Embed GenAI literacy and ethical use directly in nursing curricula rather than prohibiting it¶

Strategy · All strategies
Evidence · no claims cited

Description¶

Under Theme Three, participants argued GenAI should be addressed deliberately in the curriculum, teaching students to use it "ethically, effectively, and with an awareness of its limitations". Proposed approaches include professional development for staff redesigning units, authentic assessments with added steps before AI use, AI-generated bots for role-play practice of interviews and difficult conversations, and deliberately using inaccurate GenAI outputs to prompt critical evaluation. The article frames this as a shift from reactive adaptation to proactive, values-driven integration.

Design Implications¶

Context¶

Requirements¶

• Deliberate scaffolding within curricula and assessment so students understand both the possibilities and limitations of GenAI.

Constraints¶

• Participants stressed GenAI must not be introduced in ways that weaken clinical judgement, accountability or independent decision-making.

Target Learners¶

• undergraduate nursing students
• nursing academics

Target Learning Goals¶

• ethical and transparent GenAI use
• critical evaluation of AI-generated information
• responsible digital practice

Related Strategies¶

• Fund AI literacy initiatives integrating AI ethics into curricula and adapting assessments
• Integrate AI into nursing curricula through AI-supported case discussions, structured clinical learning activities, and AI literacy training tailored to user groups
• Institutions should respond to generative AI in education with guided critical engagement rather than prohibition
• Integrate AI literacy into health sciences curricula and tailor career counselling to programme type
• Build ethical AI integration on four coordinated levels: faculty professional development, ethics curricula, clear institutional guidelines, and interdisciplinary updating
• Embed AI literacy across disciplines by identifying intersections with existing content and using case studies, interdisciplinary modules, and collaborative projects
• Create dialogic spaces where students and educators negotiate GenAI dilemmas together
• Incorporate collaborative learning activities within AI literacy teaching, attending to activity modality and integration with other activities and assessments
• Shift from punitive detection to proactive educative approaches, co-created detailed guidelines, and assessment designs GenAI cannot do well
• Embed ethical inquiry into AI-supported instruction by having learners compare AI-generated texts with peer-reviewed sources
• Rethink the music curriculum around DAW literacy, AI literacy, rights and economics knowledge, and defended ensemble practice
• Incorporate AI literacy into educational-leadership preparation curricula
• Embed structured AI literacy in business curricula: teach verification, comparison, and transparent AI-use declarations rather than restricting or unrestrictedly encouraging GenAI
• Cultivate learners' critical AI literacy and integrity-focused group practices for GenAI-supported group work
• Embed GenAI into existing pedagogical strategies instead of undertaking full curriculum redesign
• Design authentic, scaffolded activities that convert students' intuitive GenAI concerns into explicit ethical competencies
• Provide explicit instruction in AI prompting and information verification alongside AI integration in laboratory courses

Examples¶

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Key Sources¶

• Dabkowski, Elissa; Missen, Karen; Allen, Louise; Whitehead, Dean; Worn, Ryan. (2026). 'Co-pilot won't teach you to be a nurse': nursing academics' perspectives on GenAI use in undergraduate education. International Journal for Educational Integrity. https://doi.org/10.1007/s40979-026-00220-2