The omnipresence of software systems across all aspects of society has necessitated that future technology professionals are aware of ethical concerns raised by the design and development of software and are trained to minimize harm by undertaking responsible engineering. This need has become even more urgent with artificial intelligence (AI) driven software deployment. In this paper we present a study of an interactive pedagogical intervention – role-play case studies – designed to teach undergraduate technology students about ethics with a focus on software systems. Drawing on the situated learning perspective from the Learning Sciences, we created case studies, associated stakeholder roles, discussion scripts, and pre and post discussion assignments to guide students’ learning. Open-ended data was collected from thirty-nine students and analyzed qualitatively. Findings from the study show that by taking on different perspectives on a problem, students were able to identify a range of ethical issues and understand the role of the software system process holistically, taking context, complexity, and trade-offs into account. In their discussion and reflections, students deliberated the role of software in society and the role of humans in automation. The curricula, including case studies, are publicly available for implementation.
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Using Role-Plays to Improve Ethical Understanding of Algorithms Among Computing Students
We present a Research-to-Practice paper where we used role-play case studies to improve student understanding of the ethics of algorithms. As the use of algorithmic decision-making continues to grow across areas of society, there is a need to prepare future technology workforce for ethical thinking related. Our work was informed by the situated learning paradigm, and our goal was to improve perspectival thinking among students. Recognizing an issue from multiple perspectives and taking on different perspectives to examine it leads to increased understanding. Drawing on this work, we created and implemented a role-play case study in an undergraduate computing data mining course. The role-play case study focused on the use of algorithms for facial recognition. Data were collected from pre-and post- discussion assignments, and a student survey. Thirty-one students enrolled in the course and completed the ethics module. The data collected in the assignments focused on student's recognition of ethical dilemmas, the change in student's perspective on the case due to creating a collaborative consensus and understanding the complexity of algorithmic decision making. To formally analyze the data, we created a coding schema drawing on the literature and preliminary qualitative analysis of our data. The data were independently coded by multiple coders. The findings indicate that through their participation in collaborative role-play scenarios, students were able to recognize a wide range of issues and offer potential solutions. We discuss the implications of the work. Curriculum material created as part of this work is available as an open education resource.
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- Award ID(s):
- 1937950
- PAR ID:
- 10314609
- Date Published:
- Journal Name:
- Frontiers of Education
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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