Measuring mathematics self-efficacy: Multitrait-multimethod comparison - Yu, Wenhua; Zhou, Shuodi; Zhou, Yu (Frontiers in Psychology, 2023)
Previous studies had proved that math self-efficacy is closely related to math performance. The present study used Multitrait-Multimethod (MTMM) design to measure math self-efficacy by constructing the Confirmatory Factor Analysis (CFA) model. “Number and Algebra” “Graphics and Geometry” “Synthesis and Practice” were considered as three traits, and General-Math-Task-referenced self-efficacy, Unconventional-Math-Problem-referenced self-efficacy, and Motivated Strategies for Learning Questionnaire (MSLQ) were discussed as three methods to study. The aim of the research was to observe how to measure math-self-efficacy and find which of the three traits and which of the three methods better reflect individuals’ self-efficacy. Questionnaire survey was used to obtain data. one hundred students completed all the questionnaires. Excel was used to collect math scores, and SPSS 26.0 and AMOS 26.0 were used to manage the data, confirm hypothesis, and build a model by multitrait-multimethod design and Confirmatory factor analysis. Confirmatory factor analysis was used to verify convergent validity and discriminant validity. A total of eight models were constructed in the study which include first-order confirmatory factor analysis models and second-order confirmatory factor analysis models, model D was finally selected as the most perfect model in the second-order confirmatory factor analysis model. The results showed that “Synthesis and Practice” fields was the most significant reflection of self-efficacy among the three traits. and Motivated Strategies for Learning Questionnaire was the most significant reflection of self-efficacy among the three methods. Motivated Strategies for Learning Questionnaire and Unconventional-Math-Problem-referenced self-efficacy among the three methods have better fit with the second-order model constructed by the three traits. Multitrait-Multimethod design provides a new idea and method for measuring math self-efficacy. The research confirmed confirmatory factor analysis can support MTMM data for data modeling and found the correlation between the Unconventional-Math-Problem-referenced self-efficacy and Motivated Strategies for Learning Questionnaire is higher than that of General-Math-Task-referenced self-efficacy in the second-order model.