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VOL. 10, ISSUE 3 (2025)
Artificial intelligence in identifying learning disabilities for early intervention in schools
Authors
Sunita Ganesh Satpute, Supriya Dattatraya Balode
Abstract
AI-based Artificial Intelligence (AI) has emerged as a transformative
tool in identifying learning disabilities at an early stage, enabling timely
interventions in schools. Traditional diagnostic methods often rely on
subjective assessments and delayed recognition, which can hinder academic
progress and emotional well-being. AIdriven models, leveraging machine
learning, natural language processing, and computer vision, analyze behavioral
patterns, cognitive responses, and academic performance to detect early
indicators of conditions such as dyslexia, dyscalculia, and ADHD. These systems
enhance accuracy, reduce human biases, and provide real-time insights, allowing
educators and specialists to implement personalized learning strategies.
AIpowered educational platforms, speech and handwriting analysis tools, and
eyetracking technologies further refine the detection process, ensuring a
comprehensive approach to student assessment. Additionally, data-driven
decisionmaking facilitates continuous monitoring, adapting interventions based
on individual progress. However, ethical concerns regarding data privacy,
algorithmic bias, and the need for human oversight must be addressed for responsible
AI deployment in educational settings. This paper explores the role of AI in
identifying learning disabilities, its implications for early intervention, and
the challenges associated with its adoption, ultimately advocating for an
AI-assisted framework that fosters inclusive and equitable education.
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Pages:60-63
How to cite this article:
Sunita Ganesh Satpute, Supriya Dattatraya Balode "Artificial intelligence in identifying learning disabilities for early intervention in schools". International Journal of Advanced Scientific Research, Vol 10, Issue 3, 2025, Pages 60-63
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