Neurotechnologies in pedagogical training: opportunities and risks for higher education
Keywords:
neurotechnology, neuroeducation, cognitive ethics, brain–computer interfaces, higher educationAbstract
Introduction:
The study analyzes the impact of neurotechnologies on university pedagogical training, highlighting their influence on the personalization of learning and the ethical challenges it poses. The convergence between neuroscience, artificial intelligence and higher education has transformed teaching practices through tools such as brain-computer interfaces, EEG systems and neuroimaging applied to the classroom.
Method:
A mixed approach with systematic review was employed under the PRISMA 2020 guidelines, examining 26 articles indexed in Scopus (2017–2024) on neuroeducation, teacher training, and ethics. The data were analyzed using bibliometric techniques and thematic coding with the ATLAS.ti v9 software, ensuring validity and theoretical triangulation.
Results:
85% of the studies reviewed report improvements in attention and personalization of learning, while 78% highlight the development of critical thinking and cognitive skills. However, 70% warn of risks associated with the violation of mental privacy, technological dependence and the manipulation of neural data. Only 25% of universities include training in neuroethics, evidencing a significant gap in teacher training.
Conclusions:
Neurotechnologies represent an opportunity to modernize teaching and foster pedagogical innovation based on scientific evidence. However, its implementation requires regulatory frameworks, neurodata protection protocols, and ethical training. Its responsible adoption must guarantee neurorights, mental dignity and cognitive autonomy, promoting a more critical, inclusive and humanistic education.
References
Adams, C., Pente, P., Lemermeyer, G., & Rockwell, G. (2023). Ethical principles for artificial intelligence in K-12 education. Computers and Education: Artificial Intelligence, 4, 100131. https://doi.org/10.1016/j.caeai.2023.100131
Alarcón Belmonte, I., Sánchez Collado, R., Yuguero, O., Acezat Oliva, J., Martínez-Millana, A., & Saperas Pérez, C. (2024). La alfabetización digital como elemento clave en la transformación digital de las organizaciones en salud [Digital literacy as a key element in the digital transformation of health organizations]. Atención Primaria, 56(6), 102880. https://doi.org/10.1016/j.aprim.2024.102880
Daugirdiene, A., Cesnaviciene, J., & Brandisauskiene, A. (2024). Insights from the active use of neuroscience findings in teaching and learning. Behavioral Sciences, 14(8), 639. https://doi.org/10.3390/bs14080639
Astobiza, A. M., Díez, T. A., Martín, M. T., Ferrer, R. M., Payá, M. A., & López, D. (2019). Traducir el pensamiento en acción: Interfaces cerebro-máquina y el problema ético de la agencia. Revista de bioética y derecho: publicación del Máster en bioética y derecho, 46, 29-46.
Burwell, S., Sample, M., & Racine, E. (2017). Ethical aspects of brain computer interfaces: A scoping review. BMC Medical Ethics, 18(1), 1-11. https://doi.org/10.1186/s12910-017-0220-y
Bergeron, D., Iorio-Morin, C., & Weil, A. G. (2023). Use of invasive brain–computer interfaces in pediatric neurosurgery: Technical and ethical considerations. Child’s Nervous System, 38(3–4). https://doi.org/10.1177/08830738231167736
Espinoza Freire, E. E., Calva Nagua, D. X., Espinoza Freire, E. E., & Calva Nagua, D. X. (2020). La ética en las investigaciones educativas. Revista Universidad y Sociedad, 12(4), 333-340.
Farisco, M., Evers, K., & Changeux, J.-P. (2024). Is artificial consciousness achievable? Lessons from the human brain. Neural Networks, 180, 106714. https://doi.org/10.1016/j.neunet.2024.106714
Förster, J., & López, I. (2022). Neurodesarrollo humano: un proceso de cambio continuo de un sistema abierto y sensible al contexto [Human neurodevelopment: A continuous change process of an open and context-sensitive system]. Revista Médica Clínica Las Condes, 33(4), 338–346. https://doi.org/10.1016/j.rmclc.2022.06.001
Gordon, E. C., & Seth, A. K. (2024). Ethical considerations for the use of brain–computer interfaces for cognitive enhancement. PLOS Biology, 22(10), e3002899. https://doi.org/10.1371/journal.pbio.3002899
Götte, S. R. (2024). Problemas éticos de las interfaces cerebro-computadora. Perspectivas desde una bioética personalista. Veritas, 59, 7-34. https://doi.org/10.4067/S0718-92732024000300007
Hwang, G.-J., & Chien, S.-Y. (2022). Definition, roles, and potential research issues of the metaverse in education: An artificial intelligence perspective. Computers and Education: Artificial Intelligence, 3, 100082. https://doi.org/10.1016/j.caeai.2022.100082
K, S., & I, D. (2024). Neuroscience literacy and evidence-based practices in pre-service teachers: A pilot study. Trends in Neuroscience and Education, 35. https://doi.org/10.1016/j.tine.2024.100228
Klein, E. (2020). Ethics and the emergence of brain-computer interface medicine. https://doi.org/10.1016/B978-0-444-63934-9.00024-X
Kögel, J., Schmid, J. R., Jox, R. J., & Friedrich, O. (2019). Using brain-computer interfaces: A scoping review of studies employing social research methods. BMC Medical Ethics, 20, 18. https://doi.org/10.1186/s12910-019-0354-1
Maiseli, B., Abdalla, A. T., Massawe, L. V., Mbise, M., Mkocha, K., Nassor, N. A., Ismail, M., Michael, J., & Kimambo, S. (2023). Brain–computer interface: Trend, challenges, and threats. Brain Informatics, 10(1), 1-16. https://doi.org/10.1186/s40708-023-00199-3
Moya, S., & Camacho, M. (2024). Leveraging AI-powered mobile learning: A pedagogically informed framework. Computers and Education: Artificial Intelligence, 7, 100276. https://doi.org/10.1016/j.caeai.2024.100276
Mudgal, S. K., Sharma, S. K., Chaturvedi, J., & Sharma, A. (2020). Avances en la interfaz cerebro-ordenador en neurociencias: aplicaciones y problemáticas. Neurocirugía interdisciplinaria, 20, 100694. https://doi.org/10.1016/j.inat.2020.100694
Nguyen, A. H. D., Le, T. T., Dang, T.-Q., & Nguyen, L.-T. (2024). Understanding metaverse adoption in education: The extended UTAUMT model. Heliyon, 10(19), e38741. https://doi.org/10.1016/j.heliyon.2024.e38741
Papanastasiou, G., Drigas, A., Skiannis, C., & Lytras, M. (2020). Brain computer interface based applications for training and rehabilitation of students with neurodevelopmental disorders: A literature review. Heliyon, 6(9), e04250. https://doi.org/10.1016/j.heliyon.2020.e04250
Pons, S. B., Ramon, M. R. R., Lourido, B. P., & Verger, S. (2021). El Enfoque integrador de la metodología mixta en la investigación educativa. RELIEVE - Revista Electrónica de Investigación y Evaluación Educativa, 27(1). https://doi.org/10.30827/relieve.v27i1.21053
Privitera, A. J., & Du, H. (2022). Educational neurotechnology: Where do we go from here? Trends in Neuroscience and Education, 29, 100195. https://doi.org/10.1016/j.tine.2022.100195
Ragnedda, M. (2018). Conceptualizing digital capital. Telematics and Informatics, 35(8), 2366–2375. https://doi.org/10.1016/j.tele.2018.10.006
Ragnedda, M., Ruiu, M. L., & Addeo, F. (2022). The self-reinforcing effect of digital and social exclusion: The inequality loop. Telematics and Informatics, 72, 101852. https://doi.org/10.1016/j.tele.2022.101852
Ruiz, S., Valera, L., Ramos, P., & Sitaram, R. (2024). Neurorights in the Constitution: From neurotechnology to ethics and politics. Philosophical Transactions B. https://doi.org/10.1098/rstb.2023.0098
Srinivasan, V. (2022). AI & learning: A preferred future. Computers and Education: Artificial Intelligence, 3, 100062. https://doi.org/10.1016/j.caeai.2022.100062
Published
Issue
Section
License
Copyright (c) 2024 Sonia Del Pilar Román Medina, Carolina Rodríguez Morales, Andrea Fernanda Pazmiño Arcos, Sanddy Janeth Coral Padilla (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
The article is distributed under the Creative Commons Attribution 4.0 License. Unless otherwise stated, associated published material is distributed under the same licence.
