News

       The Department of Informatics of M. Auezov South Kazakhstan University announces that the extended departmental research seminar (pre-defense) of the doctoral dissertation submitted by Elmira Tlesovna Abdrashova for the degree of Doctor of Philosophy (PhD) in the Educational Program 8D01503 – Informatics will be held. Dissertation title: «Formation of methodological competence of future computer science teachers based on digital learning models».

       Language of the pre-defense: Kazakh.

       The dissertation is submitted in the form of a dissertation manuscript.

Domestic Scientific Consultant:
Zhanar S. Kemelbekova, Candidate of Technical Sciences, Associate Professor, M. Auezov South Kazakhstan University.

Foreign Scientific Consultant:
Anatoliy A. Veryaev, Doctor of Pedagogical Sciences, Professor, Altai State Pedagogical University.

1. Zhansaya N. Ashirbayeva – Candidate of Pedagogical Sciences, Associate Professor, Department of Informatics.
2. Almira B. Ibashova – Candidate of Pedagogical Sciences, Associate Professor, Özbekali Zhanibekov South Kazakhstan Pedagogical University.

The extended departmental research seminar (pre-defense) will take place on 30 June 2026 at 11:00 a.m. in a hybrid format (on-site and online) at Room 312, M. Auezov South Kazakhstan University, A. Baitursynov Street, Shymkent 160012, Republic of Kazakhstan.

 

Research relevance. At the present stage, the development of the education system is characterized by the rapid digitalization of education, the integration of artificial intelligence technologies into the educational process, and the continuous updating of requirements for teachers' professional training. In the global educational landscape, a teacher is regarded not only as a specialist possessing subject knowledge, but also as a professional capable of designing learning in a digital environment, pedagogically integrating innovative technologies, analyzing students' learning activities using educational data, and making evidence-based pedagogical decisions. In this context, the formation of methodological competence among future informatics teachers has become a highly relevant scientific and practical issue.

Research topic: Formation of Methodological Competence of Future Informatics Teachers Based on Digital Learning Models.

Research object: The process of preparing future informatics teachers in higher education institutions.

Research subject: The content, structure, methods, and tools for developing the methodological competence of future informatics teachers.

Research aim: To theoretically substantiate the methodology for developing the methodological competence of future informatics teachers based on digital learning models (AI-TPACK, SAMR) and learning analytics, to develop its structural-content model, and to experimentally verify its effectiveness.

Research hypothesis: If the process of developing the methodological competence of future informatics teachers is implemented through a structural-content model and a specially designed methodology based on the AI-TPACK and SAMR digital learning models together with learning analytics, then the methodological competence of future teachers will be developed more effectively. This is because such an approach ensures the integrated development of subject-specific, pedagogical, technological, and digital methodological competencies, enables scientifically grounded instructional design, the development of digital learning content, teaching methods, systems of digital learning tasks, assessment instruments, and data-driven analysis of learning outcomes.

1. To identify the theoretical and methodological foundations for the development of the methodological competence of future informatics teachers.
2. To substantiate the pedagogical opportunities and methodological potential of digital learning models in developing the methodological competence of future informatics teachers.
3. To develop a structural-content model for the development of the methodological competence of future informatics teachers based on the AI-TPACK and SAMR models and learning analytics.
4. To develop a methodology and supporting tools for implementing the proposed structural-content model.
5. To verify the effectiveness of the proposed methodology through experimental work and to conduct quantitative and qualitative analyses of the obtained results.
6. To develop scientific and methodological recommendations based on the research findings.

The methodological and theoretical foundations of this research are based on the works of national and international scholars in the fields of professional training of future informatics teachers, methodological competence, digital pedagogy, digital learning models, and learning analytics.

Within the framework of the study, the development of the methodological competence of future informatics teachers was considered as an integral component of professional teacher education in higher education institutions. Its content, structure, development mechanisms, and expected outcomes were examined within the context of digital education. Accordingly, the methodological framework of the research is grounded in the systems approach, competency-based approach, activity-based approach, learner-centered approach, technological approach, and data-driven approach.

The systems approach enables the development of the methodological competence of future informatics teachers to be viewed as an integrated pedagogical system consisting of interconnected goals, content, methods, tools, organizational forms, learning outcomes, and feedback mechanisms. This approach provided the basis for interpreting the research object not as a collection of isolated elements but as a comprehensive system integrating the content, technological, and assessment components of professional teacher education. Based on the systems approach, a structural-content model for developing methodological competence was designed, and the relationships among its goal-oriented, content, technological, and outcome components were established. The theoretical foundations of the systems approach are reflected in studies that conceptualize pedagogical systems as holistic structures, including the works of A.A. Veryaev.

The competency-based approach, as one of the principal methodological foundations of this study, makes it possible to interpret the outcomes of future teacher education not merely as a combination of knowledge, skills, and abilities, but as an integrated professional quality that enables effective performance in solving professional tasks. From this perspective, methodological competence is regarded as the ability of future informatics teachers to integrate subject knowledge, pedagogical knowledge, digital technologies, assessment methods, and reflective practice in real professional contexts. The theoretical foundations of the competency-based approach are based on the works of A.V. Khutorskoy, I.A. Zimnyaya, V.A. Slastenin, and other scholars. Their findings provided the theoretical basis for substantiating the structure of methodological competence, including its cognitive, operational, motivational, and reflective components.

The activity-based approach assumes that methodological competence is not acquired in a ready-made form but is developed through purposeful educational and methodological activities. Accordingly, lesson planning, the design of digital learning tasks, the organization of students' learning activities, the assessment of learning outcomes, the purposeful selection of digital tools, and reflective practice were considered the primary means of developing methodological competence. In this study, the activity-based approach was implemented by engaging future teachers in active cognitive and practical activities, instructional design, educational modeling, and the analysis of pedagogical situations within a digital learning environment.

The learner-centered approach enables the professional development of future teachers to be considered in relation to their individual characteristics, motivation, value orientations, experience in digital environments, and reflective abilities. This approach served as the foundation for viewing future informatics teachers not merely as recipients of knowledge but as active participants who consciously shape their professional development, make pedagogically sound methodological decisions, and establish their own professional identity within digital learning environments. In the present study, the learner-centered approach was reflected in the development of individualized learning pathways, the creation of personal digital educational products, the implementation of reflective learning tasks, and professional self-assessment.

The technological approach makes it possible to organize the process of developing the methodological competence of future informatics teachers as a systematically designed pedagogical technology with clearly defined stages, content, teaching methods, instructional tools, expected learning outcomes, and assessment criteria. This approach formed the basis for implementing the proposed structural-content model as a coherent pedagogical technology. Consequently, digital learning models, artificial intelligence tools, learning activities, assessment instruments, feedback mechanisms, and supporting resources were integrated into a unified methodological system.

In accordance with the research aim and objectives, a comprehensive set of theoretical, empirical, and mathematical-statistical research methods was employed.

As theoretical research methods, analysis, comparison, systematization, generalization, modeling, structuring, and interpretation were applied to philosophical, psychological-pedagogical, methodological, and scientific literature, regulatory and legal documents, as well as national and international studies on the professional preparation of future teachers, methodological competence, digital pedagogy, digital learning models, the use of artificial intelligence tools in education, and learning analytics. These methods made it possible to identify the essence, structure, and theoretical-methodological foundations of developing the methodological competence of future informatics teachers, to substantiate the pedagogical opportunities and methodological potential of digital learning models, and to develop the structural-content model of the study. The theoretical analysis and pedagogical research were designed in accordance with the principles of scientific inquiry and a mixed-methods research approach.

The empirical methods employed in the study included pedagogical observation, surveys, interviews, testing, diagnostic tasks, analysis of students' academic, project-based, and methodological activities, expert evaluation, examination of learning outcomes within the digital educational environment, as well as practical and experimental research methods. To determine the level of methodological competence development among future informatics teachers, verify the effectiveness of the proposed methodology, and evaluate its outcomes, a quasi-experimental pedagogical study was conducted. Within the experiment, control and experimental groups were established, and comparative analyses of their baseline and final results were performed. In the experimental group, the development of methodological competence was implemented using a methodology based on the AI-TPACK framework, the SAMR model, and learning analytics, whereas the control group continued to receive instruction through traditional teaching methods.

Mathematical and statistical methods were employed to process, compare, and generalize the quantitative data obtained during the research and to verify the effectiveness of the proposed methodology. Statistical data analysis included descriptive statistics (mean, standard deviation, and percentage change), the independent-samples Student's t-test and the χ² (chi-square) test to determine the initial equivalence of the control and experimental groups, analysis of covariance (ANCOVA) to compare post-experimental results while controlling for baseline differences, and Hedges' g to determine the magnitude of the intervention effect. Cronbach's alpha coefficient was used to assess the internal consistency and reliability of the measurement instruments. The consistency of expert evaluations was determined using inter-rater agreement indices and comparative analysis methods.

The scientific novelty of this research lies in its comprehensive investigation of the development of the methodological competence of future informatics teachers based on digital learning models, artificial intelligence tools, and learning analytics. The main research findings are as follows:

1. The theoretical and methodological foundations for developing the methodological competence of future informatics teachers have been refined. Its content, structure, and component composition have been identified within the context of digital education.
2. The pedagogical opportunities and methodological potential of digital learning models in developing the methodological competence of future informatics teachers have been substantiated, and their role in the process of professional teacher education has been determined.
3. A structural-content model for developing the methodological competence of future informatics teachers has been developed based on the AI-TPACK framework, the SAMR model, and learning analytics. The proposed model is built upon the interrelationship of goal-oriented, content, technological, and assessment-outcome components and is aimed at the integrated development of the subject-specific, pedagogical, technological, and reflective competencies of future teachers.
4. A methodology and supporting tools for implementing the proposed structural-content model have been developed. The proposed educational environment enables the organization of methodological training for future informatics teachers, facilitates the use of digital resources, supports the pedagogically meaningful application of artificial intelligence tools, and provides data-driven feedback through learning analytics.
5. The effectiveness of the proposed methodology has been experimentally validated through practical and pedagogical research, and scientific and methodological recommendations for enhancing the methodological competence of future informatics teachers have been developed.

The findings of this study contribute to the theory of developing the methodological competence of future informatics teachers through the integration of digital learning models, artificial intelligence tools, and learning analytics. The study refines the content and structure of methodological competence within the context of digital education and substantiates the interrelationships among its subject-specific, pedagogical, technological, and reflective components. Furthermore, it systematizes the pedagogical foundations for integrating the AI-TPACK framework, the SAMR model, and learning analytics into the professional preparation of future informatics teachers.

The proposed structural-content model provides a theoretical framework for understanding the process of developing the methodological competence of future informatics teachers as a holistic pedagogical system comprising objectives, content, teaching methods, instructional tools, digital learning environments, and assessment mechanisms.

The research findings contribute to the modernization of the professional preparation of future informatics teachers within the framework of higher pedagogical education. They further clarify the pedagogical potential of digital learning models, establish the theoretical foundations for the methodological application of artificial intelligence tools in education, and conceptualize learning analytics as an essential component of professional teacher education.

The practical significance of this research lies in the applicability of the proposed structural-content model and its implementation methodology within higher teacher education. The research findings can be applied in the preparation of future informatics teachers at pedagogical universities, in teaching methodology-related courses, organizing elective courses and practical classes, conducting teaching practicum, and implementing professional development programs for teachers.

The supporting tools, the system of methodological tasks, instructional materials for working with digital resources, learning activities designed to promote the pedagogically meaningful use of artificial intelligence tools, diagnostic instruments, and scientific-methodological recommendations developed within the framework of this research contribute to enhancing the methodological competence of future informatics teachers. Furthermore, the research findings may be of practical value to university instructors, teacher educators, curriculum developers, educational methodologists, and specialists involved in the professional development of informatics teachers.

The validity and reliability of the research findings are ensured by the consistency of the methodological and theoretical foundations of the study, the application of a comprehensive set of theoretical, empirical, and mathematical-statistical methods appropriate to the research objectives, and the alignment of the design and implementation of the practical and experimental work with the overall research purpose.

The credibility of the findings is further supported by the scientific substantiation of the structural-content model for developing the methodological competence of future informatics teachers, the implementation and evaluation of the proposed methodology within an authentic higher education environment, the comparative analysis of the experimental and control groups, and the quantitative and qualitative analysis of the obtained results.

The validity of the research is also ensured through the systematic collection, analysis, and interpretation of data obtained during the practical and experimental stages of the study; the consistency between the criteria and indicators used to assess the levels of methodological competence and the research objectives; the reliability of the diagnostic instruments; and the scientific justification of the applied assessment methods. The experimental findings were complemented by learning analytics data, students' academic performance, the quality of methodological tasks, indicators of learners' engagement in the digital learning environment, reflective materials, and expert evaluations. The quantitative data were processed using appropriate mathematical and statistical methods, providing objective evidence of the effectiveness of the proposed methodology.

The consistency between the theoretical conclusions and the experimental findings, the successful validation of the proposed methodology in educational practice, and the implementation of the research outcomes in the educational process confirm both the scientific validity and the practical value of the dissertation.

1. The methodological competence of future informatics teachers is conceptualized as an integrated professional quality developed through the interaction of subject-specific, pedagogical, technological, and reflective components within the context of digital education.
2. Consideration of the pedagogical opportunities and methodological potential of digital learning models constitutes a key prerequisite for the development of the methodological competence of future informatics teachers, as these models enable the integration of digital technologies with instructional content, teaching methods, and assessment mechanisms.
3. The structural-content model developed on the basis of the AI-TPACK framework, the SAMR model, and learning analytics provides an effective theoretical and practical foundation for the development of the methodological competence of future informatics teachers.
4. A methodology and a supporting educational tool have been developed for implementing the proposed structural-content model. The supporting tool enables the organization of methodological training for future informatics teachers, facilitates the use of digital resources, supports the pedagogically meaningful application of artificial intelligence tools, and provides feedback based on learning analytics.
5. The effectiveness of the proposed methodology has been confirmed through practical implementation and experimental research and can be applied in the professional preparation of future informatics teachers within the system of higher pedagogical education.

The research findings have been disseminated through publications in scientific journals recommended by the Committee for Quality Assurance in Science and Higher Education of the Ministry of Science and Higher Education of the Republic of Kazakhstan, as well as in international scientific publications.

The principal findings and conclusions of the dissertation have been published in 15 scientific papers in national and international scholarly outlets. Of these, 2 papers were published in Scopus-indexed journals, 3 papers were published in journals recommended by the Committee for Quality Assurance in Science and Higher Education of the Ministry of Science and Higher Education of the Republic of Kazakhstan, 4 papers were published in other scientific journals, and 6 papers were presented in the proceedings of international scientific and practical conferences.

- Integration of SAMR, TPACK, and Artificial Intelligence in Computer Science Teacher Education: Impact on Academic Achievement and Digital Competencies - International Journal of Information and Education Technology, Vol.16, №5, 2026 – pp. 1406-1417 https://doi.org/10.18178/ijiet. 2026.16.5.2607; 73 процентиль

- The Impact of the SAMR Model with IT-Enhanced Tools on Student Performance - International Journal of Information and Education Technology, Vol.15, №4, 2025 - pp. 760-766. doi: https://doi.org/10.18178/ijiet. 2025.15.4.2281; 61 процентиль

- Scientific and Methodological Foundations for Training Pedagogical Specialists in the Use of Artificial Intelligence Tools - Вестник КазНПУ. Серия «Педагогика и психология», том 66, №1, Алматы, 2026 г., С. 159-168. https://doi.org/10.51889/2960-1649.2026.66.1.014

- Искусственный интеллект: влияние на профессионально-методическую компетентность будущих учителей информатики - Вестник Национальной академии наук Республики Казахстан, серия Экономика и Педагогика, Алматы, №3(415), 2025г. - С. 33-47. https://doi.org/10.32014/2025. 2518 -1467.950

- Использование потенциала цифровых технологий в формировании методической компетентности учителей информатики - Вестник Национальной академии наук Республики Казахстан, Алматы, №6(412), 2024г. - С. 26-43. https://doi.org/10.32014/2024.2518-1467.852

- Methodological competence of a future teacher of information science -материалы XVII МНПК «Лучшие научные достижения-2022». Том 1. София: Бял ГРАД-БГ ОДД, 2022 г. С. 39-43.

- Основы профессионального развития методической компетентности учителя информатики - международная научно - практическая конференция, посвященная 125 - летию М. О. Ауэзова «Ауэзовские чтения-20: наследие Мухтара Ауэзова-Сокровище нации». Южно-Казахстанский университет им. М. Ауэзова, Шымкент: - том 3, апрель 2022г., С. 25-29

- Сущность профессиональной компетентности в процессе непрерывного образования - сборник трудов Международной научно - практической конференции «Современные науки и технологии образования», Университет Шымкент, Шымкент, том 2, 2024г., С. 368-372.

 - Computer science teacher's competencies and ways to apply modern learning technologies - материалы XXII МНПК «Перспективные разработки - наука и техника-2025». Том 1. Прага, 2025 г. С. 145-149.

- Влияние цифровой компетентности на качество преподавания в информатике - сборник тезисов «Первого конгресса математиков Казахстана». Алматы: Институт математики и математического моделирования, 2026г. С. 777-779

- Integrating Methodological Skills in Computer Science Teacher Training to Improve Student Outcomes - труды международной научно-практической конференции «Развитие современной науки: проблемы практики, прогнозы», г. Шымкент: Региональный инновационный университет, 14-15 апреля 2026г., С. 15-25

- Значение модели TPACK в отборе цифровых образовательных ресурсов - сборник материалов МНПК, посвященный 75-летию со дня рождения доктора педагогических наук, профессора Муханбетжановой Алии Медешовны «Образование в эпоху цифровизации и искусственного интеллекта: ценности, этика и практика». Уральск: Западно-Казахстанский инновационно-технологический университет (ЗКИТУ) и филиал автономного кластерного фонда «Астана Хаб» по г. Уральск (Batys hub), 2026г. С. 472-478.

- Педагогическая эффективность использования цифровых моделей в образовательной среде - Международная научная конференция на тему «Научные открытия в образовании: современные исследования и возможности будущего», Международный казахско-турецкий университет им. Ходжи Ахмеда Ясави, г. Туркестан, 23-24 апреля 2026г., С. 448-451.

4) В других научных публикациях :

- Возникновение и развитие модели SAMR и ее влияние на формирование методической компетентности учителей информатики -МЕЖДУНАРОДНЫЙ НАУЧНЫЙ ЖУРНАЛ «IN The WORLD OF SCIENCE AND EDUCATION» international scientific-practical journal Педагогические науки, Алматы, 15 февраля - 2025г., 31-37 стр.

- Организация самостоятельной работы, направленной на развитие методической компетентности учителя информатики - международный конкурс «Лучший молодой ученый года» NATIONAL ACADEMY of SCIENTIFIC AND INNOVATIVE RESEARCH (NAcSIR), нагрудный знак «Лучший молодой ученый года», благодарственное письмо, статуэтка, Астана, апрель-2025г.

• Python Programming Language. Shymkent: Nurly Beine Publishing House, 2025. – 180 p.
• Theoretical Issues of Informatics. Shymkent: Alem Publishing House, 2025. – 224 p.

• Digital Methodologist Information and Educational Environment. Certificate of Registration in the State Register of Copyright-Protected Objects, No. 58016, dated 15 May 2025.
• Electronic Textbook "Theoretical Issues of Informatics". Certificate of Registration in the State Register of Copyright-Protected Objects, No. 70706, dated 22 April 2026.

The dissertation was completed, discussed, and recommended for defense by the Department of Informatics of M. Auezov South Kazakhstan Research University.

The dissertation consists of an introduction, two chapters, a conclusion, a list of references, and appendices.

The Introduction substantiates the relevance of the research topic and presents the research object, subject, aim, objectives, hypothesis, leading idea, methodological and theoretical foundations, research sources and methods, stages of the study, scientific novelty, theoretical and practical significance, the main provisions submitted for defense, validation and reliability of the research findings, as well as the dissemination and implementation of the research results.

Chapter One, entitled "Theoretical and Methodological Foundations for Developing the Methodological Competence of Future Informatics Teachers", examines the essence, structure, and characteristics of the methodological competence of future informatics teachers; analyzes the current state of research on the development of methodological competence within the context of teaching informatics disciplines; investigates the approaches, methods, instructional tools, and organizational forms for developing methodological competence; and substantiates the structural-content model for developing the methodological competence of future informatics teachers.

Chapter Two, entitled "Implementation and Experimental Validation of the Development of the Methodological Competence of Future Informatics Teachers Based on Digital Learning Models", presents the content and structure of the proposed methodology based on the AI-TPACK framework, the SAMR model, and learning analytics; describes the implementation of the methodology in the experimental study; analyzes the experimental results using learning analytics; and evaluates the effectiveness of the proposed methodology.

The Conclusion summarizes the research findings and presents the main conclusions together with scientific and methodological recommendations. The Appendices contain the materials of the experimental study, diagnostic instruments, questionnaires, sample learning tasks, methodological resources, and documents confirming the implementation of the research results.