Assessing Aircraft Noise Conditions Affecting Student Learning, Volume 1: Final Report (2014) / Chapter Skim
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5.3 School Noise Data The exterior noise levels at target (noise-exposed) schools were estimated using the Integrated Noise Model (INM)
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through May were appended to the previous year's data for September through December, and combined into a file representing one school year. The naming convention selected is such that the year corresponding to the September through December portion is the year to which the school year designation refers.
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Note: Entries under N are number of school years, up to 9 each, for schools open and exposed to airport noise. Nmiss is the number of records for which the noise variable was not recorded.
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In using the annual average noise levels we are making the assumption that aircraft noise has a negative effect on learning that results in lower test scores, and not that the aircraft noise interferes with the tests themselves, although this may also be true. 5.4 Ambient Noise The potential effects of aircraft noise on student learning may also be influenced by the level of external ambient noise at a school site from non-aircraft sources.
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Figure 5-2. Distribution of Leq - Lamb at Target Schools.
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insulated in the years between 2001 and 2009 as shown in Table 5-3 Of these, 29 were open for at least 2 years before and after being insulated, and had test scores available. TABLE 5-3 Numbers of Sound Insulated Elementary Schools at US Airports 5.6.
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TABLE 5-4 Grades at Which Test Scores were Included for Each State in Each Year State Grades with Quantitative Tests Grades with Verbal Tests 2000 2001 2002 2003 2004 2005 2006 2007 2008 2000 2001 2002 2003 2004 2005 2006 2007 2008 AK 34..|345.|.4..|3...|345.|345.|345.|345.|.4..
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scores included in the study in addition to these indexes are scale scores, raw scores, median percentile scores, and normal curve equivalent scores. As the tests are different in different states, and may vary with years, the only valid comparisons of test scores are between schools in the same state in the same year.
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Demographic data were available from the government's Common Core of Data (CCD) for the large majority of the schools with test scores.
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and presented for each of the six scores. The pattern of missing test scores precludes multivariate analyses of systematic relations among the six scores.
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TABLE 5-5 Total Number of Schools and Districts Included in the Test Score Database Schools in District Districts Exposed Schools Comparison Schools Both* At least 2 exposed and 2 comparison schools 104 905 5281 12 1 exposed and at least 2 comparison schools 44 46 641 1 Fewer than 2 comparison schools 129 214 69 15 Total 277 1165 5991 28 *
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likely to be above average another year. If they are correlated, then the results obtained from any analysis method would underestimate the standard errors of the quantities in the model.
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Analyses were implemented using the GLM procedure (PROC GLM) in the Statistical Analysis System (SAS (r)
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Effects in this study are reported in terms of differences in average test scores of schools with different levels of exposure to aircraft noise6. These differences, or effect sizes, are reported in fractions of standard deviations of the distributions of school test scores across the schools in the various included states and years.
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TABLE 5-8 Summary of Estimated Noise Effects for Various Aircraft Noise Metrics Noise Metric Percentile Decrease in State Ranking No. of Target Schools Affected1 Airport Noise, Leq <1 All Ambient Noise, Lamb 3 All Total Noise, Ltot 3-4 All Average Maximum Level, LAmax ~1 All Average SEL ~12 All 4 80 8 25 5 22 5 71 10 dB increase 6 103 15 dB increase 9 30 (All Target Schools)
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Test scores show a much higher correlation with non-decibel airport noise metrics, such as Number of Events above a threshold, NA(L) , and Time Above a threshold, TA(L)
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Finally, estimates were made of the effect of sound insulation on student test scores. The obvious method of comparing scores immediately before and after sound insulation was introduced was hampered by the naturally occurring variation in scores from year to year, and a sample size limited to 29 elementary schools that were insulated within the study years for which test scores were available.
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The metric that shows the largest effect is the incremental level Ltot - Lamb for ambient levels greater than 50 dB. The Number of Events Above 70 dB, NA(70)
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individual truck noise, is localized and attenuates rapidly with distance due to shielding from buildings, unlike the noise from elevated aircraft.
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learning disappeared once the school had had sound insulation installed. The issue of the effectiveness of sound insulation in reducing learning deficits associated with aircraft noise was identified as a priority in the literature review undertaken for this project.
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