DIGITAL LINGUISTICS, ARTIFICIAL INTELLIGENCE AND EDUCATIONAL TECHNOLOGIES.

INTERNATIONAL SCIENTIFIC AND PRACTICAL CONFERENCE “INTEGRATION OF MODERN LINGUISTICS WITH SCIENCE, EDUCATION, AND PRACTICE IN THE PROCESS OF GLOBALIZATION: NEW APPROACHES, OPPORTUNITIES, AND CHALLENGES”, DECEMBER 4, 2025 934 DIGITAL LINGUISTICS, ARTIFICIAL INTELLIGENCE AND EDUCATIONAL TECHNOLOGIES 1Toshtemirova Charos Ulug‘bek qizi, 1Qurbonova Muslima Laziz qizi, 1Xamdamova Aziza Doniyorovna, 1Baxtiyorova Shahzoda Umid qizi, 2Abdumuminova Dilnoza Xomit qizi. 1Navoi region, Navoi State University, 1st year student, 2Navoi region, Navoi State University, Professor-teacher https://doi.org/10.5281/zenodo.17837260 Annotation. The present phase of societal development is intricately linked to the digitalization of every aspect of public life without exception. Education, in this context, must serve as the foundation or the groundwork for the informed and skillful use of Artificial Intelligence (AI) technologies, neural networks, and other AI-based cyber-physical systems, along with robots and robotic entities. The advancement of digitalization in education is supported by economic, social, and structural conditions. The incorporation of these technologies offers fresh chances to enhance the educational process; however, the use of these technologies also encounters certain risks, the recognition of which is postponed. The objective of the article is to present methods for the advancement of legal regulation regarding AI, robots, and robotic entities in the field of education. Key words: language education, artificial intelligence, technology, globalization, digital tools, language learning apps, robots. Introduction: The Fourth Industrial Revolution, characterized by rapid technological growth and digital application, is impacting nearly every aspect of our lives. Artificial Intelligence (AI) has influenced our lifestyle and work, ranging from cleaning floors to guiding Alexa. AI holds significant promise in the domain of education. Artificial Intelligence in education is a developing area within educational technology. It possesses a vast capability of delivering digital and entirely customized education to every student. Nonetheless, the concept of incorporating AI in education is surprisingly causing anxiety among educators due to numerous misconceptions and misunderstandings about AI's role in education. This is primarily due to educators lacking awareness of its pedagogical impact on education overall and language acquisition specifically. This is also due to the absence of thorough evaluations of the educational consequences and innovative methods for incorporating AI into teaching. Consequently, this study seeks to investigate how AI can improve language learning experiences. It examines the resources that can be utilized to instruct English successfully. It also seeks to clarify how AI can promote student independence. It primarily envisions AI-integrated learning in classrooms to improve the English language teaching experience and support teachers in delivering their lessons efficiently. It emphasizes instructing pronunciation and enhancing fluency by replicating the sound pattern alongside utilizing speech recognition and speech editing tools. Additionally, it emphasizes a personalized method for language acquisition through a Chatbot that offers text-to-speech and speech-to-text capabilities, utilizing technology to transcribe spoken language for pronunciation checks, translate spoken words, and engage in conversation by employing voice commands similar to Google Assistant. INTERNATIONAL SCIENTIFIC AND PRACTICAL CONFERENCE “INTEGRATION OF MODERN LINGUISTICS WITH SCIENCE, EDUCATION, AND PRACTICE IN THE PROCESS OF GLOBALIZATION: NEW APPROACHES, OPPORTUNITIES, AND CHALLENGES”, DECEMBER 4, 2025 935 Evolution of Digital Linguistics and Prominent Scholars in AI. The incorporation of computational techniques into linguistics was not immediate; it evolved through various technological phases, each backed by key researchers and new methodological advancements. Before the concept of digital linguistics emerged, early innovators established the foundation for computational methods: Noam Chomsky (1957–1965) – introduced generative grammar, which later motivated computational syntax models; Martin Kay (1980s) – made significant contributions to computational morphology and translation systems; Douglas Biber (1990s) – created multi-dimensional analysis for corpora, impacting contemporary text analytics; Kenneth Church & Patrick Hanks – were pioneers in statistical natural language processing (NLP); Alec Radford & the OpenAI team (2018–present) – developed GPT models, vital for digital linguistics studies; James Pustejovsky – progressed computational semantics and lexical modeling. Digital Linguistics: Basics, Techniques, and Development. Definition and Appearance. Digital linguistics involves employing computational, technological, and algorithmic methods for the analysis of language. It arose from the digital shift in the humanities and the growing access to extensive digital corpora, annotation tools, and machine-readable linguistic information. Fundamental Aspects of Digital Linguistics. Digital linguistics includes various interconnected fields: • Corpus Linguistics and Big Data (instruments like Sketch Engine, AntConc, and NLTK facilitate frequency counting, concordance creation, and collocation analysis); • Computational Linguistics and NLP (These techniques offer greater understanding of language frameworks and handling). • Digital Language Preservation (digital documentation enhances conservation, accessibility, and intergenerational sharing); • Visualization and Interactive Tools (heat maps, dependency graphs, and dynamic charts assist researchers in visualizing linguistic phenomena, enhancing data interpretation). AI in Language Studies: • AI and Machine Learning as Analytical Instruments (machine learning algorithms surpass conventional manual techniques because of efficiency and magnitude); • Natural Language Processing (NLP) (NLP enables linguists to examine vast numbers of sentences in moments, facilitating innovative methods of empirical linguistic investigation); • Speech Technologies (TTS, ASR create extensive phonetic datasets and facilitate studies on intonation, rhythm, and prosody) • The cognition of Large Language Models (LLMs) questions theories of linguistic competence and performance, prompting inquiries into the essence of language and cognition. Custom Learning Pathways: AI algorithms evaluate student achievement and modify the educational journey to fulfill personal requirements. This customization guarantees that learners obtain focused practice and assistance in fields where they strive. Chatbots and Virtual Instructors: AI-driven chatbots offer immediate feedback. and dialogue exercise. Online instructors replicate genuine interactions, assisting students enhance their speaking and auditory skills in a secure setting. Machine learning techniques are transforming the way we learn languages through offering tailored, effective, and interactive learning opportunities. Via personalized learning routes, forecasting analysis, immediate responses, and suggestions for content, these algorithms improve the efficiency of language teaching and assistance extensive variety of students. Utilizing the strength of machine learning, instructors and developers are INTERNATIONAL SCIENTIFIC AND PRACTICAL CONFERENCE “INTEGRATION OF MODERN LINGUISTICS WITH SCIENCE, EDUCATION, AND PRACTICE IN THE PROCESS OF GLOBALIZATION: NEW APPROACHES, OPPORTUNITIES, AND CHALLENGES”, DECEMBER 4, 2025 936 able to build more interactive and adaptive learning settings that address the specific requirements of every student, creating opportunities for additional effective language learning and competence. Digital Linguistics and Artificial Intelligence in Language Learning: • Language Teaching Based on Corpora (learners gain knowledge from authentic usage instead of created textbook illustrations); • Learning Material Created by AI (this guarantees that resources match learner requirements); • Learning Analytics and Linguistic Profiling (enables educators to track development in quantitative terms); • Learning through multiple modes and gamified elements (gamification enhances involvement and motivation). Technology as a Learning Partner. The conventional teaching model struggles to engage students accustomed to digital settings. This is the point at which technology and AI are essential. Applications such as virtual tutors, role-playing simulations, and automated evaluations are merely a few instances of how these innovations can revolutionize language classrooms. At Dexway, the language division of CAE, we have observed the advantages of incorporating technology into education. Online and blended learning courses provide increased engagement and interaction while ensuring a more thorough educational experience. 5 Reasons to Integrate Technology and AI in Language Classrooms: 1. Interactivity. 2. Connection with Digital Students. 3. Active Participation. 4. Real-Time Evaluation and Tracking. 5. Accessibility. Approximately 87% of participants reported utilizing AI in their educational journey. Out of these, 36% utilize it for learning tasks more than once a week, 33% a few times monthly, and 10.7% every day. 12.5% of those surveyed never incorporate AI into their educational experience. More than 75% of those surveyed indicated that AI assists them in saving time. Fewer than 10% report not observing any such effect, while 14.8% expressed uncertainty. Almost 70% allocate the time they save to their personal life and leisure, indicating a wish for a balance between work and life. A significant proportion of respondents use the freed-up resources for professional development – completing additional tasks (51.5%) and improving the quality of work (45.8%). Nevertheless, merely 13% are ready to rely on AI for any responsibilities. 61% of those surveyed expressed that they do not trust AI to create diploma and final theses. One third would prefer it not to finish written assignments, another third would prefer it not to carry out practical and lab work, 24% would prefer it not to create oral presentations, and 17% would prefer it not to look for and handle educational materials in readiness for classes. Conclusion: Digital linguistics and AI have transformed linguistic research and language teaching. Cutting-edge technologies facilitate extensive data examination, automate intricate language tasks, and offer creative educational solutions. AI-powered educational resources promote flexible, customized, and engaging learning experiences. Still, ethical concerns, possible biases, and accessibility problems persist as significant challenges. The prospects of linguistics and education depend on the accountable, evidence-driven incorporation of AI, guaranteeing that INTERNATIONAL SCIENTIFIC AND PRACTICAL CONFERENCE “INTEGRATION OF MODERN LINGUISTICS WITH SCIENCE, EDUCATION, AND PRACTICE IN THE PROCESS OF GLOBALIZATION: NEW APPROACHES, OPPORTUNITIES, AND CHALLENGES”, DECEMBER 4, 2025 937 technology complements human knowledge instead of substituting it. Ongoing cooperation between linguists, educators, engineers, and policymakers will influence the future development of language research and educational technologies. RESOURCES 1. 1981-2025 & TM Voluxion, Dexway by CAE Computer Aided USA Corp. & Computer Aided Elearning, SA 2. Global Market Insights Inc. 3. НИУ ВШЭ 1993–2025. Шрифты HSE Sans и HSE Slab разработаны в Школе дизайна НИУ ВШЭ. 4. Anderson, J., & Corbett, J. (2021). Digital Linguistics: Theory and Practice. 5. 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