Student interpreters who practiced with an automated scoring system outperformed the control group on total interpreting scores at post-test¶
Claim · All claims
Evidence · 1 study · causalr1·q2·i3large
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.
q2 i3 After 14 weeks, the experimental group scored significantly higher than the control group at post-test (d = 1.03). → Chen C and Liu T 2026
Evidence¶
Chen C and Liu T 2026¶
Chen C and Liu T (2026) Impact of automated scoring on interpreting performance and self-regulated learning: evidence from a pedagogical experiment. Front. Psychol. 17:1867463. https://doi.org/10.3389/fpsyg.2026.1867463
q2 · i3 · causal · r1
In the 14-week quasi-experiment with two intact classes (n1 = 24, n2 = 22), the post-test between-group comparison showed the experimental group ahead with a large printed effect: "d = 1.03, 95% CI [0.41, 1.64]". Groups were well-matched at pre-test (d = 0.10).
"At post-test the experimental group ( M = 85.58, SD = 5.07) scored higher than the control group ( M = 80.84, SD = 4.01), t(44) = 3.50, p = 0.001, d = 1.03, 95% CI [0.41, 1.64]"
Discussion¶
Related Claims¶
- Automated scoring practice produced a significant time × group interaction on total interpreting scores — related
- In a 16-week quasi-experiment, A-Level STEM students receiving high-frequency automated marking scored 16.8 percentage points higher on a blind-graded final mock exam than control students with human marking — related
- In the 12-week quasi-experiment the experimental group's learning trajectory was significantly steeper than the control group's (group × time β = 0.52, 95% CI 0.31–0.73), with comparable baseline D-scores — related
- Gains from automated scoring concentrated in linguistic accuracy and logical coherence but were absent in information fidelity and delivery fluency — a narrower finding that bears on this claim
- Using ChatGPT during technology learning produces significantly higher post-test learning outcomes than conventional learning in a quasi-experiment of two classes of 31 students — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
automated-scoring-improves-interpreting-total-scores |
title |
Student interpreters who practiced with an automated scoring system outperformed the control group on total interpreting scores at post-test |
description |
Student interpreters who practiced with an automated scoring system outperformed the control group on total interpreting scores at post-test |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2026 |
generated |
by process:wiki-ingest on 2026-10-10 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — chen-c-and-liu-t-2026 |
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