Self-Disclosure and Beyond: Takeaways from an Online and In-Person Computing Ethics Course

We evaluate the amount and nature of self-disclosure in two versions of a 400-level computing ethics course focusing on discrimination and surveillance. The study involved 30 participants enrolled in two identical course offerings, taught by the same pair of instructors, but delivered in different formats: online versus in-person. Our analysis concentrated on the extent and contents of self-disclosure by both students and instructors. By using both quantitative and qualitative methods, we observed a higher prevalence of self-disclosure by both students and instructors in the online section. Notably, an analysis of demographic data revealed that minority group members were particularly active in self-disclosure in both formats. Overall, our findings suggest that an online setting may be more effective for delivering computing ethics courses where a primary goal is increasing open discussion and self-disclosure among participants.

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Publication Details

Published
2025-02-18
DOI
https://doi.org/10.1145/3641555.3705248
Primary Topic
Ethics and Social Impacts of AI
Type
article
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article

Self-Disclosure and Beyond: Takeaways from an Online and In-Person Computing Ethics Course

Helen Chen, Maura R. Grossman, Daniel G. Brown
Ethics and Social Impacts of AI
article

Self-Disclosure and Beyond: Takeaways from an Online and In-Person Computing Ethics Course

Helen Chen, Maura R. Grossman, Daniel G. Brown
article en

Abstract

We evaluate the amount and nature of self-disclosure in two versions of a 400-level computing ethics course focusing on discrimination and surveillance. The study involved 30 participants enrolled in two identical course offerings, taught by the same pair of instructors, but delivered in different formats: online versus in-person. Our analysis concentrated on the extent and contents of self-disclosure by both students and instructors. By using both quantitative and qualitative methods, we observed a higher prevalence of self-disclosure by both students and instructors in the online section. Notably, an analysis of demographic data revealed that minority group members were particularly active in self-disclosure in both formats. Overall, our findings suggest that an online setting may be more effective for delivering computing ethics courses where a primary goal is increasing open discussion and self-disclosure among participants.

University of Waterloo (CA)
Openalex Percentile: Top 97%
Ethics and Social Impacts of AI
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