessment for summative assessment, measuring the acquisition of LOs. Methods: We analysed formative assessment results (quizzes, homework), together with log data (video and other material use, class attendance), to determine the most influential predictors and establish a reliable predictive learning analytics model. We used the Random Forest algorithm. The model is based on the data from two university mathematical courses, delivered at different years and levels of study, incorporating 813 students in two consecutive years. Results and Conclusions: Our results show that formative assessment, together with previous summative assessment, is a stronger predictor of summative assessment results than other data on students' engagement. The study pointed to the importance of completeness and quality of data, and clear links between assessment and LOs when making predictions of student results. It suggested that predictions are less reliable for the lowest and the highest performing students. It was noted that other factors can also affect predictions, like the level of LOs, or factors not easily extracted from digital data, like the learning environment and individual students' strategies. |
| Abstractor: | As Provided |
| Entry Date: | 2024 |
| رقم الانضمام: | EJ1448499 |
| قاعدة البيانات: | ERIC |
| تدمد: | 0266-4909 1365-2729 |
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| DOI: | 10.1111/jcal.12953 |