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Validating an Instrument to Evaluate the Teaching of Mathematics Through Processes

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Abstract

The aim of this study is to validate an instrument to evaluate the teaching of mathematics through mathematical processes using a structural equation model. To that end, we have administered the instrument to 95 in-service Spanish teachers and we have also analysed the presence of mathematical processes (problem solving, reasoning and proof, communication, connections and representation) in teaching practice. The descriptive statistics obtained through a quantitative study show that all the items perform similarly in each of the processes, obtaining medium to high scores. A change in this trend is only detected in some of the items of the mathematical process “connections”, which measure if mathematical knowledge is related to other disciplines. The results obtained from the exploratory factor analysis show a high coefficient for all the processes (higher than 0.72), as well as a significant p value, and the results obtained from the confirmatory factor analysis show an internal consistency of the items of each construct, with values greater than 0.8.

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References

  • Aizikovitsh, E., & Cheng, D. (2015). Developing critical thinking skills from dispositions to abilities: Mathematics education from early childhood to high school. Creative Education, 6, 455–462.

    Article  Google Scholar 

  • Alsina, Á. (2012). Más allá de los contenidos, los procesos matemáticos en Educación Infantil [Beyond the contents, the mathematical processes in Early Childhood Education]. Edma 0-6: Educación Matemática en la Infancia, 1(1), 1–14.

  • Alsina, Á., & Coronota, C. (2014). Los procesos matemáticos en las prácticas docentes: Diseño, construcción y validación de un instrumento de evaluación [Mathematical processes in teaching practices: Design, construction and validation of an evaluation instrument]. Edma 0-6: Educación Matemática en la Infancia, 3(2), 21–34.

  • Angoff, W. H. (1971). Scales, norms, and equivalent scores. In R. L. Thorndike (Ed.), Educational measurement (2nd ed., pp. 508–600). Washington, DC: American Council on Education.

  • Beaujean, A. A. (2014). Latent variable modeling using R: A step-by-step guide. New York, NY: Routledge/Taylor & Francis Group.

  • Bransford, J. D., Brown, A. L., & Cocking, R. R. (1999). How people learn: Brain, main, experience, and school. Washington, DC: National Academy Press.

  • Carpenter, T. P. & Levi, L. (1999). Developing conceptions of algebraic reasoning in the primary grades. Retrieved Dec. 16, 2019 from http://ncisla.wceruw.org/publications/reports/RR-002.PDF.

  • Chapman, O., & An, S. (2017). A survey of university-based programs that support in-service and pre-service mathematics teachers’ change. ZDM Mathematics Education, 49, 171–185.

  • Clements, D. H., & Sarama, J. (2011). Early childhood mathematics intervention. Science, 333, 968–970.

    Article  Google Scholar 

  • Clements, D. H., Sarama, J., & DiBase, A.-M. (Eds.). (2004). Engaging young children in mathematics: Standards for early childhood mathematics education. Mahwah, NJ: Lawrence Erlbaum.

  • Cobb, P., Wood, T., Yackel, E., Nicholls, J., Wheatley, G., Trigatti, B., & Perlwitz, M. (1991). Assessment of problem-centerd second-grade mathematics project. Journal for Research in Mathematical Education, 22, 3–29.

    Article  Google Scholar 

  • Costa, A., & Kallick, B. (2000). Habits of mind: A developmental series. Alexandria, VA: Association for Supervision and Curriculum Development.

  • Duval, R. (1995). Semiosis et pensée humaine. Registres sémiotiques et apprentissages intellectuels [Semiosis and human thought. Semiotic registers and intellectual learning]. Bern, Switzerland: Peter Lang.

  • Duval, R. (1998a). Signe et object (I): Trois grandes étapes dans la problématique des rapports entre représentation et objet [Sign and object (I): Three main stages in the problematic of the relationships between representation and object]. Annales de Didactique et de Sciences Cognitives, 6, 139–163.

  • Duval, R. (1998b). Signe et object (II): Questions relatives a l’analyse de la connaissance [Sign and object (II): Questions relating to the analysis of knowledge]. Annales de Didactique et de Sciences Cognitives, 6, 165–196.

  • Ellerton, N., Clements, M. A., & Clarkson, P. (2000). Language factors in mathematics education. In K. Owens & J. Mousley (Eds.), Research in Mathematics Education in Australasia 1996–1999 (pp. 25–99). Sydney, Australia: MEGRA.

    Google Scholar 

  • Fan, L., & Zhu, Y. (2007). From convergence to divergence: The development of mathematical problem solving in research, curriculum, and classroom practice in Singapore. ZDM Mathematics Education, 39, 491–501.

    Article  Google Scholar 

  • Freudenthal, H. (1973). Mathematics as an educational task. Dordrecht, Holland: Kluwer.

    Google Scholar 

  • Ginsburg, H. P. (2009). Early mathematical education and how to do it. In O. Barbarin & B. Wasik (Eds.), Handbook of child development and early education: Research to practice (pp. 403–428). New York, NY: The Guildford Press.

  • González-Montesinos, M.-J., & Backhoff, E. (2010). Validación de un cuestionario de contexto para evaluar sistemas educativos con modelos de ecuaciones estructurales [Validation of a context questionnaire for the evaluation of educational systems with structural equations modelling]. Relieve, 16(2), 1–17.

    Google Scholar 

  • Hooper, D., Coughlan, J., & Mullen, M. (2008). Structural equation modelling: Guidelines for determining model fit. Electronic Journal of Business Research Methods, 6(1), 53–60.

    Google Scholar 

  • Janvier, C. (1987). Problems of representation in the teaching and learning of mathematical problem solving. Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Jones, K., & Pepin, B. (2016). Research on mathematics teachers as partners in task design. Journal of Mathematics Teacher Education, 19(2–3), 105–121.

    Article  Google Scholar 

  • Karsenty, R., & Sherin, M. G. (2017). Video as a catalyst for mathematics teachers’ professional growth. Journal of Mathematics Teacher Educator, 20, 409–413.

    Article  Google Scholar 

  • Kilpatrick, J., Swafford, J., & Findell, B. (2001). Adding it up: Helping children learn mathematics. Washington, DC: National Academy Press.

  • Klibanoff, R., Levine, C., Huttenlocher, J., Hedges, L., & Vasilyeva, M. (2006). Preschool children’s mathematical knowledge: The effect of teacher ‘Math talk’. Developmental Psychology, 42(1), 59–69.

    Article  Google Scholar 

  • Langrall, C. W., Mooney, E. S., Nisbet, S., & Jones, G. A. (2008). Elementary students’ access to powerful mathematical ideas. In L. English (Ed.), Handbook of international research in mathematics education (2nd ed., pp. 109–135). New York, NY: Routledge.

  • Lannin, J. K., Barker, D. D., & Townsend, B. E. (2007). How students view the general nature of their errors. Educational Studies in Mathematics, 66, 43–59.

    Article  Google Scholar 

  • Lannin, J. K., Ellis, A., Elliot, R., & Zbiek, R. M. (2011). Developing essential understanding of mathematical reasoning for teaching mathematics in grades pre-K-8. Reston, VA: NCTM.

  • Llinares, S. (2018). Guest editorial: Knowledge, teaching competences of mathematics teachers and becoming a teacher trainer. Avances de Investigación en Educación Matemática, 13, 1–3.

  • Maurandi, A., del Río, L., & Balsalobre, C. (2013). Fundamentos estadísticos para investigación. Introducción a R [Statistical foundations for research. Introduction to R]. Madrid, Spain: Bubok Publishing, S.L.

  • Mercer, N. (2001). Palabras y mentes [Words and minds]. Barcelona, Spain: Paidós.

  • NAEYC & NCTM (2002). Early childhood mathematics: Promoting good beginnings. Retrieved Dec. 16, 2019 from https://www.naeyc.org/files/naeyc/file/positions/psmath.pdf.

  • National Council of Teachers of Mathematics. (2000). Principles and standards for school mathematics. Reston, VA: NCTM.

  • National Council of Teachers of Mathematics. (2014). Principles to actions: Ensuring mathematical success for all. Reston, VA: NCTM.

  • National Council for Curriculum and Assessment. (2014a). Mathematics in early childhood and primary education (3–8 years). Definitions, theories, development and progression. Retrieved Dec. 16, 2019 from https://www.ncca.ie/media/1494/maths_in_ecp_education_theories_progression_researchreport_17.pdf.

  • National Council for Curriculum and Assessment. (2014b). Mathematics in early childhood and primary education (3–8 years). Teaching and Learning. Retrieved Dec. 16, 2019 from https://www.ncca.ie/media/2147/ncca_research_report_18.pdf.

  • National Research Council. (2009). Mathematics learning in early childhood: Paths towards excellence and equity. In C. Cross, T. Woods, & H. Schweingruber (Eds.), Committee on early childhood mathematics, center for education, division of behavioural and social sciences. Washington, DC: The National Academies Press.

  • Nolan, D. R. (2012). How teachers can understand and combat the effects of poverty on literacy development. Retrieved Dec. 16, 2019 from file:///C:/Users/u2001371/Downloads/N65_2012NolanDeirdre.pdf.

  • Novo, Mª.L., Alsina, Á., Marbán, J.Mª., & Berciano, A. (2017). Connective intelligence for Childhood mathematics education. Comunicar, 52, 29–39.

  • Pólya, G. (1945). How to solve it: A new aspect of mathematical method. Princeton, NJ: Princeton University Press.

    Book  Google Scholar 

  • R Core Team. (2017). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Retrieved Dec. 16, 2019 from https://www.R-project.org/.

  • Rosseel, Y. (2012). Lavaan: An R package for structural equation modelling. Journal of Statistical Software, 48(2), 1–36. Retrieved Dec. 16, 2019 from http://www.jstatsoft.org/v48/i02/.

  • Russell, S. J. (1999). Mathematical reasoning in the elementary grades. In L. V. Stiff (Ed.), Developing mathematical reasoning in grades K-12 (pp. 1–12). Reston, VA: NCTM.

  • Sallán, J. M., Fernande, V., Simo, P., Lordan, O., & Gonzalez Prieto, D. (2012). Structural equation modelling analysis using the lavaan package. In J. Prado-Prado & J. García-Arca (Eds.), 6th International Conference on Industrial Engineering and Industrial Management (pp. 951–958). London, England: Springer 2014.

  • Schoenfeld, A. H. (Ed.). (1994). Mathematical thinking and problem solving. Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Schumacker, R. E., & Lomax, R. G. (2004). A beginner’s guide to structural equation modelling. New York, NY: Routledge.

  • Skott, J., Zoest, L. V., & Gellert, U. (2013). Theoretical frameworks in research on and with mathematics teachers. ZDM Mathematics Education, 45, 501–505.

    Article  Google Scholar 

  • Trafton, P. R., & Hartman, C. L. (1997). Developing number sense and computational strategies in problem-centered classrooms. Teaching Children Mathematics, 4, 230–233.

    Article  Google Scholar 

  • Varela Mallou, J., & Lévy Mangin, J. P. (2006). Modelización con estructuras de covarianzas en ciencias sociales: Temas esenciales, avanzados y aportaciones especiales [Modelling with covariance structures in Social Sciences: Essential, advanced topics and special contributions]. A Coruña, Spain: Netbiblo.

  • Whitin, D. J., & Whitin, P. (2003). Talk counts. Discussing graphs with young children. Teaching Children Mathematics, 10, 142–149.

    Article  Google Scholar 

  • Wolf, C., Joye, D., Smith, T. W., & Fu, Y.-C. (2016). The SAGE handbook of survey methodology. London, England: Sage Publications Ltd.

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Correspondence to Angel Alsina.

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Table 7 Questionnaire items grouped by blocks

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Alsina, A., Maurandi, A., Ferre, E. et al. Validating an Instrument to Evaluate the Teaching of Mathematics Through Processes. Int J of Sci and Math Educ 19, 559–577 (2021). https://doi.org/10.1007/s10763-020-10064-y

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