Жарияланымдар / Публикации

Постоянный URI для этого сообществаhttps://cris.qyzpu.edu.kz/handle/123456789/2

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    Human-AI collaboration in the analysis of literary narratives:a new pedagogical paradigm
    (International University of Sarajevo, 2025-10-22)
    Roza Sabdaliyeva
    ;
    Gibadat Orynkhanova
    ;
    Karlygash Abildayeva
    ;
    Lazzat Adilbekova
    ;
    Kulmanat Auyelkhan
    The digitization of education in Kazakhstan has demonstrated the importance of using AI in the teaching of literature. The purpose of this article is to evaluate the effectiveness of collaboration between humans and AI in improving students' analytical and interpretive skills when studying literary narratives in the context of higher education. The study applied a true experimental design with a randomized controlled trial (RCT) with a pre-test/post-test control group structure. A voluntary purposeful sample (40 participants in total) with elements of randomization was used (all participants were randomly divided into two groups).The results showed that the t-test results indicated the importance of using ChatGPT, as it showed a statistically significant improvement in literary analysis skills among students. There is also a high level of positive perception of learning using AI elements. This indicates the effective introduction of AI technologies as an important factor in increasing student motivation and engagement. The main challenges to the further integration of AI systems into literary education are technical unpreparedness, further integration of AI systems into literary education are technical unpreparedness, lack of experience and skills in interacting with special programs. The advantages of using AI include the formation of individual educational trajectories, increased access to information sources, interactivity and support. The conclusions emphasize the importance of scaling up the study to obtain new empirical data.
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    Assessment of artificial intelligence literacy of preschool administrators in Kazakhstan
    (Modestum Limited, 2026-02-03)
    Sandugash S. Komekova
    ;
    Agima A. Makhanbetova
    ;
    Aigul I. Akhmetova
    ;
    Gulbarshyn Sh. Yernazarova
    ;
    Yücel Gelişli
    This study aims to determine the current state of artificial intelligence (AI) literacy among preschool administrators in Kazakhstan and evaluate its implementation in science, technology, engineering, and mathematics (STEM) contexts. In this study, a correlational survey design within the scope of quantitative methods was employed. The sample consisted of 328 administrators working in different regions, who responded to online forms. Personal information form, AI literacy scale, and AI STEM leadership scale were used as data collection tools in the research. Data were collected during September and October 2025. Analysis was performed using independent samples t-test, ANOVA test, Mann Whitney U test and hierarchical regression. This study reveals that preschool administrators in Kazakhstan possess moderate-to-high awareness of AI technologies, yet significant variations exist in their competency levels. The findings demonstrate that practical usage and critical evaluation skills are the most critical factors for successful STEM integration. The pronounced effect of demographic variables such as gender, education level, and years of service on AI literacy emphasizes that technology adoption in educational leadership is a complex process requiring tailored intervention programs for different administrator groups. The widespread use of general-purpose tools like ChatGPT alongside limited adoption of education-specific technologies indicates that administrators are navigating the AI landscape independently without adequate institutional guidance and strategic frameworks. In this context, targeted professional development programs should be designed for groups with lower AI literacy levels, and systematic training on the introduction and use of education-specific AI tools should be organized. Furthermore, institutional strategic frameworks and guidance mechanisms for AI integration need to be established, and longitudinal research examining the relationship between administrators’ AI literacy and classroom-level STEM outcomes should be conducted.
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    Тип записи:Публикация,
    Information competence and critical thinking in digital environments evidence from university students in Kazakhstan
    (Frontiers Media, 2026-04-24)
    Nurgul Yrymbayeva
    ;
    Moldir Yermekova
    ;
    Oryntay Tezekova
    ;
    Bakytgul B. Issatayeva
    ;
    Akgul Zhubandykova
    The rapid expansion of digital platforms and generative artificial intelligence has reshaped how university students access and evaluate academic information, intensifying concerns about information reliability, critical thinking, and ethical use. This study addresses the gap between students’ widespread access to digital information and their capacity to critically evaluate and responsibly use it in academic contexts, particularly in underrepresented settings such as Kazakhstan. A sequential mixed-methods design (QUAL → quan) was employed. Qualitative data explored students’ information-seeking practices, credibility judgments, responses to conflicting information, perceptions of AI-related risks, and views on institutional support. The sample consisted of 77 undergraduate students enrolled in teacher education-related programs at a university in Kazakhstan. The findings showed a clear hierarchy of search entry points: students most often began with Google Search ( n = 30), followed by university databases/library portals ( n = 16) and AI tools ( n = 15). Clear author credentials ( n = 49) and transparent methods or data ( n = 25) emerged as the strongest trust indicators. When using AI, students reported predominantly supportive uses, especially summarizing checked readings ( n = 58) and generating ideas or outlines ( n = 52), rather than relying on AI as a primary source. These patterns indicate that students’ engagement with generative AI is characterized by conditional trust, pragmatic usefulness, and uneven but developing evaluative awareness. The study contributes context-specific evidence from Kazakhstan to the emerging literature on student engagement with generative AI and suggests that higher education institutions should integrate source evaluation, critical reasoning, and AI literacy more explicitly into curriculum, pedagogy, and library support systems.
    Цитирования (OpenAlex) 2
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    ЖАСАНДЫ ИНТЕЛЛЕКТ ЖАҒДАЙЫНДАҒЫ ЖАСТАРДЫҢ ЕҢБЕККЕ ОРНАЛАСУ СТРАТЕГИЯЛАРЫ: AI-САУАТТЫЛЫҚ, АЛГОРИТМДІК ІРІКТЕУ ЖӘНЕ ЦИФРЛЫҚ МАНСАП ИНФРАҚҰРЫЛЫМЫ
    (2026-07-01)
    Ж.У. Асаубаева
    ;
    А.А. Калиева
    Мақалада жасанды интеллекттің жастардың еңбекке орналасу стратегияларына ықпалы постантропоцентризм, цифрлық онтология, task-based еңбек талдауы және мансаптық бейімделу теориялары негізінде қарастырылады. Зерттеу эмпирикалық сауалнама немесе эксперимент нәтижесін ұсынбайды, оның мақсаты –халықаралық ғылыми әдебиеттер мен ресми талдамалық баяндамалар негізінде жастардың еңбек нарығына кіру логикасында байқалып отырған ӛзгерістерді теориялық тұрғыдан жинақтау. Материалдар 1994–2025 жылдар аралығында жарияланған рецензияланған мақалалардан, монографиялардан, OECD, ILO, World Economic Forum есептерінен және Қазақстан Республикасының ресми еңбек нарығы статистикасынан іріктелді. Әдебиеттердіталдау жасанды интеллект жастарға үш негізгі арна арқылы әсер ететінін аңғартады: біріншіден, бастапқы деңгейдегі жұмыс орындарының тапсырмалық құрылымын ӛзгертеді; екіншіден, түйіндеме, онлайн-профиль, портфолио және тест нәтижелері арқылы қалыптасатын алгоритмдік кӛрінімді күшейтеді; үшіншіден, жастардың стратегиясын дипломға ғана сүйенетін ізденістен үздіксіз оқу, AI-сауаттылық, портфолиолық дәлелдеу және дерек этикасын түсіну бағытына бұрады. Қазақстан контекстінде ресми жұмыссыздық кӛрсеткіштері салыстырмалы түрде тұрақты болғанымен, цифрлық делдалдық, аймақтық теңсіздік және сапалы алғашқы жұмыс орындарына қол жеткізу мәселелері сақталып отыр. Мақалада AI жастарды автоматты түрде ығыстыратын күш немесе бәріне бірдей мүмкіндік ашатын құрал ретінде емес, институционалдық реттеуге тәуелді әлеуметтік-техникалық орта ретінде түсіндіріледі. Қорытындыда университеттерге, жұмыс берушілерге және жастар саясаты институттарына арналған саясаттық ұсыныстар беріледі.
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    Engineering students’ perceptions of mobile-assisted language learning for English terminological competence in Kazakhstan
    (Suleyman Demirel University, 2026-09-30)
    S. Bolatbek
    ;
    Aigerim T. Aliakbarovа
    This study investigates engineering students’ perceptions of the contribution of Mobile-Assisted Language Learning (MALL) tools to English terminological competence in Kazakhstan. The findings are interpreted through the Technology Acceptance Model (TAM), Self-Regulated Learning (SRL) Theory, and Mobile Learning Theory as theoretical frameworks. A quantitative survey design with supplementary open-ended responses was employed. The final analytic sample comprised 132 adult first- and second-year engineering students studying at higher education institutions in Kazakhstan after all responses from participants younger than 18 were excluded. Quantitative data were analysed using descriptive statistics, while qualitative responses were examined through thematic analysis. The findings indicate that students generally perceive MALL tools as beneficial for learning technical English terminology. Nearly half of the respondents reported daily use of mobile learning applications, with ChatGPT, Quizlet, Grammarly, and Google Classroom among the most frequently used tools. Students reported perceived benefits for understanding technical definitions, using engineering terminology accurately, and supporting academic writing. However, several challenges were identified, including the linguistic complexity of AI-generated explanations, limited access to digital resources, and insufficient pedagogical guidance. Students also described planning and monitoring behaviours consistent with aspects of self-regulated learning, whereas evidence of reflective evaluation was less consistent. The study highlights the importance of integrating mobile learning tools into English for Specific Purposes (ESP) curricula and providing students with structured AI literacy training. As the study relies on self-report data and descriptive analysis, its findings concern perceived contribution rather than objectively measured development of terminological competence.