My Approach to Using Artificial Intelligence in English Language Teaching - A Human-Centered Framework for Language Learning and Teaching

Citation: Gohar Hambardzumyan, "My Approach to Using Artificial Intelligence in English Language Teaching - A Human-Centered Framework for Language Learning and Teaching", Universal Library of Languages and Literatures, Volume 03, Issue 01.

Copyright: This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Artificial intelligence is an increasingly common feature of second-language education, offering learners new opportunities for practice, feedback, and individualized pacing. This paper presents a human-centered instructional framework that specifies how AI can be integrated into English language teaching while preserving the teacher’s professional judgment and the learner’s own communicative development. The framework organizes established principles of second-language acquisition, adult learning, corrective feedback, and responsible technology use into a structured, repeatable instructional architecture: a ten-stage instructional cycle (Identify -> Design -> Prepare -> Teach -> Practice -> Reflect -> Produce -> Evaluate -> Analyze -> Adapt) led throughout by the teacher as learning architect, a scored five-criterion rubric for deciding when AI use is instructionally appropriate, a five-step protocol for converting AI-generated feedback into independent learner production (Read -> Observe Patterns -> Revise with Understanding -> Reflect -> Demonstrate), and explicit procedures for learner prompt literacy, culturally responsive mediation, and assessment designed to distinguish AI-assisted performance from independent competence. The framework is grounded in my own published empirical research, instructional materials, and documented classroom applications (Hambardzumyan, 2026a, 2026b), as well as a documented independent implementation of a core component of the methodology. It is extended here with a scored suitability rubric, an explicit transferability dimension across learners and instructional contexts, and an instrument-based pilot protocol for further empirical evaluation. My framework’s contribution lies in the systematic integration and operationalization of established pedagogical principles into a repeatable instructional process that guides AI selection, teacher mediation, learner interaction, independent production, assessment, and instructional adaptation in AI-supported English-language teaching, with direct applicability to teacher professional development as well as classroom practice.

Keywords: Adult Language Education, Artificial Intelligence, English Language Teaching, Instructional Design, Corrective Feedback, Prompt Literacy, Teacher Development.

https://doi.org/10.70315/uloap.ullli.2026.0301005