In modern pedagogy of higher education, there is an active introduction of artificial intelligence into the educational process. Individual instructors, faculties, and entire universities are developing various approaches to its application, ranging from isolated exercises to full courses based on neural networks. Nevertheless, many questions remain controversial and unresolved. With the widespread use of neural networks and mobile applications, challenges arise in leveraging them to achieve pedagogical outcomes, particularly due to insufficient research on their impact on the quality of language training. During this phase of active adoption of new tools, it is essential to synthesize global experiences in their application.

The purpose of this study is to analyze and classify current trends in the use of artificial intelligence in foreign language teaching in higher education. Examining both Russian and international experiences in combining technology with traditional teaching methods provides a comprehensive view of modern approaches in the field of teaching foreign languages. It is necessary to identify the advantages, risks, and promising directions of artificial intelligence implementation. Systematizing the use of new technologies and integrating them into the structured framework of higher education will help unlock their potentials while considering theoretical and linguodidactics aspects. When introducing new tools into teaching, it is necessary to consider prospective and existing challenges to prevent undesirable consequences in the advancement of new directions in the field of teaching.

The research materials include publications on studies and practical applications of artificial intelligence in higher education pedagogy of foreign languages teaching in non-linguistic universities. A key feature of these materials is their international, multinational, and intercultural context. The selected articles were chosen based on thematic relevance, regardless of where the research was conducted. The classification of accumulated experience from the perspective of neural network application approaches is of particular interest.

The research methods involve the selection, study, and systematic analysis of scientific publications and empirical studies on the specified topic, identified in the research materials. A comparative assessment of neural network tools and the generalization of pedagogical experiences in integrating them into curricula help to systematize accumulated knowledge and formulate development strategies.

The study results in a classification of current trends in the linguodidactics of foreign language education, as well as a systematization of methods for optimizing learning through automated assessment, personalized tasks, and the development of communicative skills using neural networks and chatbots. In addition to classifying effective artificial intelligence applications, the study outlines negative aspects and influences of neural networks that require data accuracy control, plagiarism prevention, and the preservation of the lecturer’s role as a key participant in the educational process.

Conclusion. Thus, the use of neural networks is a widely explored field in modern higher education with a diverse system of new approaches and methods. Hybrid learning models that combine traditional methods with existing educational technologies are recognized as promising directions. Special attention is given to the integration of artificial intelligence with virtual reality capabilities, despite the current labor-intensive and cumbersome nature of this technology.

The purpose of the study is to analyze the practices of using virtual reality (VR) technologies to find new models for organizing the educational process. Modern VR technologies open up new opportunities for transforming education by providing interactive and immersive learning. This paper examines the practical aspects of integrating VR into the educational process, implemented in practice. The article considers the possibility of using virtual reality technologies in the higher education system and substantiates the possibility of expanding the educational space through the introduction of new tools that significantly change the role of teachers in the context of digital transformation.

Materials and methods. Two main methods are used in the paper: bibliometric and theoretical analysis. A selection of articles was carried out from the Dimensions.ai database to analyze the publication activity by keywords. In the study of the effectiveness of VR-learning, an analysis of existing pedagogical methods used in higher education was carried out, highlighting the key factors influencing the assimilation of the material. Based on the synthesis of research in the field of cognitive psychology and digital didactics, a model of adaptive VR learning has been developed taking into account the individual cognitive capabilities of students.

The results. The authors draw attention not only to the advantages of VR technologies in increasing students’ motivation and engagement, but also to possible problems that affect the psychophysiological state of students. The study showed that scaling virtual reality technologies in education faces three types of difficulties: technological, psychological and didactic. Technological difficulties include limitations related to hardware and software, such as the high cost of hardware, insufficient performance for mass adoption, and the lack of unified platforms for creating and reproducing educational content. Psychological aspects cover the problems of user adaptation, including cognitive overload, the emergence of cyber-diseases and general resistance to new technologies due to lack of confidence in their effectiveness. Didactic difficulties are manifested in the absence of methodically sound approaches to integrating VR into the educational process, which is reflected in the inconsistency of content with pedagogical tasks, insufficient elaboration of interactive mechanics, and a lack of standardized methods for evaluating the effectiveness of VR learning. As key measures to overcome these barriers, the study highlights the need to develop standards for educational VR content, implying the unification of formats, quality assessment methods and principles of interactive communication, as well as improving the level of technical literacy of teachers.

Conclusion. As a result of the analysis of successful cases implemented at various universities, the author systematized models of the organization of the educational process using VR technologies. These issues can become the basis for the development of VR learning standards, the creation of adaptive educational programs and recommendations for teachers and EdTech developers.

The purpose of the study. The problem of initiating students’ cognitive activity is currently acquiring ever-increasing importance. Understanding the practical impossibility of transmitting in the learning process the volumes of information necessary to form a wide range of required competencies forces us to look for new didactic approaches to achieving the goal, including a focus on the development of cognitive activity. The most important tool for this can be artificial intelligence systems, the scope of application of which has been rapidly expanding in the last two or three years. However, in the educational process, the use of artificial intelligence is not perceived positively by everyone. There are well-known discussions about the unethical nature of performing educational tasks using ChatGPT or similar systems. The search for acceptable and effective solutions was set by the authors of this paper as the main goal of the study. Another goal was to attempt to develop and introduce into teaching practice at the general education level a new non-traditional method based on the possibility of initiating students’ cognitive activity through artificial intelligence systems. The third objective was to justify the choice of physics as an academic discipline among some others to illustrate the effectiveness of the proposed teaching method in a general education physics course.

Materials and methods. The material (object) of the study was the process of teaching physics at the general education level in terms of problems that usually cause difficulties for students. Such difficulties primarily include issues related to solving physics tasks, evaluating the results obtained, understanding the need to rely in each specific case on certain physical theories and patterns, as well as understanding the reasonableness of using formulas expressing physical laws. The main general empirical method of research was the observation of various stages of the educational process. The general methods of theoretical research included an analysis of scientific literature on methods for developing students’ cognitive activity, as well as an assessment of the educational opportunities of the range of artificial intelligence systems available to students, with the development of recommendations for their practical application. A special method, characteristic of pedagogical sciences, was a pedagogical modeling of work methods at different stages of the educational process.

Results. For the first time in the system of pedagogical knowledge, a new non-traditional method of initiating students’ cognitive activity in a general education physics course based on verification of the results of search queries of artificial intelligence systems has been proposed, formulated, developed, described and tested. A methodology has been developed for working with students from the stage of setting a task by the teacher, the student’s awareness of its essential and insignificant features through the repeated formulation of search queries to the artificial intelligence system with subsequent analysis of the answers received, to the most important thing - verification of the results of work with the artificial intelligence system and substantiated conclusion about the solution to the problem. The stages of the research and the proposed methodology are illustrated in detail with examples of solving problems from the general education physics course. The results of the experimental work already at this stage demonstrated the effectiveness of initiating the cognitive activity of students in the general education course of physics through the verification of the results of search queries of artificial intelligence systems.

Conclusion. The use of computer technology and its software in general education is constantly changing the direction of its development vector. From enthusiastic expectations to a legislative ban on the use of “…mobile radiotelephone communications during educational classes in the development of primary, basic and secondary general education programs…” [1]. We hope that this applies to computing equipment only in terms of its use in the “mobile radiotelephone communication” mode. The ban does not apply to all other cases, including work with artificial intelligence systems. This is where we should expect the greatest success.

Purpose. Digital transformation of education determines the need to rethink the goals and meanings of the educational process and, at present, is associated with the problems of our time, the expansion of the role of artificial intelligence.

The paper is devoted to the presentation of the taxonomy of educational goals from the standpoint of a mental model of thinking, which allows designing new educational results in the digital transformation of education.

Methodology and methods. Unlike Bloom’s taxonomy, the main goal of modern education is the formation and development of computational thinking. The basis for constructing the taxonomy of educational goals is a mental approach, which is a set of principles and strategies for organizing the educational process aimed at forming and developing the cognitive abilities of the student. To identify the essence of computational thinking, a mental model of thinking is used, in which cognitive functions are determined by the mechanisms of perception, memorization, structuring and retrieval of information. In this model, knowledge is a structural set of mental images; mental schemes and mental models based on the first, second, and third signal systems.

Results. Consideration of the mental characteristics of a modern person in a digital society, definition of the 3rd signal system in the “person + ICT + artificial intelligence” link, in which mental schemes and mental models play the main role, made it possible to formulate the stages of the educational process target settings in the form of the taxonomy of educational goals.

The taxonomy of educational goals begins with the assignment of mental entropy - as a subject field of the future professional activity of a specialist, containing questions, tasks and problems. They can be formulated by traditional educational goals in the form of: know, be able to, master. The specification of these goals leads to target guidelines for the composition, volume and content of subject mental images, mental schemes and mental models. The set of mental images, schemes and models represent a knowledge block. In parallel, an ascending target block of universal cognitive operations is set, that a modern specialist must master. The pinnacle of the taxonomy is computational thinking. Based on the mental model of thinking, the essence of computational thinking is revealed and a set of universal cognitive operations is compiled. The basic composition of mental models that determine human cognitive behavior in a digital society is formed.

Computational thinking is a type of thinking with the activation of conceptual-abstract and conceptual-machine superstructures of mental images, mental schemes and models in the circuit of the third signal system.

Conclusion. The proposed mental taxonomy of educational goals determines the vector of the direction of digital transformation of education to achieve the main result - computational thinking. The stages of formation and the quality of computational thinking are determined by the formation of a set of universal cognitive operations, the volume and content of mental images, mental schemes and mental models of the subject area.

Purpose of research. The study aims to develop a comprehensive approach to assessing educational outcomes embedded by developers in educational programs. This approach can complement the pointrating system to provide a more detailed and multi-faceted assessment, especially within e-learning courses and, as a result, the entire electronic educational environment as a whole.

Materials and methods. The study is based on a competency-based approach, in which the assessment of educational outcomes is focused on the degree of competence formation as projected within each discipline and implemented in the educational program. The materials analyzed included the work program of the academic discipline, as well as the electronic learning course implemented for independent work on the discipline, based on LMS. Data from the electronic gradebook, generated from the results of student performance monitoring, were also used. Bloom’s taxonomy of educational objectives was utilized for the analysis and subsequent structuring of learning outcomes. Matrix modeling was applied for data processing and comparison. Additional research methods included analysis and synthesis, expert evaluation, methods of mathematical statistics (for processing the obtained matrices), as well as comparative analysis of empirical data.

Results. As part of the study, an analysis of the capabilities of the point-rating system (PRS) for assessing learning outcomes was conducted. To objectify the process of measuring educational results within a given course, it is proposed to use a structured model based on Bloom’s taxonomy of educational objectives.

This process is implemented as follows: the electronic gradebook of the course is imported in a matrix form, where the rows correspond to students and the columns to assessment elements (quizzes, assignments, projects, etc.). At the same time, a taxonomic (expert) matrix of the course is formed, in which each assessment element is assigned a weight reflecting its level according to Bloom’s taxonomy and its contribution to the achievement of specific competencies. By multiplying the gradebook matrix by the taxonomic matrix, it becomes possible to aggregate students’ individual achievements, taking into account the levels of competency achievement according to each level of the taxonomy.

An algorithmic approach to organizing a comprehensive process of learning outcomes assessment has been developed. This approach includes the stages of automated data export from LMS Moodle, matrix formation, their subsequent multiplication, and visualization of the obtained results as a results matrix. This not only ensures the objectivity of the point-rating assessment procedure but also enables regular monitoring of the achievement of the planned educational outcomes.

Empirical validation of the proposed methodology was carried out using the materials of a specific academic course delivered via an electronic learning environment. A comparison of the results obtained through the proposed algorithmic approach with the final results demonstrates the practical viability of the proposed scheme and its potential for replication in other courses and educational programs.

Conclusion. The proposed comprehensive approach to the assessment of educational outcomes ensures end-to-end traceability in the development of competencies and contributes to increased objectivity and transparency in the quality assurance procedure of education.

The purpose of the study. In the modern world, everyone is an active user of resources hosted on the global network. Logging in from different devices (computers, tablets, phones), we visit many electronic pages, correspond and view content, leaving our electronic footprint in the system each time. The purpose of the study is to identify such a trace, record it and process it using mathematical statistics methods in order to obtain personalized and generalized data for various industries. Also, based on the results obtained, recommendations are expected to be formed to protect digital footprint data from possible malicious use.

The paper examines the concept and describes in detail the sources of a digital trace of a participant in Internet interactions, identifies methods and tools for collecting and pre-processing information. The concept of active and passive components of a digital fingerprint is disclosed. Attention is focused on the need to classify the information contained in the digital trace as personal data, since it can sometimes determine a person more accurately than a document, which, in turn, requires legislative protection in terms of collection, storage, processing and further use. The article provides examples of using digital fingerprint information in various industries: criminalistics, marketing research, targeted advertising, etc.

Materials and methods. The article discusses in sufficient detail various methods of mathematical statistics for assessing the digital footprint of a network user, and provides steps that allow for the collection, preprocessing and analysis of information contained in a digital fingerprint using the Python, R programming languages and various software tools. The use of statistical analysis methods, the use of an interaction matrix, visualization capabilities, machine learning algorithms, recommendation systems, network metrics, time series, and sensitivity analysis methods are considered.

Results. Despite the fact that data obtained using mathematical statistics methods can be useful for businesses, government organizations, research institutes, and even law enforcement agencies, data collected in the course of activities on a global network and linked to a specific individual can pose a clear threat if used by intruders. These assessment methods are available both for constructive tendencies to improve our lives by selecting personalized relevant

content and improving the service, and for destructive activities through manipulative actions and blackmail. In this regard, knowledge of the trace left and the possibilities of using this data in its original and processed form makes it possible to improve the quality of life, on the one hand, and protect personal information, on the other.

Conclusion. Attention is drawn to the need for information control of one’s digital trace, in connection with which the article provides a number of recommendations for the implementation of safe Internet interaction.