Individual recommendation method of college physical education resources based on cognitive diagnosis model

Authors

DOI:

https://doi.org/10.4108/eai.10-2-2022.173379

Keywords:

Cognitive diagnosis model, College physical education, Teaching resources, Personalized recommendation, Probability matrix decomposition, Knowledge mastery attribute

Abstract

In order to improve the safety of college physical education resources recommendation and reduce the test overlap rate and resource exposure rate, a personalized recommendation method of college P.E. teaching resources based on cognitive diagnosis model is proposed. A cognitive diagnosis model based on multi-level attribute score is designed to model students' resource mastery level according to existing answers and the relevance of knowledge points. The knowledge mastery attribute model of the tested students is used for probability matrix decomposition to predict the students' answers, and make corresponding resource recommendations according to the score prediction and resource difficulty. Experiments show that resource exposure value of the method in this paper is lower than 1, and its security is high. Regarding the experiment of overlapping indicators, the value of the test overlap rate of the method in this paper is always lower than 0.01, and the recommended resources are more accurate. The F1 value of the method in this paper is up to 0.98, and the deviation of resource recommendation is small. And the real-time performance is high after the method is applied, and the phenomenon of cold start will not occur.

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Published

10-02-2022

How to Cite

1.
Guo H, Cheng X. Individual recommendation method of college physical education resources based on cognitive diagnosis model. EAI Endorsed Scal Inf Syst [Internet]. 2022 Feb. 10 [cited 2022 Oct. 6];9(5):e8. Available from: https://publications.eai.eu/index.php/sis/article/view/343