Educator perceptions of the role of neuroscience in education: evidence from Spain
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Abstract
INTRODUCTION. Practice in the educational field has been characterized by the constant concern of its professionals about the best ways to teach and learn. In recent years, this concern has been reflected in a growing interest among teachers to provide a neuroscientific basis for their educational practices. The purpose of this study was to find out in-service Spanish educators’ views on the role of neuroscience in education. METHOD. A questionnaire was designed based on the previous studies by Pickering and Howard-Jones (2007) and Serpati and Loughan (2012), and data was incidentally collected during eight academic years, using only fully completed surveys. The final sample consisted of 612 education professionals (69.6% females; age: M = 41.33, SD = 9.75, experience: M = 15.17, SD = 10.20). RESULTS. The results reveal that (1) teachers consider that it is very important to know how the brain works for the performance of their teaching tasks, especially in relation to support provision for students with special educational needs or early detection of
learning problems; 2) this view is independent on the respondents’ years of experience, but not on the educational stage in which they carry out their teaching activity, with secondary education teachers the one that tends to grant less importance to this knowledge, and 3) a positive evolution is observed regarding the importance given to understanding the brain for most aspects of educational practice considered. DISCUSSION. These findings support the evidence found in previous research and expand it by analysing the ratings given by teachers based on the educational stage and teaching experience, as well as by studying the evolution of these ratings throughout eight academic years. These results are discussed emphasizing the role of initial and continuous teacher training plans on the effective use of available neuroscientific knowledge in the educational practice.
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Anaya, D. (2014). Bases del aprendizaje y educación (2.ª ed.). Sanz y Torres.
Ansari, D. y Coch, D. (2006). Bridges over troubled waters: Education and cognitive neuroscience. Trends in Cognitive Sciences, 10(4), 146-151. https://doi.org/10.1016/j.tics.2006.02.007
Bartlett, M. S. (1954). A note on the multiplying factors for various chi-square approximations. Journal of the Royal Statistical Society. Series B (Methodological), 16(2), 296-298. http://www.jstor.org/stable/2984057
Ching, F. N. Y., So, W. W. M., Lo, S. K. y Wong, S. W. H. (2020). Preservice teachers’ neuroscience literacy and perceptions of neuroscience in education: Implications for teacher education. Trends in Neuroscience and Education, 21, Article 100144. https://doi.org/10.1016/j.tine.2020.100144
Coch, D. (2018). Reflections on neuroscience in teacher education. Peabody Journal of Education, 93(3), 309-319. https://doi.org/10.1080/0161956X.2018.1449925
Costello, A. B. y Osborne, J. W. (2005). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Practical Assessment, Research & Evaluation, 10, Article 7. https://doi.org/10.7275/jyj1-4868
De Smedt, B. (2018). Applications of cognitive neuroscience in educational research. In Oxford Research Encyclopedia of Education. https://doi.org/10.1093/acrefore/9780190264093.013.69
De Vaus, D. (2004). Surveys in social research (5th ed.). Routledge. https://doi.org/10.4324/9780203501054
Dekker, S., Lee, N. C., Howard-Jones, P. y Jolles, J. (2012). Neuromyths in education: Prevalence and predictors of misconceptions among teachers. Frontiers in Psychology, 3, Article 429. https://doi.org/10.3389/fpsyg.2012.00429
Deligiannidi, K. y Howard-Jones, P. A. (2015). The neuroscience literacy of teachers in Greece. Procedia – Social and Behavioral Sciences, 174, 3909-3915. https://doi.org/10.1016/j.sbspro.2015.01.1133
Dubinsky, J. M., Roehrig, G. y Varma, S. (2013). Infusing neuroscience into teacher professional development. Educational Researcher, 42(6), 317-329. https://www.jstor.org/stable/24571290
Dündar, S. y Gündüz, N. (2016) Misconceptions regarding the brain: The neuromyths of preservice teachers. Mind, Brain, and Education, 10(4), 212-232, https://doi.org/10.1111/mbe.12119
Egido Gálvez, I. y López Martín, E. (2016). Condicionantes de la conexión entre la teoría y la práctica en el Prácticum de Magisterio: Algunas evidencias a partir de TEDS-M. Estudios sobre Educación, 30, 217-237. https://doi.org/10.15581/004.30.217-237
Feiler, J. B. y Stabio, M. E. (2018). Three pillars of educational neuroscience from three decades of literature. Trends in Neuroscience and Education, 13, 17-25. https://doi.org/10.1016/j.tine.2018.11.001
Ferrando, P. J. y Lorenzo-Seva U. (2018). Assessing the quality and appropriateness of factor solutions and factor score estimates in exploratory item factor analysis. Educational and Psychological Measurement, 78(5), 762-780. https://doi.org/10.1177/0013164417719308
Ferrero, M., Garaizar, P. y Vadillo, M. A. (2016). Neuromyths in education: Prevalence among Spanish teachers and an exploration of cross-cultural variation. Frontiers in Human Neuroscience, 10, Article 496. https://doi.org/10.3389/fnhum.2016.00496
Gadermann, A. M., Guhn, M. y Zumbo, B. D. (2012). Estimating ordinal reliability for Likert-ty-pe and ordinal item response data: A conceptual, empirical, and practical guide. Practical Assessment, Research & Evaluation, 17, Article 3. https://doi.org/10.7275/n560-j767
George, D. y Mallery, P. (2016). IBM SPSS Statistics 23 step by step. A simple guide and reference (14th ed.). Routledge.
Gimeno Sacristán, J. (2000). La transición a la educación secundaria (4.ª ed.). Ediciones Morata.
Gleichgerrcht, E., Lira Luttges, B., Salvarezza, F. y Campos, A. L. (2015). Educational neuromyths among teachers in Latin America. Mind, Brain, and Education, 9(3), 170-178. https://doi.org/10.1111/mbe.12086
Grissom, R. J. (1994). Probability of the superior outcome of one treatment over another. Journal of Applied Psychology, 79(2), 314-316. https://doi.org/10.1037/0021-9010.79.2.314
Guerriero, S. (2017). Pedagogical knowledge and the changing nature of the teaching profession. OECD Publishing. https://dx.doi.org/10.1787/9789264270695-en
Hair, J. F., Black, W. C., Babin, B. J. y Anderson, R. E. (2014). Multivariate data analysis (7th ed.). Pearson New International Edition.
Hardiman, M., Rinne, L., Gregory, E. y Yarmolinskaya, J. (2012). Neuroethics, neuroeducation, and classroom teaching: Where the brain sciences meet pedagogy. Neuroethics, 5(2), 135-143. https://doi.org/10.1007/s12152-011-9116-6
Hook, C. J. y Farah, M. J. (2013). Neuroscience for educators: What are they seeking, and what are they finding? Neuroethics, 6(2), 331-341. https://doi.org/10.1007/s12152-012-9159-3
Horn, J. L. (1965). A rationale and test for the number of factors in factor analysis. Psychometrika, 30(2), 179-185. https://doi.org/10.1007/BF02289447
Im, S. H., Cho, J. Y., Dubinsky, J. M. y Varma, S. (2018). Taking an educational psychology course improves neuroscience literacy but does not reduce belief in neuromyths. PloS One, 13(2), Article e0192163. https://doi.org/10.1371/journal.pone.0192163
Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31-36. https://doi.org/10.1007/BF02291575
Karakus, O., Howard-Jones, P. A. y Jay, T. (2015). Primary and secondary school teachers’ knowledge and misconceptions about the brain in Turkey. Procedia - Social and Behavioral Sciences, 174, 1933-1940. https://doi.org/10.1016/j.sbspro.2015.01.858
Kline, P. (2005). Principles and practice of structural equation modeling (2nd ed.). The Guilford Press.
Macdonald, K., Germine, L., Anderson, A., Christodoulou, J. y McGrath, L. M. (2017). Dispelling the myth: Training in education or neuroscience decreases but does not eliminate beliefs in neuromyths. Frontiers in Psychology, 8, Article 1314, https://doi.org/10.3389/fpsyg.2017.01314
Painemil, M., Manquenahuel, S., Biso, P. y Muñoz Valenzuela, C. (2021). Creencias versus conocimiento en futuro profesorado. Un estudio comparado sobre neuromitos a nivel internacional.
Revista Electrónica Educare, 25(1), 1-22. https://doi.org/10.15359/ree.25-1.13
Palghat, K., Horvath, J. C. y Lodge, J. M. (2017). The hard problem of ‘educational neuroscience’. Trends in Neuroscience and Education, 6, 204-210. http://dx.doi.org/10.1016/j.tine.2017.02.001
Pickering, S. J. y Howard-Jones, P. (2007). Educators’ views on the role of neuroscience in education: Findings from a study of U.K. and international perspectives. Mind, Brain, and Education, 1(3), 109-113. https://doi.org/10.1111/j.1751-228X.2007.00011.x
Rato, J. R, Abreu, A. M. y Castro-Caldas, A. (2011). Achieving a successful relationship between neuroscience and education: The views of Portuguese teachers. Procedia - Social and Behavioral Sciences, 29, 879-884. https://doi.org/10.1016/j.sbspro.2011.11.317
Ruscio, J. (2008). A probability-based measure of effect size: Robustness to base rates and other factors. Psychological Methods, 13(1), 19-30. https://doi.org/10.1037/1082-989x.13.1.19
Serpati, L. y Loughan, A. R. (2012). Teacher perceptions of neuroeducation: A mixed methods survey of teachers in the United States. Mind, Brain, and Education, 6(3), 174-176. https://doi.org/10.1111/j.1751-228X.2012.01153.x
Timmerman, M. E. y Lorenzo-Seva, U. (2011). Dimensionality assessment of ordered polytomous items with parallel analysis. Psychological Methods, 16(2), 209-220. https://doi.org/10.1037/a0023353
Torrijos-Muelas, M., González-Víllora, S. y Bodoque-Osma, A. R. (2021). The persistence of neuromyths in the educational settings: A systematic review. Frontiers in Psychology, 11, Article 591923. https://doi.org/10.3389/fpsyg.2020.591923
West, S. G., Taylor, A. B. y Wu, W. (2012). Model fit and model selection in structural equation modeling. En R. H. Hoyle (ed.), Handbook of structural equation modeling (pp. 209-231). Guilford Press.