Keyword: «pedagogical design»

The relevance of this article is due to the problem of insufficient speed and efficiency of the education system development in the context of digitalization and its consequences: rapidly growing information flows, which create the problem of student orientation, as well as the rapid development of digital technologies. The aim of this article is to justify the effectiveness of backward design technology in planning the educational process of a university in the context of the digital transformation of society. It is noted that changes caused by digitalization affect not only the goals of the educational process, but also its components, however, the dynamism of changes should not disrupt the systematic nature of the educational process. In the article, the educational process at a university is considered as a dynamic system with changing parameters and the influence of external conditions, and the concept of backward design is proposed to be used for planning and developing educational programs and educational materials, since it allows you to build changes in individual elements depending on changes in the result. The author notes that backward design should be considered as a strategic approach for the development and implementation of innovative teaching methods and models based on digital technologies. The article also examines the basic principles and stages of backward design, including defining learning objectives, developing effective assessment methods, creating content, and selecting appropriate technologies. The advantages and challenges associated with the introduction of the concept of backward design into the educational process are considered. The need to develop the competences of participants in the educational process, including teachers and students, for the successful implementation of this concept is noted. Particular attention is paid to the problem of uncertain formulation of terms in pedagogy during the transition to the digital environment. The author notes that the digital environment requires a clear and structured description of objects, especially when using algorithms and machine learning. In conclusion, the importance of applying the concept of backward design for the effective transformation of the educational process of a university in the context of digitalization is emphasized and several practical recommendations and resources are proposed that can be used to support the process of implementing backward design in educational institutions.

The article addresses a methodological problem related to the use of generative artificial intelligence (GAI) in the system of continuing professional education (CPE), which has become particularly acute under conditions of hybrid learning and in the context of foreign language teaching. The expansion of GAI-based practices in education is accompanied by growing methodological fragmentation, when digital tools are applied without reliance on a coherent logic of pedagogical design. As a result, GAI is used primarily as a means of generating instructional content, leading to the substitution of pedagogical thinking with technical operations and to a loss of coherence in learning activities. The aim of the study is to develop and empirically validate a model of pedagogical task design involving GAI that ensures alignment between educational goals, learning actions, and learning outcomes within CPE. The methodological framework of the study is based on systemic and activity-based approaches, principles of andragogy, and UNESCO framework documents on AI competences for teachers and learners. The empirical basis includes data from pre- and post-course surveys of foreign language teachers, as well as a content analysis of instructional tasks developed by participants during an author-designed professional development program implemented in a hybrid format. The analysis revealed persistent methodological contradictions in the integration of GAI and substantiated the need for a structural model of pedagogical design. As a result, the CROPS model (Concept of the goal, Resource, Operation, Proof, Scenario) is proposed as a reproducible structure for designing learning tasks with the involvement of generative AI. The findings demonstrate that the application of the model reduces methodological fragmentation, restores the pedagogical logic of learning activities, and preserves the teacher’s subject role in an AI-enriched educational environment. The theoretical significance of the study lies in clarifying the role of structural pedagogical design models under conditions of digital transformation in CPE. The practical significance is determined by the applicability of the CROPS model in professional development and professionally oriented training programs, including hybrid and online formats.

The relevance of the research is due to the active introduction of neural network technologies into educational practice and the need for their pedagogically sound use in teaching foreign languages. The proliferation of generative text and visual models expands the possibilities of creating electronic learning materials, but at the same time exacerbates the problem of teachers' methodological readiness for their conscious and purposeful use. In the context of the digital transformation of education, teachers are increasingly acting not only as users of digital tools, but also as designers of educational content, which requires systematic training and methodological support. The aim of the research is to develop and theoretically substantiate a model for training teachers to use neural network technologies in the design of linguistic e-learning materials in English. The research is theoretical in nature and it comprises competence-based, linguodidactic and systematic approaches, as well as modern concepts of the use of artificial intelligence in education and the development of digital and methodological competences of teachers. The research resulted in a structural model of teacher training including target, content, procedural and resultant components. The model focuses on the development of teachers' methodological readiness to use generative textual and visual neural networks in accordance with the goals of teaching English, types of speech activity and the level of students’ linguistic training. The article also presents a hypothetical scenario for the implementation of the model in the system of advanced teachers’ training, demonstrating a reproducible method of professional training without necessary experimental testing. The theoretical significance of the research lies in clarifying approaches to the development of teachers' methodological readiness for the use of neural network technologies in teaching foreign languages and in systematizing the teacher's activities in the context of the use of generative models. The practical significance of the work is determined by the potential of using the proposed model in the system of teacher education and advanced training of English language teachers, as well as in the development of methodological training programs in the context of the digitalization of the educational process.

The relevance of the study is determined by the contradiction between the widespread implementation of digital gamification in universities and the lack of empirically substantiated models that differentiate its effects and minimize the risks of replacing educational goals with entertainment. The aim of the article is to develop and test a universal model of balanced pedagogical design based on the theoretically substantiated 80/20 ratio and differentiating gamification tools by types of pedagogical impact. The methodological basis was a quasi-experiment with a mixed design, conducted in parallel at a technical and a humanitarian university (n = 112). The total sample size allows for comparative analysis but requires caution in making broad generalizations and necessitated the use of non-parametric statistical methods. Data were collected using psychodiagnostic methods (A.V. Karpov's reflexivity questionnaire, the author's original learning motivation scale), expert assessments, content analysis of educational products, and analytics of digital platforms (Quizizz, Mentimeter, AhaSlides, DiaСlass, MTS Link). The main research results include: 1) developed typology of digital gamification tools based on the "depth of engagement" criterion; 2) an empirically substantiated "80/20" ratio model, where 80% of instructional time is allocated to meaningful activities with deep immersion tools (traditional lecture, project-based work, immersive case studies, practical work), and 20% to operational game activation mechanics (quizzes, interactive surveys, "brainstorming sessions"); 3) identified positive dynamics in the development of cognitive engagement and reflexivity of students in both academic samples (technical and humanitarian universities). The theoretical significance lies in integrating the principles of pedagogical design, motivation psychology and cognitive load theory into a single model operationalized through a specific normative ratio. The practical value consists in proving the contextual stability of the model for different institutional and academic environments of higher education, which is confirmed by statistically significant increases in key indicators (p < 0.05) and positive evaluation of the model by students. The obtained results prove the universal character of the model as a meta-methodology for integrating gamification into the educational process.