Claims

Pretest scores significantly predict posttest scores across CF types and outcome measures

Claim · All claims
Evidence · 1 study · associational r2 · 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? In the regression models, pretest scores were generally a significant predictor of posttest scores irrespective of CF type or outcome measure. → Yusuke Sato 2023

Evidence

Yusuke Sato 2023

Yusuke Sato. (2023). Interactions Among Declarative and Procedural Memory Systems, Different Linguistic Structures, and the Efficacy of Different Corrective Feedback Types. Journal for the Psychology of Language Learning, 5(1). https://doi.org/10.52598/jpll/5/1/4

q2 · i? · associational · r2

Secondary finding from the multiple regression analyses for both regular and irregular past tense: pretest scores on the GJT or EIT were included as covariates and were generally significant predictors, which the article notes is "in line with previous studies."

"In general, pretest scores were significantly related to posttest scores irrespective of the CF type or L2 outcome measure, in line with previous studies"

Discussion

Learner Variables

Page metadata
Field Value
type claim
id pretest-scores-predict-posttest-scores
title Pretest scores significantly predict posttest scores across CF types and outcome measures
description Pretest scores significantly predict posttest scores across CF types and outcome measures
status review
evidence_strength moderate
newest_evidence 2023
generated by process:wiki-ingest on 2026-09-28
trust unverified — no one has confirmed this page's content
sources 1 — yusuke-sato-2023

Frontmatter is the page's machine-readable record — see the Schema & Guide.