Information Technology for Education, Science, and Technics

Digital transformation processes require the integration of various information systems and the involvement of new technologies. This may lead to an increase in the risk of information loss. The paper highlights the author's point of view regarding the solution to this problem by implementing an information risk management information system in the projects of digital business transformation, which is developed based on models and methods of managing these risks. Proposed conceptual model of information risk management for digital transformation projects of business takes into account risks in the system of organization “organization's environment - organization - project”, which makes it possible to manage general information risks, in case of their occurrence in organization's business environment. Presented mathematical model of information risk management in digital transformation projects of business allows at the stage of optimization of business processes to take into account possible information risks and to choose an option for the optimization process in accordance with stakeholders’ requirements at the stage of optimization of business processes. In turn, the method of managing information risks in digital business transformation projects allows to choose business processes with optimal cost indicators, identify information risks and lay down reserves for the implementation of anti-risk measures, and the method of managing general information risks in the organization's system allows to control the stages of information risk minimization and adjust anti-risk measures throughout the entire life cycle of the project. Thus, presented information system makes it possible to increase the effectiveness of information risk management through automation, rapid response and increase in the accuracy of risk analysis.

The authors describe information technology for IT projects creative management, a corresponding structure of the database and a diagram of participants, which is based on genetic algorithm application, and is used to solve the optimization problem to achieve their maximum efficiency. To build a creative team that uses design thinking technologies and the concept of a minimum viable product, it is necessary to evaluate the following groups of indicators as: emotional intelligence of an individual as a team member; internal interactions of a team member; personal qualities of a team member. Criteria for selecting the best team members include experience, skills, cost, compatibility, and empathy. Appropriate methods and tests assess the initial level of applicants. Later, when applicants become a part of the project team, they carry out intra-team interaction, undergo the necessary learning and training for the missing positions to correct the behavior of the team members. Afterward, the testing is repeated after a certain time interval. Proposed information technology for IT projects creative management has powerful scaling capabilities, which allow it to effectively cope with the increase in the number of data and users, without losing productivity and speed. In conclusion, the presented system is a high-tech and innovative solution for creative management of IT project teams with an innovative component, which can find wide application among IT project managers and organizations that seek to improve the efficiency of their projects and achieve competitive advantages on the market.

Under modern business conditions, it is necessary to increase its competitiveness through the digital transformation of enterprise management, particularly by introducing the latest and modern technologies to improve business operations. It helps businesses to become scalable, efficient, and more profitable. To increase the strategic potential for the possibility of simultaneous implementation of a larger number of projects, the providers of housing and communal services need to constantly improve their organizational management model under conditions of uncertainty. The development of a business management information system is proposed, which allows managing business processes of any degree of complexity in all areas of activity, regardless of their labor intensity, as well as the number of personnel and equipment involved. The implementation of a business management information system in the activities of housing and communal services providers optimizes their activities while taking into account the features of their services, which include intangibility, immediacy, changeability, individuality, irreplaceability, continuity and saturation of needs. The implementation of digital transformation in the activities of housing and communal services providers helps to maximize their efficiency and social significance, which is a key element for improving the quality of life of citizens.

The authors of the article focus on digital transformation as a key element of competitiveness, innovation and efficiency of enterprises, which is a fundamental change in the way of doing business and interacting with customers. In the context of the digital transformation of an enterprise, the author singles out the business technology of omnichannel marketing, which occupies a strategically important place in enterprise management, ensuring continuity of interaction with customers, increasing satisfaction and loyalty, and promoting the efficient use of digital resources. The paper proposes a conceptual model of digital transformation of enterprise management processes, which includes six stages and represents an integrated approach to digital transformation. In this model, the authors use omnichannel marketing as a modern business approach to improving the efficiency of digital transformation processes and increasing customer experience. Based on the conceptual model, the authors propose an algorithm for managing omnichannel marketing for stakeholders, covering processes from planning to implementation and analysis of results. As key performance indicators, the authors used MROI, CR, NPS, CAC, and CLV, which are important components for assessing the success of omnichannel initiatives and helping to make management decisions on strategies to optimize customer interaction and increase the company's overall revenue.

The paper highlights and analyzes the previously understudied problem of the number of selected significant single quality indicators impact assessing of an arbitrary object on its model in the form of a comprehensive quality indicator was posed and solved. An appropriate analysis algorithm has been developed to study the parameters of the rolling process used to form a thin steel sheet. The results are consistent with the theory and practice of rolling production. The authors discovered that reducing the number of single quality indicators considered increases the sensitivity of the model to changes in the levels of direct management tools (degree of deformation and carbon equivalent), but at the same time increases the uncertainty, up to an unacceptable level, of such actions. The acquired results can be used to determine a rational list of single quality indicators for a wide range of technical, technological and/or organizational objects.

The article analyses the impact of new global trends, such as Industry 4.0, on the development of IT technologies in project management, thus allowing the authors to identify the necessity of creating digital project management systems in alignment with the concepts, ideas, principles, and provisions shaping of Industry 4.0. The research aims and objectives have been formulated, focusing on the development of digital project management through the utilization of digital twins for project-oriented manufacturing in enterprises within the mechanical engineering, aviation, instrumentation, and metallurgical sectors. An approach based on the creation and utilization of digital twins for project-oriented manufacturing has been developed in the context of digital transformation within enterprises. The authors have defined the structure of a digital environment for hosting the digital twin of project-oriented manufacturing within the proposed approach. Additionally, a method for planning enterprise activities using digital project and manufacturing twins, along with the goals and procedures for employing digital twins in digital project management, has been outlined. The authors highlight that contemporary models and methods for managing the interaction between operational and project processes at enterprises are essential for project-oriented manufacturing with the use of digital twins. Scientific and practical tools based on matrix information technologies have been proposed for managing this interaction. Furthermore, practical results of utilizing digital twins in the activities of an aircraft manufacturing enterprise and a complex geological equipment manufacturing enterprise have been showcased.

An important and relevant issue in project management is risk management. One of the most prevalent project risk management tools is the Risk Matrix method, which categorizes risks into three levels: high, medium, and low. This categorization is based on two criteria: the consequence of the risk on the project and the likelihood of its occurrence. However, this methodology occasionally presents challenges in accurately categorizing specific risks. Thus, a new problem revolving around the development of a method that would allow the project manager to accurately classify risks according to different levels of importance without being limited to only two criteria arises under such conditions. The research proposes and justifies a new method for project risk analysis. The new method is a combination of a modified Risk Matrix method, which provides the ability to assess risks with high accuracy on a broader scale and with a greater number of criteria than the traditional Risk Matrix method, and the Analytic Hierarchy Process (AHP) method, which determines the priorities and ranks of risks to prevent and mitigate those with the highest priorities first. To implement this method, a Project Risk Management Model (PRMM) has been created. In addition, the authors have developed an algorithm that implements this method. Finally, a new web resource has been developed. This web resource enables the automation of the online risk classification process, determines the priority of risks and their ranks, and also provides the user with recommendations for actions to prevent and eliminate the highest priority risks in the form of a risk register. This resource is based on modern programming languages and technologies. The acquired experimental results confirm the feasibility of applying the developed information technology to solve risk management tasks in projects.

This study aims to identify and visualize key concepts related to chatbot training through bibliometric analysis. The analysis of 549 sources from Scopus revealed a significant increase in publications from 2018, with a surge in 2023 likely driven by ChatGPT’s advent. We have identified four clusters of research areas. Those clusters are: (1) natural language processing; (2) application of natural language processing technologies in society; (3) application of machine learning for natural language processing; (4) chatbots in education and services. Central concepts were identified within each cluster. The results of our findings define natural language understanding, language modelling, controlled use of large language models in education, application of virtual assistants and diagnostic systems, and integration of chatbots into adaptive learning systems as the most prominent leading research directions. The same results offer implications for education, AI research, and organizational strategies for integrating conversational agents. Key concepts are possible to integrate into curriculum development and future research in natural language processing.

The paper suggests a method of creating combined reduced order surrogate models for solving multi-parameter inverse problems by the optimization method. The peculiarity of the method is the combination of the known advantages of these models with the introduction of additional apriori information about the objects under study. This information is obtained by modeling following the generated design of a homogeneous computer experiment at the stage preceding the application of the model. The design of experiment includes the main mandatory factors, as well as several additional factors ensure higher accuracy of the solution problem by taking into account the increased amount of information about the object when varying the effects of physical actions on it, as well as interference. The method requires the mandatory creation of surrogate models based on deep fully connected neural networks. This is due to the use of the unique generalizing properties of artificial neural networks, which allows us to implicitly determine the patterns of the object's response to physical disturbances hidden in the data. In addition, the use of deep neural networks increases the accuracy of approximation of response hypersurfaces when building surrogate models. The dimensionality of the search space is reduced by applying nonlinear transformations under the Kernel PCA method, which allows for its significant reduction, providing a considerably simplified structure of the neural network surrogate model and facilitated conditions for the implementation of optimization algorithms for finding extremes. Since inverse problems, due to their incorrect formulation, are characterized by complex topographies of response hypersurfaces when solved by the optimization method, the method provides for the use of algorithms for finding global extremes. The effectiveness of the method is demonstrated in model examples, which showed a sufficiently high accuracy on test problems.

This paper proposes a method for recognizing the age of a person from facial images by using an ensemble of neural network classifiers. The objective of this research is to enhance the effectiveness of human age recognition by employing a neural network classifiers ensemble. The developed method has several advantages: the input image is not required to be square, thereby expanding its applicability; the “convolutional layer – pooling layer” pairs count is calculated empirically, enhancing the neural network classifier accuracy; the count of layers’ planes is calculated automatically, speeding up the determination of the neural network classifier’s structure; the use of an ensemble of neural network classifiers allows for high probability age range classification of individuals. Compared to the scikit-learn package, the proposed method can explore classification using an ensemble of ANN and Hidden Markov Models rather than just an ensemble of neural networks. In addition, this method can explore classification using an ensemble of ANN and Hidden Markov Models rather than only just Hidden Markov Models when compared to the hmmlearn package. Future research prospects include the utilization of the proposed ensemble neural network image recognition method for various intelligent systems aimed at recognizing human characteristics such as gender and emotions.

The purpose of the article is to study knowledge base models for Telegram API chatbots and Android-based mobile applications. The development of knowledge base models for these systems was carried out using the KARKAS shell (Knowledge Acquisition Relevance + Knowledge Accumulation = Shell): a shell for building knowledge base models. The article discusses the main architectural characteristics of the modules of this shell: a model of a hierarchical functional system for layering the knowledge base, a rules parser, an inference engine and the technical implementation of the knowledge base model. The integration of Telegram chatbots with the KARKAS shell is considered, that is, the mechanism for displaying the shell is implemented in the dialog interface of the chatbot. For mobile applications based on Android, a multifactor knowledge base model is used. The construction of the TECHSTACK mobile application for selecting a web technology stack is discussed in detail. The main layers (factors) of the knowledge base for choosing a web technology stack are highlighted.

Road sign recognition is critical for autonomous driving and advanced driver assistance systems, ensuring road safety and efficient traffic flow. This paper presents a study on developing an accurate and robust road sign recognition system using convolutional neural networks (CNNs). The study explores various CNN architectures, training techniques, and data preprocessing methods to optimise performance. A detailed analysis of the Traffic Signs Preprocessed dataset is conducted, and a series of nine CNN models with different filter sizes are trained and evaluated. The results demonstrate the effectiveness of CNNs in extracting relevant features from road sign images and accurately classifying them into standard categories. The study also investigates the impact of filter size on model accuracy, providing valuable insights into the trade-offs between complexity and performance. Additionally, the paper discusses implementing a software application that integrates the trained CNN model for real-time road sign recognition from images and videos. The application's graphical user interface allows users to upload data and visualise the detected and classified road signs, showcasing the practical applicability of the developed system.

The paper suggests a new solution for the problem of analyzing one-dimensional digital signals by implementing a neural network approach. The proposed neural network approach allows improving the quality of approximation by simplifying structural identifying, whereas only the first hidden layer of artificial neural network models is used. The same approach allows reducing the parametric identification computational complexity and ensuring very good scalability through the usage of batch training mode of artificial neural network models. Finally, it is capable of describing nonlinear dependencies through the usage of artificial neural network models, thus achieving great accuracy through the usage of local approximation. The proposed method and models make it possible to extend the application scope of application of methods of approximation of one-dimensional digital signals based on artificial neural networks, which contributes to the efficiency of intelligent systems for special and general purposes.

The study aims to analyze a method for improving the efficiency of image classification systems by combining convolutional neural networks with different architectures into an ensemble of neural networks. The authors have comparatively analyzed the use of neural networks ensembles with different methods of combining them, such as majority vote, averaging, and stacking. The Cifar100 dataset has been chosen for testing. To speed up the development process, the models have not been trained from the very beginning but have been used as feature vector extractors, i.e., one of the types of Transfer Learning, namely, Feature extraction, has been applied. A qualitative and quantitative comparison of the obtained results has been carried out. The final conclusions analyze the possibility of applying the studied ensembles in pattern recognition tasks.

This paper proposes a modification of the scheme for protecting system logs for distributed systems (orchestrated container clusters) from intrusions by moving from the method of simple linked lists (blockchains) to hash trees (Verkle Tree). Using this scheme of work allows for preserving all the advantages of the original system, such as low demand for resources and a lack of a complex infrastructure. Increasing redundancy may provide advantages such as reducing verification time, working with distributed resources, and improving the system's overall security.

The article investigates the issue of ensuring security and confidentiality of information exchange in communication clusters of IIoT systems. The authors of the article note that existing security methods such as encryption, signatures, and authentication may be insufficient for effectively protecting against external intrusions and malicious access to data circulating within such a system. A new approach to creating resilient communication clusters is proposed, based on a combination of information exchange security and redundant hashing to localize external intrusions in industrial IoT. The authors explore various hashing techniques, their impact on system performance and security, and propose an optimal algorithm to achieve the highest level of protection. The article also examines potential security threats in communication clusters and provides practical recommendations for ensuring stability and security of information exchange. The authors highlight the advantages of the proposed approach and offer essential recommendations for its implementation. The research findings can be utilized to enhance security across a wide range of applications where security and reliability are critical aspects, including cloud systems, mobile applications, and other contemporary data exchange technologies.

This paper is based on the previous studies that allowed to define a family of square matrices of order 2 over the field of integers modulo prime. This family forms a finite field with the usual operations of matrix multiplication and addition. This paper aims at developing and applying an approach to determine primitive elements of such a finite field of square matrices. The relevance of this topic is explained by the fact that finding primitive elements is an integral component for applying a finite field in cryptographic transformation tasks, in particular, the Diffie-Hellman key agreement protocol. This study provides an answer to the conditions under which a matrix is a primitive element of a finite field, as well as the method for finding all primitive elements of a matrix field. It has been determined the number of different primitive elements of the field. Examples of searching for primitive elements for the finite field various parameters are provided. An example of using a finite field of square matrices of order 2 in the Diffie-Hellman key agreement protocol is demonstrated.

This paper offers a new microcontroller-based data protection approach employing perfect binary arrays, specifically a special class of binary arrays comprising properties that make them appropriate for application in cryptography. The recommended method employs a synchronized random sequence to produce perfect binary arrays and undertake encryption using two distinctive methods to create the reference classes. The security of the method lies in the challenge associated with locating the reference perfect binary array and the substantial number of current perfect binary arrays. The paper evaluates the security of the method and confirms that it offers an increased level of security against numerous types of attacks, for instance brute-force attacks and attacks founded upon algebraic and computational complexity. Concerning existing cryptographic and data protection methods, the suggested technique has several benefits. These benefits are a greater degree of randomness, together with fast and straightforward encryption and decryption speeds which permit use on low-power systems, for example embedded and microcontrollers which facilitate the connection with different types of devices including IoT and provide a secure path to exchange data. The paper concludes by discussing several potential applications of the proposed approach.

The recent Program for International Student Assessment indicates that many countries need to enhance their performance in the field of science. Efforts to improve science scores continue, and a potential solution to this issue has been identified in a recent study. The study employed an explanatory mixed-method approach to explore the impact of guided exploratory experiments, specifically focusing on the influence of smartphones on students’ conceptual understanding and their ability to analyze science-related data. The quantitative portion of the study utilized an experimental group-only approach with pre-test and post-test phases, while the qualitative section employed hermeneutic phenomenology. A total of 36 students participated in both the pre-test and post-test phases. The quantitative data analysis revealed a significant difference between the pre-test and post-test results, with considerable effect size according to Cohen’s d value. The study noted that many students demonstrated improved performance after the experiment's conclusion. The qualitative findings supported these quantitative results, indicating that students enhanced their conceptual understanding and data processing abilities through hands-on activities, with support from teachers and encouragement to think critically. Participants also gained insights into various theories, such as social constructivism and experiential learning theory. The study suggests that schools should consider allowing smartphones, students should receive guidance on potential errors to minimize confusion, and teachers should be trained to incorporate smartphones into experiments.

The article determines the effectiveness of the artificial intelligence systems implementation in the forming professional competencies process for fashion industry specialists. The algorithm for creating a collection of clothes with the involvement of artificial intelligence includes two iterative loops that take into account the stage of creating a prompt and the stage of visual implementation. The implementation of this algorithm proved its effectiveness and determined the number of iterations in the amount of 4–6. The two-stage process of surveying the participants of the experiment on the implementation of AI demonstrated such motivation criteria for the implementation of artificial intelligence systems as increasing the efficiency of the design process and saving time, creating conditions for creativity and innovation, and optimizing employment conditions. The effectiveness of the implementation of the algorithm is determined by several factors, including improving marketing processes, and production conditions, ensuring sustainable production, and increasing development opportunities. Further development of the algorithm takes into account the possibility of optimization with the involvement of technological, marketing, and material criteria.

The article focuses on the analysis of problems and the creation of proposals for improving the development of young IT-specialists in Ukraine. For this purpose, we performed a sociological study among young IT-specialists, and carried out a comparative analysis of educational programs for their training. The subject of the research is competencies and the need for their improvement as demanded by the labor market in modern conditions. We defined the key requirements for the development of relevant competencies in demand of the Ukrainian market as per the obtained results. The requirements are professional skills (knowledge of the programming language), knowledge of foreign languages, personal skills, time management skills, and working with modern IT technologies. The factors such as a need for developing commitment to the company, patriotism, creating a favorable (non-toxic) atmosphere, conscientious work, and developing a personalized career trajectory for a young IT-specialist turned out to be significant. For the most part, it is the result of an insufficient budget for the development of young IT-specialists, as well as their lack of motivation for development. Therefore, we propose to study the criteria for the selection of learning methods that take into account the characteristics of different generations and build individual development plans based on the principle of continuous education.

Modern tendencies and approaches to education characterized by the wide use of the Internet, personal computers, and smartphones affect the training of aviation specialists. Therefore, the use of information technologies to create a software suitable for development of different skills and acquisition of theoretical knowledge becomes an important factor in training of specialists in the field of UAS operations. In this paper, we highlight and discuss how modern information technologies can be implemented in the educational process of preparing specialists in the field of UAS operations by providing real examples of ICT products. We also analyze the benefits of the developed programs in the terms of blended approaches to education which provide a certain degree of autonomy during training by allowing to choose a convenient time for mastering particular topics and honing the necessary skills.

The rapid advancement of artificial intelligence (AI) technologies has ushered in transformative changes in education, with AI-powered personalized learning systems emerging as a game-changing innovation. However, the successful implementation of these intelligent systems hinges on the preparedness and competence of educators to effectively harness their potential. This bibliometric analysis provides a comprehensive exploration of the research landscape on teacher training and retraining for AI-powered personalized learning. By analyzing publications, authors, institutions, countries, sources, and keyword co-occurrences, this study unveils key insights, trends, and potential gaps. The results highlight the recent surge in research interest, driven by practical AI applications and the COVID-19 pandemic’s impact on education. Influential contributors, institutions, and countries are identified, shedding light on the geographical distribution and collaborative networks shaping this field. The analysis reveals the multidisciplinary nature of the research, with contributions from diverse domains such as educational technology, artificial intelligence, sustainability, and wireless communications. Through keyword co-occurrence analysis, prevalent themes, concepts, and emerging trends are uncovered, including the central focus on teachers, technology, teaching practices, classroom environments, curriculum, and specific AI models like ChatGPT. While the study identifies potential research gaps, such as the need for more pedagogical implications of AI in education, the insights gained can assist in development of effective teacher training and retraining programs, equipping educators to navigate the transformative age of AI-powered personalized learning.

The article analyzes the development of an e-demography system based on the resources of the innovative environment of science and education. The widespread use of intelligent Industry 4.0 technologies has led to the emergence of new vectors of science and education, such as Science 4.0 and Education 4.0. At the same time, there is also a significant transformation and integration of e-science and e-education, which are platforms for the formation of e-resources. The creation of a specialized e-demographic system capable of tracking demographic characteristics and supporting management decisions in such an integrated environment is extremely important from the standpoint of building an effective management system. The article analyzes international experience in this area and approaches to the development of an e-demography system. The authors describe how architectural principles for constructing such a system are developed. The system is based on the integration of existing e-resources with demographic data in the scientific-educational environment. At the same time, it is adopted as a subsystem of the “National e-demography system”. The development of such a system will provide ample opportunities for conducting socio-demographic research, studying demographic behavior, and integrating and developing science and education.

The article studies the modeling of risk management in educational projects of higher education institutions. Today fuzzy cognitive models are widely used for the analysis of complex, causal systems from the standpoint of classification, analysis, modeling, forecasting, decision-making, etc. the authors, however, suggest the application of a cognitive model for risks analysis of an educational project in the field of higher education. The model is suggested to be implemented within the framework of a qualitative analysis of factors influencing each other, the strength of their interaction, and graphical construction of a model with a display of cause-and-effect relationships in a variable weakly structured system for making optimal management decisions. Modeling visualization is a powerful tool, which allows demonstrate the results of expert assessments with subsequent development of a strategy to prevent risks’ occurrence. This approach to modeling allows to understand not only the current state of the system, but also to reproduce various scenarios of its development, which helps to determine the optimal ways for further development. In general, the use of fuzzy cognitive maps of risk management allows to make the process more systematic, effective and oriented towards achieving project success.

The paper analyzes and suggests different ways of modeling students’ project activities through the components of the pedagogical process, such as content, operational, diagnostic and effectiveness. Critical thinking and teamwork skills of students are substantiated as integrated and dynamic personality traits that reflect the formation of soft and hard skills, as well as the ability of self-development. The study is the implementation of a project-based learning for students as an integration of critical thinking and teamwork skills of students through digital technologies and computer mathematics. The matrix reflecting the dependency of a student’s critical thinking skills on the ability to work in a team during educational projects has been developed, tested, and analyzed. The study proves that the integration of critical thinking and teamwork skills of students through digital technologies and computer mathematics affects self-development, improves academic performance, develops soft and hard skills through project activities, the synthesis of which is the professional competencies of a future specialist.

Solving physical problems plays a key role in the educational process, contributing to the achievement of a number of important goals: demonstrates the practical application of theoretical knowledge, develops logical thinking, concretizes acquired knowledge, connects theory with practice, and develops personal qualities of students. The object of the study is the process of learning physics using an online platform for solving (OPS) physical problems (PP). The subject of research is methods and means of using artificial intelligence (AI) for automated verification and evaluation of PP solutions on an online platform. The task of the research: to develop a front-end for independent solution of PP with the possibility of applying AI at different steps of the solution as a hint explaining the course of the solution, and a back-end with the implementation of modern AI models such as ChatGPT, Gemini, Copilot, Claude, for automated checking and assessments PP solutions. The obtained results include substantiating the advantages of using AI, including automation of the verification process, high accuracy of analysis, error detection, objectivity of evaluation, scalability, adaptation to user needs. The pedagogical consequences of the introduction of AI in physics education and the importance of a balanced approach for the development of critical thinking, creativity and consideration of ethical considerations are considered.

This study is dedicated to researching the interconnectedness of Moodle resources and activities and their influence on student learning outcomes. We developed a conceptual model using a quantitative structural equation modelling approach based on the social constructionist pedagogy underlying Moodle’s development and the university’s regulations regarding Moodle’s course structure and assessment. The model is comprised of five elements: Information, Resources, Activities, Communication, and Assessment. The modelling results revealed a strong positive relationship between the Activities construct (interactive learning activities) and the Communication construct, suggesting that increased utilisation of interactive activities within Moodle courses is associated with higher levels of communication and engagement. Additionally, a moderate positive relationship was observed between the Resources and Activities construct, indicating that the availability and variety of resources within a Moodle course are linked to the inclusion of diverse learning activities. Furthermore, a moderate positive relationship was found between the Information construct (course description, syllabus, introduction) and the Assessment construct (student grades), implying that well-designed and informative course materials are associated with better student performance on assessments. Notably, the study did not find evidence of a significant direct relationship between Communication or Activities and the Assessment construct, suggesting that their impact on assessment performance is more complex and influenced by other factors. The research highlights that the mere use of Moodle tools does not guarantee the implementation of adaptive learning for students of pedagogical universities. To truly leverage the potential of adaptive learning, instructors and course designers must employ a deliberate and strategic approach, integrating appropriate pedagogical strategies and using Moodle’s adaptive capabilities in alignment with specific learning objectives and student needs.

The paper highlights the importance of mediated interactive communications in the educational process through web-based systems. The paper analyzes the topical issue of using remote forms of education in the training of future teachers. The authors analyze the current trends in higher pedagogical education and substantiate the importance of the implementation of distance learning design for the effective training of future specialists. The article studies the concept of educational design and its methods that can be applied to the development of distance learning forms. The authors analyze the relationship between the concepts of “educational design” and “distance course architecture”. The specifics of designing distance learning forms in the training of future teachers for the system of vocational (vocational and technical) education have been defined and substantiated. The article substantiates the need to train future vocational teachers in educational design, which will contribute to increasing the quality and efficiency of their pedagogical activities. Finally, the authors analyze different examples of the application of educational design methods in practice during the development of distance courses for the training of qualified workers in the system of vocational (vocational and technical) education by vocational teachers. These courses allow creating a balanced and informative learning environment, stimulate the interest of students, improve their skills and knowledge, and also contribute to their development.

Global trends in the development of both the field of education and its management are aimed at the transition to digital transformation. This indicates that all educational, scientific, management and other processes of a higher education institution (HEI) should be completely transferred to the digital environment. Therefore, without the implementation of digital transformation processes, HEIs cannot effectively organize a high-quality educational process, cannot function normally in competitive conditions. An information technology platform of higher education institutions digital transformation is proposed. It is based on models and methods of concentric information technology of HEI digital transformation and can be used to increase the efficiency of HEI digital transformation processes. The formation of information technology for solving functional problems of higher education institution is based on the determined optimal solution, which should ensure the minimization of costs for the creation of such technology and the maximization of benefits from its use. Therefore, the selection of functional tasks takes into account those tasks that have the highest efficiency in higher education institution educational process and the creation of which requires the least resources. The databases structure, software algorithms, schemes for information processing and management procedures implementation are offered, and examples of concentric information technology of HEI digital transformation practical implementation, which are implemented in Cherkasy State Technological University, are given.

In the post-war period, Ukraine will require measures for economic recovery while simultaneously safeguarding against all forms of potential threats from aggressive neighboring countries. Successfully achieving this task at the current global level of technological advancement is possible exclusively through high-tech principles by integrating digital transformations into all spheres of Ukrainian life. Addressing such a complex issue amidst the financial constraints of a war-torn economy necessitates ample preparation of a sufficient number of competitive and professionally motivated IT experts within the country’s universities, who are committed to effective work in the homeland’s IT army. A comprehensive analysis has been conducted on the key competencies taught to IT graduates by the country’s leading universities. The experience of leading such global universities in the relevant field has been examined. A rationale for the approach to forming a model of key competencies within the educational program is provided, exemplified by the Computer Science curriculum.

The burgeoning prominence and practical integration of Artificial Intelligence (AI) within contemporary society underscore the imperative to discern its judicious and secure utilization within academic spheres. In this context, the imperative arises to systematically evaluate the use of AI within university operations, navigating its inherent benefits and potential hazards through systematic analysis of its ramifications. The study aims to substantiate the concept of assessment (self-assessment) methodology of the university’s readiness to use AI based on a comprehensive model of the use of AI services and tools in higher education. The focal point of analysis is the operational framework of AI within university activities, while the principal focus pertains to conceptualizing the methodological approach for assessment (self-assessment) of universities’ readiness to employ AI ethically, securely, and effectively. Methodologically, this research draws upon analytical, synthetic, and content analysis methodologies, leveraging UNESCO, OECD, EU directives, and relevant scholarly literature on AI. Theoretical frameworks and methodological tools rooted in sociological inquiry provide the groundwork for the development of assessment methodologies. Consequently, a framework-based approach is posited for assessing (self-assessing) universities’ readiness for AI integration, categorized into distinct thematic domains. The implementation of the methodology, developed based on this concept, promises an objective appraisal of extant AI adoption within university settings.