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Record W3206974836 · doi:10.4995/eurocall.2011.16292

Enhancing ESL students' vocabulary acquisition through a meaningful filmmaking project

2011· article· en· W3206974836 on OpenAlexaffabout
Jia Li, Brenda C. McComb

Bibliographic record

VenueThe EuroCALL Review · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicSubtitles and Audiovisual Media
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFilmmakingScripting languageVocabularyComputer scienceDramaPedagogyMultimediaMathematics educationPsychologyLinguisticsVisual artsArt

Abstract

fetched live from OpenAlex

<p>This paper examines the impact on English learning, and in particular on vocabulary acquisition, through engaging ESL students in the filmmaking lifecycle. Twenty-three undergraduate ESL students with linguistically and culturally diverse backgrounds in a large Canadian university participated in this project. Participants from 15 majors were randomly divided into five drama groups, and contributed to screenwriting, acting, production and postproduction of the film.<br />The project outcomes show that filmmaking is a meaningful task which captivates students’ imagination, enhances their motivation, and facilitates their interaction through compelling multi-media . They further indicate that the filmmaking based on carefully written scripts, while at the same time allowing for personal interpretation of characters, is effective in creating an optimal learning environment for students’ English acquisition, particularly vocabulary.</p>

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.886
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0040.001

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 head0.145
GPT teacher head0.328
Teacher spread0.183 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2011
Admission routes2
Has abstractyes

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