AI-SUPPORTED BRAIN-BASED LEARNING MODELS: INTEGRATING NEUROPLASTICITY AND ADAPTIVE INTELLIGENCE IN EDUCATION
Keywords:
AI-Supported Brain-Based Learning, Neuroplasticity, Adaptive Intelligence, Artificial Intelligence in Education (AIEd), Neuroeducation, Personalised Learning, Cognitive Neuroscience, Learning Analytics, Multisensory Instruction, Emotion-Centred Learning, Executive Functions, Holistic Development, Foundational Stage Education, Inclusive Education, Educational Technology InnovationAbstract
Artificial intelligence (AI) has emerged as a disruptive force in education, allowing for personalised, data-driven, and adaptable learning experiences. Brain-Based Learning (BBL), which is based on neuroscience, emphasises that learning is optimised when instructional approaches fit with the brain's natural processes, particularly neuroplasticity. This research provides an integrated model of AI-Supported Brain-Based Learning (AI-BBL) that combines neuroplasticity principles with adaptive intelligence to improve overall learner development.
The paradigm is especially relevant for the foundational and early learning periods, when neuroplasticity is at its peak, and personalised scaffolding is essential. AI-BBL settings promote attention management, memory consolidation, executive functioning, and socio-emotional development while decreasing cognitive overload. From a pedagogical standpoint, instructors are repositioned as neuro-facilitators who use AI-generated insights to make informed teaching decisions.
The paper finds that combining AI with brain-based learning principles provides a scientifically sound path for future-ready education. It emphasizes the implications for curriculum design, teacher professional development, and inclusive practices, as well as the need for empirical validation of AI-BBL models across a variety of educational contexts.
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