Estimation Coefficients for Evaluating the Efficiency of IT Facilitated Online Learning

The paper gives the authors' proposal to apply the estimation coefficients for evaluating the efficiency of education delivered online, i.e. distance learning. In light of the current situation related to the COVID-19 pandemic, distance learning technologies are developing rapidly, making it necessary to ensure their effectiveness against the conventional offline full-time delivery of the educational services. Thus, the urgency of the research is caused by the emerging need to ensure the up-to-the-mark level of online studies which is becoming a global trend nowadays. So, the study pursued the goal of developing the estimation coefficients for measuring the effectiveness of the learning process delivery in the IT facilitated online mode and sharing the results of observations made throughout the pilot study. The appropriate usage of the evaluation models based on these indicators enables a more precise and accurate evaluation of the learning process efficiency in terms of both qualitative and quantitative criteria. To appraise the efficiency of the learning-teaching process, cross comparison of conventional (classical, offline) and distant (remote, online) study modes was performed. Thus, the thorough comparative analysis of the indicators allowed to identify the most important of them, both qualitative and quantitative ones, and synthesize them taking into consideration the relevant impact factors. Based on the further comprehensive analysis rational values of the estimation coefficients were identified and clarified. As a result, it was made possible to formulate and approximate the coefficients which ensure prompt and relatively accurate evaluation of the quality of the learning process delivered online. © 2021 IEEE.

Authors
Arskiy A. 1 , Golubovskaya E. 2 , Shailieva M.3
Publisher
Institute of Electrical and Electronics Engineers Inc.
Language
English
Pages
220-225
Status
Published
Year
2021
Organizations
  • 1 Moscow State University of Food Production, Department of Customs and Commodity Expertise, Moscow, Russian Federation
  • 2 RUDN University, Russian Academy of Education, Faculty of Science, Moscow, Russian Federation
  • 3 Moscow State University of Food Production, Department of Business Management and Service Technologies, Moscow, Russian Federation
Keywords
Comparative analysis; Comprehensive analysis; Distant learning; Estimation coefficients; IT facilitated education
Date of creation
16.12.2021
Date of change
16.12.2021
Short link
https://repository.rudn.ru/en/records/article/record/76162/
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