Co-design AI policies with students through open dialogue rather than enforcement and surveillance¶

Strategy · All strategies
Evidence · no claims cited

Description¶

This strategy recommends that instructors move away from enforcement- and surveillance-centered AI policies and instead "explicitly co-design AI policies with students in their classes." Through open dialogue about responsible AI use, preferred policies are collectively negotiated, making expectations explicit. The article argues this may reduce misperceptions about AI use, limit shame-driven concealment, and support use aligned with learning goals, addressing the anticipatory compliance that ambiguity produces.

Design Implications¶

Context¶

Requirements¶

• Instructors must create structured opportunities for open dialogue about responsible AI use with their students
• Policies and expectations must be made explicit and collectively negotiated rather than imposed

Constraints¶

• The article notes students expressed concealment, shame, and identity threats even in settings with highly permissive policies, so co-design alone may not remove these dynamics

Target Learners¶

• undergraduate computing students
• course instructors

Target Learning Goals¶

• responsible and intentional AI use aligned with learning goals
• reduced shame-driven concealment of AI use

Related Strategies¶

• Foster communities of practice for AI governance instead of rigid top-down policies
• Establishing Classroom Norms
• Classroom Norms Co Construction
• Address educator wellbeing structurally: institutional policies and collective responsibility rather than individual enforcement

Examples¶

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Key Sources¶

• Kate Hamilton, Irene Hou, Dev Patel, Sheena Nnam, Hena Patel, and Stephen MacNeil. (2026). “Stuck in a Spiral”: Shame and Guilt as Social Regulators of AI Use in Computing Education. https://arxiv.org/abs/2606.14920