Student-perceived curricular alignment did not differ between AI and NLE MCQs or among ChatGPT, Gemini and NLE¶
Claim · All claims
Evidence · 1 study · associationalr2·q3
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q3 i? In binary and source-specific comparisons, no significant differences in perceived curricular alignment were observed. → Vogt P 2026
Evidence¶
Vogt P 2026¶
Vogt P, Wolf N, Jordan S, Volz-Willems S, Jäger J, Dupont F. (2026). Can students identify AI? – A cross-sectional quantitative study about AI recognition in tablet-based MCQ assessment among fifth-year undergraduate medical students at Saarland University, Germany. BMC Medical Education. https://doi.org/10.1186/s12909-026-10410-8
q3 · i? · associational · r2
Kruskal–Wallis comparison of student-perceived curricular alignment across ChatGPT, Google Gemini and NLE items in the exam study. The binary AI vs NLE comparison was also non-significant (U = 188, p = 0.978; mixed-effects OR = 1.04, 95% CI 0.385–2.81, p = 0.938).
"in a source-specific analysis no significant difference was observed across the three sources (“aligned” χ 2 (2) = 4.03, p = 0.134, ε2 = 0.11; “not aligned” χ 2 (2) = 3.99, p = 0.136, ε2 = 0.11)."
Discussion¶
Related Claims¶
- AI-generated assessment items frequently need faculty correction, supporting AI as a draft generator within quality assurance — the general claim this finding bears on, with the studies behind it
- Exploratory analysis found item difficulty differed across sources, driven by the Google Gemini versus NLE contrast — related
- Judging learning-objective alignment of generated MCQs is more subjective than answering them, with only moderate human agreement — related
- Perceived overall utility of generative AI differs significantly across the five platforms used, favoring platforms with structured task breakdowns — related
- Students identified MCQ item source at a rate significantly above the 50% chance level in a real exam setting — related
- Easier items were perceived as better aligned with the curriculum (strong difficulty–alignment association) — related
- Distractor distribution did not differ across ChatGPT, Google Gemini and NLE MCQs — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
perceived-alignment-does-not-differ-ai-vs-nle |
title |
Student-perceived curricular alignment did not differ between AI and NLE MCQs or among ChatGPT, Gemini and NLE |
description |
Student-perceived curricular alignment did not differ between AI and NLE MCQs or among ChatGPT, Gemini and NLE |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2026 |
generated |
by process:wiki-ingest on 2026-10-11 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — vogt-p-2026 |
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