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Blinded quasi-experimental AI-versus-student assessment marking protocol

Design · All designs
Evidence · no claims cited

Description

A pilot evaluation protocol in which ChatGPT-generated submissions, formatted by an independent research assistant to resemble student work, were mixed with deidentified past student assessments and marked by blinded discipline-expert academics against standardized rubrics. As printed, "33 assessments, across the 5 assessment types, were selected for the study: 18 were AI-generated (experimental group), and 15 were past students’ assessments (control group)". A second-marker consensus process applied when a remark differed by more than 10 marks.

Design Implications

Context

Requirements

  • Blinded markers with postgraduate qualifications and DH or HIM expertise; standardized rubrics; deidentification of student work

Constraints

  • Quasi-experimental design without random assignment; limited samples per category; markers' informal AI-authorship judgments were sometimes inaccurate

Target Learners

  • undergraduate and master's-level digital health and health information management students

Learning Goals

  • evaluating assessment validity under generative AI
  • academic integrity benchmarking

Claims

Examples

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Key Sources

  • Wani Tafheem Ahmad, Liem Michael, Prasad Natasha, Robinson Kerin, Nexhip Abbey, Tassos Melanie, Gjorgioski Stephanie, Khan Urooj Raza, Boyd James, Riley Merilyn. (2026). Susceptibility of Assessment Types to AI-Generated Content in Digital Health and Health Information Management Education: Quasi-Experimental Pilot Study. JMIR Medical Education. https://doi.org/10.2196/82988
Page metadata
Field Value
type design
id blinded-ai-student-marking-protocol
title Blinded quasi-experimental AI-versus-student assessment marking protocol
description A pilot evaluation protocol in which ChatGPT-generated submissions, formatted by an independent research assistant to resemble student work, were mixed with deidentified past student assessments and marked by blinded...
status review
generated by process:settle-candidates on 2026-11-05
trust unverified — no one has confirmed this page's content
sources 1 — wani-tafheem-ahmad-2026

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