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Using Bayesian Networks for Cognitive Assessment of Student Understanding of Buoyancy: A Granular Hierarchy Model
- Source :
-
Applied Measurement in Education . 2023 36(1):45-59. - Publication Year :
- 2023
-
Abstract
- Cognitive diagnostic assessment based on Bayesian networks (BN) is developed in this paper to evaluate student understanding of the physical concept of buoyancy. we propose a three-order granular-hierarchy BN model which accounts for both fine-grained attributes and high-level proficiencies. Conditional independence in the BN structure is tested and utilized to validate the proposed model. The proficiency relationships are verified and the initial Q-matrix is refined. Then, an optimized granular hierarchy model is constructed based on the updated Q-matrix. All variants of the constructed models are evaluated on the basis of the prediction accuracy and the goodness-of-fit test. The experimental results demonstrate that the optimized granular-hierarchy model has the best prediction and model-fitting performance. In general, the BN method not only can provide more flexible modeling approach, but also can help validate or refine the proficiency model and the Q-matrix and this method has its unique advantage in cognitive diagnosis.
Details
- Language :
- English
- ISSN :
- 0895-7347 and 1532-4818
- Volume :
- 36
- Issue :
- 1
- Database :
- ERIC
- Journal :
- Applied Measurement in Education
- Publication Type :
- Academic Journal
- Accession number :
- EJ1381212
- Document Type :
- Journal Articles<br />Reports - Research
- Full Text :
- https://doi.org/10.1080/08957347.2023.2172014