Students showed no statistically significant apprehension about trusting automated feedback validity, and favoured granular automated marginalia over generalised human feedback¶
Claim · All claims
Evidence · 1 study · causalr2·q2
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
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This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q2 i? An independent samples t-test on Trust in Automated Feedback Validity showed no statistically significant apprehension; students explicitly favoured the objective, granular marginalia over conventional human remarks. → Matey Yordanov 2026
Evidence¶
Matey Yordanov 2026¶
Matey Yordanov, Mikhail Bychkov, and Andrei Kuchma. (2026). The Effect of High-Frequency, Automatically-marked Formative Assessments on Student Outcomes in A-Level Sciences. https://arxiv.org/abs/2607.23566 doi:10.48550/arxiv.2607.23566
q2 · i? · causal · r2
Post-intervention survey in the quasi-experiment; the trust construct was a composite mean of 5-point Likert items. The article reports no significant apprehension and that students "explicit favoured the objective, granular marginalia" over remarks such as "Good effort"; no effect size is printed, so equivalence was not tested.
"An independent samples t-test assessing “Trust in Automated Feedback Validity“ showed no statistically significant apprehension."
Discussion¶
Related Claims¶
- Manipulating anthropomorphism shows no clear causal effect on trust in controlled post-generative-AI studies, though long-term use and cue type condition its effects — related
- Participant samples in AI trust research skew WEIRD: mostly Western, adult, university-educated participants, limiting external validity — related
- Nine interaction design factors recur in post-2023 research on trust in AI-enabled systems, with explainability the most studied — related
- High-level feedback on reasoning and synthesis should remain a human responsibility for the foreseeable future — reports the opposite
- Open-ended student feedback highlighted relevance and conciseness as benefits of personalized AI videos, alongside concerns about unnaturalness, uncanny-valley discomfort, and trust — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
student-trust-in-automated-feedback-null-apprehension |
title |
Students showed no statistically significant apprehension about trusting automated feedback validity, and favoured granular automated marginalia over generalised human feedback |
description |
Students showed no statistically significant apprehension about trusting automated feedback validity, and favoured granular automated marginalia over generalised human feedback |
status |
review |
evidence_strength |
weak |
newest_evidence |
2026 |
generated |
by process:wiki-ingest on 2026-10-10 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — matey-yordanov-2026 |
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