PROCEEDINGS of the
23rd International Congress on Acoustics
9 to 13 September 2019 in Aachen, Germany

Well-being and noise annoyance outcomes from first graders andrelationships with classroom acoustics
Arianna ASTOLFI1, Giuseppina Emma PUGLISI1, Andrea PRATO2, Silvia MURGIA1, Greta
MINELLI1, Tiziana SACCO3
1
2
3

Department of Energy, Politecnico di Torino, Turin, Italy

INRiM - National Institute of Metrological Research, Turin, Italy

Department of Neuroscience, Università degli Studi di Torino, Turin, Italy

ABSTRACTThe question on the extent to which environmental noise exposure and excessive reverberation affectwell-being of children at school is still largely unexplored. Younger children of kindergarten and primaryschool can suffer more than older pupils of well-being and related mental health issues. Well-being measures
are focused on self-esteem, emotional health and resilience, quality of the relationships with friends andfamily, satisfaction of school, life satisfaction. Noise exposure to traffic noise was demonstrated to be
associated with mental health and behavioral problems in children, but nothing has been found until now that
relates noise and excessive reverberation at school with well-being and mental health issues, despite the bad
acoustic conditions that characterize classrooms in most of Europe. In this study well-being and noise
annoyance from different noise sources were investigated with a subjective survey based on validated
questionnaires. Twenty first-grade classes of primary schools located in Turin (Italy) participated in the study.
Over 367 answered the questionnaire. Classrooms were characterized by different reverberation times andnoise exposure. The happiness scale allowed to explore differences between happy and unhappy children.
Relationships with good and bad classroom acoustics have also been investigated.
Keywords: School well-being, Noise disturbance, Classroom acoustics

1. INTRODUCTION
The World Health Organization (WHO) states that the school environment is a vehicle for healthpromotion. Focusing on the effects of the acoustic environment at school, it recognizes that high levelsof noise can degrade the socio-emotional development of students as well as they can generate
physical disturbs such as discomfort and headaches. Yet, negative consequences of a poor acoustic
environment are particularly strong for those children with learning difficulties who are typically
included in regular classes [1]. Unfavorable acoustic environments in classrooms, in fact, determine
challenging environments for children, who are more sensitive than adults or older peers to noise andreverberation when performing tasks that involve listening comprehension and non -auditory features
such as short-term memory, reading and writing [2]. As results, bad acoustics determines lower speech
intelligibility scores, mostly for first graders [3,4], degradation of the accuracy in identifying andproducing newly learned words [5], reduced reading speed of second graders [6] and lower scores inthe standardized tests of literacy, mathematics, and science for pupils aged 7-11 years [7].
As abovementioned, many studies are available in literature on the relationship between classroom
acoustics and teaching and learning process, even at the lowest grades of education. Conversely, amain lack in the available literature is related to the little number of studies has deepened the extent towhich classroom acoustics, particularly poor acoustics, and the perception of disturbance due to noise
affect the self-reported well-being of young aged children at school. Epstein & McPortland [8] andTobia et al. [9] reported that the well-being of primary school pupils is positively influenced bylearning skills, which in turn are negatively influenced by bad acoustics [6].
When noise distractors are present in a classroom, pupils’ ability to understand can be degraded andthe subjective perception of the sound environment can be different from a listener to another. Throughthe administration of questionnaires towards primary school children, Shield & Dockrell [10] reported

5910

that pupils were annoyed more as the external noise level increased, then resulting in a reduced ability
to hear the teacher speaking inside the classroom. To corroborate and go further to this result, Astolfi& Pellerey [11] proved that greater noise annoyance was observed across students when a noise source
was internal in the classroom, i.e. other students talking in the classroom. Recently, Brännström et al.
[12] investigated on the students’ personal ratings of perceived noise in order to improve theclassrooms’ design, finding a strong direct relationship between noise annoyance and verbal
processing demand. Thus, it is evident that the learning process is affected by the sound environment.
However, the subjective perception of it can bring to light other aspects and comorbidities that go
beyond the students’ performance at school. In fact, the perceived well-being at school plays a crucialrole that still needs insights, particularly at the earlier stages of education.
Going beyond the available knowledge is therefore necessary. Most of the previous studies on
well-being for children aged less than 11 years are instead based on questionnaires administrated toparents or filled in by parents or children at home, and to the Authors’ knowledge, only few works areavailable so far in literature that carried out well-being and noise disturbance surveys with first graders
at school. This work is a pilot study that has the main aim of contributing to the knowledge related tothe perception of well-being and noise disturbance at school. A questionnaire was properly designed at
this work’s aim, being based on Dockrell & Shield [10], Astolfi & Pellerey [11] and Sabri et al. [13].
The subjective impressions were analyzed in relationship to classroom acoustic features, particularly
to reverberation time that has been used to discriminate classrooms into “good” or “bad” acoustics.

2. METHODOLOGY
2.1 Participants (subjects, schools and classes)
A total number of 367 pupils with parental consent from 20 first-grade classrooms belonging to 10
primary schools in Turin took part in the study. Twenty-seven children were excluded from thecomplete dataset due to cognitive or hearing deficits, or due to the incorrect completion of thequestionnaires. Pupils (55% male, 45% female) were aged 6 years (62%), 7 years (37%) and 8 years(1%). The 77% of them was Italian mothertongue, whereas the other 23% reported to speak anotherprimary language in their family context (i.e. Romanian, Moroccan, English, German, Spanish,
Albanian, Egyptian). Numerosity and demographic information are shown in Figure 1.

Number of pupils

15
12
9
6
3
0
G2 (95%)H4 (85%)H3 (90%)H2 (87%)

H1 (76%)

A3 (79%)C1 (33%)B1 (91%)L2 (96%)

L1 (86%)I1 (100%)

A2 (61%)A1 (67%)

E2 (67%)G1 (75%)F2 (44%)F1 (67%)E1 (74%)

D2 (76%)

D1 (72%)class ID

Figure 1 – Male and female students per each classroom (black and grey, respectively), and percentage of
Italian mothertongue subjects, class-by-class in brackets.
As far as the involved schools and classes is concerned, school buildings presented significant
differences in terms of urban location, period of construction and architectural features. They were all
located in the city area of Torino (northern Italy), presenting different characteristics because of theirproximity to parks or to trafficked streets, and because of the internal geometry of classrooms withvolumes that varied between 120 m 3 and 290 m3 .
2.2 Classrooms acoustic parameters
Acoustic measurements were performed in the last two months of the school year. Measurements5911

were carried out under occupied conditions, with children inside that were on average 18 across allclasses. The adopted protocol regarded the acquisition of acoustic parameters that are useful tocharacterize the classroom’s response to easy listening. Particularly useful for the aims of the present
work, the acoustic parameters of reverberation time and noise level during a silent activity in the room
were acquired, and their measurement procedures are hereby detailed.
Reverberation time (T20, s) was measured according to ISO 3382-2 [14]. Room impulse responses
were acquired from three repeated 3 s exponential sine sweep signals, which were emitted by a
TalkBox (by NTi Audio, Schaan, Liechtenstein) and recorded by a calibrated class-1 sound level meter(SLM, model XL2 by NTi Audio, Schaan, Liechtenstein) in several measurement points inside of eachclassroom when occupied. Frequency averages were calculated according to DIN 18041 [15] in therange 0.25-2 kHz.
Background noise level (L N , dBA) was considered in terms of indoor A-weighted equivalent soundpressure level (LAeq ). Repeated measurements were performed based on 3 min acquisitions [16]. For
this measure, the SLM was located in two or three positions in each classroom. Noise measurements
were carried out with children in silence, L N,sil. According to Shield & Dockrell [7] and BB93 [17],LN,sil recommended value must be less than or equal to 35 dBA.
2.3 Questionnaires
The subjective impression of well-being and noise disturbance was evaluated with children in theirown classes by means of two separate questionnaires. Each survey was given to the pupils and a
trained researcher, together with the teacher, assisted the compilation after each question was read
aloud by a child in turn who was then asked to explain its meaning. In such a way, if it was unclear or
not understood by all the classmates, an intervention by the teacher was required in order to clarify thequestion. In both questionnaires, items were adapted for the age of the involved children (i.e. 6 years),considering their readability, comprehension and ease of administration. Using a back-to-backtranslation, an Italian version of the questionnaires was obtained translating the questionnairedeveloped by Sabri et al. [13], suitable for young people with special educational needs, to assess
perceived well-being assessment, while the questionnaire on noise disturbance was adapted on thebase of the work by Dockrell & Shield [10] and by Astolfi & Pellerey [11]. Questionnaires were filled
in during sessions of about 40 min during one day in May 2017 and May 2018.
Well-being questionnaire
The well-being questionnaire started with an introductory section that consists in five items onsocio-demographic information such as age, gender, number of people living at home, the quietest
place known by the individual, primary language spoken in family. Finally, the last item of the section
and the questionnaire is an open question where the child is asked to report an opinion about the
feelings of their school sound environment. Then the questionnaire presents five sections: (1)self-esteem (questions Q1_WB, Q2_WB, Q3_WB); (2) emotional health (questions Q4_WB, Q5_WB,
Q6_WB); (3) relationship at home and with friends (questions Q7_WB, Q8_WB, Q9_WB); (4)enjoyment of school (questions Q10_WB, Q11_WB, Q12_WB); (5) scale of happiness (question
Q13_WB). Sections 1 to 4 consist in three questions each, where a three -point ordinal scale allows tochoose the accordance among the options (a) yes, (b) not sure or (c) no, where (a) corresponds to a
positive feeling and (c) to a negative feeling. For section 5 the evaluation scale consists in a 11-point
scale, where pupils had to put a cross on the number of an illustrated stair corresponding to theirperceived level of happiness where 0 corresponded to be very unhappy and 10 to be very happy. A
visual feedback with sketches and emoticons helped in the compilation of the questionnaire.
Noise questionnaire
The noise questionnaire contained three sections: (1) perceived disturbance of specific noise
sources (traffic, car sirens, internal noise and natural noise, respectively; questions Q1_N, Q2_N,
Q3_N, Q4_N), (2) perceived intensity and disturbance of noise during school activities performed
either in silence (questions Q5_N, Q6_N) or in group (questions Q7_N, Q8_N), (3) perceived voice
quality under two situations, that is, while a classmate asks a question or while the teacher explains(questions Q9_N, Q10_N). The described sections were associated with three-point ordinal scales of
evaluation, in which the judging items typically varied from the less (1) to the most (3)intense/disturbing response on noise source or good (1) to bad (3) voice quality. As in the well-being
questionnaire, figures and emoticons were used to make it easier to iden tify the type of noise being

5912

investigated and a symbology that facilitated the indication of the perceived disturbance. Finally, thelast item of the questionnaire consisted in an open question where the child was asked to optionally add
comments.
2.4 Statistical methods
The statistical analysis was carried out with SPSS (IBM Statistics 20, IBM, Armonk, NY, USA).
Outliers in the sample were identified applying two methodologies, namely one refer ring to thewell-being answers and the other to the noise answers. As far as the former is concerned, pupils weregrouped through a 2-means cluster analysis based on their answer to the happiness question “rate youractual happiness” (i.e. unhappy children for answers from 0 to 6, happy children for answers from 7 to10). Then, a logistic regression has been carried out considering the membership in the group as the
response variable and the other well-being answers as explicative variables, and the Cook’s distance,
for every pupil has been obtained. All the pupils with a Cook’s distance higher than 0.15 have beenrecognized as outliers. As far as the noise answers is concerned, outliers have been recognized for eachclass, by the corresponding box-plots related to the means of all the given answers.
The significance of the differences between happy and unhappy children in good and bad classroom
acoustics, related to several factors concerning well-being and noise, as well as the differences
between males and females, was assessed with the Mann-Whitney U Test (MWU), a test that is used
for two groups of independent observations. The relationships between the class average well-being
and noise disturbance scores and the acoustical parameters, were investigated through thenon-parametric and non-linear correlation analysis.

3. RESULTS
A preliminary analysis on the acoustic parameters measured in each classroom was performed andis hereby presented. Then, to assess a relationship between subjective impressions based on thedelivered surveys, the analyses adopted to identify outliers led to a final sample of 326 questionnaires
to be used. A furtherly reduced sample of 296 students, corresponding to the happy children only (i.e.
those who answered in the range 7-10 to the happiness question), were then used for the correlation
between the subjective and classes and schools’ characteristics. Unhappy children have been removed
from this analysis in order to have a more homogeneous sample.
3.1 Reverberation time and noise level in classrooms
Figure 2 shows the measured reverberation times class-by-class. A threshold of 0.8 s was adopted todiscriminate between good and bad acoustics, according to a number of recent studies that consider
this value as optimal for both the speaking and the listening tasks [18-22]. Therefore, 12 classes out of
20 resulted to be clustered as “bad acoustics”, and 8 classes as “good acoustics”.
2

T20occ (s)

1,5
1
0,5
0
D1 D2 E1 F1 F2 G1 E2 A1 A2

I1

L1 L2 B1 C1 A3 H1 H2 H3 H4 G2class ID

Figure 2 – Reverberation time in occupied condition (T20occ) class-by-class. Black and grey bins correspondto classes clustered as bad and good acoustics, respectively. Error bars represent T20occ standard deviations.
Similarly, Figure 3 reports the background noise levels measured class -by-class when children
were asked to be silent. In such a way it has been possible to capture the actual noisiness of all theclassrooms, which maintained their belonging to the bad or good acoustics cluster based on thereverberation time criterion.

5913

60

LN,sil (dBA)

55
50
45
40
35
30
D1 D2 E1 F1 F2 G1 E2 A1 A2

I1

L1 L2 B1 C1 A3 H1 H2 H3 H4 G2class ID

Figure 3 – Noise level measured while children were in silence (LN,sil) class-by-class. Black and grey bins
correspond to classes clustered as bad and good acoustics, respectively.
3.2 Perception of well-being and noise disturbance for males and females
A preliminary analysis has been performed that conceived the effect of gender on the subjective
perception of well-being and noise disturbance. Overall, no statistically significant differences were
found for all the inquired noise disturbance aspects between males and females. With respect to thewell-being perception, the only two aspects related to the emotional health that were felt significantly
different between genders were related to the questions “I feel pleased with myself” and “I am acheerful child”, which both resulted in lower values for males and higher for females, that is, males
have the perception of being more pleased with themselves and more cheerful than females.

yes (1) --- not sure (2) --- no (3)3.3 Perception of well-being and noise disturbance in good and bad acoustics
Figures 4 and 5 show the mean values of the answers to the questions related to the perception ofwell-being in good and bad acoustics given by happy and unhappy children, respectively. Similarly,
figures 6 and 7 show the mean values of the answers to the questions related to the perception of noise
disturbance given by happy and unhappy children, respectively.
In each figure there is a direct comparison between answers given by pupils in good and bad
acoustics. For happy pupils (figures 4 and 6), a tendency of measuring higher mean values, whichcorrespond to worse conditions, in bad acoustics compared to good acoustics was found. Significan tdifferences according to the MWU (p-values < 0.05), were found for the answers to the questions
Q6_N, Q7_N and Q8_N, which relate to noise disturbance during silence tasks, and to intensity anddisturbance during group activity, respectively. The results highlight the fact that noise in bad
acoustics, either from outdoor or indoor, can be perceived as more disturbing being more amplified byhigher reverberation. For unhappy students (figures 5 and 7) significant differences between answers
in good or bad acoustics were only found with respect to aspects related to well-being perception.
Particularly, differences were found for questions Q2_WB, Q5_WB and Q12_WB, which are related toself-esteem, emotional health and enjoyment at school, respectively.
3,0
2,5
2,0
1,5
1,0
0,5
0,0

question ID

Figure 4 – Happy students’ mean responses on the perceived well-being. Grey and black bins refer to answers
given in good (124 students) and bad (172 students) acoustics, respectively. Error bars are the standard
deviations across subjects.

5914

yes (1) --- not sure (2) --- no (3)

3,0
2,5
2,0
1,5
1,0
0,5
0,0

question ID

Figure 5 – Unhappy students’ mean responses on the perceived well-being. Grey and black bins refer toanswers given in good (15 students) and bad (15 students) acoustics, respectively. Error bars are the standard

yes (1) --- not sure (2) --- no (3)deviations across subjects.

3,0
2,5
2,0
1,5
1,0
0,5
0,0
Q1_N

Q2_N

Q3_N

Q4_N

Q5_N

Q6_N

Q7_N

Q8_N

Q9_N

Q10_N

question ID

Figure 6 – Happy students’ mean responses on the perceived noise disturbance. Grey and black bins refer toanswers given in good (124 students) and bad (172 students) acoustics, respectively. Error bars are theyes (1) --- not sure (2) --- no (3)standard deviations across subjects.
3,0
2,5
2,0
1,5
1,0
0,5
0,0
Q1_N

Q2_N

Q3_N

Q4_N

Q5_N

Q6_N

Q7_N

Q8_N

Q9_N

Q10_N

question ID

Figure 7 – Unhappy students’ mean responses on the perceived noise disturbance. Grey and black bins refer
to answers given in (15 students) and bad (15 students) acoustics, respectively. Error bars are the standard
deviations across subjects.
A correlation analysis between objective and subjective data for happy children revealed a positive
relationship between disturbance from noise coming from outside the classroom, and in particularfrom adjacent rooms and corridor (Q3_N), and the noise level measured when the chil dren were insilence, LAeq,sil. This relationship is showed in figure 8 as a linear regression between the consideredvariables, well underling as low indoor sound insulation is related to higher sound levels in classrooms5915

yes (1) --- not sure (2) --- no (3)and consistently higher perceived noise disturbance.
3,00
2,50
2,00
1,50
1,00

y = 0.09x - 2.84
R² = 0.345

0,50
0,00
35

40

45

50

55

60

LN,sil [dB]

Figure 8 – Linear regression between happy students’ mean responses to question Q3_N (i.e. “How muchsounds of radios or recorders coming from other classrooms or from the corridor disturb you?”) andmeasured noise level in silence (LN,sil).

4. CONCLUSIONSThis work investigated the relationships between objective parameters related to primary schoolclassrooms, i.e. reverberation time and noise as well as intrinsic classes characteristics, and thesubjective impression of students related to their perception of well-being and noise disturbance atschool. Results were obtained clustering the acquired data in terms of good or bad acoustics, based ona reverberation time threshold of 0.8 s that was set according to literature. Also, the sub jective
impressions of children were distinguished into answers from happy or unhappy students based on thejudgements provided to the scale of happiness question.
The most important outcomes of the study can be summarized as follows:̾ Happy children showed a tendency of giving more negative answers when they belonged classes inbad acoustics, compared to happy children in good acoustics, in the perception of noise disturbanceat school;
̾ Unhappy students were strongly influenced by good or bad acoustics only with respect to aspects
related to well-being, and particularly to self-esteem, emotional health and enjoyment at school;̾ The disturbance from noise coming from adjacent rooms and corridor was found to be strongly
correlated to the noise level measured when the children were in silence inside the classroom.

ACKNOWLEDGEMENTS
This work was funded by the Fondazione CRT of Turin (Italy) in the framework of “Io Ascolto 2”
and “Io Ascolto 3” Projects. The Authors are thankful to the teachers and school admin istrations thatmade this work possible, and to all the children who participated in the survey with enthusiasm.

REFERENCES
1.
2.
3.
4.
5.
6.

5916

Winblad U, Dudley E. Primary school physical environment and health: WHO Global School Health
Initiative. World Health Organization. (1997). http://www.who.int/iris/handle/10665/63720 (lastviewed, May 12, 2019)
Klatte M, Bergström K, Lachmann, T. Does noise affect learning? A short review on noise effects
on cognitive performance in children. Frontiers in Psychology (2013); 4:1-6.
Astolfi A, Bottalico P, Barbato G. Subjective and objective speech intelligibility investigations inprimary school classrooms. J. Ac. Soc. Am. (2012); 131(1):247-257.
Prodi N, Visentin C, Feletti A. On the perception of speech in primary school classrooms:
Ranking of noise interference and of age influence. J. Acoust. Soc. Am. (2013); 133(1):255-268.
Riley KG, McGregor KK. Noise hampers children’s expressive word learning. Language, Speech,and Hearing Services in Schools (2012); 43:325-337.
Puglisi GE, Prato A, Sacco T, Astolfi A. Influence of classroom acoustics on the reading speed: Acase study on Italian second-graders. J. Acoust. Soc. Am. (2018); EL141(2):EL144-EL149.

7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.

Shield BM, Dockrell J. The effects of environmental and classroom noise on the academic
attainments of primary school children. J. Acoust. Soc. Am. (2008); 123(1):133-144.
Epstein JL, McPartland JM. The concept and measurement of the quality of school life. American
Educational Research Journal (1976); 13(1):15-30.
Tobia V, Greco A, Steca P, Marzocchi GM. Children’s Wellbeing at School: A Multi-dimensionaland Multi-informant Approach. J. Happiness Stud. (2019); 20:841-861.
Dockrell JE, Shield B. Children’s perceptions of their acoustic environment at school and at home.
J. Acoust. Soc. Am. (2004); 115(6):2964-2973.
Astolfi A, Pellerey F Subjective and objective assessment of acoustical and overall environmental
quality in secondary school classrooms. J. Ac. Soc. Am. (2008); 123(1):163-173.
Brännström KJ, Johansson E, Vigertsson D, Morris DJ, Sahlén B, ad Lyberg-Åhlander V. How
children perceive the acoustic environment of their school. Noise Health (2017); 19(87):84-94.
Sabri F, Rotheroe A, Kazimirski A. Measuring the well-being of young people with special
educational needs. New Philanthropy Capital report (2015).
ISO 3382-2 (2008). “Acoustics: Measurement of Room Acoustic Parameters—Reverberation
time in ordinary rooms” (International Organization for Standardization, Geneva, Switzerland)
DIN 18041 (2016). “Hörsamkeit in Räumen—Anforderungen Empfehlungen und Hinweise für
die Planung” (“Acoustic quality in rooms—specifications and instructions for the room acoustic
design”) (German Institute for Standardisation, Berlin)
Puglisi GE, Astolfi A, Cantor Cutiva LC, Carullo A. Assessment of indoor ambient noise level inschool classrooms. Proc EuroNoise2015; 31 May – 3 June 2015; Maastricht, NL 2015. p.715-20.
WSP (2015). Acoustic Design in Schools: Performance Standards Building Bulletin, BB93
(Department for Education and the Educational Funding Agency, London)
Sato H, Bradley JS. Evaluation of acoustical conditions for speech communication in working
elementary school classrooms. J. Acoust. Soc. Am. (2008); 123(4):2064-2077.
Bottalico P, Astolfi A. Investigations into vocal doses and parameters pertaining to primaryschool teachers in classrooms. J. Ac. Soc. Am. (2012); 131(4):2817-2827.
Pelegrín-García D, Brunskog J, Rasmussen B. Speaker-oriented classroom acoustics design
guidelines in the context of current regulations in European countries. Acta Acust. Acust. (2014);
100:1073-1089.
Puglisi GE, Cantor Cutiva LC, Astolfi A, Carullo A. Four-day-follow-up study on the voice
monitoring of primary school teachers: Relationships with conversational task and classroom
acoustics. J. Acoust. Soc. Am. (2017); 141(1):441-452.
Calosso G, Puglisi GE, Astolfi A, Castellana A, Carullo A, Pellerey, F. A one-school year
longitudinal study of secondary school teachers’ voice parameters and the influence of classroom
acoustics. J. Acoust. Soc. Am. (2017); 142(2):055-1066.

5917