학술논문

Detection of Concentration State Using Biosignals
Document Type
Conference
Source
2019 4th International Conference on Information Technology (InCIT) Information Technology (InCIT), 2019 4th International Conference on. :264-267 Oct, 2019
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Active Learning
biomedical signals
concentration measurement system
Language
Abstract
In current Japanese academic educational system, knowledge-centered passive learning become mainstream, and it has been caused by which the students have to pass the special exam in order to get into college. As a result of this actual condition, the decline of problem finding-and solving skills voluntarily has been issue when students become age which involves the society. Active Learning (AL), which adopts joining to active study, has been suggested from about 8 years ago, it has been advanced with it to foster general skills and the skill to go to the goal. Moreover it is possible that build better relationship each other with communication. There is the issue how much the teachers capture student’s degree of self-motivated learning when this AL applies to the class. In AL, it has been assessed subjectively with experimental rule and questionnaire after class. If teacher can capture that degree, it is possible to develop more effective AL by raising the communication level between teachers and students. In this research, we examine whether biological signals we focused on can apply to class as the indicator to expect the concentration by monitoring the concentration of students on a variety of action in a class and measuring the biological signals of students who study the class. We developed the system to measure that signals, and carry out the estimation by analyzing internal condition from the change of biological signals of students who is in a class under the concentrated state and non-concentrated state with this system. As a result of analysis, we confirmed the condition of the change about a number of times of blinks, brain waves and GSR underperforming tasks. This results show that we can confirm objectively student’s state of concentration underperforming AL. So it leads to advance the contents of class with capturing student’s state for teachers, and thus it is possible to suggest the new instructional mode with AL.