The integration of artificial intelligence (AI) into undergraduate engineering education is increasingly critical for preparing students for the evolving demands of the workforce. However, universities face challenges in effectively embedding AI concepts into interdisciplinary curricula. This work-in-progress study analyzes AI-infused undergraduate engineering programs at four Canadian universities, focusing on curriculum structure, learning outcomes, and student engagement with AI concepts.
Using the TASKS framework (Task, Affect, Skills, Knowledge, Stress), this study examines how AI is introduced within core and elective engineering courses, evaluating the extent to which students develop technical proficiency, problem-solving abilities, and adaptability to AI-driven technologies. The framework aims to enhance students' technical competencies while ensuring alignment with the Canadian Engineering Accreditation Board (CEAB) standards. In addition, the study highlights institutional efforts in AI integration, including faculty development initiatives and support structures that facilitate student learning.
Findings from this study contribute to the broader discussion on best practices for AI education in engineering, offering insights into curriculum design, accreditation considerations, and the student experience. By identifying gaps and opportunities in AI curriculum implementation, this research provides actionable recommendations to enhance AI literacy and workforce readiness among engineering graduates towards Industry 5.0.
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