The Relationship Between COVID-19 Severity and Computer Science MOOC Learner Achievement: A Preliminary Analysis.

Online education, and MOOCs in particular, experienced a dramatic rise during the COVID-19 lockdown. Many had extra time to start learning new topics, while a significant fraction of the population experienced disruptions in areas such as healthcare, childcare, and potential loss of livelihood, among others. In this work we analyze learner data from multiple instances of two introductory Python MOOCs, offered before and during the COVID-19 pandemic, to understand how the pandemic affected learner progress and outcomes in these courses. We explore multiple measures of COVID-19 severity, and find a strong correlation between a measure of severity and relative change in certification rate. Specifically, we find that the change in certification rate relative to pre-pandemic baselines showed a negative correlation as COVID-19 severity increased.