Revise the cognitive model using structural equation modeling.

Shiwei Lin, Xiaolong Zhang, Guoxu Chen, Lingchen Sun, Xinyu Wang, Yongshuang Ma

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Article in Frontiers in psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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6 authors.

Shiwei Lin *College of Chemistry, Changchun Normal University, Changchun, Jilin, China.

Xiaolong Zhang *College of Chemistry, Changchun Normal University, Changchun, Jilin, China.

Guoxu Chen *College of Chemistry, Changchun Normal University, Changchun, Jilin, China.

Lingchen SunDiscipline Construction Office, Changchun Normal University, Changchun, Jilin, China.

Xinyu WangSchool of Psychology, Inner Mongolia Normal University, Hohhot, Inner Mongolia, China.

Yongshuang MaCollege of Science Education, Changchun Normal University, Changchun, Jilin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Qualitative revision of the Cognitive Model (CM) is prone to subjective bias, while classical quantitative methods can only indicate model-data misfit without offering specific revision guidance. Therefore, inadequate CM fit remains a common challenge in Cognitive Diagnosis (CD) research. Purpose: This study aims to determine the CM while avoiding both the loss of examination of disciplinary connotation due to pure data-driven approaches and the potential biases that may arise from pure qualitative research. Method: Using Structural Equation Modeling (SEM) as platform, this study analyzed the valid response data from 752 students by leveraging information such as Result: The revised CM achieved improved fit and aligned with disciplinary connotations. Conclusion: This study employs a mixed-method SEM approach. It avoids two pitfalls. Pure data-driven methods tend to deviate from disciplinary connotations, and pure qualitative analyses are prone to subjective judgment. The resulting benefits are better data-model fit, ensured disciplinary connotations of the CM, and operational efficiency. Meanwhile, it also has drawbacks related to measurement error and sample generalizability.

Indexed as

cognitive diagnosis (CD)cognitive model (CM)middle school chemistryrevisionstructural equation modeling (SEM)

Identifiers

PMID42233062

DOI10.3389/fpsyg.2026.1758968

PMCPMC13223082

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