2026 ASEE Annual Conference & Exposition

Introduction
There is increasing emphasis on the need for tightly integrated technical, social, and ethical training, particularly in areas with profound societal impact such as AI. However whether social and ethical content integrated into a technical class infringes on technical learning remains unclear. In an undergraduate course on Computational Biomedical Engineering, this study examined whether partially replacing technical AI content with social-ethical AI content affects student engagement and technical learning . The hypothesis was that due to redistribution in class time, incorporating social and ethical topics would increase engagement but reduce technical learning outcomes.

Methods
A computational biomedical engineering course was taught in 2023 and 2024 with comparable student cohorts and the same instructor. In 2024, approximately 25% of class time was allocated to social and ethical topics, replacing equivalent technical content. These sessions involved engaging with AI-related readings and artworks and having students write opinion papers and short reflections connecting the material to biomedical engineering. Quantitative and qualitative data were collected through pre- and post-course surveys assessing student interest in engineering, biology, and medicine, as well as performance on problem-solving questions identical across years. Additional data sources included short essays, written reflections on ethical AI, and course evaluations.

Results
The hypothesis that increased proportion of time spent on social and ethical topics would reduce technical learning was not supported. Students in the 2024 cohort demonstrated comparable pre-to-post course gains in performance to those in 2023, despite reduced time on technical content. In 2024, average test scores increased from 40% pre-course to 95% post-course, exceeding the 2023 post-course average of 87%, suggesting that inclusion of STS material did not diminish technical learning. Student interest levels also remained high or improved: the proportion of students who strongly agreed with the statements “I am interested in engineering,” “I am interested in biology,” or “I am interested in medicine” rose from 60% to 72% , 53% to 72% , and 53% to 72% in 2023 vs. 2024 , respectively. Surveys and written reflections further indicated increased engagement and greater awareness of AI’s role in society.

Conclusion
Incorporating social and ethical perspectives into computational coursework can strengthen engagement without diminishing technical mastery. These findings suggest that balanced pedagogical approaches—combining technical skills with reflection on ethical