SHS Web Conf.
Volume 79, 2020International Scientific and Practical Conference “Theory and Practice of Project Management in Education: Horizons and Risks”
|Number of page(s)||6|
|Section||Status and Prospects of Modern Education Digitalization|
|Published online||19 August 2020|
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Kazan (Volga region) Federal University, Institute of Psychology and Education, Department of Clinical Psychology and Personality Psychology, Kazan, Russia
2 Kazan (Volga region) Federal University, Institute of Computational Mathematics and Information Technologies, Department of Information Systems, Kazan, Russia
3 Kazan (Volga region) Federal University, Institute of Psychology and Education, Department of General Psychology, Kazan, Russia
* Corresponding author: firstname.lastname@example.org
This paper discusses the technical details of obtaining and processing data to determine a set of characteristics of texts from social networks, genre preferences in movies and music genres for students of Kazan Federal University who have different academic performance (successful, average, not-successful). The selection of such characteristics is carried out using machine learning methods (Word2Vec, tSNE). The data obtained is used in the development of a functional psychometric model of cognitive behavioral predictors of an individual’s activity within the framework of their educational activities. We also developed a web application for visualizing the obtained data using the Flask engine.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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