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The Prediction of Educational Success of Students-Humanitarians in Social Networks from the Psychometric View.

Authors :
GAFAROV, FAIL
ENIKEEVA, ZULFIRA
VAKHITOV, GALIM
NIKOLAEV, KONSTANTIN
Source :
International Journal of Pharmaceutical Research (09752366). Jan-Mar2020, Vol. 12 Issue 1, p804-811. 8p.
Publication Year :
2020

Abstract

The work is one of the pilot studies within the framework of the development of a theoretical and applied model for predicting a person's life activity in its educational activities through social networks. This study revealed that social networks are the result of profound changes in social reality models due to the intensive "digitalization" of modern society. In general, social networks reflect the virtualization of social processes which include the fusion of social and virtual realities. The behaviour of a person within the framework of social networks is reflected in the products of its virtual activity - the quantitative and qualitative (meaningful) metrics of its personal profile (friends, posts, likes, subscribers, etc.). As part of the hypothesis that the similarity of social networks users' virtual behaviour indicates the similarity of their real behaviour, we assume that a number of personal profile characteristics are psychometric predictors of future students' academic achievements. The interval distribution regularities of average quantitative characteristics values for high-achieving and lowachieving humanists' personal profiles in social networks (number of friends, communities, subscribers and photos) are shown based on their comparative analysis. As a result, psychometric predictors for academic achievements of humanists, which allow predicting their academic performance in the educational process, are presented in the work as a first approximation. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09752366
Volume :
12
Issue :
1
Database :
Academic Search Index
Journal :
International Journal of Pharmaceutical Research (09752366)
Publication Type :
Academic Journal
Accession number :
151943463
Full Text :
https://doi.org/10.31838/ijpr/2020.12.01.155