Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций
Конференция: International Scientific Conference on Innovative Approaches to the Application of Digital Technologies in Education, SLET 2020; Virtual, Stavropol; Virtual, Stavropol
Год издания: 2020
Ключевые слова: cognitive load, Eeg, intelligent learning systems
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 Показать полностьюis 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.
Журнал: CEUR Workshop Proceedings
Выпуск журнала: 2861
Номера страниц: 342-350