A Study on AI-Enabled Project-Based Instructional Design and Operational Mechanisms in Legal English Courses

DOI: https://doi.org/10.62517/jhet.202615239

Author(s)

Bin Xu

Affiliation(s)

Department of Foreign Language, Sanya University, Sanya, Hainan, China

Abstract

This study explores the design and operational mechanisms of AI-enabled project-based instruction in Legal English. Grounded in English for Specific Purposes (ESP), project-based learning (PBL), and human–AI collaborative learning theories, it constructs a task-centered instructional framework that integrates legal language learning with authentic professional contexts. The study proposes a modular course structure and examines how artificial intelligence can be embedded across instructional stages, including pre-task scaffolding, in-task support, and post-task feedback. Findings suggest that AI integration enhances learner engagement, reduces cognitive barriers in processing complex legal texts, and strengthens the practice-oriented nature of Legal English instruction. An operational model is further developed, encompassing instructional process design, role transformation, and staged learner development pathways. While the study indicates strong feasibility, it also identifies challenges such as over-reliance on AI tools, output instability, and teacher competency demands, alongside corresponding optimization strategies. The study is conceptual in nature and calls for future empirical validation in real classroom settings.

Keywords

Legal English; Artificial Intelligence; Project-Based Learning; English for Specific Purposes; Instructional Design; Human-AI Collaboration

References

[1]Dong Q. Research on the Practice of AI-Empowered College English Teaching Models. Office Informatization, 2026, 31(04): 46-48. [2]Su X, Liao Y. Research on AI-Enabled Foreign Language Classroom Teaching Model in Higher Vocational Colleges: Innovation of Classroom Teaching Model for Business English Major in Guangzhou South China Business Vocational College. Education Reform and Development, 2025, 7(11): 133-140. [3]Miao R. AI-Enabled Production-Oriented Approach: Construction and Implementation Paths for College English Teaching Design Principles. International Education Forum, 2025, 3(9): 52-60. [4]Chen L. Research on the Feasibility and Strategies of AI-enabled Formative Assessment in College Oral English Teaching. US-China Education Review A, 2025, 15(11): 66-70. [5]Zhang M. Exploration of AI-Enabled Smart Teaching in University English Education. Forum on Research and Innovation Management, 2025, 3(4): 1-6. [6]Liu J. Practice of College English Listening and Speaking Teaching in the Context of AI-enabled Cross-cultural Communication. Literature and Art Development and Innovation, 2025, 2(7): 1-5. [7]Chen S, Yang J. Innovative Research on AI-Enabled Innovation of Multiple Evaluation Systems in College English Teaching. Journal of Contemporary Educational Research, 2025, 9(8): 213-218. [8]Zhou F Y. Construction of an AI-Empowered “Teaching- Learning- Assessment Integration” System for Ideological and Political Education in College English Courses. Delta, 2025, (35): 93-95. [9]Ma S. Discussion on AI-enabled Teaching of English Majors. Research and Commentary on Humanities and Arts, 2025, 3(1): 1-4. [10]Guo W. Construction of an AI-Empowered Deep Learning Model for College English Teaching under the Core Competency Orientation. Shanxi Youth, 2025, (23): 193-195.