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Record W2790358757 · doi:10.1017/s0272263117000407

INCIDENTAL VOCABULARY ACQUISITION THROUGH VIEWING L2 TELEVISION AND FACTORS THAT AFFECT LEARNING

2018· article· en· W2790358757 on OpenAlex

Why this work is in the frame

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

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueStudies in Second Language Acquisition · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicSubtitles and Audiovisual Media
Canadian institutionsWestern University
Fundersnot available
KeywordsVocabularyMeaning (existential)RecallReading (process)PsychologyAffect (linguistics)Vocabulary developmentIncidental learningRelevance (law)LinguisticsVocabulary learningCognitive psychologyCommunication

Abstract

fetched live from OpenAlex

Abstract Research has begun to demonstrate that L2 words can be learned incidentally through watching audio-visual materials. Although there are a large number of studies that have investigated incidental vocabulary learning through reading a single text, there are no studies that have explored incidental vocabulary learning through viewing a single full-length TV program. The present study fills this gap. Additionally, three word-related variables (frequency of occurrence, cognateness, word relevance) and one learner-related variable (prior vocabulary knowledge) that might contribute to incidental vocabulary learning were examined. Two experiments were conducted with Dutch-speaking EFL learners to measure the effects of viewing TV on form recognition and meaning recall (Experiment 1) and meaning recognition (Experiment 2). The findings showed that viewing TV resulted in incidental vocabulary learning at the level of meaning recall and meaning recognition. The research also revealed that learning was affected by frequency of occurrence, prior vocabulary knowledge, and cognateness.

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.

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)0.000
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.059
GPT teacher head0.327
Teacher spread0.268 · 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