Programme-Level AI Literacy Strategy
Attribution
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
A coherent programme-wide strategy ensures AI literacy develops progressively across the nursing curriculum, aligning with NMC proficiencies and preparing graduates for AI-enhanced practice.
Strategic Framework
Vision Statement
Example Vision "To develop nursing graduates who are AI-literate, critically engaged, and ethically grounded professionals capable of integrating AI responsibly into person-centered care while maintaining professional accountability and clinical excellence."
Strategic Objectives
- Competency Development: Ensure all graduates achieve core AI literacy competencies
- Progressive Integration: Build AI literacy systematically across three years
- NMC Alignment: Map AI competencies to NMC proficiencies
- Quality Assurance: Maintain high standards in AI-enhanced education
- Ethical Practice: Embed responsible AI use throughout curriculum
Curriculum Mapping
Year 1: Foundation
Focus: Understanding and Awareness
Core Competencies
- Basic AI concepts and terminology
- Safe and ethical AI tool use
- Critical evaluation of AI outputs
- Privacy and confidentiality
- Academic integrity
Module Integration
- Foundations of Nursing: Introduction to AI in healthcare
- Digital Health: AI tools and platforms overview
- Professional Practice: Ethical frameworks for AI use
- Evidence-Based Practice: Evaluating AI-generated information
Key Activities
- AI literacy workshops
- Guided tool exploration
- Critical analysis exercises
- Ethical case discussions
- Reflective practice
Assessment
- AI knowledge assessment
- Ethical scenario analysis
- Reflective portfolio entries
- Practical demonstrations
Year 2: Application
Focus: Integration and Practice
Core Competencies
- AI-enhanced clinical reasoning
- Evidence-based AI integration
- Professional judgment with AI support
- Collaborative AI use
- Patient-centered AI application
Module Integration
- Care Planning: AI-assisted care plan development
- Pharmacology: AI for medication information (verified)
- Health Promotion: AI-generated patient education
- Clinical Skills: AI simulation and practice
- Research Methods: AI for literature review
Key Activities
- AI-enhanced assignments
- Clinical scenario analysis
- Patient education material creation
- Collaborative projects
- Placement integration
Assessment
- AI-enhanced care plans
- Critical appraisal assignments
- Portfolio development
- Practical assessments
- Peer evaluation
Year 3: Mastery
Focus: Leadership and Innovation
Core Competencies
- Advanced AI integration
- Quality improvement with AI
- Mentoring and teaching
- Policy contribution
- Innovation and research
Module Integration
- Leadership: AI in healthcare management
- Quality Improvement: AI for data analysis
- Dissertation: AI research tools
- Transition to Practice: AI in clinical settings
- Advanced Practice: Specialized AI applications
Key Activities
- Complex clinical scenarios
- Quality improvement projects
- Peer mentoring
- Policy development
- Research projects
Assessment
- Advanced portfolios
- Leadership projects
- Research dissertations
- Capstone assessments
- Professional presentations
NMC Proficiency Mapping
Platform 1: Being an Accountable Professional
AI Literacy Integration
- Understand professional accountability with AI use
- Maintain NMC Code standards
- Practice within scope of competence
- Document AI-assisted decisions
- Advocate for ethical AI use
Evidence
- Ethical AI use in all assessments
- Professional reflection on AI integration
- Disclosure of AI assistance
- Alignment with NMC Code
Platform 2: Promoting Health and Preventing Ill Health
AI Literacy Integration
- Use AI for health promotion materials
- Evaluate AI health information critically
- Adapt AI outputs for diverse populations
- Ensure cultural sensitivity
- Maintain evidence-based practice
Evidence
- AI-generated patient education (verified)
- Health promotion projects
- Cultural adaptation of AI content
- Evidence-based modifications
Platform 3: Assessing Needs and Planning Care
AI Literacy Integration
- AI-assisted holistic assessment
- Evidence-based care planning with AI
- Critical evaluation of AI recommendations
- Person-centered care maintenance
- Clinical judgment primacy
Evidence
- AI-enhanced care plans
- Critical analysis of AI suggestions
- Evidence-based justifications
- Patient-centered modifications
Platform 4: Providing and Evaluating Care
AI Literacy Integration
- AI for clinical decision support
- Evaluation of AI-assisted interventions
- Documentation of AI use
- Quality improvement with AI
- Patient safety prioritization
Evidence
- Clinical practice portfolios
- Quality improvement projects
- Safety incident analysis
- Evaluation reports
Platform 5: Leading and Managing Nursing Care
AI Literacy Integration
- Leadership in AI implementation
- Team education on AI use
- Policy development contribution
- Resource management
- Change management
Evidence
- Leadership projects
- Team teaching sessions
- Policy contributions
- Management portfolios
Platform 6: Improving Safety and Quality of Care
AI Literacy Integration
- AI for quality monitoring
- Error detection and prevention
- Data analysis for improvement
- Evidence-based practice enhancement
- Safety culture promotion
Evidence
- Quality improvement projects
- Safety analyses
- Data-driven reports
- Practice improvements
Platform 7: Coordinating Care
AI Literacy Integration
- AI for care coordination
- Communication enhancement
- Information sharing (safely)
- Multidisciplinary collaboration
- Transition planning
Evidence
- Coordination portfolios
- Communication examples
- Collaborative projects
- Transition plans
Progressive Development Model
Scaffolding Approach
Year 1: Guided Practice
- Structured AI activities
- Clear instructions
- Extensive support
- Frequent feedback
- Close supervision
Year 2: Supported Independence
- More autonomy
- Selective guidance
- Peer collaboration
- Reflective practice
- Mentor support
Year 3: Independent Practice
- Self-directed learning
- Minimal scaffolding
- Leadership opportunities
- Innovation encouraged
- Professional autonomy
Quality Assurance
Programme Monitoring
Key Performance Indicators
- Student AI literacy competency levels
- Assessment performance
- Graduate feedback
- Employer satisfaction
- NMC inspection outcomes
Data Collection
- Pre/post competency assessments
- Module evaluations
- Portfolio reviews
- Graduate surveys
- Employer feedback
Review Cycle
- Annual programme review
- External examiner reports
- Professional body feedback
- Student representation
- Continuous improvement
Standards and Benchmarks
Internal Standards
- All graduates achieve core competencies
- 90%+ pass rate on AI literacy assessments
- Positive student feedback (>80% satisfaction)
- Zero academic misconduct related to undisclosed AI use
- 100% NMC proficiency alignment
External Benchmarks
- Sector-leading AI integration
- Professional body recognition
- Employer satisfaction
- Graduate employability
- Research contributions
Stakeholder Engagement
Students
Involvement
- Programme committee representation
- Feedback mechanisms
- Co-design opportunities
- Peer support networks
- Student-led initiatives
Support
- Clear guidance and policies
- Accessible resources
- Training opportunities
- Technical support
- Academic support
Staff
Development
- AI literacy training
- Pedagogical workshops
- Technical support
- Communities of practice
- Research opportunities
Resources
- AI tool access
- Teaching materials
- Assessment exemplars
- Policy guidance
- Time allocation
Practice Partners
Collaboration
- Placement AI policies
- Mentor training
- Practice integration
- Feedback mechanisms
- Joint development
Communication
- Regular updates
- Policy sharing
- Best practice exchange
- Problem-solving
- Partnership strengthening
Professional Bodies
Engagement
- NMC alignment
- RCN collaboration
- Policy contribution
- Standards development
- Sector leadership
Implementation Roadmap
Year 1: Foundation
Q1: Planning
- Establish working group
- Review current state
- Develop strategy
- Secure resources
- Plan communication
Q2: Development
- Create policies
- Design Year 1 integration
- Develop resources
- Train staff
- Pilot activities
Q3: Implementation
- Launch Year 1 integration
- Monitor progress
- Gather feedback
- Provide support
- Adjust as needed
Q4: Review
- Evaluate outcomes
- Refine approach
- Plan Year 2
- Share learning
- Celebrate success
Year 2: Expansion
- Implement Year 2 integration
- Continue Year 1 refinement
- Develop Year 3 plans
- Build evidence base
- Expand staff development
Year 3: Maturity
- Full programme integration
- Continuous improvement
- Sector leadership
- Research dissemination
- Sustainability planning
Next: Explore Institutional Framework for university-wide strategy.