Smart Interactive Education System Based on Wearable Devices

• Published in: Sensors (Basel, Switzerland) Vol. 19; no. 15; p. 3260
• Main Authors: Liang, Jia-Ming, Su, Wei-Cheng, Chen, Yu-Lin, Wu, Shih-Lin, Chen, Jen-Jee
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 24.07.2019; MDPI
• Subjects: Artificial intelligence; data analysis; education system; instant feedback; intelligent interactivity; learning concentration; Smartphones; Students; Teaching; wearable device; Taiwan; wearable device; intelligent interactivity; data analysis; education system; learning concentration; instant feedback
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s19153260

Due to the popularity of smart devices, traditional one-way teaching methods might not deeply attract school students’ attention, especially for the junior high school students, elementary school students, or even younger students, which is a critical issue for educators. Therefore, we develop an intelligent interactive education system, which leverages wearable devices (smart watches) to accurately capture hand gestures of school students and respond instantly to teachers so as to increase the interaction and attraction of school students in class. In addition, through multiple physical information of school students from the smart watch, it can find out the crux points of the learning process according to the deep data analysis. In this way, it can provide teachers to make instant adjustments and suggest school students to achieve multi-learning and innovative thinking. The system is mainly composed of three components: (1) smart interactive watch; (2) teacher-side smart application (App); and (3) cloud-based analysis system. Specifically, the smart interactive watch is responsible for detecting the physical information and interaction results of school students, and then giving feedback to the teachers. The teacher-side app will provide real-time learning suggestions to adjust the teaching pace to avoid learning disability. The cloud-based analysis system provides intelligent learning advices, academic performance prediction and anomaly learning detection. Through field trials, our system has been verified that can potentially enhance teaching and learning processes for both educators and school students.