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The Effects of Repetition on Incidental Vocabulary Learning: A Meta‐Analysis of Correlational Studies

2019· article· en· 291 citations· W2920898950 on OpenAlex· 10.1111/lang.12343

Why is this work in the frame?

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

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.

Full frame distilled prediction

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.

Candidate categories
Insufficient payload (model declined to judge)
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: QualitativeConsensus signal: none
Genre
Candidate signal: EmpiricalConsensus signal: Empirical
Teacher disagreement score
0.303
Threshold uncertainty score
0.990
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0110.000

Machine scores (provisional)

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

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.

Opus teacher head0.017
GPT teacher head0.333
Teacher spread
0.316 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

This meta‐analysis aimed to clarify the complex relationship between repetition and second language (L2) incidental vocabulary learning by meta‐analyzing primary studies reporting correlation coefficients between the number of encounters and vocabulary learning. We synthesized and quantitatively analyzed 45 effect sizes from 26 studies ( N = 1,918) to calculate the mean effect size of the frequency–learning relationship and to explore the extent to which 10 empirically motivated variables moderate this relationship. Results showed that there was a medium effect ( r = .34) of repetition on incidental vocabulary learning. Subsequent moderator analyses revealed that variability in the size of repetition effects across studies was explained by learner variables (age, vocabulary knowledge), treatment variables (spaced learning, visual support, engagement, range in number of encounters), and methodological differences (nonword use, forewarning of an upcoming comprehension test, vocabulary test format). Based on the findings, we suggest future directions for L2 incidental vocabulary learning research. Open Practices This article has been awarded an Open Data badge. All data are publicly accessible via the Open Science Framework at https://osf.io/rmnk2 . Learn more about the Open Practices badges from the Center for Open Science: https://osf.io/tvyxz/wiki .

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.

The record

Venue
Language Learning
Topic
Second Language Acquisition and Learning
Field
Psychology
Canadian institutions
Western University
Funders
not available
Keywords
VocabularyRepetition (rhetorical device)ModerationPsychologyVocabulary developmentMeta-analysisComprehensionTest (biology)Cognitive psychologyMathematics educationLinguisticsSocial psychologyTeaching method
Has abstract in OpenAlex
yes