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ERIC Number: EJ1487480
Record Type: Journal
Publication Date: 2025
Pages: 31
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1556-1607
EISSN: EISSN-1556-1615
Available Date: 2024-07-11
Revealing the Interplay of Cognitive, Meta-Cognitive, and Social Processes in University Students' Collaborative Problem Solving: A Three-Stage Analytical Framework
Shuowen An1; Si Zhang1; Zhihui Cai2; Wei Pan2; Mingwei Li1; Mingwen Tong1
International Journal of Computer-Supported Collaborative Learning, v20 n1 p9-39 2025
An in-depth analysis of collaborative problem solving (CPS) patterns contributes to understand team dynamics and effective paths to conflict resolution. However, there remains the lack of a perspective in the field of CPS research that organically combines the cognitive, meta-cognitive, and social-communicative dimensions. Moreover, the analysis of CPS sequences has primarily focused on the temporal dimension while overlooking the differences in spatial dimensions. To shed further light on the nature of CPS in computer-based environments, this study collected discourse data generated by 24 university students through an online synchronous chat tool. They were student teachers from a variety of disciplines (math, history, English, etc.) who were required to accomplish two tasks: instructional design and multimedia courseware development. Specifically, a three-stage analytical framework was proposed to code, cluster, and analyze these discourse data to further explore the differences in CPS patterns. We clustered time sequences by calculating the distance similarity metric via the dynamic time warping (DTW) method, which took into account both the spatial and temporal characteristics of the time sequences. Consequently, 16 time sequences of CPS processes were divided into 2 kinds of clusters (CPS subgroups), i.e., cluster 1 and cluster 2. From the statistical analysis, both clusters actively used the skills included in the meta-cognitive dimensions. Cluster 1 was oriented toward the solution of the problem whereas cluster 2 focused primarily on the requirements of the collaborative problem itself. From the process mining analysis, solution-driven cluster 1 tended to focus on expressing specific ideas and evaluating and summarizing them, intermittently monitoring and regulating task progress. Problem-driven cluster 2 tended to express specific ideas intermittently, and lacked the process of summarizing and evaluating different ideas to further filter out the best solutions. Finally, we summarized the implications of this study from theoretical and practical perspectives and discussed future research directions with regard to the limitations of this study.
Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link-springer-com.bibliotheek.ehb.be/
Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A
Author Affiliations: 1Central China Normal University, Hubei Key Laboratory of Digital Education, Faculty of Artificial Intelligence in Education, Wuhan, China; 2Central China Normal University, School of Psychology, Wuhan, China