Dear Colleagues,

As the scope and depth of educational data continue to grow, the demand for novel methodologies and cross-disciplinary strategies to implement, assess, and refine AI-personalized learning has become increasingly urgent. Neuroscience and educational technology together offer transformative potential, providing new insights into cognitive development and the optimization of individualized learning trajectories. At the same time, the proliferation of AI-driven personalized learning tools introduces remarkable opportunities for learner-centered education, alongside pressing concerns regarding fairness, the redefinition of educator roles, and the preservation of instructional quality.

This special issue centers on the convergence of neuroscience, educational technology, and cognitive growth, with the goal of showcasing pioneering studies, technological advances, and conceptual models that strengthen the creation, deployment, and responsible oversight of AI-enhanced personalized education. Relevant themes include:

• Neural mechanisms underlying personalized learning and cognitive feedback loops

• Neurocognitive frameworks for designing adaptive instructional systems

• Equity, diversity, and neurodiversity in AI-supported educational interventions

• Teacher adaptation and pedagogical decision-making in neurotechnology-enhanced settings

• Neuroethical considerations and algorithmic bias in learning analytics

• Student data rights, cognitive privacy, and autonomy in AI-mediated environments

• Cross-cultural and cross-context comparisons of neuroeducational AI effectiveness

• Training and policy development for integrating neuroscience with AI-driven pedagogy

We welcome original research articles, case studies, and reviews that contribute to advancing the dialogue and practice in this dynamic and evolving field.