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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 OpenAlexaff
Tomlin Gagen, Farahnaz Faez

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.027
metaresearch head score (Gemma)0.059
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.987
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.059
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0130.042
Bibliometrics0.0090.009
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designMeta-analysis
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations17
Published2023
Admission routes1
Has abstractyes

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