magazinelogo

The Educational Review, USA

ISSN Online: 2575-7946 ISSN Print: 2575-7938 CODEN: TERUBB
Frequency: monthly Email: edu@hillpublisher.com
Total View: 6769355 Downloads: 1407214 Citations: 1026 (From Dimensions)
OpenAlex-based citation data
  • citations

    1417
  • h-index

    13
  • i10-index

    14
ArticleOpen Access http://dx.doi.org/10.26855/er.2026.04.009

The Effectiveness of Generative AI-empowered “Smart-Fun Integration” in Business English Teaching Reform: Suggestive Evidence from a Difference-in-Differences Design

Qingyu Guo, Yufei He*, Lan Li, Na Zhu

School of Economics and Management, Chongqing Metropolitan College of Science and Technology, Chongqing 402100, China.

*Corresponding author: Yufei He

This research was funded by the 2025 Higher Education Teaching Reform Project of Chongqing Metropolitan College of Science and Technology (Grant No. YJ2513), under the project “Construction and Practice of a ‘Smart-Fun Integration’ Teaching Model for the Business English Course Driven by AI”. It was also funded by the Association of Higher Education of Chongqing (Grant No. CQGJ2508C), under the project “Mechanism and Empirical Study on the Dual‑Dimensional Coupling of Human‑Computer Collaborative Learning among College Students in Chongqing under the Background of AI‑Enabled Education Transformation”. Our work also received technical and financial support from the project led by Na Zhu, namely “Research on the Construction, Improvement, and Application of a Multimodal Data-Driven Whole-Process Evaluation System for ‘Management-Engineering Integration’ Practical Training in Intelligent Manufacturing” (2026).
Published: April 26, 2026

Abstract

This study evaluates a “Smart-Fun Integration” teaching reform implemented in the Spring 2026 semester at an application-oriented college. A Business English AI dialogue platform built on the Doubao API and the TalkAI app was used to construct a generative-AI-embedded, task-driven model. A difference-in-differences (DID) design approach was applied to 154 Business Administration students across five classes. Main outcomes were measured through adapted self-report scales, supplemented by a standardized writing test. Results show that the treatment group achieved net gains of 0.41 points in self-assessed writing ability and 0.53 points in self-assessed oral interaction ability on a 5-point Likert scale (p < .05), corresponding to medium effect sizes (Cohen’s d = 0.52 and 0.61). Behavioral and cognitive engagement improved significantly, whereas emotional engagement did not. Within-treatment correlational analysis showed a positive association between AI dialogue frequency and gains in ability, without implying a causal dosage effect. Heterogeneity analysis indicated that intermediate-proficiency learners benefited the most, while low-proficiency learners showed no significant improvement in self-assessed oral interaction ability. Given identification constraints—few clusters, a single pre-treatment period, intact-class assignment, and self-reported outcomes—causal claims remain suggestive. This study offers an honest empirical record of a genuine pedagogical reform and a replicable pathway for AI integration in ESP courses.

Keyword

Generative AI; business English; Smart-Fun Integration; Doubao; DID

References

Angrist, J. D., & Pischke, J.-S. (2009). Mostly harmless econometrics. Princeton University Press.

Bertrand, M., Duflo, E., & Mullainathan, S. (2004). How much should we trust differences-in-differences estimates? Quarterly Journal of Economics, 119(1), 249-275.

Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351-370.

Cao, S., & Phongsatha, S. (2025). An empirical study of the AI-driven platform in blended learning for Business English performance and student engagement. Language Testing in Asia, 15, Article 39.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.

Fathi, J., Rahimi, M., & Derakhshan, A. (2024). Improving EFL learners’ speaking skills and willingness to communicate via artificial intelligence-mediated interactions. System, 121, 103254.

Handelsman, M. M., Briggs, W. L., Sullivan, N., & Towler, A. (2005). A measure of college student course engagement. The Journal of Educational Research, 98(3), 184-192.

Kong, L. (2026, April 9). Paradigm shift in foreign language teaching in the AI era: From “result visibility” to “process verifiability” [Lecture]. Innovative Research Forum, National Research Centre for Foreign Language Education, Beijing Foreign Studies Uni-versity.

Li, R. (2026, April 13). Myths and breakthroughs: Generative AI-driven paradigm reconstruction for foreign language teaching [Lecture]. School of Foreign Languages, Southeast University.

Marsh, H. W. (1982). SEEQ: A reliable, valid, and useful instrument for collecting students’ evaluations of university teaching. British Journal of Educational Psychology, 52(1), 77-95.

Mei, J., & Xie, Y. (2025). How can policies promote educational equity: An evaluation based on the educational effects on migrant workers’ children. Jinan Journal (Philosophy & Social Science Edition), (11), 181-196.

Ministry of Education. (2018). National standards for the quality of undergraduate teaching in Business English programs (Document No. [2018]4).

Ministry of Education. (2024, March 28). The Ministry of Education launched four actions to promote AI-enabled education. Retrieved from the Ministry of Education website.

Ministry of Education. (2026). “AI + Education” action plan. Ministry of Education and four other departments.

Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, 100041.

Pintrich, P. R., Smith, D. A. F., Garcia, T., & McKeachie, W. J. (1991). A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ). University of Michigan.

Ryan, R. M. (1982). Control and information in the intrapersonal sphere: An extension of cognitive evaluation theory. Journal of Per-sonality and Social Psychology, 43(3), 450-461.

Shao, Y., & Liu, J. (2024). Research on the reform of Business English teaching models in the context of artificial intelligence. China Informatization, (03), 22-25.

Su, Y. (2026, January 12). AI-empowered foreign language teaching: Competent use, wise use, and integrated use [Lecture]. School of Foreign Languages, Yantai Institute of Technology.

Tai, T.-Y., & Chen, H. H.-J. (2024). Improving elementary EFL speaking skills with generative AI chatbots: Exploring individual and paired interactions. Computers & Education, 220, 105112.

Tsai, S.-C. (2025). Online EFL business writing with GenAI-generated templates: Students’ performance and perceptions. Australasian Journal of Educational Technology, 41(6), 82-97.

Wang, L., & Fan, J. (2020). Assessing Business English writing: The development and validation of a proficiency scale. Assessing Writing, 46, 100490.

Warschauer, M. (2003). Technology and social inclusion: Rethinking the digital divide. MIT Press.

Wu, X.-Y. (2024). AI in L2 learning: A meta-analysis of contextual, instructional, and social-emotional moderators. System, 126, 103498.

Zhang, C., Meng, Y., & Ma, X. (2024). Artificial intelligence in EFL speaking: Impact on enjoyment, anxiety, and willingness to communicate. System, 121, 103259.

Copyright

© 2026 by the author(s).
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives (CC BY-NC-ND) license, which permits non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited and is not modified or adapted.
https://creativecommons.org/licenses/by-nc-nd/4.0/

How to cite this paper

The Effectiveness of Generative AI-empowered “Smart-Fun Integration” in Business English Teaching Reform: Suggestive Evidence from a Difference-in-Differences Design

How to cite this paper: Qingyu Guo, Yufei He, Lan Li, Na Zhu. (2026). The Effectiveness of Generative AI-empowered “Smart-Fun Integration” in Business English Teaching Reform: Suggestive Evidence from a Difference-in-Differences DesignThe Educational Review, USA10(4), 239-246.

DOI: http://dx.doi.org/10.26855/er.2026.04.009