AI-Supported Differentiated Instruction for Chinese Vocational English Reading: Enhancing Proficiency and Motivation
Year: 2025
Type: article
Study design: Clinical Trial
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.
Authors: Xiujun Sun, Sanitah Mohd Yusof
Language: English
Subfield: Language and Linguistics
Field: Arts and Humanities
Domain: Social Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W4411345317