Joyner, D. A., Bernstein, L., Dittamo, M., Engelman, B., Naran, A., Ott, A., Suh, J. & Thien, A. (2020). Attitudinal Trajectories in an Online CS1 Class: Demographic and Performance Trends. In Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education.
Abstract: In this research, we investigate the trajectory of attitudinal change towards computer science among students in an online CS1 class. We perform this investigation to address several trends in modern computer science education. First, as computer science increasingly becomes a required class for all majors, how do students’ first experiences with the subject impact their attitudes? Second , as online education continues to expand, how does enrolling in CS1 online specifically affect audiences that may be marginalized in both CS classes and in online learning environments, such as women and underrepresented minorities? Third, can we intervene to improve attitudes towards computer science, especially among those marginalized audiences? In this research, we poll students in an online for for-credit CS1 class four times to observe the change in their attitudes towards computer science over time and intervene with some students to try to improve their perception of computer science. We find that attitudes towards computer science improve with initial exposure, that women’s attitudes towards CS begin less positive but follow the same trajectory, and that mid mid-semester regression in attitudes toward computer science may predict eventual struggles to perform well in the class.