The effects of prosody instruction on listening comprehension in an EAP classroom context
Bibliographic record
Abstract
In many English language teaching contexts, listening activities resemble listening comprehension tests. Scholars have argued that this product-oriented approach is not particularly effective in helping learners improve their listening skills and have advocated for the inclusion of instruction that targets specific features of spoken language. The current study tested these claims in the context of an English-for-academic-purposes (EAP) listening and speaking course. Sixty-four post-secondary learners of English were randomly assigned to one of two groups. In addition to their regularly scheduled listening activities, one group received 100 minutes of instruction for two prosodic features (paratone and prosodic phrasing), while the other group received an equal amount of product-oriented listening instruction. After the instructional treatment, learners in the prosody group outperformed those in the product-oriented group on comprehension of the target prosodic features, and on general listening proficiency tests. It is argued that short periods of instruction targeting prosodic features can improve the effectiveness of traditional product-oriented EAP listening instruction.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".