Classroom misbehaviour management: an SVVR-based training system for preservice teachers

ABSTRACT

Training teachers to manage their instruction and the class is known to be important and challenging. In traditional teacher training programmes, micro-teaching is frequently adopted; however, its effectiveness could be limited if the learners do not have good opportunities to immerse themselves in and interact in the learning contexts. Virtual Reality (VR) technology could be a good approach to coping with this problem. Nevertheless, the development cost of a VR scene is high from the perspectives of time and money. Hence, a spherical view VR-based training system of classroom misbehaviour management (TrainCM2) is proposed in this study. TrainCM2 can situate learners in a real situation at a low cost. To verify the effectiveness of TrainCM2, an experiment was conducted. The experimental results showed that the TrainCM2 learners outperformed the micro-teaching learners in terms of misbehaviour detection rate and processing performance, showing the benefits of the proposed approach.

KEYWORDS:

• Misbehaviour management
• micro-teaching
• training system
• spherical view virtual reality
• pre-service teacher

Acknowledgements

This study is supported by the philosophy and social science research program of Zhejiang Province, grant 19NDJC144YB. This material is based upon work funded by Zhejiang Provincial Natural Science Foundation of China under Grant No. LY19F020037. We would like to thank Wenzhou University's Education Reform Project (18jg03) for its strong support.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Xindong Ye received the PhD degree in Department of Educational Information Technology from East China Normal University, Shanghai, China, 2014. He is currently an associate professor at College of Teacher Education, Wenzhou University, China. His research interests include educational technology, flipped learning and application of technology-enhanced learning spaces, Knowledge sharing in Virtual learning Environment, and big data analysis/mining.

Peng-Fei Liu is a graduate student at College of Teacher Education, Wenzhou University, China. Her research interests include educational technology, date analysis/mining, new media/technology and VR in education.

Xiao-Zhi Lee is an associate professor at College of Teacher Education, Director of the Experimental Center of College of Teacher Education, Wenzhou University, China. His research interests include ICT in education and VR technology in education.

Yi-Quan Zhang is a laboratory teacher at College of Teacher Education, Wenzhou University, China. Her research interests include rule learning, cognitive style, learning efficacy, and student psychology.

Chuang-Kai Chiu received the PhD degree in the College of Engineering from the Chung Hua University, Taiwan, in 2013. He is currently an associate professor at College of Teacher Education, Wenzhou University, China. His research interests include ICT in education, mobile/ubiquitous learning, and big data analysis/mining.

Additional information

Funding

This study is supported by the philosophy and social science research program of Zhejiang Province [grant number 19NDJC144YB]. This material is based upon work funded by Zhejiang Provincial Natural Science Foundation of China under [grant number LY19F020037]. We would like to thank Wenzhou University's Education Reform Project (18jg03) for its strong support.