Exploration of pathways and reflection on application of AI-empowered practical teaching of listening and speaking in higher vocational English
Journal: Region - Educational Research and Reviews DOI: 10.32629/rerr.v7i11.4710
Abstract
In this era of rapid digitalization and globalization, higher vocational English (HVE) takes on the task of cultivating skilled workers, both technically and cross-culturally. However, traditional practical teaching of English listening and speaking in vocational schools faces several bottlenecks, such as insufficient instruction time, genuine-language-environment deficiency, and inadequate personalized evaluation. This paper intends to look into the transforming force of Artificial Intelligence (AI) to solve the issue. By using technologies like Natural Language Processing (NLP), Automatic Speech Recognition (ASR), and adaptive learning algorithms, this paper proposes a multi-angle path for promoting the training of English practical skills. The paper examines the advantages of AI in creating immersive scenarios, designing personalized learning pathways, and enabling real-time intelligent assessment. And it also offers a critical reflection on the application of these technologies – it mentions problems associated with the new tasks of teachers, the limitations of algorithmic feedback, and the requirement of humanistic values in language education. Study finds that although AI is a catalyst for educational reform, a mutualistic "Human-AI Collaboration" model can really upgrade listening and speaking education of English in college.
Keywords
artificial intelligence; higher vocational English; listening and speaking instruction; practical teaching; educational technology; human-machine collaboration
Full Text
PDF - Viewed/Downloaded: 0 TimesReferences
[1] Huang HB, Yan X. 2025. Generative artificial intelligence in English language education: potential, challenges, and the path forward. TESOL Quarterly, 59(S1): S330-S344.
[2] Zhao J. 2025. Advancing English language education: A mixed-methods analysis of AI-driven tools' impact on engagement, personalization, and learning outcomes. Education and Information Technologies, 30(15): 1-41.
[3] Juan W. 2025. Research on the application of generative AI in the case teaching of professional English. Education Research and Innovation, 1(11): 18-22.
[4] Yue S. 2024. A practical study on artificial intelligence (AI)-assisted college English translation teaching. Journal of Research in Science and Engineering, 6(10): 15-17.
[5] Cui Y. 2024. Application of artificial intelligence technology in college English vocabulary teaching. International Journal of New Developments in Education, 6(7).
[6] Liu S. 2024. AI-enabled vocational education: teacher role reshaping and competency enhancement paths. Occupation and Professional Education, 1(7).
[7] Yuan W. 2022. English translation teaching algorithm in colleges and universities using data-driven deep learning. Mobile Information Systems, 7(11):128-132.
[8] Büyükbucakl M. 2021. Application of data-driven learning in writing courses for English majors. Journal of Educational Research and Policies, 3(8): 62-70.
[9] Javad Z, Sedigheh K, Khadijeh DA. 2023. Classroom concordancing and English academic lecture comprehension: an implication of data-driven learning. Computer Assisted Language Learning, 36(5-6): 885-905.
[10] Wang Y, Cui C. 2024. Practices and challenges of artificial intelligence-assisted teaching in vocational undergraduate public English classrooms. Applied Mathematics and Nonlinear Sciences,9(1).
[2] Zhao J. 2025. Advancing English language education: A mixed-methods analysis of AI-driven tools' impact on engagement, personalization, and learning outcomes. Education and Information Technologies, 30(15): 1-41.
[3] Juan W. 2025. Research on the application of generative AI in the case teaching of professional English. Education Research and Innovation, 1(11): 18-22.
[4] Yue S. 2024. A practical study on artificial intelligence (AI)-assisted college English translation teaching. Journal of Research in Science and Engineering, 6(10): 15-17.
[5] Cui Y. 2024. Application of artificial intelligence technology in college English vocabulary teaching. International Journal of New Developments in Education, 6(7).
[6] Liu S. 2024. AI-enabled vocational education: teacher role reshaping and competency enhancement paths. Occupation and Professional Education, 1(7).
[7] Yuan W. 2022. English translation teaching algorithm in colleges and universities using data-driven deep learning. Mobile Information Systems, 7(11):128-132.
[8] Büyükbucakl M. 2021. Application of data-driven learning in writing courses for English majors. Journal of Educational Research and Policies, 3(8): 62-70.
[9] Javad Z, Sedigheh K, Khadijeh DA. 2023. Classroom concordancing and English academic lecture comprehension: an implication of data-driven learning. Computer Assisted Language Learning, 36(5-6): 885-905.
[10] Wang Y, Cui C. 2024. Practices and challenges of artificial intelligence-assisted teaching in vocational undergraduate public English classrooms. Applied Mathematics and Nonlinear Sciences,9(1).
Copyright © 2026 Xiaochuan HUI
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License