Turkish adaptation and psychometric evaluation of the teaching mathematics for social justice beliefs scale for preservice teachers
Year: 2026
Type: article
Abstract: This study reports the Turkish adaptation and psychometric evaluation of the Teaching Mathematics for Social Justice Beliefs (TMfSJ-beliefs) scale with preservice teachers. A two-phase design was implemented across ten universities, comprising a pilot study (n = 133) and a main study (n = 359) with preservice teachers enrolled in primary and elementary mathematics teacher education programmes. Following international guidelines for test adaptation, we obtained permission from the original authors, applied forward-back translation, conducted expert review to examine semantic and conceptual equivalence, and carried out cognitive interviews before piloting the translated 11-item, six-point Likert-type scale. Using polychoric correlations and the WLSMV estimator, we ran exploratory factor analysis on the pilot data and confirmatory factor analysis on both pilot and main samples. Findings supported a three-factor, 11-item structure corresponding to the original subscales (Value of Mathematics for All Students, Social Justice Should Be Integrated into Mathematics Instruction, and Mathematics and Its Relation to Inclusiveness), with acceptable fit in the main sample (CFI = .93, TLI = .91, RMSEA = .08, SRMR = .07). Cronbach’s alpha and McDonald’s omega indicated adequate internal consistency for two subscales and somewhat lower, though theoretically coherent, reliability for the inclusiveness subscale. Overall, the Turkish TMfSJ-beliefs scale shows promising utility for researching preservice teachers’ beliefs about teaching mathematics for social justice, while further validation with in-service teachers and more diverse samples remains necessary.
Authors: Derya Sahin Ipek, Anikó Fehérvári
Institution: Eötvös Loránd University
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W7204944550
