High-performing Groups during Children's Collaborative Coding Activities: What Can Multimodal Data Tell Us?
Authors: 
Feiran Zhang, Isabella Possaghi, Kshitij Sharma, Sofia PapavlasopoulouAuthors Info & Claims
Pages 533 - 559
Abstract
Nowadays, learning activities have become more interactive and collaborative than ever before. However, it remains unclear what makes the group perform differently in such a learning context. With the empowerment of multimodal data (MMD), we conducted a field study involving 12 groups of children who collaborated during two-day-long classroom activities. This paper reports on a quantitative analysis and temporal explanation concerning the relation between children's performance and their group-level MMD measurements during a collaborative coding session in a design thinking activity. We computed each group's performance based on the created artefacts and compared the groups with better performance than the others. The results demonstrate that high-performing groups show more joint engagement, joint visual attention, and joint emotional intensity of delight, while low-performing groups show significantly more joint emotional intensity of frustration. In addition, the evolution over the four temporal phases showed different patterns between high and low-performing groups. Finally, this paper discusses design and theoretical implications for educators, researchers and practitioners.
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- High-performing Groups during Children's Collaborative Coding Activities: What Can Multimodal Data Tell Us?
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June 2024
1049 pages
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DOI:10.1145/3628516
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