Develop student AI literacy and institutional GenAI policies, guidelines and safeguards for responsible integration¶

Strategy · All strategies
Evidence · 2 claims (2 for) · 2 studies (1 associational, 1 design), q2 · 0 of 2 report an effect size · 2 claims rest on one study

Description¶

The article recommends that institutions develop policies and formal guidance on GenAI use while building students' AI literacy. Students themselves asked that "A well-balanced usage guideline needs to be in place so that the benefits of the tech can be leveraged." Suggested actions include educational resources and workshops on GenAI's ethical and societal implications, prioritizing transparency, accuracy and privacy in tool development, and rethinking curricula to emphasize critical thinking, creativity, digital literacy and AI ethics.

Design Implications¶

Context¶

Requirements¶

• Institutional commitment to policy development, workshops and curriculum revision; technical staff able to work on explainable AI models and data protection practices

Constraints¶

• Grounded in student perceptions from one cross-sectional survey; the study did not examine actual impact of GenAI on learning outcomes

Target Learners¶

• undergraduate and postgraduate university students

Target Learning Goals¶

• AI literacy, responsible and ethical use of GenAI, critical evaluation of AI-generated content

Claims¶

• Students most often urge institutions to teach responsible AI use (N=41) and provide clear rules and guidelines (N=27) [+W]
• Most higher education institutions report faculty use of generative AI in teaching, but fewer than 15% have formal ethical guidelines [+W]

Related Strategies¶

• 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
• Build ethical AI integration on four coordinated levels: faculty professional development, ethics curricula, clear institutional guidelines, and interdisciplinary updating
• Ground AI integration in higher education on core principles of human agency, academic freedom, transparency, ethics, inclusivity, and critical thinking
• Institutions should respond to generative AI in education with guided critical engagement rather than prohibition
• Provide accessible guidelines, training materials, or workshops to help students understand responsible GenAI use
• Foster communities of practice for AI governance instead of rigid top-down policies
• Higher education leaders should develop more inclusive and future-oriented GenAI policies integrating social equity, interdisciplinary experimentation, and sustainability considerations
• Provide institutional support: regular GenAI workshops, subsidized access to advanced tools, reliable resources, and curriculum inclusion

Examples¶

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Key Sources¶

• Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20:43. https://doi.org/10.1186/s41239-023-00411-8