AI for Neurodiverse Minds

AI for Neurodiverse Minds: Redesigning EdTech for Inclusive Education explores how artificial intelligence can be harnessed to create truly inclusive learning environments for neurodiverse learners. Written from the perspective of an IT management professional with nearly three decades of experience and a deep engagement with music, culture, and education, this work bridges the gap between technological innovation and human diversity. The paper examines the shortcomings of current educational technologies and proposes a three-pillar framework for inclusive AI design: Cognitive Profiling, Adaptive Content Modulation, and Affective-Social Responsiveness. Together, these elements form the foundation of a next-generation learning management system capable of recognising unique learner profiles, dynamically adapting instructional content, and responding to emotional and social needs in real time. By scripting together insights from neuroscience, educational theory, universal design for learning (UDL), and emerging fields such as affective computing, the book advocates for an education system that values difference and leverages technology to support, not marginalise, diverse ways of thinking. Accessible to educators, policymakers, EdTech developers, and researchers, this work serves both as a conceptual framework and a call to action. It challenges the status quo of “one-size-fits-all” learning and envisions a future where AI empowers neurodiverse learners to thrive academically, socially, and emotionally.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-01
DOI
https://doi.org/10.5281/zenodo.17228737
Primary Topic
SARS-CoV-2 and COVID-19 Research
Type
article
Field-Weighted Citation Impact
0.00
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article

AI for Neurodiverse Minds

Zenodo (CERN European Organization for Nuclear Research)
SARS-CoV-2 and COVID-19 Research
article

AI for Neurodiverse Minds

article en

Abstract

AI for Neurodiverse Minds: Redesigning EdTech for Inclusive Education explores how artificial intelligence can be harnessed to create truly inclusive learning environments for neurodiverse learners. Written from the perspective of an IT management professional with nearly three decades of experience and a deep engagement with music, culture, and education, this work bridges the gap between technological innovation and human diversity. The paper examines the shortcomings of current educational technologies and proposes a three-pillar framework for inclusive AI design: Cognitive Profiling, Adaptive Content Modulation, and Affective-Social Responsiveness. Together, these elements form the foundation of a next-generation learning management system capable of recognising unique learner profiles, dynamically adapting instructional content, and responding to emotional and social needs in real time. By scripting together insights from neuroscience, educational theory, universal design for learning (UDL), and emerging fields such as affective computing, the book advocates for an education system that values difference and leverages technology to support, not marginalise, diverse ways of thinking. Accessible to educators, policymakers, EdTech developers, and researchers, this work serves both as a conceptual framework and a call to action. It challenges the status quo of “one-size-fits-all” learning and envisions a future where AI empowers neurodiverse learners to thrive academically, socially, and emotionally.

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 41%
SARS-CoV-2 and COVID-19 Research
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