AI-Supported Differentiated Instruction for Chinese Vocational English Reading: Enhancing Proficiency and Motivation

This study designed an AI-supported differentiated instruction, where adaptive algorithms assisted teachers in tailoring reading materials and assessments for vocational students among Chinese learners. The primary objective is to examine the literature gap regarding the application of such strategies in vocational settings. Utilizing a pre-experimental design, the research methodically investigates the impact of these tailored instruction strategies on students’ reading proficiency and motivation. The findings render important insights into the efficacy of differentiated instruction, demonstrating significant improvements in English reading outcomes among vocational education students. These discoveries highlight the potential of AI to enhance differentiated instruction, addressing the specific needs of vocational learners. The results indicated significant improvements in students’ reading skills and heightened motivation, attributed to the personalized learning pathways and resources provided by the AI-assisted approach. The study underscores the importance of integrating adaptive technologies like AI-powered personalized learning pathways and real-time data analysis in language education, offering practical implications for educators and policymakers.

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Publication Details

Journal
International Journal of High Speed Electronics and Systems
Published
2025-06-16
DOI
https://doi.org/10.1142/s0129156425406497
Citations
2
Primary Topic
Educational Technology and Pedagogy
Type
article
Field-Weighted Citation Impact
4.96
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article

AI-Supported Differentiated Instruction for Chinese Vocational English Reading: Enhancing Proficiency and Motivation

Sanitah Mohd Yusof, Xiaodong Sun
2 citations
International Journal of High Speed Electronics and Systems
Educational Technology and Pedagogy
4.96
article

AI-Supported Differentiated Instruction for Chinese Vocational English Reading: Enhancing Proficiency and Motivation

Sanitah Mohd Yusof, Xiaodong Sun
article en
2 citations

Abstract

This study designed an AI-supported differentiated instruction, where adaptive algorithms assisted teachers in tailoring reading materials and assessments for vocational students among Chinese learners. The primary objective is to examine the literature gap regarding the application of such strategies in vocational settings. Utilizing a pre-experimental design, the research methodically investigates the impact of these tailored instruction strategies on students’ reading proficiency and motivation. The findings render important insights into the efficacy of differentiated instruction, demonstrating significant improvements in English reading outcomes among vocational education students. These discoveries highlight the potential of AI to enhance differentiated instruction, addressing the specific needs of vocational learners. The results indicated significant improvements in students’ reading skills and heightened motivation, attributed to the personalized learning pathways and resources provided by the AI-assisted approach. The study underscores the importance of integrating adaptive technologies like AI-powered personalized learning pathways and real-time data analysis in language education, offering practical implications for educators and policymakers.

International Journal of High Speed Electronics and SystemsVol. 35(04)
Hubei Polytechnic Institute (CN), University of Technology Malaysia (MY)
Openalex Percentile: Top 5%
Educational Technology and Pedagogy
4.96
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