LNELecture Notes in Education, Arts, Management and Social ScienceTBA2705-053XWHIOCE PUBLISHING PTE. LTD.10.18063/LNE.v4i2.1512ArticleEmpirical Research Report on AI-Enabled "Basic-Professional Integration" English Teaching Evaluation in the School of Economics and Managementhttps://artdesignp.com/journal/LNE/4/2/10.18063/LNE.v4i2.1512ZhuJingwei2026422026-02-26With 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.Artificial Intelligence (AI),Economics and Management English,Basic-Professional Integration (BPI),Teaching Evaluation,Mixed-Methods Research,Professional Competency,Adaptive Learning

[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.