Chapter 1. Designing English and Ukrainian language courses with AI tools: comparative approach

5 CHAPTER 1 CHAPTER 1 Designing English and Ukrainian language courses with AI tools: comparative approach DOI: 10.15587/978-617-8360-20-7.CH1 Oksana Chaika, Natalia Sharmanova, Natalia Berezovska-Savchuk © The Author(s) of chapter, 2025. This is an Open Access chapter distributed under the terms of the CC BY license Abstract This chapter examines how artificial intelligence (AI) tools, primarily ChatGPT and Copilot, can inform the design of English Language Teaching (ELT) and Ukrainian Language Teaching (ULT) courses for philology students. Grounded in a structured comparative analysis, the study synthesizes literature, analyzes AI-assisted course drafts, and considers practical use cases to evaluate impacts on course architecture, teaching processes, and learner outcomes. Framed within Education 4.0 and ongoing digital transformation, findings show that AI supports personalization, timely formative feedback, multimodal task design, and data-informed instructional decisions, while improving timeand cost-efficiency for educators and administrators. At the same time, persistent challenges include accuracy and reliability, sensitivity to linguistic and cultural nuance, uneven digital competence, technical constraints, and ethical risks related to bias, privacy, and transparency. The chapter argues that AI augments rather than replaces the teacher and that effective adoption requires capacity-building, governance for ethical and equitable use, and attention to institutional readiness. Pragmatic recommendations are offered for integrating AI into ELT/ULT course design to enhance engagement and proficiency while safeguarding human-centered aims. KEYWORDS Artificial intelligence (AI), Education 4.0, digital transformation, English Language Teaching (ELT), Ukrainian Language Teaching (ULT), course design, personalization, adaptive learning, feedback and assessment, equity and ethical governance, ChatGPT, Copilot. English Language Teaching (ELT) and Ukrainian Language Teaching (ULT) encompass a multifaceted approach to language instruction, tailored to meet the diverse needs of learners worldwide and locally [1–3]. As a field within applied linguistics, ELT and ULT draw upon various methodologies, theories, and pedagogical frameworks to facilitate the acquisition and development of English and Ukrainian language skills [4, 5] to meet the dynamic needs of learners in various linguistic and 6 Educational policy and reforms: the impact of globalization CHAPTER 1 cultural contexts [6] via the Communicative Language Teaching (CLT) methodology, which emphasizes authentic communication, meaningful interaction in real-life communicative tasks, and task-based learning activities in language classrooms [1, 7]; Task-Based Language Teaching (TBLT), which focuses on the use of authentic, purposeful tasks to promote language learning and proficiency while completing tasks that simulate real-world language use situations [8, 9]; the Direct Method, which emphasizes the use of target language in instruction and focuses on oral communication skills [1]; the Audio-Lingual Method, which emphasizes repetition, mimicry, and pattern practice to develop language skills [4]; and the Lexical Approach, which focuses on the teaching of vocabulary and collocations as the building blocks of language [10]. Moreover, in [11], on top to TBLT, such pedagogical frameworks as Content and Language Integrated Learning (CLIL), and the Sheltered Instruction Observation Protocol (SIOP) model also inform ELT and ULT practice by providing structured approaches to integrating language instruction with content learning. Further, from traditional classroom-based instruction to innovative technology-enhanced learning environments, ELT and ULT encompass a spectrum of teaching practices aimed at fostering proficiency in listening, speaking, reading, and writing in English [12, 13]. 1.1 Evolving Paradigms in Language Teaching Historically, ELT has evolved in response to changes in global communication, migration patterns, and educational paradigms [6, 14]; so did ULT [13]. The emergence of communicative language teaching (CLT) in the late 20th century marked a significant shift towards interactive and learner-centered approaches to language instruction [7, 15] and emphasized the importance of authentic communication, TBL, and meaningful interaction in language classrooms [1]. In contemporary ELT and ULT practices, educators employ a variety of instructional strategies and techniques to engage learners and promote language acquisition: communicative activities, language games, role-plays, authentic materials, and technology-mediated tasks [5, 16], primarily focusing on learner autonomy, cultural awareness, and critical language awareness, that altogether has become increasingly prominent in ELT and ULT curriculum design [17, 18]. This leads to conclude that ELT and ULT continue to evolve in response to advances in linguistic research, educational technology, and the changing needs of learners in diverse linguistic and cultural contexts [16, 19]. However, as educators strive to enhance language teaching effectiveness and promote language learning outcomes, ongoing innovation and adaptation remain essential elements of ELT and ULT practice; the integration of Artificial Intelligence (AI) in education will only strengthen language teaching by offering personalized learning experiences and adaptive feedback, empowering educators to transcend traditional instructional limitations and optimize learning outcomes. Thus, we consider AI in education to represent a paradigm shift in teaching and learning practices, offering unprecedented opportunities for innovation and transformation. AI technologies, including natural language processing (NLP), machine learning, and data analytics, are revolutionizing educational 7 chapter 1. Designing English and Ukrainian language courses with AI tools: comparative approach CHAPTER 1 processes by enabling personalized learning experiences, adaptive instruction, and data-driven decision-making [20, 21]. In the context of ELT and ULT to university philology students, AI holds immense potential to enhance language learning outcomes by providing learners with tailored support, feedback, and engagement opportunities [22, 23]. By leveraging AI-powered tools and platforms, educators can optimize ELT and ULT course design, address individual learner needs, and foster a more inclusive and effective learning environment, create dynamic, adaptive, and personalized learning experiences that cater to the diverse needs and learning styles of individual learners [24]. Through AI-driven applications such as automated writing evaluation systems, language learning chatbots, and adaptive learning platforms, educators can provide timely feedback, scaffold learning experiences, and track learner progress more effectively [25, 26]. Furthermore, AI enables educators to harness the vast amounts of data generated in digital learning environments to inform instructional decisions, identify learning trends, and improve course efficacy [27, 28]. It is assumed that integration of AI in ELT and ULT course design not only enhances language learning outcomes but also empowers educators to create more engaging, efficient, and student-centered learning experiences. Following the above, the primary purpose of this study was to examine the critical role of AI in the field of ELT and ULT, with a specific focus on its significance in designing and implementing effective language courses. Via the synthesis of existing research, theoretical frameworks, and practical examples, the work will elucidate the potential benefits, challenges, and implications of integrating AI tools into the course design process. Through an in-depth analysis of AI-powered applications and methodologies, i.e., ChatGPT and Copilot, we aimed to provide insights into how educators can harness the power of AI to optimize ELT and ULT practices, enhance pedagogy, and improve learning outcomes for language learners. Positioning this analysis within the broader paradigm of Education 4.0 and ongoing digital transformation, the chapter views AI-assisted course design as a driver of pedagogical change rather than a stand-alone technical upgrade. The comparative focus on English and Ukrainian contexts highlights how adaptive technologies support personalization, data-informed decisions, and flexible learning pathways, while exposing constraints of uneven digital competence and institutional readiness. Framing the study this way aligns the practical course-design cases with international debates on transparency, bias, and equity in AI-enhanced education. 1.2 Materials and Methods We employed a structured comparative analysis to evaluate the integration of AI tools, specifically focusing on ChatGPT and Copilot, in ELT/ULT course design for philology students. To achieve the set objectives, we utilized a range of materials to explore the integration of AI tools in English and Ukrainian language teaching. These included theoretical frameworks on educational technology, detailed drafts of AI-assisted ELT and ULT course designs, comparative studies illustrating the 8 Educational policy and reforms: the impact of globalization CHAPTER 1 practical application and outcomes of ChatGPT, Copilot and other digital tools in language education. Thus, analyzing the conceptual frameworks of research, we categorized the 52 shortlisted works into several distinct groups based on their focus on artificial intelligence (AI) in education, language teaching methodologies, and the integration of technology in language learning. The following key groups were determined: 1) AI in language learning and education (27%), where works focus on the application, impact, and potential of AI in these areas; they explore how AI tools, teachable agents, and intelligent systems can enhance educational outcomes, personalize learning experiences, and support both teachers and students in the learning process; 2) language teaching methodologies and pedagogical strategies (27%), with research findings that cover task-based learning, communicative language teaching, and the lexical approach; these provide theoretical foundations and practical strategies for effective language instruction, focusing on both traditional and innovative pedagogical approaches; 3) integration of technology in language learning (17%), which explores the role of various technologies in enhancing language learning and discusses the use of AI, virtual and augmented reality, social learning analytics, and computer-supported collaborative learning; the focus of distinguished researchers is on how these technologies can be integrated into the language learning process to improve engagement, motivation, and educational outcomes; 4) specific language contexts and innovations in teaching (10%), which helped us provide insights into specific language teaching contexts, such as teaching modern Ukrainian, teaching Ukrainian in professional settings, teaching Ukrainian as a foreign language, innovations in language teaching in Ukraine, and the use of immersive technologies; the works mainly highlight localized approaches and case studies that demonstrate the application of innovative teaching practices in different educational settings; 5) other research complementing the findings in more advanced areas, e.g., ELT, multicultural education, innovations in education etc. The research results covered a wide range of topics related to AI in education and the importance of robust pedagogical frameworks, causing the need for innovative strategies tailored to specific educational contexts. Detailed drafts of ELT and ULT courses designed with the assistance of ChatGPT and Copilot served as foundational materials for analysis, and examination of their application illustrated perspective outcomes. To evaluate the integration of AI tools in ELT and ULT course design, we conducted a structured comparative analysis, incorporating a comprehensive literature review and detailed examination of AI-assisted course drafts. We analyzed the data obtained and presented the features, capabilities, and outcomes of ChatGPT and Copilot as opposed to other AI tools in the context of ELT and ULT course design. This involved evaluating the tools' effectiveness in personalizing learning, providing feedback, and supporting instructional decisions. A supplement was the key perspective for educators and administrators – the proposed approach would turn costand time efficient. Detailed studies of the ChatGPT and Copilot course drafts helped understand the practical 9 chapter 1. Designing English and Ukrainian language courses with AI tools: comparative approach CHAPTER 1 implementation of AI tools in language teaching of English and Ukrainian to university philology students. These studies provided insights into the benefits and challenges that may be experienced by both educators and students. Ultimately, the information from theoretical frameworks, course design drafts, and comparative studies was synthesized to identify patterns, draw conclusions, and provide recommendations for effective AI integration in language teaching of English and Ukrainian to philology students. 1.3 The Role of AI in Education The role of AI in education is multifaceted and continues to evolve rapidly with advancements in technology. Based on the studies and findings by X. Hu et al. [29], M. Maas et al. [30], A. Ravenscroft et al. [31], W. Holmes et al. [32], etc., the following key aspects of AI's role in education include personalized learning, data analytics, intelligent tutoring systems, automation of administrative tasks, virtual learning environments, language learning and translation, which are not the exhaustive list (Fig. 1.1). data analytics intelligent tutoring systems virtual learning environments language learning and translation automation of administrative tasks personalized learning  Fig. 1.1 Key aspects of AI's role in education Source: research findings It is found that with personalized learning AI algorithms can analyze vast amounts of data to tailor learning experiences to individual students' needs, preferences, and learning styles. AI systems easily provide personalized recommendations, adaptive content, and targeted feedback; they can also optimize learning outcomes and engagement [33, 34]. Similarly, AI-powered tutoring systems can enhance students' performance when they simulate one-on-one tutoring experiences by providing personalized instruction, feedback, and support to students. These systems can be also used by ELT and ULTs to adapt to students' progress, diagnose learning gaps, and scaffold learning experiences to facilitate mastery of concepts [23, 29, 35]. 10 Educational policy and reforms: the impact of globalization CHAPTER 1 Data analytics enables the collection, processing, and analysis of educational data on a large scale. This data-driven approach allows ELT and ULT educators to gain insights into student performance, identify learning trends when teaching English and Ukrainian as L1 or L2, and make data-informed decisions to improve teaching and learning practices [23, 36, 37]. Further, AI technologies can save a great deal of teachers' time as they may automate routine administrative tasks, such as grading assignments, managing student records, and scheduling classes. Educators in ELT and ULT can allocate more time and resources to teaching and supporting students [31, 32, 38] instead of spending their time on assessments and taking notes manually. As VR (virtual reality) is advancing at an immense speed, AI-driven virtual learning environments can be used in ELT and ULT classrooms to create immersive and interactive learning experiences, e.g., virtual classrooms, simulations, and gamified learning activities. It is agreed with M. Maas and J. Hughes [30], and E. Abrenilla et al. [39] that "these environments enable students to engage with course materials in dynamic and engaging ways", enhancing motivation and retention [40]. Finally, AI-powered language learning platforms and translation tools can assist students in learning English and Ukrainian as L2, improving pronunciation, and translating texts in real-time. These tools leverage natural language processing and machine learning algorithms [40] to facilitate language acquisition and communication [38]. At large, AI has the potential to revolutionize education by enhancing personalized learning experiences, improving teaching efficiency, and expanding access to quality education. However, it is essential to address ethical considerations, privacy concerns, and ensure equitable access to AI technologies to maximize their benefits for all learners. Drawing upon cognitive science, learning theories, and educational psychology, theoretical frameworks arise essential guides for understanding the role of AI in education and its integration into ELT practices provide a conceptual basis for the development and implementation of AI-powered educational technologies. Within the broader context of education, various theoretical perspectives shape the discourse surrounding AI integration. Constructs from cognitive science, such as schema theory and information processing models, offer insights into how learners acquire, process, and retain knowledge, thus informing the design of AI algorithms and adaptive learning systems [41]. Moreover, dating back, learning theories such as constructivism, socio-cultural theory, and connectivism provide theoretical underpinnings for understanding how learners construct knowledge, engage with learning materials, and interact within learning environments [42, 43] and emphasize the importance of active engagement, social interaction, and authentic learning experiences. With the advance of modern digitalization, AI technologies can facilitate personalized learning pathways through collaborative platforms, and interactive learning environments. Furthermore, in the specific context of ELT and ULT, pedagogical theories play a crucial role in guiding the integration of AI tools to enhance language instruction. Constructivist approaches, which emphasize the role of learners as active participants in their own learning process, align closely with the principles of AI-driven personalized learning. They provide learners with opportunities for exploration, discovery, and reflection, AI-powered language learning platforms can scaffold learning experiences and promote 11 chapter 1. Designing English and Ukrainian language courses with AI tools: comparative approach CHAPTER 1 deeper understanding of language concepts [38, 40]. Similarly, the socio-cultural theory, which emphasizes the socio-cultural context of learning and the importance of social interaction in knowledge construction, informs the design of AI-supported collaborative learning environments in ELT/ ULT [43]. Language learning chatbots, virtual language exchange platforms, and collaborative writing tools leverage AI technologies to facilitate peer interaction, language practice, and cultural exchange among learners from diverse linguistic backgrounds. Finally, as mentioned in introduction task-based learning (TBL) theory provides a practical framework for integrating AI tools into ELT and ULT pedagogy [38]; it emphasizes the use of authentic, real-world tasks to promote language learning and communication skills, aligning closely with the goal of AI-driven language learning applications to provide contextualized, task-oriented language practice. To summarize, the theoretical framework for the role of AI in education and pedagogical theories supporting AI integration in ELT and ULT provides a rich conceptual basis for understanding the potential impact of AI technologies on language teaching and learning, enabling educators to harness the power of AI to create innovative, adaptive, and effective learning environments that empower learners to achieve their language learning goals. 1.4 Frameworks for Designing ELT and ULT Courses with AI Tools The integration of AI tools into the design and delivery of ELT courses requires a structured framework that aligns pedagogical principles with technological capabilities. Several frameworks have emerged to guide educators in effectively incorporating AI tools into ELT course design, facilitating personalized learning experiences, and optimizing learning outcomes. The literature review advances a wide variety of frameworks which aim at adaptive learning, data-driven instructional design, pedagogical agent, and social learning. The adaptive learning frameworks leverage AI algorithms to dynamically adjust course content, pace, and difficulty level based on individual learner needs and performance [44] while data-driven instructional design frameworks utilize AI-driven analytics to inform course design decisions, identify learning trends, and assess learner progress [45]. The former, as opposed to data-driven frameworks, can tailor learning pathways, recommend resources, and provide personalized feedback to enhance language acquisition and mastery by analyzing learner interactions, preferences, and performance data [33, 34, 46] while with the latter educators can iteratively refine course materials, activities, and assessments to better meet learner needs and optimize learning outcomes, by analyzing learner data, such as engagement metrics, assessment results, and learning trajectories. Next, pedagogical agent frameworks integrate AI-powered pedagogical agents into course design to provide personalized support, guidance, and feedback to learners [37, 47]. These virtual agents, powered by natural language processing and machine learning technologies, can engage learners in interactive dialogues, scaffold learning activities, and provide timely assistance, enhancing learner engagement and motivation in language learning contexts [48, 49]. However, the value of social learning frameworks cannot be underestimated as these can contribute even more as they 12 Educational policy and reforms: the impact of globalization CHAPTER 1 leverage AI technologies to facilitate collaborative learning experiences [15], peer interaction, and knowledge sharing among learners [50]. Based on the above it is found highly reasonable to incorporate social learning features such as discussion forums, collaborative projects, and peer review activities into ELT courses. It is agreed with P. Parrish and B. Wilson [51], and O. Chaika et al. [6] that then educators can create a supportive learning community where learners can engage in meaningful language practice and cultural exchange. Moreover, in line with the Qualities and Levels of Experience Model presented by P. Parrish and B. Wilson, it is taken further that both educators and learners can grow their expertise, where the engagement levels may apply to educators irrespective of their years of employment and pedagogical experience – from those designing ELT and ULT courses while having no and hardly any experience and feeling forced to do that to those enjoying challenging endeavors and aesthetic experience (Fig. 1.2). Challenging Endeavors Aesthetic Experience Pleasant Routine Scattered/Incomplete Activity Forced, Mindless Routine Unconsciousness (No experience) Intent Presence Openness Trust Immediacy Malleability Compellingness Resonance Coherence Situational Qualities Qualities and Levels of Experience Individual Qualities  Fig. 1.2 Qualities and levels of experience for educators' AI-powered ELT and ULT competence Source: [51] From the above perspective, frameworks for designing ELT and ULT courses with AI tools provide educators with structured approaches for integrating AI technologies into course design and delivery. That becomes easily manageable with leveraging adaptive learning, employing data-driven 13 chapter 1. Designing English and Ukrainian language courses with AI tools: comparative approach CHAPTER 1 instructional design, pedagogical agents, and social learning frameworks, and learning experiences once personalized will become more engaging and dynamic, which altogether will optimize language learning outcomes for diverse audience in ELT and ULT contexts. 1.4.1 AI Tools for ELT and ULT Course Design AI tools have revolutionized ELT and ULT course design, offering innovative solutions to enhance learning experiences and outcomes for students. Based on the study results, as well as discussions with teachers, the below enlisted AI tools appeared to lead and leverage advanced technologies, i.e., NLP and data analytics to provide personalized, interactive, and effective language learning experiences. Regarding ELT and ULT course design, these AI tools encompass a wide range of applications, including: a) language practice and interaction, where AI-powered chatbots and virtual assistants enable learners to engage in simulated conversations, language practice activities, and interactive exercises; these tools provide personalized feedback, guidance, and support, enhancing learners' speaking, listening, and communication skills in authentic contexts; b) personalized learning pathways relate to adaptive learning systems that utilize AI algorithms to analyze learner data and adjust course content, pace, and difficulty levels based on individual learning needs and preferences; by tailoring learning pathways to each student's strengths, weaknesses, and learning styles, these tools optimize learning outcomes and promote learner autonomy and engagement; c) feedback and assessment are crucial to ELT and ULT course design, and AI-driven feedback mechanisms enable automated evaluation of language proficiency, grammar accuracy, and writing skills; moreover, these tools provide timely, targeted feedback to philology students, identifying areas for improvement and guiding them towards mastery of language concepts and skills; d) content creation and customization, under which AI technologies facilitate the creation and customization of learning materials, exercises, and assessments; natural language generation algorithms generate text-based content, while machine learning algorithms adapt content to learners' proficiency levels, interests, and learning objectives, ensuring relevance and engagement; e) language learning analytics, AI-powered analytics tools analyze learner data to identify patterns, trends, and insights related to language learning progress and performance; educators can use these insights to track student progress, assess learning outcomes, and inform instructional decisions, thereby optimizing course design and delivery. It arrives that with AI tools ELT and ULT course design can be easily transformed into an engaging activity for educators and for learners it will offer personalized, interactive, and data-driven learning experiences. Educators can create dynamic and engaging language learning environments that cater to the diverse needs and preferences of learners, ultimately enhancing language proficiency and promoting lifelong learning. 20 Educational policy and reforms: the impact of globalization CHAPTER 1 Course objectives: 1. To familiarize students with the basic components of English grammar. 2. To develop students' ability to analyze and understand sentence structure. 3. To enhance students' proficiency in using English grammar accurately and effectively in both spoken and written communication. 4. To cultivate students' critical thinking skills through the examination and application of grammatical principles. 5. To provide opportunities for students to practice and refine their grammar skills in authentic contexts. Course outline: Week 1–2. Introduction to grammar: – overview of the course objectives, expectations, and resources; – definition of grammar and its importance in communication; – parts of speech: nouns, pronouns, verbs, adjectives, adverbs, prepositions, conjunctions, and interjections. Week 3–4. Sentence structure: – basic sentence elements: subject, predicate, object; – sentence types: declarative, interrogative, imperative, exclamatory; – sentence patterns and variations. Week 5–6. Verb tense and aspect: – overview of verb tense system: present, past, future; – progressive aspect and perfect aspect; – verb conjugation and irregular verbs; Week 7–8. Noun phrases and pronouns: – noun phrase structure: determiners, modifiers; – types of pronouns: personal, possessive, demonstrative, relative, interrogative, indefinite; – agreement between pronouns and antecedents. Week 9–10. Adjectives and adverbs: – functions and placement of adjectives; – degrees of comparison: positive, comparative, superlative; – types and functions of adverbs. Week 11–12. Sentence transformation and editing: – sentence transformation exercises: affirmative to negative, active to passive, direct to indirect speech; – proofreading and editing techniques; – peer review and feedback sessions. Week 13. Review and assessment: – review of key concepts and grammar rules covered in the course; – practice exercises and quizzes; 21 chapter 1. Designing English and Ukrainian language courses with AI tools: comparative approach CHAPTER 1 – final assessment: written exam and/or practical assignment. Course materials: – textbook: "Understanding English Grammar" by B. S. Azar; – online resources: grammar exercises, interactive tutorials, and supplementary readings; – grammar reference guides and handouts provided by the instructor. Assessment: – weekly quizzes and homework assignments (30%); – midterm exam covering grammar concepts and application (30%); – final project: writing assignment or grammatical analysis task (20%); – final exam: comprehensive assessment of course content (20%). Teaching methodology: – lectures: theoretical explanations and examples presented by the instructor; – interactive activities: group discussions, pair work, and role-play exercises; – hands-on practice: grammar drills, writing tasks, and editing exercises; – multimedia presentations: videos, audio recordings, and online tutorials. Grading policy: – A: 90–100%; – B: 80–89%; – C: 70–79%; – D: 60–69%; – F: below 60%. Course policies: – attendance: regular attendance and active participation in class activities are expected; – late submissions: assignments submitted after the due date will incur a penalty; – academic integrity: plagiarism or cheating will result in disciplinary action as per university policies; – accommodations: students with disabilities or special needs should contact the instructor to arrange appropriate accommodations. Note: this course outline serves as a general framework and can be modified or adapted according to the specific needs and preferences of the instructor and students. In summary to the above ELT courses, several advantages of Draft C course design for ELT should be noted over the courses in Drafts A and B, i.e., systematic organization and comprehensive coverage, interactive teaching methods and balanced assessment, and alignment with learning objectives and practical application. Firstly, unlike the course design created by Copilot in Draft A, which may lack detailed organization or comprehensive coverage of grammar topics, Draft C provides a clear and structured outline covering fundamental grammar concepts in depth, ensuring students receive a thorough understanding of English grammar. Secondly, the latter draft by ChatGPT in contrast to Draft B, which may lack interactive elements or varied assessment strategies, incorporates diverse teaching methodologies such as group discussions, pair work, and multimedia 22 Educational policy and reforms: the impact of globalization CHAPTER 1 presentations, along with a balanced assessment strategy including quizzes, exams, and projects, which altogether ensures active student engagement and holistic evaluation of learning outcomes. Finally, unlike both courses in Drafts A and B, which may not fully align with both theoretical and practical learning objectives, Draft C for ELT design strikes a balance between theoretical explanations and practical application, integrating real-life examples and writing/editing exercises to reinforce learning and promote effective communication skills in English. Most importantly, and what is going to be discussed in challenges of implementing AI tools for ELT course designs, Draft C includes the note in the end: "This course outline serves as a general framework and can be modified or adapted", which is critically important for ethical considerations and originality statement [18] of the work by educators. Draft D (copy-pasted from Copilot). Course title: Modern literary Ukrainian. Course description: this course introduces students to Modern Literary Ukrainian, encompassing its development, cultural context, and contemporary usage. It aims to develop students' proficiency in Ukrainian language and acquaint them with significant literary works and media that shape modern Ukrainian discourse. Course objectives: 1. To understand the evolution of the Ukrainian language and its literary forms. 2. To analyze and interpret Ukrainian literary texts and media critically. 3. To enhance language skills in reading, writing, speaking, and comprehension. 4. To explore the role of literature and media in reflecting and shaping societal values and identity. Course content: 1. Introduction to modern literary Ukrainian: – historical development of the Ukrainian language; – overview of the Ukrainian literary canon; – language structure and contemporary usage. 2. Literature and cultural identity: – study of key literary figures and their contributions; – exploration of themes such as identity, nationalism, and the individual versus society. 3. Ukrainian literature and film: – analysis of literary works adapted into films; – the interplay between visual and textual narratives. 4. Contemporary Ukrainian media: – examination of current Ukrainian media and journalism; – the impact of media on language and culture. 5. Language and politics: – the influence of political movements on language and literature; – case studies: Maidan Revolution and the Russia-Ukraine conflict. 23 chapter 1. Designing English and Ukrainian language courses with AI tools: comparative approach CHAPTER 1 Learning outcomes: – demonstrate an understanding of the structure and usage of modern literary Ukrainian; – critically analyze Ukrainian literary texts and media; – communicate effectively in both spoken and written Ukrainian; – reflect on the cultural and political dimensions of Ukrainian literature and media. Assessment methods: – written assignments analyzing literary texts and media; – oral presentations on selected topics; – participation in class discussions; – final exam encompassing comprehension, translation, and essay writing. Recommended readings: – selections from twentieth-century Ukrainian literature and film; – contemporary Ukrainian prose and poetry; – academic articles on Ukrainian language and cultural studies. Course duration: one academic year (two semesters). Prerequisites: none. This course is designed for beginners. Teaching methods: – lectures and seminars; – group discussions and debates; – film screenings and analysis; – language labs for practice. This draft is a starting point and can be tailored to meet the specific needs and goals of your academic program. It's also essential to include a variety of assessment methods to cater to different learning styles and to provide students with a comprehensive understanding of Modern Literary Ukrainian. Draft D as an AI-generated course design holds both strengths and weaknesses. First, it offers a comprehensive overview of modern Ukrainian literary language, integrating historical development, key literary figures, and contemporary media and politics. Second, the interdisciplinary approach provides students with a holistic understanding of the Ukrainian language's cultural significance. Third, the course also emphasizes practical application through language labs, film analysis, and group discussions, enhancing students' speaking, writing, and analytical skills. Finally, the focus on critical thinking and cultural identity helps students appreciate the broader socio-cultural impact of language. It may serve as a backbone to build on the necessary elements and design more specific features. At the same time, a list of weaknesses may refer to a broad range of topics, which might limit the depth of coverage for each area, potentially leaving philology students with a superficial understanding of the required information. Then, the resource-intensive nature of the course, requiring technology, materials, and skilled instructors, may not be feasible in all educational settings given the age and IT-competence of lecturers. Moreover, assessment methods, while diverse, might not cater to all learning styles, disadvantaging students uncomfortable with oral presentations 24 Educational policy and reforms: the impact of globalization CHAPTER 1 or group discussions. Additionally, despite being designed for first year philology students, the course might be challenging for those with no prior exposure to Ukrainian language or literature, necessitating additional support. Finally, the context-specific content may limit the course's appeal to a broader audience, especially those not specifically interested in Ukrainian studies. Draft E (copy-pasted from ChatGPT, Version 3.5). Course title: Modern literary Ukrainian for first-year bachelor students. Course description: this course introduces first-year bachelor students to modern literary Ukrainian, focusing on its evolution, cultural context, and contemporary usage. The course aims to develop students' proficiency in Ukrainian language skills and familiarize them with significant literary works and media shaping the modern Ukrainian discourse. Course objectives: 1. To understand the evolution of the Ukrainian language and its literary forms. 2. To critically analyze and interpret modern Ukrainian literary texts and media. 3. To enhance linguistic skills in reading, writing, speaking, and comprehension in Ukrainian. 4. To explore the role of literature and media in reflecting and shaping societal values and identity. Course outline: Week 1–2. Introduction to modern literary Ukrainian: – overview of the course objectives, expectations, and resources; – historical development of the Ukrainian language; – key characteristics of modern literary Ukrainian. Week 3–4. Literary canon and cultural identity: – introduction to significant figures in modern Ukrainian literature; – exploration of themes such as identity, nationalism, and societal values; – analysis of selected literary works. Week 5–6. Ukrainian literature in film: – examination of literary works adapted into films; – comparative analysis of narrative techniques in literature and film; – film screenings and discussions. Week 7–8. Contemporary Ukrainian media: – analysis of modern Ukrainian media and journalism; – the impact of media on language and culture; – case studies of notable media texts. Week 9–10. Language and politics: – exploration of the political influences on language and literature; – case studies on the Revolution of Dignity and the Russia-Ukraine conflict; – analysis of political discourse in literary texts. Week 11–12. Practical language skills: – language labs focusing on reading, writing, and speaking skills; 25 chapter 1. Designing English and Ukrainian language courses with AI tools: comparative approach CHAPTER 1 – practical exercises and real-life applications; – peer review and feedback sessions. Week 13. Review and assessment preparation: – review of key concepts and course materials; – practice exercises and quizzes; – preparation for final assessments. Week 14. Final assessments: – written examination covering course content; – oral presentations on selected topics; – submission of a final essay or project. Course materials: – textbook: selected works of modern Ukrainian literature; – supplementary readings: articles and excerpts from Ukrainian media; – film excerpts and documentaries; – online resources: language exercises, interactive tutorials, and multimedia content. Assessment methods: – weekly quizzes and homework assignments (30%); – midterm exam on literary analysis and language skills (25%); – oral presentations and participation in class discussions (20%); – final written exam and/or project (25%). Teaching methodology: – lectures: theoretical explanations and contextual background; – seminars: group discussions and in-depth analysis; – language labs: practical exercises and language practice; – multimedia presentations: film screenings and media analysis. Grading policy: – A: 90–100%; – B: 80–89%; – C: 70–79%; – D: 60–69%; – F: below 60%. Course policies: – attendance: regular attendance and active participation in class activities are expected; – late submissions: assignments submitted after the due date will incur a penalty; – academic integrity: plagiarism or cheating will result in disciplinary action as per university policies; – accommodations: students with disabilities or special needs should contact the instructor to arrange appropriate accommodations. Note: this course outline is a general framework and may be adapted to meet the specific needs and goals of the academic program and its students. 26 Educational policy and reforms: the impact of globalization CHAPTER 1 Draft E for ULT in addition to course title, description, and objectives, provides a detailed week-by-week breakdown of the course content, which helps in better planning and ensures comprehensive coverage of the topics. This structured approach facilitates a more organized learning experience for philology students and helps language instructors manage the course timeline effectively. It also includes a specific week dedicated to review and assessment preparation which ensures that students have ample time to consolidate their learning, clarify doubts, and prepare for the final assessments. We find it particularly beneficial for first-year philology students who might be new to university-level examinations. Another benefit of Draft E design is two weeks dedicated to practical language skills with language labs, practical exercises, and peer review sessions. This focus on practical application ensures that philology students can directly apply what they have learned, enhancing their linguistic proficiency in a hands-on manner. Additionally, Draft E explicitly outlines course policies, including attendance, late submissions, academic integrity, and accommodations for students with disabilities. This transparency helps set clear expectations from the beginning, ensuring a fair and structured learning environment. Comparing the ULT course designs, it should be noted that both ULT drafts cover similar topics, including the historical development of the Ukrainian language, literary analysis, contemporary media, and the impact of politics on language. However, Draft E's weekly outline provides a more granular approach, ensuring each topic is covered thoroughly within a specific timeframe. It should not be missed that both drafts generated by Copilot and ChatGPT employ a mix of lectures, seminars, group discussions, and multimedia presentations. They also include practical language labs, which are emphasized clearly and appear to be an integral part of the curriculum, ensuring that philology students get ample practice. Both drafts use a variety of assessment methods, including written assignments, oral presentations, and participation in class discussions. Draft E, however, is more specific about the percentage breakdown of assessments and includes a dedicated review week, which is advantageous for student preparation. Ultimately, Draft E for ULT includes detailed course policies and a clear grading policy, providing transparency and setting clear expectations for students whereas Draft D for ULT mentions diverse assessment methods but does not elaborate on policies or grading criteria. Nevertheless, both drafts by Copilot and ChatGPT are designed for a full academic year (two semesters) and are aimed at philology beginners, ensuring equal accessibility for first-year students with no prior exposure to the Ukrainian language or literature. However, it is visible that Draft E provides a more detailed and structured course design, with clear weekly outlines, dedicated time for assessment preparation, and a strong emphasis on practical language skills. These features make it a more student-centered and well-organized course, likely to enhance the learning experience for first-year philology students. Draft D for ULT, while comprehensive, lacks the detailed structure and specific preparation components that Draft E offers. Comparing the course designs for ELT and ULT from both Copilot and ChatGPT reveals distinct approaches and strengths in their frameworks. ChatGPT's course designs are organized on a weekby-week basis, providing clear progression for philology students. This detailed structure includes 27 chapter 1. Designing English and Ukrainian language courses with AI tools: comparative approach CHAPTER 1 practical language labs, an emphasis on historical development, and thematic modules covering literature, media, and politics; another strength lies in its clarity and structured progression, which makes it easier for students to follow and understand the course content. In contrast, Copilot's course designs are organized around thematic modules without a strict week-by-week breakdown. The content covers essential language skills, literature, media analysis, and cultural themes, emphasizing critical analysis and the cultural context of the language. The strength of the approach is encouragement of students to think critically and understand the broader cultural and political dimensions of language. Additionally, the course designs by Copilot and ChatGPT balance language proficiency with cultural understanding, emphasizing practical applications and the socio-political context of language use. Therefore, the main difference between the two tools in designs lies in their structure and focus. ChatGPT's designs are more structured with a clear week-by-week outline, which provides a straightforward progression for students, which when combined with practical exercises, is particularly beneficial for philology beginners. On the other hand, Copilot's designs are organized around thematic modules, allowing for flexibility and deeper thematic exploration. This approach fosters critical thinking and reflection [15] that brings a deeper understanding of cultural and political contexts, enriching the learning experience [38]. In the end, both Copilot and ChatGPT emphasize a balance between language proficiency and cultural understanding. 1.4.3 Benefits and Challenges of AI Integration in ELT/ULT Course Design Following the examples of possible application upon integration of AI, particularly through tools like ChatGPT and Copilot, into ELT/ULT and education, it should be emphasized that AI brings forth a multitude of benefits and challenges in the course design. V. Svyrydiuk et al. [52] reasonably note, "the use of information technologies, components of which include learning platforms or applications, optimizes and improves both classroom and extracurricular independent learning activities of students as a means of mastering written language independently". Among the benefits, the following can be mentioned: 1) ready-to-go draft of an ELT/ULT course to be modified and amended by educators; 2) enhanced interactivity inasmuch ChatGPT and Copilot foster interactive learning experiences, allowing learners to engage in real-time conversations or receive immediate coding support, that fosters active participation and engagement, making learning more dynamic and immersive; 3) personalized feedback as these AI tools offer personalized feedback tailored to individual learner needs, addressing specific language or proficiency areas for improvement, and by providing targeted guidance, they facilitate more effective skill development and learning progression; 4) real-time assistance with which philology students benefit from instant access to language practice or programming support, enabling them to overcome challenges and make progress in their learning journey without delays, which will accelerate learning and boost confidence; 28 Educational policy and reforms: the impact of globalization CHAPTER 1 5) authentic learning opportunities, which are enabled via ChatGPT or Copilot and their authentic language use through conversational interactions, by means of simulating authentic contexts, providing learners with practical, hands-on experience that enhances their skills and prepares them for real-world applications. To the challenges we refer: 1) accuracy and reliability of the information provided, which is paramount for education and educators; it means that educators cannot rely on the provided data and should verify the correctness of everything suggested by AI tools in order to prevent misinformation or errors that could impede learning progress; 2) language and cultural nuances, as AI models may struggle with understanding subtle language nuances or cultural contexts, leading to misinterpretations or inappropriate responses, which may threaten educational ethics, equity, diversity and the like principles in a multicultural world [6]; to mitigate these risks, educators should focus on cultural sensitivity and linguistic accuracy to provide meaningful learning experiences; 3) technical limitations, which means that ChatGPT and Copilot may face technical constraints or compatibility issues with certain platforms or devices, and on the other hand, digital literacy with educators – their age, teaching experience, digital competence, continuous learning skills, etc. may hardly be overestimated; 4) ethical considerations, which are prerequisite to address ethical concerns surrounding algorithmic bias, and the ethical use of AI in educational settings [18], for which educators must adhere to ethical guidelines and policies to safeguard learner privacy and ensure fair and equitable learning experiences. To conclude, while AI integration in ELT/ULT course design offers numerous benefits, including ready-to-go course designs, enhanced interactivity, personalized feedback, real-time assistance, and authentic learning opportunities, educators must also navigate challenges related to accuracy, cultural sensitivity, technical limitations, and ethical considerations to harness the full potential of AI in language education. Among the advantages of ChatGPT and Copilot, the above are just a few possible scenarios how these AI-powered tools may apply for ELT/ULT. For example, in a beginner-level English/Ukrainian course, educators may also incorporate ChatGPT to provide language practice activities. Students can engage in simulated conversations with ChatGPT, practicing common greetings, introductions, and everyday dialogues. Respectively, ChatGPT generates contextually relevant responses, offering immediate feedback and scaffolding language practice in a supportive environment. That means learners will benefit from interactive language practice sessions that enhance fluency and confidence in speaking. Next, in an advanced writing course, educators may integrate ChatGPT into dayto-day performance to provide feedback on student essays. After submitting their essays, students receive automated feedback from ChatGPT, highlighting grammatical errors, suggesting revisions, and providing writing tips. ChatGPT assists learners in self-editing and revising their work, improving writing accuracy and coherence. Educators may build on and take it to group discussion and 29 chapter 1. Designing English and Ukrainian language courses with AI tools: comparative approach CHAPTER 1 reflection and self-reflection activities for further growth and improvement. Ultimately, another application may be a group project-based learning course, where educators utilize ChatGPT to facilitate collaboration and communication among students. ChatGPT serves as a virtual team member, participating in group discussions, providing ideas, and coordinating project tasks. Students interact with ChatGPT to brainstorm ideas, delegate responsibilities, and track project progress, promoting teamwork and collaboration skills development. 1.5 Future Directions and Implications The integration of AI tools, e.g., ChatGPT and Copilot, in ELT/ULT course design opens new avenues for innovation and advancement in language education. Looking ahead, several future directions and implications emerge from which advancements in personalization as part of an ELT/ULT course design may require more focus in research, looking into possibilities to offer more tailored learning experiences that cater to individual learner needs, preferences, and learning styles. ChatGPT and Copilot are transforming language education by enabling personalized learning, collaborative tasks, and multimodal course designs that integrate text, audio, and visuals for immersive experiences. These tools enhance learner engagement while supporting ELT and ULT with AI-powered platforms for global accessibility and inclusivity. However, future development must prioritize ethical AI use, addressing privacy, bias, and decision-making concerns to ensure fair and equitable education. Conclusions The integration of AI tools in ELT/ULT course design holds immense promise for revolutionizing language education practices. Through the exploration of AI tools such as ChatGPT and Copilot, this study has highlighted the potential benefits and challenges associated with leveraging AI technologies in ELT/ULT contexts. It is stressed out that enhancing drafts of possible scenarios for ELT/ULT course designs with interactivity, it is easier and more time-efficient to provide personalized feedback. Offering real-time assistance, AI tools like ChatGPT and Copilot offer unique opportunities to create dynamic and engaging learning environments that cater to the diverse needs of learners. These tools enable educators to facilitate authentic language use, foster skill development, and prepare learners for real-world language and technical challenges. However, alongside these benefits come challenges related to accuracy, cultural sensitivity, technical limitations, and ethical conside rations. Educators must navigate these challenges thoughtfully to ensure the effective and ethical integration of AI technologies in ELT/ULT course design. Future directions for AI integration in ELT/ULT course design include further advancements in AI capabilities, continued research on effective pedagogical strategies, and ongoing professional development for educators. Additionally,