Impact of Covid-19 Pandemic on Student Participation in an Intro CS MOOC

Abstract

The impact of the COVID pandemic spreads far and wide, encompassing nearly all aspects of society. One important community that has been forced to enter uncharted territory is academia. Although many students and instructors were subjected to new tools such as virtual lectures, one platform that remained unchanged throughout is the MOOC (Massive Open Online Course) platform edX: a platform that enables students around the world to engage in academia through an online, virtual environment. In efforts to analyze the impacts of the pandemic, this thesis will provide a data-driven survey of the landscape of the introductory computer science course, titled 6.00.1x Introduction to Computer Science and Programming, offered on the edX platform. With enrollment ranging from thirty thousand to one hundred thousand students per run, this edX class provides many individuals with their first taste of computer programming. This large enrollment count provides ample amounts of granular data in efforts to survey pre-covid, beginning of covid, and steady-state covid class runs in the 2019, 2020, and 2021 years respectively. We first aim to take a high level overview of the differences and similarities created by the onset of the pandemic. Then, using various tools and techniques, take a deeper dive into specific aspects of student involvement and interaction to gain useful insights. Finally, we will use these findings to promote and support future iterations of the edX class.