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Record W2125841054 · doi:10.1017/s0142716409090109

Aptitude, phonological memory, and second language proficiency in nonnovice adult learners

2009· article· en· W2125841054 on OpenAlexaff
Kirsten M. Hummel

Bibliographic record

VenueApplied Psycholinguistics · 2009
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsAptitudePsychologyLanguage proficiencySecond languageRegression analysisExploratory researchExploratory factor analysisFirst languageDevelopmental psychologyLinguisticsMathematics educationPsychometricsStatisticsMathematics

Abstract

fetched live from OpenAlex

ABSTRACT This study explores the relationship between aptitude, phonological memory (PM), and second language (L2) proficiency in nonnovice adult learners of English as an L2. Native speakers of French (N= 77) enrolled in a university Teaching English as a Second Language program were the participants in the study. Exploratory factor analysis revealed three main factors corresponding to the variables examined: L2 proficiency, aptitude, and PM. Multiple regression analyses revealed aptitude subtests and PM together predicted 29% of the variance in L2 proficiency. Additional regression analyses carried out on lower and higher proficiency subgroups, created by a median split on proficiency scores, revealed that none of the variables predicted L2 proficiency in the higher proficiency subgroup. PM remained as a significant predictor for the lower proficiency subgroup, extending the pattern of results found elsewhere in younger populations to adult nonnovice L2 learners.

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.018
GPT teacher head0.274
Teacher spread0.255 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations134
Published2009
Admission routes1
Has abstractyes

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