Understanding student teachers' collaborative problem solving: Insights from an epistemic network analysis (ENA). (July 2022)

• Record Type: Journal Article
• Authors: Zhang, Si; Gao, Qianqian; Sun, Mengyu; Cai, Zhihui; Li, Honghui; Tang, Yanling; Liu, Qingtang
• Is Part Of: Computers & education. Volume 183(2022)
• Publication Date: 2022-07
• Subjects: Computer-mediated communication -- Cooperative/collaborative learning -- Teaching/learning strategies -- Pedagogical issues; Education -- Data processing -- Periodicals; Education -- Periodicals; Computers -- Periodicals; Computer-Assisted Instruction -- Periodicals; Éducation -- Informatique -- Périodiques; Electronic journals; 370.285
• DOI: 10.1016/j.compedu.2022.104485
• Languages: English
• ISSNs: 0360-1315

Abstract

Abstract: Collaborative problem solving, as a key competency in the 21st century, includes both social and cognitive processes with interactive, interdependent, and periodic characteristics, so it is difficult to analyze collaborative problem solving by traditional coding and counting methods. There is a need for a new analysis approach that can capture the temporal and dynamic process of collaborative problem solving in diversity online collaborative learning context to provide some insights into online collaborative learning design. During an eight-week semester, a total of 42 student teachers participated in two online collaborative learning activities. Student teachers' discourse data were collected, and the data were coded based on a collaborative problem solving assessment model. This study used Epistemic Network Analysis (ENA) to explore the collaborative problem solving processes of student teachers in different online collaborative learning tasks. The results showed that both the high and low academic performance groups worked to maintain positive communication, but the students in the high academic performance groups negotiated on ideas while the students in the low academic performance groups focused on sharing resources/ideas. Moreover, fine-grained centroid analysis on a weekly basis showed that the high academic performance groups began by maintaining positive communication, and ended by negotiating ideas, while the low academic performance groups began by sharing resources/ideas and ended by regulating problem solving activities. Finally, the implications, limitations, and future research were discussed. Highlights: Epistemic network analysis was used to analyze students' collaborative problem solving processes. Both the high and low academic performance groups worked to maintain positive communication. Differences in CPS strategies led to the differences between the high and low academic performance groups.