Transforming Rural and Underserved Schools with AI-Powered Education Solutions

This study explores the application of artificial intelligence (AI) technology in promoting inclusive learning in underserved schools. By integrating personalised learning platforms, intelligent tutoring systems, and automated management tools, this research evaluates the impact of AI on academic performance, learning engagement, and teacher workload. The experimental results show that AI-driven personalised learning paths and real-time feedback mechanisms significantly improved student learning outcomes, particularly in subjects such as mathematics and science. In addition, teachers' administrative burdens were effectively reduced through automated tools. The study also analyses challenges such as insufficient infrastructure and data privacy protection, proposing targeted technical solutions. This paper provides practical guidance for policymakers and educational institutions to promote the implementation of AI technology in low-resource environments.

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Publication Details

Journal
ASM Science Journal
Published
2024-12-11
DOI
https://doi.org/10.32802/asmscj.2023.1895
Citations
13
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
5.35
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article

Transforming Rural and Underserved Schools with AI-Powered Education Solutions

Wai Yie Leong
13 citations
ASM Science Journal
Online Learning and Analytics
5.35
article

Transforming Rural and Underserved Schools with AI-Powered Education Solutions

Wai Yie Leong
article en
13 citations

Abstract

This study explores the application of artificial intelligence (AI) technology in promoting inclusive learning in underserved schools. By integrating personalised learning platforms, intelligent tutoring systems, and automated management tools, this research evaluates the impact of AI on academic performance, learning engagement, and teacher workload. The experimental results show that AI-driven personalised learning paths and real-time feedback mechanisms significantly improved student learning outcomes, particularly in subjects such as mathematics and science. In addition, teachers' administrative burdens were effectively reduced through automated tools. The study also analyses challenges such as insufficient infrastructure and data privacy protection, proposing targeted technical solutions. This paper provides practical guidance for policymakers and educational institutions to promote the implementation of AI technology in low-resource environments.

ASM Science JournalVol. 19
INTI International University (MY)
Industry, innovation and infrastructure
Openalex Percentile: Top 4%
Online Learning and Analytics
5.35
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Transforming Rural and Underserved Schools with AI-Powered Education Solutions — Wai Yie Leong · ASM Science Journal (2024) | TGRS Research Map | TGRS