Empowering Students With Disabilities in Education Through AI-Driven Approaches

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Author(s): Usharani Bhimavarapu (Department of Computer Science and Engineering,)
Copyright: 2025
Pages: 24
Source title: Enablers, Barriers, and Challenges for Inclusive Curriculum
Source Author(s)/Editor(s): Erasmos Charamba (University of Limerick, Ireland)and Shalom Nokuthula Ndhlovana (University of the Witwatersrand, South Africa)
DOI: 10.4018/979-8-3373-1000-8.ch006

Keywords: Curriculum Development and Instructional Design / Gender & Diversity / Information Science Reference / Medicine & Healthcare

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Abstract

Student disability empowerment through education needs creative solutions that provide accessibility, personalized learning, and study support. In the current research, a Bi-Stacked Artificial Neural Network (Bi-Stacked ANN) is utilized in modeling student demographics, previous academic experience, and self-rated impairments to offer individualized recommendations for inclusive education. Data was gathered through recruitment campaigns and preprocessed for homogeneity, anonymity, and relevance. Feature selection using Particle Swarm Optimization (PSO) was used to improve model efficiency. Bi-Stacked ANN, which is trained with forward and backpropagation, points out the most critical accessibility issues and proposes adaptive learning techniques. The findings show that AI-based solutions can substantially enhance institutional policy and student support systems to create an inclusive learning environment for people with disabilities.

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Empowering Students With Disabilities in Education Through AI-Driven Approaches

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