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Practical Implications

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

Understanding the costs of AI is important, but what does this mean in practice for nursing education? This page translates theory into actionable guidance for educators and students.

For Nursing Educators​

Course Design​

AI-Aware Curriculum

  • Explicitly address AI use in course outlines
  • Define acceptable and unacceptable AI applications
  • Include AI literacy as a learning outcome
  • Balance AI-enhanced and AI-free activities

Assessment Strategy

  • Design assessments that measure authentic understanding
  • Include components that can't be completed with AI alone
  • Use varied assessment methods (oral, practical, written)
  • Focus on process as well as product

Example Module Structure

Week 1-2: Introduction to AI in Healthcare
- What is AI and how does it work?
- Ethical considerations
- Hands-on AI tool exploration

Week 3-4: Critical Evaluation
- Assessing AI outputs for accuracy
- Identifying bias and limitations
- Comparing AI to evidence-based sources

Week 5-6: Practical Application
- Using AI for care planning (with oversight)
- AI-assisted patient education materials
- Reflective practice on AI use

Week 7-8: AI-Free Assessment
- Clinical simulation without AI
- Oral examination on clinical reasoning
- Practical skills demonstration

Classroom Practices​

Transparent Modeling

  • Demonstrate your own AI use openly
  • Show both successes and failures
  • Discuss your decision-making process
  • Acknowledge uncertainties

Structured AI Activities

  • Guided AI exploration with clear objectives
  • Comparative exercises (AI vs. traditional methods)
  • Critical analysis of AI outputs
  • Reflection on learning process

Discussion Prompts

  • "How did using AI change your understanding?"
  • "What would you have done differently without AI?"
  • "How confident are you in this AI-generated information?"
  • "What are the risks of using this in clinical practice?"

Policy Development​

Institutional Guidelines

  • Clear statement on acceptable AI use
  • Discipline-specific examples
  • Consequences for misuse
  • Regular policy reviews

Example Policy Elements

## AI Use in Nursing Assessments

### Permitted:
- Using AI to generate initial ideas for care plans
- AI-assisted literature searches (with verification)
- Creating visual aids for patient education
- Practicing communication scenarios

### Requires Disclosure:
- Any AI use in submitted work
- Specific tools and prompts used
- How AI output was modified

### Prohibited:
- Submitting AI-generated work as your own
- Using AI for closed-book examinations
- Inputting patient-identifiable information
- Bypassing required learning processes

For Students​

Daily Practice​

Before Using AI

  1. Try it yourself first

    • Attempt the task independently
    • Identify specific areas where you're stuck
    • Use AI for targeted help, not complete solutions

  2. Define your purpose

    • What do you want to learn?
    • How will AI help you learn it?
    • What will you do with AI output?

While Using AI

  1. Stay critical

    • Question every AI response
    • Verify against authoritative sources
    • Look for bias or errors
    • Consider alternative perspectives

  2. Document your process

    • Save prompts and responses
    • Note how you modified AI output
    • Record your learning journey
    • Prepare to explain your work

After Using AI

  1. Reflect on learning

    • What did you actually learn?
    • Could you do this without AI now?
    • What gaps remain in your understanding?
    • How will you address those gaps?

  2. Practice independently

    • Test yourself without AI
    • Explain concepts to peers
    • Apply knowledge in new contexts
    • Build confidence in your abilities

Study Strategies​

Balanced Approach

  • Use AI for 20% of study time maximum
  • Prioritize active learning methods
  • Regular self-testing without AI
  • Peer study groups for discussion

AI as Study Partner

  • Generate practice questions
  • Create flashcards (then verify)
  • Explain concepts in different ways
  • Provide feedback on your explanations

Traditional Methods Still Essential

  • Handwritten notes for retention
  • Reading primary sources
  • Clinical practice and simulation
  • Face-to-face mentoring

For Programme Leaders​

Strategic Planning​

Curriculum Review

  • Audit current AI integration
  • Identify gaps in AI literacy
  • Plan phased implementation
  • Align with NMC standards

Staff Development

  • Provide AI training for educators
  • Create communities of practice
  • Share best practices
  • Support experimentation

Resource Allocation

  • Budget for AI tools and subscriptions
  • Ensure equitable access
  • Invest in training
  • Support research and evaluation

Quality Assurance​

Monitoring and Evaluation

  • Track AI use patterns
  • Assess impact on learning outcomes
  • Gather student and staff feedback
  • Adjust policies based on evidence

External Examiner Guidance

  • Brief examiners on AI policies
  • Provide examples of acceptable use
  • Clarify assessment criteria
  • Ensure consistency across cohorts

For Clinical Practice Educators​

Placement Learning​

Mentor Guidance

  • Understand student AI policies
  • Discuss appropriate AI use in practice
  • Model professional technology use
  • Support critical evaluation skills

Clinical Scenarios

  • When AI might be helpful (e.g., rare conditions)
  • When AI is inappropriate (e.g., patient interaction)
  • How to verify AI information quickly
  • Balancing efficiency with learning

Assessment in Practice

  • Observe independent clinical reasoning
  • Ask students to explain their thinking
  • Assess practical skills without AI
  • Evaluate professional judgment

Workplace Integration​

Team Discussions

  • Share experiences with AI tools
  • Discuss ethical implications
  • Develop team guidelines
  • Learn from each other

Patient Safety

  • Never rely solely on AI for clinical decisions
  • Always verify critical information
  • Maintain professional accountability
  • Document decision-making process

Implementation Challenges​

Common Obstacles​

Resistance to Change

  • Some educators uncomfortable with AI
  • Students may prefer traditional methods
  • Institutional inertia
  • Resource constraints

Addressing Resistance

  • Provide support and training
  • Start small with pilot projects
  • Share success stories
  • Acknowledge concerns

Keeping Pace with Change

  • AI evolves rapidly
  • Policies quickly outdated
  • New tools emerge constantly
  • Uncertainty about best practices

Staying Current

  • Regular policy reviews
  • Flexible frameworks
  • Continuous professional development
  • Engagement with AI community

Equity Considerations​

Access Issues

  • Not all students can afford AI subscriptions
  • Digital divide affects participation
  • Disability accommodations needed
  • International students may face barriers

Solutions

  • Institutional subscriptions
  • Alternative free tools
  • Offline options available
  • Flexible policies

Measuring Success​

Learning Outcomes​

Knowledge and Skills

  • Can students use AI effectively and ethically?
  • Do they demonstrate critical evaluation?
  • Is clinical competence maintained?
  • Are they prepared for practice?

Assessment Methods

  • Pre/post AI literacy tests
  • Reflective portfolios
  • Clinical performance evaluations
  • Graduate feedback

Programme Evaluation​

Key Indicators

  • Student satisfaction with AI integration
  • Academic integrity incidents
  • Clinical placement feedback
  • Graduate employment outcomes

Continuous Improvement

  • Regular data collection
  • Stakeholder consultation
  • Evidence-based adjustments
  • Sharing findings

Case Examples​

Successful Integration​

Example 1: Care Planning Module

  • Students use AI to generate initial care plan
  • Must verify against NICE guidelines
  • Present and defend in seminar
  • Reflect on AI's strengths and limitations

Outcomes:

  • Improved efficiency in drafting
  • Deeper engagement with guidelines
  • Better critical thinking
  • Clear understanding of AI role

Example 2: Communication Skills

  • AI generates patient scenarios
  • Students practice responses
  • Peer and tutor feedback
  • Real patient interaction follows

Outcomes:

  • More practice opportunities
  • Reduced anxiety
  • Better preparation
  • Maintained human connection

Learning from Challenges​

Example 3: Assessment Redesign

  • Initial essay assignment easily AI-completed
  • High suspected AI use
  • Redesigned to include:
    • Oral presentation
    • Reflective component
    • Process documentation
    • Peer discussion

Lessons Learned:

  • Need for AI-resilient assessment
  • Importance of process over product
  • Value of multiple assessment methods
  • Student feedback essential

Resources and Support​

For Educators​

Professional Development

  • JISC AI resources
  • NMC guidance documents
  • Nursing education conferences
  • Online communities of practice

Practical Tools

  • AI detection tools (use cautiously)
  • Assessment design frameworks
  • Policy templates
  • Case study repositories

For Students​

Learning Support

  • Academic skills workshops
  • AI literacy modules
  • Peer mentoring programs
  • Library research support

Ethical Guidance

  • Academic integrity resources
  • Professional standards documents
  • Reflective practice tools
  • Ethics discussion forums

Moving Forward​

Iterative Approach​

Start Small

  • Pilot in one module
  • Gather feedback
  • Refine approach
  • Scale gradually

Stay Flexible

  • Policies as living documents
  • Regular reviews
  • Responsive to feedback
  • Evidence-based adjustments

Collaborative Development​

Engage Stakeholders

  • Students as partners
  • Clinical educators
  • Professional bodies
  • Patients and public

Share Knowledge

  • Publish findings
  • Present at conferences
  • Contribute to policy
  • Build evidence base

Next: Use the Responsible Use Checklist for actionable steps to implement these principles.