UNA PROPOSTA TEORICA PER SVILUPPARE LE COMPETENZE DEGLI EDUCATORI ALLA LUCE DELLE NEUROSCIENZE EDUCATIVE

Contenuto principale dell'articolo

Spyridon Doukakis
Maria Niari
Chrystalla Mouza

Abstract

L’allineamento delle conoscenze degli educatori ai principi delle neuroscienze educative è un passo cruciale verso il potenziale miglioramento della pratica educativa. Analogamente ad altri domini di conoscenza, riteniamo che questa trasformazione possa avvenire attraverso cinque fasi di sviluppo (Riconoscere, Accettare, Adattare, Esplorare ed Avanzare), insieme ad altrettanti assi distinti, ma complementari: l'implementazione del curriculum, la valutazione degli studenti, l'apprendimento, l'insegnamento e l'accesso a tecnologie non invasive, portatili e indossabili per le misurazioni neurofisiologiche. Per quanto riguarda i suddetti assi, la ricerca nel campo delle neuroscienze educative ha offerto importanti risultati. In questa cornice, l'articolo propone che l’acquisizione delle conoscenze sulle neuroscienze educative, da parte degli educatori in servizio e in formazione, possa quindi basarsi sulle fasi di sviluppo e sugli assi identificati. Lo scopo è quello di incoraggiare gli educatori a sviluppare le conoscenze e le competenze necessarie ad integrare i principi e le scoperte delle neuroscienze educative nella progettazione, nell'insegnamento e nella valutazione.

Dettagli dell'articolo

Sezione
Articoli - Numero speciale

Riferimenti bibliografici

Akyuz, D. (2018). Measuring technological pedagogical content knowledge (TPACK) through performance assessment. Computers & Education, 125, 212-225. doi: 10.17471/2499-4324/1268

Association of Mathematics Teacher Educators. (2006, January). Preparing teachers to use technology to enhance the learning of mathematics. Retrieved from https://amte.net/news/2006/01/position-preparing-teachers-use-technology-enhance-learning-mathematics

Chang, Z., Schwartz, M. S., Hinesley, V., & Dubinsky, J. M. (2021, August 11). Neuroscience concepts changed teachers’ views of pedagogy and students. Frontiers in Psychology, 3264. doi: 10.3389/fpsyg.2021.685856

Chi, M. T. H. (2008). Three types of conceptual change: Belief revision, mental model transformation, and categorical shift. In S. Vosniadou (Ed.), Handbook of research on conceptual change (pp. 61-82). Hillsdale, NJ, US: Erlbaum.

Cranton, P. (2016). Understanding and promoting transformative learning: A guide to theory and practice. Sterling, VA, US: Stylus Publishing, LLC.

Dekker, S., Lee, N. C., Howard-Jones, P., & Jolles, J. (2012, October 18). Neuromyths in education: Prevalence and predictors of misconceptions among teachers. Frontiers in Psychology, 429. doi: 10.3389/fpsyg.2012.00429

Doukakis, S. (2012). Exploring undergraduate students' transformation of technological pedagogical knowledge in Mathematics as prospective teachers and as teachers in their school action. [PhD Thesis] University of the Aegean.

Doukakis, S., Sfyris, P., Niari, M., & Alexopoulos, E. (2021). Exploring educational practices in emergency remote teaching. The role of educational neuroscience. In 2021 IEEE Global Engineering Education Conference - EDUCON (Vienna, Austria, 21st-23rd April 2021) (pp. 1026-1034). IEEE. doi: 10.1109/EDUCON46332.2021.9454143

Duff, M. C., Covington, N. V., Hilverman, C., & Cohen, N. J. (2020, January 24). Semantic memory and the hippocampus: Revisiting, reaffirming, and extending the reach of their critical relationship. Frontiers in Human Neuroscience, 13, 471. doi: 10.3389/fnhum.2019.00471

Harris, I., Jennings, R., Pullinger, D., Rogerson, S., & Duquenoy, P. (2008). Helping ICT professionals to assess ethical issues in new and emerging technologies. In MINAmI workshop on ambient intelligence and ethics (Vol. 15). British Computer Society. Retrieved from https://www.academia.edu/322949/Helping_ICT_Professionals_to_Assess_Ethical_Issues_In_New_and_Emerging_Technologies

Horvath, J. C., & Donoghue, G. M. (2016, March 16). A bridge too far–revisited: reframing Bruer’s neuroeducation argument for modern science of learning practitioners. Frontiers in Psychology, 7, 377. doi: 10.3389/fpsyg.2016.00377

Howard‐Jones, P., Jay, T., & Galeano, L. (2020). Professional development on the science of learning and teachers' performative thinking—a pilot study. Mind, Brain, and Education, 14(3), 267-278. doi: 10.1111/mbe.12254

Hwang, G. J., & Chang, H. F. (2011). A formative assessment-based mobile learning approach to improving the learning attitudes and achievements of students. Computers & Education, 56(4), 1023-1031. doi: 10.1016/j.compedu.2010.12.002

Jacobs, H. H. (1997). Mapping the Big Picture. Integrating Curriculum & Assessment K-12. Alexandria, VA, US: Association for Supervision and Curriculum Development.

Jamaludin, A., Henik, A., & Hale, J. B. (2019). Educational neuroscience: Bridging theory and practice. Learning: Research and Practice, 5(2), 93-98. doi: 10.1080/23735082.2019.1685027

Janssen, T. W., Grammer, J. K., Bleichner, M. G., Bulgarelli, C., Davidesco, I., Dikker, S., ... & van Atteveldt, N. (2021). Opportunities and limitations of mobile neuroimaging technologies in educational neuroscience. Mind, Brain, and Education, 15(4), 354-370. doi: 10.1111/mbe.12302

Jarodzka, H., Skuballa, I., & Gruber, H. (2021). Eye-tracking in educational practice: Investigating visual perception underlying teaching and learning in the classroom. Educational Psychology Review, 33(1), 1-10. doi: 10.1007/s10648-020-09565-7

Kaplon-Schilis, A., & Lyublinskaya, I. (2020). Analysis of relationship between five domains of TPACK framework: TK, PK, CK math, CK science, and TPACK of pre-service special education teachers. Technology, Knowledge and Learning, 25(1), 25-43. doi: 10.1007/s10758-019-09404-x

Khasawneh, M. (2022). The relationship of curriculum, teaching methods, assessment methods, and school and home environment with learning difficulties in English language from the students’ perspectives. Journal of Innovation in Educational and Cultural Research, 3(1), 41-48. doi: 10.46843/jiecr.v3i1.51

Lin, L., Parsons, T.D., & Cockerham, D. (2019). Rethinking learning in the rapid developments of neuroscience, learning technologies, and learning sciences. In T. Parsons, L. Lin, & D. Cockerham (Eds.), Mind, Brain and Technology. Educational Communications and Technology: Issues and Innovations (pp. 3-16). Cham, CH: Springer. doi: 10.1007/978-3-030-02631-8_1

Lu, K., Xue, H., Nozawa, T., & Hao, N. (2019). Cooperation makes a group be more creative. Cerebral Cortex, 29(8), 3457-3470. doi: 10.1093/cercor/bhy215

Mason, R., Mason, F., & Culnan, M. (1995). Ethics of information management. Thousend Oaks, CA, US: Sage.

McCandliss, B., & Toomarian, E. (2020, April 13). Putting neuroscience in the classroom: How the brain changes as we learn. Trend. Retrieved from https://www.pewtrusts.org/en/trend/archive/spring-2020/putting-neuroscience-in-the-classroom-how-the-brain-changes-as-we-learn

McPhail, G. (2021). The search for deep learning: A curriculum coherence model. Journal of Curriculum Studies, 53(4), 420-434. doi: 10.1080/00220272.2020.1748231

Moser, J. S., Schroder, H. S., Heeter, C., Moran, T. P., & Lee, Y. H. (2011). Mind your errors: Evidence for a neural mechanism linking growth mind-set to adaptive posterior adjustments. Psychological Science, 22(12), 1484-1489. doi: 10.1177/0956797611419520

Newton, P. M., & Miah, M. (2017, March 27). Evidence-based higher education – Is the learning styles ‘myth’ important?. Frontiers in Psychology, 8, 444. doi: 10.3389/fpsyg.2017.00444

Niess, M. L., Ronau, R. N., Shafer, K. G., Driskell, S. O., Harper, S. R., Johnston, C., ... & Kersaint, G. (2009). Mathematics teacher TPACK standards and development model. Contemporary Issues in Technology and Teacher Education, 9(1), 4-24.

Organisation for Economic Co-operation and Development. (2002). Understanding the brain: Towards a new learning science. OECD Publishing.

Organisation for Economic Co-operation and Development. (2007). Understanding the brain: The birth of a learning science. OECD Publishing.

Plerou, A., Vlamos, P., & Triantafillidis, C. (2017). the effectiveness of neurofeedback training in algorithmic thinking skills enhancement. In P. Vlamos (Ed.), GeNeDis 2016. Advances in Experimental Medicine and Biology, 988. Cham, CH: Springer. doi: 10.1007/978-3-319-56246-9_14

Posner, G. J., Strike, K. A., Hewson, P. W., & Gertzog, W. A. (1982). Accommodation of a scientific conception: Toward a theory of conceptual change. Science Education, 66(2), 211–227.

Privitera, A. J. (2021). A scoping review of research on neuroscience training for teachers. Trends in Neuroscience and Education, 24, 100157. doi: 10.1016/j.tine.2021.100157

Saltz, J., & Heckman, R. (2020). Using structured pair activities in a distributed online breakout room. Online Learning, 24(1), 227-244. doi: 10.24059/olj.v24i1.1632

Sidiropoulou, K. (2015). Basic principles for the functioning of nervous system. Athens, GR: Kallipos, Open Academic Editions.

Smale-Jacobse, A. E., Meijer, A., Helms-Lorenz, M., & Maulana, R. (2019, November 22). Differentiated instruction in secondary education: A systematic review of research evidence. Frontiers in Psychology, 10. doi: 10.3389/fpsyg.2019.02366

Sparck, E. M., Bjork, E. L., & Bjork, R. A. (2016). On the learning benefits of confidence-weighted testing. Cognitive research: Principles and implications, 1(1), 1-10. doi: 10.1186/s41235-016-0003-x

Srisawasdi, N., Pondee, P., & Bunterm, T. (2018). Preparing pre-service teachers to integrate mobile technology into science laboratory learning: an evaluation of technology-integrated pedagogy module. International Journal of Mobile Learning and Organisation, 12(1), 1-17. doi: 10.1504/IJMLO.2018.089239

Steffe, L. P., & Gale, J. E. (Eds.). (1995). Constructivism in education. Psychology Press.

Tan, Y. S. M., & Amiel, J. J. (2022). Teachers learning to apply neuroscience to classroom instruction: case of professional development in British Columbia. Professional Development in Education, 48(1), 70-87. doi: 10.1080/19415257.2019.1689522

Taylor, E. W. (2001). Transformative learning theory: A neurobiological perspective of the role of emotions and unconscious ways of knowing. International Journal of lifelong education, 20(3), 218-236. doi: 10.1080/02601370110036064

van Gennep, A. (1960). The rites of passage (2nd Ed.). Chicago, IL, US: The University of Chicago Press.

Vaughn, A. R., Brown, R. D., & Johnson, M. L. (2020). Understanding conceptual change and science learning through educational neuroscience. Mind, Brain, and Education, 14(2), 82-93. doi: 10.1111/mbe.12237

Versteeg, M., & Steendijk, P. (2019). Putting post-decision wagering to the test: a measure of self-perceived knowledge in basic sciences? Perspectives on Medical Education, 8(1), 9-16. doi: 10.1007/s40037-019-0495-4

Versteeg, M., Wijnen-Meijer, M., & Steendijk, P. (2019). Informing the uninformed: a multitier approach to uncover students’ misconceptions on cardiovascular physiology. Advances in Physiology Education, 43(1), 7-14. doi: 10.1152/advan.00130.2018

Watagodakumbura, C. (2017). Principles of Curriculum Design and Construction Based on the Concepts of Educational Neuroscience. Journal of Education and Learning, 6(3), 54-69. doi: 10.5539/jel.v6n3p54

Wiliam, D. (2006). Formative assessment: Getting the focus right. Educational Assessment, 11(3-4), 283-289. doi: 10.1080/10627197.2006.9652993

Williamson, B. J. (2020). New digital laboratories of experimental knowledge production: Artificial intelligence and education research. London Review of Education. doi: 10.14324/LRE.18.2.05

Yfanti, A., & Doukakis, S. (2021). Debunking the neuromyth of learning style. In P. Vlamos, (Ed.), GeNeDis 2020. Advances in Experimental Medicine and Biology (pp. 145-153). Cham, CH: Springer. doi: 10.1007/978-3-030-78775-2_17