Measuring cognitive load based on EEG data in the intelligent learning systems : доклад, тезисы доклада

Murtazina M.; Avdeenko T.

Дополнительные ссылки: eLibrary · Источник статьи

База данных: Каталог библиотеки СФУ

Библиографическое описание: Measuring cognitive load based on EEG data in the intelligent learning systems : доклад, тезисы доклада / M. Murtazina, T. Avdeenko. - [S. l. : s. n.], 2020. - Текст : непосредственный // CEUR Workshop Proceedings / International Scientific Conference on Innovative Approaches to the Application of Digital Technologies in Education, SLET 2020 (2020 ; 12.11 - 13.11 ; Virtual, Stavropol). - 2020. - 2861. - P. 342-350.

Аннотация: The article presents the application of the EEG neuroheadset as a component of intelligent learning systems. Traditionally, intelligent learning systems include three knowledge representation models: an expert model, a mentor model, and a student model. The student model reflects the level of his knowledge, as well as how the task is perceived, how the student reacts to the warning and help of the mentor. The inclusion into the student model of the indicators of his reaction to the task based on the analysis of physiological signals seems to be an extremely promising direction of research aimed at improving learning outcomes and developing individual computer-based teaching methods based on feedback. One of the important indicators that can be monitored using the EEG is cognitive load. The paper analyzes methods for measuring cognitive load based on EEG data. An approach to organizing the monitoring of cognitive load using Python libraries is proposed. The MNE library was used to process the EEG data, and the PyEEG library was used to extract the features from the EEG.

Год издания: 2020

Авторы: Murtazina M. , Avdeenko T.

Источник: CEUR Workshop Proceedings

Выпуск: 2861

Мероприятие: International Scientific Conference on Innovative Approaches to the Application of Digital Technologies in Education, SLET 2020 (Virtual, Stavropol, 2020 ; 12.11 - 13.11)

Номера страниц: 342-350

Держатель оригинала документа: Novosibirsk State Technical University

Количество экземпляров:

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