EFL Parents' Empowerment: Using Supplementary Videos for Engaging EFL Parents with Their Children in Meaningful Speaking Tasks at Home
Bibliographic record
Abstract
The traditional EFL classroom is no longer enough to provide sufficient possibilities for EFL learners' verbal engagement, which has become one of the most challenging for EFL teachers inside classroom settings. This study aims to extend EFL children's oral interactions outside classroom settings by providing their parents with bilingual explainer videos and video materials designed for this purpose. The study uses interviews, pretests, and posttests as tools for data collection, and participants of the control and experimental groups were taught the same content via the traditional method. However, the supplementary videos (explainer videos & video materials) were only used to be shown to the parents of the experimental group's participants. Data analysis revealed that the experimental group’s participants whose parents employed the supplementary videos outperformed much better than the control group's participants whose parents just depended on the students’ books. Hence, bilingual explainer videos and material videos are useful tools for helping EFL parents extend speaking practices with their children at home. The children's spoken performance in several areas of the language has improved dramatically. The participants progress from nodding their heads to delivering two complex phrases. Thus, it suggests designing supplementary videos to serve as a guide for EFL parents to engage in verbal interactive tasks with their children at home.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".