UNDERSTANDING NON-COGNITIVE PROFILES OF STUDENTS THROUGH CLUSTER ANALYSIS: A CROSS-COUNTRY STUDY BASED ON PISA 2022 DATA

Authors

  • Melike Ozudogru Manisa Celal Bayar University

Abstract

This study classified students based on non-cognitive variables and PISA 2022 mathematics literacy scores. Using a survey design, data from 221.031 students across 31 countries were analyzed with two-step cluster analysis. Six clusters emerged. Cluster 1 showed the highest mathematics literacy but low perseverance, curiosity, cooperation, and empathy. Cluster 2 demonstrated strong belonging, emotional control, and stress resilience. Cluster 3 had the lowest belonging and the highest bullying levels. Cluster 5 reflected high cooperation, empathy, and assertiveness, while Cluster 6 showed strong perseverance and curiosity but the lowest mathematics literacy. Cross-country comparisons revealed key patterns: effort and persistence were lowest in Chinese Taipei, Hong Kong, and Macao; belonging, cooperation, and empathy were strongest in Switzerland, Germany, and Spain but weakest in Türkiye and Hong Kong. Curiosity was high in Türkiye and Portugal, whereas stress resistance and emotional control were strongest in Finland and Denmark. Further country-level variations were also examined.

Keywords: Cross-national comparison, large-scale assessment, non-cognitive variables, PISA 2022, two-step cluster analysis.

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Published

2026-05-05

How to Cite

Ozudogru, M. (2026). UNDERSTANDING NON-COGNITIVE PROFILES OF STUDENTS THROUGH CLUSTER ANALYSIS: A CROSS-COUNTRY STUDY BASED ON PISA 2022 DATA. International Online Journal of Education and Teaching, 13(2), 188–206. Retrieved from https://iojet.org/index.php/IOJET/article/view/2304

Issue

Vol. 13 No. 2 (2026): CURRENT ISSUE

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Articles

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Authors retain copyright to their work, licensing it under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License and grant the journal exclusive right  of first publication with the work simultaneously and it allows others to copy and redistribute the work for non-commercial purposes, with an acknowledgment of the work's authorship and initial publication in IOJET and provided that no changes were made on the article.