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Record W7116883431 · doi:10.5430/wjel.v16n3p38

Vocabulary Knowledge and Metacognitive Awareness in L2 Listening: Testing the Core-Peripheral Hypothesis

2025· article· W7116883431 on OpenAlexvenueno aff
Dan Li, Apisak Sukying, Nithipong Yothachai

Bibliographic record

VenueWorld Journal of English Language · 2025
Typearticle
Language
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsnot available
FundersMahasarakham University
KeywordsVocabularyActive listeningMetacognitionVariance (accounting)Multilevel modelVocabulary developmentLanguage proficiency

Abstract

fetched live from OpenAlex

This study tested predictions from Hulstijn’s core-peripheral framework for second-language listening by comparing the relative contributions of vocabulary knowledge and metacognitive awareness among Chinese EFL learners. Participants were 166 third-year English majors with intermediate proficiency (TEM-4 scores 65–75). They completed comprehensive assessments of four vocabulary dimensions: written breadth, written depth, aural breadth, and aural depth. They also completed a measure of metacognitive awareness and a standardized listening test. Hierarchical regression analysis revealed that vocabulary knowledge accounted for the majority of variance in listening. Aural vocabulary measures explained substantial additional variance beyond written measures. By contrast, metacognitive awareness contributed only minimal incremental variance after vocabulary had been entered into the model. Within the vocabulary dimensions, aural depth and aural breadth were the strongest predictors of performance. The coefficients for written measures were markedly reduced once aural measures were statistically controlled. These results support a hierarchical distinction between core and peripheral components. They position vocabulary knowledge, particularly in its aural modality, as foundational to listening success, whereas metacognitive awareness plays a supplementary role that may vary across proficiency levels. The clear superiority of aural over written vocabulary challenges assessment practices that prioritize orthographic knowledge, underscoring the need for modality-specific vocabulary instruction to enhance L2 listening comprehension.

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 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)0.002
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.328
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.032
GPT teacher head0.323
Teacher spread0.290 · 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 teacher head, not a consensus.

Study designQualitative
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

Citations0
Published2025
Admission routes1
Has abstractyes

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