RUS  ENG
Full version
JOURNALS // Problemy Fiziki, Matematiki i Tekhniki (Problems of Physics, Mathematics and Technics) // Archive

PFMT, 2023 Issue 3(56), Pages 88–94 (Mi pfmt924)

INFORMATION SCIENCE

Blended learning technology in the study of descriptive characteristics of a statistical sample

O. M. Demidenkoa, A. I. Yakimovb, E. A. Yakimovb, K. G. Tishchenkob

a Francisk Skorina Gomel State University
b Belarusian-Russian University, Mogilev

Abstract: A substantive description of blended learning is presented, the main elements of the blended learning model and methodology are noted: rotation, flipped class, individual plan, flexible model. The analysis of information and communication technologies and Internet resources with data sets for solving the problem of statistical data processing is performed. On an example of solving the problem of determining the descriptive characteristics of the statistical sample there is used programming language R with a set of libraries: WDI, xtable, openxlsx, psych, sm, ggplot2, tidyverse, dunn.test, rstatix, ggpubr. The implementation of parsing data from the World Bank's open data web resource (data.worldbank.org) is shown. The script in the programming language R for finding descriptive characteristics of the statistical sample is developed. The technology of using information and communication technology for the educational process in the study of statistical methods of data processing is proposed.

Keywords: blended learning, information and communication technology, parsing, R programming language, descriptive data sampling characteristics.

UDC: 004.67

Received: 10.06.2023

DOI: 10.54341/20778708_2023_3_56_88



© Steklov Math. Inst. of RAS, 2024