Generative artificial intelligence (GenAI) and machine learning technologies will have a profound influence on the professional practice of engineering graduates, offering opportunities to increase productivity. Within universities, they are changing our teaching, student learning, and our approaches to research. More generally, they may adversely impact how we think, learn across our lifetimes, communicate, and work together.
We are examining user experiences among students, instructors, and professionals with GenAI tools to identify and understand the potential challenges and opportunities that these tools present for engineering education.
Funded Project:
“Engineering Workforce Transformation Requirements in Response to Artificial Intelligence,” funded by NSERC Discovery Horizons Grant, 2024 to 2029
PI: Susan McCahan
Co-applicants: Elizabeth Dhuey and Cindy Rottmann
Other Projects:
“Challenges and Opportunities: The Educational and Social Impacts of Generative Artificial Intelligence”
PI: Greg Evans
Co-PI: Qin Liu
Representative Publications:
- Liu, Q., Yao, Y., Evans, G., Huang, R., & Jin, K. (2024). Machine intelligence and human intelligence: Exploring the potentials of machine learning based approaches to qualitative survey data analysis. Proceedings of the Canadian Engineering Education Association Conference, Edmonton, AB. https://doi.org/10.24908/pceea.2024.18579
- Kecman, T., & McCahan, S. (2024). Uses of Word Embeddings in Engineering Education. Proceedings of the Canadian Engineering Education Association Conference, Edmonton, AB. https://doi.org/10.24908/pceea.2024.18585