|
ИСТИНА |
Войти в систему Регистрация |
ИСТИНА ПсковГУ |
||
Analytical Studies of Behavior of Users of the Moscow Electronic School Serviceстатья
- Авторы: Lavrenova E.V., Frolov Yu V., Bosenko T.M.
- Сборник: Proceedings of 10th Computer Science On-line Conference
- Серия: Artificial Intelligence in Intelligent Systems
- Том: 2
- Год издания: 2021
- Издательство: Springer International Publishing AG
- Местоположение издательства: Cham, Switzerland
- Первая страница: 121
- Последняя страница: 132
- DOI: 10.1007/978-3-030-77445-5_11
- Аннотация: The article presents the results of the study, which analyzed the database of the Moscow Electronic School (MES) in the amount of about 50 thousand observations. The relevance of the study is that with the emergence of viral threats and the transition of the education system to remote learning processes, MES educational content is becoming increasingly popular. In this regard, it is important to plan work to improve the quality of user characteristics of the accumulated content and its impact on the indicators of the remote educational process. The key subject on which the motivation of the students depends and the results of their education is the teacher. Teachers in the MES system act simultaneously in different roles - both as creators of new educational content and as its users and evaluators. The aim of the study was to identify “hidden” groups of users with different typical behaviors in the MES database. The behavior of users in this work has been investigated by decomposing it into six parameters. The study used the MES database, as well as statistical, neural network methods and application software packages implementing them, which solved data clustering and visualization tasks. Based on the results of the study, the relationships between the behavioral parameters of users were determined and 5 behavioral types of MES users were identified. The analysis of used methods of statistical analysis and clustering of MES data made it possible to assess their applicability in the prediction of user groups and to identify factors that significantly influence the achievement of the goal of improving the efficiency of the MES platform and design in the perspective of the recommendation system. #CSOC1120KeywordsMoscow electronic school Database MES users Indicators of behavior of users Data clustering methods Visualization of analytical research results
- Добавил в систему: Лавренова Екатерина Владимировна