This content was published: September 8, 2025. Phone numbers, email addresses, and other information may have changed.
AI-Proofing Your Assignments: Designing for Authentic Learning in the Age of Generative AI
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Presenter: Debbie Austin
Summary
In this presentation, Debbie Austin shares practical approaches to navigating generative AI in higher education by moving away from detection tools and focusing on authentic assignment design. Rather than attempting to act as “AI police” or relying on inconsistent detection software, educators can create meaningful assessments that emphasize human strengths, critical thinking, and the journey of learning.
The session highlights key techniques for making assignments resistant to AI misuse, such as using multi-step and iterative projects, requiring personal reflections and artifacts, integrating multi-modal deliverables, and connecting course topics to real-world or localized contexts. Additionally, Austin discusses how teaching students ethical AI practices and communicating transparent expectations helps foster academic integrity and deeper student engagement.
Presentation Outcomes
- Identify course assignments and discussion prompts that are vulnerable to generative AI completion.
- Apply strategies to convert product-focused assignments into process-oriented, authentic learning experiences.
- Incorporate multi-modal, reflective, and localized elements to design AI-resistant assessments.
- Formulate an action plan to incrementally update course assignments and transparently communicate AI expectations to students.
Post generated by CTLE Web Designer Gem on 08/12/2026
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