Neuro-AI and Brain-Inspired Learning Model (NBILM): A Theoretical and Pedagogical Framework for Integrating Artificial Intelligence Into Education

Abstract

This study systematically examines the field of Brain-Inspired Learning, which is developing at the intersection of neuroscience and artificial intelligence within an educational context. A total of 404 articles published in Web of Science between 1992 and 2025 were analysed bibliometrically using the PRISMA framework. The findings demonstrate a marked increase, particularly in publications subsequent to 2008 and a strengthening of interdisciplinary interest. Thematic clusters were identified as the integration of cognitive neuroscience into education, interventions for learning difficulties, debunking neuro-myths and teachers' professional development. In this vein, the study develops the Neuro-Artificial Intelligence and Brain-Inspired Learning Model (NBILM), which combines psychopedagogical variables such as attention, working memory, motivation and cognitive load with neurophysiological data. The model facilitates personalised learning through real-time neurophysiological monitoring and AI-adaptive content design, while promoting evidence-based teaching by enhancing neuroscience literacy.