UDC: 
371.322.8
Tsatrev Yuri V.
Кандидат технических наук, Cand. Sci. (Tech.), Assist. Prof. of the Department of Information Systems, Institute of Digital Systems, Yaroslavl State Technical University, tsarevyv@ystu.ru, Yaroslavl

The possibilities of the Teams information system in creating a digital footprint of first-year students

Abstract: 
The article examines in detail the problem of assessing the involvement of first-year students in the educational process and the degree of assimilation of knowledge using digital technologies that make it possible to obtain a student’s digital footprint. The purpose of the article is to present the technology for obtaining digital footprint data when teaching first-year students at Yaroslavl State Technical University in the discipline “Information Systems Architecture” in the MS Teams environment and to show options for performing digital footprint analysis. Methodology. The formation of digital footprint data was carried out in the process of lecture surveys, work on laboratory assignments and passing an exam. To obtain a digital footprint, information systems MS Teams, MS Excel, MS Forms were used. Data obtained in the MS Teams environment was subjected to pre-processing, cleaning, merging tables, and adding (deleting) attributes. The generated tables were analyzed using classification and cluster analysis to search for non-trivial knowledge. Cluster analysis allows us to identify groups of students who successfully complete lecture and exam testing and those who have difficulties completing test tasks. The analysis allows us to identify the level of complexity of tasks and allows for their adjustment. A comparison of the success of completing tasks during the lecture course and in the exam gives an idea of the students’ ability to prepare for participation in testing and the ability to memorize large volumes of complex scientific and technical information.
Keywords: 
digital footprint; MS Teams; cluster analysis; information systems; information culture
References: 

1. Pavlenko, D., Barykin, L., Dadteev, K., 2021. Collection and analysis of digital footprints in LMS. Procedia Computer Science, Vol. 190, pp. 666–669. (In Eng.)
2. Kuznetsova, I. Yu., Dochkin, S. A., 2021. Digital footprint as a tool for selecting applicants to a university. Current scientific research in the modern world, no. 11-10(79), pp. 154–158. (In Russ.)
3. Gabdrakhmanov, N. K., Orlova, V. V., Aleksandrova, Yu. K., 2021. Digital footprint in forecasting the educational strategy of school graduates. University management: practice and analysis, Vol. 25, no. 3, pp. 6–13. (In Russ.)
4. Kogteva, U. A., 2021. Digital traces and prospects for their use in the process of managing the educational process. Social and humanitarian technologies, no. 4(20), pp. 35–41. (In Russ.)
5. Mityagina, E. V., Konyshev, E. V., Chernyshev, K. A., Saifulin, E. R., 2021. Digital traces of university graduates in the study of migration from donor regions. Bulletin of Tomsk State University, no. 467, pp. 144–155. (In Russ.)
6. Baranova, E. V., Shvetsov, G. V., 2021. Methods and tools for analyzing a student’s digital footprint when mastering an educational route. Perspectives on science and education, no. 2 (50), pp. 415–430. (In Russ.)
7. Casalino, G., Castellano, G., Vessio, G., 2021. Exploiting Time in Adaptive Learning from Educational Data. Agrati, L.S., et al. Bridges and Mediation in Higher Distance Education. HELMeTO 2020. Communications in Computer and Information Science, Vol. 1344, pp. 3–16. (In Eng.)
8. Zhuravleva, V. V., Manicheva, A. S., Kozlov, D. Yu. [et al.], 2021. Analysis of big data using parallel computing: classification of schoolchildren using digital traces. High-performance computing systems and technologies, Vol. 5, no. 1, pp. 160–165. (In Russ.)
9. Gorbatov, S. V., Krasnova, E. A., 2022. Digital footprint as a mechanism for individualizing a student’s educational trajectory (using the example of the course “Digital Technologies of Self-Education”). Perspectives of Science and Education, no. 4 (58), pp. 193–208. (In Russ.)
10. Samarina, O. V., Samarin, V. A., 2022. Analysis of the digital footprint of students of Ugra State University. Bulletin of the Altai State Pedagogical University, no. 1 (50), pp. 30–35. (In Russ.)
11. Toktarova, V. I., Semenova, D. A., Zaripov, R. N., 2021. Assessing the effectiveness of students’ project activities based on the digital footprint. Bulletin of the Mari State University, Vol. 15, no. 4, pp. 420–453. (In Russ.)
12. Krylova, M. A., 2021. Studying the motivational involvement of students in educational activities based on the digital footprint. Bulletin of TVGU. Series: Pedagogy and psychology, no. 4, pp. 77–86. (In Russ.)
13. Kuzminykh, A. A., Stupnikov, A. A., 2021. Diagnostics of the development of Soft Skills (general competencies) according to the student’s digital footprint. Informatization of education and e-learning methodology: digital technologies in education: Proceedings of the V International Scientific Conference. In 2 parts, Vol. Part 1. Krasnoyarsk: Siberian Federal University, pp. 268–272. (In Russ.)
14. Prozorova, G. V., Nekrasova, A. A., Dolin, A. A., 2020. Technology for analyzing the digital footprint to determine the professional orientation of schoolchildren. Bulletin of TOGIRRO, no. 1 (44), pp. 29–30. (In Russ.)
15. Mozolevskaya, A. N., 2022. Prospects for using the “Digital Footprint” of a student at IrGUPS. Information technologies and mathematical modeling in the management of complex systems, no. 2 (14), pp. 43–49. (In Russ.)
16. Zakharova, I. G., Avriskin, M. V., 2021. Student’s digital footprint: from data to forecasts and recommendations. Informatization of education and e-learning methods: digital technologies in education: Proceedings of the V International Scientific Conference. In 2 parts, Part 2. Krasnoyarsk: Siberian Federal University, pp. 120–124. (In Russ.)
17. Uglev, V. A., Sychev, O. A., Anikin, A. V., 2022. Intellectual analysis of the digital footprint when assessing control and measurement materials to support decision-making in the educational process. Journal of the Siberian Federal University. Series: Equipment and technology, Vol. 15, no. 1, pp. 121–136. (In Russ.)
18. Documents for Microsoft Teams administrators [online]. Available at: https://learn.microsoft.com/ru-ru/microsoftteams/ (accessed 17.04.2024). (In Russ.)
19. Administrator of Microsoft Forms [online]. Available at: https://learn.microsoft.com/ru-ru/microsoft-forms/ (accessed 17.04.2024) (In Russ.)
20. Microsoft 365 documentation [online]. Available at: https://learn.microsoft.com/ru-ru/microsoft-365/?view=o365-worldwide (accessed 17.04.2024) (In Russ.)
21. Okike, E. U., Mogorosi, M., 2020. Educational Data Mining for Monitoring and Improving Academic Performance at University Levels. International Journal of Advanced Computer Science and Applications (IJACSA), Vol. 11, no. 11, pp. 570–581. (In Eng.)