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Assessment with AI

Assessment with AI

Attribution

Original work: "Educators' guide to multimodal learning and Generative AI" โ€” Tรผnde Varga-Atkins, Samuel Saunders, et al. (2024/25) โ€” CC BY-NC 4.0
Adapted for UK Nursing Education by: Lincoln Gombedza, RN (LD)
Last Updated: December 2025

The rapid evolution of Generative AI challenges traditional essay-based assessment. This section explores how nursing education can move from "policing" students (which is increasingly inaccurate) to "designing" assessments that are authentic and AI-resilient.

The Paradigm Shiftโ€‹

Traditional AssessmentAI-Era Assessment
Product-FocusedProcess-Focused
"Write an essay about...""Critique this AI essay about..."
Testing recall of factsTesting application of knowledge in novel contexts
Written onlyMultimodal (Video, Audio, Diagram, Viva)

Key Principlesโ€‹

  1. AI Resilience: Design tasks that rely on human-specific skills (emotional intelligence, reflection on practice, real-time clinical reasoning).
  2. Assessment FOR Learning: Use AI to give students immediate formative feedback to improve their work before submission.
  3. Authenticity: Simulate real-world nursing tasks (e.g., handover, discharge planning) rather than abstract academic tasks.

In This Sectionโ€‹

Multimodal Assessmentโ€‹

Strategies for designing assessments that are harder to fake, including Vivas, Video Vlogs, and "Show Your Working" tasks.

AI Risk Calculatorโ€‹

Test the vulnerability of your assessments to GenAI misuse with our interactive tool.

AI-Enabled Feedbackโ€‹

How to use AI to provide "Pre-flight checks" for students and assist marking, with Strict Privacy Warnings.

Nursing Examplesโ€‹

A library of prompts for educators to generate rubrics, exam questions, and model answers.

AI Detection Tools

Research (e.g., Weber-Wulff et al.) suggests that AI detection software is unreliable and prone to false positives, especially against non-native English speakers. Focus on assessment design, not detection software.