Minneapolis, MN
August 23, 2022
June 26, 2022
June 29, 2022
18
10.18260/1-2--41162
https://peer.asee.org/41162
398
Ashish Hingle (he/his/him) is a Ph.D. student in the College of Engineering & Computing at George Mason University. His research interests include technology ethics, information systems, and student efficacy challenges in higher education.
This Research-to-Practice paper presents a study of the use of concept maps for assessing engineering students’ representation and identification of ethical dilemmas. The concept maps were implemented in the context of role-play case studies in a class on technology ethics. Due to the ubiquitous nature of technological applications in the field of engineering, it is important to teach students how to identify and address ethical dilemmas that might emerge through algorithms embedded in different systems. To understand how technology operates, students must explore the context around their implementation and understand the perspective of all stakeholders involved. Role-play scenarios (RPSs) are one pedagogical technique for students to explore nuanced topics and gain a situated perspective. For this study, we implemented RPSs, and data were collected from 56 undergraduate students during the Fall 2020 semester. Students were introduced to the case through a set of resources, including videos, publications, and news articles, and they created a pre-role-play scenario concept map. After participating in the role-play scenario discussions, students completed a post-discussion concept map as a group activity. Analysis of the pre-and-post concept maps shows students were able to identify a greater number of concepts and ethical dilemmas after participating in the role-play scenario. This research reduces some of the barriers to role-play activities being incorporated in the classroom from an assessment perspective.
Hingle, A., & Johri, A. (2022, August), Assessing Engineering Student’s Representation and Identification of Ethical Dilemmas through Concept Maps and Role-Plays Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. 10.18260/1-2--41162
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