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Implementation Guide

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

A successful rollout depends on clear communication and careful preparation. AI can be intimidating for both staff and students if not managed properly.

1. Prepare Your Staff​

  • Technical Briefing: Ensure all lecturers and clinical instructors know how to log in and use the specific tool.
  • Pedagogical Alignment: Explain why AI is being used in this module and how it maps to outcomes.
  • Managing Resistance: Acknowledge concerns about AI (e.g., cheating or job loss) and re-focus on AI as an "augmented intelligence" tool for better care.

2. Onboard Your Students​

  • The "AI Contract": Have a clear discussion or document outlining what is acceptable use (e.g., brainstorming) and what is not (e.g., copying verbatim for an essay).
  • Prompt Tutorials: Provide a 15-minute "How-to-Prompt" session relevant to the specific module tasks.
  • Accessibility Check: Ensure students who may struggle with technology are paired with "digital buddies" or given extra support.

3. Pilot Small, Then Scale​

  • The Alpha Test: Run the activity yourself or with a few colleagues first to find obvious "bugs" or hallucinations.
  • The Pilot: Run it with one small seminar group before rolling it out to the entire 300-person cohort.
  • Real-time Support: Have a "Teams" channel or physical helpdesk available during the first week of the AI activity.

4. Communication is Key​

  • Be Transparent: Tell students exactly which model you are using (e.g., Claude 3.5 Sonnet) and why.
  • Acknowledge Errors: If the AI makes a mistake during a demo, use it as a "teachable moment" for critical evaluation.

Next: Don't forget to close the loop with Evaluation & Iteration.