HOW AI SUPPORTS THE DEVELOPMENT OF STUDENTS’ COMMUNICATIVE SKILLS IN ENGLISH TEACHING

Аннотация

Artificial intelligence (AI) is transforming English language teaching (ELT) from drill-based practice toward rich, interactional learning. When used deliberately and ethically, AI tools—large-language-model (LLM) chatbots, automatic speech recognition (ASR), text-to- speech (TTS), and learning analytics—expand opportunities for purposeful communication, timely feedback, and individualized scaffolding. This article outlines a practical framework showing how AI can nurture linguistic, sociolinguistic, discourse, and strategic competences; presents classroom-ready applications across skills; proposes assessment approaches that keep teachers “in theloop”; and highlights implementationandethics. Keywords: AI in ELT; communicative competence; chatbots; ASR; feedback; assessment; task- based learning. 1)Introduction:From practice to interaction Communicative skills are best developed through meaningful tasks where learners must negotiate meaning, manage turn-taking, adapt to audience and context, and repair breakdowns. AI supports this shift by (a) simulating varied interlocutors and scenarios; (b) providing immediate, targeted feedback; and (c) personalizing input and difficulty. Crucially, AI augments—rather than replaces—theteacher’s role as designer, coach, and assessor. 2)A competence-based lens Abalanced communicativesyllabus targets four interlocking domains:  Linguisticcompetence: grammar, lexis, phonology.  Sociolinguistic(pragmatic)competence: register, politeness, intercultural appropriacy.  Discourse competence: cohesion, coherence, and genre conventions.  Strategic competence: planning, monitoring, clarifying, and repair. AI affordances map naturally ontoeach domain:  LLM chatbots model audience-sensitive language, provide reformulations, and support role-plays.  ASR + TTS surface pronunciation, rhythm, and intelligibility issues with repeatable, low- anxiety practice.  Analytics visualizeprogress invocabulary range, speaking time, ordiscourse moves.  Generative tools supply leveled input, prompts, and counter-arguments that fuel negotiation ofmeaning. 3)Classroom applications byskill A. Speaking &Listening www.wordlyknowledge.uz ILMIYMETODIK JURNAL JOURNAL OFIQRO –ЖУРНАЛ ИҚРО –IQRO JURNALI –volume 17,issue01,2025 ISSN:2181-4341, IMPACT FACTOR( RESEARCH BIB )–7,245,SJIF–5,431 1. AI-mediated role-plays (pairor solo). Task:“Calla hotel toresolve a booking error.” o AI support: The chatbot acts as the receptionist; difficulty can be adjusted (e.g., o uncooperative tone, background constraints). Targets:turn-openers, hedging, clarification requests, closing moves. o Follow-up:Exporttranscript →highlight repairstrategies and pragmatics. o 2. Pronunciationclinics with ASR. Routine: 10–12 minute micro-drills on problem sounds (e.g., /θ/ vs /t/), word stress, or o thought groups. Cycle: Model →student attempt →ASRfeedback →teacher cue →re-record →reflect. o 3. Listeningwith adaptivescaffolds. Setup: Upload audio; generate synchronized transcript, glossed keywords, and o comprehension checks. Strategyfocus: prediction, selective listening, and verification;gradually remove scaffolds. o B. Reading& Writing 4. Genre-aware drafting assistants. Task: Write an inquiry email to a professor and a casual message to a friend about the same o topic. AI support: Suggest genre moves (greeting, purpose, request, thanks), highlight register o mismatches, provide examplesof hedging and mitigation. Metacognition: Studentsjustify accepted/rejected suggestions. o 5. Critical responding &summarizing. Task: Summarize an article in 120 words, then have AI challenge the summary with o counter-points; studentsrefine stanceand cohesion. Targets:discourse markers, stance verbs, cohesive devices. o C. Integrated tasks 6. Project simulations. Example: Plan a community workshop. Use AI to (a) script phone calls, (b) draft flyers, (c) o rehearse Q&A. Assessment: Task achievement (clarity, relevance to audience), discourse structure, o interactional management, and language control. 4)Feedback andassessment(formative first)  Instant, criterion-linked feedback. Calibrate AI outputs to your rubric (e.g., Task Fulfilment, Coherence & Cohesion, Lexical Resource, Pronunciation/Intelligibility, Pragmatics). Students receive targeted comments and examples, while the teacher validates and adds human judgment—especially forhigh-stakes decisions.  Evidence of process. Require drafts, prompts used, AI interactions, and a short rationale note(“What did Ichange and why?”). Thisfosters responsibilityand reduces over-reliance.  Speaking analytics, not score obsession. Track turns per minute, average turn length, percentage of successful repairs, backchannel frequency, and vocabulary variety. Visualize growth across weeks.  Integrity without “detectors.” Instead of policing, design assessments that include in-class components, oral defenses, and reflective logs. 5)Implementation roadmap forschools andprograms www.wordlyknowledge.uz ILMIYMETOD