The use of brain-computer interfaces in education: potential and risks

Introduction: Higher education faces a convergence between neuroscience and artificial intelligence. In this framework, brain-computer interfaces (BCIs) promise personalization, real-time feedback, and inclusion, but they raise dilemmas about mental privacy and neurodata governance. Method: Quantitative, non-experimental and cross-sectional study with 80 participants (40 teachers, 40 students) from the areas of education, health and engineering. An Osgood semantic differential questionnaire (20 bipolar pairs; scale 1–7) was applied in four dimensions: educational potential, usability/adoption, pedagogical integration, and perceived risks. Descriptive statistics, Student's t and Pearson's correlation were used. Results: The means in potential, usability and integration were between 5.5 and 6.4, revealing high pedagogical evaluation. Risk perception was moderate (teachers 3.2; students 3.8). The student group showed slightly higher overall scores. A negative correlation was observed between educational potential and perceived risk, indicating that greater technological trust is associated with less ethical threat. Conclusions: BCIs are viable for adaptive learning and inclusion, but their adoption requires neurodigital governance, mental privacy safeguarding, consent protocols, and teacher training in neuroethics and neurodigital literacy. Clear institutional policies that articulate innovation and cognitive rights are recommended for responsible implementation in higher education.