Choosing AI Platforms
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
Selecting the right AI platform is a critical decision for nursing educators. The landscape is rapidly evolving, with a wide range of general-purpose and specialized tools available. This section provides a framework for evaluating and choosing platforms that align with pedagogical goals, professional standards, and institutional requirements.
The AI Tool Landscape
AI tools in nursing education can generally be categorized into three types:
- General-Purpose LLMs: Versatile models like ChatGPT, Claude, and Gemini that can handle a wide array of tasks.
- Specialized Healthcare AI: Tools specifically trained or fine-tuned on clinical data and medical literature.
- Educational Integration Tools: Platforms that integrate AI into existing educational workflows, such as VLE plugins or automated feedback systems.
Key Considerations for Nursing
When choosing a platform, nursing educators must prioritize:
- Clinical Accuracy: Does the model produce reliable medical information?
- Ethical Safety: Does it protect patient and student data?
- NMC Alignment: Does it support the development of required nursing proficiencies?
- Accessibility: Is it usable for all students, regardless of technical skill or financial means?
Navigate this Section
To make an informed choice, explore the following pages:
- Tool Comparison: A detailed look at major AI platforms and their features.
- Selection Criteria: A framework of educational, technical, and ethical requirements.
- Institutional Considerations: Guidance on procurement, data security, and change management.
Next: Explore the Tool Comparison to see how the major AI platforms stack up for nursing education.