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Record W2981206504 · doi:10.5539/ijel.v9n6p77

Is Listening Comprehension a Comprehensible Input for L2 Vocabulary Acquisition?

2019· article· en· W2981206504 on OpenAlexvenueno aff
Saud Mushait, Mohammed Ali Mohsen

Bibliographic record

VenueInternational Journal of English Linguistics · 2019
Typearticle
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsVocabularyActive listeningReading comprehensionReading (process)Listening comprehensionComprehensionComputer scienceLinguisticsNatural language processingCognitive psychologyPsychologyCommunication

Abstract

fetched live from OpenAlex

Vocabulary learning has received considerable attention from reading comprehension input in second language acquisition research. However, a little is known about vocabulary gains from listening comprehension input. This paper aims to review L2 vocabulary gains from listening comprehension input in comparison to reading comprehension and reading while listening comprehension activities. We search for the terms “vocabulary learning”, “vocabulary acquisition”, and “listening comprehension” in several international databases to elicit target studies. The target studies have been reviewed in terms of focus, methodology employed, L2 environment, type of participants, and findings. Results of the review found that vocabulary acquisition from listening comprehension input was significant—though less than reading input—for long run and could be stored in long term memory. Therefore, it could be retrieved more easily than vocabulary from reading comprehension input. Recommendations and suggestions for future research have been given at the end of the article.

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)0.000
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.313
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.000

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 head0.020
GPT teacher head0.334
Teacher spread0.314 · 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 designNot applicable
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

Citations3
Published2019
Admission routes1
Has abstractyes

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