A novel group cognitive graph approach for improving collaborative problem solving

Abstract Collaborative problem-solving abilities are considered crucial skills in the 21st century. However, learners often struggle with collaborative problem-solving tasks. This empirical study aimed to propose and investigate the impacts of a novel group cognitive graph (GCG) approach on collaborative problem solving. In total, 90 college students voluntarily participated in the present study, and they were assigned to three conditions: the group cognitive graph (GCG) condition, the group knowledge graph (GKG) condition, and the control group (CG) condition. The findings revealed that the GCG approach significantly improved the collaborative problem-solving performance and collaborative knowledge building of the participants. Moreover, the group cognitive graph approach did not increase the imposed cognitive load. The findings and their implications for research and practice are discussed in depth.

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Publication Details

Journal
International Journal of Educational Technology in Higher Education
Published
2025-03-28
DOI
https://doi.org/10.1186/s41239-025-00520-6
Citations
1
Primary Topic
Cognitive Science and Mapping
Type
article
Field-Weighted Citation Impact
2.48
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article

A novel group cognitive graph approach for improving collaborative problem solving

Yunchao Fan, Lei Gao, Lanqin Zheng, Z. Shi
1 citations
International Journal of Educational Technology in Higher Education
Cognitive Science and Mapping
2.48
article

A novel group cognitive graph approach for improving collaborative problem solving

Yunchao Fan, Lei Gao, Lanqin Zheng, Z. Shi
article en
1 citations

Abstract

Abstract Collaborative problem-solving abilities are considered crucial skills in the 21st century. However, learners often struggle with collaborative problem-solving tasks. This empirical study aimed to propose and investigate the impacts of a novel group cognitive graph (GCG) approach on collaborative problem solving. In total, 90 college students voluntarily participated in the present study, and they were assigned to three conditions: the group cognitive graph (GCG) condition, the group knowledge graph (GKG) condition, and the control group (CG) condition. The findings revealed that the GCG approach significantly improved the collaborative problem-solving performance and collaborative knowledge building of the participants. Moreover, the group cognitive graph approach did not increase the imposed cognitive load. The findings and their implications for research and practice are discussed in depth.

International Journal of Educational Technology in Higher EducationVol. 22(1)
Beijing Normal University (CN)
Openalex Percentile: Top 11%
Cognitive Science and Mapping
2.48
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