Exploring EFL Lecturers' Needs for AI-Assisted Teaching Strategies: A Qualitative Basis for Module Development in Henan, China

Authors

  • Shiyu Yuan

    Faculty of Education, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia
  • Nurfaradilla Mohamad Nasri

    Faculty of Education, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia
  • Khairul Azhar Jamaludin

    Faculty of Education, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia

DOI:

https://doi.org/10.30564/fls.v7i12.12396
Received: 9 October 2025 | Revised: 30 October 2025 | Accepted: 10 November 2025 | Published Online: 18 November 2025

Abstract

Artificial intelligence (AI) offers strong potential to enhance English language teaching, yet its pedagogical integration in Chinese universities remains uneven. Current training and practice often emphasize the technical use of individual tools rather than their purposeful application in communicative and interactive instruction. To address this gap, the present study examined the challenges and needs of university English as a Foreign Language (EFL) lecturers as a basis for developing a training module on AI-assisted teaching strategies in Henan, China. A qualitative design was employed, combining document analysis with semi-structured interviews involving 12 lecturers. Thematic analysis indicated that although lecturers had begun to explore AI and acknowledged its potential, their use was fragmented and largely confined to peripheral tasks. They faced barriers such as insufficient discipline-specific training, limited institutional support, and difficulties in aligning AI with teaching objectives and student proficiency levels. At the same time, they expressed strong expectations for practical and hands-on guidance, including clear objectives, classroom-based examples, step-by-step resources, and theoretically informed direction. These findings highlight a gap between current practices and desired outcomes and provide a foundation for designing a contextually relevant training module that supports the effective and responsible integration of AI in EFL teaching.

Highlights:

  • Reveals a clear gap between lecturers’ fragmented exploratory use of AI tools and their strong demand for systematic, pedagogically grounded integration.
  • Demonstrates that the lack of discipline-specific and practice-oriented training is the key barrier shaping lecturers' AI adoption in English language teaching.
  • Provides empirical support for applying McKillip's Discrepancy Model and the Dick and Carey instructional design model to technology integration in EFL contexts.
  • Underscores the critical role of Technological Pedagogical Knowledge (TPK) within the TPACK framework, as lecturers struggle to embed AI into pedagogy despite basic technological awareness.
  • Offers practical implications by calling for hands-on, contextualized, and theoretically informed training modules, supported by institutional and policy-level initiatives.

Keywords:

AI-Assisted Teaching; Needs Analysis; Second Language Teaching; Training Module

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How to Cite

Yuan, S., Mohamad Nasri, N., & Jamaludin, K. A. (2025). Exploring EFL Lecturers’ Needs for AI-Assisted Teaching Strategies: A Qualitative Basis for Module Development in Henan, China. Forum for Linguistic Studies, 7(12), 1209–1226. https://doi.org/10.30564/fls.v7i12.12396

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Vol. 7 , Iss. 12 (December 2025): In progress

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