Challenges for data collecting of teacher and student' behavior in different types of class using video and wearable device
Kanae Matsui, Tatsuhiko Kasai, Keiya Sakai · 2019
Monitoring the behavior of both teachers and students using video data or Internet of Things (IoT) devices is necessary to achieve effective interactions and improve the environment in places of education. For the future, automatic data detection is required to be implemented, but prior to that learning data needs to be stored. Therefore, as a protocol, this research proposes a protocol for collecting video and vital data. Our proposed protocol has two types of behavior detection; (1) behavior tagging by an observer, and (2) heartbeat measurement as one of vital data using wearable devices. We conducted an experiment to test proposed protocol with participants who teachers and students, by holding two types of classes, a lecture type and a workshop type, and we used the results to determine the applicability of proposed protocol.