Investigating the effect of educational equipment noise on smart classroom acoustics
Bibliographic record
Abstract
Numerous studies have been carried out highlighting and investigating the acoustics o f conventional classrooms for good Speech Intelligibility (SI).However, with the rapid advances in education and instructional technology a new generation of high-tech classrooms referred to as "smart classrooms" is emerging and becoming a necessity at educational institutions.This paper describes the features o f smart classrooms which make them different from traditional ones, focusing particularly on the Background Noise (BN) generated by instructional equipment.Measurements were conducted in similar classrooms to assess the magnitude and characteristics o f generated noise.With the instructional equipment in operation, acoustical measurements revealed an appreciable increase in the ambient noise level.A computer model o f a typical smart classroom is developed to investigate the appropriateness o f the classroom layout and surface finishes as recommended by the Acoustical Society o f America (ASA) [8].To determine the impact o f the resulting BN on SI in such specialized enclosures, simulations o f a classroom model with the recommended surface finishes under various BN conditions were carried out.Results showed that it is necessary to restrict the overall BN level to NC-25 (35 dBA), and emphasized the need to select quiet operating instructional equipment. s o m m a ir eDe nombreuses études ont été faites ayant pour but d 'exposer et d 'examiner les conditions acoustiques des classes conventionnelles en vue d 'y assurer une bonne clarté de la parole.Cependant, avec les avancements rapides dans le domaine de la technologie éducative et didactique, une nouvelle génération de classes dotées de technologie de pointe, et nommées "classes intelligentes", commencent à émerger et devenir une nécessité pour les établissements éducatifs.Cette étude décrit les traits des classes intelligentes qui les rendent différentes des classes traditionnelles, en concentrant particulièrement sur le bruit de fond produit par les équipements didactiques.Des mesures ont été prises dans des classes semblables afin de déterminer le niveau et les caractéristiques du bruit ainsi produit.Avec les équipements didactiques en cours d 'usage, les mesures acoustiques ont révélé un accroissement notable du niveau du bruit ambiant.Un modèle d 'ordinateur représentant une classe intelligente typique a été établi pour étudier la convenance du plan de la classe et du poli des surfaces en conformité avec les recommandations de la Société Acoustique de l 'Amérique (ASA) (8).En vue de déterminer l 'effet du bruit de fond causé par le bruit des équipements didactiques sur la clarté de la parole dans de tels espaces fermés, des simulations du modèle de classe susmentionné avec de différents polis de surfaces sous différentes conditions de bruit de fond ont été menées.Les résultats ont révélé qu'il est nécessaire de limiter le niveau global du bruit de fond à NC-25 (35 dBA).Ils ont de même souligné le besoin de choisir des équipements didactiques silencieux.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".