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Volume 4,Issue 2

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26 February 2026

Empirical Research Report on AI-Enabled "Basic-Professional Integration" English Teaching Evaluation in the School of Economics and Management

Jingwei Zhu*
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1 Jiangsu Maritime Institute, Nanjing 211119, Jiangsu, China
LNE 2026 , 4(2), 90–96; https://doi.org/10.18063/LNE.v4i2.1512
© 2026 by the Author. Licensee Whioce Publishing, Singapore. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
Abstract

With the deep integration of AI into higher education, the "Basic-Professional Integration" (BPI) model has become key to solving the disconnection between foundational English skills and professional competencies in Economics and Management (EM) English teaching. This study adopted a mixed-methods design, dividing 100 EM students into an experimental group (AI-enhanced BPI pedagogy) and a control group (traditional teaching), with 10 trained instructors participating. Results show the AI-enabled BPI model significantly improved students’ language proficiency (25% higher improvement in IELTS-style assessments, 0.8-point average score increase) and professional skills (80% demonstrating advanced business proposal drafting competency). AI also built a dynamic evaluation system, reduced teachers’ workload by 40%, and increased student engagement by 35%. This study identifies key challenges and proposes solutions, providing a replicable reference for EM English teaching reform.

Keywords
Artificial Intelligence (AI)
Economics and Management English
Basic-Professional Integration (BPI)
Teaching Evaluation
Mixed-Methods Research
Professional Competency
Adaptive Learning
Funding
This paper is a partial research achievement of the Education and Teaching Reform Project of Jiangsu Maritime Institute, titled Reform and Practice of Higher Vocational English Teaching for the Shipping Economics and Management Professional Cluster under the Background of Basic-Professional Integration.
References

[1] Smith J, Johnson L, Williams R, 2023, The Impact of Virtual Teacher Tools on Oral English Practice in Higher Education. Journal of Language Teaching and Technology, 27(2): 45-62.

[2] Li Y, Zhang H, Wang L, 2022, Adaptive Learning Systems: A Catalyst for Improving Student Learning Initiative in English Teaching. Chinese Journal of Applied Linguistics, 45(3): 389-405.

[3] China Association of University Foreign Language Teaching. 2023. Survey Report on the Current Situation of Economics and Management English Teaching in Chinese Universities. Foreign Language Teaching in China, 46(1), 23-35.

[4] Brown A, 2021, Artificial Intelligence in Language Education: A Systematic Review. Language Learning & Technology, 25(4): 78-96.

[5] Wang Z, Li M, 2022, The Application of Natural Language Processing in English Writing Correction for Economics and Management Students. Journal of Business English Teaching, 15(2): 56-70.

[6] Davis E, Miller S, 2023, Generative AI in Professional English Teaching: Opportunities and Challenges. Journal of Applied Linguistics and Professional Communication, 18(3): 89-105.

[7] Zhu J, Chen Q, 2021, The Construction and Practice of “Basic-Professional Integration” Teaching Model in EM English Teaching. Higher Education Research, 42(8): 102-108.

[8] Borg S, 2022, Mixed-Methods Research in Language Teaching Evaluation: Design and Implementation. Applied Linguistics, 43(5): 876-898.

[9] Liu H, Zhang Y, 2023, Data Privacy Protection in AI-Enhanced Teaching: Issues and Solutions. Journal of Educational Technology Development and Exchange, 16(1): 34-49.

[10] Thompson P, Lee J, 2022, Customizing AI Models for Discipline-Specific English Teaching: A Case Study of Economics and Management. Journal of Language and Intercultural Communication, 22(4): 512-528.

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