Neurocognitive and Computational Perspectives on Multilingual Adaptive Learning: Towards Ethical and Effective AI in Education

The increasing prevalence of multilingual learners in digital environments demands a rethinking of adaptive learning systems. This paper integrates insights from cognitive neuroscience, computational linguistics, and educational technology to propose a framework for ethically grounded, AI-enhanced adaptive learning platforms. Drawing on empirical evidence from neurocognitive studies of bilingual memory, computational approaches to semantic modeling, and instructional design principles, we argue that the next generation of educational AI must be sensitive to the cognitive realities of multilingualism while adhering to principles of transparency and inclusivity. We present a cross-disciplinary synthesis, offer design recommendations, and outline ethical challenges for the deployment of such systems.