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Record W198006553

Sound Solutions: Poor Classroom Acoustics Are Impairing Students' Hearing and Their Ability to Learn. the Need for Audio Amplification Systems Is Coming through Loud and Clear

2007· article· en· W198006553 on OpenAlexaboutno aff
Neal Starkman

Bibliographic record

VenueT.H.E. Journal Technological Horizons in Education · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Technology Integration
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyComprehensionMathematics educationAudiologyComputer science
DOInot available

Abstract

fetched live from OpenAlex

square of the he calls some of the squares of the other two sides. Some students will tell you that's the Pythagorean theorem. No, they're not dumb; no, they don't have attention deficit disorder; and no, their teacher doesn't enunciate poorly. In many instances, even if they sit just six feet away from the speaker, they simply can't hear. The problem isn't one of volume. In fact, what usually happens in a classroom when students say they can't hear is that the teacher speaks louder. That may be fine for vowels, but it doesn't do much for consonants--and it's generally the consonants that provide the intelligibility: An oo ee i ats o? (Can you see why that's so?) And even a loud voice isn't likely to make it to the students in the back row if the classroom has bad acoustics. The only tangible result is usually teacher vocal strain. Rather, student hearing difficulties are largely the result of three factors: * A child's auditory neurological network isn't fully developed until around age 15. For purposes of comprehension, children require louder voices and a quieter ambience than adults do. * Classrooms are noisy. There's noise from other students, from computers and printers and lights and heating systems, and from people in the hallways and traffic outside. * Students don't have the experience to guess at what they hear. If they don't know the word hypotenuse, then they can't process hearing high moose as anything but high moose--they can't make the connection. And this is exacerbated if the student isn't a native English speaker or really does have a hearing deficit. The main problem, as Debbie Tschirgi, director of educational technology programs for Educational Service District 112 in Vancouver, WA, explains in her widely referenced white paper, Classroom Amplification Systems: Understanding and Overcoming the Acoustical Barriers to Learning, is inadequate signal-to-noise ratio in US classrooms, which impedes communication. She says that while the American Speech-Language-Hearing Association recommends a classroom noise level no higher than 30 decibels, the typical classroom has noise levels that range from 41 to 51 dB. (Keep in mind that loudness is measured on a logarithmic scale: A 40-dB classroom is 10 times as loud as a 30-dB classroom.) Tschirgi's research indicates that for teachers to communicate well, their voices--or signals--should be 15 decibels more than that of the background noise, a score of plus 15. But she finds that most classrooms have signal-to-noise ratios ranging from minus 7 to plus 4. A multiyear study conducted by Orange County Public Schools in Orlando, FL, Performance Schools Equals High Performing Students, provides a summary, damning state of affairs: Research has shown that a typical classroom provides an inadequate environment when auditory learning is the primary tool of instruction. As many as one-third of all students miss 33 percent of verbal communication in a typical Hearing Is Believing Technology has come up with a solution: tools that focus voices in a way that minimizes intrusive ambient noise and gets to the intended receiver--not merely amplifying the sound, but also clarifying and directing it. One provider of classroom audio technology is Audio Enhancement, which has a manufacturing relationship with Panasonic. Using an Audio Enhancement system, teachers speak into a microphone, and speakers transmit the voice throughout the classroom. Teachers can also hook up the system to computers, DVD players, VCRs, interactive whiteboards, and just about any other classroom tool. They can capture audio and put it on the internet. They can even tie everything into the school's public address system. For example, Audio Enhancement's CAE-100W classroom audio system, called Innovator, comes with four infrared microphones, multimedia mute control, and a PC user interface. …

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.050
Threshold uncertainty score0.167

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0050.003
Open science0.0010.004
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0500.026

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.

Opus teacher head0.066
GPT teacher head0.381
Teacher spread0.315 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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