METHODOLOGY FOR DEVELOPING FUTURE ENGLISH LANGUAGE TEACHERS’ SKILL IN VERIFYING AI-GENERATED RESPONSES

Abstract

This article examines the transformation of professional training for future English language teachers amid the rapid development of artificial intelligence (AI) technologies. The integration of generative tools into the educational environment creates not only new didactic opportunities but also significant methodological and ethical challenges, the most critical of which is the reliability of AI-generated content. Current educational programs tend to focus primarily on the instrumental use of technology, while methodologies for developing critical-analytical skills remain underdeveloped.

The aim of the study is to theoretically substantiate and empirically test a methodology for developing the verification skill of AI-generated responses during language tasks. The paper clarifies the concept of "verification skill", defining it as an integrated professional ability to analyse, evaluate, and correct AI outputs in accordance with linguistic norms and methodological soundness. A structure for this skill is proposed, comprising four interconnected components: cognitive (knowledge of AI principles), analytical-evaluative (error detection), operational-corrective (editing), and value-reflexive (academic integrity).

Based on empirical data collected from students of the Philological Faculty, the level of development of this skill was analysed. The results indicated that future teachers mostly possess fragmented abilities in editing AI texts: the cognitive component is the most developed, whereas the operational-corrective component is the weakest due to the unsystematic nature of corrections. It was also found that students tend to focus on formal accuracy while neglecting stylistic and methodological nuances. The study concludes that purposeful implementation of verification methodology in professional training is essential to ensure teachers’ methodological autonomy in a digitized environment.