Developing English Listening Skills for Comprehension Through Repetition Technique Using Podcast
Bibliographic record
Abstract
This research is a pre-experimental study conducted with the following objectives: 1) to investigate the efficiency of using podcast in developing English listening skills for; 2) to compare the achievement of English listening comprehension before and after the repetition technique using podcast; 3) to examine the satisfaction with the intervention of using the repetition technique with podcast to enhance English listening skills for comprehension. The sample group consisted of 41 second-year students. The selection of the sample group was done through purposive sampling, whereby the sample group had to meet the language proficiency standards of level A2 or B1 according to the Common European Framework of Reference for Languages (CEFR). The experimental period spanned 11 weeks, with a total of 22 hours. The research instruments were podcast clips, practice exercises, pre and post-tests, and satisfaction questionnaire. The research findings revealed that the efficiency of using podcast in developing English listening skills for comprehension exceeded the predefined criterion of 80/80, with a score of 88.51/86.59. Moreover, when comparing the scores for the post-test English listening skills for comprehension of students using the intervention of using the repetition technique with podcast to enhance English listening skills for comprehension, it was found to be significantly higher than the average pre-test scores at a statistical significance level of .05. Overall, the students expressed a high level of satisfaction with the intervention of using the repetition technique with podcast to enhance English listening skills for comprehension. The average satisfaction score was 4.50.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".