Intelligent Systems for Early Dyslexia Detection: A Machine Learning Survey

DOI

10.2991/978-94-6239-616-6_16How to use a DOI?

Keywords

Dyslexia; reading disorder; dyslexia screening; Neuro developmental disorder; Game-based assessment Machine learning

Abstract

Reading acquisition is crucial for academic achievement and social participation, yet approximately 10–12% of children worldwide face difficulties due to dyslexia, a neuro developmental disorder that impairs reading, spelling, and writing despite normal intelligence. Early detection plays a vital role, as delayed diagnosis often results in academic struggles, frustration, and reduced self-esteem. Traditional diagnostic approaches, such as reading and writing tests or clinical assessments, are frequently subjective, time-intensive, and challenging to scale. To overcome these limitations, researchers have proposed various computational methods, including game-based assessments and machine-learning technique, to improve the accuracy and efficiency of dyslexia detection. This survey critically reviews recent advances in machine learning techniques for identifying developmental dyslexia, analyzing their methodologies, strengths, and limitations. The purpose of this effort is to provide the groundwork for future studies into creating intelligent systems that allow for prompt interventions and better learning outcomes for kids with dyslexia.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - V. Padmapriya
AU  - S. Janani
AU  - S. Sulekha
AU  - P. Prathisha
PY  - 2026
DA  - 2026/03/31
TI  - Intelligent Systems for Early Dyslexia Detection: A Machine Learning Survey
BT  - Proceedings of the International Conference on Artificial Intelligence and Secure Data Analytics (ICAISDA 2025)
PB  - Atlantis Press
SP  - 191
EP  - 200
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-616-6_16
DO  - 10.2991/978-94-6239-616-6_16
ID  - Padmapriya2026
ER  -