Integrating Artificial Intelligence into Military English for Specific Purposes Education: A Case Study at a Military University in Vietnam

Abstract

This study investigates how Artificial Intelligence (AI) can enhance two mission-critical linguistic competencies in military English for Specific Purposes (ESP): (1) technical vocabulary accuracy and (2) spoken command performance under time-pressured operational conditions. A mixed-method case study was adopted to address the limited digital access and strict security requirements at the ADAFA in Vietnam. The quantitative component involved administering a 20-item questionnaire to 60 cadets, while qualitative insights were collected through semi-structured interviews with five ESP instructors. The instruments were adapted from validated AI-in-education scales and designed to capture four dimensions relevant to defense education: usefulness, motivation, linguistic performance, and technological readiness. Findings reveal that intranet-based AI tools significantly improve cadets’ accuracy in domain-specific terminology and increase confidence in delivering English command phrases. AI-generated feedback reduces speaking anxiety, while adaptive modules provide targeted practice aligned with operational tasks such as radar coordination and artillery command. However, implementation remains constrained by teachers’ limited AI literacy, security restrictions, and insufficient infrastructural support. To address these issues, the study proposes a three-layer model combining pedagogical adaptation, secure technological mediation, and institutional capacity building. The results provide a contextualized framework for integrating AI into ESP instruction in high-security military environments.

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