The paper argues authenticity in AI-mediated assessment is achieved through design rather than detection¶
Claim · All claims
Evidence · 1 study · theoreticalr2·q1
Currency · newest study 2025 · 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.
q1 i? In an AI-mediated world, authenticity is achieved through design rather than detection, operationalised via process transparency, critical/ethical AI use, and assessable judgement. → Kickbusch 2025
Evidence¶
Kickbusch 2025¶
Kickbusch, S., Ashford-Rowe, K., Kemp, A., Boreland, J., & Huijser, H. (2025). Beyond Detection: Redesigning Authentic Assessment in an AI-Mediated World. Education Sciences, 15(11), 1537. https://doi.org/10.3390/educsci15111537
q1 · i? · theoretical · r2
This is the paper's central conceptual proposition, stated in the introduction and pursued throughout. It is a theoretical argument derived from an integrative review, analysis of sector guidance, and iterative practitioner critique, not an empirical test; the article offers no effect data for it.
"in an AI-mediated world, authenticity is achieved through design rather than detection, operationalised via process transparency, critical/ethical AI use, and assessable judgement."
Discussion¶
Related Claims¶
- GenAI feedback limitations require students to exercise evaluative judgement — related
- Human guidance remains essential for ethical grounding when integrating AI with situated learning, including resisting complacency toward generative AI outputs — related
- The most frequently cited ethical concerns about GenAI in research were hallucinated facts, fabricated references, and misleading content — related
- Judgement is theorized as the evaluative locus of educational integrity within GenAI-augmented authorship — related
- Learner agency in GenAI-mediated learning is enacted through prompting, questioning, verification, comparison, revision, and disciplinary judgment — related
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- Detection-oriented integrity approaches are increasingly misaligned with GenAI-augmented assessment (theoretical argument) — related
- Integrating AI in CS assessment raises concerns about academic integrity, algorithmic bias, transparency, and ethical evaluation — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
authenticity-through-design-not-detection |
title |
The paper argues authenticity in AI-mediated assessment is achieved through design rather than detection |
description |
The paper argues authenticity in AI-mediated assessment is achieved through design rather than detection |
status |
review |
evidence_strength |
weak |
newest_evidence |
2025 |
generated |
by process:wiki-ingest on 2026-10-12 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — kickbusch-2025 |
Frontmatter is the page's machine-readable record — see the Schema & Guide.