Provide explicit pedagogical guidance on effective and ethical GenAI use within specific assessment contexts, beyond prohibitions¶

Strategy · All strategies
Evidence · no claims cited

Description¶

Instructors should provide "explicit, pedagogical guidance beyond prohibitions, helping students explore effective and ethical GenAI use within specific assessment contexts." The strategy directs teaching effort towards shifting students away from outsourcing and towards reallocation, tailoring guidance to the demands and permissions of each assessment rather than relying on blanket bans.

Design Implications¶

Context¶

Requirements¶

• Instructor time to design context-specific guidance for each assessment

Constraints¶

• Applies to unsupervised, after-class assessment contexts in higher education as studied

Target Learners¶

• undergraduate students in higher education

Target Learning Goals¶

• effective and ethical GenAI use in assessments; shift from cognitive outsourcing to reallocation

Related Strategies¶

• Genai Literacy And Dialogue Competence Beyond Technical Skills
• Institutional governance should establish practical conditions supporting AI literacy, learner agency, and critical evaluation rather than relying on prohibition and detection
• Transition from restrictive AI governance to frameworks that formally integrate operational and epistemic workflow competencies with subject-sensitive guidance
• Teach the pedagogical rationale behind AI policies rather than only stating rules
• Institutions should respond to generative AI in education with guided critical engagement rather than prohibition
• Move beyond permit-or-restrict GenAI policies toward policies that clarify appropriate use, support equitable access, and extend rather than replace independent reasoning
• Build ethical AI integration on four coordinated levels: faculty professional development, ethics curricula, clear institutional guidelines, and interdisciplinary updating

Examples¶

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Key Sources¶

• Yan, W., Cui, Y., Chiu, T. K. F., Nakajima, T., & Kozima, H. (2026). From cognitive outsourcing to reallocation: A 3P analysis of student–generative AI engagement in unsupervised assessments. Australasian Journal of Educational Technology, 42(3), 41–61. https://doi.org/10.14742/ajet.11725