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Cost to the Individual

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

When using GenAI in nursing education, there are significant personal costs and responsibilities that both educators and students must consider.

Personal Accountability​

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For Students

Academic Integrity

  • Students must understand that using AI without proper attribution constitutes academic misconduct
  • The NMC Code emphasises honesty and integrity - this extends to academic work
  • Using AI to complete assessments without disclosure undermines professional development

Clinical Competence

  • Over-reliance on AI for clinical reasoning can weaken critical thinking skills
  • Students must develop independent clinical judgment for patient safety
  • AI should supplement, not replace, clinical learning experiences

Professional Identity

  • Nursing requires empathy, compassion, and human connection
  • Excessive AI use may diminish development of these essential qualities
  • Students need authentic experiences to develop professional values
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For Educators

Pedagogical Responsibility

  • Educators must model responsible AI use
  • Clear guidance needed on when and how AI should be used
  • Responsibility to teach AI literacy alongside clinical skills

Assessment Design

  • Need to create AI-resilient assessments that measure authentic competence
  • Responsibility to ensure assessments align with NMC standards
  • Must balance innovation with academic rigor

Privacy and Data Protection​

Patient Confidentiality

Never input patient-identifiable information into AI tools. Anonymize all case studies and adhere strictly to GDPR and institutional policies.

🔒 Personal Information

Be cautious with personal student data. Comply with GDPR and university data protection policies. Anonymize all clinical scenarios by removing identifying details (names, dates, locations).

👣 Digital Footprint

Everything shared with AI tools may be stored and used for training. Consider long-term implications of AI interactions and maintain professional standards in all communications.

Cognitive Costs​

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Critical Thinking

Skill Atrophy

Over-reliance on AI can weaken problem-solving abilities and clinical reasoning confidence.

Learning Depth

AI-generated summaries may reduce deep engagement, leading to surface-level learning that doesn't support expertise.

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Metacognition

Self-Awareness

Students must recognise when they rely too heavily on AI and understand their own learning processes, strengths, and areas for growth.

Time, Effort & Finance​

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The Efficiency Paradox

Short-term vs. Long-term: AI may save time initially but can create dependency. Quick answers don't build lasting knowledge.

Skill Investment: Learning to use AI effectively (prompt engineering) requires significant time and practice.

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Financial Costs

Premium Tools: Advanced features often require subscriptions, creating equity issues.

Hidden Costs: Data usage, potential hardware upgrades, and professional training expenses.

Emotional Considerations​

Addressing Anxiety

Students and educators may face anxiety about AI use, fear of plagiarism accusations, or "imposter syndrome" regarding AI-assisted work. Open dialogue and clear guidelines are key to mitigation.

Mitigation Strategies​

For Students

  1. Set Boundaries: Use AI as a supplement, not a replacement. Maintain regular practice without AI.
  2. Practice Transparency: Always disclose AI use and keep records of your process.
  3. Develop Self-Awareness: Regularly assess your understanding without AI.

For Educators

  1. Provide Clear Guidelines: specific policies on acceptable AI use.
  2. Model Responsible Use: Demonstrate ethical AI integration.
  3. Support Student Development: Teach AI literacy and critical evaluation.

Reflection Questions​

🤔 Evaluate Your AI Use

  • Accountability: Can you explain and justify every instance of AI use in your work?
  • Learning: Is AI enhancing or replacing your learning process?
  • Competence: Are you developing the clinical skills needed for safe practice?
  • Integrity: Would you be comfortable disclosing your AI use to patients, mentors, or examiners?
  • Balance: Are you maintaining skills that don't rely on AI?

Next: Explore Cost to the Environment to understand the sustainability implications of AI use.