Journal ArticleParallel publicationPublished versionDOI: 10.48548/pubdata-3050

A Reliability Generalization Meta-Analysis of the Science Motivation Questionnaire II

Chronological data

Date of first publication2026-02-03
Date of publication in PubData 2026-03-05

Language of the resource

English

Related external resources

Variant form of DOI: 10.1007/s10763-025-10637-9
Karaca, D., Namdar, B., Nalbantoğlu, F. G., Tümer, B., & Aydin, B. (2026). A Reliability Generalization Meta-Analysis of the Science Motivation Questionnaire II. International Journal of Science and Mathematics Education, 24(2), Artikel 16.
Published in ISSN: 1573-1774
International Journal of Science and Mathematics Education

Abstract

Science motivation is among the most important constructs affecting students’ science learning and scientific thinking skills. One commonly utilized scale to measure students’ science motivation is the Science Motivation Questionnaire II (SMQ-II), a 25-item, Likert-type, self-report scale. This study aimed to conduct a reliability generalization meta-analysis of the scale considering the Reliability Generalization Meta Analysis (REGEMA) guideline. Studies included in the analysis implemented the instrument between 2011–2024 and reported a Cronbach alpha value. Reliability evidence from 49 studies reporting a coefficient for the total score or at least for one of the five subscale scores was analyzed using a random effects model and Bonett’s transformation. The pooled Cronbach alpha reliability coefficient was 0.94 for the total score and ranged from 0.83–0.88 for the subscale scores. Moderator analyses showed generally similar reliability estimates across studies, with different study types, languages, sample types, or sample sizes for the subscales. However, the test version, sample type, sample size, and female representation in the sample showed differences in reliability estimates for the total score. The empirical evidence from the SMQ-II’s first 13 years reports high internal consistency across the scale’s scores.

Keywords

Meta-analysis; Reliability Generalization; Science Education; Science Motivation

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DDC

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Research