PEDAGOGICAL EXPERIENCE
In a teacher’s work, a large amount of data accumulates about students taking courses. The data must be processed to improve materials and test pedagogical hypotheses. But with an increase in the amount of information, this becomes almost impossible. The article discusses approaches to the analysis of students’ digital footprint and its neural network generation for constructing intelligent personalized learning trajectories. Existing approaches to adaptive learning and propose a new methodology based on time series analysis and machine learning are investigated. Application results of digital learning platform Mirera for collecting and processing student activity data and the ability to predict students’ academic success based on their digital footprint are presented. A method for categorizing learners based on their learning characteristics and behavior data collected during training is proposed. Synthetic data generation is used to improve the accuracy of prediction models and build long-term predictions. The conducted computational experiment confirms the effectiveness of the proposed approach compared to traditional methods of educational data analysis. The results obtained can be used to automate adaptive learning and improve the quality of the educational process.
The goal of the study considered in the article is to conduct a theoretical analysis of the role of digital personality and digital twin in shaping personal identity within the context of distance education. The study aims to explore the interaction between real personality, its digital projection, and the digital twin in the context of online learning, as well as to identify opportunities and challenges associated with the use of digital technologies in education.
The research is based on a comprehensive literature review, including classical and contemporary works in psychology, education, and digital technologies. Comparative analysis and conceptual modeling methods are employed to study the impact of distance learning on personal identity. The study also incorporates ideas from self-awareness, self-determination theories, and digital identity.
The study reveals that digital personality allows individuals to experiment with various aspects of their identity, while the digital twin provides tools for behavior analysis and prediction. However, the gap between real and digital personalities can lead to identity distortion.
The findings can be used to develop educational platforms that support holistic personality development and programs aimed at enhancing self-discipline and managing digital identity. The practical significance of the research lies in the development of recommendations for educators and platform developers.
The proposed approaches will help create an inclusive and supportive digital environment, fostering comprehensive personality development in distance education. The results can be used to improve student motivation, increase engagement in the educational process, and mitigate risks associated with digital identity.
The study is targeted at educators, platform developers, and researchers, making it relevant for practical application. The novelty of the results lies in a comprehensive approach to analyzing the interaction between digital personality and digital twin in education.
The research has international significance, as the digitalization of education is a global trend, and its findings can be useful for researchers and practitioners worldwide.
INFORMATIZATION OF EDUCATION
In modern conditions, developers of hardware and software are actively using the potential of digital technologies to significantly improve the quality of various spheres of life, including education. Key advantages include facilitating interaction between all participants in the educational process, increasing student interest and engagement, enhancing the overall accessibility of education, and improving its effectiveness. The purpose of the research was to study existing scientific works dedicated to the modernization of hardware and software within the system of departmental higher education to identify key development vectors. The result of the work was not only an overview of modern educational software, but also a classification of current areas of their development and modernization, used in the framework of digital support of the educational process. It is proposed to identify two major vectors covering both educational software and automation tools for education management. The practical significance of the work is stems from its comprehensive of a wide range of modern hardware and software currently used in higher educational institutions of the Russian Ministry of the Interior of Russia. The results presented by the author can become the basis for developing strategies for the digital transformation of education, as well as for creating modern educational software and equipment based on the specified universities in training personnel for internal affairs agencies.
PEDAGOGICAL ASSESSMENTS AND TESTS
The ability to work with information is becoming a key success factor in the modern world, and the formation of information and communication competence (IC competence) in the younger generation is one of the most important task of general education. Based on the data obtained during the testing of the IC competence of basic school graduates, the study answers two questions: 1) What are the main deficiencies in the IC competence of ninth-graders? 2) How realistic is it to conduct a valid assessment of the IC competence of students in a modern mass school? More than 30 thousand ninth-graders participated in the testing. To assess the IC competence, a domestic digital tool ICL-test with automatic feedback was used. The test is based on the methodology of evidence-based argumentation and consists of authentic scenario-type tasks that are close to the tasks of working with information encountered in the daily life of schoolchildren. The testing was supplemented by a parallel survey of students, their teachers and heads of educational organizations who participated in the survey. The results of the study showed that more than half of the participants failed to demonstrate competence corresponding to their readiness for successful life in the modern information society. Deficiencies were identified that require the attention of teachers, methodologists and education managers. The practical suitability of the developed tool for a fullscale assessment of the IС competence of students in a general school was proven. The results of the study will be useful for teachers, methodologists and education system managers involved in digital transformation and updating the content of general education.
The article presents the results of a comprehensive study on the impact of big data technologies on the fundamentalization processes of professional education in hospitality as a foundation for developing competitive specialists in the digital economy. The empirical basis consisted of a pedagogical experiment (2022–2024) involving 920 respondents, including 640 students in “Hotel Management” and “Tourism” programs and 280 practicing hospitality industry specialists.The methodology was based on the use of big data analytics platforms (89 % accuracy in predicting professional competencies) and intelligent educational trajectory analysis systems (adaptivity coefficient K = 24) for learning personalization. Statistical analysis revealed significant increases inthe experimental group: fundamental knowledge level by 31 %(t = 12.67, p < 0.001), proportion of students with high professional readiness from 18 %to 52 %(χ2 = 56.34, p < 0.001), digital literacy index from 2.4 to 4.1 points (t = 14.23, p < 0.001). Mathematical models were constructed for professional competency dynamics (logistic, R2 = 0.88) and digital skills (power, R2 = 0.84). Key predictors of big data effectiveness in education were identified: intensity of analytical systems usage (β = 0.43–0.47), depth of educational content personalization (β = 0.35–0.39), volume of processed learning activity data (β = 0.28–0.32), collectively explaining up to 67 %of variance in competency development. Specificity by training programs was revealed: “Hotel Management” students showed greater growth in managerial competencies (t = 3.84, p < 0.01), while “Tourism” students demonstrated stronger analytical skills (t = 4.17, p < 0.001) and creative abilities (t = 3.92, p < 0.01). Cluster analysis identified four typological groups of students: “Digital Leaders” (23 %), “Adapters” (34 %), “Traditionalists” (28 %), and “Laggards” (15 %) with 94 %discrimination probability. The results contribute to professional education theory development and can serve as a basis for developing hospitality industry specialist training standards in the big data era.
Current trends in education digitalization require a fundamental rethinking of methodological approaches to organizing professional education. The study aims to develop an integrated distance learning model that combines adaptive technologies with methodological principles of professional training. The methodology is based on systematic analysis of empirical data from 1247 participants in the educational process from 18 professional educational organizations during 2023-2024. Methods of regression analysis, clustering, machine learning, and statistical modeling were applied to identify patterns of distance learning effectiveness. Results demonstrate predictive accuracy of 89.4 % in predicting academic results. Cluster analysis identified four typological groups of students: “High-adaptive”, “Moderate- adaptive”, “Traditionalists”, and “Technophobes”. The theoretical significance of the study lies in creating a conceptual framework for designing adaptive educational systems of professional orientation. The practical value is determined by the possibility of scaling the proposed solutions in the professional education system to improve the quality of specialist training in the digital economy.
This article presents a statistical analysis of data obtained during a study of the effectiveness of a technology for developing children’s inventiveness, integrated with digital tools, as a method for fostering creativity and moral qualities in students. The data was collected during an experiment involving 480 schoolchildren and 270 engineering students. The methodology was based on the use of training neural networks and digital twins to simulate inventive activity. The analysis revealed a significant increase in the study indicators in the experimental group: creativity by 28%, the share of high levels of inventiveness from 12 %to 38 %, and the priority of moral motives from 28 %to 56 %. The study constructed mathematical models of the dynamics of creativity (logistic) and inventiveness (exponential). Key predictors of the technology’s effectiveness were identified: the intensity of neural network use, involvement invirtual modeling, and the volume of digital artifacts,whichtogether explainup to 61 %of the variance inthe development of abilities. A gender-specific pattern was identified: boys showed greater improvement in spatial and technical thinking, while girls showed greater improvement in social orientation and communication skills. Cluster analysis revealed three typological groups of students: “Innovators” who demonstrated the highest values for the parameters studied; “Practitioners” who demonstrated moderate levels of creativity and inventiveness; and “Conservatives” who demonstrated relatively low levels of creativity and inventiveness. The study’s results will be useful for developing a ability theory and can serve as a basis for developing personalized programs to support scientific and technical creativity.
The article presents a study of the application of interactive learning materials as a means of increasing engagement of foreign students in the educational process. The relevance of the topic is due to the growing need for innovative approaches that can overcome the limitations of traditional teaching methods and ensure more active student participation in the educational process. The aim of the study is to evaluate the effectiveness of interactive learning materials in increasing student engagement and to identify key factors for their successful implementation. The methodology includes a quasi-experimental design with pre-post testing on a sample of 240 foreign students. Data were collected through engagement questionnaires, observations, and focus groups, and analyzed using descriptive and inductive statistics. The results showed a statistically significant increase in behavioral, emotional, and cognitive engagement in the experimental group. Qualitative analysis revealed the role of interactivity, personalization, multimodality, and game elements in stimulating engagement. The results contribute to understanding the mechanisms of engagement of foreign students and provide practical guidelines for creating interactive learning environments. Further research may be directed at studying long-term effects and adapting the approach for different learning contexts.
ISSN 2658-7769 (Online)






















