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Journal of Environmental Psychology 40 (2014) 187e197

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Journal of Environmental Psychology

journal homepage: www.elsevier .com/locate/ jep

The impact of the classroom built environment on student perceptionsand learning

Gwen C. Marchand a, *, Nicholas M. Nardi a, 1, Douglas Reynolds b, 2, Stoil Pamoukov b, 2

a University of Nevada Las Vegas, Department of Educational Psychology and Higher Education, 4505 S. Maryland Parkway, Box 453003, Las Vegas, NV,89154, USAb University of Nevada Las Vegas, Center for Mechanical & Environmental Systems Technology, Thomas T. Beam College of Engineering, 4505 S. MarylandParkway, Las Vegas, NV, 89154, USA

a r t i c l e i n f o

Article history:Available online 5 July 2014

Keywords:Reading comprehensionListening comprehensionEnvironmental factorsStudent performance

* Corresponding author. Tel.: þ1 702 895 4303.E-mail address: Gwen.marchand@unlv.edu (G.C. M

1 Tel.: þ1 702 895 4303.2 Tel.: þ1 702 895 3807.

http://dx.doi.org/10.1016/j.jenvp.2014.06.0090272-4944/© 2014 Elsevier Ltd. All rights reserved.

a b s t r a c t

The aim of this 2 � 2 experimental study was to investigate whether the combined environmentalfactors of light, sound, and temperature in a classroom built environment set to comfortable levels or justoutside the comfort zone (OCZ) impacted undergraduate student learning, mood, and perceptions ofenvironmental influence on performance during listening and reading tasks. Results indicated thatparticipants in the OCZ listening condition had lower scores on a comprehension test than those in thenormal listening condition, but that no difference was detected between conditions for the readingmodality. Students in the OCZ condition reported more negative affect and believed that the sound andtemperature of the room had a more negative impact on their performance than those in the normalcondition. Participants in the reading conditions were more likely to attribute poor performance to thesound levels in the room than students in the listening condition.

© 2014 Elsevier Ltd. All rights reserved.

1. Introduction

The bioecological model of human development proposes thatindividual learning and psychological functioning are influenced bymultiple, nested layers of the context. Although not typically thefocus of the model (e.g., Bronfenbrenner & Morris, 2006), the builtenvironment can be considered a context for human development(Evans, 2003). Chaos or sub-optimal conditions in the built envi-ronment may interfere with the ability of individuals in school,work, or home environments to adequately process new informa-tion in a manner that will allow that information to be learned andretained (Maxwell, 2010). Effects of the built environment havebeen explored in relation to a wide range of human functioning,including cognitive processes (e.g., Hygge & Knez, 2001), affect(e.g., Loewen & Suedfeld, 1992), and mental health (Evans, 2003).The present study is focused on learning tasks typical in a class-room situation and psychological outcomes.

Higgins, Hall, Wall, Woolner, and McCaughey (2005) refer totemperature, lighting and acoustics as the “physical basics” of the

archand).

built indoor environment. In real world learning and workplaceenvironments it is unlikely that only one element in the built in-door environment would constitute a substandard setting but anegative environment may instead reflect more of a composite ofmultiple elements. For instance, the National Center for EducationStatistics (U.S. Department of Education, 2000) asked schools torank how satisfactory or unsatisfactory six different environmentalconditions were: lighting, heating, ventilation, indoor air quality,acoustics and physical security of the building. The survey revealedthat an average of 2.6 environmental conditions was reported un-satisfactory among the 43% of schools that reported at least oneunsatisfactory condition. In addition, 8% of schools rated all 6environmental conditions unsatisfactory (U.S. Department ofEducation, 2000).

The three elements of temperature, lighting, and acoustics arerarely addressed together in the same study (Higgins et al., 2005;Hygge & Knez, 2001). Researchers tend to focus on one elementin the environment or a combination of two environmental ele-ments in an effort to isolate the impact of each component and alsoto develop and test theory as to the processes underlying themechanism by which each element influences cognitive and psy-chological factors (e.g., S€orqvist, Stenfelt, & R€onnberg, 2012). Thebulk of research has focused on the individual negative impact thatnoise (Clark et al., 2006; Halin, Marsh, Hellmen, Hellstr€om, &S€orqvist, 2014; Hygge, Evans, & Bullinger, 2002; Jones, 1990;

G.C. Marchand et al. / Journal of Environmental Psychology 40 (2014) 187e197188

Kjellberg, Ljung, & Hallman, 2008; Seabi, Goldschagg, & Cockcroft,2010; S€orqvist, 2010; S€orqvist, Halin,&Hygge, 2010; Stansfeld et al.,2005), temperature (Wargocki & Wyon, 2007; Zeiler & Boxem,2009), and lighting (Barkmann, Wessolowski, & Schulte-Markwort, 2012; Dunn, Krimsky, Murray, & Quinn, 1985; Knez,1995) have on learning and psychological outcomes. To the best ofour knowledge there is only one study that has explored thesethree environmental factors and their influence on student per-formance. Hygge and Knez (2001) examined the interaction be-tween lighting, temperature, and noise on attention, problemsolving and affect. They discovered an interaction between noiseand heat, as well as light and noise on cognitive performance onreading tasks.

Although it is important to understand the unique effect ofdifferent environmental factors on student learning, a moreecologically valid approach to examining the classroom environ-mentmay be to consider multiple factors in combination to create acomposite representing the built environment in order to betterunderstand the overall influence on human learning(Bronfenbrenner & Crouter, 1983; Bronfenbrenner & Morris, 2006;Maxwell, 2010). Further, recent research has called for laboratory-based studies to include tasks similar to those experienced by in-dividuals in real-world situations, such as complex readingcomprehension tasks, when studying the impact of built environ-ment (Halin et al., 2014; Oswald, Tremblay, & Jones, 2000; S€orqvistet al., 2010). Thus, the purpose of the present study was to examinethe effects of a simulated classroom environment with sound,temperature, and lighting parameters within a normal range forcomfort and an environment with conditions set just beyond thelimits of a normal comfort zone (OCZ) on student comprehension,mood, and perceptions of the environment following a moderatelydifficult reading or listening task.

1.1. Complex cognitive tasks

Research on the effects of the built environment frequently use avariety of memory and learning tasks as outcome measures (seeBeaman, 2005 for a review on noise). When considering how thephysical environment impacts learning, compelling contributionshave been made by researchers studying the relationships amongstsound, working memory, and attention. Researchers have investi-gated task complexity and difficulty (Halin et al., 2014), type ofsound (e.g. speech and non-speech; Oswald et al., 2000; S€orqvist,2010), intensity of sound (Loewen & Suedfeld, 1992), and timingof environmental stimuli (Hughes, Hurlstone, Marsh, Vachon, &Jones, 2013), among other factors (Beaman, 2005; S€orqvist et al.,2012). Findings have emerged to suggest that the effects of noiseon cognitive processes are nuanced and complex.

One such nuance is the nature of the cognitive task (Beaman,2005), as the tasks in sound studies range from memory for wordlists to reading comprehension tasks. In the classroom environ-ment, students are faced with multiple tasks, including reading forcomprehension and listening for comprehension. For examplestudents may be asked to read quietly to themselves or studentsmay listen to lecture. Reading and listening comprehension areconstructive processes “involving an interaction between incomingdiscourse (text or speech) and the reader or listener's priorknowledge” (Royer, 2001, p. 30). Comprehension occurs when areader or listener can remember the meaning of what was heard orread. For individuals to be able to construct meaning, text must beefficiently processed on multiple levels; organized from micro-structure, the sentence structure used to represent the meaning ofthe text; to macrostructure, the higher-order organization of thetext into larger sections; to the situation model, or the meaning ofthe text interpreted with respect to prior knowledge, goals, and

other individual characteristics (Kintsch, 2004). The ultimate goalassociated with classroom learning is typically focused on the levelof the situation model, or whether the text was understood andwell integrated with an individual's background knowledge.

The most consistent negative effects for task-irrelevant soundon reading comprehension in late adolescent and undergraduatepopulations have centered on task-irrelevant speech (Oswald et al.,2000; S€orqvist, 2010; S€orqvist et al., 2010). Other types of back-ground noise, particularly noise that is consistent, may not besufficiently distracting to disrupt attentional processes associatedwith learning new information, but at the same time, may beslightly more negative than silence (Oswald et al., 2000; S€orqvist,2010). The effects of noise, particularly task-irrelevant speech,may be qualified by individual differences in working memory ca-pacity (S€orqvist & R€onnberg, 2012) as well as task difficulty. Forinstance, recent research has found that task difficulty buffered theeffect of irrelevant background speech on memory for prosereading tasks (Halin et al., 2014). The authors explained theirfindings by suggesting thatmore difficult tasks lend themselves to amore concentrated locus-of-attention that protects against theinterfering stimuli of irrelevant speech. In other words, when in-dividuals concentrate their attention on processing a difficult task,environmental distractors lose their ability to capture attention.Although these findings are specific to task-irrelevant speech, it isconceivable that the general mechanism might be applied to otherenvironmental conditions. Thus, it is likely that given a relativelydifficult task, such as reading a dense text, that requires concertedattention environment should have minimal impact.

Research on the effects of noise on listening comprehension areless common, but one study found that broadband noise interferedwith student memory for lecture, even when speech perceptionwas not a factor (Ljung, S€orqvist, Kjellberg, & Green, 2009). Draw-ing on theories of cognitive load, the authors suggested that whenstudents have to concentrate harder to hear speech in a noisyenvironment, cognitive resources that could be allocated to pro-cessing the meaning of the speech are directed toward listening.Over time, this type of interference could lead to reductions in theretention of the new information. Yet, other research found thatnoise did not interfere with listening comprehension for adults,although it did interfere with younger children (Klatte, Lachmann,& Meis, 2010).

Comparatively less research has focused specifically on the ef-fects of temperature or illumination on reading or listeningcomprehension, particularly with late adolescent or adult pop-ulations. Research with school-aged children has linked warmertemperatures to reduced performance on language-based tasks(Wargocki&Wyon, 2006, 2007). Lower levels of lighting have beenassociated with decreased cognitive performance and academicperformance (Dunn et al., 1985; Hathaway, 1995; Hygge & Knez,2001).

Findings from studies that include multiple environmental el-ements tend to report a range of effects from the different combi-nations of factors. Hygge and Knez (2001), the only study located toinvestigate three environmental factors, found that individualsperformed better on long-term recall tasks when noise levels werelower at higher temperature points, but performed about the samewhen the temperature was low.

1.2. Mood and perceptions of the environment

The effects of the built environment on psychological states,such as mood, and individual perceptions of the environmentalimpact on learning, have received less attention in the empiricalliterature associated with simulated or naturalistic classroom en-vironments with late adolescent or undergraduate populations.

G.C. Marchand et al. / Journal of Environmental Psychology 40 (2014) 187e197 189

Psychological arousal, oftenmeasured through self-report on moodquestionnaires, has been found to be lower at higher temperatures(Hygge & Knez) and higher in conditions of moderate maskednoise, as compared to silent or office noise conditions (Loewen &Suedfeld, 1992). Other research investigating illumination hasfound no relationship among illumination, performance on com-plex cognitive tasks, or mood in the form of arousal or pleasure(Veitch, 1997).

Mood is important for the current study for two reasons: (a)mood has been found to influence reading comprehension (Bohn-Gettler & Rapp, 2011; Egidi & Gerrig, 2009) and (b) environ-mental factors have been found to influence mood (Loewen &Suedfeld, 1992). In their comprehensive study of environment,mood, and cognition, Hygge and Knez (2001) reviewed theoreticalmodels suggesting that mood may mediate the relationship be-tween environment and cognition, but found little evidence formediated effects; rather they proposed that relationships betweenemotion and environment, and environment and cognition, mayoperate independently. Thus, further evidence that mood, specif-ically different aspects of negative and positive mood, may beinfluenced by environment would be useful in furthering under-standing as to the role that mood and environment play in class-room learning and adjustment.

Research investigating perceptions of the individual of the builtenvironment tends to focus primarily on adult workplace andresidential buildings (Frontczak & Wargocki, 2011). This line ofresearch supports the notion that individuals are able to distinguishbetween positive and negative aspects of the built environment(Zagreus, Huizenga, Arens, & Lehrer, 2004). The influence ofperceived environmental factors on performance attributions oncognitive tasks has not been a dominant theme in the literature.Given research that suggests that stress and negative mood mayintroduce intrusive, irrelevant thoughts during cognitive tasks(Ellis, Ottaway, Varner, Becker, & Moore, 1997), it is reasonable toconsider that an uncomfortable environment may create percep-tions of stress and negative attributions about performance basedon that source of stress (Loewen & Suedfeld, 1992). Further,stressful environmental conditions tend to be associated withfeelings of helplessness and decreased task persistence (for reviewsee Evans & Stecker, 2004). Research has shown that individuals inquiet conditions reported less distraction and stress associatedwith noise during learning tasks (Loewen & Suedfeld).

1.3. Summary

Taken together, the evidence suggests that the effects of thebuilt environment on learningmay vary depending on the nature ofthe task (listening or reading) and the nature of the environmentalelements. Further, environmental factors may directly influenceindividual mood and attributions about the effects of the envi-ronment on performance. Althoughmuch of the evidence reviewedfor the present study is rooted in research on sound, if one con-siders noise as “irrelevant stimuli” (S€orqvist et al., 2012, p. 2147)that must be filtered to better attend to a specific goal, then thefindings from this field might be applied to include other elementsof the built environment, such as temperature or lighting. Thus, thepresent study conceptualized the built environment as a compositeto determine effects on cognitive and psychological factors in whatmight be a range of realistic classroom environments.

1.4. The present study

The present study was designed to address the following goals:(a) to first determine if the classroom built environment influencedstudent learning following a reading or listening task, (b) to

examine whether differences in the physical environment andlearningmodality influenced studentmood, and (c) to uncover howstudents perceived the built environment as impacting their per-formance in different environmental and task modalities.

An experimental study was designed to investigate the effects ofcomposite built environment [normal or outside of the comfortzone (OCZ)] and learning modality (reading and listening) on stu-dent comprehension, mood, and perceptions of the impact of theenvironment on performance (Pamoukov, 2011). The reading orlistening task was designed to be moderately difficult.

Several hypotheses were tested using a series of 2 � 2 factorialANOVAs. Based on findings in previous research, it was expectedthat an interaction would be found between condition and mo-dality so that the environment would not negatively impact stu-dents in the reading condition but would negatively impactstudents in the listening condition due to the increase in cognitiveload.

In terms of mood, it was hypothesized that students in thenormal conditionwould havemore positivemood and less negativemood than those in the OCZ condition. Even if students are able toblock distractors during a reading task, they still may experiencephysical discomfort in a negative environment, which may work toinfluence their general emotive state. Given that research suggestsa possible direct effect for environmental factors onmood (Hygge&Knez, 2001) differences in positive or negative mood were notexpected by learning modality.

Students focusing attention on a speaker as opposed to a textmay be more aware of the physical environment. If this is the case,then even students in the normal listening condition may be morelikely to attribute performance challenges to environmentalstressors, particularly if they are concerned about their perfor-mance. A main effect for the listening condition was expected.Further, given evidence that individuals are able to detect negativeenvironmental factors, it was expected that students in the OCZcondition would report more negative attributions in general foreach of the environmental factors than those in the normalcondition.

2. Methods

2.1. Participants

Participants were undergraduate students from the Colleges ofEducation and Engineering at a large southwestern university.There were a total of 158 participants of whom 95 were male, 62were female and one individual did not indicate his or her gender.The participants' ages ranged from 17 to 49 years old. Three percentof the participants self-identified as African American, 18% wereAsian/Pacific Islander, 1% were Native American or Alaska Native,16% were Hispanic, 53% were Caucasian, 8% were other and 1% didnot specify.

2.2. Experimental condition and design

The experiment was conducted in the Ventilation and AcousticsSystems Technology (VAST) laboratory housed in the College ofEngineering. The laboratory allowed accurate measurement andcontrol of various environmental parameters (e.g. temperature,ventilation, lighting, and acoustics). The laboratory room di-mensions were 21 ft � 31 ft with a ceiling height of 10 ft. Thelaboratory was equipped with both a ceiling air distribution (CAD)system and an under floor air distribution (UFAD) system, and wascapable of being reconfigured between the two systems.

The VAST Laboratory was equipped with a series of sensors withprecise measuring capabilities. Temperature sensors were located

G.C. Marchand et al. / Journal of Environmental Psychology 40 (2014) 187e197190

on multiple wall locations, the floor, under the floor, in the ceilingand above the ceiling airspace. Sensors to measure airflow, tem-perature, and humidity were located in the supply and return airducts. Sensors to measure energy inputs from the test room, roomlighting, and energy consumption of the HVAC system were alsopresent. A computer running custom designed LabView softwarerecorded, monitored, and controlled conditions in the laboratory.

To measure lighting and sound intensity levels two handhelddevices were used. To ensure even lighting throughout the labora-tory, the Konica Minolta illuminance meter T-10 was used. Thisdevice has a measuring range of 0.01e299,000 lx with automaticrange switching and an accuracy of ±2% ± 1 digit of the displayedvalue. The sound levels were measured using SVANTEK 958 fourchannel, 20 kHz real time sound and vibration analyzer. The SVAN958 can perform soundmeasurements with the accuracy of a Type 1sound analyzer. The instrument measures sound by the use of fourindependent microphones. The analyzer gives the user a possibilityto obtain Leq, LMax, LMin, LPeak, Spl, SEL with different weighingfilters at the same time. The total dynamic range of the instrument is17 dBA RMSe 140 dBA Peak, with 50mV/Pamicrophone sensitivity.The analyzer has a frequency range of 0.5 Hze20 kHz.

To achieve the specified lighting intensity levels, the laboratorywas equipped with a total of 10 fluorescent light fixtures and 8flood lights. The lights were arranged in a way to promote the mostuniform lighting levels throughout the laboratory.

Armstrong Applaus series ceiling speakers were installed in theceiling to achieve desired sound levels. The speakers are rated at30 W each and they have very broad sound dispersion. They have amaximum sound pressure level of 98 dB at 1 m and a sensitivity of84 dB. There are three available tap settings at 7.5W,15W, and30W;the15Wsettingwasused. The speakerswere evenly spaced to createuniform sound levels throughout the test room. The sound that wasplayed through the ceiling speakers was recorded room ventilatorfan generated sound. This sound was characteristic of sound thatwould typically be generated by a closely located room heat pump/air conditioning unit in a portable classroom building. This soundcontributed to the low andmid frequency ranges (less than 710 Hz).This was the dominant background sound in the test room.

The conditioned air was supplied by two diffusers. Twelve inchby twelve inch Krueger SHR/5SHR series diffusers were used. Thediffusers that were selected had 4-way throw in order to produceuniform discharge air patterns on all sides. Airflow generatedsound from these diffusers contributed to the high frequencybackground sound in the test room (greater than 710 Hz). Whilethis sound was noticeable, it was less dominant than the recordedroom ventilator fan sound.

2.3. Materials

2.3.1. Test passageThe test passage was based on a chapter from Rachel Carson's

(1951) book entitled “The Sea Around Us”. It was expected that acollege level reader should take no longer than 30 min to read theentire passage. The passage was dense with information and rela-tively difficult to understand. The passage contained various typesof information; names of oceanic explores, information onmineralsfound in the ocean, methods for undersea research and the tech-nology that is used in under water exploration.

2.3.2. Comprehension assessmentThe Sentence Verification Task (SVT; Royer, Greene, & Sinatra,

1987; Royer, Hasting, & Hook, 1979) was constructed based onthe passage selected from a chapter in the book entitled the “SeaAround Us” written by Rachel Carson (1951). The SVT is a test forcomprehension that can be adapted to any reading assignment or

oral presentation. The SVT for this experiment consisted of 40sentences divided equally into 4 different types of sentences;originals, paraphrases, meaning changes, and distractors. The par-ticipants decided if the phrases are “old” or “new” to the readingtest passage or oral presentation. “Old” sentences were the same orhad the same meaning the as the test passage sentences (originalsand paraphrases). “New” sentences had different meaning than thetest passage (meaning changes and distractors). The total numberof correct responses was calculated across the 40 items. The reli-ability of the SVT has been reported in a number of studies and forthis study Cronbach's a was .70. Please refer to Royer (2001) for areview of the SVT.

2.3.3. PANASThe Positive Negative Affect Scale brief measure (Watson, Clark,

& Tellegen, 1988) was used to determine each participant's mood ineach environmental condition. The PANAS consists of 20 items,each of which portrays a word that describe different feelings oremotions, such as “interested” or “distressed”. Students then indi-cate the extent to which they feel that way at the present momenton a 5 point Likert scale ranging from 1 ¼ very slightly or not at allto 5 ¼ extremely. The PANAS is comprised of two subscales; apositive affect and negative affect. The internal consistency reli-ability coefficient, Cronbach's a, for the positive affect scale was .88and the negative affect scale was 0.74.

2.3.4. Built environment experience surveyThe Built Environment Experience (BEE) survey was created for

this study to investigate student perceptions of the test roomconditions and the extent to which they felt the environmentinfluenced their performance on the comprehension task. Thesurvey consisted of 12 items to which participants indicated theiragreement or disagreement with the item via a five point Likertscale that ranged from 1 ¼ strongly agree to 5 ¼ strongly disagree.

The 12 items were subjected to an Exploratory Factor Analysis(EFA) using principal axis factoring (PAF) to identify possible sub-scales within the BEE. The Kaiser-Meyer-OlkinMeasure of SamplingAdequacy was .83, exceeding the recommend value of .60 (Kaiser,1970, 1974) indicating adequate sample size for the procedureand the Barlett's (1954) Test of Sphericity value was significant(p ¼ .00).

Principal axis factoring revealed a three factor solution thataccounted for 78.59 percent of the variance. Factor 1 accounted for59.90 percent of the variance; factor 2 accounted for 10.37 percentof the variance; factor 3 accounted for 8.32 percent of the variance.A number of methods were employed to determine the number ofcomponents to retain; eigenvalue greater than 1 (Kaiser, 1960),scree plot (Cattell, 1966), variance, and residuals. The factor loadingmatrix for this final solution is presented in Table 1. Factor 1 waslabeled room climate and consisted of question related to the roomcondition (i.e. moisture, temperature, etc.) and student perfor-mance. The Cronbach's a for this subscale was .95. Factor 2 relatedto participants perceptions of the impact of classroom lighting onperformance (a ¼ .91). Factor 3 was comprised of questionsregarding the room's acoustics and perceived impact on perfor-mance and was subsequently named sound level (a ¼ .97). Scalescores were created for each factor by taking the mean of the scaleitems. Note that due to the item phrasing and scaling on theclimate, lighting, and sound factors, lower scores indicated astronger belief that the room conditions had a negative impact onperformance.

Fig. 2. The Vast Laboratory configuration for the LN and the LOCZ conditions.

Table 1Factor loadings for the BEE survey.

Environmental survey questions I II III

1. The room moisture negatively affected my performanceon the reading and test assignments.

.61

2. I had difficulty focusing my attention on the reading andtest assignments because of the room moisture.

.68

3. The room temperature negatively affected my perfor-mance on the reading and test assignments.

.80

4. I had a difficultly focusing my attention on the readingand test assignments because of the moisture.

.94

5. The room air (stuffy/drafty) negatively affected my per-formance on the reading and test assignments.

.96

6. I had difficulty focusing my attention on the reading andtest assignments because of the room air (stuffy/drafty).

.97

7. The room lighting negatively affected my performanceon the reading and test assignments.

.66

8. I had a difficulty focusing my attention on reading andtest assignments because of the room lighting.

.71

9. Glare on the computer screen negatively affected myperformance on the reading and test assignments.

1.01

10. Glare on the computer screen negatively affected myperformance on reading and test assignments becauseof the glare on the computer screen.

.88

11. The room sound levels negatively affected my perfor-mance on reading and test assignments.

.97

12. I had difficulty focusing my attention on the readingand test assignments because of the room sound levels.

.97

Note. Rotation converged in 5 iterations.

G.C. Marchand et al. / Journal of Environmental Psychology 40 (2014) 187e197 191

2.4. Procedures

The experimental procedure across all conditions was the samewith the exception of the task modality (reading or listening) andthe built environment condition (normal or sub-optimal). Theprocedures associatedwith themanipulation of these two variablesand the general experimental procedures are described in thefollowing sections.

2.4.1. Task modalityThe first independent variable of interest in this study was task

modality, which included two levels: reading and listening. In thereading condition, students were exposed to the test passagedescribed in Section 2.3.1 as written passage read on a computerscreen at individual stations. Participants were given a practicereading passage so that they could become familiar with the nav-igation of the material presentation and to determine a baselinereading time. The test passage was 4500 words that were dividedinto 34 word segments. Each segment was presented on a separatescreen. To advance through each screen participants had to click thenext button. The computer kept track of the time it took

Fig. 1. The Vast Laboratory configuration

participants to move from one segment to the next. The partici-pants read the passage at their own pace. The computer timed howlong it took for each student to complete the passage. See Fig.1 for aschematic of the laboratory classroom for the reading conditions.

In the listening condition, students were informed that theywould be viewing a video lecture on the television screen (seeFig. 2). Participants were seated in front of computers at individualstations but were advised not to use the laptops during the pre-sentation of the video. Participants were shown a video of aresearcher reading the experimental passage on a 55ein. SamsungLED high-definition television placed at the front of the classroom.The audio was delivered through a Sony surround sound hometheater system (model number BDV-E370). The sound level of theaudio presentation was 70 dBA. This corresponded to the soundlevel of a normal vocal effort. To ensure the test subjects couldclearly hear and understand the test passage as it was read, aminimum signal-to-noise ratio of 10 dBAwas required between thevocal effort sound level and the test room background sound level.To achieve this, it was necessary to reduce the test room back-ground sound level from 65 dBA to 60 dBA for the listening con-dition. The measured background sound level was constantthroughout the test room. The measured variation of the soundlevel associated with the vocal effort of the read test passagethroughout the test room was less than 2 dBA. The speech intelli-gibility index was not measured for these tests. However, for aperson with normal hearing, the vocal effort associated with thepresentation of the test passage was clearly audible and under-standable throughout the test room. The time elapsed to read thepassage aloud was 32 min.

2.4.2. Built environment conditionThe second independent variable was the composite built

environment, which also had two levels: normal and just outside ofthe comfort zone (OCZ). In both conditions, the physical classroom

for the RN and the ROCZ conditions.

Table 2Participant distribution across conditions.

Environmental condition

Normal OCZ

Reading comprehension N ¼ 43 N ¼ 41Listening comprehension N ¼ 36 N ¼ 35

Table 4Intercorrelations for the dependent variables for the normal and OCZ readingconditions.

Measure 1 2 3 4 5 6

1. SVT e �.16 �.23 .15 .14 .162. PAS �.10 e .14 �.02 .08 �.033. NAS �.04 �.22 e �.30 �.07 �.124. Temp �.15 .48** �.16 e .78*** .45**5. Light �.06 .29 �.28 .66*** e .41**6. Sound �.27 .43** �.11 .41** .25 e

Note. Intercorrelations for the normal condition are above the diagonal and for theOCZ condition, below the diagonal. PAS¼ positive affect scale. NAS¼ negative affectscale. **p < .01. ***p < .01.

G.C. Marchand et al. / Journal of Environmental Psychology 40 (2014) 187e197192

was arranged in the same way. To create the normal condition, thetemperature, sound level, and lighting weremanipulated and set tostandards based on previous research on ideal classroom condi-tions (e.g., ASHRAE, 2004). The test room temperature for thenormal condition was 72 �F, the room sound level was 35 dBA andthe lighting was 500 lux. To create the OCZ condition, environ-mental parameters were set slightly outside the comfort zone. Thetemperature was 80 �F and the lighting was 2500 lux. The soundlevel varied slightly between the reading and listening conditionsdescribed in Section 2.4.1 in order for the speech to be intelligible inthe listening condition. The sound level was 65 dBA in the readingcondition and was changed to 60 dBA in the listening condition sothe test room sound level was 10 dBA below the sound level of theaudio presentation.

Table 5Intercorrelations for the dependent variables for the normal and OCZ listening

2.4.3. Experimental procedureParticipants were randomly assigned to four different groups

(see Table 2): reading comprehension-normal (RN), readingcomprehension-OCZ (ROCZ), listening comprehension-normal(LN), and listening comprehension-OCZ (LOCZ).

Students assigned to each of the four conditions: RN, LN, ROCZ,LOCZ, entered the laboratory classroom and were randomlyassigned to sit in front of one of the individual computer stations.Following a paper and pencil consent session, students wereinstructed to enter into their computer a unique ID assigned tothem by the study team to begin the study. Students first completeda demographic survey. Students in the reading condition then readthe practice and test-passage. Students in the listening conditionviewed the passage read aloud as described in Section 2.4.1.Following the test passage participants completed the PANAS. Thenext task that followed was the SVT and finally participantscompleted the BEE survey. After completion of all tasks studentsreceived their score on the SVT.

Prior to conducting analyses, one participant was removedbecause his/her total reading score time was two standard de-viations below the average total reading score time. In addition twoother participants were removed because they only completed theenvironmental survey and did not complete any of the other tasks.

Table 3Mean and Standard Deviation (in parentheses) Across Conditions.

RN ROCZ LN LOCZ

SVT 26.51 (5.43) 27.76 (5.49) 28.54 (3.78) 26.11 (4.76)Positive Affect 24.51 (10.85) 22.68 (12.15) 20.72 (10.61) 22.29 (10.96)Negative Affect 13.95 (3.71) 15.36 (4.69) 13.42 (4.47) 14.71 (4.01)Temperature 3.82 (1.05) 3.66 (1.21) 4.13 (1.11) 3.56 (1.18)Lighting 3.96 (1.05) 3.79 (1.15) 4.08 (1.18) 3.94 (1.00)Sound 3.45 (1.22) 3.22 (1.39) 4.26 (1.24) 3.50 (1.37)

3. Results

3.1. Descriptive statistics and correlations

Table 3 depicts the means and standard deviations for each ofthe four conditions on each of the six dependent variables: positiveaffect, negative affect, SVT, temperature, lighting, and sound level.

Correlations amongst the dependent variables by each conditionwere conducted in an effort to describe possible relationships in thedata. For simplicity sake, correlations for participants in the readingcondition are presented in Table 4 and the listening condition inTable 5.

Overall, the correlations amongst the performance task and theaffect scales and BEE scales were very low and non-significant withthe exception of a positive correlation between performance andattributions of lighting on performance. Note that lower scores onthe BEE indicate a stronger belief of negative perceptions, thus thepositive correlation can be interpreted that individuals with higherlistening comprehension scores were less likely to attribute nega-tive performance to lighting issues. For the most part there wereconsistent moderate to strong correlations amongst the BEE scalesacross conditions, indicating that individuals were fairly likely toattribute negative performance to environmental conditions simi-larly across the three elements. Only students in the OCZ readingcondition associated mood with room attributions, with those lesslikely to attribute negative performance to sound or temperaturealso more likely to report higher levels of positive mood.

3.2. Group differences

3.2.1. ComprehensionA 2 � 2 factorial ANOVA was performed using the Statistical

Package for the Social Sciences (SPSS) v20 to assess whethercomprehension scores as measured the SVT could be predictedfrom modality of instruction (A1 ¼ reading, A2 ¼ listening), envi-ronmental condition (B1 ¼ normal, B2 ¼ OCZ), and the interactionbetween modality and environmental condition. It was

conditions.

Measure 1 2 3 4 5 6

1. SVT e .03 �.27 .32 .37* .292. PAS .09 e .45 .10 .07 .053. NAS �.19 .24 e �.06 �.11 �.074. Temp �.08 .20 �.31 e .86*** .60***5. Light .01 .21 .02 .46** e .57***6. Sound �.11 .25 .12 .54** .54** e

Note. Intercorrelations for the normal condition are above the diagonal and for theOCZ condition, below the diagonal. PAS¼ positive affect scale. NAS¼ negative affectscale. *p < .05. **p < .01. ***p < .001.

Fig. 3. Interaction between condition and modality on the comprehension task.

G.C. Marchand et al. / Journal of Environmental Psychology 40 (2014) 187e197 193

hypothesized that the negative environment would have a greaterdetrimental impact on students in the listening OCZ condition thanthe other conditions. The 2 � 2 factorial ANOVA with scores on theSVT as the dependent variable revealed an interaction (see Fig. 3)betweenmodality of instruction and environmental condition, FA�B

(1, 150)¼ 5.22, p¼ .02, partial h2 ¼ .03. An analysis of simple effectswas conducted in order explore the interaction further, contrastingfirst participants within each modality by environmental conditionand then participants within each environmental condition bymodality. For students in the listening comprehension condition,SVT scores were lower in the OCZ condition (M ¼ 26.11, SD ¼ 4.76)compared to participants in the normal condition (M ¼ 28.54,SD ¼ 3.78), as indicated by the univariate F (1, 150) ¼ 4.19, p ¼ .04,partial h2 ¼ .03. There was no difference on scores for studentswithin the reading condition by environmental group, F (1,150) ¼ 1.32, p ¼ .25, nor were there differences on scores for stu-dents with the normal condition by modality, F (1, 150) ¼ 3.23,p ¼ .07, or the OCZ condition by modality, F (1, 150) ¼ 2.06, p ¼ .15.

There was no statistically significant main effect for modality, FA(1, 150) ¼ .06, p ¼ .81, or environmental condition, FB (1, 150) ¼ .54,p ¼ .46.

Supplemental analyses were conducted to explore whetherparticipants erred in different ways in choosing items considered“old” (verbatim or paraphrase from text) or “new” (distractor ormeaning change) across modality and environmental conditions. Itwas expected that participants in the listening condition woulderroneously select items as “new” more often than erroneouslyselect items as “old” due to the increased challenge of learningmaterial while listening, particularly in adverse environmentalconditions. When students erroneously choose a sentence thatreflects a new meaning, it indicates a failure to learn the generalidea, or gist, of the material (Kintsch, 2004; Oswald et al., 2000).

Table 6Mean and Standard Deviation (in parentheses) across Conditions.

RN ROCZ LN LOCZ

“Old” selection 19.74 (4.54) 20.68 (3.76) 22.02 (5.72) 23.94 (3.80)“Old” correct 13.14 (3.56) 14.21 (3.35) 15.16 (3.10) 15.02 (2.15)“New” selection 20.26 (4.54) 19.31 (3.76) 16.86 (5.18) 16.05 (3.80)“New” correct 13.40 (3.48) 13.53 (3.31) 12.58 (4.24) 11.09 (3.73)

Looking only at the type of responses given and not whetherthose were correct, students in the listening conditions selected ahigher number of responses that reflected the original meaning ofthe text, but those in the reading condition appeared to havegreater balance in their selection (see Table 6). Descriptively, stu-dents in the reading conditions, particularly the normal condition,appeared to have erred also in similar ways, correctly selecting newand old text meanings at about the same rate, whereas students inthe extreme listening condition correctly identified the lowestnumber of new meaning items.

A 2 � 2 factorial ANOVA was performed to assess whethergroups differed in the correct selection of answers that measuredthe original meaning of the text. The 2� 2 factorial ANOVAwith oldcorrect scores on the SVT as the dependent variable revealed nointeraction between modality of instruction and environmentalcondition FA�B (1, 151) ¼ 1.46, p ¼ .23. There was a statisticallysignificant main effect for modality of instruction FA (1, 151) ¼ 7.92,p ¼ .01, partial h2 ¼ .05 on students' reported old correct scores.Contrary to expectations, participants in the listening conditionreported a higher number of correct responses that reflected theoriginal text meaning (M ¼ 15.09, SD ¼ 2.66) than those who werein the reading condition (M ¼ 13.66 SD ¼ 3.48). There was no maineffect for environmental condition FB (1, 151) ¼ .87, p ¼ .35.

A second 2 � 2 factorial ANOVA was performed to assesswhether the groups differed in the correct selection of items thatreflected new meaning of the text. The 2 � 2 factorial ANOVA withnew correct scores on the SVT as the dependent variable revealedno interaction between modality of instruction and environmentalcondition FA�B (1, 151)¼ 1.90, p¼ .17. Again, there was a statisticallysignificant main effect for modality of instruction FA (1, 151) ¼ 7.54,p ¼ .01, partial h2 ¼ .05 on students' reported new correct scores.Participants in the reading condition reported a higher number ofnew correct responses (M ¼ 13.46, SD ¼ 3.37) than those who werein the listening condition (M¼ 11.84, SD¼ 4.04). Therewas nomaineffect for environmental condition FB (1, 151) ¼ 1.30, p ¼ .26.

3.2.2. MoodA 2 � 2 factorial ANOVA was performed to assess whether

negative affect as measured by the PANAS could be predicted frommodality of instruction (A1 ¼ reading, A2 ¼ listening), environ-mental condition (B1 ¼ normal, B2 ¼ OCZ) and the interaction be-tween modality and environmental condition. The 2 � 2 factorialANOVA with negative affect scores on the PANAS as the dependentvariable revealed no interaction between modality of instructionand environmental condition FA�B (1, 151) ¼ .007, p ¼ .93. As pre-dicted, there was a statistically significant main effect for envi-ronmental condition FB (1, 151) ¼ 3.93, p ¼ .05, partial h2 ¼ .03 onstudents' reported negative affect. Participants in the extremecondition reportedmore negative affect (M¼ 15.07, SD¼ 4.38) thanthose who were in the normal condition (M ¼ 13.71 SD ¼ 4.06),although the effect was small. There was no main effect for mo-dality FA (1, 151) ¼ .76, p ¼ .39.

Results from the analyses treating positive affect as the depen-dent variable indicated no interaction between modality of in-struction and environmental condition FA�B (1, 151) ¼ .89, p ¼ .35,partial h2 ¼ .01. There was no statistically significant main effect formodality, FA (1, 151) ¼ 1.35, p ¼ .25, or environmental condition, FB(1, 150) ¼ .01, p ¼ .94.

3.2.3. Perceived environmental impactThe 2 � 2 ANOVA results investigating students' perceptions of

room temperature as negatively impacting their performancerevealed no interaction between instructional modality and envi-ronmental condition, FA�B (1, 149) ¼ 1.28, p ¼ .26, partial h2 ¼ .01.However, there was a significant main effect for environmental

G.C. Marchand et al. / Journal of Environmental Psychology 40 (2014) 187e197194

condition FB (1, 149) ¼ 3.90, p ¼ .05, partial h2 ¼ .03. As expected,participants in the extreme condition perceived the room tem-perature as having a more negative impact on their performance(M ¼ 3.62, SD ¼ 1.19) compared to participants in the normalcondition (M ¼ 3.96, SD ¼ 1.08). There was no main effect formodality, FA (1, 149) ¼ .30, p ¼ .59.

A similar result was found for student perceptions of roomsound on their performance. A 2 � 2 factorial ANOVA was per-formed to assess whether perceptions of room sound as measuredby the Built Environment Experience Survey could be predictedfrom modality of instruction (A1 ¼ reading, A2 ¼ listening), envi-ronmental condition (B1 ¼ normal, B2 ¼ OCZ) and the interactionbetween modality and environmental condition. The interactionbetween modality and environmental condition was not statisti-cally significant, FA�B (1, 149) ¼ 1.56, p ¼ .22. However, there was asignificant main effect for environmental condition FB (1,149) ¼ 5.53, p ¼ .02, partial h2 ¼ .04. Participants in the OCZ con-dition perceived the sound levels as having a more negative impacton their performance (M ¼ 3.35, SD ¼ 1.38) compared to partici-pants in the normal condition (M ¼ 3.81, SD ¼ 1.29). There was alsoa significant main effect for modality of instruction FA (1,149)¼ 6.61, p¼ .01, partial h2¼ .04. Surprisingly, participants in thereading comprehension condition perceived the sound levels ashaving a more negative impact on their performance (M ¼ 3.34,SD¼ 1.30) compared to participants in the listening comprehensioncondition (M ¼ 3.88, SD ¼ 1.35).

The 2 � 2 factorial ANOVAwith perceived lighting scores on theBuilt Environment Experience Survey as the dependent variablerevealed no interaction between modality of instruction andenvironmental condition FA�B (1, 149) ¼ .01, p ¼ .94. There was nostatistically significant main effect for modality, FA (1, 149) ¼ .58,p ¼ .45, or environmental condition, FB (1, 149) ¼ .80, p ¼ .37.Participants did not perceive the lighting of the room as having anegative impact on their listening or reading comprehension.

4. Discussion

In an effort to simulate real-world classroom built environ-ments, this study investigated the impact of a composite environ-ment consisting of temperature, lighting, and sound levels withinthe comfort zone or just outside of the comfort zone and learningmodality on student comprehension, mood, and attributions of theenvironment on performance. One novel aspect of this work withrespect to the built environment effects on learning is the use ofmultiple learning modalities of reading and listening to test builtenvironment effects. While there have been a few studies (e.g.Hygge et al., 2002) that have examined multiple modalities, to bestof our knowledge none of the studies have examined the envi-ronment as a whole in conjunction with multiple learningmodalities.

Drawing upon ideas of environmental impact on distraction andcognitive load (Ljung et al., 2009; S€orqvist & R€onnberg, 2012), itwas expected that the participants would be able to filter irrelevant,negative environmental stimuli when reading a moderately diffi-cult task, but that the combined negative environment wouldinterfere with learning due to the division of attentional resourceswhen listening. As predicted, the results indicated that the extremeenvironment was more detrimental only to those participants whowere charged with learning information through listening, asopposed to reading. This effect was small, but the finding mightsuggest that adult students are able to block out the distractions ofa substandard built environment when focused on reading a task,but may be less able to concentrate and assimilate new informationthrough listening alone when faced with a substandard learningenvironment. This finding is in line with recent research on task

difficulty, sound, and complex cognitive tasks (Halin et al., 2014).Research also supports the interpretation that it is possible par-ticipants dedicated more cognitive resources to filtering out envi-ronmental stressors, leaving less cognitive space for processingnew information (Kjellberg et al., 2008; Ljung et al., 2009). Alter-natively, the higher sound level may have interfered with partici-pants' ability to hear the information. Yet, other surprising findingsfrom this study call into question at least one of these possiblescenarios. Adult students in the reading condition were more likelythan those in the listening condition to attribute negative perfor-mance to room sound levels. One would expect the opposite ifparticipants in the listening condition felt unable to hear the ma-terial. Moreover, room parameters were set to facilitate speechperception.

There was partial support for the hypothesized effects of builtenvironmental condition on participant affect. There were no ef-fects for either environmental condition or learning modality onpositive mood. However, the results indicated that students in theOCZ condition reported more negative affect than those in thenormal condition. Low negative affect in this study would reflect ameasure of calmness, whereas high negative affect reflects distressand aversive states (Watson et al., 1988). The measures of negativeaffect used in this study may not be directly comparable to arousalscales used in other research (e.g., Hygge & Knez, 2001). Althoughprevious research suggests that arousal states may be lower withwarmer temperatures (e.g., Hygge & Knez), higher in more noisyconditions (e.g., Loewen & Suedfeld, 1992), and unrelated to illu-mination (Veitch, 1997), the findings from this study suggest that acomposite negative environment can lead to feelings of distress. Inan environment with multiple uncomfortable elements, perhapssubjective states of all elements become negatively skewed. Alter-natively, perhaps individuals attend to the negative aspect of theenvironment that is most salient to their individual needs forlearning environment. Additional research to determine individualpreferences for learning in association to unique and compositeenvironmental stressors may be needed to clarify these effects.

The findings on performance attributions associated with envi-ronmental conditions may offer some intriguing insights into thecomprehension and mood findings. Contrary to predictions, adultstudents in the reading conditionwere more apt to report sound asnegatively impacting performance.However, theseparticipants alsodemonstrated the most positive performance levels in the study,with participants in the OCZ reading condition actually having thehighest mean level of performance. Research on arousal and taskdifficulty in studies of noise suggest that at lower levels of taskdifficulty, slight environmental stressors leading to higher levels ofarousal may improve performance (Beaman, 2005). However, thelack of main effect for modality for negative affect or an interactionbetween modality and environment for negative affect, coupledwith the weak, non-significant relationships between negativeaffect and performance does not support the notion that adult stu-dents in the reading condition experienced higher levels of negativeaffect that may have contributed to better performance. Predictiverelationshipswere not examined in this study due to design choices.An alternative explanationmay be that adult students in the readingcondition either perceived the task as more difficult than those inthe listening condition or perhaps had greater psychological in-vestment in the task, leading them to attribute possible poor per-formance to an external source in an effort to defend againstvulnerabilities to their self-concept (Ashkanasy & Gallois, 1987;Thompson, Davidson, & Barber, 1995). Relationships amongst per-formance attributions, task difficulty, motivational variables, andthe built environment should be explored in future research.

Given that there were more effects for attributions associatedwith sound than for other environmental factors on the BEE, it is

G.C. Marchand et al. / Journal of Environmental Psychology 40 (2014) 187e197 195

possible that the noise level in the room was the most salient in-fluence in the composite environment. The performance findingsare in linewith previous research on sound (Halin et al., 2014; Ljunget al., 2009). Yet, participants in the OCZ condition reported nega-tive attributions also associated with temperature. Thus, it may beill-advised to assume that uncomfortable environment was in factonly a noisy environment. One avenue for future researchmay be toinvestigate the possible relations among built environment, psy-chological perceptions, and learning. It is possible that substandardbuilt environmental conditions may impact learning indirectly byaffecting adult student mood or motivation (Cohen, Evans, Krantz,& Stokols, 1980; Evans, 2006; Evans & Stecker, 2004).

4.1. Limitations and future research

Because the built indoor environment was conceptualized as acomposite with aggregate effect, examining only two environ-mental conditions (normal and OCZ), it was not possible to identifythe distinct effects of temperature, lighting, and sound on adultstudent performance, mood, and attributions. To accomplish thiswould require a substantially larger sample size. Therefore, a logicalfollow-up to this study is to determinewhich indoor environmentalfactors had the greatest impact. Previous research has suggestedthat different environmental factors may influence learning inunique ways (Hygge & Knez, 2001). Disaggregated informationwillenable administrators and engineers who work in learning settingsto more effectively decide where to dedicate limited resources forthe greatest benefit.

Further, although a laboratory study was developed with somedegree of ecological validity, the test room environment was acontrived environment, and therefore, the results may not apply toall real world settings. Yet, by keeping the OCZ conditionwithin thehigh rangeof acceptable roomenvironmental conditions as outlinedby ASHRE (2004), it is likely that students in classrooms in older,deteriorating buildings may face similar or even more extremeenvironmental conditions. Built classroom environments withworse conditionswould likely exacerbate the effects, yielding largernegative effects on student learning and psychological factors.

Another possible limitation of the study was the use of airtemperature and moisture as a measure of thermal discomfort.Even though moisture was a question in the environmental survey,it was not a variable in the normal/extreme room settings. A recentstudy suggests that thermal discomfort is a combination of theinteraction between the individual and the environment. Forexample, Lan, Wargocki, and Lian (2011) postulate that thermaldiscomfort is comprised of individual factors such as layers ofclothing, physical movement and metabolic heat production com-bined with environmental factors such as air temperature, mois-ture in the air, and air movement (speed).

In terms of measurement, the SVT was chosen because it adds tothe ecological validity of the study. The SVT can be developed andadministered by instructors and administrators with very littletraining, unlike traditional psychometric tests that are often used ineducation (Royer et al., 1987). In real world situations the SVT is amore viable options compared to other traditional measures.However, the SVT is limited in the degree of granularity that can beassessed in terms of cognition. Further, although analyses of errortypes by “new” and “old” responses across conditions were con-ducted, the results should be interpreted with caution. Participantsin the listening condition were more likely to correctly choose aresponse as reflecting meaning of the original text, but they alsoselected a higher number of “old” responses. Adult students in thereading condition, in contrast, selected a more equal number of“old” and “new” responses and were more accurate in their selec-tions. Future research may choose to investigate a finer level of

detail as to types of errors committed to gain and understanding ofwhether adult student responses were due to the ability tomemorize key words, but failure comprehend the passage-levelmeaning of the text or accurate comprehension of the gist of thetext (Royer, 1990).

Attention and working memory, key constructs in other studiesof the built environment, were not measured in this study andsubsequently important interactions may have been missed. Forinstance, S€orqvist et al. (2010) discovered that irrelevant speechinterfered with reading comprehension overall but individualswith smaller working memory capacity performed most poorly.Thus, for individuals with low working memory capacity, a quietenvironment might be more critical for learning during complextasks. Future research should include measures of workingmemory capacity to determine if these effects are present in acomposite environment situation or across listening and readingtasks.

Finally, given that participants were college students, it can beassumed that the study sample had reasonably well-developedlearning skills. Therefore, the fact that the test room environmentalconditions (normal and OCZ) had no measurable negative effect onreading modality learning performance is a reasonable studyoutcome. Yet, the OCZ test room environmental conditions resultedin a measurable decrease in learning performance for the listeningtest modality, even though adult students likely possessed arepertoire of reasonably sophisticated learning strategies. Theseresults imply that as the learning skills of a student populationdecrease, substandard classroom built environment conditionsmay have an increasingly negative effect on performance across arange of learning activities. For example, students with poorlydeveloped learning strategies, students undergoing remediation, orstudents with learning disabilities might be particularly at risk oflearning interference in substandard learning settings. Thus, thebuilt environment is not ignorable in settings of higher learning.The design of college classrooms should maximize learning; basedon this research, ensuring physical comfort should be part of thedesign conversation.

Decades of reports and research have documented agingeducational facilities and repair needs for P-12 and higher edu-cation (Kaiser & Davis, 1996; U.S. Department of Education,2000). In higher education, expenditures on maintenance andoperations for facilities typically lag behind those of instructionand funding for facilities has not kept up with need (Ehrenberg,2012). In P-12 settings, according to the U.S. General AccountingOffice, 63% of students in the U.S. attend schools where at leastone building component is in need of extensive repair, overhaul,replacement, or contains environmentally substandard condi-tions. This equates to over 14 million students in the U.S.attending schools with substandard classroom indoor environ-mental quality conditions (U.S. General Accounting Office, 1995).Across the educational continuum, failure to maintain adequatefacilities may leave students vulnerable to academic under-performance. For adult students who spend many hours offoundational learning in lecture settings, a substandard envi-ronment may contribute to the presence of task-irrelevantstimuli that interferes with the acquisition and retention ofknowledge. Hypotheses related to effects of built indoor envi-ronment across a range of student age and developmental levelson student performance during reading, listening, and othertasks should be tested in future research.

4.2. Conclusions

The results of this study are consistent with past researchfindings on the importance of the built indoor environment on

G.C. Marchand et al. / Journal of Environmental Psychology 40 (2014) 187e197196

individual learning and performance. This study has demonstratedthat during listening tasks a substandard classroom built environ-ment can have a measurable negative effect on adult studentlearning and performance, even in a test population with well-developed learning skills. The results of this study are an initialstep in better understanding how the integrated effects of multiplefacets of the built indoor environment impact student learning andperformance. It is imperative that further researcher is conductedon the impact of the totality of the built indoor environment onstudent learning and performance.

Acknowledgments

This research was supported in part by E.H. Price and SiemensCorporations.

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