Development of the Techno-mathematical Literacy Scale (TmLS): A validity and reliability study
Abstract
The aim of this study is to develop a valid and reliable measurement instrument to assess Techno-Mathematical Literacy (TmL). TmL is conceptualized as an individual’s self-efficacy perception regarding their ability to integrate mathematical knowledge and reasoning processes within the contemporary technological ecosystem through the use of technological tools, mathematical communication in digital environments, and data-driven reasoning. The study was conducted within the framework of a psychometric scale development model based on Classical Test Theory. The study group consisted of 348 pre-service mathematics teachers enrolled at three different public universities in Türkiye; following the data-cleaning process, the analyses were carried out with 342 participants. As a result of the Exploratory Factor Analysis (EFA), a four-factor structure consisting of 12 items was obtained, explaining 73.141% of the total variance. The Confirmatory Factor Analysis (CFA) results indicated that the model demonstrated a good fit to the data (χ²/df = 1.868; CFI = .952; GFI = .924; RMSEA = .071; SRMR = .059). The internal consistency coefficients, composite reliability, and average variance extracted values were found to be within acceptable limits. The results of the Fornell–Larcker criterion and the Heterotrait–Monotrait (HTMT) ratio supported the discriminant validity of the model. The findings indicate that the Techno-Mathematical Literacy Scale (TmLS) is a psychometrically robust measurement instrument. The scale can be used not only in the context of teacher education but also with different samples to determine individuals’ techno-mathematical competencies in technology-supported mathematics learning environments.
Keywords
References
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Details
Primary Language
English
Subjects
Mathematics Education, Science and Mathematics Education (Other)
Journal Section
Research Article
Early Pub Date
March 7, 2026
Publication Date
March 7, 2026
Submission Date
October 15, 2024
Acceptance Date
March 7, 2026
Published in Issue
Year 2026 Number: Advanced Online Publication