Individualized college English teaching based on artificial intelligence

With the widespread application of artificial intelligence technology in education, particularly in college English teaching, its potential for personalized instruction is gaining attention. This study aims to explore an AI-assisted personalized college English teaching model and evaluate its effectiveness in improving learning efficiency and teaching quality. Data were collected through questionnaire surveys and experimental studies on the experiences and satisfaction of students and teachers using AI teaching tools. The constructed teaching model is based on personalized learning theory and cognitive development theory, aiming to optimize the learning process and enhance learning outcomes. The experimental results showed that students using AI tools demonstrated higher improvement rates in various English skills, and both teachers and students expressed higher satisfaction with AI-assisted teaching. Despite research limitations, such as sample diversity and challenges posed by rapid technological advancements, this study provides valuable insights and recommendations for future AI applications in education.

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Publication Details

Journal
Journal of Computational Methods in Sciences and Engineering
Published
2025-08-19
DOI
https://doi.org/10.1177/14727978251367191
Primary Topic
Educational Technology and Pedagogy
Type
article
Field-Weighted Citation Impact
0.00
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article

Individualized college English teaching based on artificial intelligence

Lifang Xie
Journal of Computational Methods in Sciences and Engineering
Educational Technology and Pedagogy
article

Individualized college English teaching based on artificial intelligence

Lifang Xie
article en

Abstract

With the widespread application of artificial intelligence technology in education, particularly in college English teaching, its potential for personalized instruction is gaining attention. This study aims to explore an AI-assisted personalized college English teaching model and evaluate its effectiveness in improving learning efficiency and teaching quality. Data were collected through questionnaire surveys and experimental studies on the experiences and satisfaction of students and teachers using AI teaching tools. The constructed teaching model is based on personalized learning theory and cognitive development theory, aiming to optimize the learning process and enhance learning outcomes. The experimental results showed that students using AI tools demonstrated higher improvement rates in various English skills, and both teachers and students expressed higher satisfaction with AI-assisted teaching. Despite research limitations, such as sample diversity and challenges posed by rapid technological advancements, this study provides valuable insights and recommendations for future AI applications in education.

Journal of Computational Methods in Sciences and Engineering
Nanning Normal University (CN)
Openalex Percentile: Top 89%
Educational Technology and Pedagogy
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