AI Enable Personalized Assistive Tools to Enhance Education of Disabled Persons and Its Legal Fallacies

The integration of AI-enabled personalized assistive tools in education represents a transformative approach to enhancing learning experiences for disabled persons and children with diverse needs. This abstract explores the potential of these technologies to provide tailored educational support, facilitating engagement and fostering independence. By leveraging machine learning algorithms, natural language processing, and adaptive learning environments, these tools can customize content delivery based on individual learning styles, preferences, and abilities. AI-driven platforms can assist in identifying specific challenges faced by students, offering real-time feedback and adaptive resources that evolve with their progress. Examples include speech recognition software for students with hearing impairments, interactive visual aids for those with cognitive disabilities, and personalized learning pathways that accommodate varying levels of ability. Furthermore, the implementation of these tools promotes inclusivity in educational settings, allowing all learners to participate meaningfully. This abstract highlight the need for collaboration between educators, technologists, and policymakers to ensure the effective design and deployment of AI assistive technologies. By prioritizing accessibility and user-centric design, these innovations can significantly enhance educational outcomes, empower disabled individuals, and cultivate a more equitable learning environment.

Authors

Publication Details

Journal
International Journal For Multidisciplinary Research
Published
2024-11-27
DOI
https://doi.org/10.36948/ijfmr.2024.v06i06.31573
Citations
2
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
Field-Weighted Citation Impact
0.98
Controls
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article

AI Enable Personalized Assistive Tools to Enhance Education of Disabled Persons and Its Legal Fallacies

M - Bhakiyasri.
2 citations
International Journal For Multidisciplinary Research
Impact of AI and Big Data on Business and Society
0.98
article

AI Enable Personalized Assistive Tools to Enhance Education of Disabled Persons and Its Legal Fallacies

M - Bhakiyasri.
article en
2 citations

Abstract

The integration of AI-enabled personalized assistive tools in education represents a transformative approach to enhancing learning experiences for disabled persons and children with diverse needs. This abstract explores the potential of these technologies to provide tailored educational support, facilitating engagement and fostering independence. By leveraging machine learning algorithms, natural language processing, and adaptive learning environments, these tools can customize content delivery based on individual learning styles, preferences, and abilities. AI-driven platforms can assist in identifying specific challenges faced by students, offering real-time feedback and adaptive resources that evolve with their progress. Examples include speech recognition software for students with hearing impairments, interactive visual aids for those with cognitive disabilities, and personalized learning pathways that accommodate varying levels of ability. Furthermore, the implementation of these tools promotes inclusivity in educational settings, allowing all learners to participate meaningfully. This abstract highlight the need for collaboration between educators, technologists, and policymakers to ensure the effective design and deployment of AI assistive technologies. By prioritizing accessibility and user-centric design, these innovations can significantly enhance educational outcomes, empower disabled individuals, and cultivate a more equitable learning environment.

International Journal For Multidisciplinary ResearchVol. 6(6)
Quality Education
Openalex Percentile: Top 20%
Impact of AI and Big Data on Business and Society
0.98
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AI Enable Personalized Assistive Tools to Enhance Education of Disabled Persons and Its Legal Fallacies — M - Bhakiyasri. · International Journal For Multidisciplinary Research (2024) | TGRS Research Map | TGRS