A deep sum-score clustering diagnosis method

Yu Zhang; Jing Yang; Yingchuan Jing

doi:10.1117/12.2692011

23 August 2023 A deep sum-score clustering diagnosis method

Yu Zhang, Jing Yang, Yingchuan Jing

Proceedings Volume 12784, Second International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2023); 127841L (2023) https://doi.org/10.1117/12.2692011
Event: 2023 2nd International Conference on Applied Statistics, Computational Mathematics and Software Engineering (ASCMSE 2023), 2023, Kaifeng, China

Abstract

In the context of big data, a new deep sum-score clustering diagnosis method was proposed to mine the educational examination data by optimizing the calculation of the sum-score vectors, which was the input of K-means clustering method. Through theoretical analysis and simulation study, it is found that this method can effectively diagnose and classify the knowledge states of each student, and has improved the accuracy rate, and has good stability and applicability. At the same time, the calculation method of sum-score vectors eliminates the problem of inequality between items to a certain extent, making the method more reasonable and effective, and ensuring the fairness between test items. It helps to promote the application of cognitive diagnostic methods in psychological and educational assessments.

Citation Download Citation

Yu Zhang, Jing Yang, and Yingchuan Jing "A deep sum-score clustering diagnosis method", Proc. SPIE 12784, Second International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2023), 127841L (23 August 2023); https://doi.org/10.1117/12.2692011

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