Analytical Potential of the Distance Learning Platform InfoD Moodle MPGU

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Abstract

The article provides data revealing the nature of the development of distance learning at Moscow Pedagogical State University. It is shown that as distance educational technologies spread, more and more data is accumulated, which can be successfully used for analyzing and designing educational results. Software solutions and approaches for developing the functionality of the Moodle platform for the purpose of predicting academic performance are described.

General Information

Keywords: educational data analysis, distance learning platform, educational analytics, artificial intelligence

Publication rubric: Modeling and Data Analysis for Digital Education

Article type: theses

For citation: Demina S.A., Postyrnak V.I., Mikhaylova M.V. Analytical Potential of the Distance Learning Platform InfoD Moodle MPGU. Digital Humanities and Technology in Education (DHTE 2023),, pp. 533–548.

Information About the Authors

Svetlana A. Demina, PhD in Economics, associate professor, Director of the Center for Distance Educational Technologies, Moscow Pedagogical State University (FSBEI HE MPGU), Moscow, Russia, ORCID: https://orcid.org/0000-0003-1637-4587, e-mail: svetlana-mefi@yandex.ru

Valery I. Postyrnak, associate professor, leading specialist of the Center for Distance Educational Technologies, Moscow Pedagogical State University (FSBEI HE MPGU), Moscow, Russia, ORCID: https://orcid.org/0000-0003-3073-549X, e-mail: vip_1948@mail.ru

Marina V. Mikhaylova, Doctor of Physics and Matematics, Professor, Head of the Department of Business Informatics, Institute of Management, Economics and Finance, University of World Civilizations named after. V.V. Zhirinovsky, Professor of the Department of Algebra, Moscow State Pedagogical University, Moscow, Russia, e-mail: mmvne@yandex.ru

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