Высшее образование в России (Mar 2024)

Digital Footprint: Assessing Student Satisfaction with Education Quality

  • M. M. Krishtal,
  • A. V. Bogdanova,
  • M. G. Myagkov,
  • Yu. K. Alexandrova

DOI
https://doi.org/10.31992/0869-3617-2024-33-2-89-108
Journal volume & issue
Vol. 33, no. 2
pp. 89 – 108

Abstract

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The COVID-19 pandemic has changed the way learning is organized around the world. Russian universities have also been faced with the need to quickly transfer all teaching to an online format. The importance of student satisfaction with the education quality in online learning is increasing, since it is an important condition for motivation. The paper shows that based on the analysis of students’ messages in the social network, it is possible to observe and analyze the overall dynamics and trends in student community satisfaction with the quality of the learning / the efficiency of universities and conduct a comparative analysis of the identified characteristic data groups with their totality. It is shown that the data on the reaction of students of a particular university may have significant deviations from the totality of data, which reflects the characteristics of the reaction of students of a particular university to events occurring at the same time. This may indicate the internal differences of the university, which form an appropriate response to external events.To understand the satisfaction of students in the transition to a new implementation format of the learning. The digital traces of students from the social network VKontakte were analyzed using individual Big Data tools on the PolyAnalyst software platform. This made it possible to trace changes in the mood of students and, on the example of a single university, to identify and explain deviations in the attitude of students to the implementation of the learning, as well as to verify the methodology. The methodology developed by authors makes it possible to detect problematic issues in the university, including the moment of their occurrence, relevance, degree of concern of students. Such content analysis can be used not only to assess students’ satisfaction with the quality of the learning, but also to monitor the emergence of any problems that cause concern and strong reactions on the part of the student community, as well as other communities and individual groups.

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