In recent years, concentration has garnered attention as a metric for measuring learning effectiveness. One approach to concentration measurement involves using contact-based sensors. However, this method presents challenges such as placing a burden on users and requiring significant effort to assemble the necessary equipment. Another method, which imposes a relatively lighter burden on users, utilizes non-contact web cameras. However, these systems are primarily designed for corporate use, and there is essentially no concentration measurement system available for individual use.

In this study, we aim to develop a system that is simpler than conventional ones and capable of measuring learning effectiveness across various methods, such as online classes. We will also verify its effectiveness. We expect this system to be utilized as a tool to analyze which aspects of learning methods influence learning effectiveness and how they can be improved. Furthermore, by using this system, learners themselves can identify the optimal learning methods, break times, and duration for their needs. By monitoring their concentration during online classes, learners can prevent a decline in focus, thereby improving learning efficiency and enhancing their overall learning outcomes.

Authors:
Tomoko Kashima, Kindai University, Japan
Yuki Omasa, Kindai University, Japan
Shimpei Matsumoto, Hiroshima Institute of Technology, Japan

About the Presenter(s)
Dr. Kashima is an associate professor in the Department of Informatics, Faculty of Engineering, Kidai University, Japan.

See this presentation on the full schedule – Saturday Schedule

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