E3S Web Conf.
Volume 270, 2021International scientific forum on computer and energy Sciences (WFCES 2021)
|Number of page(s)||7|
|Published online||09 June 2021|
Intellectual analysis of education data
Surgut State University, Surgut, Russia
* Corresponding author: firstname.lastname@example.org
The relevance of the study is due to the fact that there are now more questions than specific answers on the topic in the context of educational data mining: how it is done, for what and how we can use it, what metrics to include in the sample and how to make predictions. Undoubtedly, in the coming years there will be a transition from discussions to the practical introduction of educational analytics into educational processes. The study analyzes these categories, and fundamentally differences educational analytics from pedagogical diagnostics and other methods of data collection. One of the objectives of the study is to build a model for individual educational solutions, provided that the data is well-assembled, so the study considers the types of educational analytics. The practical significance of the study is that all this can lead to a change in editorial educational policy, the language in which communication with students takes place, which is already a strategic task of learning.
© The Authors, published by EDP Sciences, 2021
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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