Large Language Models in the Diagnosis of Learning Difficulties: A Brief Review and Future Directions

Large Language Models (LLMs), a leading development in Artificial Intelligence (AI), are influencing education through applications such as chatbot tutors and personalized learning systems. Learning Disabilities (LDs) and neurodevelopmental conditions like ADHD and autism spectrum disorder (ASD) can significantly affect reading, writing, arithmetic, language comprehension, and concentration. Integrating LLMs into this area can assist professionals in diagnosing and supporting individuals with learning challenges. While LLMs have been widely explored for supporting people with Special Educational Needs and Disabilities (SEND), fewer studies address their potential for diagnosing and categorizing learning difficulties. This review examines the intersection of LLMs and learning disabilities, outlines current research on diagnostic applications, discusses practical considerations, and highlights future directions for inclusive implementation.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-11
DOI
https://doi.org/10.5281/zenodo.16794652
Primary Topic
Text Readability and Simplification
Type
article
Field-Weighted Citation Impact
0.00
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article

Large Language Models in the Diagnosis of Learning Difficulties: A Brief Review and Future Directions

Zenodo (CERN European Organization for Nuclear Research)
Text Readability and Simplification
article

Large Language Models in the Diagnosis of Learning Difficulties: A Brief Review and Future Directions

article en

Abstract

Large Language Models (LLMs), a leading development in Artificial Intelligence (AI), are influencing education through applications such as chatbot tutors and personalized learning systems. Learning Disabilities (LDs) and neurodevelopmental conditions like ADHD and autism spectrum disorder (ASD) can significantly affect reading, writing, arithmetic, language comprehension, and concentration. Integrating LLMs into this area can assist professionals in diagnosing and supporting individuals with learning challenges. While LLMs have been widely explored for supporting people with Special Educational Needs and Disabilities (SEND), fewer studies address their potential for diagnosing and categorizing learning difficulties. This review examines the intersection of LLMs and learning disabilities, outlines current research on diagnostic applications, discusses practical considerations, and highlights future directions for inclusive implementation.

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 76%
Text Readability and Simplification
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