Developing a Structural Model of Academic Self-Concept Based on Identity Dimensions in Students

This study aimed to develop a structural model of academic self-concept based on personal, social, national, and religious identity dimensions among secondary school students. This descriptive-correlational study employed path analysis. The statistical population consisted of all secondary school students in Sabzevar during the 2023–2024 academic year, from whom 327 students were selected through convenience sampling. Data were collected using the Yessen-Chen Academic Self-Concept Scale (2004) and the Cheek Identity Dimensions Questionnaire (2002). Data were analyzed using SPSS.26 and PLS software, and the reliability and validity of the instruments were confirmed by Cronbach’s alpha and factor analysis. Correlation analysis showed significant positive relationships between all identity dimensions and academic self-concept (P<0.001; r=0.43–0.71). Path analysis indicated that identity dimensions directly and positively predicted academic self-concept (P<0.001; β=0.885). Standard path coefficients revealed significant positive effects of personal identity (β=0.671), social identity (β=0.636), national identity (β=0.525), and religious identity (β=0.463) on academic self-concept. The proposed model demonstrated good fit indices. The findings suggest that identity dimensions play a crucial role in enhancing students’ academic self-concept. Strengthening different aspects of identity can improve academic self-concept and ultimately foster academic success, making it a valuable approach for school educational and counseling programs.

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Publication Details

Journal
Journal of Cognition Behavior Learning
Published
2025-01-01
DOI
https://doi.org/10.61838/jcbl.266
Primary Topic
Psychology of Development and Education
Type
article
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article

Developing a Structural Model of Academic Self-Concept Based on Identity Dimensions in Students

Abdollah Mafakheri, Hossein Mahdian, Mehri Bostani
Journal of Cognition Behavior Learning
Psychology of Development and Education
article

Developing a Structural Model of Academic Self-Concept Based on Identity Dimensions in Students

Abdollah Mafakheri, Hossein Mahdian, Mehri Bostani
article en

Abstract

This study aimed to develop a structural model of academic self-concept based on personal, social, national, and religious identity dimensions among secondary school students. This descriptive-correlational study employed path analysis. The statistical population consisted of all secondary school students in Sabzevar during the 2023–2024 academic year, from whom 327 students were selected through convenience sampling. Data were collected using the Yessen-Chen Academic Self-Concept Scale (2004) and the Cheek Identity Dimensions Questionnaire (2002). Data were analyzed using SPSS.26 and PLS software, and the reliability and validity of the instruments were confirmed by Cronbach’s alpha and factor analysis. Correlation analysis showed significant positive relationships between all identity dimensions and academic self-concept (P<0.001; r=0.43–0.71). Path analysis indicated that identity dimensions directly and positively predicted academic self-concept (P<0.001; β=0.885). Standard path coefficients revealed significant positive effects of personal identity (β=0.671), social identity (β=0.636), national identity (β=0.525), and religious identity (β=0.463) on academic self-concept. The proposed model demonstrated good fit indices. The findings suggest that identity dimensions play a crucial role in enhancing students’ academic self-concept. Strengthening different aspects of identity can improve academic self-concept and ultimately foster academic success, making it a valuable approach for school educational and counseling programs.

Journal of Cognition Behavior LearningVol. 2(3)
Openalex Percentile: Top 70%
Psychology of Development and Education
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Developing a Structural Model of Academic Self-Concept Based on Identity Dimensions in Students — Abdollah Mafakheri, Hossein Mahdian, et al. · Journal of Cognition Behavior Learning (2025) | TGRS Research Map | TGRS