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Prognostic model for assessing the success of subject learning in conditions of digitalization of education
- Authors: Noskov M.V.1, Vaynshteyn Y.V.1, Somova M.V.1, Fedotova I.M.1
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Affiliations:
- Siberian Federal University
- Issue: Vol 20, No 1 (2023)
- Pages: 7-19
- Section: MANAGEMENT OF EDUCATIONAL INSTITUTIONS IN THE INFORMATION ERA
- URL: https://journals.rudn.ru/informatization-education/article/view/34205
- DOI: https://doi.org/10.22363/2312-8631-2023-20-1-7-19
- EDN: https://elibrary.ru/BDFDRI
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Abstract
Problem statement. One of the approaches to solving the problem of predicting the academic performance of students is displayed. Unlike existing studies in this area, which are mainly aimed at predicting the effectiveness of graduation, that is, based on the results of intermediate certifications that allow us to assess the chances of students to successfully graduate from a university, the results of this study are aimed at predicting the success of education in the early stages of the educational process. Methodology. A feature and novelty of the proposed prognostic model is the forecasting of student performance based on the Markov model, the data sources of which are universal predictors of an e-learning course that determine the success of subject education based on the personal characteristics of the student. Results. The authors present a description of a predictive model for assessing the success of subject education in the context of digitalization of education, reveal their experience of its approbation for students of the Siberian Federal University in the field of study “Informatics and Computer Engineering” and the results of a qualitative assessment of the model. Conclusion. The prospects for building a digital service for predicting the academic performance of students in the electronic information and educational environment of the university based on the results of the study are stated.
About the authors
Mikhail V. Noskov
Siberian Federal University
Email: mnoskov@sfu-kras.ru
ORCID iD: 0000-0002-4514-7925
Doctor of Physical and Mathematical Sciences, Professor, Professor of the Department of Applied Mathematics and Computer Security, Institute of Space and Information Technologies
79 Svobodnyi Prospekt, Krasnoyarsk, 660041, Russian FederationYuliya V. Vaynshteyn
Siberian Federal University
Author for correspondence.
Email: yweinstein@sfu-kras.ru
ORCID iD: 0000-0002-8370-7970
Doctor of Pedagogy, Associate Professor, Professor of the Department of Applied Mathematics and Computer Security, Institute of Space and Information Technologies
79 Svobodnyi Prospekt, Krasnoyarsk, 660041, Russian FederationMarina V. Somova
Siberian Federal University
Email: msomova@sfu-kras.ru
ORCID iD: 0000-0002-8538-4108
senior lecturer, Department of Applied Informatics, Institute of Space and Information Technologies
79 Svobodnyi Prospekt, Krasnoyarsk, 660041, Russian FederationIrina M. Fedotova
Siberian Federal University
Email: ifedotova@sfu-kras.ru
ORCID iD: 0000-0002-8673-6275
Candidate of Physical and Mathematical Sciences, Associate Professor, Associate Professor of the Department of Applied Mathematics and Computer Security, Institute of Space and Information Technologies
79 Svobodnyi Prospekt, Krasnoyarsk, 660041, Russian FederationReferences
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