Sun’iy Intellekt va Raqamli Iqtisodiyot

Innovatsion turistik qo‘llanmalar yaratish yo‘nalishida E.R. Fino, J. MartinGutierrez, M. Fernandez va E. Davara tomonidan 3D animatsiyali video, xarita, QR-kodlar va kengaytirilgan reallik elementlarini o‘z ichiga olgan interaktiv turistik qo‘llanma ishlab chiqilgan [1]. Ushbu loyiha an’anaviy gidlik xizmatlarining raqamli muqobilini yaratish yo‘lidagi muhim qadamlardan biri hisoblanadi. Mazkur tadqiqotlar tahlili shuni ko‘rsatadiki, turizm sanoatida raqamlashtirish jarayoni ko‘p qirrali bo‘lib, u texnologik infratuzilma, ma’lumotlar tahlili, foydalanuvchi tajribasi va sun’iy intellekt asosidagi avtomatlashtirishni o‘z ichiga oladi. Biroq mavjud ilmiy ishlarda asosan texnologik imkoniyatlar va amaliy yechimlar yoritilgan bo‘lsa-da, ularning mintaqaviy xususiyatlar, xususan, rivojlanayotgan davlatlar turizm bozori sharoitida qo‘llanilishi yetarlicha ochib berilmagan. Turizmda raqamlashtirish jarayoni nafaqat texnologiyalarni joriy etish, balki boshqaruv modeli, marketing strategiyasi va xizmat ko‘rsatish falsafasining transformatsiyasini ham talab etadi. Ayniqsa, sun’iy intellekt, Big Data va AR/VR texnologiyalarini integratsiyalashgan holda qo‘llash sayyohlik tajribasini personalizatsiya qilish, turistik oqimlarni samarali boshqarish hamda raqobatbardoshlikni oshirishning muhim omili sifatida qaralishi lozim. Shu bois, tadqiqotlarda raqamli texnologiyalarning kompleks integratsiyasi va ularning ijtimoiy-iqtisodiy samaradorligini baholash masalalariga alohida e’tibor qaratish maqsadga muvofiq deb hisoblaymiz. Bugungi kunda sayyohlarni jalb qilish va qoniqishni oshiradigan ko‘plab muqobil turizm mahsulotlari va xizmatlari yaratildi. Raqamli iqtisodiyot an’anaviy turizmga ham salbiy ta’sir ko‘rsatsa-da, u yangi texnologiyalarni joriy etishning dastlabki bosqichlarida zarar ko‘rishi mumkin, ammo mutaxassislar mahsulot va xizmatlar sifatini yaxshilash uchun an’anaviy turizmga ehtiyoj paydo bo‘layotganini ta’kidlamoqdalar, bu esa o‘z navbatida iste’molchilarning qoniqishini va keyinchalik jalb qilinishini oshiradi [9]. Raqamli transformatsiya jarayonida turizm korxonalari uchun raqamli ekotizimni (1-rasm) shakllantirish strategik ustuvor yo‘nalishga aylanmoqda. Raqamli ekotizim deganda, turizm subyektlari (mehmonxonalar, turoperatorlar, transport kompaniyalari, restoranlar, madaniy obyektlar) o‘rtasida yagona axborot maydoni va integratsiyalashgan platformalar orqali o‘zaro hamkorlikni ta’minlovchi tizim tushuniladi. Bunday yondashuv xizmatlar zanjirining barcha bosqichlarida ma’lumotlar almashinuvini tezlashtiradi, tranzaksiya xarajatlarini kamaytiradi va mijozlar ehtiyojlariga moslashuvchan javob qaytarish imkonini yaratadi. 179

1-rasm. Turizm industriyasida integratsiyalashgan raqamli ekotizimning konseptual sxemasi Zamonaviy raqamli platformalar (onlayn bronlash tizimlari, mobil ilovalar, CRM tizimlari, aqlli navigatsiya vositalari) yordamida turistik mahsulotlar real vaqt rejimida taklif etilmoqda. Bu esa talab va taklif o‘rtasidagi nomutanosiblikni kamaytirib, turistik oqimlarni samarali boshqarish imkonini beradi. Xususan, Big Data asosida prognozlash modellari mavsumiylik omillarini, sayyohlar xattiharakatlarini hamda iste’molchilarning xarid odatlarini aniqlashda muhim ahamiyat kasb etadi. Natijada turizm subyektlari marketing strategiyalarini yanada aniq segmentatsiya asosida ishlab chiqish imkoniga ega bo‘ladi. Sun’iy intellektga asoslangan tavsiya tizimlari esa shaxsiylashtirilgan xizmat ko‘rsatish darajasini oshiradi. Masalan, sayyohning oldingi safarlari, qiziqishlari va xarid tarixi asosida individual marshrutlar, mehmonxona variantlari yoki madaniy tadbirlar tavsiya etilishi mumkin. Bu jarayon nafaqat iste’molchi qoniqishini oshiradi, balki xizmat ko‘rsatish samaradorligini ham ta’minlaydi. Shuningdek, avtomatlashtirilgan chatbotlar 24/7 rejimida mijozlarga xizmat ko‘rsatish orqali operatsion xarajatlarni kamaytiradi va tezkor aloqa imkonini beradi. Aqlli shahar (Smart City) konsepsiyasi doirasida turizm infratuzilmasini raqamlashtirish ham alohida ahamiyatga ega. IoT texnologiyalari orqali transport oqimlari, mehmonxonalardagi bandlik darajasi, muzey va tarixiy obyektlardagi tashriflar soni real vaqt rejimida monitoring qilinadi. Bu esa turistik yuklamani muvozanatlashtirish, ortiqcha zichlikni kamaytirish va ekologik barqarorlikni ta’minlashga xizmat qiladi. Shu bilan birga, AR/VR texnologiyalari tarixiy obyektlarni virtual tarzda namoyish etish orqali madaniy merosni saqlash va targ‘ib qilishda innovatsion vosita sifatida namoyon bo‘lmoqda. Raqamli marketing vositalari, jumladan, ijtimoiy tarmoqlar, kontent marketingi, influenserlik strategiyalari va maqsadli reklama (targeting) turizm mahsulotlarini global auditoriyaga yetkazishda muhim omilga aylandi. Raqamli reklama kampaniyalari an’anaviy marketing vositalariga nisbatan nisbatan kam xarajat talab qilgan holda yuqori samaradorlikni ta’minlamoqda. Ayniqsa, foydalanuvchi tomonidan yaratilgan kontent (UGC) sayyohlar qaror qabul qilish jarayonida muhim rol o‘ynaydi. 180

Biroq raqamlashtirish jarayonida bir qator muammolar ham mavjud. Avvalo, texnologik infratuzilmaning yetarli darajada rivojlanmaganligi, kadrlar salohiyatining pastligi va axborot xavfsizligi masalalari dolzarb muammo bo‘lib qolmoqda. Raqamli transformatsiya yuqori investitsiya talab etadi, bu esa kichik va o‘rta turizm subyektlari uchun muayyan moliyaviy cheklovlarni yuzaga keltiradi. Shuningdek, ma’lumotlarni himoya qilish va kiberxavfsizlikni ta’minlash masalalari iste’molchilar ishonchini shakllantirishda muhim omil hisoblanadi. Shu nuqtai nazardan, turizm sohasida raqamli texnologiyalarni joriy etish davlat siyosati va institutsional qo‘llab-quvvatlash bilan uyg‘unlashgan holda amalga oshirilishi zarur deb xisoblaymiz. Raqamli transformatsiya strategiyasi milliy turizm rivojlanish konsepsiyasi bilan integratsiyalashgan bo‘lishi, infratuzilma modernizatsiyasi, kadrlar tayyorlash va innovatsion startaplarni qo‘llab-quvvatlash mexanizmlarini o‘z ichiga olishi lozim. Xulosa va amaliy tavsiyalar. Tadqiqotlar shuni ko‘rsatadiki, turizm sanoatida raqamlashtirish jarayoni nafaqat texnologik yangilanish, balki boshqaruv va xizmat ko‘rsatish tizimining tub transformatsiyasini anglatadi. Raqamli texnologiyalarni joriy etish xizmat sifati va mijoz qoniqishini oshirish, operatsion jarayonlarni optimallashtirish hamda resurslardan samarali foydalanish imkonini bermoqda. Natijada turizm korxonalarining boshqaruv samaradorligi mustahkamlanib, ularning global bozordagi raqobatbardoshligi kuchaymoqda. Shu bilan birga, kelgusida raqamli texnologiyalarni kompleks va integratsiyalashgan yondashuv asosida qo‘llash, ularning iqtisodiy samaradorligini tizimli baholash hamda mintaqaviy xususiyatlarni inobatga olgan holda moslashtirish zarur hisoblanadi. Aynan mana shu yondashuv turizm sohasida barqaror rivojlanish modelini shakllantirish, innovatsion salohiyatni to‘liq ro‘yobga chiqarish va uzoq muddatli ijtimoiy-iqtisodiy natijalarga erishishning muhim sharti bo‘lib xizmat qiladi. Foydalanilgan adabiyotlar ro‘yhati: 1. Fino E.R., Martin-Gutierrezz J., Fernandez D.M., Davara E.A. (2013) Interactive Tourist Guide: Connecting Web 2.0, Augmented reality and QR Codes, Procedia Computer Sciences, no. 25, p. 338-344. 2. Häfner F., Härting R.-Ch., Kaim R. (2020) Potentials of digital approaches in tourism industry with changing customer needs – a quantitative study, Proceedings of the Federated Conference on Computer Science and Information Systems, no. 21, pp. 553-557. 3. Huang C.D., Goo J., Nam K., Yoo Ch. W. (2017) Smart tourism technologies in travel planning: The role of exploration and exploitation, no. 54, pp. 757-770. 4. Kontogianni A., Alepis E. Smart tourism: State of the art and literature review for the last six years. 5. Matveevskaya A.S., Pogodina V., Tarakanova T.S., Evseev V.V. (2018) Technologies of tourism in the modern urban development, International Journal of Civil Engineering and Technology (IJCIET), no. 9, pp. 1566-1574. 6. Salas-Olmedo M. H., Moya-Gomez B., Garcia-Palomares J.C., Gutierrez J. (2018) Tourists’ digital footprint in cities: Comparing Big Data sources, no. 66, pp. 13-25. 181

7. Tussyadiah I. (2020) A review of research into automation in tourism: Launching the Annals of Tourism Research Curated Collection on Artificial Intelligence and Robotics in Tourism, Annals of Tourism Research, no. 81. 8. Вишневская Е.В. Влияние цифровых технологий на развитие туристского рынка // Научный результат. Технологии бизнеса и сервиса. – Т. 5, № 4, 2019, с. 12-24, 9. Найденова М.С. Влияние цифровой экономики на развитие регионального туризма // Экономика. Финансы. Общество. №3, 2022 RAQAMLI AKTIVLARNING TRANSCHEGARAVIY AHAMIYATI Ergasheva Shohista O‘ktam qizi, TDYuU Tayanch doktorantura talabasi Annotatsiya. Raqamli texnologiyalar tez sur’atlar bilan rivojlanib borayotgan bugungi davrda raqamli aktivlarning huquqiy tabiati va ularning xalqaro muomaladagi o‘rni tobora dolzarb ahamiyat kasb etmoqda. Raqamli aktivlarning transchegaraviy xarakteri ularning muomala doirasini bitta davlat bilan cheklab bo‘lmasligini, ko‘plab yurisdiktsiyalar o‘rtasida huquqiy munosabatlar yuzaga kelishini taqozo etadi. Ushbu tezisda raqamli aktivlarning birlamchi va ikkilamchi bozorlardagi huquqiy jihatlari, ularga nisbatan qo‘llaniladigan xalqaro va milliy qonunchilik normalari, shuningdek, kollizion normalarni aniqlashda duch kelinayotgan asosiy muammolar tahlil etiladi. Kalit so‘zlar: raqamli aktivlar, xalqaro xususiy huquq, Transchegaraviy muomala, Kriptoaktivlar, tokenlar, Birlamchi va ikkilamchi bozor Аннотация. В современную эпоху стремительного развития цифровых технологий правовая природа цифровых активов и их роль в международном обороте приобретают всё более актуальное значение. Трансграничный характер цифровых активов требует, чтобы сфера их обращения не ограничивалась одной страной, а правовые отношения возникали между многими юрисдикциями. В данном тезисе анализируются правовые аспекты цифровых активов на первичном и вторичном рынках, применяемые к ним нормы международного и национального законодательства, а также основные проблемы, с которыми сталкиваются при определении коллизионных норм. Ключевые слова: цифровые активы, международное частное право, трансграничное обращение, криптоактивы, токены, первичный и вторичный рынок Abstract. In today's era of rapid digital technology development, the legal nature of digital assets and their role in international circulation are becoming increasingly relevant. The cross-border nature of digital assets requires that their scope of circulation cannot be limited to a single country, and legal relations arise between many jurisdictions. This thesis analyzes the legal aspects of digital assets in primary and secondary markets, the norms of international and national legislation applied to them, as well as the main problems faced in determining conflict of laws norms. Keywords: digital assets, international private law, cross-border circulation, cryptoassets, tokens, primary and secondary markets Kirish. Raqamli aktivlar muomalasi ularning birlamchi joylashtirish bosqichida berilishi hamda ikkilamchi bozorda o‘tkazilishi, shu jumladan kriptobirjalardagi bitimlarni o‘z ichiga oladi. Tokenlar muomalasi virtual makonda amalga oshiriladi, shuning uchun bu yerda deyarli har doim xorijiy investor 182

ko‘rinishidagi xorijiy element paydo bo‘ladi. Bunday hollarda tokenlar muomalasi transchegaraviy tus kasb etadi7. Shu bilan birga, raqamli aktiv emitenti va investor o‘rtasidagi huquqiy munosabatlarda xorijiy element boshqa shaklda ham ifodalanishi mumkin. Masalan, agar raqamli aktiv chet elda joylashgan narsani talab qilish huquqini o‘z ichiga olsa, ushbu huquqiy munosabatlar ham xorijiy element bilan murakkablashtirilgan hisoblanadi. Biroq, agar raqamli aktivlar o‘zaro bir davlat huquqiga bo‘ysunuvchi shaxslar o‘rtasida o‘tkazilayotgan bo‘lsa, bunday muomalani transchegaraviy raqamli aktivlar muomalasi deb hisoblab bo‘lmaydi8. Kollizion huquqiy tartibga solish – bu xususiy huquq sohasiga oid masala bo‘lib, chet elda yuzaga kelgan ommaviy-huquqiy xarakterdagi huquqiy munosabatlarga milliy huquq normalarini qo‘llash mumkin emas. Tokenlar chiqarilishi (ICO) tartibini tartibga soluvchi huquqiy normalar, xususan ro‘yxatdan o‘tkazish, emissiya prospektini e’lon qilish va boshqa talablar, ommaviy-huquqiy tusga ega. Shu bois, ICO o‘tkazish tartibi doimo uning o‘tkazilish joyidagi davlat huquqi bilan tartibga solinadi. Shuningdek, Rossiya va AQSh qonunchiligi tokenaktivlar chiqarilishini ro‘yxatdan o‘tkazishni nazarda tutadi. Biroq AQShda ayrim istisno holatlarda token-aktivlar chiqarilishi ro‘yxatdan o‘tkazilishi shart bo‘lmasligi mumkin. Masalan, agar tokenlar xususiy taklif asosida faqat professional ishtirokchilarga (institutsional investorlar) sotilsa, ular ro‘yxatdan o‘tkazish talabidan ozod etilishi mumkin9. Shuningdek, turli yurisdiktsiyalarda token-aktiv chiqarish to‘g‘risidagi qaror mazmuniga qo‘yiladigan talablar ham farq qiladi. Masalan, AQShning 1933-yildagi “Qimmatli qog‘ozlar to‘g‘risida”gi qonuniga ko‘ra, bunday qarorda emitentning oxirgi moliyaviy yil yakunida muomalada bo‘lgan aksiyalar soni ko‘rsatilishi lozim. Biroq 2020-yilgi “Raqamli moliyaviy aktivlar to‘g‘risida”gi Rossiya qonunchiligida bunday ma’lumotni ko‘rsatish majburiyati mavjud emas.10 Xulosa qilib aytganda, ICO tartib-taomillari ommaviy-huquqiy xarakterga ega bo‘lib, ular xususiy-huquqiy xarakterdagi raqamli aktivlar muomalasidan ajralib turadi. Aynan shu nuqtada kollizion huquqni qo‘llash masalalari yuzaga chiqadi. Raqamli aktivlarni kollizion tartibga solishni o‘rganishda quyidagi xususiyatlarni hisobga olish muhim: Raqamli aktivlarning transchegaraviy muomalasi ikki asosiy bosqichni o‘z ichiga oladi: – Birlamchi muomala (tokenlarning chiqarilishi natijasida o‘tkazilishi); – Ikkilamchi muomala (tokenlarning kriptobirja yoki jismoniy shaxs orqali sotib olinishi). Utility-tokenlar va aktiv-tokenlar doirasida sotuvchi va xaridor o‘rtasidagi huquqiy munosabatlar ikki asosiy komponentdan iborat. Tokenni sotib 7 Low, K.F.K., & Mik, E. (2020). "Pause the blockchain legal revolution." International and Comparative Law Quarterly, 69(1), 135-175 8 Bambara, J.J., & Allen, P.R. (2018). Blockchain: A Practical Guide to Developing Business, Law, and Technology Solutions. McGraw-Hill Education. 9 Murray, A. (2019). The Regulation of Cyberspace: Control in the Online Environment. Routledge. 10 Kaal, W.A. (2020). "Digital Asset Market Evolution." Stanford Technology Law Review, 23(1), 1-45. 183

olishga oid tuzilgan shartnomalardan kelib chiqadigan huquq va majburiyatlar. To‘lov tokenlari (payment tokens) esa bunday majburiyatlarga ega emas, chunki ular o‘z egasiga hech qanday huquq bermaydi va faqat to‘lov vositasi sifatida xizmat qiladi. Raqamli aktivlarning birlamchi muomalasida ushbu aktivlar ICO (Initial Coin Offering) o‘tkazilishi natijasida sotib olinadi. Bu bosqichdagi huquqiy munosabatlarning ishtirokchilari ‒ raqamli aktiv emitenti va investor hisoblanadi. Ikkinchi bozor (ya’ni, ikkilamchi muomala) doirasida raqamli aktivlar kriptovalyuta birjalarida yoki jismoniy shaxslar o‘rtasida sotiladi. Bu bosqichdagi ishtirokchilar quyidagicha bo‘lishi mumkin: kriptobirja ‒ uning mijozlari, hamda sotuvchi va xaridor. Har ikkala holatda ham yakuniy maqsad raqamli aktivlarni sotib olish bo‘lsa-da, mazkur shartnomalar tuziladigan va bajariladigan huquqiy shart-sharoitlar turlicha bo‘ladi. Shu sababli, mazkur huquqiy munosabatlarning yaqin bog‘liqlik markazi (closest connection) turli yurisdiktsiyalarga bo‘ysinishi mumkin. Shu bois, raqamli aktivlar bilan bog‘liq shartnomani birlamchi yoki ikkilamchi muomalaga mansub deb belgilash, unga nisbatan qo‘llaniladigan huquqni aniqlashda muhim rol o‘ynaydi. Oddiy misol orqali tushuntirish mumkin: avtomobil sotib olayotganda xaridor va sotuvchi o‘rtasida shartnoma asosidagi huquqiy munosabat vujudga keladi. Bitim yakunlanib, avtomobil topshirilgach, bu munosabat yakunlanadi. Biroq, tokenni sotib olish jarayonida ham sotuvchi va xaridor o‘rtasida huquqiy munosabat paydo bo‘ladi, ammo xaridor uchun tokenning o‘zi emas, balki u bilan bog‘liq huquqlar asosiy ahamiyatga ega. Ya’ni, tokenni topshirish bu huquqiy munosabatlarni tugatmaydi, balki ularning birinchi bosqichini yakunlaydi. Masalan, Rossiya huquqiga ko‘ra utilitar (foydalanuvchi) tokenlar bo‘yicha dastlab shartnoma tuzilib token sotib olinadi, keyin esa investor emitentga nisbatan o‘z huquqini talab shaklida amalga oshiradi (masalan, muayyan narsani topshirishni talab qilish). Tokenning ijro bosqichi ‒ bu talabning bildirilishi, narsaning topshirilishi esa ushbu bosqichdan tashqarida turadi va klassik shartnomaviy munosabatlar (masalan, oldi-sotdi) orqali tartibga solinadi11. Bu jihatga alohida e’tibor qaratish zarur, chunki ayrim yurisdiktsiyalarda utilitar tokenlar talab huquqini emas, balki fuqarolik huquqi obyektlariga bo‘lgan bevosita huquqni tasdiqlaydi. Bunday hollarda tokenning ijrosi ‒ bu talab shaklida emas, balki token bilan kafolatlangan huquqning bevosita amalga oshirilishida ifodalanadi. Boshqacha qilib aytganda, tokenni sotib olish orqali shaxs darhol mahsulot yoki xizmatga kirish huquqini oladi, lekin u bunga alohida talab qo‘yish huquqiga emas, balki bevosita foydalanish imkoniga ega bo‘ladi. Utillitari tokenlarning xarid qilish bosqichi va bajarilish bosqichi o‘rtasidagi aniq farqlanish ayrim holatlarda mavjud emas. Ayniqsa, agar token fuqaro-huquqiy obyektga bo‘lgan huquqni tasdiqlasa, unda tokenni xarid qilish – mahsulot yoki xizmatga bo‘lgan huquqni bevosita olishni anglatadi. Bunday holatda, utillitari tokenni xarid qilishga oid bitim tokenning mohiyatidan kelib chiqib tartibga 11 Albrecht, C. (2019). Digital Assets and Private International Law. Oxford University Press. 184

solinadi. Masalan, token xizmat ko‘rsatishni kafolatlasa, tokenni sotib olish ushbu xizmat ko‘rsatish bo‘yicha tuzilgan shartnoma asosida tartibga solinadi, oldingi holatdagi kabi oddiy sotish-shartnomasi asosida emas. Xuddi shuningdek, agar token foydalanish huquqini (masalan, intellektual mulk huquqlari) kafolatlasa, u holda tokenni sotib olishga oid bitim litsenziya shartnomasiga asoslanadi, oddiy sotish-shartnomasiga emas. Shunday qilib, bunday tokenlar bo‘yicha majburiyatlar bajarilishi talabni bildirish orqali emas, balki tomonlarning o‘z majburiyatlarini bevosita bajarishi orqali amalga oshadi. Belarus Respublikasining 2017-yildagi “Raqamli iqtisodiyotni rivojlantirish to‘g‘risida”gi Farmoni aynan utillitari tokenlarning huquqiy tabiatini shunday talqin qilishga asoslanadi. Shuningdek, Buyuk Britaniya moliyaviy nazorat organi (FCA)ning rasmiy sharhiga ko‘ra, utillitari tokenlar egasiga tovar yoki xizmatlarga kirish huquqini beradi, lekin talab huquqini emas.12 Ya’ni tokenni olish ‒ shartli tarzda bo‘lsa ham ‒ mahsulot yoki xizmatni olishga tenglashtiriladi. Bundan ham qiziq jihat ‒ Rossiyadagi 2019-yilgi “Investitsiya platformalari orqali investitsiyalar jalb qilish to‘g‘risida”gi qonun utillitari tokenlarni chiqarish (ICO) jarayonini aynan investitsiya platformalarida amalga oshirishni talab qiladi. Bu platformalarda chiqarilgan tokenlar (ya’ni raqamli guvohnomalar) bo‘yicha barcha huquqlar hisobga olinadi. Shunday qilib, raqamli aktivlarning transchegaraviy muomalasini kollizionhuquqiy tartibga solishga ta’sir ko‘rsatadigan ikkita muhim omil mavjud: Muayyan huquqiy munosabatlarning raqamli aktivlar birlamchi yoki ikkilamchi bozori doirasida yuzaga kelganini aniqlash va Token-aktivlar va utillitari tokenlar emitenti hamda ularni sotib olgan shaxs o‘rtasidagi alohida huquqiy munosabatlarni ajratib ko‘rsatish. Foydalanilgan adabiyotlar: 1. Albrecht, C. (2019). Digital Assets and Private International Law. Oxford University Press. 2. Bambara, J.J., & Allen, P.R. (2018). Blockchain: A Practical Guide to Developing Business, Law, and Technology Solutions. McGraw-Hill Education. 3. Huang, J. (2021). "Cross-Border Recognition and Enforcement of Digital Asset Rights." International Journal of Law and Technology, 29(2), 145-167. 4. Kaal, W.A. (2020). "Digital Asset Market Evolution." Stanford Technology Law Review, 23(1), 1-45. 5. Low, K.F.K., & Mik, E. (2020). "Pause the blockchain legal revolution." International and Comparative Law Quarterly, 69(1), 135-175. 6. Murray, A. (2019). The Regulation of Cyberspace: Control in the Online Environment. Routledge. 12 Huang, J. (2021). "Cross-Border Recognition and Enforcement of Digital Asset Rights." International Journal of Law and Technology, 29(2), 145-167. 185

ZAMONAVIY TA’LIM SHAROITIDA PEDAGOGIKA YO‘NALISHI TALABALARIDA SUN’IY INTELLEKT SAVODXONLIGINI RIVOJLANTIRISH ZARURATI Ermatov Sherzodbek Latibjonovich, AndDPI katta o‘qituvchisi, ermatovsher56@gmail.com Annotatsiya. Zamonaviy ta’lim tizimida sun’iy intellekt texnologiyalarining jadal rivojlanishi pedagog kadrlarning kasbiy tayyorgarligiga bo‘lgan talablarni tubdan o‘zgartirmoqda. Ushbu maqolada pedagogika yo‘nalishi talabalarida sun’iy intellekt savodxonligini rivojlantirishning ijtimoiy-pedagogik zarurati, uning tanqidiy fikrlash, axloqiy mas’uliyat va kasbiy kompetensiyalar bilan uzviy bog‘liqligi ilmiy asosda tahlil qilinadi. Kalit so‘zlar: sun’iy intellekt savodxonligi, pedagogik kompetensiya, tanqidiy fikrlash, raqamli ta’lim, kasbiy tayyorgarlik. Аннотация. Активное внедрение технологий искусственного интеллекта в систему образования приводит к качественным изменениям в профессиональной подготовке будущих педагогов. В статье раскрывается социально-педагогическая необходимость формирования искусственного интеллекта грамотности у студентов педагогических направлений, а также её связь с критическим мышлением и этической ответственностью. Ключевые слова: грамотность искусственного интеллекта, педагогическая компетентность, критическое мышление, цифровое образование, профессиональная подготовка. Abstract. The rapid integration of artificial intelligence technologies into education significantly changes the requirements for teachers’ professional training. This paper analyzes the socio-pedagogical necessity of developing AI literacy among pedagogical students, emphasizing its relationship with critical thinking, ethical responsibility, and professional competence. Keywords: artificial intelligence literacy, pedagogical competence, critical thinking, digital education, professional training. Kirish. So‘nggi yillarda ta’lim tizimida kechayotgan raqamli transformatsiya jarayonlari pedagog kadrlar tayyorlash mazmunini qayta ko‘rib chiqishni taqozo etmoqda. Raqamli savodxonlik tushunchasi endilikda faqat axborot-kommunikatsiya texnologiyalaridan foydalanish bilan cheklanib qolmay, balki sun’iy intellekt (SI) asosida ishlovchi tizimlar bilan ongli, tanqidiy va mas’uliyatli munosabatni ham o‘z ichiga olmoqda. OECD, UNESCO va Yevropa Ittifoqi kabi xalqaro tashkilotlarning tahlillarida sun’iy intellekt savodxonligi zamonaviy pedagogning kasbiy tayyorgarligini belgilovchi muhim kompetensiya sifatida e’tirof etiladi [1]. Xususan, OECD ekspertlari SI asosidagi simulyatsiyalar, adaptiv o‘quv tizimlari va raqamli baholash vositalari o‘qituvchining pedagogik imkoniyatlarini kengaytirishini, biroq bu jarayon tanqidiy va axloqiy yondashuv bilan uyg‘unlashmagan taqdirda salbiy oqibatlarga olib kelishi mumkinligini ta’kidlaydilar. Shu jihatdan, pedagogika yo‘nalishi talabalarida sun’iy intellekt savodxonligini rivojlantirish nafaqat texnologik zarurat, balki ijtimoiy-pedagogik ehtiyoj sifatida ham namoyon bo‘lmoqda. 186

Asosiy qism. Zamonaviy ta’lim muhitida o‘qituvchining kasbiy faoliyati an’anaviy bilim berish funksiyasidan tashqariga chiqib, axborotni tahlil qilish, baholash va pedagogik qaror qabul qilish jarayonlarini o‘z ichiga olmoqda. Yevropa Ittifoqi tomonidan ishlab chiqilgan DigCompEdu modelida o‘qituvchining raqamli kompetensiyalari axborot bilan ishlash, raqamli resurslardan foydalanish, baholash va o‘quvchilarni raqamli muhitda qo‘llabquvvatlash yo‘nalishlari orqali ifodalanadi [2]. Mazkur modelda sun’iy intellekt vositalaridan ongli foydalanish, algoritmik tavsiyalarni tahlil qilish va ularning ta’lim jarayoniga ta’sirini baholash zamonaviy pedagog tayyorgarligining muhim mezoni sifatida qaraladi. Bu esa bo‘lajak o‘qituvchilarni SI savodxonligiga tayyorlashni oliy pedagogik ta’limning ajralmas qismiga aylantiradi. Milliy ta’lim siyosatida ham pedagog kadrlarning raqamli va texnologik kompetensiyalarini rivojlantirish ustuvor vazifa sifatida belgilangan. “Raqamli O‘zbekiston – 2030” strategiyasida zamonaviy pedagog innovatsion texnologiyalarni egallagan, raqamli muhitda samarali faoliyat yurita oladigan mutaxassis sifatida talqin etiladi [3]. Ilmiy adabiyotlarda tanqidiy fikrlash zamonaviy pedagogning kasbiy kompetensiyalarini birlashtiruvchi tayanch sifat sifatida e’tirof etiladi. D. Halpern tanqidiy fikrlashni maqsadga yo‘naltirilgan, ongli va mulohazali kognitiv faoliyat sifatida tavsiflaydi [4]. Ushbu qarash sun’iy intellekt vositalaridan foydalanishda o‘qituvchining tanqidiy pozitsiyasi alohida ahamiyat kasb etishini ko‘rsatadi. N. Selwynning ta’kidlashicha, sun’iy intellektdan tanqidsiz foydalanish ta’limda tayyor javoblarga qaramlikni kuchaytirishi, mustaqil fikrlashning susayishiga va pedagogik mas’uliyatning algoritmlarga yuklanishiga olib kelishi mumkin [5]. Shu sababli SI savodxonligi tanqidiy fikrlash va axloqiy mas’uliyat bilan uyg‘un holda shakllantirilishi zarur. O‘zbek olimlari ham bu masalaga alohida e’tibor qaratib, sun’iy intellekt savodxonligini axborot madaniyati, ijtimoiy mas’uliyat va pedagogik etika bilan integratsiyada rivojlantirish zarurligini ta’kidlaydilar [6]. Zamonaviy pedagogik tadqiqotlarda kasbiy kompetensiyalarni shakllantirish faoliyatga yo‘naltirilgan, muammoli va raqamli muhit bilan integratsiyalashgan o‘quv jarayonida samarali amalga oshirilishi ta’kidlanadi. So‘nggi yillardagi ta’lim texnologiyalari bo‘yicha olib borilgan tadqiqotlarga ko‘ra, sun’iy intellekt asosidagi o‘quv vositalari bilan ishlash talabalarda nafaqat bilim va ko‘nikmalarni, balki tanqidiy fikrlash, refleksiya va ongli qaror qabul qilish kompetensiyalarini ham rivojlantiradi. Shu bois bo‘lajak o‘qituvchilar sun’iy intellekt vositalari bilan hali talabalik davridayoq real ta’limiy muammolarni tahlil qilish, AI natijalarini baholash va ularni pedagogik nuqtai nazardan asoslash tajribasini egallashlari zarur. Zamonaviy ijtimoiy-pedagogik yondashuvlarda o‘qituvchi shaxsi jamiyat ongini shakllantiruvchi, raqamli muhitda yo‘naltiruvchi va mas’ul subyekt sifatida qaraladi. Bugungi ilmiy qarashlarga ko‘ra, o‘qituvchi nafaqat bilim uzatuvchi, 187

balki axborotni tanlash, filtrlash, baholash va axloqiy jihatdan asoslash jarayonini boshqaruvchi professional hisoblanadi. Shu nuqtai nazardan, bo‘lajak o‘qituvchilarning sun’iy intellektdan foydalanish madaniyati, algoritmik qarorlarni tanqidiy tahlil qilish qobiliyati va axloqiy pozitsiyasi kelajak avlodning texnologiyaga munosabatini belgilovchi muhim omil sifatida namoyon bo‘ladi. Xulosa va amaliy tavsiyalar.Tahlillar shuni ko‘rsatadiki, pedagogika yo‘nalishi talabalarida sun’iy intellekt savodxonligini rivojlantirish zamonaviy ta’lim tizimining muhim ijtimoiy-pedagogik vazifalaridan biridir. Sun’iy intellekt savodxonligi faqat texnik bilimlar majmui emas, balki tanqidiy fikrlash, axloqiy mas’uliyat va ongli pedagogik qaror qabul qilish kompetensiyalarini o‘z ichiga olgan integrativ sifat sifatida namoyon bo‘ladi. Amaliy tavsiyalar: – pedagogika yo‘nalishida SI savodxonligini kompetensiyaviy yondashuv asosida shakllantirish; – ta’lim jarayonida muammoli, reflektiv va loyihaviy metodlardan foydalanishni kengaytirish; – SI vositalaridan foydalanishda axloqiy va pedagogik nazoratni kuchaytirish. Foydalanilgan adabiyotlar ro‘yhati: 1. OECD. (2021). Artificial Intelligence in Education: Challenges and Opportunities. Paris: OECD Publishing. 2. European Commission. (2022). DigCompEdu: Digital Competence Framework for Educators. Brussels. 3. O‘zbekiston Respublikasi Prezidenti. (2020). Raqamli O‘zbekiston – 2030 strategiyasi. 4. Halpern, D. (2014). Thought and Knowledge: An Introduction to Critical Thinking. New York: Psychology Press. 5. Selwyn, N. (2019). Should Robots Replace Teachers?. Cambridge: Polity Press. 6. Sobirova, M.Q. (2022). Ta’limda tanqidiy fikrlashni rivojlantirish metodikasi. Toshkent. SUN’IY INTELLEKT YORDAMIDA INDIVIDUAL TA’LIMNI TASHKIL ETISH Fayziyeva Shohista Yusup qizi, “Iqtisodiyot va pedagogika universiteti” NTM o‘qituvchisi, sh.fayziyeva583@gmail.com Annotatsiya. Maqolada sun’iy intellekt yordamida individual ta’limni tashkil etishning didaktik mohiyati yoritiladi. O‘quv jarayonini shaxsiylashtirish, adaptiv topshiriqlar, real vaqtli teskari aloqa va avtomatlashtirilgan monitoring mexanizmlari ta’lim samaradorligini oshiruvchi omillar sifatida tahlil qilinadi. Kalit so‘zlar: sun’iy intellekt, individual ta’lim, adaptiv o‘qitish, teskari aloqa, o‘quv analitikasi. Аннотация. В статье раскрываются дидактические основы организации индивидуального обучения с помощью искусственного интеллекта. Научно анализируются персонализация учебного процесса, адаптивные задания, обратная связь в реальном времени и автоматизированный мониторинг как факторы повышения эффективности обучения. 188

Ключевые слова: искусственный интеллект, индивидуальное обучение, адаптивное обучение, обратная связь, учебная аналитика. Abstract. The article examines the didactic foundations of organizing individualized learning through artificial intelligence. It analyzes personalization, adaptive tasks, real-time feedback, and automated monitoring as key mechanisms for improving learning effectiveness in higher education settings. Keywords: artificial intelligence, individualized learning, adaptive learning, feedback, learning analytics. Kirish. Globallashuv, raqamli iqtisodiyot va tezkor axborot oqimi sharoitida oliy ta’lim tizimi oldida yangi vazifalar yuzaga kelmoqda: talabalarni mustaqil o‘qishga yo‘naltirish, ularning kasbiy kompetensiyalarini rivojlantirish va o‘quv natijalarini individual ehtiyojlar asosida boshqarish. Amaliyot shuni ko‘rsatadiki, an’anaviy yondashuvlarda bir xil o‘quv kontenti barcha talabalar uchun bir xil sur’atda beriladi va bu holat tayyorgarlik darajasi turlicha bo‘lgan guruhlar uchun samaradorlikni cheklaydi. Sun’iy intellekt (SI) texnologiyalari esa ta’lim jarayonini shaxsiylashtirish, adaptiv mashqlarni taklif etish, teskari aloqani real vaqt rejimida berish hamda o‘quv faoliyatini analitika asosida monitoring qilish imkoniyatini kengaytirmoqda [1]. Xususan, generativ sun’iy intellekt va katta til modellari (Large Language Model - LLM) asosidagi vositalar matn yaratish, tahlil qilish, mashq topshiriqlarini diversifikatsiya qilish va talabaning individual qiyinchiliklarini aniqlashda yordamchi resurs bo‘lib xizmat qilmoqda [2]. Shu bilan birga, sun’iy intellektdan foydalanish akademik halollik, maxfiylik va ma’lumotlar xavfsizligi kabi masalalarda ham muayyan risklarni keltirib chiqaradi va pedagogik nazoratni kuchaytirishni talab etadi [1]. Demak, sun’iy intellekt yordamida individual ta’limni tashkil etish masalasi ilmiy-metodik jihatdan asoslashni, model va indikatorlar tizimini aniqlashni taqozo etadi. Asosiy qism. Individual ta’lim — bu talabaning bilim darajasi, o‘rganish sur’ati, motivatsiyasi va ehtiyojlariga mos o‘quv trayektoriyasini shakllantirishga qaratilgan yondashuvdir. Sun’iy intellekt asosidagi tizimlarda bunday trayektoriya o‘quv ma’lumotlari (learning data) ni yig‘ish, tahlil qilish va adaptiv qarorlar chiqarish orqali boshqariladi. Zawacki-Richter va hamkorlarining oliy ta’limdagi sun’iy intellekt tadqiqotlari bo‘yicha tahlili ta’limda sun’iy intellekt ishlanmalarining asosiy yo‘nalishlari — adaptiv o‘qitish, avtomatlashtirilgan baholash, o‘quv analitikasi va virtual yordamchilar ekanligini ko‘rsatadi [3]. 1) Ma’lumotlar yig‘ish va diagnostika. Sun’iy intellekt tizimi talabaning test natijalari, platformadagi faolligi, topshiriqlarni bajarish vaqti, xatolar turlari kabi ko‘rsatkichlarni yig‘adi. Diagnostika natijasida talabaning kuchli va zaif tomonlari aniqlanadi hamda mos resurslar tavsiya etiladi. 2) Adaptiv kontent va topshiriqlar. Algoritmlar talabaning javoblariga qarab topshiriq murakkabligini oshiradi yoki soddalashtiradi, alternativ izoh va misollarni beradi. Bu yondashuv “qiyinchilik–muvaffaqiyat” muvozanatini saqlab, motivatsiyani barqarorlashtiradi. 3) Real vaqtli teskari aloqa. Matn va nutq tahlili texnologiyalari (NLP, speech evaluation) xatolarni aniqlab, tuzatish bo‘yicha aniq ko‘rsatma beradi; 189

o‘qituvchi esa yuqori darajadagi metodik boshqaruv va refleksiv tahlilga ko‘proq vaqt ajratadi. 4) Monitoring va prognoz. O‘quv analitikasi yordamida o‘zlashtirish dinamikasi kuzatiladi, xavf guruhidagi talabalar erta aniqlanadi va intervensiya (qo‘shimcha mashq, konsultatsiya, individual maslahat) rejalashtiriladi [4]. Sun’iy intellekt asosida individual ta’limni tashkil etish mexanizmi, indikatorlari va didaktik samaralari o‘rtasidagi bog‘liqlik 1-jadvalda ifodalangan. 1-jadval Sun’iy intellekt yordamida individual ta’limni tashkil etishda qo‘llaniladigan asosiy vositalar Bosqich Sun’iy intellekt Indikatorlar Didaktik natija vosita/tizim turi Diagnostika Learning analytics / test xatolar soni, bajarish kuchli/zaif jihatlarni tahlili vaqti, daraja aniqlash Adaptiv mashq Rekomendatsiya tizimi / to‘g‘ri javoblar %, moslashtirilgan LLM urinishlar topshiriqlar Teskari aloqa NLP / speech evaluation grammar error count, tezkor tuzatish va pronunciation score rivojlantirish Monitoring Dashboard / progress dinamika, risk erta ogohlantirish va tracking indikatorlar qo‘llab-quvvatlash Amaliyotda individual ta’limni tashkil etish uchun sun’iy intellekt vositalarini fan mazmuniga mos pedagogik ssenariylar orqali joriy etish muhim. Masalan, chet tilini o‘qitishda Large Language Model (LLM) asosidagi chatbotlar talabaning darajasiga mos dialoglarni yaratishi, yozma ishlar bo‘yicha reflektiv tavsiyalar berishi hamda mustaqil mashq qilishni faollashtirishi mumkin. Biroq bunday jarayonda o‘qituvchining metodik roli saqlanadi: u maqsadni belgilaydi, baholash mezonlarini aniqlaydi, o‘quvchining faoliyatini nazorat qiladi va akademik halollik bo‘yicha qoidalarni mustahkamlaydi [5]. Xulosa va amaliy tavsiyalar: Xulosa qilib aytganda, sun’iy intellekt yordamida individual ta’limni tashkil etish o‘quv jarayonini shaxsiylashtirish, adaptiv topshiriqlarni taqdim etish, real vaqtli teskari aloqa berish va analitika asosida monitoring qilish orqali ta’lim samaradorligini oshiradi. Shu bilan birga, texnologiyadan foydalanish etik, huquqiy va metodik me’yorlar bilan uyg‘unlashgan holda yo‘lga qo‘yilgandagina barqaror natija beradi. 1. Fan dasturida sun’iy intellekt vositalaridan foydalanishga doir amaliy modul (laboratoriya/ seminar) ajratish va unda individual trayektoriya bilan ishlash ko‘nikmalarini shakllantirish. 2. O‘qituvchilar uchun “AI pedagogikasi” bo‘yicha qisqa malaka oshirish kurslarini tashkil etish (promt-savodxonlik, baholash, etik me’yorlar, akademik halollik). 3. Ta’lim jarayonida ma’lumotlar xavfsizligi va maxfiylikni ta’minlash: ruxsatlar, anonymizatsiya, platforma tanlash mezonlari va foydalanuvchi roziligi. 4. Sun’iy intellekt asosidagi baholash natijalarini faqat yakuniy ball sifatida emas, balki formativ baholash (rivojlantiruvchi feedback) vositasi sifatida qo‘llash. 190

5. Platformalarda o‘quv analitikasi paneli (dashboard)ni joriy etish va riskindikatorlar asosida erta pedagogik qo‘llab-quvvatlash mexanizmini yo‘lga qo‘yish. Foydalanilgan adabiyotlar ro‘yxati: 1. UNESCO. (2023). Guidance for generative AI in education and research. UNESCO Publishing. 2. Bond, M., Khosravi, H., Porayska-Pomsta, K., et al. (2024). A meta systematic review of artificial intelligence in higher education: A call for increased ethics, collaboration, and rigour. International Journal of Educational Technology in Higher Education, 21, Article 15. 3. Zawacki-Richter, O., Marín, V.I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education—Where are the educators? International Journal of Educational Technology in Higher Education, 16, Article 39. 4. Fayziyeva, S.Y. (2025). Talabalarni kasbiy tayyorlashda sun’iy intellekt vositalarining pedagogik imkoniyatlari. Pedagogik mahorat, (11), 93–98. 5. Fayziyeva, S.Y. (2025). Talabalarni kasbiy tayyorlashda sun’iy intellekt vositalarining pedagogik imkoniyatlari. Pedagogik mahorat, (11), 93–98. ISSN 2181-6833. ANALYSIS OF THE EFFECTIVENESS OF ARTIFICIAL INTELLIGENCE (AI) TECHNOLOGIES IN ENGLISH LANGUAGE TEACHING USING THE EXAMPLE OF CHATGPT Niyazova Feride, Shakhrisabz state pedagogical institute e-mail: fniyazova@shdpi.uz Makhmudova Maftuna, Shakhrisabz state pedagogical institute student e-mail: rahimovaxurwida@gmail.com Abstract. The rapid development of artificial intelligence (AI) technologies has significantly transformed modern education, particularly in the field of English language teaching (ELT). This article analyzes the effectiveness of AI-based tools in enhancing language learning outcomes, using ChatGPT as a representative example. The study examines how AIdriven systems contribute to improving learners’ grammar, vocabulary acquisition, writing skills, speaking practice, and overall communicative competence. Keywords: Artificial Intelligence (AI), English Language Teaching (ELT), ChatGPT, AIbased tools, language learning outcomes, grammar improvement, vocabulary acquisition, personalized learning, adaptive learning, immediate feedback, learner autonomy, educational technology. Аннотация. Стремительное развитие технологий искусственного интеллекта (ИИ) существенно изменило современное образование, особенно в области обучения английскому языку (ELT). В данной статье анализируется эффективность инструментов на базе искусственного интеллекта в повышении результатов изучения языков, используя ChatGPT в качестве репрезентативного примера. В исследовании рассматривается, как системы на базе искусственного интеллекта способствуют улучшению грамматики учащихся, овладению словарным запасом, навыкам письма, практике говорения и общей коммуникативной компетенции. Ключевые слова: Искусственный интеллект (ИИ), Обучение английскому языку (ELT), ChatGPT, инструменты на основе ИИ, результаты изучения языка, совершенствование грамматики, приобретение словарного запаса, персонализированное обучение, адаптивное обучение, мгновенная обратная связь, автономия обучающегося, образовательные технологии. 191

Annotatsiya. Sun’iy intellekt (SI) texnologiyalarining jadal rivojlanishi zamonaviy ta’limni, ayniqsa ingliz tilini o‘qitish (ELT) sohasini sezilarli darajada o‘zgartirib yubordi. Ushbu maqolada ChatGPT misolida til o‘rganish natijalarini oshirishda sun’iy intellektga asoslangan vositalarning samaradorligi tahlil qilinadi. Tadqiqotda sun’iy intellektga asoslangan tizimlar o‘quvchilarning grammatikasi, lug‘at boyligini o‘zlashtirish, yozish ko‘nikmalari, nutq amaliyoti va umumiy muloqot kompetensiyasini yaxshilashga qanday hissa qo‘shishi o‘rganiladi. Kalit so‘zlar: Sun’iy intellekt (AI), ingliz tilini o‘qitish (ELT), ChatGPT, sun’iy intellektga asoslangan vositalar, til o‘rganish natijalari, grammatikani takomillashtirish, lug‘at boyligini oshirish, shaxsiylashtirilgan ta’lim, moslashuvchan ta’lim, tezkor qayta aloqa, ta’lim oluvchi mustaqilligi, ta’lim texnologiyasi. Inrtoduction. The rapid advancement of digital technologies has significantly transformed educational practices worldwide. Among these innovations, artificial intelligence (AI) has emerged as one of the most influential forces reshaping teaching and learning processes. In particular, the integration of AI technologies into English Language Teaching (ELT) has created new oррortunities for personalized, interactive, and efficient language instruction. As globalization continues to increase the demand for English рroficiency, educators are increasingly exploring technological solutions that can enhance learning outcomes and address diverse learner needs. AI-powered tools offer various functions that support language acquisition, including automated feedback, adaptive learning pathways, natural language processing, and real-time communication simulation. One prominent example is ChatGPT, an AI-based conversational system capable of generating human-like text and engaging users in meaningful dialogue. By providing instant responses, grammar corrections, vocabulary suggestions, and writing assistance, ChatGPT has gained рoрularity among English learners and teachers alike. The effectiveness of AI technologies in ELT lies in their ability to promote learner autonomy, increase motivation, and provide continuous access to рractice outside the classroom. Unlike traditional instructional methods that may be limited by time and classroom size, AI systems can offer individualized support tailored to each learner’s proficiency level and learning pace. Furthermore, AI tools can simulate authentic communication scenarios, helping students develop рractical language skills in a low-anxiety environment. However, despite these advantages, the integration of AI in English language education also raises important pedagogical and ethical considerations. Questions remain regarding the accuracy of AI-generated content, the potential for overreliance on technology, and the role of teachers in AI-supported learning environments. Therefore, it is essential to critically examine both the benefits and limitations of AI applications in language teaching. Methods. The foundation of this study is based on the jigsaw technique, in which students are organized into groups. Each group is assigned a task related to the development of a specific language skill. After completing their tasks, all groups come together to share and discuss their findings in order to develop a 192

comprehensive understanding of their overall exрerience. According to Aronson (2008), the jigsaw method is an effective instructional strategy, especially in foreign language teaching. It encourages students to actively teach and learn from one another, which aligns with one of the рrimary objectives of this study. In this study, participants used ChatGPT in two different ways. First, they relied on it to conduct textual analysis by asking direct questions about the content. Second, they used it as a guide to suggest action steps and to provide criteria and evaluation during the exercise (see Figure 1). Initially, students applied content analysis, a method used to identify specific words, themes, or concepts within qualitative data or texts. Content analysis generally consists of two main types: conceptual analysis and relational analysis. This study employed a quasi-experimental research design to analyze the effectiveness of artificial intelligence (AI) technologies in English language teaching, using ChatGPT as a representative tool. A pre-test–post-test control group design was imрlemented to comрare the learning outcomes of students exposed to AI-assisted instruction with those receiving traditional teaching methods. The study was conducted over an eight-week instructional рeriod. The indeрendent variable was the integration of ChatGPT into English language instruction, while the dependent variable was students’ English language proficiency, measured through standardized assessments. A total of 60 undergraduate students participated in the study. The participants were selected using random sampling and were divided into two groups: Experimental group (n = 30) Control group (n = 30) The students’ ages ranged from 18 to 22 years old. All participants had an intermediate (B1) level of English proficiency according to CEFR standards. Prior to the study, none of the participants had formally used AI-based language learning tools in their coursework. Several instruments were used to collect quantitative data: Pre-test and Post-test – These assessments measured students’ grammar knowledge, vocabulary acquisition, reading comprehension, and writing skills. The tests were designed in accordance with CEFR B1-level descriptors. Questionnaire – A 20-item Likert-scale questionnaire was administered to evaluate students’ motivation, engagement, and attitudes toward the use of AI technologies in English language learning. Writing Assessment Rubric – A standardized rubric was used to evaluate students’ written assignments based on coherence, grammatical accuracy, lexical range, and task achievement.The reliability and validity of the instruments were ensured through expert review and pilot testing prior to the main study. The research procedure consisted of the following stages: 1. At the beginning of the study, both groups completed a pre-test to determine their baseline English proficiency levels. 2. During the eight-week intervention period, the experimental group used ChatGPT as a supplementary learning tool in English classes. Students engaged in 193

activities such as: AI-assisted writing practice Grammar explanation and error correction Vocabulary expansion exercises Interactive question-and-answer sessions 1. The control group received traditional instruction based on textbooks, teacher explanations, and conventional classroom activities without AI integration. 2. At the end of the intervention, both groups completed the post-test to measure learning progress. 3.Finally, students in the experimental group completed the questionnaire to assess their perceptions of AI-supported learning. Result: The analysis of the pre-test results indicated no statistically significant difference between the experimental and control groups at the beginning of the study (p > 0.05), confirming that both groups had comparable English proficiency levels prior to the intervention. After the eight-week instructional period, the post-test results revealed noticeable differences in performance between the two groups. The experimental group, which used ChatGPT as a supplementary learning tool, demonstrated a higher mean score (M = 82.4, SD = 6.3) compared to the control group (M = 74.1, SD = 7.5). An independent samples t-test was performed to compare post-test scores between the experimental and control groups. The results showed a statistically significant difference in favor of the experimental group. These findings suggest that the integration of AI technology, specifically ChatGPT, had a positive effect on students’ English language achievement compared to traditional teaching methods. The analysis of the questionnaire responses indicated generally positive student perceptions of AI-assisted learning. 87% of students agreed that AI tools improved their writing skills. 83% reported increased motivation in English classes. 90% stated that instant feedback provided by ChatGPT was helpful for correcting grammatical errors. Recent empirical studies on AI in language teaching: Recent empirical research on the application of artificial intelligence (AI) in language education highlights the rapid expansion of AI technologies within modern educational environments. Over the past decade, the integration of AI-driven systems into teaching and learning processes has significantly transformed pedagogical practices, instructional design, and student engagement. In particular, the field of language education has experienced substantial innovation through the adoption of AI-based digital tools. Within the context of second and foreign language instruction, AI technologies have emerged as powerful instructional supports that facilitate personalized learning, adaptive feedback, and interactive practice opportunities. These systems are capable of analyzing learner input, identifying linguistic errors, and generating immediate corrective feedback, thereby promoting more autonomous and self-regulated learning. As a result, AI tools are increasingly being viewed not merely as supplementary resources but as transformative agents 194

in language acquisition processes. A growing body of empirical studies has investigated the pedagogical value of AI-powered platforms, including ChatGPT, in enhancing various language skills such as writing, grammar, vocabulary development, and conversational competence. Researchers have examined their impact on learner motivation, engagement, academic performance, and critical thinking skills. The findings of these studies generally suggest that AI-assisted instruction can contribute positively to language proficiency when effectively integrated into structured learning environments. Discussion. This study addresses the growing need to enhance language proficiency by examining the transformative potential of ChatGPT-generated content in supporting language skill development. Specifically, the paper investigates the extent to which ChatGPT can contribute to the improvement of language skills in particular and to language education in general. The research employed two main methodological approaches. First, a content-oriented analysis was conducted by posing direct questions to ChatGPT and evaluating the nature and quality of its responses. Second, students analyzed the generated content over a six-week period to determine whether it effectively contributed to the development of their language skills. During this period, ChatGPT was used both as a learning guide and as an interactive partner in various classroom activities. The findings indicate that the majority of ChatGPT’s responses emphasized encouragement, persistence, and regular practice. However, many of the replies consisted primarily of extended lists of general recommendations and procedural instructions—information that is typically accessible through conventional search engines such as Google. As a result, participants from two different contexts, Iraq and the Czech Republic, reported that content-based analysis through direct questioning was not particularly effective for developing practical language skills. They emphasized that meaningful language acquisition requires active engagement with the language itself rather than exposure to descriptive or theoretical content about the language. Moreover, the implementation of ChatGPT-4 played a significant role in enhancing students’ English communicative competence. The participants in the experimental group demonstrated noticeable progress in their ability to communicate effectively in English, as reflected in their post-test performance. In comparison to their pre-test results, these students produced more accurate language, reduced grammatical and lexical errors, and showed greater fluency in expression. The observed differences between pre-test and post-test scores were statistically significant, indicating that the improvements were not due to chance but rather associated with the AI-supported instructional intervention. The findings of this study carry important implications for professionals in the field of education, particularly teachers, curriculum designers, and educational policymakers. Integrating the instructional strategies and AI-supported approaches applied in the experimental group into mainstream curricula could potentially enhance the overall effectiveness of English language instruction. By embedding 195

AI-assisted activities into classroom practice, educators may foster more interactive, responsive, and learner-centered environments. Conclusion. This study examined the effectiveness of artificial intelligence technologies in English language teaching, with particular emphasis on the application of ChatGPT as an instructional support tool. The findings demonstrate that AI-assisted instruction can positively influence students’ language development, particularly in terms of writing accuracy, grammatical competence, vocabulary expansion, and overall communicative performance. The experimental results revealed statistically significant improvements in the post-test scores of students who engaged with ChatGPT-integrated learning activities compared to those who received traditional instruction. The AI-supported group showed enhanced fluency, reduced language errors, and higher levels of engagement and motivation. These outcomes suggest that AI technologies, when implemented systematically and pedagogically, can contribute meaningfully to foreign language acquisition. At the same time, the findings indicate that the effectiveness of ChatGPT depends largely on how it is integrated into the learning process. While the tool demonstrates strong potential in supporting written production, idea generation, and structured practice, it may be less effective when used solely for content-based questioning without active linguistic engagement. Language learning requires interaction with the language itself rather than passive exposure to explanations or generalized recommendations. Therefore, AI tools should complement, rather than replace, communicative and interactive teaching approaches. References: 1. AI in English Teaching with ChatGPT: Does it really work? 2. Contemporary Educational Technology, 2025, 17(4), ep591 ISSN: 1309-517X 1(Online) 3. Contemporary Educational Technology, 17(4), ep591 4. The Use of Artificial Intelligence (AI): Chatgpt and Mastery of English-Speaking Skills 5. https://rsisinternational.org/journals/ijriss/articles/the-use-of-artificial-intelligence-ai-chatgptand-mastery-of-english-speaking-skills 6. https://www.cedtech.net/download/chatgpt-and-the-development-of-core-language-skills-anexploratory-study-of-efl-college-students-17242.pdf 7. https://research.bangor.ac.uk/en/publications/ai-in-english-teaching-with-chatgpt-does-itreally-work/ SANOAT KORXONALARINING TASHQI IQTISODIY FAOLIYAT MENEJERLARINI TAYYORLASHDA SUN’IY INTELLEKTGA ASOSLANGAN “ADAPTIVE LEARNING” TIZIMLARINING SAMARADORLIGI Gofurjanov Ibroximjon ilxomjon o‘g‘li, Turan International University texnika fanlari bo‘yicha falsafa doktori (PhD)., dotsenti v.v.b., E-mail: gofurjanovi@gmail.com Annotatsiya. Mazkur maqolada sanoat korxonalarining tashqi iqtisodiy faoliyat menejerlarini tayyorlash jarayonida sun’iy intellektga asoslangan “Adaptive Learning” 196

tizimlaridan foydalanishning pedagogik va iqtisodiy samaradorligi ilmiy jihatdan tahlil qilinadi. Tadqiqotda globallashuv va raqamli iqtisodiyot sharoitida tashqi iqtisodiy faoliyatni boshqarish jarayonlarining murakkablashuvi, menejerlardan yuqori darajadagi analitik, strategik va raqamli kompetensiyalar talab etilayotgani asoslab beriladi. Maqolada sun’iy intellektga asoslangan moslashuvchan o‘qitish tizimlarining bilimlarni individuallashtirish, o‘quv jarayonining samaradorligini oshirish, amaliy ko‘nikmalarni shakllantirish va tashqi iqtisodiy faoliyat menejerlarini tayyorlash sifatini yaxshilashdagi roli yoritiladi. Tadqiqot natijalari “Adaptive Learning” tizimlaridan tizimli foydalanish sanoat korxonalarining tashqi iqtisodiy faoliyatini boshqarishda kadrlar salohiyatini oshirish va raqobatbardoshlikni ta’minlashda muhim omil ekanligini ko‘rsatadi. Kalit so‘zlar: tashqi iqtisodiy faoliyat, TIF menejerlari, sun’iy intellekt, Adaptive Learning, raqamli ta’lim, kadrlar tayyorlash, kompetensiyalar, sanoat korxonalari. Аннотация. В данной статье с научной точки зрения анализируется педагогическая и экономическая эффективность использования систем "Adaptive Learning" на основе искусственного интеллекта в процессе подготовки менеджеров внешнеэкономической деятельности промышленных предприятий. В исследовании обосновывается, что усложнение процессов управления внешнеэкономической деятельностью в условиях глобализации и цифровой экономики требует от менеджеров высокого уровня аналитических, стратегических и цифровых компетенций. В статье освещается роль адаптивных систем обучения на основе искусственного интеллекта в индивидуализации знаний, повышении эффективности учебного процесса, формировании практических навыков и улучшении качества подготовки менеджеров внешнеэкономической деятельности. Результаты исследования показывают, что системное использование систем "Adaptive Learning" является важным фактором повышения кадрового потенциала и обеспечения конкурентоспособности в управлении внешнеэкономической деятельностью промышленных предприятий. Ключевые слова: внешнеэкономическая деятельность, менеджеры ВЭД, искусственный интеллект, Adaptive Learning, цифровое образование, подготовка кадров, компетенции, промышленные предприятия. Abstract. This article analyzes the pedagogical and economic efficiency of using "Adaptive Learning" systems based on artificial intelligence in the process of training foreign economic activity managers of industrial enterprises from a scientific perspective. The study substantiates that the increasing complexity of foreign economic activity management processes in the context of globalization and the digital economy requires managers to possess high levels of analytical, strategic, and digital competencies. The article highlights the role of adaptive artificial intelligence-based training systems in individualizing knowledge, increasing the efficiency of the educational process, developing practical skills, and improving the quality of training for foreign economic activity managers. The research results show that the systematic use of "Adaptive Learning" systems is an important factor in increasing human resource potential and ensuring competitiveness in the management of foreign economic activities of industrial enterprises. Keywords: foreign economic activity, foreign economic management, artificial intelligence, adaptive learning, digital education, personnel training, competencies, industrial enterprises. Kirish. Globallashuv sharoitida sanoat korxonalarining tashqi iqtisodiy faoliyati tobora murakkablashib, xalqaro savdo, logistika, moliyaviy hisob-kitoblar va strategik rejalashtirishni chuqur bilim va ko‘nikmalarga ega mutaxassislar 197

tomonidan boshqarishni talab etmoqda. Tashqi iqtisodiy faoliyat menejerlari xalqaro bozorlar bilan ishlash, risklarni baholash, raqamli texnologiyalardan foydalanish va tezkor qarorlar qabul qilish kabi murakkab vazifalarni bajaradi. Shu sababli ularni tayyorlash va qayta tayyorlash tizimiga qo‘yilayotgan talablar keskin oshmoqda. An’anaviy ta’lim va trening tizimlari tashqi iqtisodiy faoliyatning tez o‘zgaruvchan muhitiga moslashishda ko‘pincha yetarli darajada samarali emas. Raqamli iqtisodiyot sharoitida sun’iy intellektga asoslangan “Adaptive Learning” tizimlari ta’lim jarayonini individuallashtirish va moslashuvchan tashkil etish imkonini berib, kadrlar tayyorlash sifatini yangi bosqichga olib chiqmoqda. Shu nuqtai nazardan, ushbu tizimlarning sanoat korxonalarining tashqi iqtisodiy faoliyat menejerlarini tayyorlashdagi samaradorligini ilmiy jihatdan tahlil qilish dolzarb masala hisoblanadi. Asosiy qism. Sanoat korxonalarining tashqi iqtisodiy faoliyatini samarali boshqarish ko‘p qirrali bilim va amaliy ko‘nikmalarga ega menejerlarni talab etadi. Bunday mutaxassislar xalqaro savdo qoidalari, bojxona jarayonlari, valyuta operatsiyalari, raqamli savdo platformalari va global bozor tahlilini chuqur bilishi lozim. Ushbu kompetensiyalarni shakllantirish jarayonida “Adaptive Learning” tizimlari o‘quv jarayonini o‘rganuvchining individual tayyorgarlik darajasi va o‘zlashtirish sur’atiga moslashtirish imkonini beradi. Sun’iy intellektga asoslangan moslashuvchan o‘qitish tizimlari o‘quvchilarning bilim darajasini doimiy tahlil qilib, o‘quv materiallarini avtomatik ravishda moslashtiradi. Bu holat tashqi iqtisodiy faoliyat menejerlarini tayyorlashda bilimlardagi bo‘shliqlarni tezkor aniqlash va ularni bartaraf etishga xizmat qiladi. Natijada o‘quv jarayoni samaradorligi oshib, tayyorlanayotgan mutaxassislarning bilim darajasi yanada mustahkamlanadi [1]. “Adaptive Learning” tizimlari tashqi iqtisodiy faoliyatga oid murakkab jarayonlarni modellashtirish orqali amaliy ko‘nikmalarni shakllantirishda ham muhim rol o‘ynaydi. Sun’iy intellekt asosidagi simulyatsiyalar va real holatlarga yaqinlashtirilgan mashg‘ulotlar menejerlarning strategik fikrlash va qaror qabul qilish qobiliyatini rivojlantiradi. Bu esa sanoat korxonalarining tashqi iqtisodiy faoliyatida yuzaga keladigan murakkab vaziyatlarni samarali boshqarishga imkon yaratadi. Raqamli ta’lim tizimlaridan foydalanish tashqi iqtisodiy faoliyat menejerlarini tayyorlash jarayonida o‘qitish xarajatlarini optimallashtiradi. An’anaviy treninglarga nisbatan moslashuvchan raqamli platformalar vaqt va moliyaviy resurslardan samarali foydalanishni ta’minlaydi. Shu bilan birga, bilimlarni doimiy yangilab borish imkoniyati menejerlarning professional rivojlanishini uzluksiz qo‘llab-quvvatlaydi [2]. Sun’iy intellektga asoslangan “Adaptive Learning” tizimlari o‘qitish jarayonida subyektivlikni kamaytirib, bilimlarni baholashda aniqlikni oshiradi. Algoritmlar asosida shakllantirilgan tahlillar menejerlarning real bilim va ko‘nikmalarini ob’ektiv baholash imkonini beradi. Bu holat kadrlar tayyorlash 198