DIGITAL NEUROPEDAGOGY: HARNESSING COGNITIVE SCIENCE AND TECHNOLOGY FOR EDUCATIONAL EFFICIENCY
Abstract
This paper discusses the approaches of digital neuropedagogy aimed at optimizing educational processes through the use of technology based on cognitive sciences. The focus is on the theoretical foundations and practical applications of neuropedagogy in modern educational settings. The goal of the study is to explore the possibilities of personalized learning using digital technologies. Key findings demonstrate enhanced efficiency in cognitive processes such as attention, memory, and thinking. Methods include an analysis of educational technologies applied in the context of neuropedagogy.
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Выготский Л.С. (1978). Мышление и речь. Москва: Педагогика.
Гальперин П.Я. (1966). Умственные действия и этапы их формирования. Москва: Наука.
Давыдов В.В. (1996). Концепция развивающего обучения. Москва: Просвещение.
Зинченко В.П. (1995). Развивающая деятельность как психологический процесс. Москва: Издательство Московского государственного университета.
Леонтьев А.Н. (1975). Деятельность. Сознание. Личность. Москва: Политиздат.
Лурия А.Р. (1973). Основы нейропсихологии. Москва: МГУ.
Эльконин Д.Б. (1971). К проблеме стадий умственного развития ребенка. В Д.И. Фельдштейн (Ред.), Проблемы возраста (с. 122-134). Москва: Просвещение.
Aldrich, C. (2009). Learning by doing: A comprehensive guide to simulations, computer games, and pedagogy in e-learning and other educational experiences. John Wiley & Sons.
Anderson, J. R. (2014). Cognitive psychology and its implications. Worth Publishers.
Azevedo, R., & Hadwin, A. F. (2005). Scaffolding self-regulated learning and metacognition: Implications for the design of computer-based environments. Instructional Science, 33(5-6), 367-379.
Blankertz, B., Tangermann, M., Vidaurre, C., Fazli, S., Sannelli, C., Haufe, S., ... & Müller, K. R. (2010). The Berlin brain-computer interface: non-medical uses of BCI technology. Frontiers in Neuroscience, 4, 198.
Bruer, J. T. (1997). Education and the brain: A bridge too far. Educational Researcher, 26(8), 4-16.
Cepeda, N. J., Pashler, H., Vul, E., Wixted, J. T., & Rohrer, D. (2006). Distributed practice in verbal recall tasks: A review and quantitative synthesis. Psychological Bulletin, 132(3), 354-380.
Dede, C. (2010). Comparing frameworks for 21st century skills. In J. Bellanca & R. Brandt (Eds.), 21st century skills: Rethinking how students learn (pp. 51-76). Solution Tree Press.
Draganski, B., Gaser, C., Busch, V., Schuierer, G., Bogdahn, U., & May, A. (2004). Neuroplasticity: Changes in grey matter induced by training. Nature, 427(6972), 311-312.
Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students' learning with effective learning techniques: Promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14(1), 4-58.
Gardner, H. (2017). A synthesizing mind: A memoir from the creator of multiple intelligences theory. MIT Press.
Harley, T. A. (2014). The psychology of language: From data to theory. Psychology Press.
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education. In Data ethics: building trust: how digital technologies can serve humanity (pp. 621-653). Globethics Publications.
Illes, J. (2017). Neuroethics: Anticipating the future. Oxford University Press.
Immordino-Yang, M. H. (2016). Emotions, learning, and the brain: Exploring the educational implications of affective neuroscience. WW Norton & Company.
Immordino-Yang, M. H., & Damasio, A. (2007). We feel, therefore we learn: The relevance of affective and social neuroscience to education. Mind, Brain, and Education, 1(1), 3-10.
Kapp, K. M. (2012). The gamification of learning and instruction: Game-based methods and strategies for training and education. John Wiley & Sons.
Luckin, R. (2018). Machine learning and human intelligence: The future of education for the 21st century. Routledge.
Merchant, Z., Goetz, E. T., Cifuentes, L., Keeney-Kennicutt, W., & Davis, T. J. (2014). Effectiveness of virtual reality-based instruction on students' learning outcomes in K-12 and higher education: A meta-analysis. Computers & Education, 70, 29-40.
Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63(2), 81-97.
Nation, I. S. P. (2013). Learning vocabulary in another language. Cambridge University Press.
Neuroethics Society. (2023). Neuroethics guidelines for educational neurotechnologies. Retrieved from [website address]
O'Dowd, R. (2018). Online intercultural exchange: Policy, pedagogy, practice. Routledge.
Picard, R. W. (2000). Affective computing. MIT Press.
Rayner, K. (2009). Eye movements in reading and information processing: 20 years of research. Psychological Bulletin, 135(3), 375-422.
Sailer, M., Hense, J. U., Mayr, S. K., & Mandl, H. (2017). How gamification motivates: An experimental study of the effects of specific game design elements on learning outcomes. Computers in Human Behavior, 69, 371-380.
Shams, L., & Seitz, A. R. (2008). Benefits of multisensory learning. Trends in Cognitive Sciences, 12(11), 411-417.
Siemens, G. (2013). Learning analytics: The emergence of a discipline. American Behavioral Scientist, 57(10), 1380-1400.
Siemens, G., & Baker, R. S. J. d. (2012). Learning analytics and educational data mining: Towards communication and collaboration. In Proceedings of the 2nd international conference on learning analytics and knowledge (pp. 252-254).
Tokuhama-Espinosa, T. (2014). Mind, brain, and education science: A comprehensive guide to the new brain-based teaching. WW Norton & Company.
VanLehn, K. (2011). The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educational Psychologist, 46(4), 197-221.
Warschauer, M. (2003). Technology and social inclusion: Rethinking the digital divide. MIT Press.
Woolf, B. P. (2010). Building intelligent interactive tutors: Student-centered strategies for revolutionizing e-learning. Morgan Kaufmann.
Wu, H. K., & Lee, S. W. Y. (2022). Exploring the educational potential of the metaverse. Educational Technology & Society, 25(1), 15-28.
DOI: https://doi.org/10.22190/JTESAP240922052M
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