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Mathematical imagination, knowledge and mindset

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Abstract

The present study had the purpose of investigating empirically the structure and relationships among mathematical imagination, mathematical knowledge and mathematical mindset. The three factors are constituent parts of the Innovation Engine model by Seelig (inGenius: A Crash course on creativity, HarperOne-2012) and can influence creative thinking. The participants were two hundred seventeen sixth grade students from three urban and eight rural primary schools. The data were collected by administering a mathematical imagination test, a test measuring mathematical knowledge and a questionnaire capturing their mathematical mindset. Partial least squares structural equation modeling was applied through Smart PLS in order to examine empirically the proposed path model describing the relationships among the three factors contributing to mathematical creative thinking, namely, imagination, knowledge and mindset. The data analysis yielded that the proposed model of the paper fulfilled all evaluation criteria of partial least squares structural equation modeling. In short, students’ mathematical knowledge could be explained directly and moderately by their mathematical mindset. In addition, mathematical imagination could be explained directly and to a large extent by mathematical knowledge and indirectly by mathematical mindset. Finally, the main implications for mathematics teaching are discussed and potential research directions are suggested.

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References

  • Beck, C. T., & Gable, R. K. (2001). Ensuring content validity: an illustration of the process. Journal of Nursing Measurement, 9(2), 201–215. https://doi.org/10.1891/1061-3749.9.2.201

    Article  Google Scholar 

  • Boaler, J. (2015). Mathematical mindsets: unleashing students’ potential through creative math, inspiring messages and innovative teaching. John Wiley & Sons.

  • Cambridge Assessment International Education (CAIE). (2018). Developing the Cambridge learner attributes. Cambridge, UK: UCLES

  • Danek, A. H., & Wiley, J. (2017). What about false insights? Deconstructing the Aha! Experience along its multiple dimensions for correct and incorrect solutions separately. Frontiers in Psychology, 7, 2077. https://doi.org/10.3389/fpsyg.2016.02077

    Article  Google Scholar 

  • Davis, L. L. (1992). Instrument review: getting the most from your panel of experts. Applied Nursing Research, 5(4), 194–197. https://doi.org/10.1016/S0897-1897(05)80008-4

    Article  Google Scholar 

  • Diamantopoulos, A., & Siguaw, J. A. (2006). Formative versus reflective indicators in organizational measure development: a comparison and empirical illustration. British Journal of Management, 17(4), 263–282. https://doi.org/10.1111/j.1467-8551.2006.00500.x

    Article  Google Scholar 

  • Dweck, C. S. (2006). Mindset: the new psychology of success. Random House Incorporated.

  • Dweck, C. S., & Sorich, L. A. (1999). Mastery-oriented thinking. In C. R. Snyder (Ed.), Coping: the psychology of what works. Oxford University Press.

  • Dweck, C. S., Walton, G. M., & Cohen, G. L. (2014). Academic tenacity: mindsets and skills that promote longterm learning. Bill and Melinda Gates Foundation.

  • Dziedziewicz, D., & Karwowski, M. (2015). Development of children’s creative visual imagination: a theoretical model and enhancement programmes. Education 3–13, 43(4), 382–392. https://doi.org/10.1080/03004279.2015.1020646

    Article  Google Scholar 

  • Eckhoff, A., & Urbach, J. (2008). Understanding imaginative thinking during childhood: sociocultural conceptions of creativity and imaginative thought. Early Childhood Education Journal, 36(2), 179–185. https://doi.org/10.1007/s10643-008-0261-4

    Article  Google Scholar 

  • Edwards, J. R., & Bagozzi, R. P. (2000). On the nature and direction of relationships between constructs and measures. Psychological Methods, 5(2), 155–174. https://doi.org/10.1037/1082-989X.5.2.155

    Article  Google Scholar 

  • Egan, K. (1992). Imagination in teaching and learning: ages 8 to 15. Routledge.

  • Egan, K., & Judson, J. (2016). Imagination and the engaged learner: cognitive tools for the classroom. Teachers College Press.

  • Egan, K., & Madej, K. (Eds.). (2015). Engaging imagination and developing creativity in education. Cambridge Scholars Publishing.

  • Ervynck, G. (1991). Mathematical creativity. In D. Tall (Ed.), Advanced mathematical thinking (pp. 42–53). Kluwer.

  • Falk, R. F., & Miller, N. B. (1992). A primer for soft modeling. University of Akron Press.

  • Freudenthal, H. (1991). Revisiting mathematics education: China lectures. Kluwer Academic Publishers.

  • Gerlinger, T. (2018). Growth mindset and persistence in children's creative performance (Doctoral dissertation, University of Mississippi). http://thesis.honors.olemiss.edu/id/eprint/1233.

  • Gil, E., Ben-Zvi, D., & Apel, N. (2007). What is hidden beyond the data? Helping young students to reason and argue about some wider universe. In D. Pratt & J. Ainley (Eds.), Proceedings of the fifth international research forum on statistical reasoning, thinking and literacy: reasoning about statistical inference: innovative ways of connecting chance and data (pp. 1–26). UK: University of Warwick. http://srtl.stat.auckland.ac.nz/srtl5/presentations.

  • Goldin, G. A. (2017). Mathematical creativity and giftedness: perspectives in response. ZDM - Mathematics Education, 49(1), 147–157. https://doi.org/10.1007/s11858-017-0837-9

    Article  Google Scholar 

  • Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). Sage.

  • Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–151. https://doi.org/10.2753/MTP1069-6679190202

    Article  Google Scholar 

  • Haylock, D. (1997). Recognizing mathematical creativity in schoolchildren. ZDM - Mathematics Education, 29(3), 68–74.

    Article  Google Scholar 

  • Ho, H. C., Wang, C. C., & Cheng, Y. Y. (2013). Analysis of the scientific imagination process. Thinking Skills and Creativity, 10, 68–78. https://doi.org/10.1016/j.tsc.2013.04.003

    Article  Google Scholar 

  • Hong, Y. Y., Chiu, C. Y., Dweck, C. S., Lin, D., & Wan, W. (1999). Implicit theories, attributions, and coping: a meaning system approach. Journal of Personality and Social Psychology, 77, 588–599.

    Article  Google Scholar 

  • Jankowska, D. M., & Karwowski, M. (2015). Measuring creative imagery abilities. Frontiers in Psychology, 6, 1591. https://doi.org/10.3389/fpsyg.2015.01591

    Article  Google Scholar 

  • Johnson-Laird, P. N. (1988). Freedom and constraint in creativity. In: R. J. Sternberg (Ed.), The nature of creativity (pp. 202–219). New York, NY: Cambridge University Press.

  • Jonassen, D. H. (2000). Computers as mindtools for schools: engaging critical thinking. Prentice Hall.

  • Jupri, A., & Drijvers, P. H. M. (2016). Student difficulties in mathematizing word problems in algebra. Eurasia Journal of Mathematics, Science and Technology Education, 12(9), 2481–2502. https://doi.org/10.12973/eurasia.2016.1299a

    Article  Google Scholar 

  • Leikin, R. (2009). Exploring mathematical creativity using multiple solution tasks. In R. Leikin, A. Berman, & B. Koichu (Eds.), Creativity in mathematics and the education of gifted students (pp. 129–145). Sense Publishers.

  • Leikin, R. (2013). Evaluating mathematical creativity: the interplay between multiplicity and insight. Psychological Test and Assessment Modeling, 55(4), 385–400.

    Google Scholar 

  • Leikin, R., & Pitta-Pantazi, D. (2013). Creativity and mathematics education: the state of the art. ZDM - Mathematics Education, 45(2), 159–166. https://doi.org/10.1007/s11858-012-0459-1

    Article  Google Scholar 

  • Levav-Waynberg, A., & Leikin, R. (2012). The role of multiple solution tasks in developing knowledge and creativity in geometry. Journal of Mathematical Behavior, 31(1), 73–90. https://doi.org/10.1016/j.jmathb.2011.11.001

    Article  Google Scholar 

  • Levenson, E. (2013). Tasks that may occasion mathematical creativity: teachers’ choices. Journal of Mathematics Teacher Education, 16(4), 269–291. https://doi.org/10.1007/s10857-012-9229-9

    Article  Google Scholar 

  • Lynn, M. R. (1986). Determination and quantification of content validity. Nursing Research, 35(6), 382–385. https://doi.org/10.1097/00006199-198611000-00017

    Article  Google Scholar 

  • Massarwe, K., Verner, I., & Bshouty, D. (2011). Fostering creativity through geometrical and cultural inquiry into ornaments. In B. Sriraman & K. H. Lee (Eds.), The elements of creativity and giftedness in mathematics (pp. 217–231). Sense Publishers.

  • Murphy, K. R., & Davidshofer, C. O. (2001). Psychological testing principles and applications (5th ed.). Prentice Hall.

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

  • Pehkonen, E. (1997). The state-of-art in mathematical creativity. International Reviews on Mathematical Education, 29, 63–66. http://www.fiz-karlsruhe.de/fix/publications/zdm/adm97.

  • Pitta-Pantazi, D. (2017). What have we learned about giftedness and creativity? An overview of a five years journey. In R. Leikin & B. Sriraman (Eds.), Creativity and giftedness (pp. 201–223). Springer.

  • Polit, D. F., & Beck, C. T. (2006). The content validity index: are you sure you know what’s being reported? Critique and recommendations. Research in Nursing & Health, 29(5), 489–497. https://doi.org/10.1002/nur.20147

    Article  Google Scholar 

  • Presmeg, N. C. (1986). Visualisation in high school mathematics. For the Learning of Mathematics, 6(3), 42–46.

    Google Scholar 

  • Presmeg, N. C. (1997). Generalization using imagery in mathematics. In L. D. English (Ed.), Mathematical reasoning: analogies, metaphors and images (pp. 299–312). Erlbaum.

  • Robins, R. W., & Pals, J. L. (2002). Implicit self-theories in the academic domain: implications for goal orientation, attributions, affect, and self-esteem change. Self and Identity, 1, 313–336.

    Article  Google Scholar 

  • Sarstedt, M., Ringle, C. M., & Hair, J. F. (2017). Partial least squares structural equation modeling. In C. Homburg, M. Klarmann, & A. E. Vomber (Eds.), Handbook of market research (pp. 1–40). Springer International Publishing. https://doi.org/10.1007/978-3-319-05542-8_15-1

  • Seelig, T. (2012). inGenius: A Crash course on creativity. HarperOne.

  • Sheffield, L. J. (2009). Developing mathematical creativity—questions may be the answer. In R. Leikin, A. Berman, & B. Koichu (Eds.), Creativity in mathematics and the education of gifted students (pp. 87–100). Sense Publishers.

  • Sriraman, B., & Leikin, R. (2017). Commentary on interdisciplinary perspectives to creativity and giftedness. In R. Leikin & B. Sriraman (Eds.), Creativity and giftedness (pp. 259–264). Springer.

  • Sternberg, R. J. (2012). The assessment of creativity: an investment-based approach. Creativity Research Journal, 24(1), 3–12. https://doi.org/10.1080/10400419.2012.652925

    Article  Google Scholar 

  • Sutton-Smith, B. (1988). In search of the imagination. In K. Egan & D. Nadaner (Eds.), Imagination and education (pp. 3–29). Teachers College Press.

  • Tabachnick, B. G., & Fidell, L. S. (2014). Using multivariate statistics: Pearson new international edition (6th ed.). Pearson Education Limited.

  • The G C School of Careers examination. (2015). The G C School of Careers: Entrance examination. https://www.gcsc.ac.cy/wp-content/uploads/2018/09/MathsGreekSample5.pdf.

  • Treffers, A. (1987). Three dimensions: a model of goal and theory description in mathematics instruction—the Wiskobas project. Kluwer Academic Publishers.

  • Vale, I., & Barbosa, A. (2015). Mathematics creativity in elementary teacher training. Journal of the European Teacher Education Network, 10, 101–109.

    Google Scholar 

  • Vale, I., & Barbosa, A. (2018). Mathematical problems: the advantages of visual strategies. Journal of the European Teacher Education Network, 13, 23–33.

    Google Scholar 

  • van Alphen, P. (2011). Imagination as a transformative tool in primary school education. RoSE - Research on Steiner Education, 2(2), 1891–6511.

    Google Scholar 

  • Wallas, G. (1926). The art of thought. Jonathan Cape.

  • Waltz, C. F., Strickland, O. L., & Lenz, E. R. (2005). Measurement in nursing and health research (3rd ed.). Springer.

  • Weisberg, R. W. (1995). Prolegomena to theories of insight in problem solving: a taxonomy of problems. In R. J. Sternberg & J. E. Davidson (Eds.), The nature of insight. Cambridge: MIT Press.

    Google Scholar 

  • Wu, J. J., & Albanese, D. L. (2013). Imagination and creativity: wellsprings and streams of education—the Taiwan experience. Educational Psychology, 33(5), 561–581. https://doi.org/10.1080/01443410.2013.813689

    Article  Google Scholar 

  • Yerushalmy, M., Sternberg, B., & Gilead, S. (1999). Visualization as a vehicle for meaningful problem solving in algebra. In Proceedings of the 23th PME conference (pp. 197–211). Haifa, Israel: PME.

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Correspondence to Constantinos Christou.

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Irakleous, P., Christou, C. & Pitta-Pantazi, D. Mathematical imagination, knowledge and mindset. ZDM Mathematics Education 54, 97–111 (2022). https://doi.org/10.1007/s11858-021-01311-9

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