Research on the Construction and Practice of an AI-Driven Personalized Learning Model for College English

Journal: Journal of Higher Education Research DOI: 10.32629/jher.v6i1.3635

Yin Li

Hebei GEO University, Shijiazhuang 050031, Hebei, China

Abstract

With the rapid development of artificial intelligence technology, the field of education has ushered in new changes and opportunities, and college English teaching is also facing new challenges and higher requirements. This study focuses on the AI-driven personalized college learning model and discusses its construction principles, methods and practical effects. Through the analysis of the current university English learning difficulties, it expounds the AI technology in providing accurate learning resources, intelligent guidance and the advantages of learning path planning, builds the fusion of AI personalized learning mode and verifies in practice the students' learning enthusiasm, learning performance and the effectiveness of autonomous learning ability,which can improve and provide useful reference for college English teaching reform.

Keywords

artificial intelligence; college English; personalized learning; learning model

References

[1]S.Yan, & Y. Yang. (2021). Education informatization 2.0 in China: Motivation, framework, and vision. Ecnu Review of Education, 4(2), 410–428.
[2]C.T. Yang, Y. Pei, & J. W. Chang. (2020). Innovative computing: IC 2020. Springer, Germany.
[3]N.Y. Kim, Y. Cha, & H. S. Kim. (2019). Future English learning: Chatbots and artificial intelligence. Multimedia-Assisted Language Learning, 22(3), 32–53.
[4]H.Du. (2021). An English network teaching method supported by artificial intelligence technology and wbiets system. Scientific Programming, 2021.
[5]C. W. Wei, H. Y. Kao, H. H. Lu, & Y. C. Liu. (2018). The effects of competitive gaming scenarios and personalized assistance strategies on English vocabulary learning. Journal of Educational Technology & Society, 21(3), 146–158.

Copyright © 2025 Yin Li

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License