2026 ASEE Annual Conference & Exposition

This evidence-based practice paper examines the rapid growth of generative artificial intelligence (GenAI) and presents both the opportunities and challenges it poses for engineering education. Faculty and staff must learn not only how to integrate these tools into their professional roles but also how to guide students toward the ethical and practical use of these tools in the classroom. To address this need, the Swanson School of Engineering launched a summer workshop series designed to build GenAI literacy among educators and staff. Across seven distinct workshops, we engaged 67 unique participants, many of whom attended multiple sessions, in topics ranging from introductory AI concepts to advanced pedagogical and assessment strategies.

The workshop series emphasized two parallel goals: (1) equipping faculty and staff with GenAI skills that enhance efficiency in their own academic and administrative work, and (2) empowering educators to design learning experiences and assessments that responsibly incorporate or safeguard against GenAI. Sessions included Generative AI for the Absolute Beginner, Task Automation with Generative AI (one workshop for staff and one for faculty), Prevention, Not Policing: Redesigning Assessments to Minimize AI Misuse, Coaching Critical Thinkers: Moving Beyond AI-Proofing to AI-Guided Learning, GenAI Prompt Engineering, and Advanced Applications for Faculty. Materials and prompt banks were shared following each session to encourage continued experimentation and adoption.

Evaluation occurred through post-workshop surveys and ongoing “boomerang” surveys that examine how participants have applied GenAI since the workshops. Preliminary findings suggest that participants are utilizing GenAI to streamline course preparation, automate repetitive tasks, and redesign assessments to enhance authenticity and integrity. Faculty also reported increased confidence in discussing responsible AI use with students.

This paper will present the rationale for the workshop series, highlight key content and assessment results from two iterations of delivery, and share recommendations for other institutions seeking to develop faculty and staff capacity in GenAI. In a traditional style conference talk, we argue that such efforts are essential for advancing both professional practice and technological literacy in engineering education, while also preparing students for a future where GenAI will be integral to engineering practice.