Exploring student teachers’ social knowledge construction behaviors and collective agency in an online collaborative learning environment

ABSTRACT

The potential of online collaborative learning has been recognized in teacher education, and the value student teachers’ collective agency in predict their sustainable professional develop has been discussed. However, there is limited understanding of how student teachers’ collaborative knowledge construction behaviors correlate with their collective agency. This study investigated one class of student teachers’ collaborative knowledge construction behavioral pattern in a multi-layered interaction activity, and further explained their correlation with the participants’ collective agency. A total of 50 third-year student teachers from a class of a university in central China participated in the study. The results suggested that in terms of the average density, both intragroup and intergroup interaction networks were high-density ones. However, the number of interactions within each group was uneven. The student teachers had different reciprocity in intragroup and intergroup discussions. Their social knowledge construction behavioral patterns showed different characteristics in different stages of the multi-layered interaction activity. The questionnaire survey and interview data further revealed that though the student teachers built up collaborative learning awareness to some extent, their collective agency still has space to be improved. The authors conclude with some insights into the online collaborative learning in sustainable teachers’ professional development.

KEYWORDS:

• Collaborative learning
• social knowledge construction behavior
• teacher education
• collective agency

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability

Data can be accessed by contacting the author (saved in a personal repository).

Additional information

Funding

This work was supported by Ministry of Education of China and China Mobile (NO. MCM20170502) and the National Natural Science Foundation of China (NO. 61772012).

Notes on contributors

Si Zhang

Si Zhang received the PhD degree in educational technology from Central China Normal University, Wuhan, China, in 2017. Currently, he is an associate professor in the School of Educational Information Technology, Central China Normal University, China. His main areas of interest include technology enhanced collaborative learning, mobile learning, and learning analysis. He has published more than 20 academic papers in SCI and SSCI journals such as Computers and Education and Universal Access in the Information Society.

Yun Wen

Yun Wen is an Assistant Professor at the National Institute of Education, Nanyang Technological University (NTU, Singapore). She obtained her PhD from NTU and completed her Postdoc at the Computer-Human Interaction in Learning and Instruction (CHILI) Lab in EPFL, Switzerland. Her research interests include Computer-supported Collaborative Learning, Computer-assisted Language Learning, Learning Design, and Learning Analytics. She works on investigating how people learn through interaction and conversations in multimodal environments, and how to use technology (e.g., representational tools, augmented reality, etc.) to spark and support collaborative learning.

Qingtang Liu

Qingtang Liu received the PhD degree in communication and information system from the Huazhong University of Science and Technology, Wuhan, China, in 2005. He is currently a chair professor at the Central China Normal University, Wuhan, China. In recent years, he has published more than 30 academic papers in SCI and SSCI journals such as Computers and Education, and Knowledge-Based Systems. His research interests include adaptive learning, learning analysis, and artificial intelligence in education.