Integrating AI into communicative grammar teaching

Sun‘iy intellekt (SI), xususan, generativ sun‘iy intellektning (GenAI) jadal rivojlanishi tillarni o‘qitish va o‘rganishda yangi imkoniyatlar yaratdi. So‘nggi tadqiqotlar GenAI shaxsiylashtirilgan ta‘lim, kontent yaratish, ta‘lim oluvchilarning faol ishtiroki, qayta aloqa va til amaliyoti imkoniyatlarini qo‘llab-quvvatlay olishini ko‘rsatmoqda, biroq aniqlik, unga ortiqcha tayanib qolish, maxfiylik va o‘qituvchi yo‘l-yo‘rig‘iga ehtiyoj bilan bog‘liq xavotirlar saqlanib qolmoqda (Law, 2024; Lee, 2024; Lo et al., 2024). Maqolada grammatik shaklga e‘tiborni tilning mazmunli qo‘llanishi bilan uyg‘unlashtirish vositasi sifatida SI ko‘magidagi kommunikativ grammatik topshiriqlarning imkoniyatlari o‘rganiladi. Topshiriqlarga asoslangan til o‘qitish, kommunikativ til o‘qitish va shaklga yo‘naltirilgan ta‘lim tamoyillariga tayangan holda, SIdan grammatika mazmunli natijalarga erishish resursi bo‘lib xizmat qiladigan dinamik kommunikativ vaziyatlar yaratishda foydalanish mumkinligi asoslanadi.

R E S E A RC H F O C US xalqaro ilmiy jurnali hamkorligida

QR-kod maqolaning DOI sahifasini ochadi SAHIFALAR TIL 135–140 Ingliz IQTIBOS UCHUN U. Abatbaeva, D.T.Xadjieva. Integrating AI into communicative grammar teaching // «O‘zbekiston olima ayollarining mamlakat taraqqiyotiga qo‘shayotgan hissasi» mavzusidagi xalqaro ilmiy-amaliy konferensiya materiallari (Nukus, 2026- yil 9–10-oktyabr). – Nukus, 2026. – B. 135–140. – DOI: https://doi.org/ 10.66073/ReFocus-Conf/0910021

«O‘zbekiston olima ayollarining mamlakat taraqqiyotiga qo‘shayotgan hissasi» XALQARO ILMIY-AMALIY KONFERENSIYA NUKUS, 9–10-OKT YABR 2026

INTEGRATING AI INTO COMMUNICATIVE GRAMMAR TEACHING

U. Abatbaeva ND 2 year student of English Linguistics D.T.Xadjieva Ph.d.prof.of Foreign Languages Faculty of Karakalpak state university - scientific adviser

Abstract: The rapid development of artificial intelligence (AI), particularly generative artificial intelligence (GenAI), has created new opportunities for language teaching and learning. Recent research indicates that GenAI can support personalized learning, content generation, learner engagement, feedback, and opportunities for language practice, although concerns remain regarding accuracy, over-reliance, privacy, and the need for teacher guidance (Law, 2024; Lee, 2024; Lo et al., 2024). This paper explores the potential of AI-supported communicative grammar tasks as a means of combining attention to grammatical form with meaningful language use. Drawing on principles of task-based language teaching, communicative language teaching, and form-focused instruction, the paper argues that AI can be used to create dynamic communicative situations in which grammar functions as a resource for achieving meaningful outcomes.

Keywords: artificial intelligence, generative AI, communicative grammar, task-based language teaching, focus on form, grammar instruction, negotiation of meaning, language learning tasks 1. Introduction Grammar has traditionally occupied an important position in foreign language teaching. Conventional grammar instruction frequently involves presenting a rule, providing examples, and asking learners to complete controlled exercises. Such activities can contribute to grammatical accuracy, but they do not necessarily provide sufficient opportunities for learners to use grammatical structures spontaneously in meaningful communication.

The development of communicative language teaching encouraged a shift from grammar as an isolated object of study toward grammar as a resource for expressing meaning. Nunan (1989) defines a task as classroom work involving learners in comprehending, manipulating, producing, or interacting in the target language while their primary attention is focused on meaning.

The emergence of generative artificial intelligence has introduced new possibilities for implementing these principles. Since the appearance of tools such as ChatGPT, research on AI in language education has expanded rapidly. Recent reviews indicate that GenAI can support language learning through content generation, personalized learning, feedback, and learner interaction (Law, 2024; Lo et al., 2024). A recent meta-analysis also reported positive effects of AI interventions on language-learning outcomes, including speaking performance, motivation, and language anxiety, although the effects depend on instructional and contextual factors (Zhang et al., 2024). However, the use of AI does not automatically make a classroom activity communicative. If learners simply ask an AI system questions and copy its responses, opportunities for interpersonal interaction may actually be reduced. NUKUS · 2026

UNESCO (2023) therefore emphasizes the importance of a human-centred approach to generative AI in education, including attention to human agency, ethical use, privacy, and pedagogical suitability. The important pedagogical question is consequently not whether AI can teach grammar, but how AI can be incorporated into communicative tasks in which X A L Q A R O I L M I Y- A M A L I Y K O N F E R E N S I YA

learners use grammar to communicate with other people. This paper proposes that AI can be particularly useful as a source of contextualized input and as a generator of situations, problems, linguistic data, and communicative challenges. When these materials are incorporated into pair and group tasks, AI can support rather than replace human interaction. The central argument is that AI-supported communicative grammar tasks can connect focus on form and focus on meaning by making grammatical form relevant to the successful completion of a communicative task. 2. Communicative Grammar and Task-Based Language Teaching « O ‘ Z B E K I S T O N O L I M A AY O L L A R I N I N G M A M L A K AT T A R A Q Q I Y O T I G A Q O ‘ S H AY O T G A N H I S S A S I »

Tasks occupy a central position in communicative language teaching because they provide learners with a reason to use language. Gass (1997) views a task as a piece of work that needs to be completed, while Pica et al. (1993) emphasize that communicative tasks require learners to use language to share information, express opinions, collaborate, or achieve a particular goal.

The important characteristic of a communicative task is therefore its purpose. Learners do not produce language simply because they have been instructed to demonstrate a grammatical structure. Instead, they produce language because they need to accomplish something.

This distinction is particularly important in grammar teaching. Consider the following traditional exercise:

Learners may correctly complete the sentence with were and would travel, but there is no genuine communicative need to use the structure.

“Imagine that you have $100,000. What would you do with the money?”

Students discuss their own ideas, respond to classmates, disagree, negotiate, and finally select the best proposal. The second activity creates a communicative reason for using the second conditional.

According to Pica et al. (1993), effective communicative tasks often contain an information gap, require learners to exchange information, involve convergent goals, and lead to a clearly defined outcome. These principles can also be incorporated into AI-supported grammar tasks.

Interaction is particularly important because it creates opportunities for negotiation of meaning. When learners experience difficulty understanding one another, they may request clarification, repeat information, reformulate an utterance, or check understanding. Such interaction can draw learners' attention to gaps in their existing linguistic knowledge. Therefore, communicative tasks can involve two processes simultaneously: meaning-focused communication and attention to grammatical form. This relationship is central to the concept of communicative NUKUS · 2026

grammar tasks. 3. Communicative Grammar Tasks and Focus on Form The integration of grammar into communicative activities does not mean that grammatical accuracy should be ignored. Instead, grammar can be addressed X A L Q A R O I L M I Y- A M A L I Y K O N F E R E N S I YA

through focus on form, in which learners' attention is temporarily directed toward linguistic form while they remain engaged in meaningful communication. Ellis (1997) argues that interpretation tasks can help learners identify the meanings associated with particular grammatical features. Such tasks make grammatical forms more noticeable in meaningful input. Consciousness-raising tasks provide another possibility. Loschky and Bley-Vroman (1993) provide a particularly relevant framework by arguing that grammatical accuracy should be connected to the successful completion of a communicative task. A target structure may be natural, useful, or essential to completing the task. « O ‘ Z B E K I S T O N O L I M A AY O L L A R I N I N G M A M L A K AT T A R A Q Q I Y O T I G A Q O ‘ S H AY O T G A N H I S S A S I »

This principle is especially useful when designing AI-supported activities. For example, if learners are solving an AI-generated mystery, past perfect and past continuous forms may become useful for explaining the sequence and duration of events. If they are discussing an AI-generated hypothetical situation, conditional forms become necessary for expressing possible consequences. In this way, the grammatical structure is not artificially added to communication. It becomes relevant because learners need it to communicate their intended meaning. 4. AI as a Resource for Communicative Grammar Tasks Recent research suggests that GenAI has several potential applications in language education. Law (2024), in a scoping review of research on GenAI in language teaching and learning, identifies applications involving content generation, language practice, feedback, and personalization. Similarly, Lee (2024) reports potential benefits of GenAI for personalization, efficiency, and learner engagement while emphasizing concerns about over-reliance, output quality, and the need for teacher guidance. These findings suggest that AI can perform several useful functions in communicative grammar tasks:  Input generator: AI can create dialogues, stories, examples, and contextualized language.  Scenario generator: AI can produce realistic problems, dilemmas, mysteries, and role-play situations.  Language-data generator: AI can produce examples that learners analyze during consciousness-raising activities.

 Feedback resource: AI can provide suggestions that learners subsequently evaluate.  Personalization tool: AI can adapt situations to learners' interests, proficiency levels, and communicative needs. However, these functions should be implemented within a human-centred NUKUS · 2026

pedagogical framework. UNESCO (2023) stresses that AI use in education should protect human agency and be guided by appropriate pedagogical and ethical considerations. Thus, AI should be viewed not as a replacement for classroom communication but as a resource for designing richer communicative experiences. X A L Q A R O I L M I Y- A M A L I Y K O N F E R E N S I YA

5. AI-Supported Communicative Grammar Activities 5.1. AI Mystery Detective Target grammar: Past simple, past continuous, and past perfect Level: B1– B2 Interaction: Groups of three or four The teacher asks an AI tool to generate a short mystery involving several characters, locations, and events. Each student receives different information about what happened. For example, the situation may involve a missing laptop at a university. « O ‘ Z B E K I S T O N O L I M A AY O L L A R I N I N G M A M L A K AT T A R A Q Q I Y O T I G A Q O ‘ S H AY O T G A N H I S S A S I »

Student A knows what happened in the classroom, Student B knows what happened in the library, and Student C knows what happened outside the building. Students interview one another and reconstruct the sequence of events: “What were you doing at 10 o'clock?” “Where had you gone before you arrived at the university?” “What happened after the teacher left?” Students then agree on the most likely explanation. Communicative outcome: The group identifies the most likely explanation of the mystery. The task creates a genuine need for past-tense forms because learners need to establish the sequence and duration of events. It therefore combines an information gap with attention to grammatical form. 5.3. AI Grammar Investigator Target grammar: Any selected grammatical structure Level: B1–C1 Interaction: Pairs or groups The teacher asks AI to generate 10–15 examples containing a target structure, including some correct and incorrect examples. For example, for the present perfect: “I have visited London three times.” “She has went to the university.” “Have you ever seen this film?” Students investigate the data rather than simply correcting the sentences. They discuss: 1. Which sentences are correct? 2. Which sentences are problematic?

3. What grammatical pattern can be identified? 4. Can the group formulate a rule? 5. Can the AI-generated examples contain errors? The groups then compare their conclusions. Communicative outcome: Students formulate and explain a grammatical NUKUS · 2026

rule. This activity directly connects with consciousness-raising tasks described by Ellis and Fotos (1991). The innovative element is that AI becomes the source of linguistic data. Students are also encouraged to develop critical AI literacy because they learn that AI-generated language must be evaluated rather than automatically X A L Q A R O I L M I Y- A M A L I Y K O N F E R E N S I YA

accepted. 5.4. AI Future Planner Target grammar: Future forms, modal verbs, and first conditional Level: A2–B1 Interaction: Pairs or groups Students ask AI to generate a realistic travel or event-planning situation: “Create a three-day trip for two university students with a limited budget. Include transportation, accommodation, weather, and two unexpected problems.” Students discuss and develop a plan: “We are going to stay…” « O ‘ Z B E K I S T O N O L I M A AY O L L A R I N I N G M A M L A K AT T A R A Q Q I Y O T I G A Q O ‘ S H AY O T G A N H I S S A S I »

“We should book…” “If it rains, we will…” “We might…” Halfway through the activity, the teacher asks AI to introduce a new problem, such as a change in the weather or cancellation of transportation. Students must modify their plan. Communicative outcome: Students present a final plan and explain their decisions. The changing conditions encourage spontaneous language use and require learners to reformulate their ideas. 7. Pedagogical Implications The integration of AI into communicative grammar teaching has several pedagogical implications. First, AI can increase the variety and flexibility of classroom materials. Teachers can generate different scenarios for different groups and adapt tasks to learners' proficiency levels and interests (Law, 2024). Second, AI can make grammar practice more contextualized. Instead of practicing isolated sentences, students can use grammatical structures to solve problems, make decisions, plan activities, and discuss hypothetical situations. Third, AI can support learner autonomy. Students can experiment with language, request alternative examples, and investigate grammatical patterns. Nevertheless, autonomy should be accompanied by critical evaluation because AI-generated content can contain inaccurate or inappropriate information (Lo et al., 2024).

Fourth, teachers remain essential. AI can generate content, but teachers determine the pedagogical purpose of the task, select appropriate materials, monitor interaction, and provide feedback. Recent reviews of AI in language education similarly emphasize the continuing importance of teacher guidance and responsible integration (Law, 2024; Lee, 2024). NUKUS · 2026

Finally, communicative grammar tasks should maintain a balance between technology and human interaction. The objective should not be to maximize learners' time interacting with AI. Rather, AI should be used when it can create better conditions for learners to communicate with one another. X A L Q A R O I L M I Y- A M A L I Y K O N F E R E N S I YA

8. Conclusion AI-supported communicative grammar tasks offer one possible way of addressing these challenges. AI can generate contextualized input, problems, dilemmas, mysteries, and linguistic data, while learners use these materials to interact, negotiate meaning, evaluate language, and achieve communicative outcomes. The activities presented in this paper demonstrate how AI can support information-gap tasks, consciousness-raising activities, problem-solving tasks, and communicative production. In each case, grammar is not treated as an isolated collection of rules. Instead, it functions as a resource for achieving a communicative « O ‘ Z B E K I S T O N O L I M A AY O L L A R I N I N G M A M L A K AT T A R A Q Q I Y O T I G A Q O ‘ S H AY O T G A N H I S S A S I »

purpose. The central principle can therefore be summarized as follows: AI should not replace communication in the language classroom; it should create better reasons for learners to communicate. When appropriately designed, AI-supported communicative grammar tasks can provide a contemporary approach to grammar teaching in which form serves meaning, technology supports interaction, and communication drives language learning.