JOURNAL OF IQRO – ЖУРНАЛ ИҚРО – IQRO JURNALI – volume 17, issue 01, 2025
ISSN: 2181-4341, IMPACT FACTOR ( RESEARCH BIB ) – 7,245, SJIF – 5,431
ILMIY METODIK JURNAL
Ozotov Akbarjon Odiljon o’g’li
Navoiy region Pedagogical skills center Head teacher
Sayfidinova Nozima Saydullo qizi
The graduate of the Uzbekistan-Finland Pedagogical Institute
HOW AI SUPPORTS THE DEVELOPMENT OF STUDENTS’ COMMUNICATIVE
SKILLS IN ENGLISH TEACHING
Abstract:
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 the loop”; and highlights implementation and ethics.
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—the teacher’s role as designer, coach, and assessor.
2) A competence-based lens
A balanced communicative syllabus targets four interlocking domains:
Linguistic competence:
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 onto each 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
visualize progress in vocabulary range, speaking time, or discourse moves.
Generative tools
supply leveled input, prompts, and counter-arguments that fuel
negotiation of meaning.
3) Classroom applications by skill
A. Speaking & Listening
JOURNAL OF IQRO – ЖУРНАЛ ИҚРО – IQRO JURNALI – volume 17, issue 01, 2025
ISSN: 2181-4341, IMPACT FACTOR ( RESEARCH BIB ) – 7,245, SJIF – 5,431
ILMIY METODIK JURNAL
1.
AI-mediated role-plays (pair or solo).
o
Task:
“Call a hotel to resolve a booking error.”
o
AI support:
The chatbot acts as the receptionist; difficulty can be adjusted (e.g.,
uncooperative tone, background constraints).
o
Targets:
turn-openers, hedging, clarification requests, closing moves.
o
Follow-up:
Export transcript → highlight repair strategies and pragmatics.
2.
Pronunciation clinics with ASR.
o
Routine:
10–12 minute micro-drills on problem sounds (e.g., /θ/ vs /t/), word stress, or
thought groups.
o
Cycle:
Model → student attempt → ASR feedback → teacher cue → re-record → reflect.
3.
Listening with adaptive scaffolds.
o
Setup:
Upload audio; generate synchronized transcript, glossed keywords, and
comprehension checks.
o
Strategy focus:
prediction, selective listening, and verification; gradually remove scaffolds.
B. Reading & Writing
4.
Genre-aware drafting assistants.
o
Task:
Write an inquiry email to a professor and a casual message to a friend about the same
topic.
o
AI support:
Suggest genre moves (greeting, purpose, request, thanks), highlight register
mismatches, provide examples of hedging and mitigation.
o
Metacognition:
Students justify accepted/rejected suggestions.
5.
Critical responding & summarizing.
o
Task:
Summarize an article in 120 words, then have AI challenge the summary with
counter-points; students refine stance and cohesion.
o
Targets:
discourse markers, stance verbs, cohesive devices.
C. Integrated tasks
6.
Project simulations.
o
Example:
Plan a community workshop. Use AI to (a) script phone calls, (b) draft flyers, (c)
rehearse Q&A.
o
Assessment:
Task achievement (clarity, relevance to audience), discourse structure,
interactional management, and language control.
4) Feedback and assessment (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 for high-stakes decisions.
Evidence of process.
Require drafts, prompts used, AI interactions, and a short
rationale
note
(“What did I change and why?”). This fosters responsibility and 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 for schools and programs
JOURNAL OF IQRO – ЖУРНАЛ ИҚРО – IQRO JURNALI – volume 17, issue 01, 2025
ISSN: 2181-4341, IMPACT FACTOR ( RESEARCH BIB ) – 7,245, SJIF – 5,431
ILMIY METODIK JURNAL
1.
Purpose & policy.
Define acceptable uses (e.g., idea generation, language repair,
pronunciation practice, scenario rehearsal) and boundaries for high-stakes tasks. Communicate
clearly to students and parents.
2.
Teacher capacity building.
Short, iterative PD cycles on: prompt design for pedagogy;
moderating AI feedback; AI-supported assessment; and inclusive practices.
3.
Tool selection criteria.
o
Privacy posture and data controls.
o
Classroom features (transcript export, rubric alignment, difficulty controls).
o
Accessibility (mobile/offline options, TTS voices, captioning).
o
Transparency (explainable feedback rather than opaque scores).
4.
Equity and access.
Provide low-tech equivalents (print role cards, teacher-led reading
circles), shared devices, and offline practice packs.
5.
Monitoring & evaluation.
Set quarterly targets (e.g., “reduce teacher talk time by 15%,”
“increase student turns by 30%”) and use common tasks to benchmark progress.
6) Ethics and safe use
Bias & appropriacy.
Review outputs for cultural and gender biases; expose learners to
global Englishes and multiple registers.
Privacy & consent.
Avoid uploading sensitive data; anonymize student work; obtain
consent for recording.
Well-being.
Keep AI interactions time-bounded; prioritize human discussion and
collaboration.
Transparency.
Tell learners what AI did in teaching, feedback, and grading—and what the
teacher decided.
7) Sample 90-minute lesson (B1–B2): Handling a complaint call
Objective:
Develop sociolinguistic and strategic competence (polite complaints and repair).
1.
Lead-in (10’):
Brainstorm problems; extract target language (e.g., “I’m afraid there’s been a
mistake,” “Could you clarify…?”).
2.
Model (10’):
Teacher demo + quick noticing (openings, empathy, solution, closing).
3.
AI Role-play (25’):
Students call an AI “agent”; each call must (a) explain the issue, (b) ask
clarifying Qs, (c) propose/accept a solution.
4.
Feedback (15’):
Export transcripts; annotate repair moves and politeness markers; teacher
adds corrections and upgraded phrases.
5.
Pronunciation focus (10’):
ASR drills on sentence stress and thought groups for key
phrases.
6.
Live performance (15’):
Pair-to-pair role-play without AI; peers use a micro-rubric.
7.
Reflection (5’):
“Which phrases felt natural? What would you try next time?”
Micro-rubric (5 points each):
Task clarity | Politeness & tone | Repair strategies | Fluency/turn-
taking | Intelligibility.
8) Prompt bank for communicative practice (copy-paste ready)
Role-play generator:
“Act as a [hotel receptionist / academic advisor / shop assistant]. Give me a realistic scenario
with 2–3 problems to solve. Vary your tone slightly (neutral → mildly impatient). Keep
responses to 1–3 sentences so I must ask follow-ups.”
JOURNAL OF IQRO – ЖУРНАЛ ИҚРО – IQRO JURNALI – volume 17, issue 01, 2025
ISSN: 2181-4341, IMPACT FACTOR ( RESEARCH BIB ) – 7,245, SJIF – 5,431
ILMIY METODIK JURNAL
Pragmatics coach:
“Rewrite my message for a professor (formal) and for a friend (casual). Explain the key
differences in tone, hedging, and directness in 3 bullets.”
Repair trainer:
“During our chat, deliberately misunderstand me once in a while. I will practice clarification.
After 5 minutes, summarize which repair phrases I used and where I could improve.”
Pronunciation focus:
“Give me 8 sentences that contrast /θ/ and /s/, then listen to my recording and point out
segmental and word-stress issues. Provide minimal pairs for targeted re-practice.”
9) Conclusion
AI’s greatest contribution to communicative skill development is
quantity and quality of
interaction with feedback
. Chatbots and ASR widen practice windows, lower anxiety, and make
feedback immediate; analytics help teachers individualize support; genre-aware drafting tools
cultivate discourse control and audience awareness. When anchored in clear learning aims,
robust pedagogy, and ethical safeguards—and when teachers remain the ultimate decision-
makers—AI becomes a powerful ally in helping learners speak, listen, read, and write English
more effectively and confidently.
Used literature:
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ОF
A
CОMMUNICATIVЕ
MЕTHОD
FОR
TЕACHING
FОRЕIGN
LANGUAGЕS.
INTERNATIONAL JOURNAL OF SOCIAL SCIENCE & INTERDISCIPLINARY
RESEARCH ISSN: 2277-3630 Impact factor: 8.036
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12
(06), 200-203.
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ORDER COGNITIVE DEVELOPMENT.
Академические исследования в современной
науке
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(45), 111-115.
4. Shakhnoza, T., & Nargiza, D. (2022). Curriculum Improvement At Secondary
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Достижения науки и
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