Engagement and Anonymity in Online Computer Science Course Forums

Abstract

Online discussion boards, designed to facilitate learning from peers and instructors in an accessible space, are a vital part of course design, especially in large scale computer science classes. Previous work has shown that women in computer science tend to use anonymity more often than men on these boards, a trend not found in humanities, social science or business courses. In this work, we build on these findings using an intersectional lens, analyzing both gender and race/ethnicity. We find this combined analysis reveals differences in anonymity that are not apparent when examining gender alone. For example, we find a significantly greater difference in anonymity use between Hispanic men and women than would be expected from analyzing race/ethnicity and gender independently. We additionally analyze type of content (e.g., questions, answers), course, platform, and data source to characterize the many factors at play in measuring students’ choice to participate anonymously. In doing so, we show that different approaches used in prior work for eliciting information on gender — whether using registrar data, a survey, or imputing gender based on name — changes how over of students are classified, particularly affecting nonbinary students and Asian students. Understanding when students participate anonymously can help educators and platform designers to make students’ experience of online discussion boards more welcoming.

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