Teach the pedagogical rationale behind AI policies rather than only stating rules¶

Strategy · All strategies
Evidence · 1 claim (1 for) · 1 study (1 theoretical), q1 · 0 of 1 report an effect size · 1 claim rests on one study

Description¶

The article recommends that AI policy and educational practice move beyond articulating rules and instead help students understand why the policies exist, including why honest representation of one's own knowledge matters for learning and assessment. The recommendation rests on the finding that students' rationalizations show they are unaware of the implicit social contract in which students are honest about what they know, and that AI use blurs the boundary between student and AI work in ways instructors cannot assess. Making the rationale explicit is offered as a key intervention for higher education.

Design Implications¶

Context¶

Requirements¶

• Instructors and institutions must communicate the learning- and assessment-related reasons behind AI policies, not only the rules themselves.

Constraints¶

• The article notes faculty alone cannot bear the loss of homework assessment capacity, so institutional-level supports are also needed.

Target Learners¶

• undergraduate students in higher education

Target Learning Goals¶

• honest self-representation of knowledge; understanding why AI policies support learning

Claims¶

• Existing generative AI guidance in higher education focuses on policy and academic integrity rather than learning mechanisms [+W]

Related Strategies¶

• Move beyond generic AI policies to method-based ethical policies and process-oriented assessment
• Transition from restrictive AI governance to frameworks that formally integrate operational and epistemic workflow competencies with subject-sensitive guidance
• Design task-sensitive institutional AI policies rather than blanket permitted/prohibited distinctions
• Foster communities of practice for AI governance instead of rigid top-down policies
• Provide explicit pedagogical guidance on effective and ethical GenAI use within specific assessment contexts, beyond prohibitions

Examples¶

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Key Sources¶

• Kim, Jiyoon; Toyama, Kentaro; Kim, Sangmi; Carroll, John. (2026). "It's OK Because...": The Wild West of Student Rationalization of AI Use in Academic Writing. https://arxiv.org/abs/2605.29090. doi:10.48550/arxiv.2605.29090