Empirical prediction of the effect of classroom design on verbal-communication quality
Bibliographic record
Abstract
This study used empirical prediction models to investigate how verbal-communication quality in 'small', 'medium' and 'large' classrooms varies with classroom design, and identified the optimal designs.Verbalcommunication quality was quantified by the room-average speech intelligibility.The design parameters studied were the occupancy, the unoccupied background-noise level, and whether or not the rooms were carpeted, had ceiling and/or wall absorption, or upholstered seats.The design parameters were varied, and the following quantities calculated: average classroom surface-absorption coefficient at 1 kHz, 1-kHz earlydecay time, A-weighted background-noise level, and A-weighted speech-signal to background-noise level difference.The conditions under which optimal verbal-communication quality occurred were identified.Quality did not vary with absorption or early-decay time in any systematic way.High background noise, combined with either high absorption or low early-decay time, can lead to very low verbal-communication quality.Quality was low for negative values o f signal-to-noise level, but increased quickly for higher values.In the 'small' and 'medium' classrooms, the optimal verbal-communication quality occurred with carpeting and absorption, and with un-upholstered seats.In the 'large' classroom, the optimal quality occurred with carpeting, absorption and upholstered seats.The most significant design factor in determining the verbalcommunication quality o f the rooms was the background noise.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".