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Record W4243108826 · doi:10.22215/etd/2016-11476

Exploring the Potential of Subtitled Foreign Media for the Learning of Conventional Expressions

2016· dissertation· en· W4243108826 on OpenAlexaff
Shayna Lodge

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldArts and Humanities
TopicSubtitles and Audiovisual Media
Canadian institutionsCarleton University
Fundersnot available
KeywordsDramaVocabularyPsychologyMeaning (existential)Context (archaeology)Foreign languageExpression (computer science)LinguisticsChinese as a foreign languageTask (project management)Control (management)Mathematics educationComputer scienceLiteratureArtArtificial intelligenceEngineeringHistoryPhilosophy

Abstract

fetched live from OpenAlex

Subtitled media have been found to be a beneficial tool in the acquisition of second language vocabulary, particularly for beginner-level learners. The present study follows up on Koolstra and Beentjes' (1999) suggestion that subtitled media may also be helpful in learning expressions and their associated contexts. Six beginner-level learners of Japanese as a foreign language (JFL) were taught the same thirty conventional expressions taken from a subtitled Japanese television drama -a control group without pragmatic instruction and a treatment group viewing the drama while taking note of form, meaning, and context of the expressions, as per All participants were tested prior and subsequently with an oral discourse completion task (ODCT) and interviewed regarding their experiences. The results suggest that utilizing a target language television drama may be more beneficial than traditional methodology in multiple ways for learners both immediately and long-term.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.914
Threshold uncertainty score0.993

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

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 head0.127
GPT teacher head0.287
Teacher spread0.160 · 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 designTheoretical or conceptual
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

Citations1
Published2016
Admission routes1
Has abstractyes

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