Factor analysis and psychometric evaluation of the mathematical modeling attitude scale for teachers of mathematics
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Factor analysis and psychometric evaluation of the mathematical modeling attitude scale for teachers of mathematics Reuben S. Asempapa1 · Gordon P. Brooks2 Accepted: 27 October 2020 © Springer Nature B.V. 2020
Abstract The effective teaching and learning of mathematics through mathematical modeling and connecting mathematics to the real world has gained rapid growth at various educational levels all over the world. The growth in modeling practices in the United States of America (US) and the international community is the result of the development and implementation of new mathematics standards and curricula across the world. In this article, we report on the development and use of a quantitative instrument aimed at assessing teachers of mathematics attitudes toward mathematical modeling practices. Based on the responses of 310 practicing teachers of mathematics from the US, the mathematical modeling attitude scale was evaluated using item analysis, exploratory factor analysis, confirmatory factor analysis, and other psychometric properties. The scale isolated four dimensions: constructivism, understanding, relevance and real-life, and motivation and interest. These 4 factors accounted for 59% of the variation in the 28-item measure. Cronbach’s alpha coefficient for the overall scale was .96, and that for the subscales was .93 for constructivism, .81 for understanding, .88 for relevance and real-life, and .89 for motivation and interest. The findings suggest a psychometrically useable, reliable, and valid scale for studying teacher’s attitudes toward mathematical modeling. We discuss the instrument’s merit for research and teaching, and implications for teacher education, professional development, and future research. Keywords Mathematical modeling · MMAS · Attitudes · Teachers’ attitudes · Factor analysis
* Reuben S. Asempapa [email protected] Gordon P. Brooks [email protected] 1
Penn State Harrisburg, W311D Olmsted Building, Middletown, PA 17057, USA
2
Ohio University, 302Q McCracken Hall, Athens, OH 45701, USA
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R. S. Asempapa, G. P. Brooks
Introduction In the past few decades, mathematical modeling education has experienced rapid growth all over the world and especially in the United States of America (US), and this growth is expected to continue. With the development and enactment of the Common Core State Standards for Mathematics (CCSS–M) (National Governors Association Center for Best Practices [NGA Center] and Council of Chief State School Officers [CCSSO] 2010), the Guidelines for Assessment in Mathematical Modeling Education [GAIMME] report (Consortium for Mathematics and Its Application [COMAP] and Society for Industrial and Applied Mathematics [SIAM] Consortium for Mathematics and Its Applications [COMAP] and Society for Industrial and Applied Mathematics [SIAM] 2016), and modeling standards across the world including Australia, Germany, Japan, The Netherlands, and Singapore (Ang 2015; Geiger 2015; Ikeda 2015; Kaiser et al. 2011), come new standards for mathematical pra
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