Designing Assignments that AI can’t Solve: Strategies for Educators

In this session, participants will explore strategies for designing AI-resistant assignments. These assignments are carefully crafted to significantly reduce, and in some cases entirely prevent, students from using AI tools to earn high grades without genuine effort. By minimizing the potential for AI to complete tasks on behalf of students, these approaches ensure that academic integrity is upheld. Furthermore, they alleviate the need for instructors to act as "AI investigators," removing the burden of determining whether AI was involved in the completion of student work.

Instructor: Ashley Evans

Tuesday, 6 January 2026
02:30 pm - 04:30 pm (EST)

Objectives

By the end of this session, participants will be able to:

• Identify characteristics of assignments that are most vulnerable to AI-generated responses;
• Apply practical strategies to redesign existing assignments so they better measure authentic student understanding;
• Create an action plan for adapting at least one of their own assignments to reduce the risk of AI misuse.

Audience

Faculty, librarians, teaching and learning staff, or anyone interested in curriculum design strategies involving the use (or disuse) of AI in the classroom.

Please bring one assignment you currently use that could be easily completed by AI.

Agenda

02:30: Lecture and Discussion: Strategies for writing assessments that make them more resilient to AI use by students.

03:00: Hands-On Activity: Participants review a provided assignment and apply redesign strategies.

03:30: Group Sharing: Discuss revised assignment ideas and provide peer feedback.

04:00: Reflection & Takeaway: Each participant drafts a short “next step” plan for implementing at least one redesigned assignment in their own teaching context.