Self-Regulation Scale in Mathematics: short form development and validity-reliability study

Year 2025, Volume: 6 Issue: 1, 67 - 75, 30.06.2025

Barış Demir , Esra Çanakçı Fatma Nur Düzgün Merve Çam Rümeysa Beyazhançer

https://doi.org/10.5281/zenodo.15780927

Abstract

Self-regulation in mathematics is the organization of the student in line with the mathematics course outcomes. Students' ability to organize the mathematics learning process in a healthy way can increase their mathematics achievement. Knowing students' self-regulation towards mathematics will contribute to providing the necessary education for mathematics achievement. The purpose of this study is to develop a valid and reliable short-form scale to measure middle school students' self-regulation skills towards mathematics. In this context, existing self- regulation scales were examined and an item pool of 56 items was created by utilizing the items in the literature and the statements developed by the researchers. In line with expert opinions, a preliminary form of 25 items consisting of positive statements was prepared and this form was applied to 342 middle school students. As a result of exploratory factor analysis, the number of items was reduced to 14 and the scale had a four-factor structure: Effort, Integrated, Review and Getting Support. Confirmatory factor analysis confirmed this structure. The overall Cronbach's alpha reliability coefficient of the scale was calculated as .78, and the coefficients related to the sub- dimensions were found to be acceptable. The developed Short Mathematics Self-Regulation Scale (S-MSRS) is recommended as a tool that can be applied in a short time, has understandable expressions and can be used at different grade levels.

Keywords

Mathematics education , Reliability , Scale development , Self-regulation , Validity

References

• Ainley, M., & Patrick, L. (2006). Measuring self-regulated learning processes through tracking patterns of student interaction with achievement activities. Educational Psychology Review, 18(3), 267-286.
• Aktan, O. (2012). The relationship between self-regulatory learning strategies and academic achievement of fifth grade elementary school students. Education and Science, 37(164), 179-190.
• Aktan, S. (2012). The relationship between students' academic achievement, self-regulation skills, motivation and teachers' teaching styles. Bayburt Education Faculty Journal, 14(28), 324-346. https://doi.org/10.35675/befdergi.487409.
• Arslan, S., and Gelişli, Y. (2015). Development of perceived self-regulation scale: Validity and Reliability Study. Sakarya University Journal of Education, 5(3), 67- 74
• Bandura, A. (1986). The explanatory and predictive scope of self-efficacy theory. Journal of Social and Clinical Psychology, 4(3), 359-373
• Çiltaş, A. (2011). A study on the importance of self-regulation teaching in education. Mehmet Akif Ersoy University Journal of Institute of Social Sciences, 3(5), 1-11.
• Cleary, T. J., & Chen, P. P. (2009). Self-regulation, motivation, and math achievement in middle school: Variations across grade level and math context. Journal of School Psychology, 47(5), 291-314. https://doi.org/10.1016/j.jsp.2009.04.002
• Çokçalışkan, H., Sakız, G., & Doğan, M.C. (2019). Development of self-regulated learning inventory for primary school fourth grade students: validity and reliability study.
• Erdogan, F., & Sengul, S. (2014). A review of self-regulatory learning strategies for elementary school students in mathematics. The Journal of Education and Training Researches, 3(3), 108-118.
• Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
• Gaskin, J.,Validity and Realiability, http://statwiki.gaskination.com/index.php? title=CFA#Validity_and_Reliability.
• Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage Publication
• Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance- based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135.
• İpek, H. (2019). Investigation of middle school students' mathematics anxiety, mathematics self-efficacy beliefs and self-regulation skills towards mathematics course. Doctoral dissertation, Marmara University, Istanbul, Turkiye.
• Kadıoğlu, C., Uzuntiryaki, E., & Çapa Aydın, Y. (2011). Development of Self-regulated Learning Strategies Scale (SLLS). Eğitim ve Biliṁ, 36(160).
• Koç, N., & Hadaya, P. (2018). Minimum sample size estimation in PLS-SEM: Inverse square root and gamma- exponential methods. Journal of information systems, 28 (1), 227-261.
• Lee, G., Lim, K., & Grabowski, B. (2010). Improving self-regulation, learning strategy use, and achievement with metacognitive feedback. Educational Technology Research and Development, 58(6), 629-648. https://doi.org/10.1007/s11423-010-9153-6.
• Özdamar, K. (2004). Statistical Data Analysis with Package Programs I. Eskisehir: Kaan Bookstore.
• Pintrich, P. R., Smith, D. A. F., Garcia, T., & McKeachie, W. J. (1991). A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ). University of Michigan.
• Tavşancil, E., & Keser, H. (2002). Development of Likert Type Attitude Scale Towards Internet Use. Journal of Educational Sciences and Applications, 1 (1).
• Üredi, İ., & Üredi, L. (2005). The power of self-regulation strategies and motivational beliefs of 8th grade elementary school students to predict mathematics achievement. Mersin University Faculty of Education Journal, 1(2).
• Usta, N. (2014). Factors that enable students to be successful in mathematics according to students participating in Bartın province inter-secondary mathematics competition. Journal of Faculty of Education, 3(2), 153-173.