Audiovisual translation in primary education. Students’ perceptions of the didactic possibilities of subtitling and dubbing in foreign language learning
Bibliographic record
Abstract
This paper investigates the use of Audiovisual Translation (AVT) as a didactic tool in primary education. Several studies confirm that subtitling and dubbing are beneficial for productive and receptive skills, vocabulary acquisition, translation competence, and learners’ motivation and engagement. However, research in the field has been devoted primarily to university students enrolled in translation and language programmes, and there is a dearth of papers exploring the use of AVT in early educational stages. This paper is intended to fill this gap by examining the perceptions of primary education students on the use of interlingual subtitling and creative dubbing in learning English at school. The sample includes 120 students from 10 public primary schools in Spain who participated in a 3-month teaching study. The research tool was a student questionnaire aimed at gathering their perceptions on the use of AVT; this survey was complemented with in-class observations. Results underline the favourable views students had on the use of AVT in language learning in primary education, with a slight preference for dubbing over subtitling. This outcome brings to the fore the educational possibilities of AVT, which may be a useful resource in language teaching.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
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".