Individual AI Competencies
Original work: "Educators' guide to multimodal learning and Generative AI" — Tünde Varga-Atkins, Samuel Saunders, et al. (2024/25) — CC BY-NC 4.0
Adapted for UK Nursing Education by: Lincoln Gombedza, RN (LD)
Last Updated: December 2025
AI literacy is not just about using tools—it's about developing critical competencies that enable safe, effective, and ethical integration of AI into nursing practice. This page outlines the core competencies every nursing student should develop.
📐 AI Literacy Framework for Nursing
1. Foundation Level
Understanding AI
- Recognize different types of AI
- Identify capabilities & limitations
- Understand training data & bias
2. Intermediate Level
Critical Evaluation
- Evaluate outputs for accuracy
- Identify bias & errors
- Compare with evidence-base
3. Advanced Level
Ethical Integration
- Apply ethical frameworks
- Maintain confidentiality
- Advocate for responsible use
🧠 Core Competency Domains
💻 Technical
Skills: Prompt crafting, tool navigation, troubleshooting.
Nursing Use: Creating care plans, simulations, and study resources.
📚 Info Literacy
Skills: Source verification, evidence checking, citing AI.
Nursing Use: Always verify against NICE/Cochrane. AI is a starting point, not an endpoint.
🤔 Critical Thinking
Skills: Questioning assumptions, detecting hallucinations, logic checks.
Nursing Use: Applying clinical judgement independently of AI suggestions.
⚖️ Ethical Awareness
Skills: Privacy, GDPR, academic integrity, bias mitigation.
Nursing Use: Never input patient data. Uphold the NMC Code at all times.
💬 Communication
Skills: Explaining AI to others, transparent disclosure, collaboration.
Nursing Use: Reassuring patients about AI tools and training colleagues.
🎓 Competency Development Pathway
Select a year to see the progression logic:
- Year 1: Foundation
- Year 2: Integration
- Year 3: Mastery
Learning Outcomes
- Understand basic AI concepts & limitations
- Use AI tools safely protecting patient data
- Practice ethical use & academic integrity
Key Activities
- Workshops: Introduction to AI literacy
- Exploration: Guided prompt engineering exercises
- Ethics: Case discussions on privacy and bias
Assessment
- AI knowledge quiz
- Basic prompt crafting exercise
- Reflective portfolio entry on "My First AI Interaction"
Learning Outcomes
- Apply AI to nursing scenarios & care planning
- Evaluate clinical relevance & accuracy
- Integrate AI results with evidence-based practice
- Care Planning: AI-enhanced care plan drafting (critiqued)
- Simulation: Clinical scenario analysis
- Creation: Developing patient education materials
Assistive Technology: Use voice-to-text AI to support communication for people with physical disabilities. Task: Evaluate if the AI accurately interprets non-standard speech patterns.
Assessment
- Critical appraisal of an AI-generated care plan
- Evidence-based practice assignment (comparing AI vs NICE)
- Peer teaching session
Learning Outcomes
- Demonstrate advanced AI literacy & leadership
- Mentor peers in safe AI use
- contribute to policy & advocacy
Key Activities
- Complex Support: Using AI for complex decision support (with critique)
- QI Projects: Quality improvement initiatives using AI
- Mentoring: Guiding junior students
Assessment
- Advanced clinical scenario management
- Leadership project or policy contribution
- Capstone portfolio showcasing AI fluency
✅ Interactive Checkist
Track your progress against the core competencies:
Foundation Level: Understanding AI
Intermediate Level: Critical Evaluation
Advanced Level: Ethical Integration
🔗 Development Resources
Self-Directed Learning
- Online AI literacy courses
- Nursing informatics resources
- Professional body guidance (RCN/NMC)
Institutional Support
- Workshops and mentoring programmes
- Communities of practice (Join our GitHub Discussions!)
Continuous Learning
- Stay current with AI developments (it moves fast!)
- Regular Review: Self-assess competencies annually
Next: Explore Module Integration to see how these competencies are developed through curriculum.