INCIDENTAL ACQUISITION OF MULTIWORD EXPRESSIONS THROUGH AUDIOVISUAL MATERIALS
Bibliographic record
Abstract
Abstract There has been limited research on the efficacy of captioned second language (L2) television in facilitating the incidental acquisition of multiword expressions (MWEs). The present study aims to fill this gap. Additionally, this study examines the role of typographic enhancement and repetition. One-hundred and twenty-two L2 learners were assigned to one of six conditions that differed in terms of caption condition (no captions, normal captions, enhanced captions) and the number of times they watched the same video (once, twice). The participants took a cued MWE form recall test before watching the video, immediately and 2 weeks after watching it. A content comprehension test was also administered. Compared to single viewing, repetition resulted in better content comprehension as well as better acquisition of MWEs. Both caption types positively influenced MWE recall relative to watching the video without captions, but typographic enhancement reduced the benefits of captions for content comprehension.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".