Generative AI in the Classroom: Best Practices in Syllabus Policy and Citation Requirements

Audience Level: 
All
Session Time Slot(s): 
Institutional Level: 
Higher Ed
Streamed: 
Onsite
Special Session: 
Blended
Research
Diversity & Inclusion
Abstract: 

Generative AI in the Classroom: Best Practices in Syllabus Policy and Citation Requirements

One ubiquitous topic today at academic institutions today involves generative AI and how to (or not to) introduce it into the classroom. How might the use of generative AI fuel innovative thought and creativity?

Extended Abstract: 

Generative AI in the Classroom: Best Practices in Syllabus Policy and Citation Requirements

One ubiquitous topic today at academic institutions involves generative artificial intelligence (AI) and how to (or not to) introduce it into the classroom. How might the use of generative AI fuel innovative thought and creativity into any subject area? 

Ensuring academic integrity is at the forefront of this discussion, naturally. We aim to flip the conversation by discussing how to encourage students to take scholarly risks in their learning with the support of generative AI,  to produce unique artifacts based on these explorations, and to gain confidence in and awareness of this new paradigm of learning and curating as they enter an AI-infused workplace. 

In this discovery session, we present our work to date in generative AI in the classroom, specifically, but not limited to, syllabus policy and citation requirements in assignments. Our views in October may be quite different than when this abstract was published, so we will briefly journal our own learning pathway for the months leading up to the conference, accompanied by tips, templates, and samples of our classroom experiments.  We look forward to discussing evolving approaches for incorporating generative AI tools effectively in the classroom with other educators, administrators, and instructional designers!  

Position: 
4
Conference Session: 
Concurrent Session 2
Conference Track: 
Technology and Future Trends
Session Type: 
Discovery Session
Intended Audience: 
Administrators
Design Thinkers
Faculty
Instructional Support
Students
Training Professionals
Technologists
All Attendees
Researchers