Construction of a collaborative learning grouping model: Integration of knowledge complementarity and dynamic diagnosis.
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| Title: | Construction of a collaborative learning grouping model: Integration of knowledge complementarity and dynamic diagnosis. |
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| Authors: | Li, Haojun1 424389370@qq.com, Chen, Yaohan1 1635058484@qq.com, Liao, Weixia2 359579851@qq.com, Wang, Xuhui3 zgdlhj@zjut.edu.cn |
| Source: | Educational Technology & Society. Jul2026, Vol. 29 Issue 3, p19-33. 15p. |
| Subject Terms: | *Collaborative learning, *Dynamic assessment (Education), *Machine learning, K-means clustering |
| Abstract: | In the process of collaborative learning, effective grouping is the key to improving learning efficiency. A well-structured collaborative learning group can markedly improve the learning efficiency of both individuals and the group as a whole. Nonetheless, current grouping methods for collaborative learning frequently fall short of a comprehensive assessment of students' knowledge proficiency, thereby failing to guarantee that group members' knowledge structures are mutually complementary. Therefore, a grouping model combining knowledge complementarity and dynamic diagnosis is proposed. The grouping model is divided into five layers. Firstly, the learning objective analysis layer deconstructs the teaching content into several core knowledge points. On this basis, the dynamic knowledge diagnosis layer uses the improved deep knowledge tracking model DKVMN-KT to dynamically diagnose students' mastery of core knowledge points. Then, in the personalized grouping layer, K-means algorithm is used to cluster the personalized grouping results. Furthermore, teachers were involved in the manual fine-tuning of the grouping results. Finally, the model forms a closed-loop feedback link through a deep interactive optimization layer to promote the iterative optimization of the collaborative learning grouping model. The experimental results indicate that the collaborative learning grouping model is helpful to effectively group students at the level of knowledge structure, and can improve the efficiency of collaborative learning, In order to guarantee more equitable and diverse grouping outcomes, this methodology promotes positive interplay among students, enabling them to mutually learn from one another and thereby enhance their comprehension of diverse knowledge points effectively. [ABSTRACT FROM AUTHOR] |
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| Database: | Education Research Complete |
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