Captioned Instructional Video: Effects on Content Comprehension, Vocabulary Acquisition and Language Proficiency
Bibliographic record
Abstract
This experimental design study examined the effects of viewing captioned instructional videos on EFL learners’ content comprehension, vocabulary acquisition and language proficiency. It also examined the participants’ perception of viewing the captioned instructional videos. The 92 EFL students in two classes, who were undertaking the Tape and Video Interpretation course, participated in this study. The randomly assigned experimental class viewed 30 episodes of captioned Connect with English and the control class viewed the same episodes without captions. Adopting the quantitative approach, a Michigan English Test, Content-Specific Tests and a questionnaire were administered to examine the participants’ content comprehension, vocabulary acquisition and language proficiency development as well as the experimental group’s perception towards viewing captioned instructional videos. Although, both groups recorded gains, the findings were in favor of the use of captioned instructional videos. The results showed that the effects of viewing captioned instructional videos are greater on vocabulary acquisition and language proficiency development than on content comprehension. The participants’ perceptions of the use of captioned instructional video were consistent with the results. They felt that it enhanced their language learning, but did not affect their comprehension of the movie and that captions were not a form of distraction. Pedagogical implications for EFL instructions, especially where multimedia technology tools may be limited is that, captioned instructional videos can be deemed as a promising media to enhance language learning.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".