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Platform Selection Criteria

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 evaluating an AI tool for use in a nursing module or programme, it's helpful to categorize your requirements into four main areas: Pedagogical, Technical, Ethical/Legal, and Sustainable.

1. Pedagogical Criteria​

The primary question is: Does the tool enhance learning in a way that aligns with nursing competencies?

  • Accuracy of Medical Knowledge: Does the tool provide accurate nursing theory, pathophysiology, and clinical guidance?
  • Nuance and Tone: Can the tool adopt a professional, empathetic nursing tone appropriate for patient interaction simulations?
  • Reasoning Capability: Can it handle complex "What if?" patient scenarios requiring clinical judgment?
  • Output Variety: Does it support the multimodal needs of the module (text, images, audio)?

2. Technical Criteria​

The tool must be usable and stable within the existing institutional infrastructure.

  • Ease of Access: Is there a web interface? Mobile app? Single Sign-On (SSO) integration?
  • API Availability: Can the tool be integrated into other nursing education software (e.g., VLEs)?
  • Stability and Performance: Is the tool reliable during peak usage hours (e.g., during an exam or workshop)?
  • Customization: Can we provide "system instructions" or "custom instructions" to keep the AI focused on UK nursing standards (NMC)?

Nursing education is bound by strict ethical and professional standards (NMC Code).

  • Data Security & Privacy: Where is the data stored? Is it used for training the model? Is it GDPR compliant?
  • Bias and Fairness: How does the tool handle diverse patient scenarios (different ethnicities, genders, socio-economic backgrounds)?
  • Transparency: Is it clear when the output is AI-generated? Does the tool cite its sources?
  • Intellectual Property: Who owns the outputs created by students and staff?

4. Sustainability Criteria​

The long-term viability of the tool must be considered.

  • Financial Sustainability: Is the pricing model predictable? Are there free tiers or academic discounts?
  • Environmental Impact: Does the provider have a commitment to net-zero carbon operations?
  • Scalability: Can the tool support a whole cohort of 200+ nursing students simultaneously?

Evaluation Checklist for Educators​

Before introducing a new AI tool to students, run through this quick checklist:

  1. [ ] Accuracy: Have I tested it on a known complex clinical topic?
  2. [ ] Security: Have I confirmed it meets university data privacy requirements?
  3. [ ] Accessibility: Can students with disabilities or those without expensive hardware use it?
  4. [ ] Professionalism: Does its output align with the NMC Code of Conduct?

Next: Learn about the Institutional Considerations for deploying AI platforms across a department or university.