  Social network analysis (SNA) has been gaining traction as a technique for
quantitatively studying student collaboration. We analyze networks, constructed
from student self-reports of collaboration on homework assignments, 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 the course at the Colorado
School of Mines (in a fully remote format) with results from a previous
pre-pandemic study of student collaboration at the Colorado School of Mines (in
a hybrid format). We compute nodal centrality measures and calculate the
correlation between student centrality and performance. Results varied widely
between each of the courses studied. The course at the Colorado School of Mines
had strong correlations between many centrality measures and performance which
matched the patterns seen in the pre-pandemic study. The courses at the
University of Colorado Boulder showed weaker correlations, and one course
showed nearly no correlations at all between students' connectivity to their
classmates and their performance. Taken together, the results from the trio of
courses indicate that the context and environment in which the course is
situated play a more important role in fostering a correlation between student
collaboration and course performance than the format (remote, hybrid,
in-person) of the course. Additionally, we conducted a short study on the
effect that missing nodes may have on the correlations calculated from the
measured networks. This investigation showed that missing nodes tend to shift
correlations towards zero, providing evidence that the statistically
significant correlations measured in our networks are not spurious.
