2025 ASEE Annual Conference & Exposition

Work in Progress: STEMtelling as a Method towards Ethical Awareness in Machine Learning

Presented at Engineering Ethics Division (ETHICS) Technical Session - Ethics in ML/AI

The recent surge in artificial intelligence (AI) developments has been met with an increase in attention towards incorporating ethical engagement in machine learning discourse and development. This attention is noticeable within engineering education, where comprehensive ethics curricula are typically absent in engineering programs that train future engineers to develop AI technologies. Artificial intelligence technologies operate as black boxes, presenting both developers and users with a certain level of obscurity concerning their decision-making processes and a diminished potential for negotiating with its outputs. The implementation of collaborative and reflective learning has the potential to engage students with facets of ethical awareness that go along with algorithmic decision making – such as bias, security, transparency and other ethical and moral dilemmas. However, there are few studies that examine how students learn AI ethics in electrical and computer engineering courses. This paper explores the integration of STEMtelling, a pedagogical storytelling method/sensibility, into an undergraduate machine learning course. STEMtelling is a novel approach that invites participants (STEMtellers) to center their own interests and experiences through writing and sharing engineering stories (STEMtells) that are connected to course objectives. Employing a case study approach grounded in activity theory, we explore how students learn ethical awareness that is intrinsic to being an engineer. During the STEMtelling process, STEMtellers blur the boundaries between social and technical knowledge to place themselves at the center of knowledge production. In this WIP, we discuss algorithmic awareness, as one of the themes identified as a practice in developing ethical awareness of AI through STEMtelling. Findings from this study will be incorporated into the development of STEMtelling and address challenges of integrating ethics and the social perception of AI and machine learning courses.

Authors

Dr. Jenny Tilsen http://orcid.org/https://0000-0003-4301-3592 Bucknell University [biography]

Dr. Jenny Tilsen is a postdoctoral researcher in the Electrical and Computer Engineering Department at Bucknell University. She is an interdisciplinary scholar with a background in Science and Technology Studies (STS) and STEM Education. Her research and teaching interests examine methods and theories that take place across institutional and disciplinary boarders within practices of participatory knowledge, the narrative construction of science and technology, science communication, and public pedagogies of technoscience.
Prof. Robert M Nickel Bucknell University [biography]

Robert M. Nickel received a Dipl.-Ing. degree in electrical engineering from the RWTH Aachen University, Germany, in 1994, and a Ph.D. in electrical engineering from the University of Michigan, Ann Arbor, Michigan, in 2001. During the 2001/2002 academic y
Dr. Stewart Thomas http://orcid.org/0000-0002-5554-1475 Bucknell University [biography]

Stewart J. Thomas received the B.S. and M.Eng. in Electrical Engineering from the University of Louisville in Louisville, Kentucky in 2006 and 2008, respectively, and the Ph.D. in Electrical and Computer Engineering from Duke University in Durham, North Carolina in 2013. He has served on the organizing committee for the IEEE International Conference on RFID series since 2014, serving as the Executive Chair in 2022, with research interests in areas of low-power backscatter communications systems and IoT devices. He is also interested in capabilities-based frameworks for supporting engineering education. He is currently an Assistant Professor at Bucknell University in the Electrical and Computer Engineering Department, Lewisburg, PA USA.
Sarah Appelhans http://orcid.org/0000-0002-7313-3504 Lafayette College [biography]

Sarah Appelhans is an Assistant Professor of Engineering Studies at Lafayette College. She earned her PhD in Cultural Anthropology at the University at Albany (SUNY) where she conducted research on the cultural factors that contribute to inequalities in engineering. As a postdoc at Bucknell University, she was the resident ethnographer in the Electrical and Computer Engineering Department, exploring applications of Amartya Sen’s capabilities approach in engineering education. Her current book project, On the Bleeding Edge: Gender, Immigration and Precarity in Semiconductor Engineering, investigates the intersections of gender, race/ethnicity, and immigration status among semiconductor engineers.
Dr. Alan Cheville Bucknell University [biography]

Alan Cheville studied optoelectronics and ultrafast optics at Rice University, followed by 14 years as a faculty member at Oklahoma State University working on terahertz frequencies and engineering education. While at Oklahoma State, he developed courses

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 22, 2025, and to all visitors after the conference ends on June 25, 2025

« View session

For those interested in:

Advocacy and Policy
computer science
engineering technology
undergraduate
Broadening Participation in Engineering and Engineering Technology
engineering