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Record W2970518675 · doi:10.1080/07294360.2023.2280700

The predictive validity of IELTS scores: a meta-analysis

2023· article· en· W2970518675 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHigher Education Research & Development · 2023
Typearticle
Languageen
FieldPsychology
TopicEducational and Psychological Assessments
Canadian institutionsWestern University
Fundersnot available
KeywordsModerationPsychologyMeta-analysisActive listeningReading (process)Predictive validityClinical psychologyLinguisticsSocial psychologyMedicine

Abstract

fetched live from OpenAlex

Thousands of education institutions worldwide rely on IELTS scores as criteria for accepting international students whose first language is not English. Individual studies have found varying degrees of strength of correlations and conflicting results between IELTS entry scores and subsequent academic success. These conflicting results were examined through a meta-analysis, while also investigating multiple moderating variables: research funding bias, individual skill scores, level of study, country of study, and presence of additional English courses. Results from 20 studies show an approaching-small effect size of r = .231 for the relationship between IELTS scores and post-secondary GPA. The majority of macro skills (listening, writing, and speaking) do not reach the small effect size, however reading approaches it with an effect size of r = .232. Most moderator analyses were inconclusive owing to the small number of studies, but potential differences from individual studies are examined and discussed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.690
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.394
GPT teacher head0.542
Teacher spread0.148 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it