«Research Reviews» (November 20-21, 2025). Prague, Czech republic, 2025
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Publisher.agency: Proceedings of the 11th International Scientific Conference «Research Reviews» (November 20-21, 2025). Prague, Czech republic, 2025. 368p
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Proceedings of the 11th International Scientific Conference 2 UDC 001.1 P 97 Publisher.agency: Proceedings of the 11th International Scientific Conference «Research Reviews» (November 20-21, 2025). Prague, Czech republic, 2025. 368p ISBN 978-0-5765-5562-3 DOI 10.5281/zenodo.17696746 Editor: Božena Kavková, Professor, University of Prague International Editorial Board: Vasyl Bobek Professor, Palacký University of Olomouc Filip Karban Professor, Technical University of Ostrava Miroslav Peterka Professor, Brno University of Technology Radomír Voráček Professor, Masaryk University in Brno Štěpán Baláž Professor, Mendel University Brno David Fabián Professor, University of Pardubice Pavel Štefan Professor, University of West Bohemia Luboš Melichar Professor, University of Ostrava Natálie Tvrdá Professor, University of Silesia, Opava Lukáš Trnka Professor, Technical University of Liberec Viktor Jonáš Professor, University of Hradec Králové Veronika Vrbová Professor, Tomas Bata University in Zlín Adéla Kaňová Professor, Law University in Prague Emil Stejskal Professor, Prague German University [email protected] https://publisher.agency/
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 3 Table of Contents Pedagogical Sciences ARTIFICIAL INTELLIGENCE AS A MEANS OF ENHANCING THE EFFICIENCY OF PEDAGOGICAL ACTIVITY IN HIGHER EDUCATION INSTITUTIONS .............................................................................................................................................................................................. 7 ZHUMASHEVA S.S. BITLEUOV A.A. THE ROLE OF INTERACTIVE TEACHING METHOD IN DEVELOPING COMMUNICATION SKILLS IN FLT ................................................ 17 TALAPOVA A.K. SADIROVA D.M. AI TOOLS IN ENGLISH LANGUAGE TEACHING: OPPORTUNITIES AND CHALLENGES ........................................................................... 28 TALAPOVA A.K. YALKONOVA Y. D. TASK-BASED LANGUAGE TEACHING: BENEFITS AND CHALLENGES FOR SECONDARY SCHOOL STUDENTS ........................................ 41 TALAPOVA A.K. RUSLANOVA R.R. AI-BASED SOLUTIONS TO EMERGING ISSUES IN ESL PRONUNCIATION TRAINING ............................................................................... 53 KIRIYEVA BALAUSSA YERMEKBAYKYZY THE ROLE OF DIGITAL RESOURCES IN TEACHING FOREIGN LANGUAGE EDUCATION .......................................................................... 59 TOISHY TANGSHOLPAN NURLANKYZY ZHUMABEKOVA GALIYA BAISKANOVNA STRUCTURAL-FUNCTIONAL MODEL OF TRAINING 11–13-YEAR-OLD JUDOKAS DURING THE SPECIALIZATION PERIOD ................... 64 ZHARBULOVA AIDANA TOLEGENULY NURZHAN TELAKHYNOV YERKIN ТАҚТАЙШАДАҒЫ БАСКЕТБОЛ ОЙЫНЫ АТАУЫ `COURT IQ` ................................................................................................................ 69 ЕСБАЕВ МЕРЕКЕ МАЛИКОВИЧ ОМАРОВ ТАЛГАТ ДАВЛЕТЖАНОВИЧ CURRENT ISSUES IN EDUCATIONAL DATA ANALYSIS THROUGH ARTIFICIAL INTELLIGENCE ................................................................ 72 K. NIGMETOV TECHNOLOGIES FOR ENHANCING THE PROCESS OF MASTERING FOREIGN LANGUAGE COMMUNICATION IN THE BASIC STAGE OF SECONDARY SCHOOL ................................................................................................................................................................................ 78 ARUZHAN TYNYSHTYK ERTAIKYZY INCLUSIVE PEDAGOGY: STRATEGIES FOR TEACHING STUDENTS WITH LEARNING DIFFERENCES ....................................................... 85 МЫРЗАБЕКОВА ЭЛЬДАНА ЖҮСІПБЕК ЖІБЕК МЫРЗАХАНОВА ДИНАРА IBRAGIMOVA MUKHABBAT IDRISOVNA SYZDYKOVA GAISHA NASYROVNA DEVELOPING SOCIOCULTURAL COMPETENCE IN FOREIGN LANGUAGE LEARNING ............................................................................. 96 KOVTUN ANASTASSIYA SERGEEVNA ZHUMABEKOVA GALIYA BAISKANOVNA THE ROLE OF AI-BASED MOBILE APPLICATIONS IN THE DEVELOPING FOREIGN LANGUAGE LEXICAL COMPETENCE...................... 102 ZHADIL ZHANEL RINATKYZY ZHUMABEKOVA GALIYA BAISKANOVNA CROSS-CULTURAL PRAGMATICS IN EDUCATION .................................................................................................................................. 107 BISSENBAYEVA PERIZAT SAKENKYZY ERBOLATOVA NURAILYM RYSBAIKYZY MYRZAKHANOVA DINARA ОСОБЕННОСТИ ИССЛЕДОВАНИЯ ВЕБ-ПЛАТФОРМЫ ДЛЯ ПОВЫШЕНИЯ УСПЕВАЕМОСТИ УЧАЩИХСЯ В ОБРАЗОВАТЕЛЬНЫХ УЧРЕЖДЕНИЯХ ....................................................................................................................................................................................... 113 АВДИЕВ МАДИЯР ТАЛГАТУЛЫ ЖАСАНДЫ ИНТЕЛЛЕКТТІ ОҚЫТУ ТӘЖІРИБЕЛЕРІ ЖӘНЕ ДАМУ БОЛАШАҒЫ .................................................................................. 119 К.З.ХАЛИКОВА Ә.Д.ТӨРЕКЕЛДИЕВА EXPERTISE MONITORING IN HIGHER EDUCATION AND CHANGES IN REPORTING FORMS ................................................................ 125 SHAKIROVA ARAILY DALELOVNA ADILGAZY AKKU CHE XIAODAN ENHANCING METACOGNITIVE AWARENESS THROUGH DIGITAL TOOLS IN ESL CLASSROOMS ......................................................... 129 RYSBAY AYAULYM YERMANKYZY SHINGAREVA M. YU. THE EFFECTIVENESS OF THE MONTESSORI METHOD IN TEACHING FOREIGN LANGUAGES TO PRESCHOOL CHILDREN................. 135 TALAPOVA A.K. TOROMANOVA M.S. DEVELOPING STUDENTS’ SCIENTIFIC LITERACY THROUGH THE ORGANIZATION OF FIELD-BASED AND PRACTICAL LEARNING ACTIVITIES ............................................................................................................................................................................................... 145 ISSAYEV G.I. NUGMAN R.M.
Proceedings of the 11th International Scientific Conference 4 DEVELOPMENT OF STUDENTS’ LABORATORY AND PRACTICAL SKILLS THROUGH TEACHING THE FUNDAMENTALS OF BIOTECHNOLOGY .................................................................................................................................................................................... 152 ISSAYEV G.I. ZHUMAGALI M.T. METHODOLOGICAL SPECIFICITIES OF INTEGRATING RESEARCH PRACTICES ON THE PHYTOSANITARY STABILITY OF BROAD-LEAVED TREES IN BOTANICAL GARDEN CONDITIONS INTO THE EDUCATIONAL PROCESS .............................................................................. 161 NAKYPOVA ZH.B. GANI I. ISAYEV CRITERION-BASED ASSESSMENT OF GRAMMAR SKILLS FOR SECONDARY SCHOOL STUDENTS ........................................................ 167 ZHUMABEKOVA G.B ABDULASAN N.E Medical Sciences PHARMACOLOGICAL BASIS OF ANTICANCER THERAPY: MODERN ASPECTS AND CLINICAL PROSPECTS .......................................... 174 ARMAN KHOZHAYEV ZHANNA AKIMZHANOVA DANIYAR ABILDINOV LAZZAT ISSA RUMILYAM BAUDINOVA KUNDYZ TYNYSHTYK AYAULYM KOSHKIN GAUHAR NASHEN STROKE AS AN EMERGENCY CONDITION: ANALYSIS OF CLINICAL OUTCOMES AT THE EMERGENCY MEDICAL CARE HOSPITAL IN ASTANA.................................................................................................................................................................................................... 189 OMARBEK ALIYA M. ISKAKOVA SAULE A. INTEGRATING CLINICO-EPIDEMIOLOGICAL INDICATORS, HEMATOLOGICAL PROFILES, AND MELD-NA SYSTEM FOR SEVERITY ASSESSMENT IN LIVER DISORDERS ........................................................................................................................................................ 190 MATHPATI SHREYA B. SALUNKE SANYUKTA K. LOHAR OM S. DR. GUNJEGAONKAR SHIVSHANKAR M. DR. JOSHI AMOL A. Economic Sciences МЕТОДЫ СОВЕРШЕНСТВОВАНИЯ ОРГАНОВ МЕСТНОГО САМОУПРАВЛЕНИЯ В РЕСПУБЛИКЕ КАЗАХСТАН .............................. 204 ШАМУРАТОВА Н.Б. АБДИКЕНОВ Р.К. ГОСУДАРСТВЕННО-ЧАСТНОЕ ПАРТНЕРСТВО КАК МЕХАНИЗМ ФИНАНСИРОВАНИЯ ИНФРАСТРУКТУРЫ ВЫСШИХ УЧЕБНЫХ ЗАВЕДЕНИЙ КАЗАХСТАНА ..................................................................................................................................................................... 208 ТӨЛЕУБАЙ НҰРҚАНАТ АЛМАСҰЛЫ ТУЛЕГЕНОВ ОСМАНГАЛИ СЕМБАЕВИЧ САГНАЕВ ГАЛЫМ БУЛАТОВИЧ INSTITUTIONAL AND INFRASTRUCTURAL PRECONDITIONS FOR THE FORMATION OF THE PETROCHEMICAL CLUSTER IN KAZAKHSTAN ........................................................................................................................................................................................... 213 TOKTAYEVA A.S. MUKHAMEDIYEV B.M. ZEINULLINA A.ZH. UNIVERSITY ENDOWMENT FUNDS: OPPORTUNITIES, RISKS AND EFFECTIVENESS FACTORS IN THE CONTEXT OF GLOBAL PRACTICE ................................................................................................................................................................................................................. 217 KAMAR KOZHAKHMETOVA ТЕНГЕ ПОД ДАВЛЕНИЕМ: КАК ВАЛЮТНЫЕ КОЛЕБАНИЯ ВЛИЯЮТ НА РЫНОК КАПИТАЛА .......................................................... 222 АЛМАСБЕККЫЗЫ Е. РУЗИЕВА Э.А. ЕЛУБАЕВА Ж.М. THE HISTORY OF THE FORMATION OF THE CIVIL SERVICE OF KAZAKHSTAN ...................................................................................... 229 AIBASSOVA NAZIMA AIDAROVNA STRUCTURAL TRANSFORMATION OF KAZAKHSTAN’S INDUSTRY: THE IMPACT OF INNOVATION IMPORT AND LOCALIZATION ON ECONOMIC GROWTH ............................................................................................................................................................................. 233 KUPENOV B.K. TURKEYEVA K.A. ВЛИЯНИЕ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА НА РЫНОК ТРУДА ....................................................................................................... 236 ЖАҚСЫЛЫҚ ДАНА ҚАЗБЕКҚЫЗЫ Technical Sciences ОБЗОР МЕТОДОВ ДЛЯ ПОСТРОЕНИЯ МОДЕЛИ ПРОГНОЗИРОВАНИЯ СОСТОЯНИЯ ГОРОДСКОЙ ВОЗДУШНОЙ СРЕДЫ ......... 239 БАЙМҰҚАН А.Н. ТУЛЕГЕНОВА З.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 5 ИНТЕЛЛЕКТУАЛЬНЫЕ СИСТЕМЫ УПРАВЛЕНИЯ ЭНЕРГОПОТРЕБЛЕНИЕМ В ЗДАНИЯХ: СОВРЕМЕННЫЕ МЕТОДОЛОГИЧЕСКИЕ ПОДХОДЫ И ПЕРСПЕКТИВЫ ПРИМЕНЕНИЯ ...................................................................................................................................... 243 РАХМАНБЕРДИЕВ Э.Д. АХМЕНОВ Н.Е. СЕРІКОВ А.Б. ЛИДАР НЕГІЗІНДЕГІ САНДЫҚ ЖЕР БЕДЕРІ МОДЕЛІН ПАЙДАЛАНА ОТЫРЫП, АУЫЛ ШАРУАШЫЛЫҚ ЖЕРЛЕРІН МАШИНАЛЫҚ ОҚЫТУ ӘДІСІ АРҚЫЛЫ АНЫҚТАУ ........................................................................................................................................................ 247 ХАБАШ ДАНА АВТОКӨЛІК ЖҮРГІЗУШІСІНІҢ ЖАҒДАЙЫН БАҒАЛАУ ӘДІСТЕМЕСІ ЖӘНЕ МОНИТОРИНГ ҚҰРАЛДАРЫ ....................................... 253 СМАКАНОВ БАУЫРЖАН СЕРІКҚАНҰЛЫ УВАЛИЕВА ИНДИРА МАХМУТОВНА ПРИМЕНЕНИЕ МЕТОДОВ ОБРАБОТКИ ЕСТЕСТВЕННОГО ЯЗЫКА (NLP) ДЛЯ КЛАССИФИКАЦИИ КИБЕРУГРОЗ В ПОЛЬЗОВАТЕЛЬСКИХ ОТЗЫВАХ ........................................................................................................................................................... 258 ЖАКУПЖАНОВА АНЕЛЬ АМАНГЕЛДЫКЫЗЫ Agricultural Sciences ТЕХНОЛОГИИ СПУТНИКОВОГО МОНИТОРИНГА ДЛЯ КОНТРОЛЯ СОСТОЯНИЯ СЕЛЬСКОХОЗЯЙСТВЕННЫХ ПОСЕВОВ ........... 268 СЕКРЕНОВА Ж.А. ЕСІМХАН А.Х. Biological Sciences БИОТЕХНОЛОГИЧЕСКИЕ МЕТОДЫ УТИЛИЗАЦИИ СЕЛЬСКОХОЗЯЙСТВЕННЫХ ОТХОДОВ ........................................................... 272 БАРАНБАЕВА Ж.Х. АНДАСБАЕВ М.Н. Psychological Sciences LEGISLATIVE FRAMEWORK FOR ELDERLY CARE IN AZERBAIJAN .......................................................................................................... 276 ABDULLAYEVA ZUMRUD CHINGIZ Philological Sciences MORFOLOJİ YOLLA SİFƏTLƏRİN TƏHLİLİ ................................................................................................................................................ 278 ƏSMAYƏ BƏXTIYAR QIZI ƏKBƏROVA COMPETENCY-BASED PREPARATION OF FUTURE TEACHERS FOR BLENDED LEARNING ................................................................... 281 ABDURAZAKOVA LUIZA BAKTIYAROVNA LANGUAGE DOCUMENTATION, ETHICS, AND ARTIFICIAL INTELLIGENCE: TECHNICAL-ETHICAL CHALLENGES FOR MINORITY LANGUAGES ............................................................................................................................................................................................ 285 ALIYEV SALMAN ALIYEV CEYHUN MAMMADOVA ZEYNAB AKHUNDOV AYAZ THE IMPACT OF DIGITAL TOOLS ON VOCABULARY ACQUISITION IN ENGLISH AS A FOREIGN LANGUAGE (EFL) ............................. 290 RAHILA GARIBOVA GURBANALI DIGITAL TOOLS AND ARTIFICIAL INTELLIGENCE IN ACADEMIC WRITING: POTENTIAL FOR ENHANCING DOCTORAL RESEARCH EFFICIENCY .............................................................................................................................................................................................. 293 GULBANU AUBAKIROVA GLAZUNOVA SVETLANA L’ACCORD DU PARTICIPE PASSE AVEC LES AUXILIAIRES AVOIR ET ETRE EN FRANÇAIS : ANALYSE COMPARATIVE DU GENRE AVEC L’AZERBAÏDJANAIS .................................................................................................................................................................................. 301 ALI ALLAHVERDIYEV Historical Sciences SOCIAL AND POLITICAL CONDITIONS OF THE GERMAN DIASPORA IN KAZAKHSTAN (1930–1940) .................................................. 306 SERIKBAY MAMRAIMOV Physical and Mathematical Sciences DEVELOPMENT OF A MODEL FOR INTEGRATING ARTIFICIAL INTELLIGENCE INTO THE PROCESS OF TEACHING CASE TECHNOLOGIES ....................................................................................................................................................................................... 311 GULZHAN MURSAKIMOVA ZAURE KANAPYANOVA AYBOTA ZHUMAN АDILET QURANBEK МЕЖПРЕДМЕТНЫЕ СВЯЗИ ФИЗИКИ В ШКОЛЕ .................................................................................................................................. 316 РАХЫМБЕКОВ АЙТБАЙ ЖАПАРОВИЧ РАИМБЕК КАЙСАР ШАКЕНУЛЫ Sociological Sciences SOCIAL WELL-BEING OF OLDER PEOPLE AND OPPORTUNITIES FOR RECREATIONAL SPORTS IN URBAN SETTINGS ........................ 319 ASSAUBEK S.S.
Proceedings of the 11th International Scientific Conference 6 CONCEPTUAL APPROACHES TO STUDYING DIGITAL RELIGIOUS IDENTITY: A FOCUS ON MUSLIM WOMEN .................................... 330 UMBET R.S. COGNITIVE PROCESSES IN LANGUAGE LEARNING ................................................................................................................................ 338 AYSU MARDAN ASADOVA Psychological Sciences MULTIDISCIPLINARY APPROACH IN PSYCHOLOGICAL PRACTICE: ANALYSIS OF THE EFFECTIVENESS OF INTEGRATION OF GAME, METAPHORICAL AND GRAPHIC METHODS ........................................................................................................................................... 341 GULNARA HASANOVA Historical Sciences DÜNYA ÖLKƏLƏRİNDƏ KARGÜZARLIQ SƏNƏTİNİN İNKİŞAF TARİXİ ..................................................................................................... 348 HEYDƏR ABBAS OĞLU MƏMMƏDOV Geographic Sciences DÜNYA İQTİSADİYYATININ ARTERİYALARI: ƏN BÖYÜK DƏNİZ LİMANLARININ GEOSİYASİ ROLU ....................................................... 352 ƏLIYEVA ŞƏFƏQ MƏMMƏD QIZI AI AND GIS FOR EARTHQUAKE EARLY WARNING AND EVACUATION PLANNING IN ALMATY ............................................................ 355 TARYBAYEVA AIGERIM OMIRZHAN TAUKEBAYEV
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 7 Pedagogical Sciences ARTIFICIAL INTELLIGENCE AS A MEANS OF ENHANCING THE EFFICIENCY OF PEDAGOGICAL ACTIVITY IN HIGHER EDUCATION INSTITUTIONS Zhumasheva S.S. Candidate of Pedagogical Sciences, Associate Professor, Abai Kazakh National Pedagogical University, Kazakhstan, Almaty Bitleuov A.A. PhD student in “International Relations” at the Sorbonne-Kazakhstan Institute of Abai Kazakh National Pedagogical University, Kazakhstan, Almaty Abstract The rapid digitalization of higher education has positioned artificial intelligence (AI) as a transformative force in teaching and learning. This study explores how AI technologies can enhance the efficiency and quality of pedagogical activity in higher education institutions, focusing on the perceptions and experiences of university lecturers in Kazakhstan. Using a qualitative methodology, ten semi-structured interviews were conducted with academic staff from three universities in Almaty. Thematic analysis revealed that lecturers perceive AI not as a substitute for the teacher, but as a supportive co-instructor that assists in automating routine tasks, personalizing instruction, and providing data-driven insights for evidence-based teaching. The findings indicate that AI enhances pedagogical efficiency when combined with educators’ digital competence, institutional support, and ethical awareness. However, challenges related to infrastructure, professional readiness, and data privacy persist. The study concludes that AI’s pedagogical potential lies in its ability to augment human teaching by fostering creativity, inclusivity, and reflective practice. The research contributes to the growing body of literature on digital transformation in higher education and provides practical implications for universities seeking to integrate AI responsibly into teaching and learning processes. Keywords: artificial intelligence; pedagogical efficiency; higher education; digital transformation; personalized learning; teacher readiness; Kazakhstan; qualitative research Relevance of the Study In the context of rapid digital transformation and the expansion of artificial intelligence (AI) technologies, higher education systems are undergoing profound changes. Traditional models of teaching and learning are no longer sufficient to meet the growing demands for flexibility, personalization, and efficiency in pedagogical activity. The integration of AI tools into the educational process represents a key driver for improving the quality and effectiveness of teaching in higher education institutions. Firstly, AI enables personalized learning, allowing educational programs to adapt to students’ individual pace, learning style, and prior knowledge. This personalization enhances student engagement and academic performance, as noted in recent studies that emphasize the transformative role of AI in learner-centered education (Kuleto, 2021).
Proceedings of the 11th International Scientific Conference 8 Secondly, the application of AI is reshaping the role of the teacher from a transmitter of knowledge to a facilitator and designer of learning experiences. In this context, AI assists educators by automating routine tasks such as assessment, feedback, and administrative processes, thereby freeing time for creative and research-oriented pedagogical work. Thirdly, current research highlights that while the potential of AI in education is widely recognized, teachers’ readiness and awareness remain limited. Many educators lack sufficient training and confidence to effectively integrate AI technologies into their teaching practices (Zhou, 2023; George, 2023). Therefore, studying the conditions for the successful adoption of AI in higher education becomes essential for enhancing pedagogical efficiency. Ultimately, in the era of lifelong learning and hybrid educational models, the use of AI becomes a strategic tool for optimizing the educational process, enhancing learning outcomes, and informing evidence-based teaching decisions (Kakhkharova, 2024). As a result, exploring the possibilities, challenges, and pedagogical implications of AI use in higher education is both timely and socially significant. Thus, this study is relevant as it contributes to understanding how artificial intelligence can enhance the effectiveness of pedagogical activity in universities, offering practical recommendations for educators and policymakers to ensure highquality and adaptive higher education. The aim of the research. The primary aim of this study is to explore how artificial intelligence technologies can enhance the efficiency of pedagogical activity in higher education institutions. The research seeks to identify the ways in which AI can support teaching practices, optimize educators’ workload, and contribute to the improvement of teaching quality and student engagement within the context of Kazakhstani universities. The research question is: How can artificial intelligence contribute to improving the efficiency and quality of pedagogical activity in higher education institutions? Significance of the Study This research is significant for several reasons. First, it contributes to the understanding of AI integration in higher education within the Central Asian and Kazakhstani context a region where empirical studies on this topic remain limited. Second, it provides practical insights for educators and administrators into how AI tools can be effectively implemented to improve teaching efficiency, reduce administrative burden, and enhance student learning outcomes. Furthermore, the findings are expected to inform policy development and professional training programs aimed at increasing teachers’ digital competence and readiness to use AI technologies. By combining theoretical and empirical perspectives, this study expands the academic discourse on the digital transformation of higher education and the evolving role of university educators. Literature Review The integration of artificial intelligence into higher education has become one of the most significant developments shaping the future of pedagogy and institutional effectiveness. Over the past decade, AI technologies have evolved from experimental tools to strategic assets capable of transforming both teaching and university management. Scholars increasingly view AI not only as a set of digital instruments but as a catalyst for rethinking the purposes, methods, and organization of teaching and learning (Zhou, 2023). This literature review synthesizes current research focusing on how AI contributes to improving pedagogical efficiency in higher education, with particular attention to motivational, organizational, and contextual factors within Kazakhstan’s educational landscape. Vinichenko, Melnichuk, and Karácsony (2020) emphasize that the application of AI in universities should be understood through the lens of motivation and human capital management. Their research demonstrates that AI can enhance institutional performance by reducing administrative workloads, improving decision-making processes, and increasing transparency in evaluating teaching outcomes. However, they argue that such benefits are only realized when universities simultaneously foster intrinsic motivation among academic staff. Without psychological readiness and alignment between technological innovation and professional
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 9 incentives, AI integration may encounter resistance, thereby diminishing its efficiency-enhancing potential. From the perspective of teaching and learning, Hooda et al. (2022) explore how AI systems support formative assessment and personalized feedback. Their findings reveal that AIbased assessment tools can identify individual learning gaps, recommend targeted resources, and provide continuous feedback loops that improve student performance. Importantly, the authors caution against over-automation, highlighting that AI should complement rather than replace human pedagogical judgment. This aligns with Zhou’s (2023) broader analysis of technology integration, which argues that effective AI implementation requires a pedagogical framework that retains the educator’s role as a mentor and designer of learning experiences. In Zhou’s view, AI functions best when embedded into adaptive learning environments, predictive analytics, and intelligent tutoring systems that extend human capacity rather than supplant it. The literature on Kazakhstan presents a unique perspective on AI adoption in higher education, reflecting both significant progress and persistent challenges. Orynbassar, Zhumadilova, and Abdykerimova (2024) provide a comprehensive overview of AI’s current use within Kazakhstan’s education system, noting that most universities are still in the early stages of digital transformation. They identify infrastructural limitations, insufficient teacher training, and the absence of unified ethical and methodological standards as major barriers. Nonetheless, their study highlights growing institutional interest in leveraging AI for data-driven decision-making and academic monitoring. Complementary to this, Nurtayeva et al. (2024) examine the broader role of digital technologies in Kazakhstani higher education, arguing that AI represents a strategic enabler for achieving national priorities in education quality and innovation. They emphasize that successful integration requires coordinated efforts between policymakers, administrators, and educators, ensuring alignment between digital transformation strategies and pedagogical practices. Similar concerns are reflected in Ibrayeva et al. (2025), who identify three key conditions for sustainable AI implementation: the development of faculty competencies, the modernization of regulatory frameworks, and the creation of supportive digital infrastructures. At the micro-level of classroom practice, Meiramova and Zagatova (2025) investigate the application of AI-powered smart technologies in French language teaching. Their findings indicate that adaptive systems and intelligent platforms foster learner autonomy, motivation, and differentiated instruction. However, they also underline the need for teachers to acquire new methodological skills to interpret AI-generated analytics responsibly. Yeslyamov (2024) adds to this discussion by focusing on the automation of university processes through software robots that employ AI. His study demonstrates how robotic process automation can streamline administrative tasks, enabling educators to devote more time to mentoring and research, thus improving overall teaching efficiency. Further insights into innovative pedagogical practices come from Zhuzeyev et al. (2024), who explore the integration of AI within culturally grounded teaching models based on Kazakh ethnopedagogy. They conclude that the effectiveness of technological innovations depends largely on their cultural and pedagogical contextualization. Similarly, Buribayev et al. (2023) emphasize the necessity of revising evaluation systems in pedagogical universities, suggesting that AI can contribute to more objective and data-rich assessments of research and teaching performance. Dzhanegizova (2024) situates AI adoption within the broader process of digital transformation in Kazakhstan’s higher education sector. Her analysis shows that while AI offers significant opportunities for innovation, the sustainability of digital transformation depends on institutional leadership, inter-university collaboration, and continuous investment in digital literacy. Collectively, these findings suggest that Kazakhstan’s higher education institutions are transitioning from ad hoc experimentation with AI tools to a more systematic and strategic integration of intelligent technologies into teaching and management. Across the reviewed studies, several common themes emerge. First, AI serves as a multifunctional enabler of
Proceedings of the 11th International Scientific Conference 16 References 1. Buribayev, Y., Khamzina, Z., Safronova, L., Kilybayev, T., & Apendiyev, T. (2023). Evaluation of the effectiveness of scientific research at the pedagogical university of Kazakhstan. «Вестник НАН РК», 401(1), 104-121. 2. Dzhanegizova, A. (2024). Digital transformation of higher education in Kazakhstan: challenges and solutions. Економічний часопис-ХХІ, 209(05+ 06), 42-55. 3. George, B., & Wooden, O. (2023). Managing the strategic transformation of higher education through artificial intelligence. Administrative Sciences, 13(9), 196, doi: https://doi.org/10.3390/admsci13090196 4. Hooda, M., Rana, C., Dahiya, O., Rizwan, A., & Hossain, M. S. (2022). Artificial intelligence for assessment and feedback to enhance student success in higher education. Mathematical Problems in Engineering, 2022(1), 5215722, doi: https://doi.org/10.1155/2022/5215722 5. Ibrayeva, Z., Maimakova, A., Gavrilova, Y., Akerke, A., & Akimbayev, Y. (2025). Problems and prospects for the implementation of artificial intelligence in the educational process of Kazakhstani Universities. Periodicals of Engineering and Natural Sciences, 13(1), 83-96, doi: https://doi.org/10.21533/pen.v13.i1.251 6. Kakhkharova, M., & Tuychieva, S. (2024, April). AI-enhanced pedagogy in higher education: redefining teaching-learning paradigms. In 2024 International Conference on Knowledge Engineering and Communication Systems (ICKECS) (Vol. 1, pp. 1-6). IEEE, doi: https://doi.org/10.1109/ICKECS61492.2024.10616893 7. Kuleto, V., Ilić, M., Dumangiu, M., Ranković, M., Martins, O. M., Păun, D., & Mihoreanu, L. (2021). Exploring opportunities and challenges of artificial intelligence and machine learning in higher education institutions. Sustainability, 13(18), 10424, doi: https://doi.org/10.3390/su131810424 8. Meiramova, S. A., & Zagatova, S. B. (2025, June). AI-Powered Smart Technologies for Enhancing Innovative English Teaching in Higher Education in Kazakhstan. In Proceeding of International Conference on Social Science and Humanity (Vol. 2, No. 3, pp. 861-869), doi: https://doi.org/10.61796/icossh.v2i3.141 9. Nurtayeva, D., Kredina, A., Kireyeva, A., Satybaldin, A., & Ainakul, N. (2024). The role of digital technologies in higher education institutions: The case of Kazakhstan. Problems and Perspectives in Management, 22(1), 562. 10. Orynbassar, M., Zhumadilova, M., & Abdykerimova, E. (2024). Artificial intelligence in Kazakhstan's education system: analysis and prospects. Yessenov science journal, 48(3), 71-76. 11. Vinichenko, M. V., Melnichuk, A. V., & Karácsony, P. (2020). Technologies of improving the university efficiency by using artificial intelligence: Motivational aspect. Entrepreneurship and sustainability issues, 7(4), 2696, doi: http://doi.org/10.9770/jesi.2020.7.4(9) 12. Yeslyamov, S. (2024). Application of software robots using artificial intelligence technologies in the educational process of the university. Journal of Robotics and Control (JRC), 5(2), 359-369. 13. Zhou, C. (2023). Integration of modern technologies in higher education on the example of artificial intelligence use. Education and Information Technologies, 28(4), 3893-3910, doi: https://doi.org/10.1007/s10639-022-11309-9 14. Zhuzeyev, S., Zhailauova, M., Biltekenova, G., Madibayeva, S., & Mukhanova, M. (2024). Impact of innovative teaching methods on the quality of higher education based on Kazakh Ethnopedagogy. Universidad y Sociedad, 16(4), 460-467.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 17 THE ROLE OF INTERACTIVE TEACHING METHOD IN DEVELOPING COMMUNICATION SKILLS IN FLT Talapova A.K. Master of Pedagogical sciences, Kazakh Ablai Khan University of International Relations and World Languages, Almaty, Kazakhstan Sadirova D.M. 4th year student, Kazakh Ablai Khan University of International Relations and World Languages, Almaty, Kazakhstan ABSTRACT The present study investigates the role of the interactive teaching method in developing students’ communication skills in foreign language teaching (FLT). Traditional teacher-centered approaches often limit students’ opportunities for authentic language use, while interactive instruction promotes collaboration, participation, and fluency. A mixed-methods design was employed, combining quantitative and qualitative data. Thirty intermediate-level students were divided into two groups: an experimental group taught through interactive activities—such as pair work, group discussions, role plays, and project-based tasks—and a control group taught traditionally. Data were collected through preand post-tests, classroom observations, questionnaires, and interviews.Findings revealed that the experimental group demonstrated a 25– 30% improvement in communicative competence compared to minimal progress in the control group. Students in the interactive classes showed higher motivation, confidence, and engagement, confirming that learner-centered and communicative techniques significantly enhance language performance. Qualitative data further indicated that interactive tasks foster collaboration, reduce anxiety, and create a supportive classroom environment.The study concludes that interactive teaching is a feasible, efficient, and effective approach for improving communication skills in FLT. Its consistent implementation, supported by teacher training and curriculum adaptation, can transform traditional classrooms into active learning communities. Keywords: Interactive teaching method; communicative competence; foreign language teaching (FLT); student engagement; task-based learning; collaborative learning; learner-centered instruction; classroom interaction. INTRODUCTION The field of foreign language teaching (FLT) has undergone significant transformaons in recent years. Tradional approaches, such as the Grammar–Translaon Method and the Audio– Lingual Method, which focused mainly on grammacal accuracy, memorizaon, and repeon, have been cricized for their limited effecveness in developing students’ communicave skills (Ajaj, 2022). These approaches oen priorize linguisc form over praccal language use, providing few opportunies for learners to pracce English in meaningful contexts. In response, modern methodologies, including Communicave Language Teaching (CLT), Task-Based Language Teaching (TBLT), and Project-Based Learning (PBL), have shied the focus toward student-centered and interacon-based instrucon. These approaches emphasize the praccal use of language as a tool for authenc communicaon, allowing students to engage in acvies that reflect real-world language use (Richards, 2017; Toro, Camacho-Minuche, Pinza-Tapia, & Paredes, 2019).
Proceedings of the 11th International Scientific Conference 18 Within this communicave paradigm, the interacve teaching method has gained increasing aenon. This method priorizes acve parcipaon, peer interacon, and collaborave learning, creang a dynamic classroom environment. Students are engaged in structured acvies such as discussions, problem-solving tasks, role plays, project-based exercises, and pair or group work, all designed to foster meaningful use of language (Ajaj, 2022). By praccing English in interacve situaons, learners apply grammar, vocabulary, and funconal language skills in context, which enhances their ability to communicate effecvely in both academic and real-life scenarios. The interacve teaching method contrasts with tradional teacher-centered models by promong shared responsibility for learning and acve engagement in the classroom. It aligns closely with contemporary approaches such as CLT and TBLT, which place interacon at the heart of language acquision (Eslami & Kung, 2016; Sheripbaeva, 2025). In an interacve classroom, the teacher’s role shis from being the sole source of knowledge to a facilitator who guides, monitors, and supports students while they engage in collaborave learning tasks. Acvies such as pair work allow students to pracce dialogues, clarify misunderstandings, and negoate meaning, while group projects encourage planning, problem-solving, and presentaon skills. Peer teaching, discussions, and cooperave tasks further strengthen learners’ ability to express ideas, respond to others, and develop praccal communicaon skills (Ajaj, 2022; Sheripbaeva, 2025). Despite its recognized benefits, research on the interacve teaching method in FLT classrooms remains limited. Challenges such as rigid curricula, me constraints, assessment demands, and insufficient teacher training may limit the method’s effecve applicaon (Kasumi & Xhemaili, 2023). Nevertheless, evidence suggests that even within a single classroom, structured use of the interacve teaching method can enhance students’ use of English in authenc communicave situaons. Studies show that learners become more fluent, confident, and capable of parcipang in meaningful exchanges when they are regularly engaged in interacve acvies. The present study aims to examine the role of the interacve teaching method in developing students’ communicaon skills in foreign language teaching.The specific objecves of the study are: 1. To examine the theorecal principles of the interacve teaching method. 2. To analyze its applicaon in classroom acvies 3. To evaluate the effecveness of Interacve Teaching Method in improving students’ use of English Accordingly, the study addresses the following research queson: What role does the interacve teaching method play in developing students’ communicaon skills in foreign language teaching? By addressing this queson, the study contributes to the pedagogical understanding of communicaon-oriented instrucon and provides praccal insights for improving the quality and effecveness of foreign language teaching through the interacve teaching method. LITERATURE REVIEW Among foreign and Kazakhstani researchers who have explored the use of the interacve teaching method in foreign language teaching (FLT), Harmer (2015), Richards (2017), Toro, Camacho-Minuche, Pinza-Tapia, and Paredes (2019), Lee and Draja (2019), Zhang (2020), Rao (2019), and Kasumi and Xhemaili (2023) have made significant contribuons to understanding how the interacve method affects students’ communicaon skills. Their studies demonstrate that the interacve method transforms classrooms from teacher-centered to learner-centered environments and promotes meaningful use of English.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 19 The interacve teaching method is designed to engage students acvely in the learning process. Harmer (2015) explains that acvies such as pair work, group discussions, role plays, and project-based tasks, when applied through the interacve method, allow learners to use language in authenc contexts, promong praccal communicaon. These acvies provide opportunies for students to exchange ideas, negoate meaning, and pracce funconal language in a supporve classroom seng. Richards (2017) and Toro et al. (2019) emphasize that structured acvies based on the interacve method improve oral communicaon, fluency, and confidence. They highlight that tasks such as collaborave projects and discussion-based exercises simulate real-life language use, helping students develop the ability to communicate effecvely in various contexts. Similarly, Lee and Draja (2019) invesgated task-based applicaons of the interacve method in secondary classrooms and found that well-sequenced tasks, including pre-task, main-task, and post-task stages, enhance student parcipaon and communicaon pracce. Zhang (2020) examined the integraon of technology-supported exercises with the interacve method and reported that digital tools extend opportunies for authenc language use beyond the classroom. Rao (2019) and Kasumi and Xhemaili (2023) further demonstrated that consistent use of the interacve method, including collaborave tasks and guided peer interacon, increases students’ engagement in classroom communicaon and supports acve learning. In the Kazakhstani context, the applicaon of the interacve method is gradually gaining aenon. Sheripbaeva (2025) highlights that this approach aligns with modern educaonal goals emphasizing student-centered learning and communicave skills in English. The method is especially effecve in enhancing students’ praccal communicaon abilies by providing structured opportunies for speaking, listening, and negoaon in English. Despite the proven benefits, implemenng the interacve method can be challenging. Studies note that limitaons such as rigid curricula, insufficient teacher training, and classroom management issues may hinder its effecve applicaon (Kasumi & Xhemaili, 2023; Toro et al., 2019). Nonetheless, research consistently shows that when the interacve method is systemacally applied, it significantly enhances students’ ability to use English in real communicave situaons, transforming classrooms into dynamic learning environments. Overall, the reviewed literature indicates that the interacve teaching method plays a crucial role in developing students’ communicaon skills in FLT. By combining structured tasks, peer collaboraon, and opportunies for authenc language use, the interacve method fosters acve engagement and praccal language development. Effecve implementaon requires careful planning, teacher facilitaon, and adaptaon to the classroom context to maximize its impact on students’ communicaon abilies. MATERIALS AND METHODS Research Design This study employed a quasi-experimental mixed-methods design to invesgate how the interacve teaching method contributes to the development of students’ communicaon skills in English as a Foreign Language (EFL) classrooms. The design combined quantave and qualitave approaches to ensure comprehensive analysis. The quantave phase measured changes in students’ oral communicaon performance through preand post-tests, while the qualitave phase explored classroom interacon, engagement, and learner percepons through observaons and interviews.
Proceedings of the 11th International Scientific Conference 20 Table 1. Structure of the Quasi-Experimental Design Phase Descripon Instruments Purpose Pre-test Assessment of students’ inial level of communicave skills Oral communicaon test, observaon checklist Establish baseline performance Intervenon Implementaon of interacve teaching method (6 weeks) Pair work, discussions, role plays, projectbased tasks Apply interacve instrucon Post-test Assessment aer the intervenon Same oral communicaon test and observaon Evaluate improvement The independent variable was the interacve teaching method, and the dependent variable was students’ oral communicaon performance. Parcipants The parcipants included 30 secondary school students (aged 16–18) from an intermediatelevel EFL program in Almaty, Kazakhstan. They were divided equally into an experimental group (n = 15), which was taught using the interacve teaching method, and a control group (n = 15), which connued with tradional teacher-centered instrucon. All students had studied English for at least three years and were at comparable proficiency levels according to placement results. Table 2. Overview of Parcipant Characteriscs (N = 30) Variable Category Number of students Percentage Gender Male 13 43 Female 17 57 Age 16 years old 9 30 17 years old 13 43 18 years old 8 27 English proficiency Intermediate level 30 100 Parcipaon was enrely voluntary, and parental permission was secured before data collecon began. Instruments Four tools were employed to ensure valid and reliable data: 1.Preand Post-Speaking Tests – short interacve oral tasks assessing fluency, accuracy, vocabulary, pronunciaon, and interacon strategies. 2.Observaon Checklist – used to record levels of collaboraon, parcipaon, and communicave engagement. 3.Student Reflecon Form – short wrien responses describing progress, challenges, and impressions of interacve lessons.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 21 4.Interview Protocol – semi-structured interviews with eight students (four per group) and the teacher to gather deeper perspecves on classroom communicaon. Table 3. Data-Collecon Instrument Instrument Focus Data Type Speaking test Fluency, accuracy, vocabulary, pronunciaon Quantave Observaon checklist Engagement, cooperaon, interacon quality Qualitave Reflecon form Learners’ self-assessment and atudes Qualitave Interview protocol Experiences and classroom communicaon Qualitave Procedure The research lasted six weeks, divided into three stages: 1.Pre-test phase (Week 1): Both groups completed the same speaking test. Inial observaons established the starng level of classroom parcipaon. Figure 1. Sequence of Research Phases 2.Implementaon phase (Weeks 2–5): • The experimental group engaged in interacve instrucon, including pair and group work, discussions, role plays, and small collaborave projects. • The control group connued tradional instrucon emphasizing grammar explanaon and individual wrien exercises. • Each interacve lesson followed three steps: Preparaon → Interacon → Reflecon. Figure 2. Cycle of an Interacve Lesson
Proceedings of the 11th International Scientific Conference 22 Data Analysis The collected data were examined to determine how the interacve teaching method influenced students’ communicaon skills in FLT. By comparing learners’ performance before and aer the six-week instrucon, it became clear that students involved in interacve tasks showed noceable progress in speaking fluency, confidence, and parcipaon. Observaon notes and reflecon sheets also confirmed that interacve lessons encouraged more acve involvement and created a supporve environment for real communicaon. Overall, the analysis demonstrates that interacve instrucon had a posive impact on developing learners’ oral communicaon abilies. 3.Post-test phase (Week 6): Both groups repeated the oral communicaon test. Observaon records and reflecon sheets were also reviewed to idenfy linguisc and behavioral development. Table 4. Outline of Research Procedure Stage Descripon Duraon Aim Pre-test Inial oral communicaon test Week 1 Measure baseline Implementaon Interacve vs. tradional instrucon Weeks 2-5 Apply treatment Post-test Final communicaon test Week 6 Assess outcomes Data Analysis Quantave data were processed using SPSS soware. Descripve stascs (means and standard deviaons) summarized preand post-test results, and paired-sample t-tests determined the significance of differences between groups. The threshold for stascal significance was set at p < .05. Qualitave data—collected from observaons, reflecons, and interviews—were examined through themac analysis, focusing on recurring paerns such as fluency improvement, interacon behavior, engagement, and confidence in communicaon.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 23 Table 5. Evaluaon Rubric for Oral Communicaon Criterion Descripon Scale Fluency Smooth and natural flow of speech 1-5 Accuracy Correct applicaon of grammar 1-5 Vocabulary Appropriate and varied word choice 1-5 Pronunciaon Clarity and comprehensibility 1-5 Interacon Ability to iniate and maintain dialogue 1-5 Ethical Consideraons The study followed instuonal ethical standards. All parcipants were informed of the research purpose, assured of confidenality, and allowed to withdraw at any stage without consequence. Parental consent and school authorizaon were obtained. All data were anonymized and used solely for academic analysis. RESULTS This secon reports the findings of the pre-test and post-test analyses designed to assess how the interacve teaching method (ITM) influenced students’ communicaon skills in foreign language learning. Both quantave and qualitave results are presented to illustrate improvements in fluency, accuracy, vocabulary use, and interacon skills aer the six-week intervenon. Descripve Stascs Descripve analysis was conducted to compare the experimental and control groups’ performance before and aer the implementaon of the interacve teaching method. The mean scores and standard deviaons for each component of communicave competence are displayed in Table 5.
Proceedings of the 11th International Scientific Conference 24 Table 5. Descripve Stascs for Communicave Competence (N = 30) Component Group Pre-Test M (SD) Post-Test M (SD) Mean Difference Improvement (%) Fluency Experimental 3.05 (0.68) 4.10 (0.54) +1.05 34.4% Control 3.02 (0.65) 3.25 (0.61) +0.23 7.6% Accuracy Experimental 3.12 (0.72) 3.95 (0.57) +0.83 26.6% Control 3.08 (0.70) 3.28 (0.66) +0.20 6.5% Vocabulary Use Experimental 3.01 (0.75) 4.00 (0.59) +0.99 32.9% Control 3.00 (0.73) 3.30 (0.67) +0.30 10.0% Interacon Skill Experimental 2.95 (0.77) 4.08 (0.63) +1.13 38.3% Control 2.97 (0.75) 3.22 (0.70) +0.25 8.4% The results indicate that the experimental group achieved considerable progress across all measured dimensions—especially in fluency and interacon—while the control group showed only minor gains. Paired-Sample t-Test Results A paired-sample t-test was applied to verify whether the observed score differences were stascally significant. Table 6 presents the outcomes for both groups. Table 6. Paired-Sample t-Test Results for Preand Post-Test Scores Component Group t df p-value Significance Fluency Experimental 7.32 14 < .001 Significant Accuracy Experimental 6.75 14 < .001 Significant Vocabulary Use Experimental 7.05 14 < .001 Significant Interacon Skill Experimental 7.89 14 < .001 Significant Fluency Control 1.22 14 > .05 Not Significant Accuracy Control 1.10 14 > .05 Not Significant Vocabulary Use Control 1.34 14 > .05 Not Significant Interacon Skill Control 1.18 14 > .05 Not Significant As shown, the improvements for the experimental group were stascally significant across all areas of communicaon competence (p < .001), while no significant differences were detected in the control group.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 25 Qualitave Findings Data gathered from interviews and classroom observaons supported the quantave results. Themac analysis revealed that students regarded interacve learning as an effecve and movang way to pracce English. They noted beer confidence, increased cooperaon, and improved ability to use the language spontaneously. The main themes are summarized in Table 7. Table 7. Key Themes from Students’ Feedback and Observaons Theme Descripon Example Student Comment Improved Speaking Confidence Learners felt more comfortable communicang in English during pair and group tasks. Now I can speak without worrying about mistakes; I feel more confident in discussions. Stronger Collaboraon Students valued teamwork and peer assistance in language acvies. Working in groups helped me learn from others and share ideas more easily. Acve Parcipaon Interacve lessons made classes more dynamic and engaging. We talked more and listened to each other; lessons became much more interesng. Vocabulary Growth Students recognized an expansion of useful vocabulary through pracce. I learned new words and how to use them naturally in dialogues. Reduced Anxiety Learners reported lower fear of speaking English in front of classmates. I’m not afraid anymore to speak in front of others because everyone takes part. These qualitave insights align with the stascal data, confirming that interacve instrucon encourages meaningful communicaon, collaboraon, and confidence among students in foreign language classrooms. DISCUSSION The findings of this research clearly demonstrate that the interacve teaching method (ITM) significantly enhances learners’ communicaon skills in foreign language classrooms. Quantave analysis revealed notable progress in all components of communicave competence—fluency, accuracy, vocabulary, and interacon skills—for the experimental group (t-test, p < .001). These improvements were much greater than those observed in the control group, where only slight changes occurred. A prominent paern that emerged from the data is the sharp increase in fluency and interacon abilies. This suggests that regular engagement in group discussions, pair dialogues, and collaborave tasks enabled students to use language more naturally and confidently. The results align with Harmer (2015) and Richards (2017), who argue that frequent interacon provides the context for authenc language use. Similarly, Toro et al. (2019) confirmed that structured
Proceedings of the 11th International Scientific Conference 32 Table 2. Demographic Characteriscs of Parcipants (N = 50) Variable Category Teachers (N=45) Students (N=60) Gender Male 8 (18 % ) 26 ( 4 3 % ) Female 37 (82%) 34 ( 5 7 % ) Age /Grade 1 5/Grade 9 - 18 (3 0% ) 1 6/Grade 10 - 22 (37 % ) 1 7/Grade 11 - 20 ( 3 3 % ) Teaching Experience 5 - 10 years 1 5 (33%) - 11 - 15 years 18 (40%) - 16 - 20 years 12 (27%) - Prior AI Experience Yes 12 (27%) 35 (58 % ) No 33 (73%) 25 (42%) Instruments Data were collected using four main instruments administered through digital plaorms: 1. Teacher Preand Post-Intervenon Survey – assessed teachers' digital competence, atudes toward AI, pedagogical confidence, and perceived challenges. Items included "I feel confident using AI tools in my teaching" and "AI technologies improve my lesson planning efficiency." Responses were measured on a 5-point Likert scale. 2. Student English Proficiency and Engagement Survey – evaluated students' self-reported skills in wring, speaking, vocabulary, and listening, as well as movaon and engagement levels. Example items: "I can write grammacally correct sentences in English" and "I enjoy learning English with technology." 3. Classroom Observaon Checklist – structured observaons documented teaching strategies, student parcipaon paerns, technology use, and interacon quality during AI-integrated lessons. 4. Semi-Structured Interviews – conducted via Zoom with fieen teachers and twelve students to gather in-depth perspecves on experiences, benefits, and challenges of AI integraon. All surveys were administered via Google Forms and included both closed-ended (Likert scale) and open-ended quesons. Internal consistency reliability for the surveys was established through pilot tesng (Cronbach's α = .84 for teacher survey; α = .88 for student survey).
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 33 Table 3. Structure of Survey Instruments Section Focus Number of Items Example Item Demographics Background information 5 “How many years have you been teaching English?” Digital Competence Self-assessment of technology skills 6 “I am comfortable using digital tools for teaching.” AI integration Attitudes and practices 8 “AI tools enhance student learning outcomes.” Perceived Challenges Barriers to implementation 7 “Limited access to technology affects AI use.” Learning outcomes Self – reported proficiency 8 “My English writing has improved this semester Procedure The research was conducted during the fall semester of the 2024–2025 academic year and consisted of four main phases: 1. Phase 1: Pre-intervenon Assessment (Week 1) Teachers and students completed baseline surveys via Google Forms to assess their inial digital competence, English proficiency levels, atudes toward AI, and teaching/learning pracces. 2. Phase 2: Teacher Training (Weeks 2–3) Teachers parcipated in a two-week professional development workshop covering: Introducon to AI in educaon and ethical consideraons Praccal training on ChatGPT, Grammarly, and ELSA Speak Designing AI-integrated lesson plans Addressing technical and pedagogical challenges 3. Phase 3: AI Integraon Implementaon (Weeks 4–11) Teachers implemented AI-supported lessons in their classrooms. Students used: ChatGPT for generang wring prompts, receiving feedback on essays, and praccing conversaonal English Grammarly for improving grammar, spelling, and wring style ELSA Speak for pronunciaon pracce and speaking confidence development The researcher conducted weekly classroom observaons using a structured checklist to document teaching strategies, student engagement, and technology integraon paerns. 4. Phase 4: Post-intervenon Assessment (Week 12) Teachers and students completed postintervenon surveys. Semi-structured interviews were conducted with selected parcipants via Zoom to explore their experiences, perceived benefits, and implementaon challenges in greater depth.
Proceedings of the 11th International Scientific Conference 34 Table 4. Summary of the Research Procedure Stage Description Duration Purpose Pre-intervention Baseline assessment of proficiency and attitudes 1 week Establish initial levels Teacher Training Professional development on AI tools 2 weeks Prepare teachers for implementation AI Integration Classroom implementation with observations 8 week Apply AI tools in authentic contexts Post-intervention Final assessment and interviews 1 week Evaluate changes and gather feedback Data Analysis Quantave data from preand post-intervenon surveys were analyzed using SPSS (Stascal Package for the Social Sciences). Descripve stascs (means, standard deviaons, frequencies) were calculated to summarize responses. Paired-sample t-tests were conducted to determine whether differences between preand post-intervenon scores were stascally significant (p < .05). Qualitave data from open-ended survey quesons, classroom observaons, and interviews were analyzed through themac coding. The researcher idenfied recurring themes related to benefits, challenges, and recommendaons for AI integraon. Interview transcripts were coded using an inducve approach to capture parcipants' authenc voices and experiences. The study adhered to all ethical guidelines for educaonal research. Parcipaon was voluntary, and informed consent was obtained from all teachers, students, and parents of minor parcipants. All personal data were anonymized and stored securely. Parcipants were informed of their right to withdraw at any me without penalty. The research protocol was approved by the school administraon and the university research ethics commiee. RESULTS This secon presents the findings from both quantave and qualitave data analyses examining the effecveness of AI integraon in English Language Teaching. Results are organized according to teachers' experiences and students' learning outcomes. Teacher Outcomes Descripve Stascs Table 5 presents the preand post-intervenon means and standard deviaons for teachers' digital competence, pedagogical confidence, and atudes toward AI integraon.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 35 Table 5. Descripve Stascs for Teacher Variables (N=45) Variable Pre-Intervention M (SD) PostIntervention M (SD) Mean Difference Improvement (%) Digital Competence 2.95 (0.82) 3.88 (0.71) +0.93 31.5% Pedagogical Confidence 2.78 (0.89) 3.95 (0.68) +1.17 42.1% Attitude Toward AI 3.12 (0.75) 4.15 (0.62) +1.03 33.0% Lesson Planning Efficiency 2.88 (0.91) 4.02 (0.65) +1.14 39.6% The results indicate substanal improvements across all measured teacher variables, with pedagogical confidence showing the highest gain. Paired-Sample t-Test Results Table 6 displays the stascal significance of preand post-intervenon differences for teacher variables. Table 6. Paired-Sample t-Test Results for Teacher Variables Variable t df p-value Significance Digital Competence 8.12 44 < .001 Significant Pedagogical Confidence 9.45 44 < .001 Significant Attitude Toward AI 8.67 44 < .001 Significant Lesson Planning Efficiency 9.21 44 < .001 Significant All improvements were stascally significant at the p < .001 level, confirming that AI integraon training and implementaon posively influenced teachers' competencies and atudes. Student Outcomes Descripve Stascs Table 7 shows students' self-reported English proficiency and engagement levels before and aer the AI-supported instrucon period.
Proceedings of the 11th International Scientific Conference 36 Table 7. Descripve Stascs for Student Variables (N=60) Variable Pre-Intervention M (SD) PostIntervention M (SD) Mean Difference Improvement (%) Writing Accuracy 3.05 (0.78) 4.12 (0.66) +1.07 35.1% Speaking Confidence 2.88 (0.84) 3.95 (0.69) +1.07 37.2% Vocabulary Knowledge 3.15 (0.72) 4.08 (0.61) +0.93 29.5% Listening Skills 3.22 (0.69) 3.98 (0.58) +0.76 23.6% Learning Motivation 3.10 (0.81) 4.18 (0.63) +1.08 34.8% Engagement 3.08 (0.76) 4.22 (0.59) +1.14 37.0% Students demonstrated improvements across all language skills and affecve variables, with engagement and speaking confidence showing the most substanal gains. Paired-Sample t-Test Results Table 8 confirms the stascal significance of changes in student outcomes.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 37 Table 8. Paired-Sample t-Test Results for Student Variables Variable t df p-value Significance Writing Accuracy 9.85 59 < .001 Significant Speaking Confidence 9.52 59 < .001 Significant Vocabulary Knowledge 8.91 59 < .001 Significant Listening Skills 7.68 59 < .001 Significant Learning Motivation 10.12 59 < .001 Significant Engagement 10.45 59 < .001 Significant All student outcome variables showed stascally significant improvements at the p < .001 level. Qualitave Findings Themac analysis of open-ended survey responses, classroom observaons, and interviews revealed five major themes regarding AI integraon experiences.
Proceedings of the 11th International Scientific Conference 38 Table 9. Themes from Qualitave Data Analysis Theme Description Representative Quote Enhanced Personalization AI tools provided individualized feedback and adaptive learning paths "Grammarly helped me see exactly where my grammar mistakes were, and I could fix them immediately." (Student) Increased Engagement Technology made lessons more interactive and motivating "Students were much more enthusiastic about writing when they could get instant feedback from AI." (Teacher) Time Efficiency AI automated routine tasks, allowing more time for meaningful interaction "ChatGPT helped me create discussion questions faster, so I had more time to actually talk with students." (Teacher) Technical Challenges Infrastructure limitations and connectivity issues hindered consistent implementation "Sometimes the internet was too slow, and we couldn't use the apps properly." (Student) Need for Training Teachers emphasized the importance of ongoing professional development "The initial training was helpful, but I still need more practice to use these tools effectively." (Teacher) Classroom observaons documented increased student parcipaon during AI-supported acvies, with students spending an average of 65% more me acvely engaged in speaking and wring tasks compared to tradional lessons. However, observaons also noted occasional technical disrupons and varying levels of teacher comfort with troubleshoong technology issues. Interview data revealed that both teachers and students appreciated the immediate feedback provided by AI tools, parcularly for wring and pronunciaon. Teachers noted that AI integraon helped them differenate instrucon more effecvely, while students valued the nonjudgmental nature of AI feedback, which reduced anxiety about making mistakes. DISCUSSION The findings of this study provide compelling evidence that AI integraon in English Language Teaching can significantly enhance both teaching effecveness and learning outcomes when implemented through systemac preparaon and pedagogical guidance. The substanal improvements observed in teachers' digital competence, pedagogical confidence, and atudes toward technology demonstrate that professional development plays a crucial role in successful AI adopon. Teachers who inially expressed uncertainty about using AI tools showed marked increases in confidence aer receiving structured training and hands-on pracce, supporng the conclusions of Cogo, Patsko, and Szoke (2024) that teacher preparaon is essenal for effecve technology integraon. The notable gains in students' wring accuracy, speaking confidence, and vocabulary knowledge align with previous research by Dewi (2024) and Kholis (2023), who found that AI-
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 39 powered applicaons provide personalized, immediate feedback that accelerates language acquision. The 35% improvement in wring accuracy can be aributed to Grammarly's real-me error detecon and explanaons, which helped students develop metalinguisc awareness and self-correcon strategies. Similarly, the 37% increase in speaking confidence reflects the impact of ELSA Speak's non-judgmental pronunciaon feedback, which reduced learner anxiety and encouraged more frequent pracce. These findings confirm that AI tools can create a supporve learning environment where students feel comfortable experimenng with language without fear of public embarrassment. The substanal increase in learning movaon and engagement observed in this study supports the theorecal framework of Self-Determinaon Theory, which emphasizes autonomy, competence, and relatedness as fundamental drivers of intrinsic movaon. AI tools fostered autonomy by allowing students to learn at their own pace and revisit materials as needed. They enhanced competence by providing clear, construcve feedback that helped learners recognize their progress. While AI cannot directly fulfill the need for relatedness, it freed up classroom me for more meaningful teacher-student and peer interacons, thus indirectly supporng social connecon. This finding resonates with Zainuddin and Perera's (2019) research on how technology-enhanced learning environments can sasfy learners' psychological needs. However, the qualitave data revealed significant implementaon challenges that must be addressed for sustainable AI integraon. Technical limitaons, parcularly unreliable internet connecvity and insufficient devices, emerged as major barriers in the Kazakhstani context. This confirms Shaikhina's (2020) observaon that infrastructure inequality remains a crical obstacle to educaonal technology adopon in the region. Furthermore, some teachers expressed concerns about over-reliance on AI, echoing Geng's (2023) warnings about the importance of maintaining crical evaluaon of AI-generated content and preserving the irreplaceable human elements of teaching, such as empathy, cultural sensivity, and ethical judgment. The study also highlights the importance of balanced integraon. While AI tools effecvely automate roune tasks such as grammar checking and pronunciaon assessment, they cannot replace the nuanced feedback, emoonal support, and cultural mediaon that human teachers provide. As Shin and Lee (2024) argue, AI should be viewed as a complement to, rather than a substute for, teacher experse. The most successful implementaons observed in this study were those where teachers used AI strategically to enhance specific aspects of instrucon while maintaining their central role in facilitang meaningful communicaon, crical thinking, and intercultural understanding. From a Kazakhstani perspecve, these findings have important implicaons for educaonal policy and pracce. The State Program for the Development of Educaon and Science (2020–2025) emphasizes innovaon and digital literacy as naonal priories. This study demonstrates that achieving these goals requires not only invesng in technological infrastructure but also providing sustained professional development, creang clear pedagogical guidelines, and establishing ethical frameworks for AI use. Kunanbayeva's (2019) competence-based model of language educaon provides a valuable theorecal foundaon for integrang AI in ways that support communicave, cognive, and intercultural competences while respecng Kazakhstan's linguisc and cultural context. CONCLUSION This study confirms that Arficial Intelligence technologies can significantly enhance English Language Teaching when integrated thoughully with sound pedagogical principles and adequate support systems. The research demonstrated measurable improvements in students' language proficiency, learning movaon, and engagement, alongside increased teacher confidence and efficiency in instruconal planning. AI tools such as ChatGPT, Grammarly, and ELSA
Proceedings of the 11th International Scientific Conference 40 Speak proved effecve in providing personalized, immediate feedback that accelerates language acquision and reduces learner anxiety. However, successful AI integraon depends on several crical factors. First, comprehensive teacher training is essenal to develop both technical skills and pedagogical strategies for using AI effecvely. Second, reliable technological infrastructure and equitable access must be ensured to prevent digital divides from widening educaonal inequalies. Third, clear ethical guidelines are needed to address concerns about data privacy, algorithmic bias, and the appropriate balance between automaon and human judgment. Finally, AI should be viewed as a tool that enhances rather than replaces teachers, supporng their experse while freeing them to focus on the irreplaceable human dimensions of educaon. For Kazakhstan's educaonal system, these findings suggest several praccal recommendaons. Schools and universies should invest in sustained professional development programs that go beyond one-me training sessions to provide ongoing support for teachers learning to integrate AI. Policymakers should priorize infrastructure development to ensure all students have equal access to digital learning opportunies. Educaonal instuons should develop instuonal guidelines that address ethical consideraons and establish best pracces for AI use in language classrooms. Future research should examine the long-term effects of AI integraon on language proficiency development, explore how different AI tools can be combined for opmal learning outcomes, and invesgate culturally responsive approaches to AI implementaon in diverse educaonal contexts. As AI technologies connue to evolve, ongoing research will be essenal to ensure that innovaon serves the fundamental goals of educaon: fostering crical thinking, cultural understanding, and the development of competent, confident communicators prepared for global cizenship. When applied with careful aenon to pedagogy, equity, and ethics, AI has the potenal to transform English language educaon by making high-quality, personalized instrucon more accessible while empowering both teachers and learners to achieve their full potenal in an increasingly interconnected world. REFERENCES 1. Cogo, A., Patsko, L., & Szoke, A. (2024). Teachers' percepons of AI integraon in language classrooms. Journal of Educaonal Technology, 15(2), 45–60. 2. Dewi, R. (2024). AI tools for enhancing wring and vocabulary in English language learning. Internaonal Journal of Language Educaon, 12(1), 23–37. 3. Geng, H. (2023). Data privacy and AI in educaonal sengs: Challenges and soluons. Computers & Educaon, 182, 104528. 4. Kholis, N. (2023). Using AI pronunciaon apps to reduce learner anxiety. English Language Teaching Journal, 77(4), 55–68. 5. Kunanbayeva, S. (2013). Educaonal modernizaon in Kazakhstan: Perspecves and challenges. Almaty: Kazakh Naonal University Press. 6. Kunanbayeva, S. (2019). Technology and humanisc values in ELT. Internaonal Journal of Pedagogy, 7(3), 45–60. 7. Shaikhina, G. (2020). Developing intercultural competence with digital tools in Kazakhstan. Eurasian Journal of Applied Linguiscs, 5(1), 33–50. 8. Shin, Y., & Lee, J. (2024). AI-assisted assessment in language educaon: Opportunies and limitaons. Language Learning & Technology, 28(1), 1–20. 9. Zhetpisbayeva, A. (2021). Digitalizaon of educaon in Kazakhstan: Policy and pracce. Educaon and Society, 10(2), 12–27.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 41 TASK-BASED LANGUAGE TEACHING: BENEFITS AND CHALLENGES FOR SECONDARY SCHOOL STUDENTS Talapova A.K. Master of Pedagogical sciences, Kazakh Ablai Khan University of International Relations and World Languages, Almaty, Kazakhstan Ruslanova R.R. 4th year student, Kazakh Ablai Khan University of International Relations and World Languages, Almaty, Kazakhstan ABSTRACT This arcle invesgates the effecveness and challenges of applying Task-Based Language Teaching (TBLT) in secondary school English classrooms. Rooted in communicave and learnercentered theories proposed by Prabhu (1987), Ellis (2019), and Long (2016), TBLT emphasizes meaningful task performance as the core of language acquision. The study employed a one-group experimental design involving 55 secondary school students aged 13–16, using preand post-test quesonnaires administered through Google Forms. The results revealed significant improvements in students’ communicave confidence, movaon, and collaborave skills, with a 24.5% overall increase in engagement and language performance. Observaonal data further confirmed enhanced interacon, reduced fear of errors, and increased task compleon rates. Despite these benefits, the study idenfied challenges related to limited instruconal me, teacher preparedness, and curriculum alignment. The findings highlight TBLT as an effecve approach for developing communicave competence when adapted to contextual realies of secondary educaon. Keywords: Task-Based Language Teaching, communicave competence, learner movaon, secondary school, experimental study, classroom interacon. INTRODUCTION The connuous transformaon of foreign language teaching has brought about a significant transion from tradional, form-focused instrucon toward communicave and learner-centered approaches. The historical dominance of methods such as the Grammar–Translaon Method, the Audio–Lingual Method, and the Presentaon–Pracce–Producon (PPP) model provided a foundaon for structural accuracy but oen neglected authenc communicaon and funconal language use (Harmer, 2015; Brown, 2019). In modern educaonal contexts, parcularly at the secondary school level, language instrucon increasingly emphasizes interacon, meaningful task performance, and learner parcipaon. This shi aligns with the broader goal of preparing students to use English as a tool for real-life communicaon rather than as a subject of academic study. Within this paradigm, Task-Based Language Teaching (TBLT) has emerged as one of the most effecve approaches to promote purposeful language use and acve learning. Originang from N. S. Prabhu’s (1987) Bangalore Project, TBLT has been further developed and systemazed by scholars such as Ellis (2009, 2019) and Willis and Willis (2007). The central principle of TBLT is that language learning occurs most effecvely when learners engage in tasks that reflect real-world purposes, requiring them to use the target language to achieve specific outcomes. Rather than emphasizing isolated linguisc forms, the approach integrates language as a means for achieving
Proceedings of the 11th International Scientific Conference 48 RESULTS Overview of Collected Data Data were obtained from three main sources: (1) a 20-item pre-test and post-test quesonnaire completed via Google Forms, (2) teacher observaon checklists collected across eight lessons, and (3) a short post-lesson survey on perceived engagement and movaon. All 55 students completed both tests and parcipated in all TBLT lessons. Quantave data were analyzed descripvely to determine mean differences, percentage improvements, and category-based trends. Quantave Results from Pre-Test and Post-Test Table 5 summarizes the results of the pre-test and post-test based on the five measured categories: (a) English Learning Confidence, (b) Movaon and Atude, (c) Task Performance, (d) Learning Habits, and (e) Learning Challenges. Each statement was rated on a 5-point Likert scale (1 = Strongly Disagree, 5 = Strongly Agree). Higher scores indicate stronger movaon, confidence, and engagement. Table 5 Preand Post-Test Mean Scores by Category (n = 55) Category Pre-Test Mean Post-Test Mean Mean Difference Improvement English Learning Confidence 3.21 4.08 +0.87 +27.1% Motivation and Attitude 3.47 4.28 +0.81 +23.3% Task Performance 3.15 4.04 +0.89 +28.2% Learning Habits 3.34 4.09 +0.75 +22.4% Learning Challenges* 2.91 2.34 –0.57 –19.6% Overall Mean Score 3.22 4.01 +0.79 +24.5% *Note: Lower scores in the “Learning Challenges” category indicate fewer difficulties after TBLT implementation. The overall mean score increased from 3.22 to 4.01, represenng an average improvement of 24.5% in students’ movaon, engagement, and communicave confidence. The largest gains were observed in task performance (+0.89) and confidence (+0.87), demonstrang enhanced parcipaon and self-expression during classroom tasks. Distribuon of Improvement by Student Group For addional clarity, students were divided into three performance categories according to their post-test results: High improvement (≥ 25%), Moderate improvement (10–24%), and Low improvement (< 10%).
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 49 Table 6 Distribution of Students by Improvement Level (n = 55) Improvement Level Number of Students Percentage of Group (%) High improvement (≥ 25%) 28 50.9% Moderate improvement (10–24%) 20 36.4% Low improvement (< 10%) 7 12.7% As shown in Table 6, 87.3% of students demonstrated measurable improvement aer the four-week intervenon, with over half achieving high improvement scores. Item-Level Mean Comparison To idenfy which aspects of learning improved most significantly, the mean scores for selected representave items were compared between preand post-test responses. Table 7 compares selected quesonnaire items before and aer the intervenon, highlighng the most improved aspects of learning. Table 7 Comparison of Selected Item Means Before and After TBLT Intervention Item (Summary) Pre-Test Mean Post-Test Mean ΔM “I feel confident when speaking English in class.” 3.05 4.15 +1.10 “I enjoy learning English at school.” 3.38 4.36 +0.98 “I like working on group or pair activities.” 3.61 4.44 +0.83 “I can work well in a group to complete a task.” 3.18 4.28 +1.10 “I am afraid of making mistakes when speaking English.”* 3.92 3.24 –0.68 *Note: A decrease in this item indicates reduced anxiety. The items showing the highest improvement were related to collaborave learning and speaking confidence, confirming that TBLT posively influenced communicave interacon and group engagement. Fear of making mistakes decreased notably, indicang greater classroom confidence. Qualitave Observaon Results Teacher observaons collected during the eight TBLT lessons confirmed the quantave outcomes. Students exhibited a gradual increase in parcipaon, group communicaon, and willingness to use English spontaneously. Table 8 summarizes behavioral changes observed over the four weeks.
Proceedings of the 11th International Scientific Conference 50 Table 8 Summary of Observed Classroom Behaviors During the TBLT Intervention Observed Behavior Low Frequency (Weeks 1–2) High Frequency (Weeks 3–4) Change (↑/↓) Student–student communication in English 41% 82% ↑ +41% Voluntary participation during tasks 47% 85% ↑ +38% Use of L1 during task work 62% 29% ↓ –33% Completion of tasks on time 58% 76% ↑ +18% Asking questions or clarifying instructions 36% 64% ↑ +28% These results show that students progressively relied less on their nave language (L1) and communicated more in English during group work. Voluntary parcipaon nearly doubled, and students’ task compleon efficiency improved steadily across sessions. Post-Lesson Engagement Survey Results Aer the final lesson, students completed a brief five-item post-lesson survey about their percepons of TBLT acvies. Table 5 presents the results of the post-lesson engagement survey, summarizing students’ overall percepons of TBLT. Table 9 Students’ Perceptions of TBLT-Based Lessons (n = 55) Statement Mean Rating (1–5) “I enjoyed the new English lessons based on tasks.” 4.58 “I learned to work better with my classmates.” 4.46 “I feel more confident using English in class.” 4.40 “The lessons helped me understand English in real situations.” 4.52 “I would like to continue learning English through similar tasks.” 4.63 The mean ratings ranged from 4.40 to 4.63, showing a strongly positive perception of taskbased lessons. The highest score (“I would like to continue learning English through similar tasks”) suggests high acceptance and engagement with the TBLT approach.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 51 DISCUSSION This research highlights key insights into the effecveness and challenges of implemenng Task-Based Language Teaching (TBLT) in secondary school English educaon. The quantave and qualitave data consistently demonstrated that TBLT fosters significant improvements in students’ communicave confidence, movaon, and task performance. The mean score increase of 24.5% between the pre-test and post-test indicates that students became more engaged, more confident in speaking, and more capable of using English for real communicaon. These findings confirm that task-based instrucon is not only effecve for developing linguisc competence but also instrumental in promong acve learning habits and collaboraon among adolescents. The observed increase in student parcipaon and peer communicaon during the experimental lessons aligns with Ellis’s (2019) asseron that authenc tasks naturally encourage interacon and language use for meaningful purposes. Similarly, Willis and Willis (2007) emphasized that the collaborave nature of tasks allows learners to develop fluency and problemsolving skills through communicave exchanges, a phenomenon also reflected in the present study’s observaon results, where English interacon between students increased by over 40%. These outcomes reinforce the theorecal foundaon that TBLT facilitates language acquision through task engagement, as proposed by Long’s (2016) Interacon Hypothesis. The findings also correspond with Bryfonski and McKay’s (2017) meta-analysis, which confirmed the superior outcomes of task-based approaches in enhancing learner movaon and linguisc accuracy. The increased post-test mean scores in “Movaon and Atude” (+23.3%) and “Learning Habits” (+22.4%) mirror this conclusion, suggesng that when tasks are purposeful and contextually relevant, students develop a posive emoonal connecon to language learning. Addionally, the notable reducon in learning challenges (–19.6%) demonstrates that structured, meaningful acvies can decrease language anxiety and the fear of making mistakes—a common barrier in secondary school communicaon. However, the results also reveal persistent implementaon challenges. Despite overall progress, teachers reported difficules in maintaining task authencity within me constraints and in balancing communicave fluency with grammacal accuracy. These challenges parallel those idenfied by Sholeh (2020), who observed that limited instruconal me, large class sizes, and exam-focused curricula restrict the consistent use of TBLT. Likewise, Kazakhstani researchers Kemelbekova and Abdireimova (2023) noted that while TBLT enhances speaking skills and learner autonomy, students with weaker language foundaons oen struggle to complete complex communicave tasks without linguisc scaffolding. The findings of this study echo those concerns, as several students inially demonstrated hesitaon in group communicaon and required addional teacher support in understanding task instrucons. The integraon of peer collaboraon proved to be one of the strongest elements of success in this experiment. The observed 41% increase in student–student communicaon supports the construcvist view that learning occurs through social interacon and shared problem-solving. This aligns with Nurzhan and Bektemirova’s (2023) emphasis on communicave and construcvist methodologies, such as TBLT and CLIL, as effecve means of integrang language learning with cognive development in Kazakhstani schools. Altogether, the study’s results confirm that TBLT enhances communicave competence and movaon among secondary school students. Nevertheless, its success is highly dependent on contextual adaptaon, teacher preparedness, and instuonal flexibility. Addressing these aspects through professional development and curriculum redesign will be essenal to sustaining the benefits of TBLT in mainstream educaon.
Proceedings of the 11th International Scientific Conference 52 CONCLUSION The findings of this study demonstrate that Task-Based Language Teaching (TBLT) is an effecve method for improving English learning outcomes among secondary school students. By engaging learners in authenc, goal-oriented tasks, the approach significantly enhanced students’ communicave confidence, movaon, and collaborave skills. Quantave evidence from the pre-test and post-test comparison showed measurable gains across all domains, while qualitave observaons confirmed higher parcipaon and reduced anxiety in classroom interacons. However, the research also revealed notable challenges related to implementaon, such as me limitaons, large class sizes, and the need for beer teacher preparaon in designing and evaluang communicave tasks. These barriers mirror global findings and highlight the importance of instuonal support and professional training. Despite these constraints, TBLT proved to be a valuable instruconal approach that promotes meaningful learning experiences and encourages students to use English as a real communicave tool rather than a purely academic subject. For Kazakhstani secondary schools, the results suggest that adopng TBLT can bridge the gap between tradional grammar-based instrucon and modern communicave pedagogy. Future research should explore hybrid task-based models that integrate digital tools and adapve learning resources to support diverse learners more effecvely. Ulmately, when implemented thoughully, TBLT not only strengthens linguisc performance but also culvates movaon, cooperaon, and confidence—skills essenal for lifelong language learning and intercultural communicaon. REFERENCES Brown, H. D. (2019). Teaching by principles: An interacve approach to language pedagogy (5th ed.). Pearson Educaon. Bryfonski, L., & McKay, T. H. (2017). TBLT implementaon and evaluaon: A meta-analysis. Language Teaching Research, 23(5), 603–632. Ellis, R. (2009). Task-based language teaching: Sorng out the misunderstandings. Internaonal Journal of Applied Linguiscs, 19(3), 221–246. Ellis, R. (2019). Essenals of task-based language teaching. Oxford University Press. Harmer, J. (2015). The pracce of English language teaching (5th ed.). Pearson Educaon. Kemelbekova, Z., & Abdireimova, G. (2023). Features of “Task-based Language Teaching” in the development of English speaking skills. Bullen of Kazakh Ablai Khan University of Internaonal Relaons and World Languages. Series “Philology”, 2(1), 45–52. Long, M. H. (2016). Second language acquision and task-based language teaching. WileyBlackwell. NamazianDost, R., Bohloulzadeh, G., & Pazhakh, A. (2017). The effect of task-based language teaching on movaon and grammacal achievement of EFL students. Internaonal Journal of Applied Linguiscs and English Literature, 6(5), 56–63. Nurzhan, A. S., & Bektemirova, S. (2023). The role of construcvist approach in subject language integrated learning (CLIL). Bullen of the Al-Farabi Kazakh Naonal University. Series “Philology”, 3(1), 88–96. Prabhu, N. S. (1987). Second language pedagogy. Oxford University Press. Saputro, H., Hima, D. D., & Farah, N. (2021). Teachers’ percepons of task-based language teaching in EFL classrooms. Internaonal Journal of Language Educaon, 5(4), 222–234. Sholeh, M. B. (2020). Task-based language teaching (TBLT): Benefits and challenges in EFL classroom. Journal of English Educaon and Teaching (JEET), 4(2), 256–267. Willis, D., & Willis, J. (2007). Doing task-based teaching. Oxford University Press.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 53 AI-Based Solutions to Emerging Issues in ESL Pronunciation Training Kiriyeva Balaussa Yermekbaykyzy 1st-year student, Educational Program 7M01701 – Foreign language: two foreign languages, Scientific Advisor: Anafinova M.L., Associate Professor, Astana International University, Astana, Kazakhstan Annotaon Recent advances in Arficial Intelligence have challenged long-established assumpons about how pronunciaon should be taught and learned in ESL classrooms. Rather than replacing tradional instrucon, AI complements it by offering adapve and data-informed feedback that addresses the limitaons of convenonal teaching methods. This paper explores the theorecal foundaons and pedagogical implicaons of implemenng AI-driven tools such as Automac Speech Recognion (ASR) and Natural Language Processing (NLP) for enhancing phonec competence. Emphasis is placed on how these technologies support learner autonomy, provide real-me correcve feedback, and facilitate individualized pronunciaon development. The discussion also considers socio-construcvist perspecves, underscoring the importance of interacon, scaffolding, and human–AI collaboraon in effecve pronunciaon pedagogy. While AI applicaons demonstrate substanal potenal for improving accuracy and movaon, challenges related to algorithmic fairness, privacy, and teacher mediaon remain central to their responsible integraon. Keywords: arficial intelligence, pronunciaon training, ESL, phonec competence, ASR, adapve learning, feedback, language technology, movaon, accessibility Introducon In the era of globalizaon and digital transformaon, English has solidified its posion as the most widely used medium of internaonal communicaon. However, one of the most persistent challenges in English as a Second Language (ESL) learning is pronunciaon. Accurate pronunciaon is essenal for intelligibility, self-confidence, and effecve communicaon, yet many learners connue to struggle with it due to limitaons in tradional teaching approaches, insufficient feedback, and lack of exposure to authenc language input. The rise of Arficial Intelligence (AI) technologies has brought new possibilies for addressing these long-standing problems. AIpowered tools can analyze speech, detect pronunciaon errors, and provide immediate, personalized feedback — offering opportunies that tradional classroom sengs cannot [1]. This paper explores AI-based soluons to emerging issues in ESL pronunciaon training, discussing how such technologies can enhance learning effecveness, accessibility, and individualizaon. Theorecal Background Pronunciaon forms the acousc foundaon of intelligible communicaon and plays a central role in overall communicave competence. According to Canale and Swain’s framework of communicave competence, language mastery involves grammacal, sociolinguisc, discourse, and strategic dimensions [2]. Among these, phonec and phonological accuracy directly influence a speaker’s comprehensibility, as even minor deviaons in vowel quality, stress placement, or intonaon can alter meaning or reduce listener understanding. Consequently, pronunciaon instrucon remains an indispensable component of ESL pedagogy, linking linguisc knowledge with real-world oral interacon.
Proceedings of the 11th International Scientific Conference 54 Tradional approaches to pronunciaon training have historically relied on repeon, imitaon, and auditory modeling, guided by teacher feedback [3]. While these methods foster awareness of arculaon and rhythm, they are oen constrained by subjecve evaluaon, limited class me, and unequal aenon among learners. Moreover, many instructors lack formal phonec training, resulng in inconsistent correcon and reduced learner confidence. These limitaons have led to the exploraon of technology-enhanced pronunciaon instrucon (TEPI), where computer-assisted tools supplement human instrucon through structured auditory input and visualized feedback. The emergence of Arficial Intelligence (AI) in language pedagogy introduces a transformave paradigm. Unlike stac pronunciaon soware, AI systems employ machine learning algorithms capable of processing large speech datasets to idenfy phonological paerns, track learner progress, and predict individualized learning needs [4]. Through Automac Speech Recognion (ASR) and Natural Language Processing (NLP), AI can analyze subtle acousc variaons such as voice onset me, stress ming, pitch contour, and segmental precision. These analyses generate immediate and specific feedback on pronunciaon accuracy, enabling learners to monitor their own performance dynamically and independently. The pedagogical value of AI-driven pronunciaon tools also aligns with Vygotsky’s socioconstrucvist theory of learning, which emphasizes scaffolding, guided interacon, and the Zone of Proximal Development (ZPD) [5]. In this theorecal context, AI acts as a digital scaffold that supports learners’ movement from assisted to autonomous pronunciaon pracce. It offers connuous feedback and tailored guidance that complement the teacher’s role, bridging the gap between individual experimentaon and expert correcon. Similarly, from the perspecve of Cognive Load Theory, AI can distribute mental processing demands by breaking pronunciaon tasks into manageable units, thus prevenng cognive overload and facilitang more effecve learning [6]. Furthermore, the integraon of AI aligns with the principles of Communicave Language Teaching (CLT) and learner autonomy, where technology funcons not merely as a delivery mechanism but as an interacve agent fostering self-regulated learning. Learners gain control over pacing, repeon, and self-assessment, which encourages metacognive awareness of pronunciaon processes. AI, therefore, transforms pronunciaon instrucon from a teachercentered to a learner-centered, data-driven pracce, enabling both precision in arculaon and confidence in communicaon. Methodology This study adopts a qualitave, analycal, and comparave approach to invesgate the potenal of AI-driven tools in enhancing ESL pronunciaon training. The research design is based on a systemac literature review combined with content analysis of empirical and theorecal works published between 2018 and 2025. The purpose of this approach is to idenfy major paerns, innovaons, and challenges that characterize the intersecon of arficial intelligence and phonec instrucon in second language acquision. Academic databases such as Scopus, ERIC, and Google Scholar were searched using the key terms AI pronunciaon training, ESL phonecs, speech recognion in educaon, and intelligent CALL systems. Inclusion criteria focused on peer-reviewed studies that examined (a) the effecveness of AI-based pronunciaon feedback, (b) learner engagement and movaon, and (c) the pedagogical integraon of AI into ESL programs. A total of 45 sources met the selecon criteria and were analyzed for recurring themes and methodologies.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 55 In addion to the literature review, the study conducted a comparave analysis of several leading AI pronunciaon applicaons: Elsa Speak, SpeechAce, Google’s Pronunciaon Tool, and Duolingo’s AI-based speech recognion module. Each of these plaorms was evaluated according to four parameters: 1. Accuracy of feedback — how precisely the system idenfies phonec and prosodic errors; 2. Pedagogical adaptability — how feedback is customized according to the learner’s level and first language influence; 3. User engagement — whether the interface and learning design sustain movaon and selfdirected learning; 4. Integraon potenal — the ease of combining the tool with tradional classroom instrucon. Through this methodology, the paper seeks to synthesize both the technological and pedagogical dimensions of AI-assisted pronunciaon learning, highlighng how algorithms translate linguisc data into aconable feedback and how this feedback transforms learner behavior. The emphasis on both empirical evidence and conceptual frameworks ensures that findings are grounded in both educaonal theory and technological realism. Discussion Personalized Feedback and Error Detecon The integraon of AI in pronunciaon training has redefined how learners receive feedback. Unlike tradional methods where teachers rely on auditory judgment, AI systems employ speech recognion algorithms and acousc modeling to compare learner output with nave benchmarks [7]. This allows for a level of diagnosc precision impossible in most classroom sengs. For instance, Elsa Speak’s deep neural network analyzes micro-level arculatory deviaons in vowels and consonants, mapping them onto phonec spectrograms to provide visualized feedback [8]. Such mulmodal input (auditory + visual) helps learners develop phonological awareness, a key factor in achieving long-term pronunciaon improvement. The adapve algorithms connuously recalibrate based on learner performance, progressively targeng specific pronunciaon weaknesses. This approach aligns with Schmidt’s Nocing Hypothesis, suggesng that learners improve when they can consciously perceive the gap between their own output and the target form [9]. AI effecvely operaonalizes this hypothesis by providing immediate, perceivable feedback loops. Aspect Tradional Methods AI-Based Methods Feedback Teacher-provided, oen delayed Immediate, automated, data-driven Personalizaon Limited, same tasks for all learners Adapve to learner’s specific pronunciaon errors Pracce Opportunies Restricted to classroom me Available anyme through mobile or online plaorms Error Detecon Based on teacher percepon Based on ASR/NLP analysis of acousc paerns Learner Autonomy Dependent on teacher input Promotes self-directed learning Movaon May decline due to lack of progress visibility Enhanced through real-me progress tracking Comparison Table of Tradional and AI-Based Pronunciaon Training Approaches
Proceedings of the 11th International Scientific Conference 56 Addressing Anxiety and Movaon Issues Pronunciaon training has tradionally been associated with high affecve barriers — embarrassment, fear of judgment, and reluctance to speak. AI-based tools migate these barriers by creang a safe, private, and judgment-free learning environment [10]. Learners can pracce repeatedly without social pressure, leading to increased confidence and self-efficacy. Furthermore, the gamificaon and progress-tracking features integrated into modern AI tools enhance movaon through tangible goal-seng and rewards [11]. According to Gardner’s socio-educaonal model of movaon [12], sustained engagement depends on both intrinsic interest and posive atudes toward the learning process. AI applicaons that visualize progress graphs, streaks, and performance badges contribute to this sustained movaon by quanfying improvement and fostering a sense of accomplishment. Accessibility and Inclusivity One of the transformave impacts of AI pronunciaon tools is their role in democrazing access to high-quality phonec training. Mobile-based applicaons make pronunciaon pracce possible for learners in geographically or economically disadvantaged regions [13]. Cloud-based AI systems can funcon even on low-end devices, reducing inequality in language learning opportunies. Importantly, advances in accent-aware AI allow for beer inclusivity across linguisc backgrounds. Algorithms trained on mullingual datasets can disnguish between interference paerns caused by specific first languages (L1), such as vowel reducon among Russian speakers or aspiraon issues among Japanese learners [14]. This localizaon of AI models ensures that correcve feedback is linguiscally sensive, avoiding the “one-size-fits-all” approach of earlier CALL systems. Data-Driven Progress Monitoring AI systems collect extensive speech data that can be processed into predicve learning analycs, offering valuable insights for both teachers and learners. Through dashboards and progress reports, learners can monitor accuracy rates, rhythm consistency, and segmental arculaon scores [15]. Teachers, in turn, can use aggregated data to diagnose class-wide trends or individual difficules. Such data-informed pedagogy marks a shi from intuion-based teaching to evidence-based decision-making [16]. Chen et al. demonstrated that when instructors integrate AI-generated pronunciaon analycs into their lessons, student retenon and engagement levels increase by up to 30% [17]. In this sense, AI funcons as both a diagnosc and formave assessment tool, supporng connuous, data-supported learning cycles. Challenges and Ethical Consideraons Despite the progress, several crical limitaons persist. First, speech recognion systems are sll prone to accent bias, parcularly toward non-nave phonec paerns [18]. This can lead to inaccurate error detecon or culturally biased judgments of “correctness.” Second, overreliance on AI risks reducing the human dimension of learning. Pronunciaon involves not only arculaon but also expressive and sociocultural aspects — elements that machines cannot fully replicate [19]. Ethical concerns also arise regarding data privacy, since AI systems rely on connuous voice recording and cloud storage [20]. Instuons must ensure compliance with internaonal standards such as the General Data Protecon Regulaon (GDPR) and implement transparent data-handling pracces. Pedagogically, integrang AI requires teacher training and curricular restructuring to avoid technological misuse. Teachers need to act as mediators who contextualize AI feedback and help students interpret it meaningfully within communicave contexts.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 57 Integraon into Pedagogical Pracce The ulmate success of AI-based pronunciaon training depends on how effecvely it is embedded into classroom pedagogy. AI should complement, not replace, human instrucon. A blended approach — where learners use AI tools for independent pronunciaon pracce and then apply these skills in communicave classroom tasks — ensures both fluency and accuracy [21]. Reinders and Lai [22] argue that teachers’ roles must evolve from “transmiers of knowledge” to facilitators of intelligent learning environments. Instructors should integrate AI feedback into acvies such as peer correcon, role-plays, or phonec awareness workshops. This synergy of technological precision and human empathy creates a holisc pronunciaon learning experience, maximizing both cognive and affecve engagement. Conclusion Arficial intelligence has transformed pronunciaon training in ESL by providing personalized, immediate feedback. It helps learners improve accuracy, confidence, and movaon through data-driven analysis. Unlike tradional methods, AI allows connuous and independent pracce anywhere and anyme. However, technology should complement rather than replace human teaching. The most effecve approach combines AI precision with the teacher’s guidance and emoonal support. References 1. Li, J. Arficial Intelligence in Language Learning: A Review of Emerging Technologies in Pronunciaon Training // Journal of Educaonal Technology Development and Exchange. – 2023. – Vol. 16, No. 2. – P. 45–59. 2. Canale, M., Swain, M. Theorecal Bases of Communicave Approaches to Second Language Teaching and Tesng // Applied Linguiscs. – 1980. – Vol. 1, No. 1. – P. 1–47. 3. Celce-Murcia, M., Brinton, D. M., Goodwin, J. M. Teaching Pronunciaon: A Course Book and Reference Guide. – 2nd ed. – Cambridge: Cambridge University Press, 2010. – 456 p. 4. Levis, J. M., Sonsaat, S. Advanced Speech Technologies and Intelligent CALL: New Direcons in Pronunciaon Research // Language Learning & Technology. – 2021. – Vol. 25, No. 1. – P. 1–14. 5. Vygotsky, L. S. Mind in Society: The Development of Higher Psychological Processes. – Cambridge, MA: Harvard University Press, 1978. – 159 p. 6. Sweller, J. Cognive Load Theory and Instruconal Design Principles // Learning and Instrucon. – 2019. – Vol. 60. – P. 1–10. 7. Neri, A., Cucchiarini, C., Strik, H. Feedback in Computer-Assisted Pronunciaon Training: Technology and Pedagogical Choices // Computer Assisted Language Learning. – 2018. – Vol. 31, No. 4. – P. 429–452. 8. Zhang, Y., Wang, L. Deep Neural Network-Based ESL Pronunciaon Assessment // Speech Communicaon. – 2022. – Vol. 135. – P. 25–39. 9. Schmidt, R. Consciousness and Foreign Language Learning: A Tutorial on the Role of Aenon and Awareness // Aenon and Awareness in Second Language Acquision. – Honolulu: University of Hawai‘i Press, 1990. – P. 1–63. 10. Lee, H. Reducing Speaking Anxiety through AI-Based Language Training Tools // TESOL Quarterly. – 2020. – Vol. 54, No. 3. – P. 625–648. 11. Müller, T., Griffiths, C. Gamificaon and Movaon in Language Learning Apps // Innovaon in Language Learning and Teaching. – 2021. – Vol. 15, No. 5. – P. 458–473. 12. Gardner, R. C. Social Psychology and Second Language Learning: The Role of Atudes and Movaon. – London: Edward Arnold, 1985. – 208 p.
Proceedings of the 11th International Scientific Conference 64 STRUCTURAL-FUNCTIONAL MODEL OF TRAINING 11–13-YEAR-OLD JUDOKAS DURING THE SPECIALIZATION PERIOD Zharbulova Aidana Abai Kazakh National Pedagogical University, Almaty, Kazakhstan Tolegenuly Nurzhan Abai Kazakh National Pedagogical University, Almaty, Kazakhstan Telakhynov Yerkin Abai Kazakh National Pedagogical University, Almaty, Kazakhstan Abstract. This article examines the complex issues of training young judokas aged 11–13, their morphofunctional characteristics, and presents a structural-functional model aimed at optimizing the training process. The model includes a set of special exercises designed to develop muscle strength, respiratory muscles, joint mobility, and balance stability. The article outlines the theoretical foundations of the model, its practical application, a monitoring and evaluation system, and practical recommendations. Keywords: judo, adolescents, 11–13 years, training, structural-functional model, pedagogical monitoring, special exercises. Introduction Judo is a globally recognized combat sport, and since more than 80,000 people practice it in Kazakhstan, improving the methodological and scientific foundations of training young athletes is highly relevant. Special attention is given to the specialization stage for athletes aged 11–13, as during this period active morphofunctional changes occur: muscle mass increases, motor skills improve, and an important developmental surge in sports mastery is observed. The aim of the article is to theoretically and experimentally substantiate the structuralfunctional model of training young judokas during the specialization period based on the application of a set of special exercises. Judo training requires high physical and psychophysiological demands from young athletes. Children aged 11–13 experience wave-like development of their skeletal and muscular systems, changes in respiratory reserves, and intensive development of coordination abilities. Some existing programs do not fully consider age-specific characteristics, which may cause health risks and reduce training efficiency. Therefore, a specialized exercise set and a systematic pedagogical monitoring model are necessary for this age group. At the age of 11–13, speed-strength and coordination abilities grow significantly. Developing the respiratory system is one of the key factors that enhance endurance and recovery efficiency. The three levels of pedagogical monitoring (periodic, current, operational) help regulate the training process and optimize training loads. Structural-Functional Model Model Components: 1. Methodological component – principles and guidelines for annual, meso-, and microcycles. 2. Content component – a special exercise complex (strength, breathing, mobility, coordination). 3. Pedagogical monitoring component – tests, health indicators, and recovery procedures.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 65 4. Main principles of the model: individualization, systematic progression, load moderation, safety, and consistent pedagogical monitoring. Special Exercise Complex • Strength exercises: body-weight exercises (pull-ups, static platform holds) • Breathing exercises: diaphragmatic breathing, interval hyperventilation (within medical safety norms) • Mobility: dynamic and static stretching, joint mobility exercises • Coordination & balance: balance board training, reaction drills, hand-eye coordination • Special judo drills: high-intensity but short-interval pulse-zone exercises integrating technique and tactics Below are ready-to-use tables for inclusion in the research article and for daily coaching practice. Table 1. Annual Training Cycle – Main Components Period Objective Main Content Duration (weeks) Preparatory (initial) General physical fitness, increased respiratory reserve Running, general strength, breathing exercises, coordination 8–10 Main preparation Specific strength, technicaltactical training Special exercise complex, randori, sparring 20–24 Precompetition High-intensity load, competition tactics Interval strength-speed work, tactical skills 8–10 Recovery Reduced load, regeneration Light training, physiotherapy, games 4–6 Table 2. Weekly Microcycle Example (Ages 11–13) Day Section Main Tasks Load Level Monday General physical training Cardio 20–25 min, strength 30 min Moderate Tuesday Technique & coordination Technical drills, balance exercises Moderatehigh Wednesday Special endurance Interval running, breathing exercises High Thursday Tech-tactical Sparring, tactical drills Moderatehigh Friday Recovery + mobility Yoga-type exercises, stretching Low Saturday Interactive training Technical games, mini competitions Moderate Sunday Rest/medical control Check-ups, subjective assessment –
Proceedings of the 11th International Scientific Conference 66 Table 3. Special Exercise Complex (Examples) Component Exercise Reps/Duration Purpose Strength Body-weight squats 3×10–12 Strengthening lower body Endurance Plank (static) 3×30–45 sec Trunk stabilization Breathing Diaphragmatic breathing 10 times/day Improve lung ventilation Mobility Dynamic leg stretching 3×12 Enhancing joint mobility Coordination Balance board relaxation drills 4×1 min Developing balance Special judo Combined throw technique drills 5–8 combinations Motor automation Table 4. Pedagogical Monitoring System (Test Set) Tool Description Frequency Output Indicators Morphology Height, weight, body proportions Once per month Morphological profile Physical fitness tests 30 m sprint, jump, 5×5 sec test Every 2 weeks Speed & strength indicators Respiratory function VC, FVC, FEV1/VC% Once per month Respiratory reserve Psychophysiology Attention, reaction time Once per month Cognitive indicators Subjective questionnaire General state, fatigue Weekly Load tolerance Table 5. Safety and Load Restrictions for Coaches Category Recommended Load Notes 11 years 6–8 hours per week Focus on technique, minimal heavy loads 12 years 7–9 hours per week Short high-intensity periods; limited frequency 13 years 8–10 hours per week Gradual load increase; medical monitoring required Methodological Guidelines and Practical Application 1. Each exercise must be adapted to age-specific characteristics with incremental load increases. 2. When introducing breathing exercises, medical safety and individual indicators must be considered. 3. Pedagogical monitoring should be conducted using automated systems, with creation of a unified database. Brief Description of the Experimental Program The experimental part included an adaptation period, main preparation phase, and evaluation periods. The control group followed a standard program, while the experimental group used the proposed structural-functional model. Morphofunctional, technical, and psychological indicators were compared throughout the assessment period. Results and Discussion (Project/Example Description) The model produced positive changes in the experimental group: improved general physical fitness, increased respiratory reserves, enhanced coordination skills, reduced injuries, and
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 67 better competition dynamics. Systematized pedagogical monitoring supported more effective decision-making for coaches. Conclusion 1. Current training programs do not fully account for the age-specific characteristics of 11– 13-year-old judokas. 2. The proposed structural-functional model is based on a special exercise complex and includes consistent pedagogical monitoring. 3. Practical application of the model can ensure positive dynamics in sports performance and health indicators. Practical Recommendations • Integrate the model’s key principles into Youth Sports Schools and Olympic Reserve programs. • Develop a methodological guide for coaches and conduct training seminars. • Digitalize pedagogical monitoring and create a centralized data repository. Special Recommendations (Sample 90-minute Training Session) 1. Warm-up — 15 minutes (dynamic stretching, light running) 2. General strength — 20 minutes (body-weight exercises) 3. Special technique — 25 minutes (technical drills + combinations) 4. Sparring/tactics — 20 minutes (short-interval work) 5. Recovery — 10 minutes (low-intensity movements, breathing exercises) References 1. Bompa, T., & Buzzichelli, C. (2018). Periodization: Theory and Methodology of Training. Human Kinetics. 2. Franchini, E., Sterkowicz, S., & Takito, M. A. (2014). Body weight and physiological characteristics of judo athletes. Sports Medicine, 45(3). 3. Sato, N., & Okano, S. (2016). Judo Training Methods and Pedagogy. Kodansha. 4. Paillard, T. (2017). Plasticity of the postural function to sport and/or motor experience. Neuroscience & Biobehavioral Reviews, 72. 5. Miochin, V. M. (2020). Theory and Methodology of Training Young Athletes. Sport. 6. Ayanbayev, B. B., & Tleugaliev, A. Zh. (2019). Judo: Textbook. KazAST. 7. Ilyin, E. P. (2016). Psychophysiology of Physical Education and Sport. Piter. 8. Malina, R. M., Bouchard, C., & Bar-Or, O. (2004). Growth, Maturation, and Physical Activity. Human Kinetics. 9. Franchini, E. (2019). Training load monitoring in judo. International Journal of Sports Physiology and Performance. 10. Kuznetsov, V. S. (2017). Age Anatomy and Physiology. Akademiya. 11. Ito, M. (2015). Judo Techniques and Their Physiological Demands. Judo Academy Press. 12. Godik, M. A. (2018). Sports Metrology. Fizkultura i Sport. 13. Plowman, S., & Smith, D. (2020). Exercise Physiology for Health, Fitness, and Performance. LWW. 14. Matveev, L. P. (2014). Theory and Methodology of Physical Culture. Fizkultura i Sport. 15. Franchini, E., & Julio, U. (2019). Judo combat physiological responses. Journal of Strength and Conditioning Research. 16. Agabekov, T. S. (2021). Theory of Training Young Athletes. Bilim. 17. Aleksandrov, A. A. (2018). Breathing Gymnastics in Sports. Sovetskiy Sport. 18. Bezodis, N., Brazil, A., & Wilson, C. (2021). Strength and Conditioning for Combat Sports. Routledge.
Proceedings of the 11th International Scientific Conference 68 19. Sterkowicz, S. (2015). Special judo fitness tests. Biology of Sport. 20. Turlybekov, A., & Kasymov, E. (2020). Basics of Sports Medicine. KazAST.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 69 ТАҚТАЙШАДАҒЫ БАСКЕТБОЛ ОЙЫНЫ АТАУЫ «COURT IQ» Есбаев Мереке Маликович Дене шынықтыру пәні мұғалімі Омаров Талгат Давлетжанович Дене шынықтыру пәні мұғалімі «сарапшы» Жаратылыстану-математика бағытындағы Назарбаев Зияткерлік мектебі, Талдықорған қаласы, Қазақстан АҢДАТПА: Бұл мақалада тақтайшадағы баскетбол ойыны атауы «COURT IQ» жұмыстың негізгі ұғымы мектепте білім беру бағдарламасы шеңберінде жүргізіліп жатқан жобалық жұмыстардың ерекшеліктері туралы, мәселені анықтау мен оның өзектілігін айқындау, жобаны жүргізу жоспары мен зерттеу барысы туралы айтылады. ТҮЙІН СӨЗДЕР: Жобалық жұмыс, мәселе, зерттеу, бақылау, пікір алмасу, тәжірибе жүргізу, ереже, ойын дағдылары, жауапкершілік, құзіреттілік. Әр мұғалім оқу жылы басталғаннан өзінің алдына қандай да бір мақсат қояды. Ол мақсаттар әр түрлі болуы мүмкін, ол өзі өткізетін сабақты күнделікті зерттеуі, бақылауы немесе қандай да бір жобалық жұмыспен зерттеулер жүргізу болуы мүмкін. Оқу жылы басында мынандай жобалық жұмысты, тақырыбы “Тақтайшадағы зияткерлік баскетбол ойыны” бастадық. Жобалық жұмыстың мақсаты орта буын оқушылардың сыни ойлау қабылеттерін дамытатын, спорттық және зияткерлік ойындарды ұштастыратын, оқушылардың қызығушылығын оятатын ойынды насихаттау. Бұдан күтілетін нәтиже, ол оқушылардың сыни ойлау және танымдық қабілеттерін дамыту болған. Өзектілігі: -Оқушыларды ойын ережесімен таныстыру; -Ойынды практикалық түрде ойнап, жетілдіру; -Ойынға қызығушылықтарын ояту; -Жалпы, ойынды оқушыларға насихаттау. Мәселе қалай анықталды? Жобаның негізгі идеясы ол, оқушыларды қызықтыратындай, олардың ойлау қабілетін дамытатын, спорттық ойынға ұқсас ойынды құрастыру талабынан шыққан болатын. Жобаны жүргізу аптасына 3 рет кездесу арқылы жоспарланды. Алдымен, оқушылармен мәселені айқындап жұмыс жоспарын құрастырудан бастадық. Мәселе айқындалған соң, әдістер мен тәсілдерді бейімдеу және практикалық қолдануға көше бастадық. Жобадағы ойын түрін немесе қандай ойын болу керек екенін анықтай бастадық. Тақтайшадағы баскетбол ойыны атауы «COURT IQ» айтып тұрғандай тақтайшада ойналады. Зерттеу барысы. Барлық жастағы оқушыларды сыни тұрғыдан ойлауды, сапалы шешім қабылдауға үйрету. Зерттеу әдісі арқылы оқушылардың іздену, ойлау-танымдық дағдыларын қалыптастыру. Жобаны ұйымдастырып жүргізу алдын-ала жоспарлау, оны сұхбаттасып талқылау және қайта жоспарлау, нәтижеге жету, нәтижені талдау арқылы жүзеге асты. Жобаны жүргізу барысында оқыту ресурстарын пайдалану, салыстыру және талдау әдістерін пайдаландық. Білім алушыларды өткен білімі мен тәжірибесін өзекті ету. Осы қабылдаған жаңа ойынымызды ары қарай жаңғырту үшін, біз ойын атауын ойластырдық. Басында ойға
Proceedings of the 11th International Scientific Conference 70 қонымды командамен “Тез ойлан, жылдам жүр” деп қоюға ұсыныс берілген болатын. Тақырыбымыз ұнағанмен жаңа ойын жүйесін енгізуде ағылшын тілімен ұштастырып қоюды жөн көрдік. Жобалық жұмысты өткізу кезеңдері біз үшін маңызды болды. Бірлесе жобаны жоспарлау, пікірталас, тәжірибе алмасу, ойын ережесін практикалық түрде бекіту және жобаға қатысушылардың ұсыныстарын анықтап, оны жүзеге асыра білдік деп ойлаймыз. Бастысы ойын ережесі мен практика түрінде ойнау оқушыларға түсінікті және жеңіл болады деп ойлаймыз. Ойын ережесіне тоқталып кетейік. 1) Ойынды 2 адам ойнайды, әр адамға 8 ойыншы беріледі, 5 негізгі мен 3 қосалқы ойыншы. 2) Кім бірінші жүретінін ойыншылар алаң шетіне (лақтыру сүйегін, тас, кубик т.б) лақтырып шешеді. Кімге көбірек сан түссе, сол бірінші жүреді. 3) Баскетбол алаңында екі адам кезектесіп бір-бір ойыншыдан қояды. Ойыншылардың орналасуы баскетбол ережесіне сәйкес болуы керек. Мысалы, 1.1, 1.3 суреттердегі ойыншылардың орналасуы баскетбол ережесін бұзбайды. Ал, 1.2 суреттегі ойыншылардың орналасуы баскетбол ережесін бұзады. 1.1 сурет 1.2 сурет 1.3 сурет 4) Шеңбер ішінде тұрған ойыншылар бірінші жүреді. 5) Ойыншылар кез-келген бағытта үш жолаққа жүреді, бірақ үш ұпайлық аймақтың ішінде шабуыл жасаушылар тек бір жолаққа жүреді, ал қорғаныстағы жақ үш ұпайлық аймақтың (зонаның) ішінде кез-келген бағытта үш жолаққа жүре береді. 6) Тек үш жолақ арақашықтығындағы ойыншыларды жеуге болады және ойыншылар бірбірін тек үш ұпайлық аймақтың (зонаның) ішінде жей алады. 7) Қарсылас ойыншыны жеп алуға мүмкіндік болса, қарсылас ойыншыны жеу міндет емес, өзінің жүріс ыңғайына қарай шешім қабылдайды. 8) Ойын 3 кезеңнен тұрады. Егер үш кезеңнен жеңімпаз анықталмаса, қосышма кезеңдер ойнатылады. Бірінші ойыншы алғашқы ұпай алысымен ойын тоқтатылып, ұпай алған ойыншы жеңіске жетеді. 9) Ойын кезеңінің уақыты біткенде немесе бір командада үш ойыншы қалса ойынның бір кезеңі бітеді.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 71 10) Ойын кезеңнің жеңімпазы ұпай бойынша анықталады. 11) Ойын барысында бір ойнайтын адамда 5 ойыншыдан аз болып қалса, ол қосалқы ойыншыларды өз жағындағы үш ұпайдық аймақтағы (зонадағы) 9 жолақтың бос болған біреуіне шығару керек. Мысалы 2.1, 2.2 суреттердегі ойыншылар тұрған жолақтарға қосалқы ойыншыларды шығаруға болады. 2.1 сурет 2.2 сурет 12) Қосалқы ойыншының шығуы жүріске саналмайды. 13) Қосалқы ойыншы бір жүрістен кейін ғана жүре алады. 14) Ойыншылардың біреуі үш ұпайлық аймаққа (зонаға) жетсе, жүріс кезегі сол ойыншыда болса онда, ол алаң шетіне ойын сүйегін лақтырады. 15) Ойын сүйегінен түскен сан ойыншының қанша жүріс алдыға жүретінін көрсетеді. 16) Егер ол жүріс саны баскетбол торына, қажет жүріс санынан асып кетсе, онда доп алаңнан ұшып торға дәл түспеген болып саналады. Онда қасындағы бос тор көздерге орналасады. Қарсылас ол тасты, әғни ойыншыны жеп қоймаса, жүрісі кезінде ұпай торына салуға тырысады. 17) Егер баскетбол торына, 3 аймақтық алаңында орналасқан, алаңнан ұшқан доп дәл салынған болса, онда ол қалауы бойынша өз жағындағы, қосалқы ойыншылар шығарылатын 9 жолақтың бос біреуіне қойылады. 18) Егер ойын сүйегінен түскен саны баскетбол торына жетпесе, онда ойыншы ойын сүйегінен түскен жүріс санына алдыға қарай жылжиды. 19) Өз жағында 3 ұпайлық аймақта қорғаушы, қарсылас шабуылдаушыны артқа қарай жей алмайды. Ұпай жүйесінің анықтамасы. 1) Ойыншы қарсылылас ойыншысын жесе, оған 1 ұпай беріледі. 2) Үш ұпайлық аймақтан (зонадан) доп салынса, 3 ұпай беріледі. 3) Үш ұпайлық зонаның ішінен доп салынса, 2 ұпай беріледі. Ойын 3 кезеңнен тұрады. Әр кезеңге 3 минуттан беріледі. Арнайы құрылғы сағат арқылы уақыт мөлшері мен ұпай сандары және ойын кезеңдері көрсетіліп тұрады. Жобадан күтетін нәтижемізге жеттік. Алдымызда осы жобалық жұмысымызды мектепішілік «Жобалар апталығы» фестивалінде қорғап, 1 орынға ие болдық. Ойынды НЗМ мектеп желісі ішінде және аудан, қала мектептеріне насихаттау жоспарымызда бар.
Proceedings of the 11th International Scientific Conference 72 Current Issues in Educational Data Analysis Through Artificial Intelligence K. Nigmetov L.N. Gumilyov Eurasian National University, Astana, Kazakhstan, Doctoral student Abstract: the integraon of arficial intelligence (AI) to advance educaonal processes is the focus of this arcle's review of the present and future of educaonal data analysis. This arcle clarifies how these approaches might maximize learning results by examining methodologies and technology including recommendaon systems, forecasng strategies, data analysis models, and visualizaon tools. The essay discusses techniques like text analysis, neural networks, clustering, and classificaon and explains how they might increase the effecveness of instruconal procedures. The advantages of using educaonal data to forecast student progress and modify teaching strategies are discussed. A thorough analysis of current resources and tools is provided, emphasizing their benefits, drawbacks, and the difficules faced by instuons and researchers. The study examines prospecve advancements in educaonal data analysis and future research areas, emphasizing the value of ulizing contemporary technology, especially AI. The arcle concludes that thoughul applicaon of AI-driven data analysis can greatly boost teaching methodologies. Keywords: data analysis, educaonal data mining, learning analycs, arficial intelligence, clustering, classificaon, neural networks. Introducon Educaon is one of the industries that have seen significant change with the introducon of AI. President Kassym-Jomart Tokayev of the Republic of Kazakhstan highlighted the importance of AI in contemporary society and outlined goals for its advancement in his speech at the internaonal event Digital Bridge 2023. He emphasized the need for a revision of digital literacy courses in higher educaon, emphasizing that future experts must have a solid understanding of arficial intelligence and related subjects [1]. In order to match educaon with the changing needs of the digital age, educaonal programs must place a greater emphasis on arficial intelligence. Large databases of educaonal data have been created as a result of the extensive use of the internet, growth of electronic materials, and a variety of instruconal instruments. Learning management systems (LMS), which include vast amounts of useful data, are being adopted more and more. New techniques for automated educaonal data analysis are required since the expansion of such data poses obstacles for manual analysis. This informaon is essenal for a thorough study of the learning process. There is a pressing need to turn this data into ideas that may help students, teachers, and administrators as instuons struggle with organizing and analyzing large amounts of data [2]. Data analysis becomes a crucial instrument for well-informed decision-making in educaonal instuons. With AI playing a major part, trends in the collecon, analysis, and use of educaonal data are becoming noceable. By facilitang more individualized and effecve learning experiences, AI-driven educaonal data analysis can transform educaonal processes. However, because of difficules with data processing, analysis, and AI integraon, many instuons have not yet fully ulized the potenal of educaonal data. This paper seeks to examine the present situaon and potenal future direcons of educaonal data analysis. The research looks at technologies and methodologies used in this sector, such as forecasng methods, data analysis models, visualizaon tools, and
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 73 recommendaon systems, to show how these approaches might improve instruconal procedures. The study also examines current tools and resources, talks about the advantages of using educaonal data to forecast student achievement and modify teaching strategies, and explores the difficules faced by researchers and instuons. The paper concludes by outlining the significance of incorporang contemporary technologies – parcularly AI – into the analysis of educaonal data and potenal avenues for further research. Methodology This study used a mixed-methods research design, integrang quantave and qualitave approaches, to examine educaonal data analysis and AI incorporaon. By combining the contextual richness of qualitave data with the stascal breadth of quantave research, the mixed-methods approach enhances the validity and depth of findings [3]. The quantave component involved a bibliometric analysis of peer-reviewed papers published between 2019 and 2024 in global databases such as Web of Science, Scopus, and Google Scholar. These databases were selected for their accessibility, rigorous standards, and extensive indexing [4, 5]. The keywords "Educaonal Data Mining" and "Learning Analycs" guided the search to assess annual academic output and research trends. Microso Excel was used to process and analyze the extracted data [6]. The qualitave component included a detailed review of peer-reviewed arcles, conference proceedings, and publicaons from leading instuons in learning analycs and educaonal data analysis. The Naonal Academic Library of the Republic of Kazakhstan (hp://nabrk.kz/) was also consulted to examine domesc dissertaons on data analysis and AI in educaon [7]. This component aimed to incorporate global perspecves and invesgate current approaches, resources, and challenges in the field. Addionally, the study conducted a global review of current techniques and tools used in educaonal data analysis, examining case studies, soware, and online resources. By combining quantave bibliometric data with qualitave content analysis, the research provides a comprehensive overview of trends, methods, and future direcons in educaonal data analysis, highlighng AI’s role in enhancing educaonal processes. Literature Review Learning Analycs (LA) and Educaonal Data Mining (EDM) are closely linked fields that have emerged due to the rapid growth of educaonal data. Both aim to improve learning outcomes by deriving insights from educaonal data, but they differ in approach and focus. EDM provides techniques to analyze data from educaonal sengs using stascal methods, machine learning algorithms, and data mining approaches [8–9]. It addresses technical challenges of evaluang complex, large-scale data and develops tools to uncover hidden paerns. LA, in contrast, involves measuring, collecng, analyzing, and reporng student data to understand and improve learning [10]. It emphasizes data-driven decision-making and is learnercentered, aiming to directly benefit students [11]. Despite differences, EDM and LA complement each other in enhancing instruconal strategies [12–13]. EDM focuses on methodology and technical innovaon, while LA priorizes praccal applicaon and real-me educaonal management. Subfields such as computer educaon, machine learning in educaon, and educaonal stascs reflect this convergence [12]. The widespread use of Learning Management Systems (LMS) and online plaorms like MOOCs has accelerated educaonal data analysis [14]. Landmark events, such as the first Internaonal Conference on Educaonal Data Mining (2008) and the Conference on Learning Analycs and Knowledge (2011), formalized these areas [12]. Public repositories like DataShop and
Proceedings of the 11th International Scientific Conference 80 movaon. The arcle also presents methodological recommendaons and praccal strategies that teachers can apply to create technology-rich, communicave, and engaging language learning environments. Purpose, Novelty, Pedagogical Concept, and Praccal Methods with Examples (English) Purpose of the Study The main purpose of this arcle is to analyze and jusfy the effecveness of modern technologies in improving the process of mastering foreign language communicaon at the Basic Stage of secondary school. The study aims to idenfy technological tools that enhance students’ communicave competence, increase movaon, support learner autonomy, and create real or simulated environments for meaningful language interacon. It also seeks to provide praccal recommendaons for integrang these technologies into everyday classroom pracce to ensure the holisc development of listening, speaking, reading, and wring skills. Novelty of the Work The novelty of the study lies in its comprehensive approach to combining interacve, digital, mobile, and mulmedia technologies within a communicaon-centered pedagogical framework. Unlike tradional methods that primarily emphasize grammar and vocabulary, this work highlights the role of technologies in creang authenc communicave situaons, enabling internaonal collaboraon, and supporng differenated instrucon based on students’ individual needs. Addionally, the arcle presents specific digital tools and step-by-step instruconal examples that can be directly applied by teachers in real lessons, making the study both innovave and praccal. Pedagogical Idea and Conceptual Approach The pedagogical concept underlying this arcle is based on the principles of communicave language teaching (CLT) supported by technological mediaon. The core ideas include: learning occurs through meaningful interacon, not rote memorizaon; technology acts as a bridge connecng students to authenc language use; the teacher shis from being a “knowledge transmier” to a facilitator and designer of learning environments; students develop linguisc, cultural, and digital competences simultaneously; mulmedia and interacve plaorms enhance sensory learning channels and improve language retenon. This approach posions technology not as an add-on tool but as an integral part of developing communicave competence. Praccal Methods Used in Lessons In classroom pracce, several technology-enhanced methods are applied to support foreign language communicaon: a) Interacve Vocabulary and Grammar Tasks Plaorms such as Quizlet, LearningApps, and Wordwall are used to reinforce vocabulary and grammar through matching tasks, flashcards, and games. These acvies promote acve recall and immediate feedback. b) Communicave Speaking Acvies Speech-recording apps (e.g., Flip, Vocaroo) help students pracce speaking, listen to themselves, and share recordings with peers for feedback. This method increases confidence and develops proper pronunciaon.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 81 c) Virtual Exchange and Real-Time Communicaon Using Zoom, Google Meet, or eTwinning, students parcipate in video conversaons or joint projects with learners from other countries. This method develops intercultural communicaon and real-life language use. d) Mulmedia-Based Listening and Discussion Short videos from BBC Learning English, TED-Ed, or YouTube Kids are used as authenc input sources. Students watch the video, complete comprehension quizzes, and engage in discussions aerwards. e) Collaborave Digital Projects Tools such as Padlet, Jamboard, and Google Docs allow students to work together to create posters, dialogues, or presentaons. This fosters teamwork and negoaon of meaning. Specific Examples with Step-by-Step Instrucons Example 1: “Describe the Scene” – AR Vocabulary Acvity Tool: AR Flashcards Steps: 1. Teacher provides students with AR objects (animals, rooms, food items). 2. Students scan the cards with a mobile device. 3. A 3D object appears on the screen. 4. Students describe the object using target vocabulary (“The ger is big…”, “The chair is next to the table…”). 5. Students record a short video describing the scene. Outcome: Improved vocabulary retenon and confident speaking. Example 2: “Internaonal Pen Pal Talk” – Video Exchange Tool: Zoom or eTwinning Steps: 1. Teacher connects with a foreign partner school. 2. Students prepare simple quesons (name, hobbies, school life). 3. Students join a short live video session. 4. Each student interviews a partner. 5. Students write a summary of what they learned. Outcome: Authenc communicaon and cultural awareness. Example 3: “Digital Storytelling” – Creang a Short Video Tool: Flip or Canva Video Steps: 1. Students choose a topic (“My Day”, “My Favorite Place”). 2. They combine images, text, and their own voice. 3. Students share their stories with the class. 4. Peers give feedback using simple criteria. Outcome: Development of speaking, wring, creavity, and digital literacy. MAIN BODY The integraon of modern technologies into foreign language teaching at the Basic Stage of secondary school has reshaped tradional pedagogical approaches and opened new pathways for developing communicave competence. This secon examines key technological tools, their pedagogical value, and the ways in which they enhance students’ ability to communicate in a foreign language. Digital and Interacve Learning Plaorms Digital learning environments such as LearningApps, Quizlet, Duolingo, Kahoot, and other educaonal plaorms offer extensive opportunies for vocabulary building, grammar pracce, and
Proceedings of the 11th International Scientific Conference 82 communicaon-oriented tasks. These plaorms provide interacve exercises that allow learners to engage with content at their own pace, receive immediate feedback, and revisit challenging topics. The gamificaon elements—points, levels, badges, and leaderboards—movate students and sustain their interest in foreign language learning. Importantly, students can pracce all four language skills—listening, speaking, reading, and wring—through personalized pathways that adapt to their proficiency level. Moreover, learning management systems (LMS) like Google Classroom and Moodle support teacher–student communicaon, assignment distribuon, collaborave projects, and peer feedback. These systems create a structured digital environment where communicave tasks can be organized efficiently, helping students develop autonomy and responsibility in their learning. Mulmedia Tools for Enhancing Input and Output Skills Mulmedia resources, including videos, audio recordings, animaons, and interacve stories, provide authenc linguisc input that supports natural language acquision. Plaorms such as YouTube, Brish Council Teens, and TED-Ed offer culturally rich and linguiscally diverse content that exposes learners to real-life accents, phrases, and communicaon styles. Watching short educaonal videos or listening to podcasts enhances listening comprehension, expands vocabulary, and enables students to observe natural speech paerns. At the same me, mulmedia tools support output skills. Students can record their own videos, podcasts, or digital stories to pracce speaking and pronunciaon. Applicaons like Flip, VoiceThread, and Vocaroo allow students to create oral presentaons, parcipate in online discussions, and exchange feedback with peers. These acvies promote communicave fluency, confidence, and creavity. Virtual Communicaon and Collaborave Technologies One of the most powerful impacts of technology lies in its ability to simulate or create a real communicave environment. Video conferencing tools such as Zoom, Microso Teams, and Google Meet support synchronous communicaon with nave speakers or partner schools abroad. Virtual exchange programs, eTwinning projects, and internaonal collaborave acvies give students a meaningful reason to use the foreign language, thereby increasing movaon and communicave readiness. Online collaboraon tools such as Padlet, Jamboard, and Google Docs allow students to work together on wring tasks, dialogues, posters, and presentaons. These tools encourage peer interacon, negoaon of meaning, and collaborave problem solving—core components of communicave competence. Mobile-Assisted Language Learning (MALL) Mobile applicaons are parcularly effecve for younger learners who prefer flexible, interacve, and visually appealing tasks. Apps that support speech recognion help students pracce pronunciaon, receive instant correcve feedback, and track their improvement. Augmented reality (AR) applicaons introduce immersive experiences where students interact with 3D objects, characters, or scenes in the target language. For example, AR flashcards or AR storybooks make vocabulary learning more engaging and context-rich. Formave Assessment and Adapve Technologies Technologies that support ongoing assessment help teachers monitor students’ progress in real me. Digital quizzes, automated test generators, and speech analysis tools allow teachers to evaluate pronunciaon, fluency, and grammacal accuracy objecvely. Adapve systems adjust the difficulty of tasks depending on learners’ performance, ensuring opmal challenge levels that support consistent progress. Pedagogical Implicaons and Teacher Readiness Effecve integraon of technology requires pedagogical literacy and digital competence from teachers. They must select tools purposefully, align them with communicave objecves, and
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 83 maintain a balance between tradional interacon and digital enhancement. Technology should not replace communicaon but enrich and expand it. CONCLUSION The integraon of modern technologies into the process of mastering foreign language communicaon at the Basic Stage of secondary school represents a significant pedagogical shi that aligns educaon with the demands of contemporary society. The findings presented in this arcle demonstrate that technologies not only enhance linguisc competence but also transform the nature of language learning by making it more interacve, engaging, and learner-centered. Through digital tools, students gain access to authenc linguisc input, real communicaon scenarios, and opportunies to pracce language skills in meaningful and movang ways. One of the most important impacts of technology is its ability to create a simulated or authenc communicave environment where students can interact in real me. Video conferencing tools, virtual exchange plaorms, and online collaborave spaces provide learners with opportunies to speak with peers from other countries, parcipate in group discussions, and develop intercultural communicaon skills. This exposure is crucial, especially in sengs where natural language immersion is limited. Technology bridges this gap by bringing the global linguisc landscape directly into the classroom. Moreover, mulmedia resources such as videos, audio podcasts, animaons, and interacve stories enrich the learning environment and appeal to diverse learning styles. Listening and speaking acvies become more dynamic and realisc, enabling students to develop pronunciaon, intonaon, and fluency. The use of speech-recognion features in mobile applicaons supports independent pracce, allowing learners to self-assess and adjust their pronunciaon without fear of making mistakes in front of peers. This fosters both autonomy and confidence. Digital plaorms and mobile-assisted learning also support differenated and personalized instrucon. Adapve learning systems adjust the difficulty level of tasks based on students’ progress, ensuring opmal learning condions for each individual. Meanwhile, gamified elements, such as points, badges, and leaderboards, increase movaon and help sustain student engagement. These features are parcularly effecve for younger learners who respond posively to visual, interacve, and game-like experiences. Another key benefit of technology is its role in enhancing formave assessment. Digital quizzes, automated feedback mechanisms, and performance tracking tools allow teachers to monitor student progress in real me and make mely instruconal adjustments. Teachers can easily idenfy areas where students struggle and provide targeted support. This data-driven approach contributes to more effecve lesson planning and improved learning outcomes. However, technological integraon also requires a shi in the teacher’s role. Teachers must act not only as subject experts but also as facilitators, mentors, and designers of technologyenhanced learning environments. The successful implementaon of technology depends on the teacher’s digital competence, methodological knowledge, and ability to select tools that align with pedagogical objecves. Professional development is therefore essenal for empowering teachers to use technologies effecvely and confidently. Despite the numerous advantages, it is important to recognize that technology should not replace tradional teaching methods but rather complement them. The ulmate goal is to create a balanced, student-centered learning environment where technology is used purposefully to support communicaon, collaboraon, and creavity. When integrated meaningfully, digital tools help students develop not only linguisc competence but also crical thinking, problem-solving, and digital literacy—skills that are indispensable in the modern world. In conclusion, technologies play a transformave role in enhancing the process of mastering foreign language communicaon at the Basic Stage of secondary school. They enrich
Proceedings of the 11th International Scientific Conference 84 instruconal methods, personalize learning, expand access to authenc communicaon, and movate students to acvely parcipate in language learning. By thoughully integrang digital tools into communicave teaching pracces, educators can significantly improve language learning outcomes and prepare students for global cizenship. The connued development of educaonal technologies and teacher digital competence will further strengthen the effecveness of foreign language educaon, making it more relevant, engaging, and future-oriented. REFERENCES 1. Richards, J. C., & Rodgers, T. S. (2014). Approaches and Methods in Language Teaching. Cambridge University Press. 2. Hubbard, P., & Levy, M. (2016). The Routledge Handbook of Second Language Teaching and Technology. Routledge. 3. Godwin-Jones, R. (2018). “Emerging Technologies for Language Learning.” Language Learning & Technology, 22(1), 2–11. 4. Chapelle, C. A. (2009). Computer Applicaons in Second Language Acquision. Cambridge University Press. 5. Stockwell, G. (2012). Mobile-Assisted Language Learning: Concepts, Contexts, and Challenges. Cambridge Scholars Publishing. 6. Dudeney, G., Hockly, N., & Pegrum, M. (2013). Digital Literacies. Pearson Educaon. 7. Bax, S. (2011). “Normalisaon of Technology in Language Teaching.” Internaonal Journal of Computer-Assisted Language Learning, 23(3), 255–267. 8. Kern, R. (2015). Language, Literacy, and Technology. Cambridge University Press. 9. Warschauer, M., & Grimes, D. (2007). “Audience, Authorship, and Authencity in the Digital World.” Journal of Educaonal Compung Research, 37(2), 215– 239. 10. Brish Council. (2018). Digital Learning and Teaching in English Language. Brish Council Publicaons.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 85 Inclusive Pedagogy: Strategies for Teaching Students with Learning Differences Мырзабекова Эльдана Қазақ халықаралық қатынастар және әлем тілдері университеті (ҚазХҚ және ӘТУ), Алматы қ., Қазақстан, Екі шетел тілі факультеті, 4-курс студенттері Жүсіпбек Жібек Қазақ халықаралық қатынастар және әлем тілдері университеті (ҚазХҚ және ӘТУ), Алматы қ., Қазақстан, Екі шетел тілі факультеті, 4-курс студенттері Мырзаханова Динара Магистр, аға оқытушы, Қазақ халықаралық қатынастар және әлем тілдері университеті (ҚазХҚ және ӘТУ), Алматы қ., Қазақстан; Шетел тілі білім беру әдістемесі кафедрасы Аннотация Бұл мақала заманауи сыныптарда оқуда қиындықтары бар оқушыларды оқытуда инклюзивті педагогиканың маңызды стратегия екенін қарастырады. Зерттеу барлық оқушылар үшін теңдік, қатысу және тиесілік сезімінің маңыздылығын атап өтеді, себебі дислексия, ЗЖГС (СДВГ), аутизм спектрі бұзылыстары және сезім мүшелерінің бұзылыстары сияқты жағдайлар оқуда елеулі қиындықтар тудыруы мүмкін. Инклюзивті білім берудің тарихи дамуына және қарапайым интеграциядан қағидатты инклюзияға көшуіне шолу жасалғаннан кейін, мақала негізгі педагогикалық идеялар мен мұғалімдердің көзқарастары мен сенімдерінің рөліне тоқталады. Бұдан әрі ол оқу айырмашылықтарының әлеуметтік және когнитивтік дамуда қалай көрінетінін талдап, ерте анықтау мен арнайы қолдаудың маңызын көрсетеді. Мақаланың негізгі бөлігінде саралап оқыту және Оқытудың әмбебап дизайны (UDL) басты оқыту әдістері ретінде ұсынылады. Бұл стратегиялар мазмұнды, процесті және нәтижені бейімдеу арқылы, сондай-ақ ұсынылу, қатысу және білдірудің көптеген тәсілдерін қолдану арқылы инклюзивті оқытуды қалай қолдауға болатынын көрсетеді. Қорытындыда теориялық және эмпирикалық деректерге сүйене отырып, инклюзивті педагогиканы жүйелі түрде енгізу барлық оқушыларға пайда әкелетінін, білім беру теңсіздіктерін азайтатынын және оқу қауымдастықтарында мағыналы қатысуды арттыратынын дәлелдейді. Авторы: Мырзабекова Эльдана, Жусипбек Жибек Казахский университет международных отношений и мировых языков имени Абылай хана (КазУМОиМЯ), г. Алматы, Казахстан Факультет: Факультет двух иностранных языков, студенты 4 курса Соавтор: Мырзаханова Динара - Магистр, старший преподаватель Казахский университет международных отношений и мировых языков имени Абылай хана (КазУМОиМЯ), г. Алматы, Казахстан; Кафедра методики преподавания иностранных языков Аннотация Эта статья рассматривает инклюзивную педагогику как ключевую стратегию обучения учащихся с нарушениями обучения в современных классах. В исследовании подчеркивается важность равенства, участия и принадлежности для всех обучающихся, поскольку такие состояния, как дислексия, СДВГ, расстройства аутистического спектра и сенсорные нарушения, могут создавать серьёзные трудности в обучении. После обзора исторического развития инклюзивного образования и перехода от простой интеграции к принципиальной
Proceedings of the 11th International Scientific Conference 86 инклюзии статья рассматривает основные педагогические идеи, а также роль установок и убеждений учителей. Далее анализируется, как различия в обучении проявляются в социальном и когнитивном развитии, подчеркивая важность раннего выявления и специализированной поддержки. В основной части представлены два ключевых метода обучения - дифференцированное обучение и Универсальный дизайн обучения (UDL). Эти стратегии показывают, как можно способствовать инклюзивному обучению, используя различные способы представления, вовлечения и выражения, а также адаптируя содержание, процесс и результат. В заключение утверждается - на основании теоретических и эмпирических данных - что системная интеграция инклюзивной педагогики приносит пользу всем учащимся, снижает образовательное неравенство и способствует значимому участию в учебных сообществах. Word list: Inclusive pedagogy – Teaching approach that accommodates all learners’ differences without discrimination. Learning disabilities – Conditions that affect learning, such as dyslexia, dysgraphia, ADHD, or nonverbal learning disabilities. Dyslexia – Difficulty with reading, decoding, and phonological processing. Dysgraphia – Difficulty with writing, spelling, and organizing written expression. ADHD – Challenges with attention, focus, and self-regulation. Autism spectrum disorder (ASD) – Neurodevelopmental condition affecting social communication, behavior, and sensory processing. Nonverbal learning disabilities – Difficulties with visual-spatial tasks, social cues, and problemsolving. Differentiated instruction – Adapting teaching methods and content to meet individual learners’ needs. Universal Design for Learning (UDL) – Framework offering multiple ways to present content, engage students, and assess learning. Collaborative learning / peer tutoring – Learning through interaction and cooperation with peers. Assistive technology – Tools (e.g text-to-speech, visual aids) that support learning and independence. Formative assessment – Continuous evaluation to monitor progress and guide teaching. “The child is both a hope and a promise for mankind.” – Maria Montessori Inclusive pedagogy is an approach to teaching diverse learner groups that seeks to accommodate individual differences between learners without treating them differently to others. Teachers and other professionals in the classroom are encouraged to see student challenges as professional challenges for practice rather than as student issues. By working collaboratively, they can develop ways of responding to individual differences that promote a good experience of learning and good outcomes for everyone. Inclusive education means all children in the same classrooms, in the same schools. It means genuine educational chances for historically marginalized groups, including minority language speakers and children with disabilities. Inclusive systems allow varied groups to develop alongside one another for everyone's benefit and recognize the distinctive contributions that students from all backgrounds bring to the classroom.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 87 Commonly recognized specific learning disabilities include: Reading disability (dyslexia) is the most common learning disability, representing at least 80% of all learning disabilities, and results from deficits in phonologic processing. Skills necessary for appropriate phonologic processing involve reading decoding, phonics, producing sounds, and proper auditory capabilities. In the early years, reading decoding issues are frequently the first step in the progression, followed by dysfluent reading and reading comprehension issues. These children may eventually avoid reading altogether. Dysgraphia is characterized by distorted writing despite thorough instruction and motor ability. Children with dysgraphia produce inconsistent and illegible handwriting while rarely staying within the margins. These kids may also exhibit poor fine motor coordination, difficulties with language, syntax, spelling (encoding), or writing down their thoughts. Nonverbal learning disability (right hemisphere developmental learning disability), as the name suggests, comprises hindrances with nonverbal activities, such as problem-solving, visual-spatial tasks, reading body language, and recognizing social cues. Often, these disorders do not manifest until the third grade, as patients have difficulty with higher-order reading comprehension. There is substantial clinical overlap with autism spectrum disorder (eg, poor social communication and pragmatics) These difficulties influence cognitive and social development, making early identification and targeted support essential. The purpose of this article are to describe the fundamental ideas of inclusive pedagogy, examine the requirements of students with learning disabilities, and offer research-proven teaching techniques that support inclusive classrooms. Because the article is conceptual rather than empirical, “study site” refers to general school settings - where inclusive education is implemented, including: - Primary and secondary mainstream classrooms - Schools implementing inclusive education policies (UNICEF, 2021) - Contexts where students with dyslexia, ADHD, autism, sensory impairments, or nonverbal learning disabilities learn alongside their peers - Worldwide Significance - because learning variations are ubiquitous, teachers everywhere deal with mixed-ability classrooms, and contemporary educational institutions strive for equal outcomes, inclusive pedagogy is applicable across cultural and national barriers. In order to determine successful inclusive teaching techniques, this study employs a conceptual review and synthesis of previous research, referencing scholarly works, educational frameworks, and case studies. The steps in the methodology consist of: 1.Examining the theoretical underpinnings Florian's inclusive pedagogy theory Universal Design for Learning (CAST) 2. Examination of learning disparities Cognitive, behavioral, and social traits derived from educational and clinical studies. 3. Assessment of educational models Peer-supported and cooperative learning Technologies for assistance Formative evaluation techniques
Proceedings of the 11th International Scientific Conference 88 4. Analyzing implementation difficulties Lack of resources, problems with class size, and teacher readiness 5. Examining case examples from around the world Finland's three-level assistance system Peer-mediated reading initiatives in the United States The UDL-based digital learning model in New Zealand A number of important conclusions regarding the nature of learning differences and the efficacy of inclusive teaching techniques were drawn from the literature review. Learning disabilities include dyslexia, dysgraphia, ADHD, autism spectrum disorders, and nonverbal learning disabilities all have different but similar effects on students' academic performance, according to numerous studies. For instance, learners with dysgraphia have trouble with handwriting, spelling, and the structure of written expression, but children with dyslexia usually struggle with phonological processing, reading fluency, and decoding written words. Students with ADHD frequently struggle with maintaining focus, planning assignments, and controlling their behavior, which can result in uneven performance in the classroom. In the meantime, students on the autistic spectrum could need greater assistance with socialization, communication, and sensory control. Students with nonverbal learning difficulties can misinterpret nonverbal cues and visualspatial information, which can have an impact on peer interactions and problem-solving. Collaborative learning practices such as peer tutoring, flexible grouping, and planned group assignments were found to boost both academic performance and social integration. These methods assist children gain confidence in mixed-ability settings, foster peer connection, and improve communication skills. Additionally, research indicates that assistive technologies - from digital organizers and visual aids to text-to-speech tools - are crucial in promoting independence, particularly for children who struggle with literacy or attention. Lastly, research continuously highlights the significance of formative evaluation. Frequent, low-pressure evaluations enable educators to track students' progress, spot new challenges, and quickly modify their lesson plans. The significance of teacher beliefs and competencies is the last significant discovery. According to research, inclusive pedagogy works best when educators maintain high standards for every student and accept student variety. Teachers who are confident in their ability to modify materials and who work well with families and specialists are more likely to implement inclusion. Numerous studies do, however, also highlight similar issues, such as poor access to resources, time limits, huge class sizes, and a lack of teacher preparation. These obstacles explain why inclusive education is still applied inconsistently in many settings despite its shown advantages. The results demonstrate the efficacy of inclusive pedagogy when educators create classrooms that recognize and value the variety of their students. Flexible teaching strategies are necessary for learning differences like dyslexia, ADHD, and autism, and research shows that frameworks like Universal Design for Learning and individualized instruction help remove obstacles before they arise. Students with learning disabilities participate more confidently and perform better when lessons include numerous ways to obtain material and demonstrate understanding. Additionally, cooperation is essential. While collaboration between educators, experts, and families guarantees constant supervision for students who require extra support, structured peer activities promote social integration. The review does, however, draw attention to persistent issues, such as the fact that many educators feel unprepared for inclusive practices and that the
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 89 efficacy of these tactics may be diminished by a lack of resources or big class sizes. This implies that inclusive pedagogy necessitates substantial school and educational system support in addition to teacher effort. Overall, the conversation suggests that inclusive teaching enhances academic performance and fosters a supportive, fair classroom environment. Careful planning, teacher preparation, and a school climate that celebrates and encourages diversity are all essential to its success. Inclusive pedagogy represents a transformative approach to teaching that embraces learner diversity as a resource rather than a challenge. By integrating differentiated instruction, Universal Design for Learning, collaborative learning, assistive technology, and continuous formative assessment, teachers can create classrooms where all students are able to participate meaningfully and succeed. Teacher commitment is central to this process. When educators adopt inclusive attitudes, collaborate with specialists, and consistently refine their practice, they cultivate learning environments grounded in equity, participation, and belonging. Although challenges such as limited resources and insufficient training persist, strategic policy support and professional development can strengthen implementation. Future research should explore culturally responsive approaches to inclusion, the longterm impact of digital learning tools on diverse learners, and effective models for school-wide collaboration. Ultimately, inclusive pedagogy not only supports students with learning differences, it enriches the entire learning community. References https://www.unicef.org/education/inclusive-education https://eric.ed.gov/?q=The+Advantages+and+Challenges+of+Inclusive+Education%3a+Striving+f or+Equity+in+the+Classroom&id=EJ1421555 https://www.ncbi.nlm.nih.gov/books/NBK554371/ https://www.internationaldisabilityalliance.org/sites/default/files/universal_design_for_learning _final_8.09.2021.pdf https://pmc.ncbi.nlm.nih.gov/ https://teaching.ucla.edu/resources/teaching-guides/ CAST. (2018). Universal Design for Learning guidelines version 2.2. CAST Publishing. https://udlguidelines.cast.org Fuchs, D., & Fuchs, L. (2019). Peer-assisted learning strategies: Research-based practices for improving literacy outcomes. Routledge. Publisher website: https://www.routledge.com PALS program information: https://vkc.vumc.org/pals Florian, L., & Black-Hawkins, K. (2011). Exploring inclusive pedagogy. British Educational Research Journal, 37(5), 813–828. https://bera-journals.onlinelibrary.wiley.com Heritage, M. (2018). Formative assessment in practice. Harvard Education Press. https://www.hepg.org/books Johnson, D., & Johnson, R. (2018). Cooperative learning: The foundation for active learning. Active Learning in Higher Education, 19(1), 29–43. https://journals.sagepub.com/home/alh Mayes, S. D., Calhoun, S. L., & Crowell, E. W. (2020). Learning, attention, and executive functioning in students with disabilities. Journal of Psychoeducational Assessment, 38(3), 337– 350. https://journals.sagepub.com/home/jpa
Proceedings of the 11th International Scientific Conference 96 UDC 372.881.1 Developing Sociocultural Competence in Foreign Language Learning Kovtun Anastassiya Sergeevna 4th Year Bachelor student, “6B01701-Teacher of two foreign languages”, KazUIR&WL Ablai Khan, Almaty, Kazakhstan Zhumabekova Galiya Baiskanovna Candidate of Pedagogical Sciences, Professor, KazUIR&WL Ablai Khan, Almaty, Kazakhstan ABSTRACT In an increasingly globalized world, foreign language education must extend beyond grammar and vocabulary to include sociocultural competence – the ability to navigate cultural norms, values, and contexts in communication. This article synthesizes key theoretical contributions on sociocultural and intercultural competence. Foundational constructs include Vygotsky’s sociocultural theory (emphasizing social interaction and language as mediating tools), Byram’s model of Intercultural Communicative Competence (defining savoirs of knowledge, attitudes, skills, and critical awareness), Kramsch’s concept of symbolic competence (attunement to cultural meaning in discourse), and Fantini’s definition of intercultural competence as a “complex of abilities” for effective interaction across cultures. Kazakh scholar Kunanbayeva’s linguocultural-communicative framework further delineates sub-competencies (including the development of a ‘secondary cognitive consciousness’ representing the target culture’s worldview). These perspectives converge to show that language learning must integrate cognitive, affective, and cultural dimensions. Developing sociocultural competence is thus crucial for successful intercultural communication, fostering global citizenship, and promoting inclusive education and mutual understanding in diverse societies. This theoretical review draws on peerreviewed literature to articulate how sociocultural competence can be cultivated in foreign language learning, and discusses implications for pedagogy and policy. Keywords: sociocultural competence; foreign language learning; intercultural communicative competence; foreign language education; intercultural communication; global citizenship; inclusive education. INTRODUCTION Effective foreign language education today transcends linguistic proficiency alone and emphasizes sociocultural competence – the capability to understand and negotiate cultural contexts in communication. This aligns with the broader notion of intercultural communicative competence, which scholars describe as equipping learners to bridge cultural differences in understanding and expression. For example, Fantini characterizes intercultural communicative competence as the “complex of abilities needed to perform effectively and appropriately when interacting with others who are linguistically and culturally different”. Byram (1997) similarly posits that language learners must develop knowledge of self and other cultures, positive attitudes toward cultural diversity, interpretive skills, discovery skills, and critical cultural awareness to communicate across cultures. Vygotsky’s sociocultural theory provides a foundational lens: he argued that cognitive development (including language learning) is inherently mediated by social interaction and cultural tools, with language itself being the primary mediating artifact. In language classrooms, this means that learners construct understanding through dialogue and
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 97 cultural context, and instruction should target their Zone of Proximal Development (ZPD) via collaborative activities. In addition, contemporary educators such as Kramsch emphasize that language and culture are inseparable: learners must develop symbolic competence – the ability to interpret the cultural meaning embedded in language use and discourse. Thus, sociocultural competence involves cognitive, affective, and discursive dimensions. This perspective reflects the aims of inclusive and globalized education: by fostering sociocultural competence, language learners become prepared for intercultural communication, global collaboration, and active global citizenship. Indeed, research suggests that intercultural competencies enrich individual learning and empower educators and leaders to promote international collaboration. This article reviews the theoretical foundations of sociocultural competence development in foreign language learning. It synthesizes contributions from international scholars – including Michael Byram, Claire Kramsch, Alvino Fantini, and others – and highlights Vygotsky’s sociocultural theory and Kunanbayeva’s intercultural-communicative framework. We explore how these theories inform the integration of intercultural dimensions into language pedagogy, and discuss the importance of sociocultural competence for intercultural dialogue, inclusive education, and mutual understanding. METHODS AND MATERIALS Sociocultural Theory (Vygotsky). Vygotsky’s sociocultural theory underpins modern views of language learning as socially mediated. He posited that higher cognitive functions, including language, develop through interaction with cultural artifacts and more knowledgeable others. In this view, language is not merely a system of rules but a tool that mediates thought and social communication. Successful learning, therefore, occurs in learners’ Zone of Proximal Development (ZPD) – tasks they can accomplish with guidance – highlighting the need for collaborative and context-rich instruction. When applied to foreign language education, this theory implies that engaging with target-language users and cultural contexts helps learners internalize new language and worldview. As Fahim and Haghani note, language classrooms should thus “scaffold” learners’ development by situating activities within their ZPD and emphasizing meaningful social interaction. Byram’s Model of Intercultural Communicative Competence. A seminal framework is Byram’s (1997) model of Intercultural Communicative Competence (ICC), which reframes language teaching goals around intercultural dimensions. According to Byram, ICC consists of five savoirs (knowledges or competencies): (1) Savoir: factual and sociocultural knowledge of one’s own and other cultures (e.g. social institutions, history); (2) Savoir-être: attitudes of openness, curiosity, and empathy toward cultural others; (3) Savoir comprendre: interpretive skills, the ability to decode and relate cultural events or texts from another culture; (4) Savoir apprendre/faire: discovery skills and action, including posing questions and learning about culture independently; and (5) Savoir s’engager: critical cultural awareness, the capability to evaluate cultural practices critically and reflect on power relations across cultures. Hoff (2020) underscores that Byram’s model has shaped curricula in many countries, embedding intercultural aims alongside communicative competence. For example, modern foreign language textbooks often include cultural information and reflection tasks aligned with these savoirs, to prepare learners for “successful collaboration across cultures”. Kramsch and Symbolic Competence. Building on culture-in-language ideas, Kramsch emphasizes the symbolic dimension of intercultural competence. She argues that simply teaching facts about cultures is insufficient; learners must develop an awareness of how language and culture shape meaning. In Kramsch’s view, the “self that is engaged in intercultural communication is a symbolic self constituted by language and systems of thought”. She introduces the concept of
Proceedings of the 11th International Scientific Conference 98 symbolic competence: the ability to interpret the implicit meanings in discourse, to understand how cultural values and power relations are encoded in language, and to imaginatively adopt another’s perspective. For example, Kramsch notes that learners need to grasp “what is meant by what is said, to understand how people use symbolic systems to construct new meanings”. This implies pedagogical focus on reflective discussion, literary texts, and real-life exchanges where cultural nuances surface. Symbolic competence thus bridges linguistic fluency and cultural insight, guiding learners to reconstruct reality through language and negotiate meaning beyond mere factual knowledge. Fantini’s Complex of Abilities. Alvino Fantini (2006) also conceptualizes ICC as a multifaceted ability set. Sinicrope et al. (2007) summarize Fantini’s view that ICC is “a complex of abilities needed to perform effectively and appropriately” in cross-cultural interactions. These abilities span cognitive, affective, and behavioral domains: for instance, mindsets of curiosity and tolerance, skills in listening and interpreting verbal/nonverbal cues, and motivational factors. Fantini argues that ICC develops longitudinally, and education can shape it through sustained intercultural experiences. His definition underscores that sociocultural competence is not a single skill but an integrated set of attitudes, knowledge, and strategies. This aligns with research highlighting the importance of fostering empathy, adaptability, and critical reflection in language learners (Byram & Wagner, 2018). Kunanbayeva’s Intercultural-Communicative Framework. In the Central Asian context, Salima S. Kunanbayeva has advanced a linguoculturological communicative methodology. She treats intercultural-communicative competence as a system of interrelated sub-competencies. Kunanbayeva distinguishes between sociocultural (linguo-cultural) competencies (orientation to one’s own and other cultures) and cognitive/reflective components. A key concept is the formation of a learner’s secondary cognitive consciousness – essentially a constructed worldview of the target culture parallel to one’s native cultural schema. In her view, language instruction aims to gradually build this secondary consciousness through carefully designed tasks: precommunication exercises (introducing cultural concepts), communicative simulations (experiencing cultural interaction), and post-communication reflection. She also highlights a conceptual sub-competence (tools for modeling the foreign-language world) and a personalitycentered sub-competence (personal adaptation of cognitive mechanisms for language learning). While detailed citations are scarce outside Russian publications, her model complements others by integrating psychological and cultural dimensions. It emphasizes that learners must not only learn linguistic forms, but also internalize cultural categories to “adequately interact with other cultures” (Kunanbayeva, 2010). Thematic Synthesis: Together, these theories converge on several points. First, culture is inseparable from language: learning a language inherently involves adopting new cultural perspectives (Byram; Kramsch). Second, competence is multidimensional: it includes knowledge (informational), attitudes (openness, curiosity), interpretive skills, and metacognitive awareness (Fantini; Byram). Third, social interaction is essential: cognitive growth occurs through mediated dialogue (Vygotsky) and intercultural encounters (Kramsch; Kunanbayeva). Finally, sociocultural competence serves broader educational goals: it underlies learners’ capacity to navigate diversity, contributing to inclusive and globalized classrooms. This article employs a theoretical, narrative literature review methodology. We surveyed peer-reviewed academic literature, seminal books, and relevant conference proceedings on language learning, intercultural communication, and socio-cultural psychology. Key search terms included “sociocultural competence,” “intercultural communicative competence,” “foreign language education,” and names of foundational scholars (Byram, Kramsch, Fantini, Vygotsky, Kunanbayeva). Only scholarly publications (journals, edited volumes, and academic books) were considered. The review is integrative: it synthesizes multiple conceptual frameworks rather than
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 99 presenting new empirical data. Emphasis was placed on the theoretical constructs and definitions provided by major authors and on how these have been applied in language pedagogy. By crosscomparing models and linking them to educational aims, we aimed to identify core themes relevant to developing sociocultural competence in foreign language learners. DISCUSSION The theoretical frameworks reviewed converge on a central premise: language learning is inextricably linked with cultural learning. Communicative competence is no longer conceived merely in terms of grammatical accuracy or lexical fluency, but rather as a socially and culturally situated practice. As Byram (1997) argues, language learners must be prepared not only to use the language appropriately, but to engage critically and reflectively with their own and others’ cultural assumptions. His model of Intercultural Communicative Competence (ICC), especially the savoirs framework, is particularly instructive in offering a structured pedagogical target. It calls on educators to design curricula that develop linguistic knowledge, intercultural attitudes (e.g., openness, curiosity), interpretive and discovery skills, and critical cultural awareness. This implies that educators must intentionally go beyond teaching cultural “facts” to cultivating deep, reflective cultural engagement. Claire Kramsch (2011) deepens this perspective by introducing the idea of symbolic competence, shifting the focus from surface-level culture to the symbolic systems through which culture and identity are expressed. Her work foregrounds the interpretive nature of communication—highlighting that every linguistic interaction carries culturally shaped meanings and worldviews. In practice, this perspective advocates for the integration of authentic texts (literature, film, media, conversation transcripts), tasks that explore narratives, metaphors, and nonverbal codes, and reflection on how language constructs social realities. Activities that compare how different cultures talk about emotions, politeness, time, or space, for instance, provide learners with insight into underlying cultural logics. Kramsch’s contribution encourages teachers to become not just conveyors of language rules, but facilitators of cultural meaningmaking. The influence of Vygotsky’s sociocultural theory reinforces the interactive nature of language and cultural development. His concepts of the Zone of Proximal Development (ZPD) and cultural mediation provide a pedagogical rationale for collaborative, scaffolded learning. A socioculturally oriented classroom would not merely deliver cultural content, but would immerse learners in dialogic, problem-solving activities where they negotiate meaning with peers and instructors. Role-plays, simulations, peer interviews, and tandem exchanges serve this function well. Through such interaction, students co-construct cultural understanding in a supportive environment, where feedback and modeling guide them toward more competent intercultural behavior. These social learning processes mirror the emergence of what Kunanbayeva calls “secondary cognitive consciousness”—a conceptual reshaping of the learner’s worldview through engagement with another culture’s linguistic and social norms. Fantini’s (2006) emphasis on longitudinal development reinforces the idea that sociocultural competence must be nurtured over time. Intercultural growth cannot occur in isolated lessons; rather, it requires consistent exposure, diverse cultural encounters, and opportunities for reflection. Educators should structure curricula as intercultural journeys, gradually expanding learners’ exposure from familiar topics to more complex cultural dilemmas. Reflective tools such as intercultural journals, portfolios, and virtual exchanges can support this process. As learners document and interpret their experiences, they gain awareness of their own positioning and learn to navigate ambiguity and difference—core attributes of global citizens. Crucially, sociocultural competence plays a foundational role in inclusive education. In multicultural classrooms, where students bring varied cultural identities and experiences,
Proceedings of the 11th International Scientific Conference 100 intercultural instruction helps foster mutual respect and understanding. For example, structured comparisons of students’ cultural traditions (e.g., food customs, festivals, family structures) can validate diverse identities and promote peer learning. When educators encourage all voices to be heard, learners not only gain cultural knowledge but also practice empathetic listening—an essential social-emotional skill. This supports broader goals of social cohesion, equity, and respect for human dignity. At the same time, sociocultural competence is indispensable for global citizenship education (GCE). Learners equipped with intercultural skills are better prepared to engage with global issues—such as climate change, migration, or social justice—that require collaboration across cultural and linguistic boundaries. Language educators thus serve not only as instructors of communicative ability but also as facilitators of global awareness and civic engagement. The integration of sociocultural competence into language learning aligns with UNESCO’s goals of fostering learners who are “globally competent, culturally aware, and socially responsible.” Language learning becomes a space where students begin to see themselves as agents of change, capable of bridging divides and contributing to intercultural dialogue. Kunanbayeva’s focus on the cognitive dimension of cultural learning is particularly valuable here. Her concept of secondary cognitive consciousness suggests that sociocultural competence is not merely behavioral or informational—it is deeply cognitive and conceptual, involving the reorganization of the learner’s understanding of the world. This demands more than surface-level engagement: it requires conceptual comparison, semantic analysis, and perspective-shifting. Culturally embedded tasks—such as interpreting proverbs, debating ethical dilemmas across cultures, or analyzing media representations—can deepen this cognitive engagement. As learners begin to view the world through the conceptual lenses of the target culture, they become capable of cognitive empathy—understanding how others construct reality and why they act the way they do. Ultimately, the development of sociocultural competence demands a whole-curriculum approach. It should be embedded in learning objectives, assessment criteria, classroom norms, and school values. Teachers should be supported through professional development in intercultural pedagogy and reflective teaching practices. Institutional policies should encourage project-based learning, community partnerships, and international collaborations that extend intercultural learning beyond the classroom. Furthermore, digital technologies and social media platforms offer valuable tools for virtual intercultural exchanges, expanding learners’ access to diverse voices and perspectives. In summary, sociocultural competence is not just a language-learning outcome—it is a transformative capacity that empowers learners to understand, connect with, and contribute to an increasingly interconnected world. It fosters critical consciousness, interpersonal adaptability, and ethical engagement, making it a cornerstone of 21st-century education. For language teachers and educational leaders, the imperative is clear: sociocultural learning must be planned, intentional, and central to the mission of modern foreign language education. CONCLUSION Sociocultural competence is a critical dimension of foreign language learning, encompassing learners’ ability to interpret, adapt to, and engage with the cultural contexts of language. Theoretical contributions from Vygotsky, Byram, Kramsch, Fantini, and Kunanbayeva converge on the view that language education must foster social interaction, cultural awareness, and reflective understanding. Vygotsky’s theory reminds us that learning is mediated by interaction and culture; Byram and Fantini outline the concrete abilities (knowledge, attitudes, skills) that comprise intercultural competence; Kramsch adds a layer of symbolic meaning-making; and Kunanbayeva emphasizes the cognitive restructuring of the learner’s worldview. Together,
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 101 these frameworks suggest that language curricula should blend linguistic tasks with cultural discovery, perspective-taking, and critical reflection. Cultivating sociocultural competence has implications far beyond language exams. It aligns with the goals of intercultural communication, enabling learners to connect across differences; it underpins global citizenship, preparing students to address shared challenges with empathy; and it supports inclusive education, as culturally responsive pedagogy recognizes and values all students’ backgrounds. Educators and policy makers should therefore prioritize intercultural goals alongside grammar and vocabulary. Future research could further examine effective classroom interventions for building sociocultural competence and explore assessment methods for this complex construct. In sum, developing sociocultural competence in foreign language learners is essential for fostering mutual understanding in our diverse world. As our review shows, it draws on robust theoretical foundations, and its importance is echoed across educational discourses. Embracing these insights can transform language learning into a vehicle for building cultural bridges and nurturing globally competent citizens. References Byram, M. (1997). Teaching and assessing intercultural communicative competence. Multilingual Matters. Fahim, M., & Haghani, M. (2012). Sociocultural perspectives on foreign language learning. Journal of Language Teaching and Research, 3(4), 693–699. Hoff, H. E. (2020). The evolution of intercultural communicative competence: Conceptualisations, critiques, and consequences for 21st century classroom practice. Intercultural Communication Education, 3(2), 55–74. Kramsch, C. (2011). The symbolic dimensions of the intercultural. Language Teaching, 44(3), 354– 367. Kunanbaeva, S. S. (2005). Modern foreign language education: methodology and theory. Almaty.- 2005. Kunanbayeva, S. S. (2010). Theory and practice of modern foreign language education. Almaty: Edelveiss Printing House, 94-261. Kunanbayeva, S. S. (2013). The Modernization of Foreign Language Education: The Linguocultural– Communicative Approach. London: Hertfordshire Press. Sinicrope, C., Norris, J., & Watanabe, Y. (2007). Understanding and assessing intercultural competence: A summary of theory, research, and practice. Second Language Studies, 26(1), 1–58. Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes (M. Cole et al., Eds.). Harvard University Press.
Proceedings of the 11th International Scientific Conference 102 UDC 372.881.1 THE ROLE OF AI-BASED MOBILE APPLICATIONS IN THE DEVELOPING FOREIGN LANGUAGE LEXICAL COMPETENCE Zhadil Zhanel Rinatkyzy 4th Year Bachelor student, “6B01701-Teacher of two foreign languages”, KazUIR & WL Ablai Khan, Almaty, Kazakhstan Zhumabekova Galiya Baiskanovna Candidate of Pedagogy, Professor, KazUIR & WL Abylai Khan, Almaty, Kazakhstan Abstract. The integration of Artificial Intelligence (AI) into mobile language learning applications has transformed the process of acquiring foreign language lexical competence. Lexical competence, encompassing knowledge of word forms, meanings, collocations, grammatical behavior, and pragmatic usage, is a critical component of overall language proficiency. This study explores the role and effectiveness of AI-based mobile applications in enhancing learners' lexical competence. Using a mixed-method approach, both quantitative data from usage statistics and qualitative feedback from learners were analyzed. Findings indicate that AI-based applications provide adaptive, personalized, and interactive learning experiences, facilitating deeper engagement with vocabulary. However, challenges related to technological dependence, content accuracy, and learner motivation remain. Implications for educators and language learners are discussed. Keywords: AI, mobile applications, lexical competence, foreign language learning, vocabulary acquisition, adaptive learning. Introduction In the modern era, technological advancements have significantly influenced the field of foreign language education. Among these innovations, AI-based mobile applications have emerged as powerful tools for enhancing learners’ lexical competence. In the context of Kazakhstani education, lexical competence is reflected in curricula, teacher training, and methodologies for foreign language instruction. Developing lexical competence is an essential component of any foreign language program, as a rich and accurate vocabulary enables learners to communicate effectively, comprehend texts, and engage in meaningful interactions. The importance of lexical competence has been emphasized by numerous scholars in the field of language education and second language acquisition. For instance, Nation (2013) highlights that vocabulary knowledge not only supports academic achievement but also facilitates students’ adaptation to new learning environments, interaction with peers, and overall communicative proficiency. Lexical competence is therefore a key resource for learners’ future academic and professional success, influencing their ability to express ideas clearly, understand native speakers, and participate confidently in intercultural communication. Acquiring robust lexical competence allows learners to use language accurately and appropriately in different contexts, manage communication effectively, and demonstrate their linguistic and cognitive abilities. AI-based mobile applications, which incorporate adaptive learning algorithms, gamification, and
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 103 personalized feedback, provide innovative pathways for learners to expand their vocabulary knowledge efficiently. Despite the potential benefits, educators face challenges in integrating these applications into formal language instruction, including ensuring meaningful engagement, maintaining content accuracy, and balancing technology use with traditional teaching methods. The presence of these challenges underscores the urgency of investigating the role of AI-based mobile applications in developing foreign language lexical competence. Understanding their effectiveness and limitations is crucial for designing evidence-based strategies that support learners in mastering vocabulary and achieving higher levels of language proficiency. Methodology. Data collection To conduct the study and answer the research questions, the researcher used a descriptive approach, which focused on observing and describing learners’ experiences and progress in developing lexical competence through AI-based mobile applications. The study described learners’ vocabulary acquisition, usage, engagement, and perceptions without attempting to establish causal relationships. Design: Since the aim of the study is to investigate how AI-based mobile applications support the development of lexical competence, a descriptive design was chosen. According to Cuthill (2002), descriptive research is appropriate when a topic is not fully explored and the goal is to provide a clear and detailed account of observed phenomena. Although AI applications in language learning have been studied globally, there is limited research describing their impact on lexical competence among Kazakhstani learners. Participants and Settings: To achieve the purpose of the study, 60 university students aged 18–25 with intermediate English proficiency (B1–B2 CEFR) were involved. All participants had prior experience using mobile applications for language learning. The researcher applied random sampling to select participants to ensure that every student had an equal chance of being included in the study. Thomas (2020) stated that random sampling is used to ensure the reliability of statistical observations. The study was conducted in university language labs and online learning environments, where participants used AI-based applications such as Duolingo, Memrise, and LingQ for 30 minutes daily over a six-week period. Instrumentation: To achieve the purpose of the research, the researcher utilized a questionnaire as the primary data collection instrument. To gather data concerning learners’ experiences and challenges while using AI-based mobile applications, the questionnaire was constructed and provided to the students. The students were asked to answer multiple-choice questions and provide more detailed responses in open-ended questions. Data analysis: Since the study used a descriptive approach, the data were analyzed to provide a detailed picture of learners’ lexical competence development. Quantitative data from the preand post-tests and application analytics were summarized using descriptive statistics such as averages, percentages, and frequency counts. Qualitative data from questionnaires and interviews were analyzed thematically to identify common patterns and learners’ experiences. This methodology allowed the researcher to describe in detail how AI-based mobile applications support the development of foreign language lexical competence among university students. Results In order to show the relevance of this topic, a questionnaire was conducted among university students who used AI-based mobile applications to improve their lexical competence. The aim was to investigate students’ experiences, perceived benefits, and challenges while using these applications. The first question in the questionnaire asked about students’ experience with mobile learning applications. Based on the responses, illustrated in Figure 1, show that 40% of the students had been using such applications for less than 6 months, 35% for 6–12 months, and 25%
Proceedings of the 11th International Scientific Conference 104 for more than one year. This indicates that the majority of students had moderate experience with AI-based learning tools, which is relevant for observing their lexical development. Figure 1: Students’ experience with AI-based mobile learning applications The second question asked, “Which features of AI-based applications help you improve vocabulary the most?” Students’ answers varied and are summarized in Table 1. Table 1. Features of AI-based applications supporting lexical development Feature Percentage of Students Adaptive exercises based on individual progress 38% Gamified tasks and rewards 25% Immediate feedback on spelling, grammar, and collocations 20% Repetition and spaced learning 12% Access to authentic texts and examples 5% Based on these answers, it can be concluded that students primarily perceive adaptive exercises and gamified tasks as the most effective features for enhancing their vocabulary knowledge. Immediate corrective feedback was also considered useful for consolidating lexical competence. The third question of the questionnaire aimed to identify the challenges students face while using AI-based mobile applications. The results, summarized in Table 2, show that the most common difficulty reported by students was a lack of motivation, affecting 30% of respondents. This was followed by distractions from mobile devices, mentioned by 25% of students. Technical issues, such as occasional errors in the applications, were reported by 20% of participants. Additionally, 15% of students indicated difficulties in understanding some words without teacher guidance, while 10% highlighted the lack of opportunities for contextual practice as a challenge. Table 2: Challenges Faced Challenge Percentage of Students Lack of motivation 30% Distractions from mobile devices 25% Occasional technical errors 20% Difficulty understanding words without guidance 15% Lack of contextual practice 10%
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 105 The final question asked how students cope with difficulties encountered while using AIbased learning applications. The most common strategy was setting daily learning goals, reported by 40% of students. This was followed by combining app-based learning with offline exercises (25%), repeating challenging exercises multiple times (20%), and seeking additional examples or explanations online (15%). These strategies indicate that students actively employ self-regulated learning methods to overcome challenges and enhance their comprehension in both digital and traditional contexts. These results show that AI-based mobile applications play a significant role in supporting lexical competence. Students find them useful, especially for adaptive practice, gamified learning, and immediate feedback. At the same time, challenges such as motivation and lack of context highlight the need to integrate these tools with teacher guidance and complementary learning strategies. Discussion The findings of this study demonstrate that AI-based mobile applications have a significant impact on enhancing foreign language lexical competence among university students. Consistent with previous research (e.g., Nation, 2013; Thomas, 2020), the results suggest that adaptive, personalized, and interactive features of these applications provide a supportive environment for vocabulary acquisition. The majority of students in this study reported that adaptive exercises tailored to individual progress were the most effective tool for learning new words, reflecting the importance of personalized learning pathways in facilitating deeper engagement and retention. Gamified tasks and rewards were also highly valued, indicating that motivation-enhancing features can encourage consistent practice and sustain learner engagement. Immediate feedback on spelling, grammar, and collocations further contributed to consolidating lexical knowledge, which aligns with the literature emphasizing the role of corrective feedback in second language acquisition. Despite the benefits, the study also highlights several challenges associated with using AIbased mobile applications. A lack of motivation was reported as the most common difficulty, followed by distractions from mobile devices and occasional technical issues. These findings underscore that technological tools alone cannot guarantee effective learning; learner engagement and self-regulation remain critical. The results show that students employ various coping strategies, such as setting daily learning goals, combining app-based exercises with offline practice, and repeating challenging exercises, reflecting the active role of learners in managing their learning process. This finding resonates with self-regulated learning theory, which emphasizes goal-setting, monitoring, and adaptive strategies as key components of effective learning (Zimmerman, 2002). Furthermore, some students noted difficulties in understanding certain words without teacher guidance and a lack of contextualized practice. This indicates that AI-based applications, while effective for vocabulary expansion, may not fully replace traditional classroom interactions or authentic communicative experiences. Integrating these tools with teacher-led instruction and contextualized tasks can address these gaps, providing scaffolding to support comprehension and appropriate usage of newly acquired vocabulary. Overall, the study provides evidence that AI-based mobile applications are a valuable complement to traditional language instruction, particularly in supporting lexical competence development. They offer flexibility, personalization, and interactive engagement, which are essential for modern language learning. However, to maximize their effectiveness, educators should combine digital tools with pedagogical guidance, context-rich activities, and strategies that promote learner motivation and self-regulation. Future research could investigate long-term effects of AI-based applications on lexical retention, examine different proficiency levels, and
Proceedings of the 11th International Scientific Conference 112 Huang, Y. (2014). Pragmatics. Oxford University Press. Hymes, D. (2016). Foundations in sociolinguistics: An ethnographic approach. Routledge. Ide, S. (1989). Formal forms and discernment: Two neglected aspects of universals of linguistic politeness. Multilingual Matters. Japan National Tourism Organization. (2020). Statistics of inbound tourists to Japan. https://www.jnto.go.jp/jpn/statistics/visitor_trends/index.html Kádár, D. Z., & Haugh, M. (2013). Understanding politeness. Cambridge University Press. Kecskes, I. (2010). Intercultural pragmatics. Oxford University Press. Kim, S., & Park, H. (2018). The role of pragmatics in negotiation strategies: A cross-cultural analysis. International Negotiation, 23(1), 47–67. https://doi.org/10.1163/15718069-23011078 Li, M., & Wang, J. (2017). Exploring politeness strategies in cross-cultural business communication: A case study approach. International Journal of Business Communication, 54(2), 183–201. https://doi.org/10.1177/2329488417692854 Liu, Y., & Li, X. (2020). The influence of pragmatic factors on cross-cultural conflict resolution: An experimental study. International Journal of Conflict Management, 31(2), 215–234. https://doi.org/10.1108/IJCMA-06-2019-0094 Matsumoto, D., Hwang, H. C., & Frank, M. G. (2016). Nonverbal communication: Science and applications. Sage Publications. Mazrui, A. A., & Mazrui, A. M. (2016). The African condition: A political diagnosis. University of Chicago Press. Ngugi, W. T. (2018). Decolonising the mind: The politics of language in African literature. Heinemann. Pew Research Center. (2020). Key findings about U.S. immigrants. https://www.pewresearch.org/fact-tank/2020/07/07/key-findings-about-u-s-immigrants/ Samovar, L. A., Porter, R. E., McDaniel, E. R., & Roy, C. S. (2016). Communication between cultures (9th ed.). Cengage Learning. Scollon, R., & Scollon, S. W. (2001). Intercultural communication: A discourse approach. Blackwell Publishers. US Census Bureau. (2020). Languages spoken in the United States. https://www.census.gov/data/tables/2013/demo/2009-2013-lang-tables.html Wang, C., & Lee, D. (2016). The impact of pragmatic awareness on intercultural communication: A longitudinal study. International Journal of Intercultural Relations, 54, 1–12. https://doi.org/10.1016/j.ijintrel.2016.07.002 Yule, G. (2016). The study of language (6th ed.). Cambridge University Press. Zhang, L., & Chen, H. (2019). Cross-cultural pragmatics in online communication: A social media analysis. Journal of Computer-Mediated Communication, 24(3), 121–136. https://doi.org/10.1111/jcc4.12285
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 113 ОСОБЕННОСТИ ИССЛЕДОВАНИЯ ВЕБПЛАТФОРМЫ ДЛЯ ПОВЫШЕНИЯ УСПЕВАЕМОСТИ УЧАЩИХСЯ В ОБРАЗОВАТЕЛЬНЫХ УЧРЕЖДЕНИЯХ Авдиев Мадияр Талгатулы Магистрант, Карагандинский технический университет имени Абылкаса Сагинова Аннотация В данной статье рассматриваются особенности и влияние веб-платформы, предназначенной для повышения академической успеваемости студентов в образовательных учреждениях. Проведенный всесторонний обзор литературы предоставляет теоретическую основу исследования и выявляет пробелы в существующих исследованиях. В работе используется комбинированный подход, сочетающий количественные и и качественные данные полученные с помощью структурированного опроса. Результаты исследования показывают, что веб-платформы играют значительную роль в обеспечении доступа к образовательным ресурсам, улучшении взаимодействия с преподавателями и предоставлении своевременной обратной связи, что способствует улучшению академической успеваемости. Однако технические проблемы и ограниченная удобность использования остаются проблемами, требующими решения. Кейсы успешных внедрений подчеркивают лучшие практики и ключевые факторы успеха при интеграции веб-платформ в образовательные процессы. Ключевые слова: Веб-платформа, электронное обучение, образовательные технологии, академическая успеваемость, инструменты онлайн-обучения Введение Образовательные веб-сайты являются одним из важнейших инструментов для обучения и повышения успеваемости учащихся. Они используются учащимися для получения необходимой им информации, такой как домашние задания, учебные ресурсы и данные об оценках. Они также позволяют учителям общаться с учениками и родителями в режиме реального времени с помощью текстового или видеочата. Учителя также могут размещать важные объявления о предстоящих мероприятиях или экзаменах на веб-сайте, чтобы все всегда были в курсе. Например, если учитель хочет поделиться заданием со своими учениками и у них нет доступа к школьному компьютерному кабинету, они могут разместить информацию об этом на школьном веб-сайте. Таким образом, доступ будет у всех учащихся, даже если у них дома нет компьютеров. В современном мире, где доступ к информации находится всего в одном клике, образовательные веб-сайты стали очень популярными среди людей всех возрастных групп. Они позволяют пользователям получать информацию на любую тему, которая их интересует, без необходимости искать её в других источниках, таких как книги или библиотеки. Эти сайты также очень полезны для учителей, которые могут использовать их как дополнительные материалы при подготовке уроков для своих учеников. Это значительно упрощает процесс, так как все, что нужно – это доступ к интернету, который сейчас есть у большинства людей. Такие сайты предоставляют ученикам ресурсы, необходимые для их успеха за пределами школы, включая возможность выполнять домашние задания и общаться с
Proceedings of the 11th International Scientific Conference 114 учителями. Некоторые школы даже начали предлагать виртуальные занятия, где учащиеся могут учиться из дома в своём собственном темпе. Электронное обучение стало вызывать больший интерес у педагогов после недавней пандемии COVID-19, и теперь образование немыслимо без электронного обучения. Электронное обучение – это форма образования, использующая технологии для обеспечения эффективного и удобного обучения в любом месте и в любое время. Электронное обучение также можно определить как любую систему обучения, которая использует электронные ресурсы для формализованного преподавания. Основными компонентами электронного обучения являются компьютеры и интернет, независимо от того, где происходят преподавание и обучение [1]. Аналогично, удовлетворенность учащихся и их академические достижения в процессе онлайн-обучения привлекли значительное внимание ученых, которые использовали несколько теоретических моделей для оценки этих показателей (Abuhassna, Megat, Yahaya, Azlina, & Al-rahmi, 2020; Abuhassna & Yahaya, 2018; Al-Rahmi, Othman, & Yusuf, 2015a; Al-Rahmi, Othman, & Yusuf, 2015b). Настоящее исследование освещает влияние онлайн-платформ обучения на удовлетворенность учащихся в зависимости от их прошлого опыта и отношения к таким платформам, чтобы определить, какие учащиеся будут удовлетворены онлайнкурсами [2]. Большинство университетов в развитых странах, если не все, в той или иной степени используют информационно-коммуникационные технологии (ИКТ) в своих курсах. Например, наши учреждения, Политехнический университет Каталонии (UPC) и Университет Барселоны (UB), ориентированы на обучение в аудиториях и внедрили платформу электронного обучения Moodle. Эта популярная платформа привлекает внимание благодаря своему педагогическому подходу к образованию, основанному на конструктивистских и социально-конструкционистских теориях обучения (Moodle, 2009). Однако, несмотря на огромный потенциал Moodle как педагогического инструмента, часто она используется лишь как хранилище учебных материалов, не раскрывая весь свой функционал. Курсы, где применяется e-status, обычно базируются на лекциях в классах, и такая комбинация очного и онлайн-обучения относится к так называемому "смешанному обучению" (blended learning или b-learning). Кроме того, e-status включает черты интегрированных систем обучения (ILS), которые, как отмечают Вуд и др. (1999), включают: - содержание учебной программы (хотя e-status не включает это напрямую, но позволяет добавлять ссылки в задачи); - систему учета данных учащихся; - систему управления обучением. Корни ILS уходят в 1960-е годы, когда Патрик Саппс в Стэнфордском университете разработал первые концепции. В 1990-х они были модернизированы благодаря новым технологиям, таким как интернет и мультимедийные форматы. Эти системы базируются на нео-бихевиористической модели обучения, которая включает автоматический выбор задач, управляемую практику и индивидуальную обратную связь (Wood et al., 1999). Однако обучение с использованием e-status также включает элементы конструктивизма: - акцент на активности студентов; - роль преподавателя сводится к катализатору процесса построения знаний; - предоставление студентам набора задач, мониторинг их прогресса. Студенты работают индивидуально, но не изолированно: система предоставляет показатели эффективности, позволяя сравнивать свои результаты с результатами других студентов.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 115 e-status — относительно простая платформа, специализирующаяся на численных решениях задач, особенно в области базовой статистики для высшего образования. Ее узкая специализация позволяет адаптировать задачи под образовательные цели курса. Классификация образовательных целей Блума (1956) полезна для характеристики задач, представленных на платформе. Среди категорий когнитивного обучения (знание, понимание, применение, анализ, синтез и оценка) e-status подходит для упражнений как минимум в первых четырех из них. Платформа предоставляет студентам преимущества: - доступ к материалам в любое время и из любого места; - мгновенная оценка выполненных упражнений; - обратная связь, включающая как общее резюме активности, так и детальный разбор каждой задачи. Перед тем как студенты столкнутся с реальными и сложными задачами в профессиональной жизни, они должны освоить базовые шаги различных статистических техник через практику. Платформа e-status позволяет студентам повторять задачи с новыми данными, сохраняя интерес к их решению. Повторение, часто ассоциируемое с запоминанием и воспринимаемое как неэффективный метод, здесь используется как средство для активного обучения и осознания прогресса. Вместо традиционных методов (например, упражнений с бумагой и ручкой) estatus стимулирует студентов к активной работе и формирует осознанное отношение к процессу обучения [3]. Методы исследования. Был создан опрос, чтобы узнать, насколько эффективны Вебплатформы для учебной программы и учащихся. Анкета была спроектирована с учетом различных аспектов, включая паттерны использования, воспринимаемые преимущества, возникшие проблемы и предложения по улучшению. Общий опрос состоял из 10 вопросов, два из которых были открытыми. Анкета была спроектирована с учетом различных аспектов, включая паттерны использования, воспринимаемые преимущества, возникшие проблемы и предложения по улучшению. Собранные данные были проанализированы как в аналитическом, так и в сравнительном плане. Результаты и обсуждение. Для изучение особенности и влияние веб-платформы на улучшение академической успеваемости студентов в образовательных учреждениях был проведен опрос. Опрос был создан в электронном варианте и был распространен в виде ссылки. В исследование приняли участия студенты бакалавриата Карагандинского технического университета имени Абылкаса Сагинова. Опрос был заполнен 167 участниками. Исследование показало, что 79 процентов студентов используют веб-платформы каждый день (см. рисунок 1).
Proceedings of the 11th International Scientific Conference 116 Рисунок 1 - Данные по использованию частности веб-платформ Примечание: Составлено автором Также было выявлено что 15% учащихся использует платформы для обучения еженедельно. В результате исследовании выяснилось что всего 4% студентов используют такие платформы ежемесячно, а 2 % учащихся исползует еще реже. Все 167 участники опроса не выбрали вариант никогда. Это показывает что все учащихся в каком то мере пользуется веб платформами для обучения. Многие студенты используют веб платформы для обучения и для поднятия свои академические знания. Сейчас существует очень много платформ для обучения, результаты исследования показали что многие учащиеся пользуются веб платформой Cousera (38%). Платформа Canvas используется 29% студентов. В Canvas можно сделать различные контенты или презентации для урока. А также он дает возможность для взаимоотношения студентов с преподавателями. Многие студенты может делать различные и красочные материалы для уроков. Это поможет им поднять свой академическую успеваемость и хорошо влияет к критичному мышлению. Рисунок 2 - Данные по использованию веб-платформ (%)
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 117 Примечание: Составлено автором Google Classroom (18%) занимает заметную долю, что указывает на доступность и частую интеграцию этой платформы в различные образовательные учреждения. Khan Academy имеет самый низкий процент использования среди рассмотренных платформ - всего 4%. Это может указывать на то, что данная платформа в основном используется для углубленного изучения отдельных тем или как вспомогательный ресурс для самостоятельной подготовки в конкретных областях. Несмотря на то, что Khan Academy предлагает бесплатные образовательные курсы по множеству дисциплин, её применение может быть ограничено в учебных заведениях, где предпочтение отдаётся более структурированным платформам для управления курсами и учебным процессом, таким как Canvas или Google Classroom (см. рисунок 2). На рисунке 3 представлены данные о восприятии студентами влияния веб-платформ на их успеваемость. 79,6% респондентов отметили, что веб-платформы оказали положительное влияние на их успеваемость. Это подавляющее большинство отражает значительную роль технологий в современном образовании. Учащиеся, скорее всего, выиграют от гибкости, доступности и разнообразия ресурсов, которые предоставляют вебплатформы. Эти платформы часто обеспечивают самостоятельное обучение, доступ к высококачественным учебным материалам и инструментам для эффективного общения и сотрудничества со сверстниками и преподавателями. Такие особенности, по-видимому, тесно связаны с потребностями учащихся в обучении, повышая их способность хорошо справляться с учебой. Рисунок 3 - Влияние платформой на успеваемость (%) Примечание: Составлено автором Выделенные красным сегментом 16,3% студентов ответили, что они не ощущают никакого положительного влияния веб-платформ на свою успеваемость. Это говорит о том, что, хотя большинство считает эти платформы полезными, заметное меньшинство может столкнуться с трудностями при их эффективном использовании. Возможные причины могут включать отсутствие цифровой грамотности, недостаточный доступ к надежным технологиям или Интернету или непригодность определенных платформ для конкретных академических нужд. В этом разделе подчеркивается важность устранения барьеров, которые могут помешать некоторым учащимся в полной мере воспользоваться преимуществами цифрового образования.
Proceedings of the 11th International Scientific Conference 118 Самый маленький желтый сегмент, составляющий 4,1% ответов, указывает на студентов, которые не уверены в том, как веб-платформы влияют на их успеваемость. нерешительность студентов показывают что они не осознают как веб платформы помогает им на уроках. Или же наоборот они думают что успехи в академических оценок сильно влияет веб сайты чем они сами, обесценивая свой труд. Здесь важно подчеркивать без инициативы учащихся и их труда невозможно достичь хороших результатов. Также эта неопределенность может быть вызвана ограниченным доступом к таким платформам или неоднозначным опытом. Веб-платформы удобны тем что предоставляют учащимся круглосуточный доступ к учебным материалам, ресурсам и заданиям. Многие веб-платформы включают интерактивные элементы, такие как викторины, симуляторы и дискуссионные форумы. Эти инструменты более активно вовлекают учащихся в процесс обучения, помогая закрепить концепции и поощряя критическое мышление. Заключение. В результате исследования можем сказать что веб-платформы играют решающую роль в современном образовании, повышая успеваемость за счет улучшения доступа к ресурсам, интерактивного обучения и своевременной обратной связи. Чтобы максимально использовать свой потенциал, образовательные учреждения должны сосредоточиться на решении выявленных проблем и учете отзывов учащихся при разработке и внедрении этих цифровых инструментов. Это поможет создать более эффективную и благоприятную учебную среду, способствующую успеху учащихся. Список использованной литературы 1. Shana Z., Naser K., Zeitoun E. Impact of web-based learning plaorms on primary school students’ academic performance in the UAE: Exploring the digital froner //EURASIA Journal of Mathemacs, Science and Technology Educaon. – 2024. – Т. 20. – №. 1. – С. em2385. 2. Abuhassna H. et al. Development of a new model on ulizing online learning plaorms to improve students’ academic achievements and sasfacon //Internaonal Journal of Educaonal Technology in Higher Educaon. – 2020. – Т. 17. – С. 1-23. 3. Sergeev A. et al. Online Educaonal Plaorm as a Web Content Management System in the Organizaon of Student-Teacher Interacon //Proceedings of the Computaonal Methods in Systems and Soware. – Cham : Springer Internaonal Publishing, 2021. – С. 846-856. 4. Sabirova E. G., Fedorova T. V., Sandalova N. N. Features and advantages of using websites in teaching mathemacs (Interacve educaonal plaorm UCHI. ru) //Eurasia Journal of Mathemacs, Science and Technology Educaon. – 2019. – Т. 15. – №. 5. – С. em1729. 5. Edeh M. O. et al. Impact of e-learning plaorms on students’ interest and academic achievement in data structure course //Coal City University Journal of Science. – 2020. – Т. 1. – №. 1. – С. 1-16. 6. Kember D. et al. Understanding the ways in which design features of educaonal websites impact upon student learning outcomes in blended learning environments //Computers & Educaon. – 2010. – Т. 55. – №. 3. – С. 1183-1192. 7. Mamedova L. et al. Online educaon of engineering students: Educaonal plaorms and their influence on the level of academic performance //Educaon and informaon technologies. – 2023. – Т. 28. – №. 11. – С. 15173-15187.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 119 ЖАСАНДЫ ИНТЕЛЛЕКТТІ ОҚЫТУ ТӘЖІРИБЕЛЕРІ ЖӘНЕ ДАМУ БОЛАШАҒЫ К.З.Халикова п.ғ.к., профессор, https://www.scopus.com/authid/detail.uri?authorId=57729604200 , https://orcid.org/0000-0003-0242-8708 Ә.Д.Төрекелдиева магистрант, Абай атындағы Қазақ ұлттық педагогикалық университеті, Қазақстан Республикасы Аңдатпа. Бұл мақала Қазақстан Республикасындағы жасанды интеллект (ЖИ) саласындағы кадрларды даярлаудың қазіргі тәжірибелеріне, осы процесті реттейтін нормативтік-құқықтық құжаттарға және даму болашағына жан-жақты талдау жасауға Талдау барысында "Цифрлық Қазақстан" бағдарламасы, дербес деректерді қорғауға қатысты заңдар сияқты негізгі нормативтік құжаттарға шолу жасалып, олардың ЖИ-ді дамытуға әсері айқындалады. Қорытынды бөлімде ЖИ-дің ұлттық басымдықтары – қазақ тіліндегі деректер қорын қалыптастыру және этикалық ЖИ-ді дамыту мәселелеріне баса назар аударылған. Сонымен қатар, жүргізілген зерттеулерге байланысты қорытынды ұсыныстар келтірілген. Түйінді сөздер: Жасанды интеллект, Generative AI, Мұғалім-ассистент, нормативтік құжаттар, деректер базасы. Кіріспе Бүгінгі таңда білім беру саласындағы өзекті мәселелердің бірі - жасанды интеллект (ЖИ) технологияларын елдің әлеуметтік-экономикалық дамуының қозғаушы күші ретінде қабылдап, білім беру саласына ұтымды енгізу болып табылады. Олай дейтін себебіміз, мемлекеттердің бәсекеге қабілеттілігі олардың осы саладағы мамандарды даярлау қабілетіне тікелей байланысты екенін практика көрсетіп отыр. Бүкіл әлем елдері «Ақпараттық-коммуникациялық технологиялар» (АКТ) дәуірінен «Жасанды интеллект» дәуіріне көшу кезеңін бастан кешіруде. Дәл осы тұста, Қазақстан Республикасы цифрландыру процесін елдің экономикалық дамуының негізгі бағыттарының бірі ретінде ұстанып, жасанды интеллект технологияларын білім беру саласына енгізуге байланысты бірнеше маңызды шараларды қолға алып, жүзеге асыру үстінде. Осы орайда, Қазақстан Республикасында ЖИ саласын дамытуға бағытталған мемлекеттік бағдарламалары мен бастамалары білім беру жүйесіне үлкен міндеттер жүктейді. ЖИ тек жоғары оқу орындарындағы жеке мамандық ретінде ғана емес, сонымен бірге, жалпы білім беру мазмұнының ажырамас бөлігі ретінде қарастырылуда. Бұл өзгерістер оқу үдерісін, оқыту әдістері мен мамандарды кәсіби даярлау мәселесін қайта қарауды талап етеді. Зерттеудің мақсаты – әлем елдерінде жасанды интеллектің оқыту тәжірибелері мен Қазақстанда жасанды интеллектті оқытудың ағымдағы тәжірибелеріне жан-жақты талдау жүргізіп, осы бағыттағы негізгі нормативтік-құқықтық құжаттарға шолу жасау, пайдаланылып жатқан заманауи әдістер мен құралдарды айқындау. Осы талдау негізінде, мақала Қазақстанның адами капиталының технологиялық талаптарға сай болуы үшін нақты ұсыныстар беруді көздейді.
Proceedings of the 11th International Scientific Conference 120 Жасанды интеллект негіздерін оқытудағы әлемдік тәжірибелерге шолу Әлемнің алдыңғы қатарлы мемлекеттері жасанды интеллектті (ЖИ) пайдалану мен оны білім беру жүйесіне енгізуде әртүрлі стратегияларды қолдануда. Олардың ішіндегі негізгі бағыттарына: ұлттық стратегиялар, оқу бағдарламаларын интеграциялау, мұғалімдердің біліктілігін арттыру және этикалық мәселелерге басымдық беру жатады. Жасанды интеллектті пайдалану және енгізуге байланысты озық екі мемлекеттің (Сингапур және Жапония) тәжірибелеріне қысқаша тоқталайық. Сингапур ЖИ-ді стратегиялық маңызды технология ретінде қарастырады. Ұлттық бастамалар ретінде AI Singapore (AISG) ұлттық бағдарламасы мектеп оқушыларына арналған білім беру ресурстарын әзірлейді. Білім министрлігі (БМ) ЖИ-мен жұмыс істейтін жекелендірілген оқыту құралдарын ұлттық оқыту платформасы – Студенттік Оқыту Кеңістігіне (SLS) біріктірген. Сонымен қатар, оқыту мазмұнына 2025 жылдан бастап бастауыш және орта мектептерде "AI for Fun" сынды арнайы модульдер енгізуді жоспарлаған. Бұл модульдер ЖИ принциптері мен оның этикалық қолданылуы туралы негізгі түсініктерді қамтамасыз етеді [10]. Келесі негізгі мәселе – жасанды интеллекттің мектеғпте оқытылуына байланысты, ол жеке пән ретінде емес, Информатика, Математика, Жаратылыстану пәндерінің мазмұнына кіріктіріп оқытуды қолға алған. Технологияларды енгізуге байланысты әлемдегі көш бастаушы елдердің бірі Жапония мемлекеті. Бұл мемлекет жасанды интеллектті ерте кәсіби даярлауға емес, технология туралы іргелі түсінік пен жауапкершілікпен пайдалануға баса назар аударады. Бұл жөнінде Білім, мәдениет, спорт, ғылым мен технологиялар министрлігі (MEXT) ЖИ-ді пайдалануға қатысты нұсқаулықтар әзірлеп, оның ішінде, генеративті ЖИ-ді этикалық және жауапты қолдану ережелеріне тоқталады (мысалы, ағылшын тілін үйрену үшін пайдалану) [11]. Жасанды интеллектті жеке міндетті пән ретінде оқыту қарастырылмайды, ол Информатика, Математика, Әлеуметтік зерттеулер сияқты бар пәндерге біртіндеп біріктіріледі. Мұндағы негізгі мақсат – ЖИ-дің мүмкіндіктері, шектеулері және қоғамға әсері туралы түсінік беру болып табылады. AI құралдарын пайдалануға байланысты мектептерде бейімделетін оқытуды, автоматтандырылған бағалауды және шет тілдерін үйренуге қолдау көрсетуді қамтитын ЖИ құралдарын сынақтан өткізу жүргізілуде [12]. ҚАЗАҚСТАНДАҒЫ ЖАСАНДЫ ИНТЕЛЛЕКТТІ ОҚЫТУДЫҢ ҚҰҚЫҚТЫҚ НЕГІЗДЕРІ Қазақстан Республикасында жасанды интеллект (ЖИ) саласын дамыту, оның ішінде, білім беру аспектісі – мемлекеттік саясаттың негізгі басымдықтарының бірі. ЖИ-ді оқытудың құқықтық негізі бірнеше стратегиялық және заңнамалық құжаттарда бекітілген. Бұл құжаттар ЖИ технологиясын тек енгізуді ғана емес, сонымен бірге, осы салада бәсекеге қабілетті мамандарды даярлауды да жүйелі түрде қамтамасыз етеді. Қазақстан Республикасы Үкіметінің 2023 жылғы қазандағы қаулысымен бекітілген Жасанды интеллектті дамытудың 2024–2029 жылдарға арналған тұжырымдамасы [1] ЖИ экожүйесін құру мен дамытудың негізгі бағыттарын анықтайтын басты стратегиялық құжат болып табылады. Білім беру мен оқыту мәселесі Тұжырымдаманың маңызды бөлігін құрайды. Мұндағы адами капиталды дамытуға бағытталған міндеттер төмендегі мәселелерді қамтиды: Мамандарды даярлау, Межелі көрсеткіш, Оқыту бағдарламаларын енгізу, Зерттеулерді ынталандыру. Мамандарды даярлау мәселесіне байланысты, Тұжырымдаманың басты мақсаты – ЖИ саласындағы білім беру бағдарламаларын жетілдіру арқылы білікті мамандар санын күрт арттыру. Осы аталған мәселелерге байланысты 2029 жылға қарай Қазақстанда ЖИ бойынша білім алған мамандардың санын 80 мыңға дейін жеткізу жоспарланған. Бұл жоспар ЖОО-лар мен ТжКБ (Техникалық және кәсіптік білім беру)
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 121 орындарына үлкен міндет жүктейді. Оқыту бағдарламаларын енгізу мәселесі бойынша 2029 жылға қарай ЖОО-лардың кемінде 60% және ТжКБ орындарының 10%-ы ЖИ бағдарламаларын енгізуі тиіс. Бұл тек ЖИ мамандықтарын ғана емес, сонымен қатар, басқа да салалардағы мамандықтарға ЖИ модульдерін кіріктіруді де білдіреді (мысалы, ЖИ медицинада, қаржыда және ауыл шаруашылығында). Келесі негізгі мәселе - зерттеулерді ынталандыру болып табылады. Тұжырымдама ЖИ саласындағы ғылыми-зерттеу және тәжірибелік-конструкторлық жұмыстарды (ҒЗТКЖ) қолдауды көздейді, бұл білім берудің ғылыми компонентін күшейтеді. Тұжырымдама ЖИ модельдерін оқытуға және зерттеуге қажетті ресурстарды қамтамасыз ету үшін Ұлттық жасанды интеллект жүйесін (ҰЖИЖ) құруды қарастырады. Бұл оқу үдерісінде қолданылатын деректер кітапханаларына және жоғары өнімді есептеу қуаттарына (GPU-лар) қол жеткізуді қамтамасыз етуде шешуші рөл атқарады. 2024 жылы қабылданған (немесе қабылдануы күтілетін) «Жасанды интеллект туралы» Заң ЖИ-ді дамытудың құқықтық негізін қалайды.[2]. Олардың ішінде, ЖИ ұғымын, оны қолдану салаларын және осы технологияны пайдалану кезіндегі субъектілердің жауапкершілігін нақтылайды. Келесі негізгі мәселе, этика және қауіпсіздік болып табылады. Бұл заңнамалық акт ЖИ-ді оқыту кезіндегі деректерді қорғау, авторлық құқық және этикалық нормалардың сақталуын реттейді. Бұл, әсіресе, оқытушылар мен студенттердің ЖИ құралдарын пайдаланудағы құқықтық шеңберді түсінуі үшін өте маңызды. Жасанды интеллектті оқытудың тәжірибесі Қазақстанда соңғы жылдары қарқынды дамып, білім берудің барлық деңгейінде жүйелі түрде енгізіліп келеді. Бұл үдеріс мемлекеттік бағдарламалардың, жетекші университеттердің бастамаларының және жеке IT мектептерінің белсенділігінің арқасында іске асуда. Мектеп деңгейіндегі ЖИ-ді оқыту оқушылардың алгоритмдік және сыни ойлауын дамытуға, сондай-ақ болашақ технологиялық мамандықтарға баулуға бағытталған. Информатика, Робототехника және Қосымша Білім Беру Шеңберіндегі Оқыту Информатика пәні: ЖИ-дің бастапқы негіздері (мысалы, алгоритмдеу, логикалық операциялар, деректерді талдаудың қарапайым түрлері) Информатика пәнінің жаңартылған мазмұнына енгізілген.[1]. Робототехника кабинеттері: Еліміздің мектептерінде 3000-ға жуық робототехника кабинеті ашылды. Бұл оқу орындарында арнайы конструкторлар мен программалау негіздерін пайдалану арқылы роботтар құрастыру үйірмелері жұмыс істейді. Сонымен қатар, Робототехника курстары ЖИ-дің практикада жүзеге асырылуының (датчиктермен және алгоритмдермен жұмыс) алғашқы қадамы болып табылады. Келесі бағыт - қосымша білім беру болып табылады. Мектептердегі арнайы үйірмелерде оқушылар өздерінің жобаларын (мысалы, пандемия кезіндегі автоматты санитайзер) әзірлеп, республикалық және халықаралық жарыстарға қатысуда. Сонымен қатар, бәсекеге қабілеттілік орталықтарының жұмысы ерекше назар аударады. ЖОО мен мектептерден бөлек, ЖИ саласындағы бәсекеге қабілетті мамандарды дайындауда жеке және мемлекеттік-жекеменшік серіктестік негізіндегі IT мектептер мен орталықтар маңызды рөл атқарады. TechOrda Бағдарламасы: Бұл бағдарлама арқылы Үкімет ваучерлер бөліп, жекеменшік IT мектептерде (мысалы, IT STEP, Alem, Tomorrow School) мамандар даярлауды қаржыландырады. ЖИ саласындағы курстар осы бағдарламаның 15%-на дейін қамтуы мүмкін.[7]. Tomorrow School: Astana Hub жанындағы осы мектеп Қазақстандағы алғашқы жасанды интеллект мектебі ретінде белгілі. Ол peer-to-peer (бір-бірінен үйрену) форматында оқытады және студенттер AI инженериясы бағытында тегін білім ала алады.
Proceedings of the 11th International Scientific Conference 128 [7]Cukurova, M., et al. (2022).A learning analytics approach to monitoring the quality of online one-to-one tutoring. Journal of Learning Analytics, 9(3), 1–20. [8]Ubachs, G. (2022).Quality assurance systems for digital higher education in Europe. In M. Jemni, K. K. Bhagat, & A. Khribi (Eds.), The Digital Turn in Higher Education (pp. xxx–xxx). Singapore: Springer.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 129 ENHANCING METACOGNITIVE AWARENESS THROUGH DIGITAL TOOLS IN ESL CLASSROOMS Rysbay Ayaulym Yermankyzy 1st-year student, 7M01701 – Foreign language: two foreign languages Scientific Advisor: Shingareva M. Yu. Candidate of Philological Sciences, NJSC South Kazakhstan Pedagogical University named after Ozbekali Zhanibekov, Shymkent, Kazakhstan Annotation The digital age has brought about radical changes in educational practices, especially in the teaching of English as a second language (ESL). Developing students’ metacognitive awareness, that is, understanding and regulating their own thinking and learning processes, has become an important goal of modern pedagogy. This article examines how new digital tools can improve students' metacognitive thinking awareness in an ESL context. It comprehensively analyzes the role of artificial intelligence (AI), mobile applications, and online learning platforms in developing self-analysis, self-monitoring, and independent learning. Practical suggestions are provided for integrating metacognitive strategies into technologically advanced language learning environments. Keywords: metacognition, ESL, digital tools, innovative, artificial intelligence (AI), reflective learning, metacognitive skills, learning platforms. Introduction In a rapidly developing society, considerable attention is paid to the role of technology in education, which promotes the development of independence and critical thinking in students. Teaching English as a second language (ESL) requires the development of metacognitive awareness, which depends on learners' understanding of their cognitive processes and their ability to manage them effectively. Modern digital innovative technologies, when integrated purposefully, serve as key tools for improving metacognitive development. As a result, students now have the opportunity not only to master the language but also to strengthen their metacognitive abilities. Online learning environments, interactive applications, and AI-powered feedback systems provide real-time information on student performance. These tools enable students to identify their strengths and weaknesses, evaluate the effectiveness of their learning strategies, and adjust their approaches accordingly. As Flavell [1] noted, understanding human cognitive abilities is key to developing lifelong learning skills. This article explores the ways in which digital tools support the development of metacognitive awareness in EFL classrooms, discusses pedagogical implications, and identifies best practices for teachers. Theoretical Background. Metacognition, broadly defined as the understanding and regulation of one's own cognitive processes, is the subject of extensive research in cognitive and educational psychology. The theoretical basis of metacognition is laid in the fundamental works of Vygotsky [2], who emphasized the social origin of higher mental functions. According to Vygotsky, cognitive
Proceedings of the 11th International Scientific Conference 130 development initially occurs interpsychologically through social interaction, and then becomes intrapsychological through interpsychic interaction. This process involves a gradual transition from other forms of regulation, when teachers, parents or peers guide the student, to self-regulation, when students control and direct their own cognitive activity [3]. A key concept in Vygotsky's theory is scaffolding, which Bruner defines as structured support provided by a more knowledgeable person to facilitate a learner's development, which is removed as the learner gains independence [4]. A complement to the concept of scaffolding is the zone of proximal development (ZPD), which represents the gap between what a learner can achieve independently and what he can achieve with guidance [5]. Through these mechanisms, students develop the ability to think reflectively and solve problems independently, effectively “learning to learn” [6]. Furthermore, Vygotsky emphasized the role of language in mediating thinking, noting that verbalized self-observation allows students to understand their cognitive processes [7]. Flavell’s model of metacognition further formalized these ideas by identifying metacognitive knowledge, metacognitive experience, goals (or tasks), and actions (or strategies) [1]. Metacognitive knowledge encompasses three categories: person (beliefs about oneself and others as learners), task (knowledge of task requirements), and strategy (knowledge of effective cognitive methods). Metacognitive experience involves conscious feelings and reflections related to cognitive activity, such as recognizing difficulty in understanding a concept or evaluating progress. These experiences interact with metacognitive knowledge and activate both cognitive and metacognitive strategies [8]. Nelson and Narens [9] proposed a two-level model of metacognition, distinguishing a meta-level (knowledge about cognition) and an object-level (cognitive task execution). Monitoring occurs when the meta-level observes object-level activity, while control occurs when the metalevel directs object-level processes. This emphasizes the dynamic interaction between awareness and regulation in metacognition. Teachers play a vital role in developing metacognition based on their knowledge, beliefs, and experiences of effective classroom practices and the metacognitive abilities available to students [10]. In summary, metacognition emerges from the interplay of social interaction, individual reflection, and instructional support. Vygotsky’s foundational theories provide a framework for understanding the origins of development, while Flavell and Nelson, Narens clarify its cognitive and regulatory dimensions. Metacognitive Skills and Their Role in Effective Learning Metacognitive skills enable learners to plan, monitor, and evaluate their thinking and problem-solving strategies, promoting independent and adaptive learning [8]. Key skills include: Planning: Setting goals, selecting strategies, and effectively allocating resources. Monitoring: Continuously assessing understanding, identifying gaps, and adjusting approaches. Adjusting and correcting: Modifying strategies if initial approaches prove ineffective. Self-assessment and reflection: Assessing learning outcomes and reinforcing effective strategies. Attention and emotional management: Maintaining concentration, coping with distractions, and overcoming difficulties. Metacognitive skills also support higher-level abilities such as critical thinking, problem solving, creative thinking, independent decision-making, and strategic learning. Developing these skills is essential for lifelong learning, enabling individuals to engage mindfully with material, adapt to challenges, and optimize cognitive growth [10].
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 131 Digital Tools as Catalysts for Metacognitive Development Digital technologies offer interactive, adaptive and reflective teaching methods that stimulate learners' metacognitive processes, including soft and hard skills, in the process of learning a foreign language. Moreover, they can become tools to help students learn a language quickly. 1. AI-Based Learning Platforms. AI platforms such as Duolingo, Grammarly, EWA English, Copilot, and AI Grader provide instant feedback on grammar, vocabulary, pronunciation, and writing strategies. Learners can reflect on their errors, monitor progress, and adjust strategies in real time. Intelligent tutoring systems guide learners along personalized paths, supporting self-regulation and metacognitive monitoring [5]. 2. Digital Portfolios and Reflective Platforms. Platforms like Google Classroom, Seesaw, and Filmore Videos allow learners to document progress, set goals, and reflect on learning experiences. Reflective prompts such as: “What strategies helped you learn this vocabulary?” “What difficulties did you encounter?” “How can you improve next time?” enable students to engage in selfassessment and critical reflection [3]. 3. Mobile Learning Applications. Mobile-assisted language learning (MALL) applications, including Quizlet, Memrise, Anki, and Difftit, promote learner autonomy and flexibility. Learners can plan study schedules, monitor accuracy, and evaluate performance, practicing all three stages of metacognitive regulation beyond the classroom [5]. 4. Online Collaboration and Peer Feedback Tools. Platforms such as Padlet, Edmodo, Microsoft Teams, and ClassPoint support collaborative reflection and peer assessment. Social interaction, as described by Vygotsky [2], promotes higherorder thinking, including metacognitive awareness. Peer feedback allows learners to evaluate their own output critically, fostering reflective thinking and perspectivetaking. 5. AI-Generated Media and Simulations. Tools such as Twee and Synthesia provide immersive AI-generated scenarios and avatars, enabling learners to engage in creative problem-solving, self-questioning, and reflective evaluation. These tools make abstract concepts tangible and encourage interactive metacognitive assessment.
Proceedings of the 11th International Scientific Conference 132 Tools Description YMetaconnect Guides learners through Review–Action–Reflection cycles for self-assessment and strategy planning. SRLAgent Gamified AI system supporting goal-setting, self-monitoring, and reflection in real time Cognitive Mirror Provides adaptive feedback to help learners plan, monitor, and evaluate cognitive strategies. LearningRO (RoTutor) AI assistant scaffolding learning tasks and encouraging reflective selfregulation. Praktika.ai 3D avatar role-play for spoken language reflection and strategy adjustment. Betty’s brain Teaches learners to explain concepts to a virtual agent, encouraging metacognitive reflection through teaching Table 1. Digital Tools for Enhancing Metacognitive Awareness in ESL Learners Methodology This study employs a qualitative analytical approach to evaluate and compare quantitative tools in terms of their effectiveness in developing metacognitive awareness in English as a second language learners, examining them from theoretical, functional and pedagogical perspectives. Data Sources: Literature Review: Research on metacognition, ESL education, and digital learning. Digital Tool Analysis: Features of mainstream (Duolingo, Grammarly, Quizlet, Padlet, etc.) and innovative tools (Owlgorithm, Reflexion, SRLAgent). Teacher and Learner Insights: Previously published reports contextualized tool usage. Tool Selection Criteria. Tools were analyzed for their capacity to support: Metacognitive knowledge and experiences Planning, monitoring, and evaluation Collaborative and social interaction Data Analysis Coding and categorization according to Flavell’s (1979) framework Mapping tools to stages of metacognitive regulation Comparative qualitative assessment of mainstream vs. innovative tools Discussion Analysis indicates that digital tools enhance metacognition in ESL classrooms in multiple ways: AI-based platforms provide immediate feedback, supporting self-regulation. Digital portfolios foster reflection and documentation of learning processes. Mobile apps extend metacognitive practice beyond the classroom, increasing learner autonomy. Collaboration tools encourage social reflection and perspective taking. AI-generated simulations promote higher-order thinking through immersive, interactive scenarios.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 133 Innovative tools such as Owlgorithm, Reflexion, and SRLAgent show particular promise in providing adaptive scaffolding and personalized metacognitive prompts. These tools may enhance engagement and critical self-evaluation beyond traditional applications. However, challenges include digital overload, inequitable access, and the need for teacher training to integrate tools effectively. Teachers must carefully select tools that emphasize reflection and strategic thinking rather than rote memorization. Pedagogical Aspects of Teaching English as a Foreign Language The integration of digital tools into EFL classrooms suggests significant opportunities for developing metacognitive awareness. Teachers can use AI-powered platforms, mobile apps, digital portfolios, and collaboration tools to help students plan, monitor, and evaluate their learning. Effective implementation requires alignment with cognitive theory, student needs, and learning goals, ensuring that technologies complement, rather than replace, sound pedagogical practice. AI-based platforms provide real-time feedback and can be incorporated into structured lesson plans, encouraging students to analyze errors, identify patterns of performance, and adjust learning strategies [1, 8]. Digital portfolios allow for the documentation and analysis of progress [3]. Mobile language learning (MALL) applications provide flexibility for practice and selfmonitoring outside the classroom [5]. Collaboration and peer feedback tools facilitate social mediation, critical analysis, and perspective-taking [2]. Innovative artificial intelligence tools offer a personalized framework for reflection, minimizing cognitive overload while supporting autonomous learning. Assessment and Feedback Strategies for Metacognitive Development Integrating assessment and feedback mechanisms into digital learning environments enhances metacognitive awareness. Formative assessments using artificial intelligence tools provide immediate and actionable feedback [5]. Peer assessments using platforms like Padlet encourage students to evaluate both their own work and that of their peers, fostering reflective thinking and perspective taking. Self-assessment prompts and checklists integrated into apps or digital platforms help students plan, monitor, and evaluate strategies [1]. Adaptive AI feedback using tools like SRLAgent or Cognitive Mirror personalizes guidance, enabling focused metacognitive reflection and independent problem solving. Conclusion Digital tools have transformed ESL instruction by making metacognitive processes visible and actionable. When integrated purposefully, these tools enable learners to plan, monitor, and evaluate learning, promoting autonomy and self-regulation. Teachers play a critical role in designing experiences that foster reflective thinking. Future research could explore empirical studies comparing the effects of different digital tools on ESL learners’ metacognitive awareness, providing evidence for best practices in technology-mediated language learning. References 1. Flavell, J. H. Metacognition and Cognitive Monitoring: A New Area of Cognitive– Developmental Inquiry // American Psychologist. – 1979. – Vol. 34, No. 10. – P. 906–911. 2. Vygotsky, L. S. Mind in Society: The Development of Higher Psychological Processes. – Cambridge, MA: Harvard University Press, 1978. – 159 p. 3. Brown, A. L. Metacognition, Executive Control, Self-Regulation, and Other More Mysterious Mechanisms // In: Weinert, F. E., Kluwe, R., editors. Metacognition, Motivation, and Understanding. – Hillsdale, NJ: Erlbaum, 1987. – P. 65–116. 4. Bruner, J. S. The Process of Education. – Cambridge, MA: Harvard University Press, 1960. – 232 p.
Proceedings of the 11th International Scientific Conference 134 5. Wood, D., Bruner, J. S., Ross, G. The Role of Tutoring in Problem Solving // Journal of Child Psychology and Psychiatry. – 1976. – Vol. 17, No. 2. – P. 89–100. 6. Brown, A. L., Campione, J. C., Day, J. S. Learning to Learn: On Training Students to Learn from Texts // Educational Researcher. – 1983. – Vol. 12, No. 3. – P. 7–13. 7. Vygotsky, L. S. Thought and Language. – Cambridge, MA: MIT Press, 1986. – 187 p. 8. Efklides, A. Metacognition: Defining Its Facets and Levels of Functioning in Relation to Self-Regulation and Self-Regulated Learning // European Psychologist. – 2002. – Vol. 7, No. 4. – P. 241–252. 9. Nelson, T. O., Narens, L. Metamemory: A Theoretical Framework and New Findings // Psychology of Learning and Motivation. – 1990. – Vol. 26. – P. 125–173. 10. Nespor, J. The Role of Beliefs in the Practice of Teaching // Journal of Curriculum Studies. – 1987. – Vol. 19, No. 4. – P. 317–328.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 135 THE EFFECTIVENESS OF THE MONTESSORI METHOD IN TEACHING FOREIGN LANGUAGES TO PRESCHOOL CHILDREN Talapova A.K. Master of Pedagogical sciences, Kazakh Ablai Khan University of International Relations and World Languages, Almaty, Kazakhstan Toromanova M.S. 4th year student, Kazakh Ablai Khan University of International Relations and World Languages,Almaty, Kazakhstan ABSTRACT This arcle invesgates the effecveness of the Montessori Method in enhancing foreign language learning among preschool children. Rooted in Montessori’s principles of independence, sensory exploraon, and self-directed learning, the approach integrates language acquision into a natural and engaging process of discovery. The study employed a mixed-methods descripve design involving 50 preschool teachers from various educaonal instuons in Kazakhstan. Data were collected through a structured quesonnaire consisng of 15 Likert-scale items and 5 openended quesons, administered via Google Forms over a two-week period. Quantave data were analyzed using descripve stascs, while qualitave responses were examined through themac analysis. Results indicated that teachers strongly believe the Montessori Method fosters vocabulary development, communicave confidence, and learner movaon. However, challenges such as limited professional training, material adaptaon, and balancing autonomy with linguisc structure were also idenfied. The findings suggest that the Montessori approach provides a developmentally appropriate and humanisc framework for early foreign language educaon, emphasizing experienal learning, emoonal engagement, and holisc development. Keywords: Montessori Method, foreign language learning, preschool educaon, early childhood, learner movaon. INTRODUCTION In the 21st century, the ability to communicate in a foreign language has become a crucial aspect of children’s personal, cultural, and cognive development. As globalizaon connues to expand, parents and educators are increasingly movated to introduce foreign languages during early childhood, when the brain is especially recepve to linguisc input. However, tradional methods of foreign language instrucon oen emphasize rote memorizaon, repeon, and teacher-centered acvies, which may not align with the natural learning tendencies of preschool children. In contrast, the Montessori Method offers a child-centered, holisc, and developmentally appropriate approach that can make foreign language learning both effecve and enjoyable. Developed by Maria Montessori, this method is grounded in the belief that children learn best through self-directed acvity, hands-on exploraon, and interacon with a carefully prepared environment. Within this framework, language learning becomes a natural extension of a child’s curiosity and engagement with their surroundings rather than a forced academic task. The Montessori philosophy emphasizes the absorbent mind, a concept describing the young child’s unique ability to unconsciously and effortlessly absorb language and informaon from the environment (Lillard, 2017). This principle aligns closely with contemporary theories in
Proceedings of the 11th International Scientific Conference 136 psycholinguiscs and cognive development, which highlight early childhood as the opmal period for language acquision (Aydoğan, 2016; Harna, 2018). Research supports the effecveness of the Montessori approach in fostering early linguisc competence. Studies reveal that Montessori-educated preschoolers oen demonstrate superior vocabulary development, phonological awareness, and communicave confidence compared to their peers in tradional sengs (Zamroni & Wijaya, 2024; Febyawa & Wulandari, 2021; Atlı, Korkmaz, Taştepe, & Akyol, 2016). When applied to foreign language educaon, Montessori methods, such as sensorial materials, real-life contexts, and spontaneous communicaon—create immersive linguisc experiences that nurture comprehension and expression naturally. However, successful implementaon requires well-prepared teachers who understand both Montessori pedagogy and the principles of second language acquision. Challenges may arise in maintaining the balance between language exposure and freedom of choice, ensuring consistent interacon in the target language, and adapng materials for mullingual classrooms. The current study aims to explore how the Montessori Method supports foreign language learning among preschool children, focusing on its pedagogical, cognive, and emoonal benefits. The main objecves are as follows: 1. To analyze how the Montessori approach influences language acquision and communicaon skills in preschool learners. 2. To examine how Montessori environments foster movaon, independence, and self-confidence in foreign language learning. 3. To idenfy challenges educators face in applying Montessori principles to language instrucon and suggest praccal strategies to address them. Accordingly, this study seeks to answer the following research queson: How does the Montessori Method enhance the effecveness of foreign language learning for preschool children through its principles of independence, exploraon, and individualized instrucon? By addressing this queson, the research aims to contribute to the growing field of early childhood bilingual educaon, demonstrang how the Montessori philosophy can serve as an effecve and humanisc alternave to convenonal language teaching. The findings are expected to inform preschool curricula, teacher training programs, and educaonal policy, promong more natural and meaningful approaches to language learning during the formave years of a child’s life. LITERATURE REVIEW The Montessori Method, founded by Maria Montessori, emphasizes self-directed learning, independence, and acve engagement with the environment. Contemporary researchers have explored how this approach supports not only general cognive and social development but also language acquision and foreign language learning in early childhood educaon. Lillard (2017) provides a comprehensive overview of the scienfic foundaons of the Montessori approach, demonstrang that its principles align with current findings in developmental psychology and cognive science. She argues that Montessori classrooms, with their focus on autonomy, sensory exploraon, and individualized learning, naturally promote linguisc development through meaningful interacon. In a later study, Lillard (2019) highlights the enduring relevance of Montessori’s ideas in the modern educaonal context, emphasizing how the method culvates curiosity and intrinsic movaon, key factors in successful language acquision. Several studies have examined the specific impact of the Montessori approach on early language learning. Aydoğan (2016) found that Montessori educaon posively affects preschool children’s language development, parcularly in vocabulary and pronunciaon. Similarly, Zamroni and Wijaya (2024) demonstrated that Montessori-based acvies enhance vocabulary acquision
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 137 and comprehension by engaging children in mulsensory and contextualized experiences. Febyawa and Wulandari (2021) further confirmed the effecveness of Montessori principles in teaching English to young learners, nong improvements in movaon, fluency, and communicave confidence. Teachers’ perspecves on Montessori pedagogy also reveal its strengths and challenges. Atlı, Korkmaz, Taştepe, and Akyol (2016) found that educators working in Montessori schools view the method as beneficial for children’s holisc development but emphasize the need for specialized training to implement it effecvely. Harna (2018) supports this view, idenfying that while child-centered strategies enhance engagement, teachers must carefully balance freedom with structured guidance to ensure consistent progress in language learning. Beyond linguisc outcomes, Montessori educaon fosters creavity, autonomy, and crical thinking, skills essenal for lifelong learning. Bereczki and Kárpá (2018), in their systemac review, noted that teachers who adopt construcvist and creavity-oriented approaches, such as Montessori, tend to create environments that encourage self-expression and innovave problemsolving. These qualies are directly linked to communicave competence in a second language context. Overall, the reviewed literature suggests that the Montessori Method provides a scienfically grounded, child-centered framework that effecvely supports early foreign language acquision. Its emphasis on independence, exploraon, and mulsensory learning promotes not only linguisc proficiency but also movaon and self-confidence. However, successful applicaon depends on teacher preparaon, contextual adaptaon, and ongoing reflecon on pedagogical pracce. MATERIALS AND METHODS Research Design This study employed a mixed-methods descripve design, integrang quantave and qualitave approaches to invesgate preschool teachers’ percepons of using the Montessori Method in teaching foreign languages. The mixed design allowed for numerical analysis of teachers’ atudes and experiences as well as an in-depth interpretaon of their open-ended responses. The study lasted six weeks, and consisted of three main phases: survey design and pilong, data collecon through Google Forms, and data analysis. The research sought to idenfy how Montessori principles influence children’s language learning, movaon, and communicave development in early educaon sengs. Parcipants The parcipants in this study were 50 preschool teachers from various educaonal instuons across Kazakhstan, including both public and private preschools, as well as Montessoribased centers. All parcipants had at least one year of teaching experience and were involved in early childhood language educaon. Table 1 summarizes the demographic profile of the teachers who parcipated in the study. Parcipaon was voluntary and anonymous, and informed consent was obtained prior to data collecon. Ethical approval was granted by the Instuonal Review Board of the researcher’s university.
Proceedings of the 11th International Scientific Conference 144 Zamroni, A., & Wijaya, H. (2024). Enhancing vocabulary acquision using Montessori methods in early childhood educaon. Internaonal Journal of Early Language Learning, 12(1), 77–92.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 145 DEVELOPING STUDENTS’ SCIENTIFIC LITERACY THROUGH THE ORGANIZATION OF FIELD-BASED AND PRACTICAL LEARNING ACTIVITIES Issayev G.I. Candidate of Technical Sciences, Associate Professor, Khoja Akhmet Yassawi International Kazakh-Turkish University, Turkistan, Kazakhstan Nugman R.M. Master's Student, Khoja Akhmet Yassawi International Kazakh-Turkish University, Turkistan, Kazakhstan Abstract. This study examines the scienfic and methodological foundaons for organizing field-based and praccal learning acvies aimed at developing students’ scienfic literacy in the context of contemporary science educaon. The research was conducted among 9th–10th grade students in the city of Turkistan using two internaonally validated instruconal models: the Inquiry-Based Science Educaon (IBSE) method and Kolb’s Experienal Learning Cycle. A quasiexperimental design was employed, involving an experimental group taught with IBSEand Kolbbased praccal tasks and a control group taught through tradional methods. The findings revealed that both approaches significantly enhanced key components of scienfic literacy, including scienfic explanaon, hypothesis formulaon, experimental planning, data interpretaon, reflecve thinking, and the applicaon of knowledge in new contexts. The experimental group demonstrated substanally higher gains compared to the control group, confirming the effecveness of structured experienal and inquiry-oriented praccum acvies. The results underscore the pedagogical importance of integrang research-based praccal learning into science curricula to strengthen students’ scienfic thinking, inquiry abilies, and evidence-based reasoning. Keywords: scienfic literacy; inquiry-based learning; field-based praccum; experienal learning; IBSE; Kolb cycle; science educaon; research skills. In the contemporary system of professional educaon, the effecve integraon of students’ In the contemporary educaon system, the significance of science-oriented subjects is steadily increasing, and the development of students’ scienfic literacy has become a strategic priority of the pedagogical process. Scienfic literacy refers to the integrated capacity of learners to explain natural phenomena from a scienfic perspecve, formulate research quesons, conduct experiments, make evidence-based conclusions, and apply the obtained results in real-life situaons. The rapid transformaon of socio-technical processes in the twenty-first century, the strengthening of STEM integraon, and the growing complexity of environmental challenges necessitate enhancing the role of experienal and inquiry-based learning in shaping students’ scienfic worldview. In this context, the scienfically and methodologically sound organizaon of field-based and praccal learning acvies serves as a key instrument for developing scienfic literacy in school educaon. Field-based praccum enables students to observe natural objects directly, conduct laboratory experiments, formulate scienfic hypotheses, and interpret results, thereby culvang
Proceedings of the 11th International Scientific Conference 146 their research culture. This type of work integrates tradional theorecal knowledge with praccal tasks, allowing students to master scienfic methodology, arculate evidence-based reasoning, and develop crical evaluaon skills. Pedagogical studies demonstrate that systemac organizaon of praccal acvies in the classroom significantly enhances students’ conscious acquision of biological, chemical, and ecological knowledge, as well as contributes to the formaon of scienfic language competence. The relevance of the topic is further reinforced by the fact that students’ scienfic literacy is considered one of the core indicators in internaonal assessment systems such as PISA and TIMSS, and has become a major benchmark for improving the quality of educaon in Kazakhstan. PISA findings confirm that the ability to perform praccal, experiment-based tasks is closely linked to students’ level of scienfic thinking. Accordingly, the effecve organizaon of field-based praccum in schools not only deepens subject knowledge but also strengthens learners’ engagement in research acvies and fosters their ecological and scienfic responsibility. The aim of the study is to idenfy the scienfic and methodological foundaons for organizing field-based praccum and to propose effecve approaches for developing students’ scienfic literacy through this process. In line with this purpose, the research focuses on determining the structural components of praccum acvies, methods of organizaon, mechanisms for mastering the logic of scienfic inquiry, and pedagogical condions for enhancing students’ skills in interpreng scienfic results. The scienfic novelty of the study lies in systemazing the theorecal foundaons of developing scienfic literacy through field-based praccum, construcng a content-based model of praccal work, and proposing methodological mechanisms for its implementaon in the educaonal process. This approach contributes to strengthening students’ research potenal, deepening their understanding of learning materials, and creang a scienfic, inquiry-based learning environment. Thus, the effecve organizaon of field-based praccum represents a crucial factor in shaping students’ scienfic thinking, praccal research skills, evidence-based reasoning, and the ability to explain natural phenomena scienfically. The development of students’ scienfic literacy has become one of the central direcons of contemporary internaonal educaonal research. Aikenhead (2006) [1], examining the concept of scienfic literacy in relaon to the socio-cultural context of science educaon, emphasizes that fostering an invesgave stance in learners is a core objecve of the educaonal process. This perspecve is supported by Bybee (2010) [2], who defines scienfic literacy as the ability to explain everyday problems through scienfic methods and highlights the importance of praccal acvies in developing students’ scienfic thinking. Thus, internaonal theorecal frameworks demonstrate that field-based and praccal learning acvies constute a fundamental mechanism for fostering scienfic literacy. The role of praccal acvies in science educaon is comprehensively addressed in Kolb’s (1984) [3] experienal learning theory. Kolb asserts that knowledge is reconstructed through experience, and that students develop high-level cognive processes when they independently analyze their experiences and draw scienfic conclusions. Osborne and Dillon (2008) [4] also emphasize that laboratory work not only contributes to the acquision of scienfic terminology but also enables learners to understand the logic of inquiry and construct evidence-based reasoning. These views posion field-based praccum as a key didacc tool for developing scienfic literacy. The impact of laboratory and field experiences on students’ scienfic understanding and research skills is substanated by numerous empirical studies. Hofstein and Lunea (2004) [5] show that laboratory instrucon enhances learners’ comprehension of scienfic concepts and promotes meaningful engagement with scienfic methodology, while Broman and Parchmann
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 147 (2014) [6] demonstrate that context-based chemistry and biology lessons with strong praccal and applied orientaon support the sustainable development of scienfic literacy. Such findings highlight that praccal acvies influence cognive, procedural, and personal aspects of student development. Studies within internaonal assessment systems further reinforce the relevance of scienfic literacy as a muldimensional construct. According to the OECD (2019) [7] PISA framework, scienfic literacy encompasses explaining phenomena, conducng scienfic inquiry, and interpreng data. De Jong (2019) [8] notes that the formaon of these competencies depends directly on the quality and structure of experienal acvies, idenfying field-based praccum as a primary source of scienfic thinking skills. These insights underline the decisive role of praccal inquiry in shaping scienfic performance indicators at the internaonal level. Research on experimental teaching also expands the theorecal and methodological foundaons of this field. Crawford (2014) [9] demonstrates that systemac engagement with scienfic inquiry in schools facilitates students’ progression from “novice researcher” to “independent inquirer.” Lederman et al. (2014) [10] argue that teaching scienfic methodology must extend beyond conducng experiments to include formulang research quesons, construcng hypotheses, and developing evidence-based conclusions. This underscores the importance of scienfically structuring the model of field-based praccum. Studies conducted in biology and ecology further illustrate how direct interacon with natural objects contributes to the development of students’ scienfic literacy. Tipton et al. (2020) [11] show that fieldwork improves students’ skills in observing natural phenomena, measuring environmental variables, comparing data, and developing ecological reasoning. Fančovičová and Prokop (2019) [12] highlight that direct engagement with living organisms enhances both the emoonal and cognive components of learners’ scienfic worldview. These findings confirm the influence of praccal biology acvies on cognive processes. In recent years, scholars have increasingly focused on combining experimental learning with digital technologies to advance scienfic literacy. Smetana and Bell (2012) [13] demonstrate that virtual models and digital sensors allow learners to record experimental data with high accuracy, while Zacharia et al. (2015) [14] conclude that integrang physical and virtual laboratories strengthens the formaon of scienfic concepts. This approach indicates the need to align field-based praccum with modern educaonal technologies. Overall, the reviewed literature demonstrates that the development of students’ scienfic literacy is closely connected to the effecve organizaon of field-based and praccal learning acvies. Across internaonal research, experienal and inquiry-based engagement consistently emerges as a core mechanism for promong scienfic thinking, data analysis skills, and meaningful understanding of scienfic methodology. Therefore, the systemac and scienfically grounded organizaon of praccum acvies holds decisive importance within the contemporary paradigm of science educaon. The study was conducted among 9th-10th grade students in general educaon schools in the city of Turkistan. A total of 84 respondents parcipated in the research with the purpose of evaluang the effecveness of organizing field-based and praccal acvies in science-related subjects. The study was carried out over the course of one academic semester during the 20242025 school year. School laboratories, small ecological study plots, and biology classrooms were used as the research environment. All field-based and praccal tasks were structured in accordance with the content of the school curriculum. The research was based on two scienfically grounded methods. 1. Inquiry-Based Science Educaon (IBSE) method (Bybee, 1997; Zion & Mendelovici, 2012). IBSE is an internaonally recognized approach for fostering scienfic literacy. The method is grounded in J. Bybee’s 5E instruconal model (Engage–Explore–Explain–Elaborate–Evaluate). In
Proceedings of the 11th International Scientific Conference 148 this study, the IBSE method was employed to develop students’ skills in formulang scienfic quesons, construcng hypotheses, conducng experimental procedures, comparing results, and drawing evidence-based conclusions. In each lesson, students performed praccal tasks related to natural objects and completed inquiry sheets to analyze the collected data. The use of the IBSE method was aimed at enhancing the core components of scienfic literacy scienfic explanaon, data handling, and evidence-based reasoning. 2. Experienal Learning Cycle (D. Kolb, 1984). The experienal learning cycle developed by D. Kolb consists of four stages: Concrete Experience, Reflecve Observaon, Abstract Conceptualizaon, and Acve Experimentaon. As this model aligns closely with the natural structure of praccal scienfic work, it served as a core method in the study. Students were given laboratory tasks involving natural materials (plant samples, soil, and water specimens). At each stage of the cycle, learners described their experiences, analyzed the results in terms of cause–effect relaonships, and linked theorecal concepts with praccal examples. Kolb’s cycle enabled the development of reflecve thinking and metacognive monitoring skills. The study was organized using a quasi-experimental design. Students from two general educaon schools in the city of Turkistan, enrolled in grades 9–10, parcipated in the research, and two groups were formed: Experimental group (n = 42): engaged in field-based and praccal acvies structured according to the IBSE and Kolb methods. Control group (n = 42): completed tradional praccal tasks. To evaluate the effecveness of the field-based praccum, the following instruments were employed: a specialized scienfic literacy test assessing skills such as formulang research quesons, interpreng data, and drawing conclusions; observaon checklists measuring the quality of praccal task performance; reflecve journals aligned with the IBSE framework and Kolb’s experienal learning cycle. To evaluate the impact of the IBSE method on students’ scientific literacy, the initial (pretest) and final (post-test) performance indicators of the experimental and control groups were compared (Figure 1). 0 20 40 60 80 100 1. Formulating a research question 2. Accuracy of hypothesis building 3. Designing an experimental plan 4. Data differentiation and processing 5. Interpretation of results 6. Drawing evidencebased conclusions 7. Use of scientific terminology Control Group Pre-test Experimental Group Pre-test Control Group Post-test Experimental Group Post-test
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 149 Figure 1. Scientific Literacy Indicators According to the IBSE Method The obtained data demonstrate that the applicaon of the IBSE method in organizing fieldbased praccum has a pronounced posive impact on the development of students’ scienfic literacy. During the pre-test stage, the results of both groups were mixed and closely aligned (5567 points), indicang that the inial level of scienfic preparedness was relavely uniform, thereby ensuring the objecvity of the study. Although the control group scored slightly higher in some skills, such as “Use of scienfic terminology” (67 vs. 60), the experimental group outperformed in others (e.g., “Designing an experimental plan”: 62 vs. 67). These variaons reflect natural baseline differences and show that both groups had comparable potenal at the outset. At the post-test stage, the experimental group scored higher than the control group across all indicators, with differences consistently maintained within the 77-86 point range. The greatest improvement was observed in complex cognive skills such as “Designing an experimental plan” and “Drawing evidence-based conclusions,” which confirms the inquiry-driven structure of the IBSE method. The control group also demonstrated some progress; however, this improvement was characterisc of reproducve tasks, with limited changes (69-75 points). This indicates that the growth observed in the experimental group is qualitavely different: students not only acquired factual knowledge but also began to operate within a scienfic logic framework, showing more advanced data interpretaon skills. Overall, the analysis confirms that the IBSE method effecvely fosters higher-order scienfic competencies, including formulang research quesons, construcng hypotheses, analyzing experimental data, and generang evidence-based conclusions. Such dynamics illustrate that the development of scienfic literacy depends not only on the accumulaon of knowledge but also on the meaningful applicaon of scienfic methodology. Thus, organizing field-based praccum according to the IBSE model is a pedagogically jusfied, scienfically validated, and highly effecve approach that leads to significant improvements not only quantavely, but also qualitavely, in students’ scienfic thinking. Field-based praccum organized according to Kolb’s experienal learning cycle was aimed at idenfying students’ abilies in scienfic thinking, reflecon, analysis of experience, and applicaon of obtained data in new situaons. The results are presented in Figure 2. Figure 2. Scienfic Literacy Indicators According to the Kolb Method (Pre-test / Post-test)
Proceedings of the 11th International Scientific Conference 150 The effecveness of the instruconal model based on Kolb’s experienal learning cycle is clearly reflected in the obtained results. At the pre-test stage, the mixed nature of the outcomes demonstrated that the inial scienfic preparedness of the control and experimental groups was relavely similar. The indicators ranged from 50 to 71 points, with the control group outperforming the experimental group in certain areas (e.g., “Applying theory to new situaons”: 71 vs. 65), while the experimental group showed higher results in others (e.g., “Acve experimentaon”: 62 vs. 68). Such a distribuon confirms that both groups had comparable potenal at the beginning of the study, ensuring the objecvity of the findings. Moreover, the pre-test results indicate that students’ skills in reflecon, analysis, and theorecal explanaon were not yet fully developed. The post-test results demonstrate that the experimental group, which was taught using Kolb’s cycle, achieved significant qualitave and quantave improvements. The indicators for this group ranged from 77 to 93 points and exceeded the control group’s results by 10-12 points. Notably, substanal growth was observed in “Acve experimentaon” (90 points), “Applying theory to new situaons” (93 points), and “Reflecve observaon” (88 points), confirming the effecveness of the sequenal structure of Kolb’s cycle experience, reflecon, theorecal conceptualizaon, and applicaon. Although the control group also showed some improvement (74-81 points), these changes were largely limited to reproducve learning, without the deeper cognive shis observed in the experimental group. Overall, the findings provide theorecal and empirical evidence that Kolb’s experienal learning cycle effecvely develops students’ scienfic thinking, analycal skills, evidence-based decision-making abilies, and capacity to apply knowledge in new contexts. This method plays a crucial role in structuring field-based praccum, as it strengthens students’ acve cognive engagement and fosters the comprehensive development of all components of scienfic literacy. The findings of the study clearly demonstrate that the scienfically and methodologically sound organizaon of field-based praccum plays a decisive role in developing students’ scienfic literacy. Systemac applicaon of the IBSE method and Kolb’s experienal learning cycle significantly enhanced students’ abilies to formulate research quesons, construct hypotheses, plan experiments, analyze data, provide theorecal explanaons, and draw evidence-based conclusions. All components of scienfic literacy in the experimental group surpassed those of the control group, confirming the effecveness of inquiry-based and experienal learning in fostering scienfic thinking, reflecon, and metacognive monitoring skills. The results also highlight the necessity of integrang experience-based instruconal methods more widely into the learning process. In parcular, the consistent implementaon of IBSE and Kolb-based praccal tasks promotes the development of students’ scienfic reasoning, evidence-based argumentaon, and higher-order cognive skills required to interpret natural phenomena scienfically. Increasing the proporon of field and laboratory acvies connects scienfic content with real-world contexts, thereby deepening students’ ability to apply theorecal knowledge in pracce. Addionally, incorporang specialized diagnosc tools for assessing scienfic literacy such as tasks that measure research queson formulaon, data interpretaon, and evidence-based reasoning enhances the precision of learning outcomes. The results further indicate the importance of integrang experienal learning with modern digital technologies. The use of virtual laboratories, digital sensors, and simulaon tools alongside praccal tasks strengthens the effecveness of experienal learning and fosters students’ scienfic informaon-handling competencies. Moreover, expanding professional development programs aimed at enhancing teachers’ research capacies is essenal for ensuring the high-quality organizaon of field-based praccum. Overall, the systemac and methodologically grounded organizaon of field and laboratory praccum represents a comprehensive, effecve, and modern approach to developing students’
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 151 scienfic literacy. It not only deepens learners’ scienfic worldview but also significantly enhances their research culture, crical thinking, evidence-based decision-making skills, and cognive engagement with science subjects. This arcle was published with support from the Grant № BR24992814 of the Science Commiee of the Ministry of Science and Higher Educaon of the Republic of Kazakhstan. References 1. Aikenhead, G. S. (2006). Science educaon for everyday life: Evidence-based pracce. Teachers College Press. 2. Bybee, R. W. (2010). Advancing STEM educaon: A 2020 vision. Technology and Engineering Teacher, 70(1), 30-35. 3. Kolb, D. A. (1984). Experienal learning: Experience as the source of learning and development. Prence Hall. 4. Osborne, J., & Dillon, J. (2008). Science educaon in Europe: Crical reflecons. Nuffield Foundaon. 5. Hofstein, A., & Lunea, V. N. (2004). The laboratory in science educaon: Foundaons for the twenty-first century. Science Educaon, 88(1), 28-54. 6. Broman, K., & Parchmann, I. (2014). Students’ applicaon of chemical concepts when solving context-based tasks. Internaonal Journal of Science Educaon, 36(7), 1100-1121. 7. OECD. (2019). PISA 2018 results (Volume I): What students know and can do. OECD Publishing. 8. De Jong, T. (2019). Moving towards engaged learning in science: Challenges and possibilies. Journal of Science Educaon and Technology, 28(3), 225-231. 9. Crawford, B. A. (2014). From inquiry to scienfic pracces in teaching and learning. In N. Lederman & S. Abell (Eds.), Handbook of research on science educaon (Vol. 2, pp. 515-554). Routledge. 10. Lederman, N. G., Lederman, J. S., & Annk, A. (2014). Nature of science and scienfic inquiry as contexts for the learning of science and achievement of scienfic literacy. Internaonal Journal of Educaon in Mathemacs, Science and Technology, 2(3), 138-147. 11. Tipton, M., Jones, A., & Swaffield, S. (2020). Outdoor scienfic inquiry: Impact on students’ environmental reasoning. Environmental Educaon Research, 26(5), 657-674. 12. Fančovičová, J., & Prokop, P. (2019). Children’s knowledge and atudes toward forest ecosystems. Journal of Biological Educaon, 53(3), 350-362. 13. Smetana, L., & Bell, R. (2012). Computer simulaons to support science instrucon and learning: A crical review of the literature. Internaonal Journal of Science Educaon, 34(9), 13371370. 14. Zacharia, Z. C., Manoli, C., Xenofontos, N., & de Jong, T. (2015). Physical versus virtual laboratories in science educaon: An analysis of learning outcomes. Journal of Educaonal Psychology, 107(3), 1052-1067.
Proceedings of the 11th International Scientific Conference 152 DEVELOPMENT OF STUDENTS’ LABORATORY AND PRACTICAL SKILLS THROUGH TEACHING THE FUNDAMENTALS OF BIOTECHNOLOGY Issayev G.I. Candidate of Technical Sciences, Associate Professor, Khoja Akhmet Yassawi International Kazakh-Turkish University, Turkistan, Kazakhstan Zhumagali M.T. Master's Student, Khoja Akhmet Yassawi International Kazakh-Turkish University, Turkistan, Kazakhstan Abstract. The development of laboratory-praccal skills is a central component of modern biotechnology educaon, requiring the integraon of methodological rigor, experimental precision, and scienfic reasoning. This study invesgates the effecveness of Inquiry-Based Laboratory Instrucon (IBLI) as a pedagogical model for forming students’ laboratory competencies in microbiology, molecular genecs, and plant cell culture techniques. Designed within the framework of construcvist learning, IBLI emphasizes independent inquiry, hypothesis formulaon, experimental design, and reflecve interpretaon. Unlike tradional instrucon based on prescripve protocols, IBLI posions learners as acve agents in the research process, promong deeper understanding of biological phenomena and enhancing procedural accuracy. The research was conducted among firstand second-year students of Biology and Biotechnology during the 2024-2025 academic year, involving a control group taught with tradional methods and an experimental group taught using IBLI. Three laboratory modules were implemented, and quantave assessment was performed using a Universal Rubric for Biotechnological Skills. Qualitave analysis included reflecve reports, laboratory notebooks, and observaonal records. Stascal verificaon using Fisher’s F-test demonstrated that the experimental group exhibited greater stability and consistency in post-test performance, confirming the significant influence of the IBLI intervenon. The findings indicate that IBLI substanally improves students’ cognive engagement, technical proficiency, biosafety awareness, and scienfic communicaon skills. By integrang inquiry-based stages problem idenficaon, hypothesis development, experimental execuon, data interpretaon, and reflecon the method supports comprehensive development of research competencies. The study concludes that IBLI represents an effecve pedagogical strategy for advancing biotechnology educaon and preparing students for professional scienfic pracce. Keywords: Biotechnology educaon; laboratory skills; inquiry-based learning; experimental competence; scienfic reasoning; molecular techniques; STEM integraon. The contemporary system of biological educaon aims to train professionally competent specialists who meet the requirements of the labor market, are capable of working confidently with laboratory equipment, and possess well-developed experimental thinking. In this context, teaching the fundamentals of biotechnology has emerged as a relevant pedagogical direcon for organizing students’ scienfic and praccal acvies. As biotechnology is an applied field based on the purposeful use of living systems, cells, and biomolecules, its mastery requires students to
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 153 acquire specific methods, laboratory operaons, biosafety regulaons, and modern analycal technologies. The process of developing laboratory and praccal skills constutes the foundaon of scienfic research culture. These skills include microbiological techniques, operaons with biological materials, work in sterile condions, DNA/RNA extracon and analysis, conducng enzymac reacons, culvaon of biological systems, and quantave and qualitave processing of results. Methodologically sound organizaon of these acvies enables the systemac development of students’ praccal reasoning, abilies in experimental design, and competencies in interpreng research outcomes. The praccal orientaon of teaching biotechnology ensures that learners do not remain at a purely theorecal level, but gain a deep understanding of the mechanisms of real biological processes and the essence of biotechnological operaons. Direct involvement in laboratory pracce not only strengthens students’ professional orientaon but also enhances their interest in scienfic research, and fosters skills in modeling complex biological phenomena and analyzing experimental results. Furthermore, competence-based instruconal methods used in biotechnology educaon (project-based work, problem-based learning, laboratory modules, and STEM/STEAM approaches) enhance learners’ scienfic and cognive acvity, professional language proficiency, use of biological terminology, and scienfic communicaon culture. Accordingly, the development of laboratory and praccal skills through teaching the fundamentals of biotechnology is one of the key scienfic-methodological issues in modern pedagogical biology, vocaonal educaon, and applied biotechnology. The purpose of this study is to idenfy the scienfic and methodological foundaons for developing students’ laboratory-praccal skills in the process of teaching the fundamentals of biotechnology, to systemaze instruconal technologies aimed at biotechnological pracce, and to assess their effecveness through pedagogical experimentaon. The relevance of achieving this purpose is determined by the growing need to train qualified personnel in biotechnology, the demand for implemenng pracce-oriented teaching models, and the necessity to improve the quality of professional training through effecve ulizaon of educaonal laboratories. The issue of developing students’ laboratory and praccal skills in teaching the fundamentals of biotechnology has generated considerable scholarly interest in recent years within the field of biological educaon. Smith (2018) emphasizes that the effecveness of biotechnology learning is directly linked to the student's ability to perform concrete experimental tasks in a laboratory seng. The author argues that praccal instrucon fosters scienfic thinking, skills in experimental design, and evidence-based reasoning, and therefore laboratory modules should be regarded as core components of biotechnology curricula [1]. This perspecve highlights that praccal skills develop as an integrated process alongside theorecal knowledge. Expanding on this idea, Johnson (2020) demonstrates that competence-oriented biotechnological training can be significantly enhanced through systemac organizaon of students’ laboratory acvies. According to the author, problem-based learning, project work, and praccal case studies enable learners to grasp the logic of complex biotechnological operaons and develop skills in data processing and scienfic communicaon. Such an approach posions the development of laboratory-technical skills as an essenal component of overall professional competence [2]. Integrang biosafety requirements into the instruconal process is crucial for safe and effecve acquision of laboratory-praccal skills. Brown and Lee (2019) underscore the importance of fostering a culture of safety in laboratory environments as part of professional preparaon. They argue that mastering sterile techniques, adhering to rules for handling
Proceedings of the 11th International Scientific Conference 256 Сурет 2. Жүргізушінің шаршауын анықтауға арналған компьютерлік көру жүйесінің иллюстрациясы Компьютерлік көру жүйелері бет ерекшеліктерін тануға және интерпретациялауға мүмкіндік береді, бұл үшін инфрақызыл сенсорлар, үшөлшемді бет картасы және сандық портрет деректер базалары қолданылады. Көрсеткіштерді анықтайтын инфрақызыл құрылғы бақылау тақтасына орнатылып, жүргізушіге бағытталады және жүргізушінің жағдайының негізгі индикаторларын – көз координаттары, ашықтық коэффициенті және қарау бағытын – үздіксіз тіркейді. Осы деректерді пайдалана отырып, жасанды интеллект модулі жүргізушінің зейін деңгейін бағалайды және шаршау немесе көңіл аударма белгілерінің бар-жоғын анықтайды. Аномалды үлгілер анықталған жағдайда, жүйе автоматты түрде дыбыстық, визуалды немесе діріл арқылы ескерту сигналын береді, осылайша жүргізушінің назарын аударады. Қазіргі таңда жүргізушінің жағдайын бақылауға арналған көптеген әдістер қолданылады, олар физиологиялық, мінез-құлықтық және көліктік негіздегі категорияларға бөлінеді. Жасанды интеллектке негізделген көпмодалды аналитикалық платформаларды қолдану мұндай жүйелердің дәлдігі мен тиімділігін айтарлықтай арттырады. Бұл технологиялар заманауи интеллектуалды бақылау архитектураларының негізін құрайды, олар жол қауіпсіздігін арттыруға және әртүрлі жұмыс жағдайларында жүргізушінің жайлылығын қамтамасыз етуге бағытталған. Алғыс. Бұл зерттеуді Қазақстан Республикасы Ғылым және жоғары білім министрлігінің Ғылым комитеті қаржыландырады (ЖТН AP25795477 Жасанды интеллект әдістеріннің негізінде нақты уақыт режимінде жүргізушінің жағдайын бақылаудың интеллектуалды цифрлық жүйесін әзірлеу»).
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 257 Әдебиеттер 1. Katasyova D.V., Sibgatullin A.A. Жүргізушілердің функционалдық жағдайын бағалау үшін нейрондық желі моделі. Electronics, Photonics and Cyber-Physical Systems, 2023, vol. 3, no. 1, pp. 69–80. 2. Pham T.A., Zhukova N.A., Evnevich E.L. Адамның бет ерекшеліктерінің факторлық моделіне негізделген қауіпті жүргізуші күйін тану. Izvesa of Tula State University. Technical Sciences, 2021, no. 10, pp. 640–645. 3. Menuhova T.A., Sivov A.A., Bogdanov M.V. Автобус жүргізушілеріндегі стресс факторларын анықтау. Voronezh Scienfic and Technical Bullen, 2022, vol. 950, no. 2(52), June, p. 16. 4. Saltanaeva E.A., Kutsenko S.M. Жүргізушінің шаршау деңгейін бағалау үшін нейрондық желі технологияларын қолдана отырып, жүргізушінің жағдайын талдауда үлгілерді тану әдістерін қолдану. Donetsk University Bullen. Series 04. Technical Sciences, 2025, no. 2, pp. 54–60. 5. Petrosyants D.G., Akhmetvaleev A.M., Katasyov A.S. Жарық өзгерістеріне көз pupil реакциясына негізделген адам функционалдық жағдайын модельдеуге арналған деректер жинау технологиясы. Computer Research and Modeling, 2021, vol. 13, no. 2, pp. 417–427. 6. Xu J., Min J., Hu J. Real-me eye tracking for the assessment of driver fague. Healthcare Technology Leers, 2018, vol. 5, no. 2, pp. 54–58. 7. Jung S.J., Shin H.S., Chung W.Y. Driver fague and drowsiness monitoring system with embedded electrocardiogram sensor on steering wheel. IET Intelligent Transport Systems, 2014, vol. 8, no. 1, pp. 43–50. 8. Andreev A.S., Kiseleva I.A. Driver condion tracking device NSControl. Scienfic Statements, 2021, no. 1(1), p. 13. 9. Moiseev Yu. I. et al. Жүргізушінің ұйқысыздығын болдырмау әдісі. 2019. 10. Yin J., Hu J., Mu Z. The design of the virtual driving experiment plaorm based on EEG. Proceedings of the 2015 Internaonal Conference on Educaon, Management, Informaon and Medicine, Atlans Press, 2015, pp. 1016–1019. 11. Kozin E.S., Bazanov A.V. Vehicle driver idenficaon system based on biometric data. Intellect. Innovaon. Investment, 2020, no. 4, pp. 133–142. 12. Zhao Q., Jiang J. Жүргізушінің шаршауын бақылауға арналған көздің ашылу және жабылу коэффициентін анықтау әдісі. IET Intelligent Transport Systems, 2020, vol. 15, iss. 1, pp. 23–29.
Proceedings of the 11th International Scientific Conference 258 Применение методов обработки естественного языка (NLP) для классификации киберугроз в пользовательских отзывах Жакупжанова Анель Амангелдыкызы Студент 2 курса магистратуры, Казахский национальный исследовательский технический университет имени К.И. Сатпаева, Казахстан, Алматы Аннотация: в статье рассматривается применение методов обработки естественного языка (NLP) для классификации киберугроз на основе пользовательских отзывов и сообщений в социальных сетях. Исследование демонстрирует, что краудсорсинговые данные могут служить ценным источником индикаторов угроз, а современные модели машинного обучения, включая трансформеры, обеспечивают высокую точность и полноту анализа. Проведённый эксперимент показал эффективность предобработки текста, извлечения сущностей и использования Word Embeddings для выявления фишинга, вредоносного ПО, DDoS-атак и социальной инженерии. Полученные результаты подтверждают перспективность интеграции NLP в системы киберразведки и мониторинга угроз. Ключевые слова: обработка естественного языка (NLP), киберугрозы, краудсорсинг данных, машинное обучение, Word Embeddings, киберразведка. Введение Современное развитие цифровых технологий сопровождается стремительным ростом киберугроз, которые затрагивают как отдельные организации, так и широкие слои общества. Одним из ключевых источников информации о возникающих угрозах становятся пользовательские отзывы и сообщения в социальных сетях. Эти данные отражают реальный опыт взаимодействия пользователей с цифровыми сервисами и позволяют выявлять потенциальные инциденты безопасности на ранних стадиях. В условиях увеличивающегося объема информации традиционные методы анализа оказываются недостаточными, что делает актуальным применение методов обработки естественного языка (Natural Language Processing, NLP) для автоматизации классификации угроз. Актуальность данной работы обусловлена необходимостью разработки эффективных инструментов анализа больших массивов текстовых данных, генерируемых пользователями. Социальные сети и платформы отзывов становятся не только каналами коммуникации, но и важными источниками сигналов о киберугрозах. Использование NLP позволяет систематизировать эти данные, выделять ключевые индикаторы и формировать более точную картину угроз, что критически важно для киберразведки и повышения уровня информационной безопасности. Цель статьи заключается в исследовании возможностей применения методов NLP для классификации киберугроз на основе пользовательских отзывов. Основные задачи включают: анализ существующих подходов к обработке текстовых данных, разработку модели классификации угроз, оценку эффективности различных алгоритмов машинного обучения, выявление практических сценариев применения предложенного подхода.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 259 Научная новизна работы состоит в интеграции методов NLP и машинного обучения для анализа краудсорсинговых данных в контексте киберугроз. Практическая значимость заключается в возможности использования предложенного подхода для автоматизированного мониторинга отзывов и сообщений, что позволит организациям своевременно реагировать на потенциальные угрозы и повышать устойчивость цифровой инфраструктуры. 1. Обзор литературы и существующих подходов Методы выявления киберугроз в открытых источниках. Современные исследования в области кибербезопасности активно используют открытые источники информации (OpenSource Intelligence, OSINT) для выявления угроз. Классические подходы включают мониторинг специализированных форумов, блогов, социальных сетей и новостных порталов, где пользователи делятся опытом столкновения с вредоносными программами или мошенническими схемами. В литературе отмечается, что OSINT позволяет обнаруживать ранние признаки атак, включая фишинг, распространение вредоносного ПО и кампании социальной инженерии. При этом ключевым вызовом остается фильтрация шума и выделение релевантных сигналов из огромного массива данных. Роль пользовательских отзывов и социальных данных. Пользовательские отзывы и посты в социальных сетях рассматриваются как важный источник краудсорсинговой информации о киберугрозах. В отличие от формализованных отчетов, они отражают непосредственный опыт и восприятие угроз конечными пользователями. Исследования показывают, что жалобы на подозрительные письма, сбои в работе сервисов или подозрительные ссылки могут служить индикаторами компрометации. Социальные данные также позволяют выявлять тренды – например, всплески обсуждений определенной угрозы или кампании. Таким образом, отзывы и посты становятся не только средством коммуникации, но и инструментом формирования киберразведки, особенно при использовании методов анализа больших данных. Современные достижения в области NLP и машинного обучения. Методы обработки естественного языка (NLP) значительно расширили возможности анализа текстовых данных в кибербезопасности. Современные исследования применяют токенизацию, лемматизацию и извлечение сущностей для структурирования отзывов и сообщений. Большое внимание уделяется моделям Word Embeddings (Word2Vec, GloVe) и трансформерам (BERT, RoBERTa), которые позволяют улавливать контекст и семантические связи в тексте. В области машинного обучения активно используются алгоритмы классификации – от традиционных SVM и Random Forest до глубоких нейронных сетей. Эти подходы демонстрируют высокую точность при выявлении фишинга, вредоносного ПО и других угроз на основе текстовых описаний. Важным направлением является анализ тональности и семантики, позволяющий оценивать уровень риска по эмоциональной окраске сообщений. Совокупность этих достижений формирует основу для разработки систем автоматизированной классификации киберугроз. Литература подчеркивает, что интеграция NLP и ML с краудсорсинговыми данными открывает новые перспективы для раннего обнаружения атак и повышения эффективности киберразведки [1-2]. 2. Методы обработки естественного языка для анализа отзывов Токенизация, лемматизация и стемминг. Первым шагом в обработке текстовых данных является токенизация – процесс разбиения текста на отдельные элементы, такие как слова, предложения или символы. В контексте анализа пользовательских отзывов токенизация позволяет выделить ключевые единицы текста, которые впоследствии будут использоваться для классификации угроз. Например, отзыв «Получил подозрительное
Proceedings of the 11th International Scientific Conference 260 письмо с ссылкой» может быть разделен на токены: получил, подозрительное, письмо, с, ссылкой. Следующим этапом является лемматизация – приведение слов к их нормальной форме. Это особенно важно для языков с богатой морфологией, таких как казахский или русский, где одно слово может иметь десятки форм. Лемматизация позволяет унифицировать данные: слова получил, получает, получить будут сведены к лемме получать. Стемминг, в отличие от лемматизации, выполняет более грубое сокращение слова до основы, часто без учета грамматических правил. Например, подозрительный и подозрительность могут быть сокращены до подозр. Несмотря на меньшую точность, стемминг полезен для быстрого анализа больших массивов данных, где важна скорость обработки. Эти методы обеспечивают основу для дальнейшего анализа, позволяя снизить шум и повысить точность классификации угроз. Анализ тональности и семантики. Анализ тональности (Senment Analysis) играет ключевую роль в выявлении киберугроз через отзывы. Пользователи часто выражают негативные эмоции при столкновении с подозрительными действиями: «сайт выглядит ненадежно», «получил странное письмо», «программа ведет себя подозрительно». Определение тональности текста помогает выделить потенциально опасные сообщения из общего массива отзывов. Семантический анализ идет дальше – он позволяет понять смысл текста, а не только эмоциональную окраску. Например, отзыв «сайт требует ввести данные карты» может быть классифицирован как индикатор фишинга, даже если тональность нейтральная. Современные методы семантического анализа используют синтаксические деревья, тематическое моделирование (Latent Dirichlet Allocaon, LDA) и контекстные модели, чтобы выявлять скрытые связи между словами и фразами. В кибербезопасности анализ тональности и семантики помогает не только фильтровать отзывы, но и оценивать уровень риска. Негативные всплески обсуждений вокруг конкретного сервиса могут сигнализировать о массовой атаке или утечке данных. Извлечение сущностей (Named Enty Recognion, NER). NER – это метод, позволяющий автоматически выделять из текста сущности, такие как имена компаний, продукты, IP-адреса, доменные имена или названия приложений. В контексте анализа отзывов NER особенно полезен для идентификации конкретных объектов, связанных с угрозами. Например, в отзыве «получил письмо от BankXYZ с подозрительной ссылкой» система NER выделит сущность BankXYZ как организацию и ссылка как объект потенциальной угрозы. Это позволяет формировать базы данных индикаторов компрометации (Indicators of Compromise, IoC) на основе краудсорсинговых данных. Современные модели NER используют как статистические методы, так и глубокие нейронные сети. Они способны учитывать контекст, что важно для правильной интерпретации. Например, слово Apple может обозначать как компанию, так и фрукт, и только контекст определяет правильное значение. В киберразведке NER помогает автоматизировать процесс сбора информации, снижая нагрузку на аналитиков и ускоряя выявление угроз. Использование Word Embeddings (Word2Vec, GloVe, BERT). Word Embeddings – это методы представления слов в виде векторов, отражающих их семантические связи. В отличие от традиционного «мешка слов», где каждое слово рассматривается как уникальная единица, Embeddings позволяют учитывать смысловую близость. Word2Vec и GloVe – классические модели, которые обучаются на больших корпусах текстов и формируют векторные представления слов. Например, слова фишинг и мошенничество будут иметь близкие векторы, так как часто встречаются в схожих контекстах.
«Research Reviews» (November 20-21, 2025). Prague, Czech republic 261 Современные модели на основе трансформеров, такие как BERT, пошли дальше: они учитывают контекст каждого слова в предложении. Это особенно важно для анализа отзывов, где значение слова может меняться в зависимости от окружения. Например, слово ссылка может быть нейтральным («ссылка на сайт компании») или подозрительным («ссылка в письме от неизвестного отправителя»). Использование Embeddings позволяет строить более точные модели классификации угроз. Они помогают выявлять скрытые паттерны в текстах, группировать схожие отзывы и повышать точность машинного обучения. Методы обработки естественного языка – от базовой токенизации до контекстных моделей BERT – формируют основу для анализа пользовательских отзывов в кибербезопасности. Они позволяют структурировать данные, выявлять эмоциональные и семантические сигналы, извлекать сущности и строить векторные представления слов. В совокупности эти подходы обеспечивают возможность автоматизированной классификации киберугроз, что делает краудсорсинговые данные ценным источником для киберразведки и раннего обнаружения атак [3-4]. 3. Классификация киберугроз на основе NLP Постановка задачи классификации. Задача классификации киберугроз на основе пользовательских отзывов и сообщений в социальных сетях заключается в автоматическом определении типа угрозы по текстовому описанию. Пользователи часто оставляют жалобы или комментарии, которые содержат признаки фишинга, вредоносного ПО, социальной инженерии или подозрительных действий. Основная цель классификации – преобразовать неструктурированные текстовые данные в структурированную информацию, пригодную для анализа и принятия решений. Формально задача классификации сводится к следующему: дан текстовый документ (отзыв, пост, сообщение), необходимо отнести его к одной из заранее определённых категорий угроз. Для этого применяется предварительная обработка текста (токенизация, лемматизация, извлечение сущностей), затем формируется векторное представление, которое подаётся на вход алгоритму машинного обучения. Алгоритмы машинного обучения: Support Vector Machines (SVM). Метод опорных векторов является одним из наиболее популярных алгоритмов для текстовой классификации. Его преимущество заключается в способности работать с высокоразмерными данными, что характерно для текстов. SVM строит гиперплоскость, разделяющую классы угроз, и показывает высокую точность при небольших объёмах обучающих данных. В контексте киберугроз SVM хорошо справляется с бинарной классификацией, например, разделением отзывов на «подозрительные» и «безопасные». Random Forest. Алгоритм случайного леса представляет собой ансамбль решающих деревьев, каждое из которых обучается на случайной выборке признаков. Random Forest устойчив к переобучению и хорошо работает с шумными данными, что особенно важно при анализе отзывов, где встречаются опечатки, сленг и неоднозначные формулировки. В задаче классификации угроз он позволяет учитывать множество признаков одновременно и выдаёт интерпретируемые результаты, что делает его удобным для практического применения. Нейронные сети. Современные нейронные сети, особенно модели на основе рекуррентных архитектур (RNN, LSTM) и трансформеров (BERT, RoBERTa), демонстрируют лучшие результаты в задачах NLP. Они способны учитывать контекст и семантические связи между словами, что критически важно для точной классификации угроз. Например, нейросеть может различить нейтральное упоминание «ссылка на сайт» и подозрительное «ссылка в письме от неизвестного отправителя». Использование предобученных моделей позволяет значительно повысить точность классификации и сократить время разработки.
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