Claims

ENL students were near-evenly split in preference between AI-generated and human tutor feedback

Claim · All claims
Evidence · 1 study · associational r1 · q2
Currency · newest study 2023 · 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.

q2 i? Across six weeks, weekly survey respondents split almost evenly between preferring human tutor feedback and AI-generated feedback, with AI slightly ahead on the forced-choice item. → Escalante 2023

Evidence

Escalante 2023

Escalante, J., Pack, A., & Barrett, A. (2023). AI-generated feedback on writing: insights into efficacy and ENL student preference. International Journal of Educational Technology in Higher Education, 20:57. https://doi.org/10.1186/s41239-023-00425-2

q2 · i? · associational · r1

Study 2 weekly Qualtrics survey with 43 ENL students receiving both feedback types; forced-choice item 9 averaged near the 1.5 even-split point (grand mean 1.53). "The six-week average of the number of students that preferred feedback from human tutors was 18" vs 19.667 for AI.

"The six-week average of the number of students that preferred feedback from human tutors was 18, which was slightly lower than the average of those that preferred AI-generated feedback (19.667)"

Discussion

Page metadata
Field Value
type claim
id enl-near-even-split-ai-human-feedback-preference
title ENL students were near-evenly split in preference between AI-generated and human tutor feedback
description ENL students were near-evenly split in preference between AI-generated and human tutor feedback
status review
evidence_strength moderate
newest_evidence 2023
generated by process:wiki-ingest on 2026-10-15
trust unverified — no one has confirmed this page's content
sources 1 — escalante-2023

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