Impact of classroom noise on reading and vocabulary skills in elementary school-aged children
Bibliographic record
Abstract
Classroom noise levels often exceed recommendations and, in large scale retrospective studies, it has been suggested that higher noise levels often correlate significantly with poorer academic performance [e.g., Shield., et al. (2002)]. However, experimental data on the performance of individual children are limited. This study therefore examined the effect of noise on the performance of children in grades 3–4 and 7–8 on standardized tests of oral reading, silent reading, and vocabulary (the Gray Oral Reading Test, the Gray Silent Reading Test, and the Peabody Picture Vocabulary Test). Each child completed parallel forms of a test in quiet and in classroom noise presented at 60 dB SPL. Required speech was presented at +10 S/N. Results from grouped data showed significantly reduced performance in noise only on the silent reading task and only for the older group of children. However, across tasks, when the effects of noise were evaluated as a function of childrens quiet performance levels, the noise effect was shown to be significant for the children performing at above average levels in quiet. These findings suggest that the effect of classroom noise may vary significantly across tasks and children. [Work supported by CLLRNet.]
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".