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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2017. Assessing Aircraft Noise Conditions Affecting Student Learning–Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/24941.
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Ass ACKNOWLED This work was Research Prog Sciences, Eng COPYRIGHT I Authors herein persons who o Cooperative R purposes. Per FMCSA, FRA, product, metho uses will give a request permis DISCLAIMER The opinions a are not necess or the program The informatio edited by TRB essing GMENT sponsored by t ram (ACRP), w ineering, and M NFORMATION are responsibl wn the copyrigh esearch Progra mission is give FTA, Office of d, or practice. ppropriate ack sion from CRP nd conclusions arily those of th sponsors. n contained in t . Aircraf Le Q he Federal Avia hich is adminis edicine. e for the authen t to any previo ms (CRP) gran n with the unde the Assistant Se It is expected th nowledgment o . expressed or im e Transportatio his document w AC Web-Only t Noise arning– Mary Brad Sco Bur Cha ueen Mary Lo G Corn It tion Administra tered by the Tra ticity of their m usly published o ts permission to rstanding that n cretary for Res at those reprod f the source of a plied in this re n Research Bo as taken direct RP Docume Condit Case S Ellen Eagan ley Nicholas tt McIntosh HMMH lington, MA rlotte Clark University of ndon, UK ary Evans ell Universit haca, NY tion (FAA). It w nsportation Re aterials and for r copyrighted m reproduce ma one of the mate earch and Tec ucing the mate ny reprinted or port are those o ard; the Nation ly from the subm nt 34: ions Aff tudies London y Contrac as conducted t search Board ( obtaining writte aterial used he terial in this pub rial will be used hnology, PHMS rial in this docu reproduced ma f the researche al Academies o ission of the a ecting tor’s Final Rep hrough the Airp TRB) of the Na n permissions f rein. lication for clas to imply TRB, A, or TDC endo ment for educat terial. For oth rs who perform f Sciences, Eng uthor(s). This m Studen ort for ACRP Pr Submitted ort Cooperative tional Academie rom publishers sroom and not AASHTO, FAA rsement of a p ional and not-fo er uses of the m ed the researc ineering, and M aterial has not t oject 02-47 May 2017 s of or -for-profit , FHWA, articular r-profit aterial, h. They edicine; been

The National Academy of Sciences was established in 1863 by an Act of Congress, signed by President Lincoln, as a private, non- governmental institution to advise the nation on issues related to science and technology. Members are elected by their peers for outstanding contributions to research. Dr. Marcia McNutt is president. The National Academy of Engineering was established in 1964 under the charter of the National Academy of Sciences to bring the practices of engineering to advising the nation. Members are elected by their peers for extraordinary contributions to engineering. Dr. C. D. Mote, Jr., is president. The National Academy of Medicine (formerly the Institute of Medicine) was established in 1970 under the charter of the National Academy of Sciences to advise the nation on medical and health issues. Members are elected by their peers for distinguished contributions to medicine and health. Dr. Victor J. Dzau is president. The three Academies work together as the National Academies of Sciences, Engineering, and Medicine to provide independent, objective analysis and advice to the nation and conduct other activities to solve complex problems and inform public policy decisions. The National Academies also encourage education and research, recognize outstanding contributions to knowledge, and increase public understanding in matters of science, engineering, and medicine. Learn more about the National Academies of Sciences, Engineering, and Medicine at www.national-academies.org. The Transportation Research Board is one of seven major programs of the National Academies of Sciences, Engineering, and Medicine. The mission of the Transportation Research Board is to increase the benefits that transportation contributes to society by providing leadership in transportation innovation and progress through research and information exchange, conducted within a setting that is objective, interdisciplinary, and multimodal. The Board’s varied committees, task forces, and panels annually engage about 7,000 engineers, scientists, and other transportation researchers and practitioners from the public and private sectors and academia, all of whom contribute their expertise in the public interest. The program is supported by state transportation departments, federal agencies including the component administrations of the U.S. Department of Transportation, and other organizations and individuals interested in the development of transportation. Learn more about the Transportation Research Board at www.TRB.org.

Author Acknowledgments iii Author Acknowledgments This project reflects the very best of ACRP: a collaborative inquiry into a challenging problem, with a multi‐ disciplinary team of international experts; an engaged Project Panel; and a supportive TRB staff. Many thanks to  our educational research team of Charlotte Clark and Gary Evans, who provided academic research rigor and  perspective that complemented HMMH’s practical airport noise expertise. Thanks also to our great team of eager  and careful research observers, including: Daysi Analuisa, Araz Arakelyan, Marisa Patel, Adam Peng, Isabella  Cordova, Margil Fahit, Norma Tuynman, Jinah Chiang, Erin Sands, and Sara Montolla.  Finally, thanks to our Project Panel, who weathered a very long research project, focused on problem solving, and  provided insightful feedback at every step. Special thanks to Scott Tatro of LAWA, for making the measurements  around LAX possible; this project would not have happened without his intervention.

Summary iv Summary The effects of aircraft noise on children’s learning are a longstanding concern of parents, educators, and planners  living and teaching near airports. The focus of this study was to attempt to determine how the behaviors of  students and teachers are affected by this type of noise exposure. More specifically, the stated objectives were to:   Develop and implement a rigorous case study methodology to identify and measure those factors at the individual classroom, student, and teacher level that influence the impact of aircraft noise on student achievement, especially as it relates to reading comprehension.  Identify appropriate metrics that define the level and characteristics of aircraft noise that impact student achievement.  Develop practical guidance for use by decision makers on how to reduce the impact of aircraft noise on student achievement. The study team for this project was comprised of experts in aviation noise and experienced researchers in the field  of psychology: Professor Stephen Stansfeld and Dr. Charlotte Clark of the Queen Mary University of London, Dr.  Gary Evans of Cornell University, and Mary Ellen Eagan along with a team of consultants specializing in aviation  noise from HMMH.  Summary of Findings The primary interest of this research is the impact of aircraft noise on student and teacher classroom behaviors.   While it is challenging to provide conclusive results on this point given the complexity of the subject, a few key  findings are summarized here.  Additional context and explanation appear in the remainder of the Summary  and the main body of the report.     Classroom dynamics, particularly teacher behavior, are associated with fluctuations in external noise, (i.e., the study team found a correlation between aircraft noise events and teacher voice‐masking, which occurs when the teacher’s voice is distorted or drowned out by noise, or voice‐raising across the various noise metrics tested).  The findings suggest that even moderate levels of aircraft noise exposure can impact children’s learning experiences.  External noise seems to matter regardless of what the internal noise level is inside the classroom.  Teachers reported a negative impact of aircraft noise on students.  Specifically, 53% of teachers felt that aircraft noise interfered with teacher‐student communication, 51% felt that aircraft noise caused students to lose concentration, and 45% felt that aircraft noise negatively impacted the quality of their students’ work.  25% of teachers reported being at least slightly annoyed by aircraft noise.  Teachers in schools experiencing higher levels of aircraft noise were more likely to report negative impacts on student concentration due to aircraft noise.  Additional study would be beneficial in order to fully understand the link between aircraft noise and its effect on classroom behavior for both teachers and students.

Study D The study f and six fro of the airp to the sout in this dist from the m group.  The study  and extern Additional online surv classrooms (chronic) s Classroo The classro school to lo of indoor o session, on observer lo exterior no esign ocused on 11  m the Hawtho ort; they are s h of Lennox, w rict are not as  uch smaller H analyzed the r al noise levels ly, teachers re ey. Noise leve  simultaneous chool‐day nois m Observa om observatio g aircraft and bservers set u e classroom o gged the start ise and all per Figure ES‐ schools surrou rne District. Le ubject to noise ell away from heavily influen awthorne Airp elationship be  at the schools ported their at ls were assess  to the classro e exposure.  tions and n team consis  other noise e p a noise mon bserver watch  and end of al iods when the 1. Locations of nding Los Ang nnox District s  primarily from  the extended ced by noise f ort). For this r tween the beh . Observers in titudes and ex ed through dir om observatio Noise Meas ted of two ob vent outside o itor in their cla ed the teache l periods durin  teacher used   Study School eles Internatio chools are ver  arrival opera  runway cente rom LAX opera eason, Hawth aviors and att  individual cla periences rela ect measurem ns (acute) and urements servers inside f the school. P ssroom, as sh r(s) continuou g which the te a raised voice s in Relation t nal Airport (L y close to the  tions at LAX. T rlines, and be tions (though orne schools w itudes of stude ssrooms logge ted to aircraft ents outside t  using compu each classroom rior to beginn own below. Fo sly. Using a tab acher’s voice  . The other cla o LAX  AX), five from  ends of two ru he Hawthorn cause of their   they are subj ere chosen as nts and teach d student and  noise exposu he schools an ter modeling o  plus one pe ing the data co r each ninety let applicatio was masked b ssroom observ Sum the Lennox Di nways at LAX e District scho positioning, sc ect to some no  the study con ers and the in  teacher beha re through an  d within the  f long‐term  rson outside th llection, each  ‐minute obser n, the teacher  y classroom o er watched th mary v strict  , east  ols lie  hools  ise  trol  ternal  viors.  e  pair  vation  r  e 

children on distracted  classroom  Simultaneo the school noise even Teacher A voluntar mechanism SurveyMon survey que Noise M In addition noise expo These calc used to est of the scho Noise Leve represents exposure o also compu discreet no e at a time in  and the cause observation se us to each cla . The outside o ts and their so Survey y survey consis s was distribu key, an online stions were ba odeling  to the noise m sure at the sch ulations were  imate noise le ol days 2016.  l (LAeq 7 hour  total exposur ver the course ted for a varie ise events and two minute in  of the distract ssions were c ssroom observ bserver took n urces.  Figure ES ting of questio ted to all teac  survey tool, a sed on well a easurements ools using the based on actua vels at each sc Noise metrics  s) and externa e during an ap  of a full 24 ho ty of noise th  classroom be tervals.  The st ion using the t onducted.  ation session, otes on the g ‐2. Example of ns relating to hers at each sc nd provided i ccepted survey  collected duri  Federal Aviat l aircraft fligh hool for the p that were com l 24‐hour Equi proximate sch ur day. Time  resholds; thes haviors.   udent observ ablet applicat  an exterior no eneral noise e  Indoor Noise  teachers’ attit hool in both d n two waves to s in the behav ng the classro ion Administra t paths and op articular obse puted include valent Noise L ool‐day period Above (TA) an e metrics were er logged all in ion. A total of  ise observer c nvironment an  Monitoring S udes toward a istricts. Surve  all teachers i ioral science l om observatio tion’s (FAA) In erations statis rvation school  the external 7 evel (LAeq 24  , and the 24 h d Number of E  chosen to exa stances when 134 one‐and‐a ollected noise d logged the s etup  ircraft noise a ys were condu n all schools in iterature.  ns, the study t tegrated Nois tics for 2016 a ‐day as well as ‐hour school‐ hours); the 7 h our LAeq repr vents Above ( mine relation Sum  the student w ‐half‐hour   levels outside tart of all loud nd coping  cted via   both districts eam compute e Model (INM t LAX. The INM  the average o day Equivalen our LAeq  esents total no NA) metrics w ship between  mary vi as   of    . The d the  ).   was  f all  t  ise  ere -

Summary vii Analysis Two types of analysis were carried out with the acute noise data collected:   Analysis comparing measured noise levels over short‐time‐periods (1 second, 5 seconds, 10 seconds, 30 seconds) preceding the onset of a behavioral event such as teacher voice‐masking, or teacher voice‐raising.  Analysis comparing noise metrics across the entire test session to the total number of behavioral events observed. Multilevel regression statistical models taking into account the clustering of the data by class and school were then  used to examine the association between these noise metrics in periods prior to an event being observed (1s, 5s,  10s, and 30s, depending on the noise metric). These regression models estimate the increase in odds for an event  being observed (i.e., teacher voice‐masking or voice‐raising) given the specific noise metric of interest.   Analysis was also conducted comparing the number of aircraft noise events above set thresholds per hour when  a classroom session is being observed (defined as the Number Above or NA metrics), with the number of teacher  voice‐masking events observed in a classroom session per hour and with the number of teacher voice‐raising  events observed in a classroom session per hour.  Additional analysis was performed on the cumulative percentage of time the sound level exceeded certain  threshold levels during a classroom observation period (defined as the time above or TA metrics). These analyses  proved less effective than the NA metrics at capturing continuous noise exposure, and as such are only discussed  briefly.  Results Classroom Observations: Students The predominant source of distraction for students was other students, which accounted for 51% of the total  number of distraction events. The second largest source of distractions was “other” at 29%. This category includes  primarily distractions that the students cause to themselves, such as playing with various items and daydreaming.   Of particular interest to this study is the fact that there were no observed aircraft noise‐related distractions on  any day of the study period. The overall percentage of observed student distractions due to other transportation  noise was also very low, less than 1%.   It is possible that the study design, which limited student behavior observations to two minutes per student and  only one student at a time, may have resulted in observers “missing” student distractions from aircraft noise (i.e.,  in a classroom of 20, any number of students may have been distracted during a noise event, but the observer was  focused on a student who was not distracted). Additional research would be needed to draw conclusions.   Given the lack of meaningful observations of students, the student data were not carried forward for statistical  analysis.  Classroom Observations: Teachers A number of analyses were performed to evaluate effects of noise on teacher behaviors, including:   The relationship between aircraft noise events and the onset of masking of teacher’s voice or raising of teacher’s voice.  The relationship between aircraft noise and the number of times teachers raised their voice or teacher’s voice was masked per hour.

Summary viii Acute Noise Exposure and the Onset of Teacher Voice-Masking and Voice-Raising Events Analyses examined how acute noise exposure over short‐time periods (1 second, 5 seconds, 10 seconds and 30  seconds) related to the start of a teacher voice‐masking or voice‐raising event being observed. Internal and  external noise metrics were examined, focusing on LAeq and the TA metrics.  Internal and external LAeq metrics  (for 1, 5, 10, and 30 seconds) and internal and external TA metrics (for 55, 60 and 65 dBA) showed an association  with the onset of teacher voice‐masking events.  Increases in both internal and external LAeq and TA metrics were  associated with an increase in the odds that a voice‐masking event would occur. Internal LAeq metrics were  significantly associated with voice‐raising events, but external LAeq metrics were not. An increase in internal LAeq  increased the odds of a voice‐raising event.  The different findings for internal versus external LAeq in relation to the onset of teacher voice‐raising events may  indicate that voice‐raising is more strongly associated with internal noise levels than external noise levels. This  contrasts with the findings for voice‐masking events, where both internal and external LAeq showed associations.   There is consistency between the findings for the two external metrics, with the findings indicating that both  external LAeq and external TA were not associated with the onset of teacher voice‐raising events. This supports  the hypothesis that internal noise might be more important for teacher voice‐raising events. Again, the noise  metric time frame did not seem to greatly alter the strength of the associations observed.   Acute Noise Exposure and the Number of Teacher Voice-Masking Events The data was also examined by comparing the associations between the acute noise metrics from the classroom  sessions with the number of teacher voice‐masking events observed across the classroom session. For these  analyses, no teacher voice‐masking events were observed in 51% of the sessions, one event was observed in 22%  of the sessions, two events were observed in 10% of the sessions, and three or more events were observed in 17%  of the sessions.    Internal and external TA metrics were not significantly associated with an increased risk for observing one, two, or three or more masking events in a classroom session.  Internal NA60 and NA65 showed significant associations with the number of teacher voice‐masking events, but NA55, NA70, NA75, and NA80 did not.  External NA55, NA60, NA65, and NA70 showed significant associations with the number of teacher voice‐ masking events, but NA75 and NA80 did not. The study team found a lack of associations for internal NA metrics greater than 70 dBA and external NA metrics  greater than 75 dBA, which is probably indicative of the few events observed at these levels, resulting in low power  to test these associations in the data. Contrasting the NA and TA metric results, one interpretation of the findings  may be that it is the number of noise events per se, rather than the time spent above a certain noise threshold  that is more important for teaching voice‐masking events.  Acute Noise Exposure and the Number of Teacher Voice-Raising Events Associations of the NA metrics and TA metrics with the number of teacher voice‐raising events observed across the  classroom session were also examined. In these analyses, the mean internal NA per hour ranged from 19.7 at 55  dBA, falling to less than 1 at 80 dBA. The mean external NA per hour ranged from 22 at 55 dBA, falling to 2.5 at 80  dBA. No teacher voice‐raising events were observed in 63% of the sessions, one event was observed in 14% of the  sessions, two or more events were observed in 23% of the sessions.   Internal TA55, TA60 and TA65 were associated with the number of teacher voice‐raising events observed, but  external TA55, TA60 and TA65 were not.  A 1% increase in internal TA metrics (at TA55, TA60, and TA65) showed  an increased risk for one or more voice‐raising events. Comparing these findings across the increasing noise  metrics, it appears that the risk of observing voice‐raising events increases as the threshold level for the TA  metric increases.   Both internal and external NA metrics showed associations with the number of teacher voice‐raising events. A  one event increase in internal NA metrics was associated with a 11‐30% increase in the risk for observing zero to 

one voice‐ noise even one voice‐ a 9‐10% in Contrastin associated showed as raising eve important  Chronic A The model sample. A  and the ris  The dat maskin associa more t to one   The dat events. with a  one vo raising events, t increase in e raising events. crease in the r g the findings   with voice‐rai sociations with nts, and also s than the time ircraft Nois ed annual airc 1 dBA increase k for observing a suggest a do g events. Usin ted with an 80 han two voice voice‐masking a suggest a do  Using our est 130% increase ice‐raising eve Figure ES‐3  and a 11‐113% xternal NA me  A one noise e isk for observi for the NA and sing events, ye  voice‐raising uggest that in  above.  e Exposure raft‐only LAeq  in LAeq 24 ho  more than tw se‐response r g estimates, it  % increase in ‐masking even  events by 13% se‐response r imates, we cal  in risk for zer nts.  . Number of T  increase in t trics was asso vent increase  ng more than   TA metrics, w t for the exter  events. These  terms of exte  24 hour for ea urs increased  o voice‐mask elationship be was calculated  risk for one to ts. A 1 dBA in  and the risk f elationship be culate that a 1 o to one voice eacher Voice‐ he risk for obs ciated with an in external NA one voice‐raisi e observe tha nal noise met  findings conf rnal noise tha ch school ran the risk for ob ing events by 1 tween annual  that a 10 dBA  two voice‐m crease in LAeq or observing m tween annual 0 dBA increas ‐raising event erving more th  8‐20% increas 55, NA60, NA6 ng event.   t internal TA a rics only exter irm the impor t the number ged from 42.6 serving one to 7%.   external LAeq  increase in a asking events  24 hours incr ore than one external LAeq e in annual LA s and a 210%  Raising Events vs Outdoor LA an one voice‐ e in the risk fo 5, and NA70 w nd internal NA nal NA and no tance of intern  of events ma  dBA to 67.4 d  two voice‐ma  24 hours and  nnual LAeq 24  and a 170% in eased the risk   voice‐maskin  and the risk o eq 24 hours w increase in ris eq (per Class Sum raising event.  r observing ze as associated  were both  t external TA  al noise for v y be more  BA in the data sking events b the risk of voic  hours would crease in risk for observing  g event by 21% f voice‐raising ould be asso k for more tha room)  mary ix A one  ro to   with  oice‐   y 8%  e‐  be   for  zero  .    ciated  n 

Summary x Comparison of Findings Across Noise Metrics For the onset of events, all the internal and external noise metrics examined showed associations with the onset of  teacher voice‐masking events. All of the internal noise metrics, with the exception of internal TA55, showed  associations with the onset of teacher voice‐raising events, yet none of the external noise metrics showed  associations with the onset of teacher voice‐raising events.  For the number of events, both internal and external NA show associations with teacher voice‐masking and  teacher voice‐raising. External TA metrics showed no associations with teacher voice‐masking and teacher voice‐ raising. External TA metrics showed no associations with number of teacher masking events or teacher voice‐ raising events. Internal TA metrics showed associations with the number of voice‐raising events but not voice‐ masking events.  To some extent, we might expect to observe similar associations of all the internal noise metrics and of all the  external noise metrics, given the high correlations between noise metrics.  External noise seems to matter even when we control for internal noise. This means that regardless of how loud  it is inside, when noise levels outside increase, even in a well‐attenuated building, we observed teachers react.  Teacher Survey The teacher survey assessed a range of demographic factors, perceived health, noise annoyance, perceived  interference of noise on school activities, and the perceived impact of aircraft noise on student and teacher  behaviors. A total of 105 teachers from nine of the 11 observed schools participated in the teacher survey.   Perceived Health and Cognitive Failures One of the survey items completed by teachers was the Perceived Stress Scale (PSS), which assesses the  perception of stress in the past month. While there were few significant differences in PSS according to  demographic factors, it should be noted that females typically scored higher than males. No significant differences  were found when comparing schools exposed to external LAeq 24 hours above 55 dBA to those schools not  exposed to external LAeq 24 hours above 50 dBA.  Another portion of the survey contained the Cognitive Failures Questionnaire (CFQ), which assesses self‐reported  failures in perception, memory and motor function. Again, there were no significant differences in scores when  controlling for age, grade taught, school, years teaching in total, years teaching at the school, or the school  external LAeq. As with the PSS, the only significant factor was gender, as again, female respondents typically  scored higher than male respondents.   Noise Annoyance A portion of the survey focused on noise annoyance and asked teachers to rate the frequencies of occurrence as  well as the effects of noise events from aircraft, road traffic, and students.    81% of respondents reported sometimes, often or always hearing aircraft noise around their school(s), and 29% reported always hearing aircraft noise. Almost two‐thirds of the respondents reported not being annoyed by aircraft noise at all when teaching; however 25% of respondents reported being slightly, moderately, or very annoyed by aircraft noise when teaching.  There were no differences in aircraft noise annoyance levels based on demographic factors, however analysis found that teachers from schools that are exposed to 55 dBA external LAeq or higher from aircraft were seven times more likely to report aircraft noise annoyance at school than teachers from schools exposed to less than 50 dBA external LAeq from aircraft.  79% of respondents reported sometimes, often, or always hearing road traffic noise around their school, and 17% reported always hearing road traffic. Of these, 42% of respondents reported no road traffic noise annoyance, and 51% reported slight or moderate annoyance. There were no respondents who felt extremely annoyed by road traffic.

Summary xi  Of participants responding to questions on student‐caused noise, 45% reported being slightly, moderately, or very annoyed, compared with 48% who reported no annoyance. Noise Interference with School Activities Another section of the survey asked teachers about how noise affects classroom activities, and most reported  some interference from aircraft noise.    53% of respondents felt that aircraft noise interfered with communication between teachers and students and with students’ attention, 46% felt that aircraft noise interfered with students’ performance, and 45% felt that aircraft noise interfered with the quality of students’ work.  In comparison, 57% and 56% of the sample, respectively, felt that road traffic noise sometimes, often or always interfered with students’ attention and students’ concentration. 49% of the sample felt that road traffic noise interfered with communication between teachers and students, 34.3% felt that road traffic noise interfered with the students’ performance, and 31.9% felt it interfered with the quality of students’ work.  Overall, the percent reporting interference from aircraft noise and road traffic noise was similar for communication between teachers and students, students’ attention, and students’ concentration. More teachers reported aircraft noise interfering with students’ performance and the quality of students’ work, compared with reports for road traffic noise. There were strong associations between LAeq at school and reports of aircraft noise sometimes, often or always  interfering with school activities. Teachers from schools with LAeq above 55dBA from aircraft were 13 times more  likely to report interference with communication; nine times more likely to report interference with students’  attention; 15 times more likely to report interference with students’ concentration; 11 times more likely to report  interference with students’ performance; and 14 times more likely to report interference with the quality of  students’ work.  Impact of Noise on Student and Teacher Behavior Teachers were also asked about the impact of noise on student and teacher behavior.  More than half of teachers  surveyed reported that aircraft noise impacted teacher and student behavior.   Over half (51%) of respondents reported that aircraft noise caused students to lose concentration, and 26% felt that it caused students to chat and talk; however few teachers reported aircraft noise causing students to fidget and misbehave. 33% of teachers reported stopping speaking and 30% reported raising their voice when exposed to aircraft noise, while 11% reported doing nothing or ignoring the students’ change in behavior.  Teachers from schools with external LAeq above 55 dBA from aircraft were twice as likely to report raising their voice compared with teachers from schools with external LAeq below 50 dBA, but this association became non‐ significant after adjustment for age, gender, grade taught, and years teaching in school. Teachers from schools with LAeq above 55 dBA were four to five times as likely to report stopping speaking compared with teachers from schools with LAeq below 50 dBA.  Over half of respondents (51%) reported aircraft noise sometimes, often, or always causing them to stop explanations and 52% reported raising their voices as a result. Only 23% of teachers reported closing windows in response to aircraft noise.

Overall, te stopping e “other” ch below 50 d Conclu The study  the study d The classro relationshi  For the onset o showed showed  For the teache events  raising  greater  To som externa achers from sc xplanations, fi anges to how t BA.  sions did not show o esign, and no om observatio p between air  onset of even f teacher voic  associations   associations   number of ev r voice‐raising or teacher voi events but not  impact on lea e extent, we m l noise metric Figure ES hools with ext ve times more hey taught in  bservable stu t necessarily a n methodolog craft noise and ts, all the inte e‐masking eve with the onset with the onset ents, both inte . External TA m ce‐raising even  voice‐maskin rning than the ight expect to s, given the hig ‐4. Survey Res ernal LAeq ab  likely to repor response to ai dent distractio  defensible fin y we develop  various teach rnal and exter nts. All of the   of teacher vo  of teacher vo rnal and exter etrics showed ts. Internal TA g events. This   time spent ab  observe simi h correlations ults by Percen ove 55 dBA fro t speaking lou rcraft noise th ns from aircra ding.  ed for this stu er behaviors:  nal noise metr internal noise  ice‐raising eve ice‐raising eve nal NA show a  no associatio  metrics show suggests that  ove a given th lar association  between nois t of Respond m aircraft we der, and 14 tim an teachers fr ft noise, but it dy was sufficie    ics examined s metrics, with t nts, yet none  nts.   ssociations w ns with numbe ed association the number of reshold.  s of all the inte e metrics.   ents  re 16 times mo es more likel om schools wi  is possible tha nt to draw inf howed associ he exception  of the externa ith teacher vo r of teacher v s with the nu  aircraft noise rnal noise me Sum re likely to re y to report ma th external LA t this is a resu erences about ations with the of internal TA5 l noise metrics ice‐masking an oice‐masking  mber of voice‐  events may h trics and of al mary xii port  king  eq  lt of   the    5,    d  ave a  l the 

Summary xiii  External noise seems to matter even when we control for internal noise. This means that regardless of how loud it is inside, when noise levels outside increase, even in a well‐attenuated1 building, we are seeing teachers react. The teacher survey findings suggest the following:   Many of the schools included in the teacher survey can be considered to have low to moderate levels of aircraft noise exposure. Schools classified as having an external LAeq above 55 dBA ranged in exposure from 55 to 69 dBA, with few participants experiencing exposure greater than 65 dBA. The survey indicates that even at these levels of aircraft noise exposure, teachers are reporting an impact on teaching activities and student behavior, as well as noise annoyance responses. The findings suggest that even moderate levels of aircraft noise exposure can impact children’s learning experiences.  Despite the small sample size and the lack of teachers from schools with high levels of aircraft noise exposure, the validity of the survey is demonstrated by the associations observed, as hypothesized, between LAeq at school and key outcomes such as noise annoyance, interference with school activities, and student and teacher behavior. Suggestions for Future Studies A preliminary conclusion that can be drawn from the present data is that classroom dynamics, particularly teacher  behavior, are associated with fluctuations in external noise. Given the well documented effects of chronic noise  exposure from airport noise on children’s reading acquisition, an important next step would be to test whether  changes in noise‐related teaching behavior (e.g., noise masking, voice‐raising) can account for some of the noise‐ reading relations.  As discussed, we did not observe student distractions from aircraft noise. Modifications to the study design (i.e.,  longer observation periods and/or observations of all students simultaneously, possibly by video camera) might  produce different results.  The relationships between the various noise metrics and teacher outcomes examined here need to be replicated in  larger and more varied samples and in airports of varying operations. Additional research topics that would  increase our understanding of the relationship between aircraft noise and student learning include the following:   Examine the differences between mitigated and non‐mitigated classrooms.  Study schools with higher levels of noise exposure that had not been mitigated.  Conduct additional research on noise exposure and student distraction.  Replicate the teacher survey with larger samples and in different contexts (i.e. teachers from schools with higher levels of noise exposure).  Examine more closely how teacher reactions to noise influence teacher / student behavior.  Explore the relationship between teacher judgments about the impacts of aircraft noise on teaching activity and actual student behavior. 1 While there is no standard definition for “well‐attenuated,” it is used in this context to indicate any structure that  provides appreciable sound‐dampening to external noise. 

Contents xiv Contents 1  Introduction .............................................................................................................................................. 1  1.1  Overview of Research Need ............................................................................................................................... 1  1.2  Summary of Related Research ........................................................................................................................... 2  1.2.1  Road Traffic Noise and Aircraft Noise Exposure and Children’s Cognition and Health (RANCH Study) ............. 2  1.2.2  The Munich Study: A Prospective Study of Some Effects of Aircraft Noise on Cognitive Performance in  Schoolchildren .............................................................................................................................................................. 2  1.2.3  Effects of Aircraft Noise on Children’s Learning (FICAN).................................................................................... 2  1.2.4  ACRP 02‐26: Assessing Aircraft Noise Conditions Affecting Student Learning ................................................. 3  2  Site Selection and Data Collection Protocols ............................................................................................. 4  2.1  Acoustic Measurements ..................................................................................................................................... 4  2.2  Noise Level Predictions ...................................................................................................................................... 4  2.3  Classroom Observations ..................................................................................................................................... 5  2.3.1  Tablet Application .............................................................................................................................................. 5  2.4  Teacher Interviews/Survey ................................................................................................................................ 8  3  Statistical Methodology ............................................................................................................................ 9  3.1  Classroom Observation ...................................................................................................................................... 9  3.2  Teacher Survey ................................................................................................................................................. 10  4  Results .................................................................................................................................................. 11  4.1  Measured Noise Levels .................................................................................................................................... 13  4.2  Modeled Noise Levels ...................................................................................................................................... 17  4.3  Classroom Observations ................................................................................................................................... 21  4.3.1  Student Observations ....................................................................................................................................... 23  4.3.2  Teacher Observations ...................................................................................................................................... 25  4.4  Statistical Analysis ............................................................................................................................................ 26  4.4.1  Acute Noise Exposure and the Onset of Teacher Voice‐Masking Events ........................................................ 27  4.4.2  Acute Noise Exposure and the Onset of Teacher Voice‐Raising Events .......................................................... 28  4.4.3  Acute Noise Exposure and the Number of Teacher Voice‐Masking Events .................................................... 28  4.4.4  Acute Noise Exposure and the Number of Teacher Voice‐Raising Events ...................................................... 29  4.4.5  Chronic Aircraft Noise Exposure ...................................................................................................................... 30  4.4.6  Comparison of Findings Across Noise Metrics ................................................................................................. 30  4.5  Teacher Surveys ............................................................................................................................................... 32  4.5.1  Perceived Health .............................................................................................................................................. 34  4.5.2  Noise Annoyance .............................................................................................................................................. 35  4.5.3  Noise Interference with School Activities ........................................................................................................ 36  4.5.4  Impact of Noise on Student and Teacher Behavior ......................................................................................... 36  5  Conclusions and Recommendations ........................................................................................................ 37  5.1  Findings ............................................................................................................................................................ 37  5.2  Suggestions for Future Studies ......................................................................................................................... 37  6  References and Notes .............................................................................................................................39 

Contents xv Appendices Appendix A  Noise Measurement Protocol Memorandum………………………………………………………………………..A‐1  Appendix B  Data Modeled for Noise Predictions……………………………………………………………………………………..B‐1  Appendix C  Classroom Observation Protocol…………………………………………………………………………………………..C‐1  Appendix D  Teacher Survey…………………………………………………………………………………………………………………….D‐1  Appendix E  Observational Classroom Study Report…………………………………………………………………………………E‐1  Appendix F  Teacher Survey Report………………………………………………………………………………………………………….F‐1  Appendix G  Classroom Photographs………………………………………………………………………………………………………..G‐1  Appendix H  Glossary of Terminology……………………………………………………………………………………………………….H‐1  Figures Figure 1. Tablet Application Home Screen .................................................................................................................... 6  Figure 2. Tablet Application Session Configuration Screens .......................................................................................... 6  Figure 3. Tablet Application Teacher Observations Module ......................................................................................... 7  Figure 4. Tablet Application Student Observations Module .......................................................................................... 7  Figure 5. Tablet Application Noise Observations Module ............................................................................................. 8  Figure 6. Locations of Study Schools in Relation to LAX .............................................................................................. 11  Figure 7. Observed Outdoor Noise Events by Source .................................................................................................. 14  Figure 8. Observed Outdoor Noise Events by Source per District ............................................................................... 14  Figure 9. Aerial View of Washington Elementary School ............................................................................................ 15  Figure 10. Number of External Events above 55 dBA and 70 dBA Threshold per Hour by School ............................. 16  Figure 11. Percent of Time Above 55 dBA and 70 dBA Threshold by School .............................................................. 17  Figure 12. Percent of Time Above 55 dBA and 70 dBA Threshold by School (No Clipping)......................................... 22  Figure 13. Percent of Time Above 55 dBA and 70 dBA Threshold by School (30 Minute Clipping) ............................ 23  Figure 14. Student Distraction Sources by Count ........................................................................................................ 25  Figure 15. Observed Teacher Speaking Modes by Duration ........................................................................................ 26  Figure 16. Number of Participants by Aircraft‐only External LAeq 24 hours at School ............................................... 33  Figure 17. Distribution of PSS Scores ........................................................................................................................... 34  Figure 18. Distribution of CFQ Scores .......................................................................................................................... 35 

Contents xvi Tables Table 1. Study Summary by School .............................................................................................................................. 12  Table 2. Summary of Observation Sessions by School ................................................................................................ 13  Table 3. School‐day LAeq and Lmax for All Measured Data by School ........................................................................ 15  Table 4. Number of Aircraft Noise Events Above a Given Threshold (per Hour) ......................................................... 16  Table 5. Percent of Outdoor Time Spent Above a Given Threshold at Each School .................................................... 17  Table 6. Modeled Daily Aircraft‐only School‐day External LAeq by School ................................................................. 18  Table 7. Comparison of Measured to Modeled 7‐Hour External LAeq ........................................................................ 19  Table 8. Modeled Daily Aircraft‐only School‐day External Lmax by School ................................................................ 20  Table 9. Modeled Annual Aircraft‐only DNL, 24‐hour Lmax, 24‐hour LAeq, and School‐day LAeq ............................. 21  Table 10. Total Subject Time and Mitigation Status by School .................................................................................... 21  Table 11. Percent of Indoor Time Spent Above a Given Threshold (No Clipping) ....................................................... 22  Table 12. Percent of Indoor Time Spent Above a Given Threshold (30 Minute Clipping) ........................................... 23  Table 13. Grades of Observed Classrooms by School .................................................................................................. 24  Table 14. Total Time Learning vs. Distracted by School .............................................................................................. 24  Table 15. Summary of Teacher Observations by School ............................................................................................. 26  Table 16. Ranges of Mean Internal and External Noise Before a Voice‐Masking Event ............................................. 27  Table 17. Ranges of Mean Internal and External Noise Before a Voice‐Raising Event ............................................... 28  Table 18. Summary of Associations Observed Between Internal Noise Metrics and Key Outcomes .......................... 31  Table 19. Summary of Associations Observed Between External Noise Metrics and Key Outcomes ......................... 32  Table 20. Summary of Survey Respondents ................................................................................................................ 33  Table 21. PSS Data Availability ..................................................................................................................................... 34  Table 22. CFQ Data Availability .................................................................................................................................... 35  Table B‐1. Runway Data ............................................................................................................................................. B‐1  Table B‐2. Operations by Aircraft Type ...................................................................................................................... B‐2  Table B‐3. Runway Utilization .................................................................................................................................... B‐4 

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TRB's Airport Cooperative Research Program (ACRP) Web-Only Document 34: Assessing Aircraft Noise Conditions Affecting Student Learning–Case Studies attempts to determine how the behaviors of students and teachers are affected by aircraft noise exposure. The report identifies metrics that define the level and characteristics of aircraft noise that impact student achievement. It also develops guidance for use by decision makers on how to reduce the impact of aircraft noise on student achievement. The report is accompanied by a brochure on the Effects of Aircraft Noise on Student Learning.

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