Needs Analysis for the Design and Development of an AI-integrated Learning Module in English Speaking Classes: A Study on Chinese University Students

Needs analysis is the key part of designing and developing an AI-integrated learning module aimed at enhancing English speaking proficiency among Chinese university EFL learners. Scholars have investigated the speaking difficulties faced by Chinese tertiary EFL learners, and research has explored how artificial intelligence can help address these challenges. However, there has been insufficient focus on students’ needs and wants in AI-enhanced English speaking modules in English speaking classes. This research aims to fill this gap by examining the speaking-related requirements of Chinese university learners in AI-driven learning practice. This study is the first phase of a needs analysis for the design and development of an AI-integrated learning module, and the findings are expected to provide the basis for further designing and developing the module. The researchers chose Zhengzhou Business University as the research site and carried out qualitative research on students registered for an AI-integrated speaking class. By purposive convenience sampling and the rule of saturation, eight students were interviewed using a semi-structured interview, carefully videoed, transcribed, and finally analysed by NVivo 14. The findings indicate the primary speaking barriers Chinese university students face, the preferred integrated learning strategies and AI tools in speaking class, as well as students’ acceptance of the AI-integrated learning module. Students support AI tools as a complement to traditional English speaking learning methods and prioritize two kinds of applied AI tools for improving their speaking. They advocate a combination of AI tools with interactive and collaborative activities in English speaking classes; they showed a perceived willingness towards an AI-integrated learning module, regarding it as useful. This investigation is expected to contribute to the advancement of AI-integrated EFL speaking curricula and to offer insightful directions for further investigations into the application of AI in language education practice.

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Publication Details

Journal
International Journal of Learning Teaching and Educational Research
Published
2025-09-25
DOI
https://doi.org/10.26803/ijlter.24.9.27
Primary Topic
Geological Studies and Exploration
Type
article
Field-Weighted Citation Impact
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article

Needs Analysis for the Design and Development of an AI-integrated Learning Module in English Speaking Classes: A Study on Chinese University Students

International Journal of Learning Teaching and Educational Research
Geological Studies and Exploration
article

Needs Analysis for the Design and Development of an AI-integrated Learning Module in English Speaking Classes: A Study on Chinese University Students

article en

Abstract

Needs analysis is the key part of designing and developing an AI-integrated learning module aimed at enhancing English speaking proficiency among Chinese university EFL learners. Scholars have investigated the speaking difficulties faced by Chinese tertiary EFL learners, and research has explored how artificial intelligence can help address these challenges. However, there has been insufficient focus on students’ needs and wants in AI-enhanced English speaking modules in English speaking classes. This research aims to fill this gap by examining the speaking-related requirements of Chinese university learners in AI-driven learning practice. This study is the first phase of a needs analysis for the design and development of an AI-integrated learning module, and the findings are expected to provide the basis for further designing and developing the module. The researchers chose Zhengzhou Business University as the research site and carried out qualitative research on students registered for an AI-integrated speaking class. By purposive convenience sampling and the rule of saturation, eight students were interviewed using a semi-structured interview, carefully videoed, transcribed, and finally analysed by NVivo 14. The findings indicate the primary speaking barriers Chinese university students face, the preferred integrated learning strategies and AI tools in speaking class, as well as students’ acceptance of the AI-integrated learning module. Students support AI tools as a complement to traditional English speaking learning methods and prioritize two kinds of applied AI tools for improving their speaking. They advocate a combination of AI tools with interactive and collaborative activities in English speaking classes; they showed a perceived willingness towards an AI-integrated learning module, regarding it as useful. This investigation is expected to contribute to the advancement of AI-integrated EFL speaking curricula and to offer insightful directions for further investigations into the application of AI in language education practice.

International Journal of Learning Teaching and Educational ResearchVol. 24(9)
National University of Malaysia (MY)
Quality Education
Openalex Percentile: Top 35%
Geological Studies and Exploration
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