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Article

Investigating Sequence Patterns of Collaborative Problem-Solving Behavior in Online Collaborative Discussion Activity

1
School of Computer and Information Engineering, Henan University of Economics and Law, Zhengzhou 450046, China
2
Faculty of Education, Beijing Normal University, Beijing 100875, China
3
School of Computing and Information Technology, University of Wollongong, Wollongong, NSW 2522, Australia
4
College of Education, Zhejiang University, Hangzhou 310058, China
*
Author to whom correspondence should be addressed.
Sustainability 2020, 12(20), 8522; https://doi.org/10.3390/su12208522
Received: 22 September 2020 / Revised: 10 October 2020 / Accepted: 13 October 2020 / Published: 15 October 2020
Collaborative problem solving (CPS) is an influential human behavior affecting working performance and well-being. Previous studies examined CPS behavior from the perspective of either social or cognitive dimensions, which leave a research gap from the interactive perspective. In addition, the traditional sequence analysis method failed to combine time sequences and sub-problem sequences together while analyzing behavioral patterns in CPS. This study proposes a developed schema for the multidimensional analysis of CPS. A combination sequential analysis approach that comprises time sequences and sub-problem sequences is also employed to explore CPS patterns. A total of 191 students were recruited and randomly grouped into 38 teams (four to six students per team) in the online collaborative discussion activity. Their discussion transcripts were coded while they conducted CPS, followed by the assessment of high- and low- performance groups according to the developed schema and sequential analysis. With the help of the new analysis method, the findings indicate that a deep exploratory discussion is generated from conflicting viewpoints, which promotes improved problem-solving outcomes and perceptions. In addition, evidence-based rationalization can motivate collaborative behavior effectively. The results demonstrated the potential power of automatic sequential analysis with multidimensional behavior and its ability to provide quantitative descriptions of group interactions in the investigated threaded discussions. View Full-Text
Keywords: behavioral sequence patterns; problem-solving task; online collaborative discussion; visualization behavioral sequence patterns; problem-solving task; online collaborative discussion; visualization
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MDPI and ACS Style

Zheng, Y.; Bao, H.; Shen, J.; Zhai, X. Investigating Sequence Patterns of Collaborative Problem-Solving Behavior in Online Collaborative Discussion Activity. Sustainability 2020, 12, 8522. https://doi.org/10.3390/su12208522

AMA Style

Zheng Y, Bao H, Shen J, Zhai X. Investigating Sequence Patterns of Collaborative Problem-Solving Behavior in Online Collaborative Discussion Activity. Sustainability. 2020; 12(20):8522. https://doi.org/10.3390/su12208522

Chicago/Turabian Style

Zheng, Yafeng, Haogang Bao, Jun Shen, and Xuesong Zhai. 2020. "Investigating Sequence Patterns of Collaborative Problem-Solving Behavior in Online Collaborative Discussion Activity" Sustainability 12, no. 20: 8522. https://doi.org/10.3390/su12208522

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