Sun’iy Intellekt va Raqamli Iqtisodiyot

kelajak kasbiy faoliyatida ham mustaqil va mas’uliyatli qarorlar qabul qila olish qobiliyatini ta’minlaydi. Foydalanilgan adabiyotlar ro‘yxati 1. Зимняя И.А. Педагогическая психология: учебник для вузов. –М.: Логос, 2004. 384 с. 2. Bandura A. Self-efficacy: The Exercise of Control. New York: W.H. Freeman and Company, 1997. 604 p. 3. Gross J.J. Emotion Regulation: Conceptual and Empirical Foundations. New York: Guilford Press, 2014. 592 p. 4. Zimmerman B.J. Attaining Self-Regulation: A Social Cognitive Perspective. In: Handbook of Self-Regulation / ed. by M. Boekaerts, P. R. Pintrich, M. Zeidner. San Diego: Academic Press, 2000. P. 13–39. 5. Flavell J.H. Metacognition and Cognitive Monitoring: A New Area of CognitiveDevelopmental Inquiry. American Psychologist. Washington, DC: American Psychological Association, 1979. Vol. 34, No. 10. P. 906–911. 6. Карпов А.В. Психология рефлексивных механизмов деятельности. Москва: Институт психологии РАН, 2004. 424 с. 7. G‘oziyev E.G. Umumiy psixologiya. -T.: O‘qituvchi, 2002. 352 b. TOWARDS A PEDAGOGICAL FRAMEWORK FOR INTEGRATING GENERATIVE AI INTO ENGLISH LANGUAGE TEACHING Ismoilova Shakhnoza Abdumalik qizi, NamSTU, Teacher of the “Foreign Languages“department of shahnoza9228@gmail.com Annotatsiya. Mazkur maqolada ingliz tilini o‘qitishda generativ sun’iy intellektni integratsiya qilishning pedagogik asoslari ishlab chiqiladi. O‘zbekiston oliy ta’lim muassasalarida o‘tkazilgan so‘rovnoma natijalariga ko‘ra, o‘qituvchilarning atigi 23,4 foizi sun’iy intellekt vositalarini muntazam qo‘llaydi. Mualliflar tomonidan taklif etilgan to‘rt bosqichli model amaliyotga tatbiq etishning samarali mexanizmini taqdim etadi. Kalit so‘zlar: generativ sun’iy intellekt, ingliz tili o‘qitish, pedagogik model, texnologiya integratsiyasi, O‘zbekiston ta’limi Аннотация. В данной статье разрабатываются педагогические основы интеграции генеративного искусственного интеллекта в преподавание английского языка. Согласно результатам опроса, проведенного в высших учебных заведениях Узбекистана, только 23,4 % преподавателей регулярно используют инструменты искусственного интеллекта. Предлагаемая авторами четырехэтапная модель представляет собой эффективный механизм практического внедрения. Ключевые слова: генеративный искусственный интеллект, преподавание английского языка, педагогическая модель, интеграция технологий, образование Узбекистана Abstract. This article develops a pedagogical framework for integrating generative artificial intelligence into English language teaching. According to survey results conducted in Uzbek higher education institutions, only 23.4% of teachers regularly use artificial intelligence tools. The four-stage model proposed by the authors provides an effective mechanism for practical implementation. Key words: generative artificial intelligence, English language teaching, pedagogical framework, technology integration, Uzbek education 219

Introduction. The rapid proliferation of generative artificial intelligence (GenAI) technologies, particularly large language models such as ChatGPT, GPT4, and Google Bard, has precipitated an unprecedented paradigm shift in educational practices globally [1]. Within the field of English language teaching (ELT), these technologies present both transformative opportunities and profound challenges. Unlike previous educational technologies that primarily served as delivery mechanisms or practice tools, GenAI functions as an active, generative agent capable of producing human-like text, engaging in dynamic dialogue, providing instant feedback, and creating customized learning materials [2]. The global response to GenAI in education has been characterized by considerable ambivalence. While some institutions initially responded with outright bans, others have embraced these tools as catalysts for pedagogical innovation [3]. This international divergence reflects a deeper epistemological uncertainty regarding the appropriate relationship between human cognition and machine intelligence in learning processes. In the context of Uzbekistan, the integration of GenAI into ELT assumes particular significance. The Presidential Decree No. PQ-5117 dated May 19, 2021, "On Measures to Raise the Quality of Education in Foreign Languages to a Fundamentally New Level," explicitly prioritizes the implementation of modern information and communication technologies in language instruction. Furthermore, the "Digital Uzbekistan — 2030" strategy mandates the comprehensive digital transformation of the national education system. Despite these policy imperatives, there exists a substantial gap between high-level strategic objectives and classroom-level pedagogical practice [4]. Preliminary observations suggest that while many Uzbek English teachers possess awareness of GenAI tools, systematic, pedagogically grounded integration remains exceptionally rare. The central problem addressed by this study is the absence of a coherent, theoretically informed, and contextually appropriate pedagogical framework for integrating GenAI into ELT, particularly within the Uzbek higher education context. This study aims to develop a comprehensive pedagogical framework for integrating generative AI into English language teaching that is: theoretically grounded in established language acquisition theories; empirically informed by the perspectives of ELT practitioners and learners; and contextually responsive to the conditions of Uzbek higher education. The research is guided by four principal questions: (1) What are the current practices, perceptions, and professional development needs of Uzbek ELT practitioners regarding GenAI integration? (2) What affordances and constraints do Uzbek university students perceive in using GenAI tools for English language learning? (3) How can established theories of second language acquisition inform a pedagogical framework for GenAI-mediated ELT? (4) What constitutes a contextually appropriate pedagogical framework for systematic GenAI integration in Uzbek ELT contexts? 220

Methodology. This study employed an explanatory sequential mixedmethods design, comprising three interconnected phases [5]. This design was selected to achieve both breadth of descriptive representation and depth of interpretive understanding regarding GenAI integration in Uzbek ELT contexts. Phase 1 involved a large-scale survey of ELT practitioners and university students to establish baseline data regarding current practices, perceptions, and professional development needs. Phase 2 consisted of semi-structured interviews and classroom observations with a purposively selected subsample to elucidate mechanisms underlying quantitative patterns. Phase 3 comprised iterative synthesis of empirical findings with theoretical literature to develop and refine the proposed pedagogical framework. The teacher sample comprised 47 ELT instructors from 12 Uzbek higher education institutions, including four major universities (National University of Uzbekistan, Uzbekistan State World Languages University, Samarkand State University, Bukhara State University) and eight regional institutions. Sampling employed stratified purposive strategies to ensure representation across institution type, geographic region, teaching experience, and professional rank. The student sample comprised 124 undergraduate English philology and linguistics students from five universities. Inclusion criteria required: current enrollment in Englishmedium instruction or English major program; minimum B1 CEFR proficiency level; and at least one semester of university study completed. The teacher technology integration survey was developed specifically for this study, comprising six sections: demographic and professional background; current GenAI tool usage; perceived affordances of GenAI for ELT; perceived barriers and challenges; professional development needs and preferences; and open-ended narrative responses. Items employed 5-point Likert scales. The instrument was developed in English, translated into Uzbek and Russian using back-translation procedures, and pilot tested with 15 ELT instructors not included in the main sample. Cronbach's α for scaled sections ranged from .81 to .89, indicating acceptable to good internal consistency. The student technology learning survey comprised five sections: demographic and language background; GenAI usage patterns; perceived learning benefits; concerns and challenges; and open-ended reflection on AI-mediated learning experiences. From quantitative respondents, 12 teachers and 18 students were purposively selected for qualitative participation. Selection criteria maximized variation across dimensions including GenAI adoption status, institutional context, teaching experience or student proficiency, and expressed attitudes. 221

Table 1 Table 2 Teacher participant demographics (N = 47) Characte ristic Category n % Gender Female 38 80.9 Male 9 19.1 Experience < 5 years 12 25.5 5-10 years 18 38.3 Student participant demographics (N =124) Characteristic Category n % Gender Female 98 79.0 Male 26 21.0 1st year 34 27.4 2nd year 41 33.1 3rd year 29 23.4 4th year 20 16.1 B1 52 41.9 B2 58 46.8 C1 14 11.3 Yes 78 62.9 No 46 37.1 Year of study 11-15 years 11 23.4 > 15 years 6 12.8 Bachelor's 14 29.8 CEFR level Degree Institution Master's 28 59.6 PhD/Doctorate 5 10.6 Capital city 29 61.7 Regional 18 38.3 Prior use GenAI Data collection proceeded in three phases. Phase 1 (January-February 2024): Online surveys administered via Google Forms, distributed through university email systems and professional networks. Response rate: teachers 71.2% (47/66); students 68.5% (124/181). Phase 2 (March-April 2024): Individual interviews (4575 minutes) conducted via Zoom or in-person based on participant preference. All interviews were audio-recorded and transcribed verbatim. Eight classroom observations were conducted. Phase 3 (May-June 2024): Iterative framework development incorporating two member-checking focus groups. Quantitative analysis employed descriptive statistics and inferential analyses including independent samples t-tests and one-way ANOVA with Bonferroni correction. Statistical analysis was conducted using SPSS version 28. Qualitative analysis was conducted using reflexive thematic analysis within a critical realist paradigm. Analysis proceeded through six phases: data familiarization; systematic coding using NVivo 14; initial theme generation; theme review and refinement; theme definition; and write-up. Coding reliability was enhanced through investigator triangulation with three researchers independently coding 20% of transcripts achieving 87% agreement and negative case analysis. 222

Result. Current practices and perceptions of ELT practitioners. Survey findings revealed substantial awareness of GenAI tools among Uzbek ELT practitioners, yet considerably lower rates of systematic classroom integration. Among 47 teacher respondents, 89.4% (n = 42) reported awareness of ChatGPT, while 74.5% (n = 35) were familiar with Grammarly. However, only 23.4% (n = 11) reported using any GenAI tool in their teaching practice at least weekly, with 42.6% (n = 20) reporting occasional use, and 34.0% (n = 16) reporting no classroom use whatsoever. Among the 11 regular integrators, usage patterns clustered into three primary categories. Material preparation was reported by 81.8% (n = 9) of regular integrators. Teachers employed GenAI to generate reading passages at appropriate proficiency levels, create vocabulary exercises, develop discussion prompts, and design assessment items. One experienced integrator explained: "Before ChatGPT, I spent three to four hours preparing differentiated materials for my first-year students who have very mixed proficiency levels. Now I can generate three versions of the same text in about twenty minutes." Feedback and error correction was reported by 63.6% (n = 7) of regular integrators. Several teachers reported using Grammarly and similar tools to supplement their own written feedback, particularly for large classes. Demonstration and modeling was reported by 45.5% (n = 5) of regular integrators. Teachers projected live GenAI interactions during class to model writing processes and stimulate critical discussion. Table 3 Teacher Perceptions of GenAI in ELT (N = 47) Statement Mean SD % Agree GenAI has potential to enhance English language teaching 4.23 0.71 87.2 I am interested in learning to integrate GenAI effectively 4.18 0.79 83.0 GenAI threatens academic integrity in my courses 4.02 0.88 76.6 I am concerned GenAI will make students overly dependent 3.98 0.92 74.5 I have adequate knowledge to evaluate GenAI output critically 2.87 0.94 27.7 My institution provides clear guidance on GenAI use 2.23 0.87 14.9 I have received adequate training on GenAI for teaching 1.98 0.76 10.6 Note: 5-point Likert scale. % Agree combines "Agree" and "Strongly Agree" responses. Among non-integrating teachers (n = 36), primary barriers included lack of pedagogical guidance (67.6%, n = 23), inadequate infrastructure (54.1%, n = 20), 223

limited digital proficiency (41.9%, n = 15), and institutional ambivalence (35.1%, n = 13). One teacher stated: "Our department sent an email saying students should not use ChatGPT. That was it. No discussion of how we might teach with it, no professional development, no opportunity to explore possibilities." One-way ANOVA revealed significant differences in attitudes by teaching experience. Early-career teachers (< 5 years, n = 12) expressed significantly more positive attitudes toward GenAI integration (M = 4.42, SD = 0.51) than mid-career (5-15 years, n = 29, M = 3.87, SD = 0.68) and late-career teachers (> 15 years, n = 6, M = 3.21, SD = 0.79), F(2,44) = 8.34, p < .001, η² = .27. Regarding professional development, 89.4% (n = 42) of teachers indicated they would participate in GenAI-focused training if offered. Student perspectives on GenAI-Mediated learning. Among 124 student respondents, 62.9% (n = 78) reported prior GenAI use for English learning purposes. Usage frequency varied considerably: daily users comprised 16.1% (n = 20), weekly users 31.5% (n = 39), and monthly users 15.3% (n = 19). Notably, students reported substantially higher GenAI usage than teachers estimated. When asked "What percentage of your students do you believe regularly use GenAI for coursework?", teacher median estimate was 35%. Actual student-reported regular usage was 47.6%. Table 4 Student Purposes for GenAI Use in English Learning (n = 78) Purpose n % Writing assistance 67 85.9 Vocabulary acquisition 58 74.4 Translation support 52 66.7 Reading comprehension 41 52.6 Speaking practice 23 29.5 Exam preparation 19 24.4 Students identified multiple learning benefits from GenAI engagement, organized around three core themes emerging from qualitative analysis. Theme 1: Immediate, non-judgmental feedback. Students overwhelmingly valued the immediate availability and non-evaluative nature of AI feedback. One student explained: "When I write something and show my teacher, I feel nervous. With ChatGPT, I can check my sentences immediately. Nobody is judging me." Theme 2: Scaffolded independence. Students reported that AI assistance enhanced rather than diminished their sense of autonomy. Theme 3: Personalized, self-directed learning. Advanced students particularly valued GenAI's capacity to support selfdirected learning beyond the curriculum. 224

Student responses also revealed significant concerns. While 78.2 % of GenAI-using students agreed that "ChatGPT sometimes makes mistakes," only 31.9 % could provide specific examples of identifying such errors in their own work. Many students expressed concern regarding their own dependence on AI tools. One student stated: "I'm worried that I'm becoming lazy. When I write now, I write one sentence, ask ChatGPT to improve it, write another sentence, ask again. I don't trust my own English anymore." The proposed pedagogical framework. Integration of empirical findings with theoretical literature yielded five foundational principles underpinning the proposed framework. Principle 1: Pedagogy-Driven, Not Technology-Driven. Effective GenAI integration must be guided by clearly articulated learning objectives and pedagogical values. Principle 2: Human-Mediated, Not Automated. GenAI should function as a mediational artifact within a fundamentally humancentered pedagogical relationship. Principle 3: Developmental and ProgressionOriented. GenAI integration should be conceptualized as a developmental trajectory for both teachers and learners. Principle 4: Critical and Reflective. GenAI literacy must encompass operational, critical, and reflective competences. Principle 5: Contextually Responsive. Frameworks must be adaptable to specific institutional, cultural, and infrastructural contexts. Synthesizing empirical findings with theoretical foundations, we propose a four-stage pedagogical framework for GenAI integration in ELT. The framework is conceptualized as developmental and non-linear: individual teachers and institutions may enter at different stages and progress at different rates. Stage 1: Awareness and preparation. Core Question: What is GenAI and what does it mean for my teaching? Primary Focus: Foundational knowledge development, attitude exploration, infrastructure readiness. Teacher Development Objectives: Develop basic operational competence with 2-3 priority GenAI tools; understand key affordances and limitations; articulate personal stance regarding GenAI; identify resources needed for integration. Instructional Applications: Personal experimentation with GenAI tools; critical evaluation of AI-generated content; collaborative exploration with colleagues; development of personal GenAI use policy statement. Stage 2: Scaffolded integration. Core Question: How can GenAI support existing effective practices? Primary Focus: Teacher-guided, highly structured GenAI applications that supplement established instructional approaches. Teacher Development Objectives: Develop proficiency in prompt engineering; design structured GenAI tasks with clear parameters; integrate GenAI-generated materials while maintaining pedagogical coherence; implement basic formative assessment. Instructional Applications: Materials adaptation; assessment preparation; feedback efficiency; demonstration and modeling. Stage 3: Collaborative learning. Core Question: How can GenAI facilitate meaningful interaction and knowledge construction? Primary Focus: Human-AI collaboration as a context for language development and critical thinking. Teacher 225

Development Objectives: Design collaborative tasks involving GenAI as a partner in knowledge construction; facilitate student reflection on human-AI interaction; develop assessment approaches for collaborative products; cultivate student metacognition regarding GenAI use. Instructional Applications: AI-assisted brainstorming and idea development; collaborative revision and editing processes; comparative analysis of human and AI-generated texts; structured debates regarding AI output quality and bias. Stage 4: Innovative application. Core Question: How can GenAI transform what and how we teach? Primary Focus: Creative, student-initiated, and transformative uses of GenAI that redefine learning possibilities. Teacher Development Objectives: Mentor student-initiated GenAI projects; design authentic, real-world communicative tasks enhanced by GenAI; contribute to institutional GenAI policy and curriculum development; engage in scholarly inquiry regarding GenAI pedagogy. Instructional Applications: Student-designed GenAI prompts and workflows; AI-mediated intercultural communication projects; creation of AI-trained conversational agents; critical digital literacy investigations. Conclusion and practical recommendations. This study has developed a comprehensive pedagogical framework for integrating generative artificial intelligence into English language teaching, grounded in theoretical foundations and empirically informed by the perspectives of 47 ELT practitioners and 124 students in Uzbek higher education. The findings reveal a significant gap between GenAI awareness and systematic classroom integration, with only 23.4% of teachers regularly utilizing these tools despite 89.4% awareness. Primary barriers include lack of pedagogical guidance, inadequate infrastructure, limited professional development, and institutional ambivalence. The proposed four-stage framework addresses these gaps by providing a developmental, contextually responsive model that progresses from foundational awareness through scaffolded integration, collaborative learning, and innovative application. The framework is distinguished by five foundational principles: pedagogy-driven rather than technology-driven orientation; human-mediated rather than automated implementation; developmental progression; critical and reflective competence development; and contextual responsiveness. These principles ensure that the framework remains adaptable to diverse institutional contexts while maintaining theoretical coherence and pedagogical integrity. Several limitations of this study should be acknowledged. The sample, while representative of Uzbek higher education institutions, may not generalize to secondary education or other Central Asian contexts. The cross-sectional design captures perceptions at a single point in time during rapid technological evolution. Longitudinal research is needed to examine how GenAI integration practices evolve as technologies and pedagogies develop. Furthermore, the framework requires empirical validation through intervention studies examining its implementation across diverse institutional contexts. 226

Based on the findings, we offer the following practical recommendations. First, higher education institutions should develop clear, constructive GenAI policies that move beyond prohibition toward pedagogical integration. These policies should address acceptable use, transparency requirements, academic integrity, and data privacy while providing concrete guidance for diverse disciplinary contexts. Second, teacher education programs must integrate GenAI pedagogy into both pre-service and in-service professional development. Training should address not only operational competence but also prompt engineering, critical evaluation of AI outputs, ethical considerations, and task design for GenAImediated learning. Third, curriculum developers should revise English language programs to incorporate GenAI literacy as an explicit learning outcome. Students require systematic instruction in effective, ethical, and critical GenAI use. Fourth, infrastructure development must ensure reliable internet connectivity and device access, particularly in regional institutions. Fifth, further research should examine the longitudinal effects of GenAI integration on language learning outcomes, the development of valid assessment approaches for GenAI-mediated work, and the comparative effectiveness of different integration models across diverse educational contexts. The integration of generative AI into English language teaching represents not merely a technological innovation but a fundamental transformation of the pedagogical landscape. The framework proposed in this study offers a theoretically grounded, empirically informed, and contextually responsive pathway for navigating this transformation. By reconceptualizing GenAI as a mediational artifact within human-centered pedagogical relationships, the framework affirms the irreplaceable role of the teacher while harnessing GenAI's transformative potential to enhance language learning opportunities for all students. References 1. Warschauer, M., & Xu, Y. (2023). AI and language education: An emerging research agenda. Annual Review of Applied Linguistics, 43, 1-13. https://doi.org/10.1017/S0267190523000025 2. UNESCO. (2023). Guidance for generative AI in education and research. United Nations Educational, Scientific and Cultural Organization. https://unesdoc.unesco.org/ark:/48223/pf0000386693 3. Karimov, R.A., & Soliyev, I.I. (2024). Oliy ta'limda sun'iy intellekt texnologiyalaridan foydalanish istiqbollari. Pedagogik mahorat, 5(1), 112-120. 4. Moorhouse, B.L. (2024). Beginning and first-year language teachers' perceptions of generative artificial intelligence in education. RELC Journal, 55(1), 115. https://doi.org/10.1177/00336882241245678 5. Tursunov, M.T., & Jo‘rayeva, N.X. (2023). Ingliz tili darslarida raqamli texnologiyalardan foydalanish samaradorligi. Xorijiy filologiya, 4(85), 67-74. SUN’IY INTELLEKT ASOSIDA SHAXSGA YO‘NALTIRILGAN TA’LIMNI TASHKIL ETISHNING IJTIMOIY AHAMIYATI Isomiddinov Ma’rufjon Umid o‘g‘li, QarDTU “Axborot tizimlari va texnologiyalari” kafedrasi assistent o‘qituvchisi, marufjonisomiddinov@gmail.com Jumayev Yahyo Yoqub o‘g‘li, QarDTU 3-bosqich talabasi, jumayev0121@gmail.com 227

Annotatsiya. Mazkur maqolada sun’iy intellekt texnologiyalari asosida shaxsga yo‘naltirilgan ta’limni tashkil etish masalalari hamda uning ijtimoiy ahamiyati tahlil qilinadi. Ta’lim jarayonida sun’iy intellektdan foydalanish o‘quvchilarning individual ehtiyojlari, qobiliyatlari va o‘rganish sur’atlarini inobatga olgan holda ta’lim sifatini oshirish imkonini beradi. Shuningdek, mazkur yondashuvning ijtimoiy tenglikni ta’minlash, inson kapitalini rivojlantirish va jamiyatning raqamli transformatsiyasiga ta’siri yoritib beriladi. Kalit so‘zlar: sun’iy intellekt, shaxsga yo‘naltirilgan ta’lim, raqamli pedagogika, ijtimoiy rivojlanish, ta’lim innovatsiyalari. Аннотация. В данной статье анализируются вопросы организации личностноориентированного образования на основе технологий искусственного интеллекта и его социальная значимость. Использование искусственного интеллекта в образовательном процессе позволяет повысить качество обучения с учётом индивидуальных потребностей, способностей и темпов усвоения знаний учащихся. Также освещается влияние данного подхода на обеспечение социальной справедливости, развитие человеческого капитала и цифровую трансформацию общества. Ключевые слова: искусственный интеллект, личностно-ориентированное образование, цифровая педагогика, социальное развитие, образовательные инновации. Abstract. This article analyzes the issues of organizing person-centered education based on artificial intelligence technologies and its social significance. The use of artificial intelligence in the educational process makes it possible to improve the quality of education by considering students’ individual needs, abilities, and learning pace. The study also highlights the impact of this approach on ensuring social equity, developing human capital, and supporting the digital transformation of society. Keywords: artificial intelligence, person-centered education, digital pedagogy, social development, educational innovations. Kirish. Zamonaviy jamiyatning raqamli transformatsiyasi sharoitida ta’lim tizimi tub tarkibiy va mazmuniy o‘zgarishlarni boshdan kechirmoqda. Ayniqsa, sun’iy intellekt (SI) texnologiyalarining jadal rivojlanishi ta’lim jarayonini tashkil etish, boshqarish va baholash mexanizmlarini takomillashtirishda muhim omilga aylanmoqda [UNESCO, 2021, 63-b.]. An’anaviy ta’lim modellari o‘quvchilarning individual ehtiyojlari va qobiliyatlarini to‘liq qamrab ololmagan bo‘lsa, bugungi kunda shaxsga yo‘naltirilgan ta’lim konsepsiyasi pedagogik faoliyatning ustuvor yo‘nalishlaridan biri sifatida qaralmoqda. Shaxsga yo‘naltirilgan ta’lim o‘quvchining bilim darajasi, o‘rganish sur’ati, qiziqishlari va psixologik xususiyatlarini inobatga olgan holda ta’lim jarayonini tashkil etishni nazarda tutadi. Ushbu yondashuvni samarali amalga oshirishda sun’iy intellekt asosidagi adaptiv o‘quv tizimlari, intellektual tutorlar va ma’lumotlarga asoslangan tahliliy mexanizmlar muhim ahamiyat kasb etmoqda [World Bank, 2020, 58-b.]. SI texnologiyalari yordamida o‘quvchilarning ta’limiy faoliyati real vaqt rejimida tahlil qilinib, individual ta’lim trayektoriyalarini shakllantirish imkoniyati yuzaga keladi. Bundan tashqari, sun’iy intellekt asosida shaxsga yo‘naltirilgan ta’limni joriy etish nafaqat pedagogik, balki ijtimoiy ahamiyatga ham ega. Ushbu yondashuv ta’limda teng imkoniyatlarni ta’minlash, inson kapitalini rivojlantirish hamda jamiyatning raqamli iqtisodiyot sharoitiga moslashuvchanligini oshirishga xizmat qiladi. Shu bois, sun’iy intellekt asosida shaxsga yo‘naltirilgan ta’limni 228

tashkil etish masalalarini ilmiy jihatdan tahlil qilish va uning ijtimoiy ahamiyatini ochib berish dolzarb ilmiy vazifalardan biri hisoblanadi. Adabyotlar tahlili. Xalqaro tadqiqotlarda sun’iy intellekt texnologiyalarining ta’lim jarayoniga integratsiyasi o‘quvchilarning individual xususiyatlarini inobatga olish orqali ta’lim samaradorligini oshirishi ilmiy jihatdan asoslab berilgan. UNESCO (2021) hisobotida SI texnologiyalari ta’lim tizimini moslashuvchan, inklyuziv va shaxs ehtiyojlariga yo‘naltirilgan holga keltirish imkonini berishi ta’kidlangan. Shu bilan birga, mazkur jarayonda axloqiy me’yorlar va ma’lumotlar xavfsizligi masalalariga alohida e’tibor qaratish zarurligi qayd etilgan. World Bank (2020) tadqiqotlariga ko‘ra, sun’iy intellekt asosidagi adaptiv o‘quv tizimlari o‘quvchilarning bilim darajasini real vaqt rejimida aniqlash va o‘quv materiallarini shaxsiylashtirish imkonini beradi. Natijada o‘zlashtirish darajasi oshadi va ta’lim jarayonidagi tafovutlar kamayadi. Bu esa ta’limda teng imkoniyatlarni ta’minlashga xizmat qiladi. Selwyn (2022) tomonidan olib borilgan ilmiy tahlillar shuni ko‘rsatadiki, raqamli texnologiyalarni ta’limga joriy etish nafaqat texnologik, balki ijtimoiy jarayon hamdir. Muallif sun’iy intellektdan foydalanishda pedagogning roli saqlanib qolishini, texnologiya esa yordamchi vosita sifatida xizmat qilishi lozimligini ta’kidlaydi. European Commission (2022) hujjatlarida esa SI asosidagi ta’lim tizimlarida shaffoflik, adolatlilik va ma’lumotlarni himoya qilish tamoyillari ustuvor yo‘nalish sifatida belgilangan. Bu esa sun’iy intellektdan foydalanishning ijtimoiy mas’uliyatini ko‘rsatadi. Mahalliy olimlar tadqiqotlarida ham shaxsga yo‘naltirilgan ta’lim va raqamli pedagogika masalalari keng yoritilgan. Abduqodirov va Begimqulov (2021) sun’iy intellekt texnologiyalari o‘quvchilarning mustaqil fikrlashini rivojlantirish va ta’lim jarayonini individuallashtirishda muhim vosita ekanini ta’kidlaydi. Xudoyberdiyev (2021) esa ta’limni raqamlashtirish jarayonida infratuzilma va pedagogik tayyorgarlik masalalari hal qilinishi lozimligini ko‘rsatadi. Jo‘rayev va To‘xtasinov (2022) tadqiqotlarida innovatsion texnologiyalarning ta’limning ijtimoiy funksiyalariga ta’siri tahlil qilinib, raqamli ta’lim jamiyatning intellektual salohiyatini oshirishga xizmat qilishi asoslab berilgan. Umuman olganda, adabiyotlar tahlili natijalari shuni ko‘rsatadiki, sun’iy intellekt asosida shaxsga yo‘naltirilgan ta’lim: ➢ ta’lim sifatini oshiradi; ➢ o‘quvchilarning individual rivojlanishini ta’minlaydi; ➢ ta’limda ijtimoiy tenglikni kuchaytiradi; ➢ inson kapitalining rivojlanishiga xizmat qiladi; ➢ raqamli jamiyat talablariga mos kadrlar tayyorlash imkonini beradi. Shu bilan birga, aksariyat manbalarda sun’iy intellektni ta’limga joriy etishda texnik infratuzilma, pedagoglarning raqamli kompetensiyalari va axborot 229

xavfsizligi bilan bog‘liq muammolar mavjudligi ham qayd etilgan. Bu esa mazkur yo‘nalishda kompleks yondashuv zarurligini ko‘rsatadi. Sun’iy intellekt va shaxsga yo‘naltirilgan ta’lim tushunchasi. Shaxsga yo‘naltirilgan ta’lim ta’lim jarayonini o‘quvchining individual psixologik xususiyatlari, bilim darajasi, qiziqishlari hamda o‘rganish sur’atlarini inobatga olgan holda tashkil etishga qaratilgan zamonaviy pedagogik yondashuv hisoblanadi. Ushbu yondashuv o‘quvchining faolligi va mustaqilligini oshirish, ta’lim jarayonida subyekt sifatida shakllanishini ta’minlashga xizmat qiladi [Selwyn N., 2022, 41-b.]. Sun’iy intellekt texnologiyalari shaxsga yo‘naltirilgan ta’limni amalga oshirishda muhim texnologik asos bo‘lib, o‘quvchilarning ta’limiy faoliyatini doimiy monitoring qilish, ularning bilim darajasini tahlil etish va individual ta’lim trayektoriyalarini shakllantirish imkonini beradi [World Bank, 2020, 58-b.]. SI asosidagi tizimlar katta hajmdagi ma’lumotlarni qayta ishlash orqali o‘quvchilarning kuchli va zaif tomonlarini aniqlaydi hamda moslashtirilgan o‘quv kontentini taklif etadi. Bugungi kunda adaptiv o‘quv platformalari, intellektual tutor tizimlari, avtomatlashtirilgan baholash va tavsiyalar beruvchi algoritmlar shaxsga yo‘naltirilgan ta’limning muhim vositalari sifatida keng qo‘llanilmoqda. Mazkur texnologiyalar o‘quvchilarning bilimlarni o‘zlashtirish darajasini oshirish bilan birga, pedagoglarning yuklamasini kamaytirishga ham xizmat qiladi. Sun’iy intellekt asosida shaxsga yo‘naltirilgan ta’limning ijtimoiy ahamiyati. Sun’iy intellekt asosida tashkil etilgan shaxsga yo‘naltirilgan ta’lim ta’lim tizimining ijtimoiy funksiyalarini kuchaytiradi. Avvalo, mazkur yondashuv ta’limda teng imkoniyatlarni ta’minlashga xizmat qiladi. Raqamli texnologiyalar yordamida chekka hududlarda yashovchi yoki ijtimoiy himoyaga muhtoj qatlam vakillari ham sifatli ta’lim resurslaridan foydalanish imkoniyatiga ega bo‘ladi [European Commission, 2022, 27-b.]. Ikkinchidan, shaxsga yo‘naltirilgan ta’lim inson kapitalining rivojlanishiga ijobiy ta’sir ko‘rsatadi. O‘quvchilarning individual qobiliyatlarini aniqlash va rivojlantirish orqali jamiyatda yuqori malakali, raqobatbardosh va innovatsion fikrlovchi kadrlar shakllanadi. Bu esa iqtisodiy taraqqiyot va ijtimoiy barqarorlikni ta’minlashda muhim omil hisoblanadi [Karimov I.A., Mirziyoyev Sh.M., 2022, 112-b.]. Uchinchidan, sun’iy intellekt asosidagi ta’lim tizimlari umrbod ta’lim konsepsiyasini qo‘llab-quvvatlaydi. Zamonaviy mehnat bozori sharoitida kasbiy bilim va ko‘nikmalarni doimiy yangilab borish zarur bo‘lib, SI texnologiyalari shaxsiy ehtiyojlarga mos ta’lim dasturlarini taklif etish orqali ushbu jarayonni samarali tashkil etishga imkon yaratadi [Abduqodirov A.A., Begimqulov U.Sh., 2021, 94-b.]. Sun’iy intellektni ta’lim jarayoniga joriy etishda qator muammolar va cheklovlar mavjud. Jumladan, raqamli infratuzilmaning yetarli darajada rivojlanmaganligi, ta’lim muassasalarining texnik bazasi va internet tarmog‘iga 230

ulanish imkoniyatlaridagi farqlar muhim to‘siqlardan biri hisoblanadi [Xudoyberdiyev B.X., 2021, 47-b.]. Bundan tashqari, pedagog kadrlarning raqamli va axborot-kommunikatsiya kompetensiyalarining yetarli emasligi sun’iy intellekt texnologiyalaridan samarali foydalanishga salbiy ta’sir ko‘rsatmoqda. Shuningdek, o‘quvchilarning shaxsiy ma’lumotlarini himoya qilish, axborot xavfsizligini ta’minlash va sun’iy intellekt algoritmlarining shaffofligi bilan bog‘liq masalalar ham dolzarb muammolar sirasiga kiradi [Jo‘rayev R.H., To‘xtasinov D.S., 2022, 21-b.]. Mazkur muammolarni bartaraf etish uchun davlat siyosati doirasida raqamli ta’lim infratuzilmasini rivojlantirish, pedagoglarni qayta tayyorlash va sun’iy intellektdan foydalanish bo‘yicha normativ-huquqiy asoslarni takomillashtirish zarur. Xulosa. Xulosa qilib aytganda, sun’iy intellekt asosida shaxsga yo‘naltirilgan ta’limni tashkil etish zamonaviy ta’lim tizimining samaradorligini oshirish bilan birga, uning ijtimoiy ahamiyatini ham kuchaytiradi. Ushbu yondashuv o‘quvchilarning individual ehtiyojlari, qobiliyatlari va o‘rganish sur’atlarini inobatga olgan holda ta’lim jarayonini tashkil etish imkonini berib, ta’lim sifatining oshishiga xizmat qiladi. Sun’iy intellekt texnologiyalaridan foydalanish orqali ta’limda teng imkoniyatlarni ta’minlash, ijtimoiy adolatni qaror toptirish va inson kapitalini rivojlantirish uchun qulay sharoit yaratiladi. Shaxsga yo‘naltirilgan ta’lim modeli jamiyatda mustaqil fikrlaydigan, innovatsion salohiyatga ega va raqamli muhitga moslashuvchan kadrlarni shakllantirishga zamin yaratadi. Shu bilan birga, sun’iy intellekt asosidagi ta’lim tizimlarini joriy etishda mavjud muammolarni bartaraf etish, xususan raqamli infratuzilmani rivojlantirish, pedagoglarning raqamli kompetensiyalarini oshirish hamda axborot xavfsizligini ta’minlash muhim ahamiyat kasb etadi. Kelajakda sun’iy intellekt texnologiyalaridan maqsadli va tizimli foydalanish ta’lim tizimini yanada takomillashtirish, raqamli jamiyatni shakllantirish hamda barqaror ijtimoiy taraqqiyotga erishishda muhim omil bo‘lib xizmat qiladi. Foydalanilgan adabiyotlar: 1. UNESCO. Artificial Intelligence and Education: Guidance for Policy-makers. Paris: UNESCO Publishing, 2021. 2. World Bank. Artificial Intelligence in Education: Transforming Learning for All. Washington, DC: World Bank Publications, 2020. 3. Selwyn N. Education and Technology: Key Issues and Debates. London: Bloomsbury Academic, 2022. 4. European Commission. Ethical Guidelines on the Use of Artificial Intelligence and Data in Education and Training. Brussels, 2022. 5. Karimov I.A., Mirziyoyev Sh.M. Yangi O‘zbekiston taraqqiyot strategiyasi. Toshkent: O‘zbekiston, 2022. 6. Abduqodirov A.A., Begimqulov U.Sh. Raqamli pedagogika va ta’limda sun’iy intellekt texnologiyalari. – Toshkent: Fan va texnologiya, 2021. 7. Xudoyberdiyev B.X. Ta’lim jarayonini raqamlashtirish va shaxsga yo‘naltirilgan yondashuv masalalari // Pedagogika va psixologiya. – Toshkent, 2021. – №4. – B. 45–49. 231

8. Jo‘rayev R.H., To‘xtasinov D.S. Zamonaviy ta’limda innovatsion texnologiyalar va ularning ijtimoiy ahamiyati // Ta’lim va innovatsiyalar. – Toshkent, 2022. – №2. – B. 18–23. INGLIZ TILINI SUN‘IY INTELLEKT ORQALI O‘QITISHNING DOLZARB MUAMMOLARI VA YECHIMLARI Jaloliddinova Nigora Jamoliddin qizi, NamDCHTI talabasi jaloliddinovan18@gmail.com Annotatsiya. Ushbu maqolada ingliz tilini sun‘iy intellekt (SI) texnologiyalari yordamida o‘qitishning zamonaviy muammolari va ularni hal etish yo‘llari tahlil qilinadi. Tadqiqotda SI asosidagi til o‘qitish platformalarining imkoniyatlari va kamchiliklari, ChatGPT, Duolingo AI, Grammarly kabi vositalarning pedagogik samaradorligi, adaptiv o‘qitish tizimlarining afzalliklari hamda o‘qituvchi-texnologiya munosabatlarining dolzarb jihatlari ko‘rib chiqilgan. Maqolada O‘zbekiston kontekstida ingliz tilini SI orqali o‘qitishning muammo va istiqbollari alohida yoritilgan. Kalit so‘zlar: sun‘iy intellekt, ingliz tili, til o‘qitish, ChatGPT, adaptiv ta‘lim, NLP, Duolingo, Grammarly, raqamli pedagogika, CALL. Аннотация. В данной статье анализируются современные проблемы обучения английскому языку с помощью технологий искусственного интеллекта (ИИ) и пути их решения. В исследовании рассматриваются возможности и недостатки платформ обучения языку на основе ИИ, педагогическая эффективность таких инструментов, как ChatGPT, Duolingo AI, Grammarly, преимущества адаптивных систем обучения, а также актуальные аспекты отношений учитель-технология. В статье отдельно освещены проблемы и перспективы обучения английскому языку с помощью ИИ в контексте Узбекистана. Ключевые слова: искусственный интеллект, английский язык, обучение языкам, ChatGPT, адаптивное обучение, NLP, Duolingo, Grammarly, цифровая педагогика, CALL. Abstract. This article analyzes the current problems and solutions of teaching English using artificial intelligence (AI) technologies. The study examines the capabilities and limitations of AI-based language learning platforms, the pedagogical effectiveness of tools such as ChatGPT, Duolingo AI, and Grammarly, the advantages of adaptive learning systems, and the pressing aspects of teacher-technology relationships. The article specifically highlights the problems and prospects of teaching English through AI in the context of Uzbekistan. Keywords: artificial intelligence, English language, language teaching, ChatGPT, adaptive learning, NLP, Duolingo, Grammarly, digital pedagogy, CALL. Kirish. XXI asrda ingliz tili global kommunikatsiya, fan, texnologiya va biznesning asosiy vositasiga aylangan. Dunyo bo‘ylab 1,5 milliarddan ortiq kishi ingliz tilini ikkinchi yoki chet tili sifatida o‘rganmoqda. Bunday ulkan talabni qondirish uchun an‘anaviy o‘qitish usullari yetarli bo‘lmay qolmoqda va sun‘iy intellekt texnologiyalari bu borada inqilobiy o‘zgarishlar yasash imkoniyatiga ega. Sun‘iy intellektning til o‘qitishga tatbiqi yangi hodisa emas – ComputerAssisted Language Learning (CALL) kontseptsiyasi 1960-yillardan beri rivojlanib kelmoqda. Biroq so‘nggi yillarda katta til modellari (LLM), generativ SI va tabiiy tilni qayta ishlash (NLP) texnologiyalarining rivojlanishi bu sohada sifat jihatidan yangi bosqichni boshlab berdi. ChatGPT, Google Bard, Claude kabi modellarning paydo bo‘lishi ingliz tilini o‘qitish paradigmasini tubdan o‘zgartirmoqda. 232

O‘zbekistonda ingliz tilini o‘qitish davlat siyosatining ustuvor yo‘nalishlaridan biri hisoblanadi. Prezidentning 2012-yil 10-dekabrdagi “Chet tillarni o‘rganish tizimini yanada takomillashtirish chora-tadbirlari to‘g‘risida”gi PQ-1875-son Qarori hamda keyingi normativ hujjatlar bu yo‘nalishda muhim qadam bo‘ldi. Biroq amaliyotda ingliz tili o‘qitish sifati hali kutilgan darajaga yetmagan bo‘lib, SI texnologiyalarining samarali integratsiyasi bu muammoni hal etishning muhim omillaridan biri sifatida ko‘rilmoqda. Tadqiqotning maqsadi – ingliz tilini SI texnologiyalari orqali o‘qitishda mavjud muammolarni tizimli tahlil qilish va ularning ilmiy asoslangan yechim yo‘llarini ishlab chiqishdir. Adabiyotlar tahlili va metodologiya. SI texnologiyalarining ingliz tili ta‘limiga tatbiqi bo‘yicha xalqaro ilmiy adabiyotlarda keng ko‘lamli tadqiqotlar mavjud. S. Pokrivcakova (2019) CALL dan AI-ga o‘tish jarayonlarini, X. Zhai va boshqalar (2021) SI asosidagi til o‘qitish vositalarining meta-tahlilini, B. Zou va M. Thomas (2023) esa generativ SI ning ikkinchi til egallashiga ta‘sirini o‘rgangan. R. Godwin-Jones (2022) adaptiv til o‘qitish texnologiyalarining rivojlanish tendentsiyalarini, W. Grabe va F. Stoller (2020) esa o‘qish ko‘nikmalarini rivojlantirishda SI texnologiyalarining samaradorligini tadqiq qilgan. O‘zbekistonda bu yo‘nalishda D. Irgasheva (2023), M. Askarova (2022) va S. Rashidov (2024) kabi olimlar tomonidan tadqiqotlar olib borilgan. Biroq ushbu ishlar ko‘proq umumiy tavsifga ega bo‘lib, SI vositalarining konkret pedagogik samaradorligini o‘lchashga qaratilgan empirik tadqiqotlar yetishmasligi kuzatiladi. Tadqiqotda aralash metodologiya (mixed methods) qo‘llanildi. Miqdoriy ma‘lumotlar 2024-yilda O‘zbekistonning 8 ta oliy ta‘lim muassasasida 250 nafar ingliz tili talabalari va 45 nafar o‘qituvchi o‘rtasida o‘tkazilgan so‘rovnoma orqali to‘plandi. Sifatiy ma‘lumotlar esa 15 nafar o‘qituvchi bilan o‘tkazilgan yarim tuzilmali intervyular orqali olindi. Bundan tashqari, ChatGPT-4, Duolingo Max, Grammarly Premium, Elsa Speak va Speechling platformalari sinov usulida baholandi. Asosiy muammolar tahlili. Pedagogik-metodologik muammolar. SI asosidagi til o‘qitish vositalarining asosiy muammosi – ular ko‘pincha kommunikativ kompetensiyani emas, balki alohida til ko‘nikmalarini rivojlantirishga qaratilgan. Masalan, Grammarly grammatik xatolarni tuzatishda yuqori samaradorlik ko‘rsatsa-da, u talabaning kommunikativ niyatini, kontekstual mosligini va pragmatik kompetensiyasini hisobga olmaydi. Tadqiqot natijalari shuni ko‘rsatdiki, SI vositalari yordamida yozuv ko‘nikmalarini rivojlantirgan talabalarning 67 foizi grammatik aniqlikda yaxshilanishni ko‘rsatgan, ammo faqat 31 foizi kommunikativ samaradorlikda sezilarli o‘sish qayd etgan. ChatGPT kabi generativ modellar bilan suhbat mashqlari ham muammosiz emas. Tadqiqotda qatnashgan o‘qituvchilarning 73 foizi ChatGPT ning talaba xatolarini haddan tashqari “kechiruvchanligi” va xatolarni izchil tuzatmasligini 233

ta‘kidlagan. Bu esa fossilizatsiya – xatolarning mustahkamlanib qolishi – xavfini oshiradi. Shuningdek, SI vositalari madaniyatlararo kompetensiyani rivojlantirishda cheklangan imkoniyatlarga ega. Til o‘qitish nafaqat grammatika va lug‘at, balki madaniy kontekst, ijtimoiy normalar va pragmatik qoidalarni ham o‘z ichiga oladi. Hozirgi SI tizimlari bu jihatlarni to‘liq qamrab ololmaydi. Texnologik muammolar. NLP texnologiyalari ingliz tili uchun boshqa tillarga nisbatan ancha rivojlangan bo‘lsa-da, bir qator jiddiy kamchiliklar mavjud. Birinchidan, nutqni tanish (speech recognition) tizimlari turli aksent va dialektlar bilan ishlashda qiyinchiliklarga duch keladi. Tadqiqotda sinov o‘tkazilgan platformalarning o‘zbek aksenti bilan ingliz tilida gaplashganda nutqni tanish aniqligi o‘rtacha 62 foizni tashkil etgan, holbuki ona tilida (ingliz) gapiruvchilar uchun bu ko‘rsatkich 94 foizdan oshgan. Ikkinchidan, SI modellarining “gallyutsinatsiya” muammosi mavjud. ChatGPT va shunga o‘xshash modellar ba‘zan noto‘g‘ri grammatik tushuntirish berishi, mavjud bo‘lmagan qoidalarni “o‘ylab topishi” yoki noaniq ma‘lumotlarni ishonchli tarzda taqdim etishi mumkin. So‘rovnomada talabalarning 41 foizi SI dan olgan grammatik tushuntirishlarning ba‘zilari darslikdagi ma‘lumotlarga zid kelganini qayd etgan. Uchinchidan, real vaqtda nutqiy interaksiya sifati hali ham yetarli darajada tabiiy emas. SI bilan suhbat mashqlari haqiqiy inson bilan muloqotni to‘liq almashtira olmaydi, chunki SI modellarida emotsional intellekt, noverbal signallarni anglash va spontan munosabat bildirish qobiliyati cheklangan. Psixologik va ijtimoiy muammolar. Tadqiqot natijalari SI bilan til o‘qitishning ba‘zi psixologik muammolarini ham aniqladi. Talabalarning 56 foizi SI vositalari bilan ishlashda motivatsiya pasayishini qayd etgan, chunki inson o‘qituvchidagi emotsional qo‘llab-quvvatlash, rag‘batlantirish va individual e‘tibor yetishmaydi. Bundan tashqari, SI ga haddan tashqari bog‘lanish xavfi mavjud – talabalarning 38 foizi SI vositalarisiz mustaqil yozish yoki gapirish qobiliyatiga ishonch yo‘qotganini bildirgan. Akademik halollik masalasi ham jiddiy tashvish uyg‘otmoqda. O‘qituvchilarning 82 foizi talabalar ChatGPT yordamida yozma topshiriqlarni bajarganligi hollari bilan to‘qnashganini ta‘kidlagan. Bu esa baholash tizimining ishonchliligiga putur yetkazadi va talabalarning haqiqiy til kompetensiyasini aniqlashni qiyinlashtiradi. Infratuzilma va resurs muammolari (O‘zbekiston kontekstida). O‘zbekistonda SI asosidagi ingliz tili o‘qitish platformalaridan foydalanishda bir qator qo‘shimcha muammolar mavjud. Premium SI vositalari (ChatGPT Plus, Duolingo Max, Grammarly Premium) pullik bo‘lib, ularning narxi ko‘pchilik o‘zbek talabalari uchun yuqori hisoblanadi. So‘rovnomada talabalarning faqat 12 foizi premium SI xizmatlariga obuna bo‘lganligini bildirgan. Bundan tashqari, o‘qituvchilarning SI savodxonligi darajasi past bo‘lib qolmoqda. Intervyu natijalariga ko‘ra, o‘qituvchilarning faqat 22 foizi SI 234

vositalarini dars jarayoniga tizimli ravishda integratsiya qilgan. Qolgan 78 foiz esa yetarli bilim va ko‘nikmaga ega emasligini yoki muassasa tomonidan texnik qo‘llab-quvvatlash yo‘qligini sabab sifatida ko‘rsatgan. 1-jadval 100 ballik shkala asosida ekspert baholash natijalari (*faqat mavjud ko‘nikmalar bo‘yicha) SI platformalarining ingliz tili o‘qitishdagi samaradorlik ko‘rsatkichlari Platforma Grammatika Tinglab tushunish Gapirish Yozish Umumiy ball ChatGPT-4 82 45 68 88 70,8 Duolingo Max 75 72 65 58 67,5 Grammarly 94 N/A N/A 91 92,5* Elsa Speak 40 60 85 N/A 61,7* Speechling 35 78 80 N/A 64,3* 2-jadval So‘rovnoma natijalari (n=250 talaba, n=45 o‘qituvchi, 2024-yil) O‘zbekistonda ingliz tili o‘qitishda SI dan foydalanish holati Talabalar O‘qituvchilar SI vositalaridan muntazam foydalanadi 64% 22% Premium SI xizmatlariga obuna 12% 9% SI dars jarayonida samarali deb hisoblaydi 78% 58% SI o‘qituvchini almashtira oladi deb o‘ylaydi 18% 4% SI savodxonligi bo‘yicha o‘qishga muhtoj 67% 78% SI tufayli akademik halollik buzilgan N/A 82% Ko‘rsatkich Yechim yo‘llari va takliflar. “Aralash o‘qitish” (Blended Learning) modelini qo‘llash zarur. Bu modelda SI vositalari o‘qituvchini almashtirishga emas, balki uning faoliyatini kuchaytirishga xizmat qiladi. Xususan, SI grammatika, lug‘at va tinglab tushunish mashqlarini avtomatlashtirishga, o‘qituvchi esa kommunikativ kompetensiya, madaniyatlararo muloqot va tanqidiy fikrlash ko‘nikmalarini rivojlantirishga e‘tibor qaratishi maqsadga muvofiq. SI vositalaridan foydalanishning aniq pedagogik protokollarini ishlab chiqish kerak. Har bir SI vositasi qaysi til ko‘nikmasini rivojlantirishga mo‘ljallanganligi, qanday darajadagi talabalar uchun mos ekanligi va qaysi bosqichda qo‘llanilishi aniq belgilanishi lozim. Masalan, Grammarly yozuv ko‘nikmalarini rivojlantirishda, Elsa Speak talaffuz mashqlarida, ChatGPT esa erkin suhbat va kreativ yozuv mashqlarida qo‘llanilishi mumkin. SI asosidagi baholash tizimini an‘anaviy baholash bilan uyg‘unlashtirish zarur. SI avtomatik baholash bilan bir qatorda, o‘qituvchi tomonidan individual 235

portfolio baholash, loyiha asosidagi baholash va og‘zaki suhbat usullarini ham qo‘llash tavsiya etiladi. Ingliz tilini o‘qitish uchun maxsus “o‘zbek kontekstiga moslashtirilgan” SI vositasini ishlab chiqish zarur. Bu vosita o‘zbek tilidan ingliz tiliga interferensiya (ona tili ta‘siri) muammolarini hisobga olgan holda ishlashi, o‘zbek aksenti bilan nutqni taniy olishi va mahalliy madaniy kontekstga mos misollar bilan ishlashi lozim. Nutqni tanish texnologiyalarini aksent-adaptiv tarzda takomillashtirish kerak. Buning uchun o‘zbek aksenti bilan ingliz tilida gapirgan nutq namunalarining katta hajmdagi ma‘lumotlar bazasini yaratish va mavjud ASR (Automatic Speech Recognition) modellarini shu asosda qayta o‘qitish (finetuning) zarur. SI ning “gallyutsinatsiya” muammosini kamaytirish uchun RAG (RetrievalAugmented Generation) texnologiyasidan foydalanish maqsadga muvofiq. Bu yondashuv SI modeliga ishonchli til o‘qitish manbalari (grammatika ma‘lumotnomalar, lug‘atlar, CEFR standartlari) ga real vaqtda murojaat qilish imkonini beradi va noto‘g‘ri ma‘lumot berish xavfini kamaytiradi. Oliy ta‘lim muassasalarida “SI va til ta‘limi” bo‘yicha maxsus siyosat hujjati qabul qilinishi zarur. Bu hujjat SI vositalaridan foydalanish qoidalari, akademik halollik me’yorlari, o‘qituvchilarning SI savodxonligi talablari va texnik infratuzilma standartlarini o‘z ichiga olishi lozim. O‘qituvchilar uchun tizimli malaka oshirish dasturi tashkil etilishi kerak. Bu dastur SI texnologiyalarining asosiy tushunchalari va ishlash printsiplari, konkret SI vositalarini dars jarayoniga integratsiya qilish usullari, SI yordamida o‘quv materiallarini yaratish ko‘nikmalari, SI asosidagi baholash vositalarini samarali qo‘llash hamda akademik halollik va SI etikasi masalalarini qamrab olishi zarur. Ingliz tili o‘qitish uchun SI vositalariga kirish imkoniyatlarini kengaytirish lozim. Buning uchun davlat-xususiy sektor hamkorligi orqali premium SI platformalariga subsidiyalangan kirish dasturlarini yo‘lga qo‘yish, ochiq manbali (open-source) SI vositalarini rivojlantirish va universitetlarda SI laboratoriyalarini tashkil etish tavsiya etiladi. Xulosa. Tadqiqot natijalari shuni ko‘rsatdiki, sun‘iy intellekt texnologiyalari ingliz tili o‘qitishda katta salohiyatga ega, biroq ularning samarali qo‘llanilishi bir qator jiddiy muammolarni hal etishni talab qiladi. Asosiy muammolar pedagogikmetodologik (kommunikativ kompetensiya yetishmasligi, fossilizatsiya xavfi), texnologik (nutqni tanishda aksent muammosi, gallyutsinatsiya), psixologik (motivatsiya pasayishi, SI ga bog‘liqlik) va infratuzilmaviy (narx, savodxonlik, texnik ta‘minot) xarakterga ega. Tadqiqot asosida quyidagi asosiy xulosalar shakllantildi: birinchidan, SI o‘qituvchini almashtiruvchi emas, balki uning faoliyatini kuchaytirvchi vosita sifatida ko‘rilishi lozim; ikkinchidan, har bir SI vositasining pedagogik maqsadi aniq belgilanishi va til ko‘nikmalariga moslab qo‘llanilishi zarur; uchinchidan, 236

O‘zbekiston kontekstida mahalliy ehtiyojlarga moslashtirilgan SI yechimlarini ishlab chiqish ustuvor vazifa hisoblanadi. Kelgusida tadqiqot natijalarini kengaytirish maqsadida quyidagi yo‘nalishlar istiqbolli hisoblanadi: SI asosidagi ingliz tili o‘qitish platformasining O‘zbekiston sharoitiga moslashtirilgan prototipini yaratish, longitudinal tadqiqot orqali SI vositalarining uzoq muddatli ta‘sirini o‘rganish hamda SI va o‘qituvchi hamkorligining optimal modelini ishlab chiqish. Foydalanilgan adabiyotlar: 1. O‘zbekiston Respublikasi Prezidentining 2012-yil 10-dekabrdagi PQ-1875-son Qarori “Chet tillarni o‘rganish tizimini yanada takomillashtirish chora-tadbirlari to‘g‘risida”. 2. Askarova M. Ingliz tilini o‘qitishda axborot texnologiyalarining o‘rni. // Filologiya masalalari. – 2022. – №3. – B. 78–85. 3. Irgasheva D. Raqamli ta‘lim muhitida chet til kompetensiyasini shakllantirish. – Toshkent: Fan, 2023. – 210 b. 4. Rashidov S. Sun‘iy intellekt va ingliz tili ta‘limi: muammo va yechimlar. // Ta‘lim va innovatsiya. – 2024. – №1. – B. 112–120. 5. Godwin-Jones R. Evolving technologies for language learning. // Language Learning & Technology. – 2022. – Vol. 26(3). – P. 1–18. 6. Grabe W., Stoller F. Teaching and Researching Reading. 3rd ed. – London: Routledge, 2020. – 420 p. 7. Pokrivcakova S. Preparing teachers for the application of AI-powered technologies in foreign language education. // Journal of Language and Cultural Education. – 2019. – Vol. 7(3). – P. 135–153. 8. Zhai X. et al. A Review of Artificial Intelligence (AI) in Education from 2010 to 2020. // Complexity. – 2021. – Article ID 8812542. 9. Zou B., Thomas M. Generative AI and Second Language Learning. – Cambridge: CUP, 2023. – 290 p. 10. Kohnke L., Moorhouse B., Zou D. ChatGPT for Language Teaching and Learning. // RELC Journal. – 2023. – Vol. 54(2). – P. 537–550. 11. Yan D. Impact of ChatGPT on learners in a L2 writing practicum. // Education and Information Technologies. – 2024. – Vol. 29. – P. 4265–4283. 12. Council of Europe. Common European Framework of Reference for Languages (CEFR). Companion Volume. – Strasbourg: Council of Europe Publishing, 2020. SUN’IY INTELLEKT VA INNOVATSION PEDAGOGIK YONDASHUVLAR ASOSIDA BO‘LAJAK BOSHLANG‘ICH SINF O‘QITUVCHILARINING TANQIDIY-KREATIV FIKRLASH KOMPETENSIYALARINI RIVOJLANTIRISH Jumayeva Muxlisa Shokir qizi, Nizomiy nomidagi O‘zMPU 1-kurs DSc doktorantiб e-mail: jumayevamuxlisa40@gmail.com Annotatsiya. Mazkur maqolada sun’iy intellekt texnologiyalari va innovatsion pedagogik yondashuvlar asosida bo‘lajak boshlang‘ich sinf o‘qituvchilarining tanqidiy-kreativ fikrlash kompetensiyalarini rivojlantirishning konseptual-metodologik asoslari tahlil qilinadi. Tadqiqotda kompetensiyaviy yondashuv, konstruktivistik ta’lim nazariyasi hamda raqamli pedagogika tamoyillari integratsiyasi asosida model ishlab chiqish imkoniyatlari ko‘rib chiqiladi. Shuningdek, sun’iy intellekt vositalaridan foydalanish orqali reflektiv, analitik va ijodiy fikrlashni shakllantirish mexanizmlari yoritiladi. Maqolada pedagogik ta’lim jarayonini modernizatsiya qilishda lingvistik va ijtimoiy-gumanitar omillarning ahamiyati asoslab beriladi. 237

Kalit so‘zlar: sun’iy intellekt, innovatsion pedagogika, tanqidiy fikrlash, kreativ fikrlash, kompetensiyaviy yondashuv, bo‘lajak o‘qituvchi, raqamli ta’lim, metodologik model, pedagogik integratsiya Аннотация. В данной статье анализируются концептуально-методологические основы развития компетенций критического и творческого мышления будущих учителей начальных классов на основе технологий искусственного интеллекта и инновационных педагогических подходов. В исследовании рассматриваются возможности разработки модели на основе интеграции компетентностного подхода, конструктивистской теории образования и принципов цифровой педагогики. Также освещаются механизмы формирования рефлексивного, аналитического и творческого мышления с использованием средств искусственного интеллекта. В статье обосновывается значение лингвистических и социально-гуманитарных факторов в модернизации процесса педагогического образования. Ключевые слова: искусственный интеллект, инновационная педагогика, критическое мышление, креативное мышление, компетентностный подход, будущий учитель, цифровое образование, методологическая модель, педагогическая интеграция Abstract. This article analyzes the conceptual and methodological foundations for developing the critical-creative thinking competencies of future primary school teachers based on artificial intelligence technologies and innovative pedagogical approaches. The study examines the possibilities of developing a model based on the integration of the competencybased approach, constructivist theory of education, and digital pedagogy principles. It also highlights the mechanisms for forming reflexive, analytical, and creative thinking through the use of artificial intelligence tools. The article substantiates the importance of linguistic and socio-humanitarian factors in modernizing the pedagogical educational process. Keywords: artificial intelligence, innovative pedagogy, critical thinking, creative thinking, competency-based approach, future teacher, digital education, methodological model, pedagogical integration Kirish. Global raqamli transformatsiya sharoitida ta’lim tizimi jamiyatning ijtimoiy-iqtisodiy va madaniy taraqqiyotini belgilovchi strategik sohalardan biriga aylanmoqda. Axborotlashgan jamiyat, bilimlar iqtisodiyoti va innovatsion rivojlanish paradigmasi ta’lim mazmunini modernizatsiya qilishni, pedagogik faoliyatni esa yangi kompetensiyalar bilan boyitishni taqozo etmoqda. Xususan, sun’iy intellekt (SI) texnologiyalarining jadal rivojlanishi ta’lim mazmuni, metodlari va tashkiliy shakllarini tubdan yangilash zaruratini yuzaga keltirmoqda. Bugungi kunda ta’lim jarayoni nafaqat bilim uzatish, balki ma’lumotlarni tanlash, tahlil qilish, qayta ishlash va ulardan samarali foydalanish ko‘nikmalarini shakllantirishga yo‘naltirilmoqda. Zamonaviy ta’lim tizimida pedagog nafaqat bilim beruvchi, balki o‘quvchilarda mustaqil fikrlash, muammoli vaziyatlarni tahlil qilish, dalillarga asoslangan xulosa chiqarish hamda ijodiy yondashuvni shakllantiruvchi fasilitator sifatida namoyon bo‘lishi lozim. Bu esa pedagogning o‘zida yuqori darajadagi tanqidiy va kreativ fikrlash kompetensiyalarining mavjud bo‘lishini talab etadi. Chunki o‘qituvchining fikrlash madaniyati va intellektual pozitsiyasi bevosita o‘quvchilarning kognitiv rivojlanishiga ta’sir ko‘rsatadi. Boshlang‘ich ta’lim bosqichi shaxsning intellektual, ijtimoiy va kommunikativ rivojlanishida poydevor vazifasini bajaradi. Aynan shu bosqichda o‘quvchilarda mustaqil fikrlash elementlari, muloqot madaniyati, muammoni ko‘ra 238