Capturing patterns of argumentation elements, encountered challenges, and social regulation in collaborative argumentation: an epistemic network analysis study

Collaborative argumentation is a crucial learning activity affected by various factors, including the use of argumentation elements, encountered challenges, and social regulation. Few studies examined how these factors collectively impact argumentation outcomes based on fine-grained process data. This research employed Chi-squared tests and epistemic network analysis (ENA) to reveal the different frequencies and patterns of these factors in 4 high- and 4 low-performing groups. The data were derived from a 90-minute argumentation task involving 55 undergraduates. The Chi-squared test revealed the frequency differences, indicating that high-performing groups tended to use strong claims, whereas low-performing groups typically used weak counterclaims/rebuttals and encountered more socioemotional challenges. The ENA results further illustrated the differences in the co-occurrences of these factors. In low-performing groups, weak counterclaims/rebuttals intertwined with socioemotional and cognitive challenges. Although students attempted to use socioemotional regulations to address challenges, their efforts were ineffective due to the tense atmosphere. Conversely, high-performing groups successfully alternated between cognitive and socioemotional regulations to formulate strong claims and overcome challenges. These findings highlight the advantages of using ENA to analyze and compare patterns of factors and suggest the need to design educational tools to support effective social regulations.