TEACHER-SUPERVISED ARTIFICIAL INTELLIGENCE AND EDUCATIONAL CORPORA FOR DEVELOPING FUTURE OFFICERS’ PROFESSIONAL ENGLISH LEXICAL COMPETENCE
Keywords:
artificial intelligence, future officers, educational corpus, professional English, lexical competence, teacher supervision, feedback.Abstract
This article proposes a teacher-supervised design combining generative artificial
intelligence with a curated educational corpus for professional English vocabulary
learning. It addresses the risk that fluent generated language may contain inaccurate
terminology, unsuitable collocations or unsupported institutional equivalents. The
proposed sequence begins with verified lexical entries and approved educational
examples, followed by constrained task generation, teacher review, learner production
and evidence-based revision. A material review matrix, prompt specification, feedback
protocol and subsequent pilot design are provided. The distinction between an AI
assisted product and independent lexical performance is maintained throughout. The
paper is a theoretical and methodological contribution; it does not report an
implemented system or measured learning gains. Its central argument is that generated
material should enter the course through a documented editorial process rather than
through fluency alone.
References
[1] UNESCO. Guidance for generative AI in education and research. Paris, 2023.
https://www.unesco.org/en/articles/guidance-generative-ai-education-and-research
[2] Hutchinson T., Waters A. English for Specific Purposes A Learning centred
Approach.
Cambridge
University
Press,
1987.
https://www.cambridge.org/core/books/english-for-specific
purposes/449E5F788C04B222B0C9CD58FEB16868
[3] Nation I. S. P. Learning Vocabulary in Another Language. Third edition.
Cambridge University Press, 2022. https://www.cambridge.org/core/books/learning
vocabulary-in-another-language/97C1293EBC8716EA70B77626E00740AA