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Abstract Title: Social network analysis of student collaboration in pandemic-affected courses
Abstract Type: Contributed Poster Presentation
Abstract: Social network analysis (SNA) has been gaining traction as a technique for quantitatively studying student collaboration. We analyze networks in two courses from the University of Colorado Boulder and one course from the Colorado School of Mines. All three courses occurred during the COVID-19 pandemic, which allows for a comparison between courses in a variety of formats (i.e., in-person, remote, or hybrid). We compute nodal centrality measures and calculate the correlation between student centrality and performance. Results varied widely between each of the courses studied which suggests that the context and environment in which the course is situated has an important effect on the link between student collaboration and performance. Additionally, we investigated the effect of missing nodes on the correlations we measured, which showed that missing nodes tend to shift correlations towards zero, suggesting that the statistically significant correlations measured in our networks are not spurious.
Session Time: Poster Session 3
Poster Number: III-62

Author/Organizer Information

Primary Contact: Nate Crossette
University of Colorado Boulder
and Co-Presenter(s)
Bethany Wilcox, University of Colorado Boulder