The "AI Quick Bytes" series offers practical guidance for faculty on effectively integrating AI into teaching and learning. The videos cover two key approaches: leveraging AI as a collaborative tool for students in activities like peer review and strategically designing AI-resistant assessments that foster deeper human engagement and critical thinking. Faculty will learn concrete strategies for promoting critical AI literacy in the classroom while designing assessments that are genuinely worth doing.
Spring 2025
Integrating AI (NotebookLM) into Revision and Peer Review Workshops
Richard Hunt, Lecturer, University Writing Program
In this presentation, Richard Hunt discusses integrating AI (NotebookLM) into revision and peer review workshops, emphasizing the need for a critical AI literacy framework. Hunt presents AI as a tutor or collaborator and outlines models for its use, particularly one where the AI is grounded in assignment materials (rubric and prompt). He notes that while AI feedback doesn't match an experienced teacher's, it can be on par with or better than standard peer review by breaking down social barriers among students. The core goal is teaching students how and when to use AI effectively.
Designing AI-Resistant Assessments: 10 Strategies for Deeper Human Engagement
Karthikeyan Chandrasegaran, Assistant Professor, Entomology
In this presentation, Professor Kathikeyan Chandrasegaran offers 10 strategies for designing AI-resistant assignments to deepen human engagement and elevate learning experiences. Rather than restricting AI, the approach encourages educators to design assessments that reward originality, curiosity, and reflective thinking. The strategies focus on making assignments personal (drawing on lived experience) , requiring reflection on sources , reframing questions creatively , and using real-world data and critique. The goal isn't just to be "AI-proof," but to create assessments genuinely worth doing that demand deep thought and meaningful engagement from students.