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Responsible Use

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)

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

For Educators​

📝

Course Design

  • AI-Aware: Explicitly address AI in course outlines. Define "acceptable" vs "unacceptable" use.
  • Assessment: Focus on process (reflections, oral defense) over product. Include AI-free components.
Example Module Structure

Wk 1-2: Intro & Ethics

Wk 3-4: Critical Evaluation (AI vs Evidence)

Wk 5-6: Practical App (Care Planning with oversight)

Wk 7-8: AI-Free Assessment (Simulation/Viva)

💬

Classroom Practices

  • Model Transparency: Show your own AI use—successes and failures.
  • Structured Activities: Run "AI vs Traditional" comparative exercises.
  • Discussion: Ask "What would you have done differently without AI?"
Policy Development

Institutional Guidelines must be clear, and should say what is allowed for each assessment rather than banning AI outright (Jisc). Many universities use a "Traffic Light" system:

  • Green: Generating ideas, communication practice.
  • Amber (Disclose): Drafting text, literature searching.
  • Red (Prohibited): Patient data entry, closed-book exams.

For Students​

🎓

Daily Practice Protocol

  1. Try First: Attempt the task independently. Use AI only for specific blocks.
  2. Stay Critical: Question every response. Verify against NICE/BNF guidelines.
  3. Document: Save your prompts. Be ready to explain how you used the tool.
📚

Study Strategies

  • Test, don't just read: Ask AI to quiz you rather than summarise for you. Recalling answers builds memory; re-reading summaries doesn't (see Cost to Knowledge).
  • Active Learning: Use AI to generate practice questions or flashcards, then check them against your sources.
  • Own words: Make notes in your own words from primary sources, whether typed or handwritten.

Leadership & Practice​

🏛️ Programme Leaders

Strategy: Plan phased implementation aligned with NMC standards and the Council of Deans of Health's principles for generative AI in healthcare education (February 2026).

Quality: Brief external examiners on AI policies. Monitor impact on learning outcomes.

🏥 Clinical Educators

Placement: Discuss appropriate AI use in clinical settings, including AI scribes and Microsoft 365 Copilot, which many NHS staff now have (see AI scribes on placement).

Safety: No patient data in personal or unapproved AI tools. Assess independent clinical reasoning.

Implementation Challenges​

🚧 Obstacles

  • Resistance to change from staff/students.
  • Rapid pace of tool evolution.
  • Digital divide: Not all students can afford subscriptions. In the 2026 HEPI survey, 38% of UK undergraduates said their university provides AI tools (HEPI, 2026).

🚀 Solutions

  • Start small with pilot modules.
  • Adopt flexible frameworks over rigid rules.
  • Provide institutional access or use free, capable alternatives.

Example Activities​

Example 1: Care Planning

Activity: Students draft a care plan with AI, then correct it using NICE guidelines.

Aim: Deeper engagement with guidelines and practice in spotting AI errors.

Example 2: Assessment Redesign

Change: Replaced an essay with a reflective oral presentation.

Aim: An authentic student voice and a direct check of genuine understanding.

Resources​

Next: Use the Responsible Use Checklist for actionable steps.