Preprint / Version 1

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

Authors

DOI:

https://doi.org/10.64748/eph8sq43

Keywords:

multilingualism, adaptive learning, cognitive neuroscience, computational linguistics, educational technology, ethics

Abstract

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.

Author Biographies

  • Helena Varga, Leiden University

    Dr. Helena Varga is an Associate Professor specializing in memory, learning, and brain plasticity. Her research focuses on how neural networks adapt during skill acquisition, particularly in multilingual individuals. She integrates experimental psychology with neuroimaging techniques, aiming to bridge cognitive theory and applied educational practice. Dr. Varga has published extensively on working memory models and leads several EU-funded projects on bilingual education and neuroplasticity. She serves on the editorial boards of Cognitive Science and Frontiers in Psychology.

  • Marcello Conti, Sapienza University of Rome

    Prof. Marcello Conti is a Full Professor of Computational Linguistics and Natural Language Processing. His research spans machine learning applications to semantic modeling, discourse analysis, and human–AI interaction. With a background in both linguistics and computer science, he has been at the forefront of developing multilingual corpora for low-resource languages. Prof. Conti is the coordinator of several Horizon Europe initiatives on AI-driven language technologies. He is also a frequent reviewer for ACL, COLING, and Computational Linguistics.

  • Aisha Rahman, University of Edinburgh

    Dr. Aisha Rahman is a Senior Lecturer focusing on educational technology, digital pedagogy, and AI-enhanced learning environments. Her research investigates how digital tools reshape knowledge acquisition and collaboration in higher education. She works at the intersection of instructional design, data-driven assessment, and ethics in educational AI. Dr. Rahman regularly consults for UNESCO on digital literacy initiatives and is an associate editor for the British Journal of Educational Technology. She has received multiple grants for cross-institutional projects on adaptive learning platforms.

    • Downloads

    Posted

    2025-08-30

    How to Cite

    Neurocognitive and Computational Perspectives on Multilingual Adaptive Learning: Towards Ethical and Effective AI in Education. (2025). In Substack Scholarly Posts. https://doi.org/10.64748/eph8sq43

    License

    Copyright (c) 2025 Helena Varga, Marcello Conti, Aisha Rahman (Author)

    Creative Commons License

    This work is licensed under a Creative Commons Attribution 4.0 International License.