A Smart Learning Assistance Tool for Inclusive Education
Abstract
The government has established special schools to cater to the needs of children with disabilities but they are often segregated rather than receiving equitable opportunities. Artificial Intelligence has opened new ways to promote special education with advanced learning tools. These tools enable to adapt to a typical classroom set up for all the students with or without disabilities. To ensure social equity and the same classroom experience, a coherent solution is envisioned for inclusive education. This paper aims to propose a cost-effective and integrated Smart Learning Assistance (SLA) tool for Inclusive Education using Deep Learning and Computer Vision techniques. It comprises speech to text and sign language conversion for hearing impaired students, sign language to text conversion for speech impaired students, and Braille to text for communicating with visually impaired students. The tool assists differently-abled students to make use of various teaching-learning opportunities conferred to them and ensures convenient two-way communication with the instructor and peers in the classroom thus makes learning easier.
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AI and VR technologies can address physical, social, and cognitive barriers that have historically excluded students with disabilities from fully engaging in learning.
“These new emerging immersive technologies have the capability to address some physical, social, and cognitive barriers that have historically excluded students with disabilities from fully engaging and participating in the learning processes [6,37,41].”
AI-based platforms have been shown to reinforce and promote comprehension and retention by dynamically adjusting the complexity of educational materials, as supported by existing research [6,71].
“AI-based platforms have been shown to reinforce and promote comprehension and retention by dynamically adjusting the complexity of educational materials, as supported by existing research [6,71].”
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- Authors
- Srivastava, S., Varshney, A., Katyal, S., Kaur, R., & Gaur, V.
- Affiliations
- University of Delhi (IN)
- Corresponding author
- Gaur, Vibha
- Venue
- Journal of Intelligent & Fuzzy Systems
- Publisher
- SAGE Publications
- Published
- 2021-06-21
- Volume
- 40
- Issue
- 6
- Pages
- 11981-11994
- ISSN
- 1064-1246 (ISSN-L)
- 1875-8967
- OpenAlex
- W3161911585
- Cited by
- 31
- References
- 7
- Citations by year
- 2026: 3 · 2025: 17 · 2024: 8 · 2023: 2 · 2022: 1
- FWCI
- 4.53
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Intelligent & Fuzzy Systems (publishedVersion)
- Topics
- Health Sciences › Health Professions › Occupational Therapy › Assistive Technology in Communication and Mobility
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Information Systems › Educational Technology in Learning
- Keywords
- inclusive education, special education, assistive technology, sign language recognition, speech-to-text, Braille recognition, visually impaired students, hearing-impaired students, classroom communication, deep learning, computer vision
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