Publications
Do Embedded Ethics Modules Have Impact Beyond the Classroom? (SIGCSE '24)
Embedded ethics education integrates ethical considerations into computer sciences courses in support of ethics-informed design, development, and deployment of technology. Scholarly assessment has demonstrated that such modules can influence students' attitudes about the relevance and importance of ethics to their work, as well as their perceived ability to tackle ethical issues in the workplace. In this paper, we report on a study that investigates whether embedded ethics modules have an impact beyond the classroom. Specifically, we examine whether embedded ethics modules influence students to learn more about ethics on their own, whether students are better able to recognize ethical issues when they enter the workplace for an industrial or research work experience, and whether they report that the modules they participated in helped them to navigate the ethical situations they encountered at work. While further assessment is needed to investigate these questions fully, our results suggest that embedded ethics modules can indeed have this kind of positive impact beyond the classroom.
Diane Horton, David Liu, Sheila A. McIlraith, Steven Coyne, and Nina Wang. 2024. Do Embedded Ethics Modules Have Impact Beyond the Classroom? In Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1 (SIGCSE 2024). Association for Computing Machinery, New York, NY, USA, 533–539. https://doi.org/10.1145/3626252.3630834
Embedded Ethics: Pandemic Exposure Notification Systems and Giving Ethical Justifications
Maryam Majedi, Emma McClure, Benjamin Wald, Diane Horton, and Sheila A. McIlraith. November 2023. Embedded Ethics: Pan- demic Exposure Notification Systems and Giving Ethical Justifica- tions. In ACM EngageCSEdu. ACM, New York, NY, USA, 4 pages.
Embedded Ethics: Pandemic Contact Tracing and Ethical Trade-offs
Maryam Majedi, Emma McClure, Benjamin Wald, Diane Horton, and Sheila A. McIlraith. November 2023. Embedded Ethics: Pan- demic Contact Tracing and Ethical Trade-offs. In ACM EngageCSEdu. ACM, New York, NY, USA, 4 pages.
Is More Better When Embedding Ethics in CS Courses? (SIGCSE '23)
Embedding ethics modules in computer science (CS) courses is an approach to post-secondary ethics education that has been gaining traction. In contrast to dedicated courses on ethics in CS, embed- ding ethics modules into CS courses supports tight connections between ethical considerations and CS concepts, as well as enabling repeated exposure to ethics across multiple courses. Initial studies of the effectiveness of such modules suggest that this approach can increase both student interest in ethics and technology, and student self-efficacy towards incorporating ethical considerations in their computing work. Departments wishing to deploy embedded ethics (EE) modules need to decide how to invest resources, including class time, to maximize effectiveness while maintaining curriculum objectives. Such considerations include the number of EE module experiences a student has throughout their degree program, as well as the spacing of those experiences.
Research to date has focused on the effect of a single embedded ethics module. In this paper, we report on a study examining the impact of experiencing EE modules in multiple courses. Among our findings, our results suggest that more is not necessarily better — that a modest number of periodic exposures to EE modules over the course of a degree program may be sufficient to achieve sustained positive attitudes and self-efficacy among students. While a picture is beginning to emerge, these results highlight the need for further research on the effectiveness of embedded ethics programs as a whole.
Diane Horton, David Liu, Sheila A. McIlraith, and Nina Wang. 2023. Is More Better When Embedding Ethics in CS Courses?. In Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1 (SIGCSE 2023), March 15–18, 2023, Toronto, ON, Canada. ACM, New York, NY, USA, 7 pages. https://doi.org/10.1145/3545945.3569881
Embedding Ethics in Computer Science Courses: Does it Work? (SIGCSE '22)
Abstract: Technology is shaping the way people live, work, and interact with each other, and graduates of our computer science programs increasingly find themselves designing algorithms and using data that raise ethical issues they may not be aware of or equipped to address. Courses that contemplate the role of technology in society have been a standard, but often optional, part of curricula for years. An emerging alternative is to embed ethical discussions as modules within CS courses. This approach offers the opportunity to tie ethical issues to technical content at the moment students learn it, and to have students engage with these issues repeatedly throughout their degree. However, little is known about the effect of embedded ethics education on students.
We report on a study examining the impact of a pair of ethics modules embedded into a CS2 course. We describe our pedagogical goals and the strategies employed to realize them, as well as our study. We found that students' interest in ethics and technology, and their confidence in identifying, raising, and discussing ethical issues, increased significantly after completing the modules. The study also demonstrated that we achieved our pedagogical goals. These results show that even a modest intervention can have a positive impact. We hope that the articulation of our pedagogical approach and our assessment results will encourage others to embed ethics modules into their courses, to innovate with respect to embedded ethics pedagogy, and to do principled assessment of what is effective in this emerging area of CS education.
Diane Horton, Sheila A. McIlraith, Nina Wang, Maryam Majedi, Emma McClure, and Benjamin Wald. 2022. Embedding Ethics in Computer Science Courses: Does it Work? In Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V. 1 (SIGCSE 2022), March 3–5, 2022, Providence, RI, USA. ACM, New York, NY, USA, 7 pages. https://doi.org/10.1145/3478431.3499407