AI, Ethics, and Education
Project Description
The School of Engineering Education and the School of Applied and Creative Computing at Purdue seek a postdoctoral fellow to identify aspects of the hidden curriculum in the use of generative AI in undergraduate education. Positive aspects of the hidden curriculum may include undergraduate students’ self-regulated learning skills and ethical digital literacy when using generative AI. Negative aspects of the hidden curriculum when using generative AI may include over-reliance on AI and passive learning, and experiencing negative emotions like shame. This project will involve mixed-methods approaches, including the use of surveys, interviews, and think-aloud to investigate student understandings and perceptions of technical/disciplinary knowledge (e.g., AI algorithms and techniques) and associated social and ethical considerations. One central objective of this research is to develop new instructional materials, initiatives, and strategies that improve students’ hidden curriculum associated with generative AI in terms of conceptual understanding of machine learning techniques while also increasing awareness of how such technologies shape and are shaped by the social contexts where they are developed and used. The fellow will have opportunities to relate research to instructional practice by helping to pilot and assess educational interventions, while engaging with the broader policy and outreach dimensions of this topic through the National Institute for Engineering Ethics (NIEE).
Start Date
Spring 2025 or later
Postdoc Qualifications
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Minimum Qualifications: 1) Ph.D. in Computer Science, Computer Engineering, Engineering or Computing Education, Learning Sciences, or closely related field, 2) programming expertise and ability to learn data science and machine learning skills, 3) familiarity or interest in the societal and ethical implications of AI, and 4) strong interest in discipline-based education research. |
Co-advisors
Alejandra Magana, Ph.D., Professor, School of Applied and Creative Computing, E-mail: admagana@purdue.edu
Bibliography
Howland, S. J., Kim, D., & Jesiek, B. K. (2022). Senior engineering students’ reflection on their learning of ethics and morality: A qualitative investigation of influences and lessons learned. International Journal of Ethics Education, 7: 171-199. DOI: 10.1007/s40889-022-00139-5
Magana, A. J., Mubarrat, S. T., Kao, D., and Benes, B. (2024). AI-based automatic detection of online teamwork engagement in higher education. IEEE Transactions on Learning Technologies. 17: 2091-2106. https://doi.org/10.1109/TLT.2024.3456447
Sirnoorkar, A., Zollman, D., Laverty, J. T., Magana, A. J., Rebello, S., & Bryan, L. A. (2024). Student and AI responses to physics problems examined through the lenses of sensemaking and mechanistic reasoning. Computers & Education: Artificial Intelligence, 7. DOI: 10.1016/j.caeai.2024.100318
Wiese, L., Schiff, D., Magana, A.J., & Patil, I.D. (2025). AI ethics education: A systematic literature review. Computers & Education: Artificial Intelligence, 8. DOI: 10.1016/j.caeai.2025.100405