AI Solutions for Accessible Education in Underserved Communities

Zhang, Hongli and Leong, Wai Yie (2024) AI Solutions for Accessible Education in Underserved Communities. Journal of Innovation and Technology, 2024 (11). pp. 1-8. ISSN 2805-5179

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Abstract

This paper explores the application of artificial intelligence technology in the field of education, particularly how it can help bridge educational gaps in remote and underserved communities through scalable and accessible learning solutions. The aim of the study is to enhance educational equity and provide personalized learning experiences by utilizing AI technologies such as adaptive learning systems, language processing technologies, and data analytics. The paper analyzes these tools and discusses how they integrate with practical cases like mobile learning platforms, cloud infrastructure, open resources, and collaborative learning to massively distribute educational resources and address global educational inequalities. The research methods include case studies and data analysis, with results indicating that these technologies significantly improve learning efficiency and engagement among students in remote areas. Ultimately, the paper demonstrates the potential of artificial intelligence in promoting global educational equity and offers suggestions for the future development of educational technology. This work is of significant importance to the field of educational technology, providing innovative perspectives and practical solutions for addressing disparities in educational resources.

Item Type:	Article
Uncontrolled Keywords:	Artificial Intelligence, InclusiveEducation, Adaptive Learning, Mobile Learning, Cloud Computing
Subjects:	L Education > L Education (General) Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Depositing User:	Unnamed user with email masilah.mansor@newinti.edu.my
Date Deposited:	02 Sep 2024 07:35
Last Modified:	02 Sep 2024 07:35
URI:	http://eprints.intimal.edu.my/id/eprint/1989

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