Human-AI tutoring is associated with a 36% rise in IXL skill proficiency, but the gap widened in favor of reactively tutored students (difference-in-differences preprint)¶
Claim · All claims
Evidence · 1 study (2 entries) · causalr2·q2
Currency · newest study 2026 · checked against its sources 2026-10-20 (automated, 2 of 2 entries) · 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? Human-AI tutoring significantly improved student skill proficiency in IXL (36% in the IK bandwidth; +6.10 skills, p<.001). → Ashish Gurung 2026
q2 i? Despite improvements for both groups, the skill proficiency gap widened by 3.69 skills (14.79%), with the reactive group demonstrating greater proficiency than the proactive group. → Ashish Gurung 2026 (2)
Evidence¶
Ashish Gurung 2026¶
Ashish Gurung, Ge Gao, Jordan Gutterman, Danielle R. Thomas, Shivang Gupta, Lee Branstetter, Emma Brunskill, Vincent Aleven, Kenneth R. Koedinger. (2026). Improving Hybrid Human-AI Tutoring by Differentiating Human Tutor Roles Based on Student Needs. arXiv preprint. https://arxiv.org/abs/2605.11155 doi:10.48550/arxiv.2605.11155
q2 · i? · causal · r2
Within-subject DiD analysis of IXL skill proficiency (SmartScore-based skills mastered) over the 10 weeks before each MAP test. Improvement was "significant improvement in student skill proficiency in both the IK bandwidth subsample (36%; +6.10 skills, p<.001)" and the full sample.
"human-AI tutoring was associated with significant improvement in student skill proficiency in both the IK bandwidth subsample (36%; +6.10 skills, p<.001) and the full sample (42%; +6.75 skills, p <.001)."
Ashish Gurung 2026 (2)¶
Ashish Gurung, Ge Gao, Jordan Gutterman, Danielle R. Thomas, Shivang Gupta, Lee Branstetter, Emma Brunskill, Vincent Aleven, Kenneth R. Koedinger. (2026). Improving Hybrid Human-AI Tutoring by Differentiating Human Tutor Roles Based on Student Needs. arXiv preprint. https://arxiv.org/abs/2605.11155
q2 · i? · causal · r2
DiD comparison of proactive versus reactive groups on IXL skill proficiency (Table 6). The article reports the "proficiency gap widened by 3.69 skills (14.79%)" favoring the reactive group; the proactive group had lower baseline proficiency (-2.17, p=.067 in the IK bandwidth).
"Following the introduction of human support, despite improvements for both groups, the proficiency gap widened by 3.69 skills (14.79%), with the reactive group demonstrating greater proficiency than their proactive peers."
Discussion¶
Related Claims¶
- Introducing human-AI tutoring improves relative MAP academic growth by 61% over an AI-only baseline within the IK bandwidth — related
- Human-AI tutoring increases IXL time on task by 25% with no significant difference between proactive and reactive groups — related
- Proactive tutoring produced larger relative MAP growth than reactive tutoring on average (75% marginally significant in the IK bandwidth) — reports the opposite
- At the median cutoff, proactive and reactive tutoring show no significant difference in MAP growth, with proactive benefits increasing for students farther below the cutoff — reports the opposite
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
human-ai-tutoring-skill-proficiency-gap-widens |
title |
Human-AI tutoring is associated with a 36% rise in IXL skill proficiency, but the gap widened in favor of reactively tutored students (difference-in-differences preprint) |
description |
Human-AI tutoring is associated with a 36% rise in IXL skill proficiency, but the gap widened in favor of reactively tutored students (difference-in-differences preprint) |
status |
review |
evidence_strength |
mixed |
newest_evidence |
2026 |
source_checked |
2026-10-20 |
generated |
by process:wiki-ingest on 2026-10-11 |
trust |
unverified — no one has confirmed this page's content |
sources |
2 — ashish-gurung-2026, ashish-gurung-2026-2 |
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