Layered AI feedback led to significantly more tasks requiring three or more submissions, while total submissions, learning time and edit distance did not differ¶

Claim · All claims
Evidence · 1 study · causal r2 · q3 · i1 small
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 i1 Layered feedback participants submitted three or more responses on significantly more tasks (M = 2.1) than non-layered participants (M = 1.5), d = 0.36. → Jie Cao 2026

Evidence¶

Jie Cao 2026¶

Jie Cao, Chloe Qianhui Zhao, Christian Schunn, Elizabeth A. McLaughlin, Jionghao Lin, Kenneth R. Koedinger. (2026). Assessing the Impact and Underlying Pathways of Sequenced AI Feedback on Student Learning. arXiv. https://arxiv.org/abs/2604.07469 doi:10.48550/arxiv.2604.07469

q3 · i1 · causal · r2

Behavioral log analysis during learning-by-doing in the randomized experiment; the number of tasks (out of 13) with more than two submissions was the persistence indicator, with a significant between-group difference, d = 0.36.

"learners in the layered feedback group submitted three or more responses on significantly more tasks (M= 2.1) than those in the non-layered group (M= 1.5),t(197) = 2.5,p=.012,d= 0.36."

Discussion¶

Learner Variables¶

Time and Continuity — outcome: instruction changes it

In a case analysis, probing instructor feedback with required revise-and-resubmit moved one teacher candidate toward citing student evidence, though his progress was not linear and another candidate did not improve — the general claim this finding bears on, with the studies behind it
Feedback type shifts engagement by question type: educator feedback yields more MCQ submissions while AI feedback trends toward more open-ended revisions, with no overall difference — related
A negative behavioral path through frequent resubmissions counteracted the affective benefit of layered feedback — a narrower finding that bears on this claim
The total effect of layered feedback on learning outcomes was significantly negative, with an unmediated negative direct effect — related

Page metadata

Field	Value
`type`	`claim`
`id`	`layered-feedback-more-tasks-three-plus-submissions`
`title`	`Layered AI feedback led to significantly more tasks requiring three or more submissions, while total submissions, learning time and edit distance did not differ`
`description`	`Layered AI feedback led to significantly more tasks requiring three or more submissions, while total submissions, learning time and edit distance did not differ`
`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 — `jie-cao-2026`

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