- Мінтій, І.С. (orcid.org/0000-0003-3586-4311) (2026) Methodological System of Blended Learning for Pre-Service Computer Science Teachers Other thesis, Інститут цифровізації освіти.
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Abstract
Mintii I. S. Methodological System of Blended Learning for Pre-Service Computer Science Teachers.– Qualifying scientific work, manuscript. Extended abstract of the dissertation for the degree of Doctor of Pedagogical Sciences in the specialty 13.00.10– Information and Communication Technologies in Education.– Institute for Digitalisation of Education of the NAES of Ukraine, Kyiv, 2026. This dissertation presents the theoretical substantiation, development, and experimental validation of a methodological system of blended learning for pre-service computer science teachers. The relevance of the study is determined by the need for high-quality training of computer science teachers in the context of the digital transformation of education and the recognition of computer science as a fundamental STEM discipline, European requirements for integrating blended learning into teacher education, and the lack of a holistic, evidence-based methodological system for such training. The choice of the Ukrainian term «kombinovane navchannia» rather than «zmishane navchannia» as the equivalent of «blended learning» was substantiated. Its definition was refined as a planned, pedagogically sound, adaptive combination, interpenetration, and integration of face-to-face and distance, formal and non-formal, real and virtual, and individual and collective learning by means of intelligent technologies. Approaches to organizing blended learning were classified by three criteria – the mode of combining learning forms, the type of ICT tools, and the type of pedagogical technologies. The largest systematic review of computer science teacher training to date was conducted (300 studies, 52 years, 1972–2024, 44 countries, 6 databases). Its results are reproducible, its data comply with the FAIR principles, and data extraction was verified with the aid of intelligent technologies. Four key patterns were identified: 1) the triad «subject-matter training – pedagogical training – teaching practice», aligned with TPACK, with a characteristic imbalance in favor of the subject-matter component; 2) a paradigm shift from lectures to active methods; 3) the growing role of blended learning in the absence of validated methodological systems; and 4) a misalignment between assessment and the predominant teaching methods. These patterns form the evidence base for designing the methodological system. An integrated five-component model of the methodological system of blended learning for pre-service computer science teachers was developed (goal, content, technological, organizational, and diagnostic-outcome components), with a dual – theoretical and empirical – justification of its design principles. Cross-cutting coherence is ensured by the triple theoretical framework TPACK – CoI – ICAP. A set of organizational and pedagogical conditions was substantiated, each grounded in the systematic review data and a corresponding theoretical framework (TPACK, CoI, ICAP, DigCompEdu, and Self-Determination Theory). The methodological system was designed as an implementation of the developed model; this included the development of a TPACK-oriented curriculum map and an architecture for the blended learning environment. Seven interconnected methods for implementing the system were developed (the use of the Moodle learning management system; synchronous and asynchronous interaction; digital competence development; microteaching with peer assessment; project-based learning; the use of immersive AR/VR technologies; and teaching programming). A criterion-based diagnostic toolkit for assessing the level of digital competence was developed (cognitive, operational-activity, motivational-value, and reflective-evaluative criteria; a level-based scale; and diagnostic instruments). A three-stage pedagogical experiment (2015–2024) at Kryvyi Rih State Pedagogical University confirmed the system’s effectiveness. The findings were triangulated using three independent data streams: quantitative diagnostics, learning analytics, and a qualitative analysis of students’ theses. The results have been implemented at ten higher education institutions in Ukraine.
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