Prognostic model for assessing the success of subject learning in conditions of digitalization of education

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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 Federation

Yuliya 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 Federation

Marina 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 Federation

Irina 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 Federation

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Copyright (c) 2023 Noskov M.V., Vaynshteyn Y.V., Somova M.V., Fedotova I.M.

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