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The Influence of Color on Student Emotion, Heart Rate, and Performance in Learning Environments


Abstract and Figures

In this study, six colors (vivid red, vivid blue, vivid yellow, pale red, pale blue, and pale yellow †) were manipulated in a simulated study environment to determine their effects on university students' learning performance , emotions, and heart rate. It was hypothesized that learning, physiological and emotional states would be affected by different colors in private study spaces. A total of 24 undergraduate and postgraduate students participated in this study. The dependent variables were reading task performance, emotional responses, and changes in heart rate. The results showed that, although participants assessed the situation as relaxed, calm, and pleasant in the pale color conditions, reading scores were significantly higher in the vivid color conditions. Heart rates were significantly affected by hue; they increased in the red and yellow conditions. In addition, the results suggested that, regardless of the degree of whiteness, the hue had a significant impact on partici-pants' emotions; blue increased relaxation and calmness feelings of participants compared to the other colors. Implications of these findings and suggestions for further research are discussed.
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The Influence of Color on Student
Emotion, Heart Rate, and Performance
in Learning Environments
Aseel AL-Ayash,
* Robert T. Kane,
Dianne Smith,
Paul Green-Armytage
Department of Architecture and Interior Architecture, School of Built Environment, Curtin University, Perth, Western Australia
School of Psychology-Clinical, School of Psychology and Speech Pathology, Curtin University, Perth, Western Australia
Department of Architecture and Interior Architecture, School of Built Environment, Curtin University, Perth, Western Australia
Department of Design, School of Design and Art, Curtin University, Perth, Western Australia
Received 12 June 2014; revised 13 January 2015; accepted 15 January 2015
Abstract: In this study, six colors (vivid red, vivid blue,
vivid yellow, pale red, pale blue, and pale yellow
) were
manipulated in a simulated study environment to deter-
mine their effects on university students’ learning per-
formance, emotions, and heart rate. It was hypothesized
that learning, physiological and emotional states would
be affected by different colors in private study spaces. A
total of 24 undergraduate and postgraduate students par-
ticipated in this study. The dependent variables were
reading task performance, emotional responses, and
changes in heart rate. The results showed that, although
participants assessed the situation as relaxed, calm, and
pleasant in the pale color conditions, reading scores
were significantly higher in the vivid color conditions.
Heart rates were significantly affected by hue; they
increased in the red and yellow conditions. In addition,
the results suggested that, regardless of the degree of
whiteness, the hue had a significant impact on partici-
pants’ emotions; blue increased relaxation and calmness
feelings of participants compared to the other colors.
Implications of these findings and suggestions for further
research are discussed. V
C2015 Wiley Periodicals, Inc. Col Res
Appl, 00, 000–000, 2015; Published Online 00 Month 2015 in Wiley
Online Library ( DOI 10.1002/col.21949
Key words: color; learning environment; emotions; heart
rate; interior design
Approaches to learning in educational environments are
changing. These important changes in learning methods
are in response to learners becoming more diverse in age,
ability, and background.
Some people prefer formal
learning that is systematic and guided by instruction, such
as listening to lectures, while others prefer informal learn-
ing without teachers, arising from interactions between
individuals via networked mobile devices and group dis-
In addition, each person has a different learning
style. A particular style is the expression of how people
perceive and process information, and is the most com-
fortable way to learn.
reveals that learners use
three basic learning styles: (1) visual learning, which
involves viewing, watching, observing and reading; (2)
auditory learning, which involves concentrating on les-
sons or listening to audiotapes; and (3) tactile-kinesthetic
learning, which involves touching. Learners remember
better when they write, doodle or draw, and participate in
laboratory experiments.
University students often prefer to study in private
rooms, especially when they work on complex tasks that
need a high level of concentration. Color, in addition to
†The color system used for this study was the Natural Colour System
(NCS). Under METHODS, the NCS notations are given for the six colors
tested. The colors are in two nuance groups, identified here as “vivid” and
“pale.” Vivid colors are to be understood as colors with high chromaticness
and little whiteness or blackness; pale colors as having more whiteness than
chromaticness and virtuallynoblackness.
*Correspondence to: Aseel AL-Ayash (e-mail:
C2015 Wiley Periodicals, Inc.
Volume 00, Number 00, Month 2015 1
interior form, space, light, and texture, is a major design
element that can be used to enrich the physical learning
environment, and it has a significant effect on students,
influencing their emotions, performance and heart rate.
Previous studies have investigated color in learning envi-
ronments in terms of college students’ wall color prefer-
ence for computer classrooms.
Other studies have
focused on the impact of color on children’s behavior in
and on the learning and behavior of students
with disabilities.
Previous color studies in the field of interior design
have focused on residential, work and commercial envi-
ronments. Color studies in learning environments are
scarce, especially for individual study environments. How
wall colors in an individual study room influence adult
students’ learning performance and concentration is
Studies of the relationship between color and learning
performance have yielded inconsistent results. Some stud-
ies failed to detect the effects of color on human perform-
; however, Hamed and Newport
found that
children’s hand strength was affected by room color.
Hand strength was higher in a pink room and decreased
in a blue room, and decreased further when the children
moved to a gray room. These findings support the notion
that cool colors are calming whereas warm colors are
Thus, reds make people more active and
people are calmed by blues.
Similarly, Kwallek and Lewis
have found that color
can influence emotion, mood and performance. In their
study, although students perceived a white office to be
more appropriate and less distracting than red or green
offices, they made fewer errors on a clerical task in a red
Perhaps red is more arousing, while white and
green are more calming. If the task is boring, therefore, a
red condition may stimulate individuals and enhance their
performance. These findings are supported by Kwallek
et al.’s
study on the effects of nine different colors on
short-term worker productivity. The study found that par-
ticipants performed worse in the white office interior than
in any of the other eight interior colors (red, green,
orange, yellow, blue, beige, gray, and purple). Further
analysis showed that the performance was worse in light
colored offices than in dark colored offices. This suggests
that the chromaticness and whiteness of a color play a
significant role in determining its effects on worker
In addition, there is a study by Stone
on the effects of
study setting (private or open-plan), environmental color
(blue, red, or white) and study material (reading or math
comprehension) on adult students’ mood, satisfaction,
motivation and performance. The results indicated that
math performance was not influenced by environmental
color, but color had an impact on reading performance,
with reading performance significantly decreasing in the
red condition. The reason for this was that the participants
rated the reading task as more difficult than the math task.
Therefore, the reading task might demand more attention
than the math task. If the color red is over-stimulating, then
attention could be distracted, causing a decrease in per-
formance levels. In psychology, the Yerkes–Dodson Law
proposes that there is a curvilinear relationship between
arousal and performance. Up to a certain point, increased
arousal can actually help individuals perform better. After
reaching an optimal level of arousal, any increase in
arousal will lead to decreased performance.
Color can also affect an individual’s emotional and
physiological state. Clarke and Costall
point out that the
colors green, blue, and violet are generally considered
cool, comfortable, relaxing, peaceful, and calming; hence,
these colors can decrease anxiety levels. In contrast, red,
yellow and orange are considered warm and arousing;
hence, these colors can stimulate human feelings and acti-
vate people. Neutral colors have less emotional content
and therefore less psychological impact. Some evidence
shows that there is a correlation between emotion and
performance. According to Kuschel, Forster, and Den-
feelings of happiness tend to facilitate the genera-
tion of free associations, which then enhances the ability
to solve problems requiring insight.
Color also has an influence on human physiology, such
as heart rate, blood pressure, body temperature and
Abbas, Kumar and Mclahlan
have also studied
the impact of color and light on physiological states. The
results of this study showed significant changes in heart
rate after 2-min exposures to different colored lights with
various intensities. They also found an increase in heart
rate during exposure to red, indicating that red is arous-
ing. In the blue conditions, the participants’ heart rate
decreased slightly, so blue can be considered calming.
On the other hand, there are some studies that did not
find any differences in heart rate during exposure to dif-
ferent color conditions. For example, Caldwell and
projected red, white and blue lights, equalized for
brightness, on a wall covered with white paper. They
found no color effects on measures of eye blinks, skin
conductance, finger pulse volume, and heart rate. These
contradictory results may have been due to the reduced
exposure time to the colors, which was less than one
minute, and suggest that the time exposure should be
long enough to allow participants to adapt to the color
conditions before the physiological and emotional states
and changes are measured.
The aim of the current study was to examine the
impact of colors on adult students’ learning performance
and potential mediators of learning performance, namely,
emotions and heart rate. For this study, it was hypothe-
sized that learning performance would be affected by dif-
ferent colors such as red, blue and yellow in the learning
space. It was further hypothesized that the physiological
and psychological processes of learners (namely, heart
rate and emotional reactions to the color) would vary as a
function of the color of the learning environment. In pre-
vious color studies regarding learning spaces, yellow and
blue were proposed to be suitable colors for educational
environments, and therefore provided a basis for the
2 COLOR research and application
present experiment. Other studies have argued that warm
colors, such as red, are appropriate for highly active
learning areas because they can stimulate communication
among students and increase interaction.
previous studies did not identify which of the numerous
yellows, blues and reds are appropriate. Therefore, this
research examines colors that might be appropriate and
assesses their impact on learning performance.
The purpose of this experiment was to examine the
impact of six colors varying in hue and whiteness on
reading comprehension, emotional assessment, and heart
rate. The experiment was focused on individual study
areas because little rigorous research in the field of color
studies has focused on this type of learning environment.
According to G*Power Version 3.1.2,
a power analy-
sis program for a variety of statistical tests, at least 24
participants are required to capture a “moderate” interac-
tion between hue and whiteness. Eleven males (45.8%)
and 13 females (54.2%) were recruited from undergradu-
ate and postgraduate students at Curtin University in
Western Australia. The participants’ ages ranged between
20 and 38 years. Ten participants were international stu-
dents (with English as their second language), and 14 par-
ticipants were native English speakers. None of the
participants had defective vision, as verified with the Ishi-
hara Color Blindness Test (ICBT).
Participants were
asked to complete a Learning Channel Preference Ques-
which revealed that all participants were vis-
ual learners.
Color Samples
Color samples were taken from the NCS Color Atlas
which orders colors according to hue, and nuance.
NCS samples were measured and house paints were for-
mulated to be a close match. The NCS notations for the
colors used in this experiment were S 1080-R (vivid red),
S 0580-Y (vivid yellow), S 1565-B (vivid blue), S 0540-
R (pale red), S 0540-Y (pale yellow), S 0540-B (pale
blue), and S 0300-N (neutral white) (Fig. 1).
Color Blindness. The Ishihara Color Blindness Test
(ICBT) has been used for checking color vision. The test
consists of 14 plates, each with a circular image consist-
ing of colored dots as in a pointillist painting. Numerals
within the circles of dots are distinguishable if the indi-
vidual has normal color vision. Only the first 11 plates
were used to detect general color deficiency. Each partici-
pant had to correctly identify 10 or more plates to be
deemed to have normal vision and therefore eligible to
participate. Each plate was held at a right angle to the
participant’s line of sight. The experimenter instructed the
participant to “please read the numbers” and allowed the
subject 3 seconds to respond.
Learning Channel Preference Questionnaire. This
questionnaire is designed to identify students’ learning
It is divided into three categories (visual, auditory
and haptic or kinesthetic) learning styles. Each category
contains 10 questions, giving a total of 30 questions
across the three categories. Participants were asked to rate
each statement on a three-point scale according to how it
generally relates to them (three often applies, two some-
times applies, and one never or almost never applies).
Scores are totalled in each category; the category with the
highest score represents the participant’s preferred learn-
ing style.
Color Emotion Scales. To assess the emotional
response of participants to the colors of the room, nine
bipolar color-emotion scales were used in the experiment:
dark/light, pleasant/unpleasant, fresh/stale, heavy/light,
calm/exciting, dull/sharp, tense/relaxed, warm/cool, inter-
Each adjective pair is scored on a seven-
point semantic differential rating scale. Participants were
asked during the experimental session “What emotional
response do you associate with this color?”. After
Fig. 1. The position of the study colors in the NCS triangles (Swedish Standards Institute, 2004).
Volume 00, Number 00, Month 2015 3
finishing each experimental session, the participants were
interviewed and asked “Does this color motivate you to
study and help you to focus? Why?” to obtain more in-
depth qualitative data.
Physiological Recordings. The Fingertip Pulse Oxim-
eter MD300C21/Beijing Choice Electronic Technology
was used to record heart rate. This device consists of a
transmitter that is held to the subject’s thumb with a port-
able digital output mechanism. The equipment is unobtru-
sive. Two measurements were taken before and during
the experiment and the average of each pair was reported.
Performance Assessment. Because all participants
were visual learners, reading rather than audio compre-
hension tests were used to assess learning performance.
The participants were asked to read a passage and then
they answered seven multiple choice questions. These
tests were adopted from the SAT Comprehension Test
website. The reading tests were of comparable difficulty
across the six color conditions. The passages covered dif-
ferent topics such as science (420 words), social life (473
words), novel (500 words), psychology (488 words), liter-
ature (525) and politics (520 words).
Room Design. Two experimental rooms were set up in
the School of Built Environment within Curtin University.
The first was a neutral waiting room with light gray walls
and ceiling and dark gray floor. It was furnished with two
chairs and a table (Fig. 2). This served as an adaptation
room. The second room was the test room (3.68 m length
32.88 m wide 33 m high); it had no windows so that no
natural light entered the office, thereby eliminating any
fluctuations of natural daylight. The walls and ceiling were
painted white and the floor dark gray. Neutral colors would
reduce any effects of the room on the colors to be used in
the experiment. The experimental room was divided by a
partition in order to establish an individual study area
(1.80 m long 31.30 m wide 33 m high) (Fig. 3). Colors
were manipulated by hanging Corflute panels, 180 cm 3
180 cm 32 mm thick, which were painted vivid red (S
1080-R), vivid yellow (S 0580-Y), vivid blue (S 1565-B),
pale red (S 0540-R), pale yellow (S 0540-Y), or pale blue
(S 0540-B) (Fig. 4). Each colored panel was hung on the
wall so that it extended 1.70 m above the top of the desk.
The room was furnished with a white student desk and one
gray chair. The student desk was centred along the wall,
and faced the colored panel. In addition, the desk of the
experimenter was located behind the participant on the left
side so that she could check the time and measure the heart
rate (HR) of the participant during the experimental ses-
sion. Ambient temperatures of Rooms 1 and 2 were
recorded on several occasions on different days; the tem-
perature of both rooms was a constant 25 C. The rooms
were located internally in the basement of a multi-level
building; their temperature and humidity vary little
throughout the year. The test room was illuminated with
four Osram flourescent tubes (36 W), having a correlated
color temperature (CCT) of 3500 C and a color rendering
index (CRI) of 75–82; and 3350 lumens. The average of
illuminance was 360 Lux, illuminance and luminance were
measured using digital light meter, model Lutron LM-
Experimental Procedure
The participants in this study were first taken to a wait-
ing room (Fig. 2), which was located outside the door of
the test room. In this room, the participants were adminis-
tered the Ishihara Color Blindness Test (ICBT). After the
participants passed this test, they were asked to read the
information sheet outlining the experimental procedure.
The purpose of the study was explained to the partici-
pants, and they were then administered the Learning
Channel Preference questionnaire in order to identify their
learning styles. This procedure was followed on the first
visit only.
The participants were told that they needed to be in the
first room for at least five minutes before entering the test
room in order to adapt to room conditions and to have
their HR measured before the experiment. Participants
Fig. 2. Plan of the waiting room where participants were
informed about the experimental procedure, administered
the Ishihara Color Blindness Test (ICBT), and had their
baseline HR measured. Participants remained in this room
for 5 min in order to adapt to room conditions.
Fig. 3. Plan of the test room showing the relative posi-
tions of the experimenter’s desk, the participant’s desk,
the colored panel, and the partition.
4 COLOR research and application
were then tested individually in the test room and seated
at the desk facing the selected colored panel. The partici-
pants were asked first to focus on the colored panel for 5
min. At the end of the five minutes, they rated their emo-
tions on the Color Emotion questionnaire. Waiting for 5
min before completing the color emotion questionnaire
reduces any interference from the initial adaptive
response to the colored panel. K
uller and Mikellids
emphasize the importance of controlling the exposure
time to the color stimulus. If the exposure time is too
short, such as 1 min, it will measure just the initial
response to the color. After completing the color emotion
questionnaire, participants’ heart rates were taken again.
To assess their learning performance, they were given a
reading task, which involved studying the text and then
answering comprehension questions for 10 min. Finally,
they were interviewed for five minutes to obtain more in-
depth qualitative data. All participants were tested indi-
vidually. To eliminate expectancy bias, participants were
not forewarned concerning the exact colors to which they
would be exposed. The researcher told them “this experi-
ment looks at how the colors of space impact on the
learning activity.”
This process was conducted six times and each time
the participant was exposed to a different color condition.
The order in which the colors were presented was coun-
terbalanced across participants according to a Balanced
Latin Square design.
There was 1 day free between one
session and the next which served as a wash-out period,
to reduce carry-over effects from one color to the other.
The experiment took twenty minutes for each color. Data
on the participant’s emotional state, physiological state
and comprehension test performance were subsequently
analyzed with inferential statistics.
A series of generalized linear mixed models (GLMMs)
were tested in order to determine whether the partici-
pant’s emotional state, physiological state and compre-
hension test performance varied as a function of color.
The GLMM represents a special class of regression
model. The GLMM is “generalized” in the sense that it
can accommodate outcome variables with markedly non-
normal distributions; the GLMM is “mixed” in the sense
that it includes both random and fixed effects. For the
present GLMMs, there was one nominal random effect
(participant) and two categorical fixed effects (hue: red,
yellow, blue; whiteness: vivid, pale). The GLMMs were
implemented through SPSS’s (Version 20) GENLIN-
MIXED procedure. To optimize the likelihood of conver-
gence, a separate GLMM analysis was run for each
outcome measure.
Reading Comprehension
For reading comprehension, the results show that the
main effect of whiteness was significant (F[1,138] 55.41,
P50.022). Reading comprehension scores were signifi-
cantly higher in the vivid color conditions compared to
the pale color conditions. However, the main effect of
hue was non-significant (F[2,138] 50.39, P50.676).
Fig. 4. The six color schemes used in the study. Colors were painted onto Corflute panels and hung in front of the desk
where the participant was seated.
Volume 00, Number 00, Month 2015 5
These results indicate that reading performance did not
differ significantly across the three hues. As well as, there
was no significant Hue x Whiteness interaction
(F[2,138] 50.24, P50.784) (see Fig. 5).
Heart Rate Response
The main effect for hue was significant
(F[1,138] 511.93, P<0.001). The graph suggests that,
regardless of whiteness, the red and yellow conditions
caused increases in heart rate whereas the blue condition
caused a decrease in heart rate. LSD (least significant dif-
ference) contrasts conducted on the main effect for hue
indicated that heart rate increased to the same degree in
the red and yellow conditions (P=0.315), and there was
a significant difference between the heart rate decrease in
the blue condition and the heart rate increases in the red
and yellow conditions (P<0.001 for both contrasts). The
Hue 3Whiteness interaction, however, was non-
significant (F[2,138] 50.60, P50.548). Likewise, the
main effect for whiteness was not significant
(F[2,138] 53.64, P50.058) indicating that changes in
heart rate did not differ significantly between the pale and
vivid conditions (see Fig. 6).
Emotional Responses
For the dark/light scale, the Hue 3Whiteness interac-
tion was significant (F[2,138] 55.37, P50.006) indicat-
ing that main effects of hue and whiteness can no longer
be interpreted independently of each other. This interac-
tion is graphed in (Fig. 7). The graph suggests that indi-
viduals tended to rate towards the light end of the scale
in the pale condition and towards the dark end of the
scale in the vivid condition. LSD contrasts conducted
across the interaction indicated that red was rated signifi-
cantly darker than yellow (P<0.001) and blue (P<
0.001), and blue was rated significantly darker than yel-
low (P=0.009) but only in the vivid condition. In the
pale condition, there were no significant differences in
ratings across hues.
However, the Hue 3Whiteness interaction was non-
significant for pleasant/unpleasant (F[2,138] 51.27, P5
0.285), fresh/stale (F[2,138] 51.40, P50.250), heavy/
light (F[2,138] 50.86, P50.425), calm/exciting
(F[2,138] 50.21, P50.811), tense/relaxed (F[2,138]
0.38, P50.687), warm/cool (F[2,138] 50.67, P5
0.515), dull/sharp (F[2,138] 51.05, P50.353) and inter-
esting/boring (F[2,138] 50.41, P50.668). For these
scales, therefore, each of the two main effects can be
interpreted independently of one another.
The main effect of whiteness was found to be signifi-
cant in terms of “pleasant/unpleasant” (F[1,138] 514.21,
P<0.001), “fresh/stale” (F[1,138] 511.88, P50.001),
“heavy/light” (F[1,138] 571.10, P<0.001), “calm/
exciting” (F[1,138] 57.52, P50.007), “tense/relaxed”
(F[1,138] 531.91, P<0.001), “warm/cool” (F[1,138] 5
20.05, P<0.001) and “dull/sharp” (F[1,138] 58.98,
P50.003). These effects indicate that, regardless of hue,
the pale conditions were rated as significantly more pleas-
ant, fresh, calm, dull, relaxed and cool than the vivid
Fig. 5. The data represent group means for reading
scores and their 95% confidence intervals. Whiteness had
a significant effect on reading scores (P50.022).
Fig. 6. The data represent group means for HR fluctua-
tions from baseline and their 95% confidence intervals.
Hue had a significant effect on heart rate (P<0.001).
Fig. 7. The data represent group means for assessments
on the dark/light scale and their 95% confidence intervals.
The Hue 3Whiteness interaction was significant
(P<0.006) indicating that main effects of hue and white-
ness cannot be interpreted independently of each other.
6 COLOR research and application
conditions. In addition, pale colors tended to be rated as
light whereas vivid colors tended to be rated as heavy.
However, whiteness was found to have no significant
effect on “interesting/boring” (F[1,138] 50.45, P5
0.502) indicating that, regardless of hue, ratings did not
differ significantly between the pale and the vivid
The main effect of hue was significant for “pleasant/
unpleasant” (F[2,138] 511.32, P<0.001), “fresh/stale”
(F[2,138] 510.33, P<0.001), “heavy/light” (F[2,138] 5
12.53, P<0.001), “calm/exciting” (F[2,138] 512.56,
P<0.001), “tense/relaxed” (F[2,138] 520.27, P<0.001),
“warm/cool” (F[2,138] 530.69, P<0.001) and “interesting/
boring” (F[2,138] 53.59, P50.030). LSD contrasts con-
ducted on the main effect for hue indicated that, regard-
less of whiteness, blue was rated significantly more
pleasant than either red (P<0.001) or yellow (P5
0.003); no significant difference was found between
red and yellow (P=0.414). Blue was rated as signifi-
cantly calmer than either red (P=0.007) or yellow
(P<0.001); and red was rated significantly calmer than
yellow (P=0.025). Blue was rated significantly less
tense than either red (P<0.001) or yellow (P<0.001);
there was no significant difference between red and
yellow (P=0.231).
In addition, blue was rated significantly cooler than
either red (P<0.001) or yellow (P<0.001); there was no
significant difference between red and yellow (P=
0.696). Moreover, the participants rated blue as signifi-
cantly more interesting than red (P=0.008); there was
no significant difference between red and yellow (P=
0.152) or between blue and yellow (P<0.219). Red was
rated as significantly less fresh than either blue
(P<0.001) or yellow (P=0.001); there was no signifi-
cant difference between blue and yellow (P=0.277).
Red was also rated as significantly heavier than either
blue (P<0.001) or yellow (P<0.001); there was no sig-
nificant difference between blue and yellow (P=0.346).
A nonsignificant effect of hue was found for “sharp/dull”
(F[2,138] 53.06, P50.050) indicating that ratings did
not differ significantly across the three hues.
Interview Results
Each participant attended a post-test interview. For
each of the six colors, participants were asked “does this
color motivate you to study and help you to focus?
Why?” Responses to this question would provide subjec-
tive data regarding the color’s impact on emotions and
learning performance, and general reactions to the color.
Participants were briefed before the interview so that they
fully understood its purpose and the topics that would be
covered. The responses for each color condition were
analyzed for commonalities and differences. Responses
were coded and subjected to a thematic analysis. Qualita-
tive findings were categorized into seven themes: emo-
tion, physical bodily, association, spatial properties,
motivation, intellectual activity and task.
Pale Colors
The results indicated that hues with a higher level of
whiteness such as pale blue and pale yellow evoked the
more active emotions, and had a more positive impact on
the physical body, motivation, intellectual activity and
spatial properties. For example, 70% of participants
believed that pale blue was associated with calmness,
happiness, relaxation, comfort, and peacefulness, because
it is related to the calming aspects of nature such as the
sky and water. In addition, participants thought that pale
blue made them active, motivated them for study and
increased their concentration levels. The participants
made the following comments regarding pale blue:
“I feel excited with this color because it is associated
with nature like sky and water ... I feel I am in an open
space may be it is a cool and peaceful color. It did
increase my concentration on the reading task ... so it
motivates me to study” (Participant 8)
In addition, 58% of respondents also believed that pale
yellow had positive effects on learning performance. It was
associated with positive feelings such as happiness, cheer-
fulness, and relaxation. The participants described it as a
sun, a source of light, and said that it made them feel
active, awake, and enlarged the space; it focused their
attention on the reading task and motivated them to study:
“I feel good ... it is very motivated color for study
because this color brings light ... and I like shiny colors.
It helps me to be active and alert ... more focused on
reading task” (Participant 21)
However, 66% of the responses indicated that pale red
was considered boring, annoying, bright, warm and
uncomfortable, because it was believed to increase nerv-
ousness, tiredness and distraction. In addition, the partici-
pants saw pale red as a very feminine color, suitable for
bed rooms but not for learning environments. As a result,
it was agreed that pale red did not motivate them to study
or focus on the reading task:
“It is tense color ... I cannot focus with it because it is
slightly bright ... and it is girly color” (Participant 11)
“This color makes me feel nervous and stress because
it is slightly bright and there is a strong reflection that
causes distraction when I read. I cannot focus and it does
not motivate me to study ... it may appropriate for party
activity” (Participant 2)
Vivid Colors
The majority of participants agreed that the vivid red
and the vivid yellow were not suitable colors for individ-
ual study areas because they had a negative impact on
their emotional state, physical body, intellectual activity
and motivation. For example, 66% of participants
reported that vivid red was associated with depression,
annoyance, discomfort, warmness, and with negative con-
cepts such as blood, war, and danger. Furthermore, the
participants felt nervous and stressed, and said that the
color distracted their vision because of its highly reflec-
tive nature. The participants agreed that vivid red did not
Volume 00, Number 00, Month 2015 7
motivate them to study for any length of time, and they
found it difficult to focus on the reading task. The partici-
pants made similar comments about vivid red:
“I feel uncomfortable with this color because it is dark
color ... doesn’t help me to focus because it is distractive
color and causes eye fatigue ... It is very active but it
doesn’t encourage me to study” (Participant 4)
“It doesn’t help me to study because it is related to
war, blood, and danger .... it’s too vivid so I cannot
focus on the reading task” (Participant 17)
Likewise, vivid yellow was considered an uncomfort-
able color for studying. It was perceived as a very bright,
annoying and strong color. Moreover, 75% of the partici-
pants reported that vivid yellow increased their discom-
fort level. This occurred, they believed, because yellow
with its high chromaticness had a negative effect on the
physical body. Participants also thought that the reflective
nature of vivid yellow was distracting, caused eye fatigue,
and made them feel nervous, tired and hot. In addition, it
was reported that vivid yellow was very arousing and
they believed that it may be suitable for tasks that
demand a high level of activity such as sport. Further-
more, the participants confirmed that it was difficult to
concentrate on the reading task; and therefore, not ideal
for motivating them to study:
“It is so bright color ... I feel hotness with this color it
is like a sun ... It is unmotivated color for study may it
good for sport activity or for kids’ places” (Participant 6)
“It is distractive and annoying color ... uncomfortable
for eyes because it reflects too much light. It does not
motivate me to study” (Participant 22)
A few participants 25%, however, associated vivid yel-
low with positive feelings:
“It is shiny color it helps me to read clearly and con-
centrate on the reading task ... It is active more energetic
and natural color like daylight” (Participant 3)
In contrast, vivid blue was considered an appropriate
color for learning environments. For example, 62% of
participants thought that it had positive effects on their
emotions, performance, physical body, and concentration
levels. It was perceived as a calming, cool, quite bright
and comfortable color, and related to aspects of nature
such as the sky, beach and summer. The participants
reported that vivid blue made them awake and active, and
helped them to concentrate. They commented:
“It is comfortable and it makes me awake and active
because it is related to clear sky and sea water and I
really like this atmosphere to study ... more concen-
trated” (Participant 3)
Table I summarizes the results of the interview.
The main goal of the present research was to investigate
the effects of different colors on students’ learning, emo-
tions and heart rates within the individual study areas of
university libraries. The study took place in a full scale
space that was designed to simulate a typical space for
individual study in the university library.
Heart Rate Responses
Baseline heart rate was recorded in the waiting room
(gray color condition), and then recorded again during the
experimental session after 5-min exposure to each of the
six colored panels. The results indicated that changes in
heart rate did not differ significantly between pale colors
and vivid colors. However, hue induced significant
changes in heart rate. Red and yellow increased heart rate
whereas blue decreased heart rate. Heart rate increased to
the same degree in the red and yellow conditions (P=
0.315); there was a significant difference between the
heart rate decrease in the blue condition; and the heart
rate increased in the red condition (P<0.001) and the
yellow condition (P<0.001). This finding supports the
notion that color has a strong impact on the physiology
of people who stayed in the colored room.
In addition,
several color studies have indicated that long-wavelength
colours such as red and yellow are more arousing than
short-wavelength colors such as blue and green.
It seems that warm colors such as red and yellow,
regardless of whiteness or chromaticness, have arousing
properties that stimulate people and make them feel more
active, producing increases in heart rate. These results
support the hypothesis that heart rate will vary as a func-
tion of the color of the learning environment.
Reading Comprehension
Reading comprehension varied across the different col-
ors as expected. Specifically, the whiteness dimension
(but not the hue) had a significant effect on reading com-
prehension. Reading comprehension scores were higher
for the vivid colors compared to the pale colors. These
findings agree with the findings of Kwallek et al.,
showed that participants made more errors in the paler
color offices than in the darker color offices. This effect
seemed to be related to the whiteness of the hues. Pale
colors may, in some sense, be more distracting than vivid
TABLE I. Results summary of interview.
Colours Pale Vivid
Blue Motivates study, comfortable for eyes, facilitates concentration Active, relaxed, helps to focus attention on study
Red Distractive, does not motivate for study, does not focus attention,
induces feelings of stress and nervousness
Tense, annoying, does not motivate study and
does not facilitate concentration
Yellow Comfortable for eyes, active, motivates study, helps to focus
Does not motivate for study, impairs attention,
distractive, feelings of hotness
8 COLOR research and application
colors. This suggests that the chromaticness and white-
ness (NCS nuance) of a color play an important role in
determining the effects of the color on students’ learning
The findings are also consistent with the notion that
vivid colors are more arousing than pale colors. If the
reading tasks are difficult, therefore, the vivid color con-
ditions may increase arousal to optimum levels, thereby
enhancing learning performance. This finding supports the
Yerkes–Dodson Law about the relationship between
arousal and performance.
Another explanation for this
finding is that the vivid colors were considered to be
more distracting than the pale colors because of their
higher chromaticness; perhaps participants become more
focused on the reading tasks in an attempt to ignore the
distracting stimulus. Interestingly, participants who felt
positive in the pale colour conditions showed enhanced
learning in the vivid color conditions.
Consistent with the findings of K
uller, Mikellides, and
and Ou et al.,
the results clearly indicate that
both hue and whiteness had a strong impact on partici-
pants’ emotional reactions. The results also supported the
second hypothesis that emotions will vary as a function of
the color of the interior environment. The participants felt
more positive in the pale color conditions compared to the
vivid color conditions, because pale colors were perceived
to be pleasant, fresh, calm, relaxed, light, cool and less
sharp. These findings are consistent with those of Manav,
which showed that colors with high value (whiteness)
were associated with positive emotional responses. The
participants reported that pale colors increased the feelings
of relaxation and calmness, making them less active and
energetic and therefore less motivated to study.
Emotion ratings also differed significantly across the
three hues. It was found that blue put the participants into
a more positive state, because it was perceived to be
more pleasant, fresher, calming, relaxing, cooler, lighter,
more interesting and less sharp compared to the other two
hues. These findings are contrary to previous findings
which showed that hues did not have a significant impact
on emotion.
The participants were interviewed individually and
asked about the impact of each color on their emotions
and learning performance. They reported that, in addition
to the effect of color on emotions, color can have a per-
ceived impact on the physical body, motivation, intellec-
tual activity, and spatial properties of the environment. In
general the blue colours, whether pale or vivid, were con-
sidered appropriate colors for learning in the individual
study area. The blues were perceived to be relaxed and
calm because of their association with the calming
aspects of nature such as the sea and sky. The blues were
also comfortable for vision, and enlarged subjective space
by virtue of their coolness and lightness. Compared to
pale blue, vivid blue helped participants remain alert,
active and focused for a longer time. This finding is con-
sistent with the results of the comprehension test, which
indicated that scores were higher in the vivid color condi-
tions compared to the pale conditions. If the reading task
requires careful attention, then colors such as vivid blue
can help students to be more focused on their tasks. In
contrast, pale blue can be helpful for tasks that require
insight such as creative or mathematical tasks. Perhaps
subjects in the vivid blue condition attempted to ignore
the bright surrounding color by concentrating more on the
test, thereby making fewer errors.
Pale yellow was also perceived as more suitable for
studying in the individual study room than vivid yellow.
The participants reported that pale yellow had a positive
impact on their learning performance and it was a color
that motivated them for studying. They concurred that it is
related to positive emotions such as happiness, cheerfulness
and relaxation. The results corroborate previous research
concerning the qualities of yellow. For example, Clarke
and Costall
and Ballast
found that yellow was associ-
ated with smiling, cheerfulness and joviality. The partici-
pants reported also that pale yellow was like the sun, it
reflects light and makes them feel active and awake, which
helped them focus on the reading tasks and motivated them
to study. However, these subjective reports are inconsistent
with the objective data which showed that performance on
the comprehension task was poorer in the pale color condi-
tions compared to the vivid color conditions.
With the red conditions, the results suggest that vivid
red and pale red are unsuitable for learning, having a neg-
ative impact on intellectual activity. Specifically, partici-
pants reported that these colors impaired their
concentration. They claimed that vivid and pale red
increased stress levels because they strongly reflected
light, were distracting and over stimulating. This finding
is inconsistent with the comprehension test results for the
vivid conditions. In general, most participants believed
that pale colors with high whiteness would be appropriate
color schemes in learning environments because they are
considered calm and relaxing. However, the calmness and
relaxation aspects may not help students to be alert and
active. Therefore, the participants performed better in the
vivid color conditions, because these colors have arousing
properties that stimulate neural activity. According to
Draper and Brooks,
colors should arouse and activate
the brain in order to help students undertake activities in
the learning environment within the library.
The study found that color affected emotions, heart rate
and the reading performance. Hue and whiteness had a
significant impact on students’ emotions. The pale colors
were rated more positively than the vivid colors because
they were considered to be calming and relaxing. Blue
Volume 00, Number 00, Month 2015 9
and yellow put the participants into a more positive state.
In addition, the results suggest that whiteness had a sig-
nificant impact on learning as reflected in comprehension
test scores; comprehension was significantly better in the
vivid color conditions. Furthermore, heart rate was signifi-
cantly affected by hue; it increased in the red and yellow
conditions and decreased in the blue condition. This sug-
gests that colors can evoke physiological and emotional
responses in individuals that focus attention and thereby
facilitate learning.
This study has some limitations. First, although the
number of participants was calculated by a power analysis
program, the size of the sample is considered small. Also,
the time spent studying in various colour conditions was
short. In addition, this study was focused on the impact
of colour on adult students, therefore, it may not be appli-
cable for children or elderly.
Thus, more research is needed to investigate these
points. The next step would be to conduct long-term stud-
ies in real environments. In addition, research is needed
to address the effect of colour in other learning spaces
such as group study rooms and computer study areas. The
proposal that physiological and emotional reactions medi-
ate the impact of color on learning remains to be tested.
1. Jamieson P. Designing more effective on-campus teaching and learning
spaces: A role for academic developers. Int J Acad Dev 2003;8:119–133.
2. Oblinger DG. Space as a change agent. In: Oblinger DG, editor. Learn-
ing Spaces. Washington: EDUCAUSE; 2006. p 1.1–1.2.
3. Busato VV, Prins FJ, Elshout JJ, Hamaker C. Learning styles: A cross-
sectional and longitudinal study in higher education. Br J Educ Psychol
4. Melton CD. Bridging the cultural gap: A study of chinese students’
learning style preferences. RELC J 1990;21:29–54.
5. Wang H, Russ RR. Computer classroom wall color preference and the
relationship with personality type of college students. Color Des Crea-
tivity 2008;2:1–13.
6. K
uller R, Mikellides B, Janssens J. Color, arousal, and performance—
A comparison of three experiments. Color Res Appl 2009;34:141–152.
7. Read MA, Sugawara AI, Brandt JA. Impact of space and color in the
physical environment on preschool children’s cooperative behavior.
Environ Behav 1999;31:413–428.
8. Gaines KS, Curry ZD. The inclusive classroom: The effects of color on
learning and behavior. J Fam Consumer Sci Educ 2011;29:46–50.
9. Ainsworth RA, Simpson L, Cassell D. Effects of three colors in an
office interior on mood and performance. Perceptual Motor Skills 1993;
10. Stone NJ English A. Task type, posters and workspace color on mood,
satisfaction, and performance. J Environ Psychol 1998;18:175–185.
11. Hamid PN, Newport AG. Effect of color on physical strength and
mood in children. Perceptual Motor Skills 1989;69:179–185.
12. Ballast DK. Interior Design Reference Manual. Belmont: Professional
Pub, Inc; 2002.
13. Clarke T, Costall A. The emotional connotations of color: A qualitative
investigation. Color Res Appl 2008;33:406–410.
14. Kwallek N, Lewis CM. Effects of environmental color on males and
females: A red or white or green office. Appl Ergonom 1990;21:275–
monochromatic office interior colors on clerical tasks and worker
mood. Color Res Appl 1996;2:448–458.
16. Stone NJ. Designing effective study environments. J Environ Psychol
17. Yerkes RM, Dodson JD. The relation of strength of stimulus to rapidity
of habit-formation. J Comp Neurol Psychol 1908;18:459–482.
18. Kuschel S, Forster J, Denzler M. Going beyond information given:
How approach versus avoidance cues influence access to higher order
information. Social Psychol Pers Sci 2010;1:4–11.
19. Pile JF. Color in Interior Design. New York: McGraw-Hill; 1997.
20. Abbas N, Kumar D, Mclachlan N. The Psychological and Physiological
Effects of Light and Colour on Space Users, 27th Annual International
Conference of the IEEE Engineering in Medicine and Biology Society,
Shanghai China; 2006.
21. Caldwell JA, Jones GE. The effects of exposure to red and blue light
on physiological indices and time estimation. Perception 1985;14:19–
22. Brown CR. Interior Design for Libraries: Drawing on Function and
Appeal. Chicago: Carol R. Brown; 2002.
23. Kaya N, Crosby M. Color associations with different building types:
An experimental study on american college students. Color Res Appl
24. Faul F, Erdfelder E, Buchner A, Lang AG. Statistical power analyses
using G* power 3.1: Tests for correlation and regression analyses.
Behav Res Methods 2009;41:1149–1160.
25. Ishihara S. Ishihara’s Tests for Color-Blindness. Tokyo: Plate Edition;
26. O’Brien L. Learning styles: Make the student aware. NASSP Bull
27. Swedish Standards Institute. The International Language of Colour
Communication NCS Colour System. Stockholm: Scandinavian Colour
Institute; 2004.
28. Osgood CE, Suci GJ, Tannenbaum PH. The Measurement of Meaning.
USA: University of Illinois Press; 1957.
29. SAT Reading Comprehension. Accessed September 2012. Available at:
30. K
uller R, Mikellids B. Simulated studies of color, arousal, and comfort.
In: Marans RW, Stokols D, editors. Environmental Simulation:
Research and Policy Issues. New York: Plenum Press; 1993. p 163–
31. Lewis JR. Pairs of latin squares that produce digram-balanced Greco-
latin designs: A basic program. Behav Res Methods Instrum Comp
32. Venolia C. Healing Environments: Your Guide to Indoor Well-Being.
Berkely: Celestial Arts; 1988.
33. Ou L, Luo MR, Woodcock A, Wright AA. study of color emotion and
color preference. Part I: Color emotions for single colors. Color Res
Appl 2004;29:232–240.
34. Manav B. Color-emotion associations and color preferences: A case
study for residences. Color Res Appl 2007;32:144–151.
35. Draper J, Brooks J. Interior Design for Libraries. Chicago: American
Library Association; 1979.
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The computer classroom is widely used in colleges and high schools in the United States. In order to create a more comfortable and effective teaching environment, the most preferred wall colours for a computer classroom were examined in the study. Also, personality types of students were tested to determine if type had an impact on wall colour preference. The sample consisted of 145 undergraduate interior design students at a university located in the south-western United States. Students ranked 15 slides that depicted the same computer classroom with 15 different wall colour applications. Results indicated that personality type did not impact colour preference for a computer classroom. The results suggested cool colours in the Master Palette Color System are preferred more for wall colour in a computer classroom.
Following a literature review of some recent research on learning styles and EFL-related research in the People's Republic of China, this article describes a replication of a study done by Reid in 1987 of learning style preferences of ESL students in the U.S. With minor modifications, the same questionnaire asking students to identify their learning style preferences was administered in either Chinese or English to 331 students at five universities in the PRC. Statistical analyses indicated that language of the questionnaire did not in fluence the outcome; that sex of the respondent, level in college, years of English study, and number of semesters with a foreign teacher are all related to learning style differences; and that PRC students appear to have multiple major learning styles. The study concludes with suggested activities for the ESL classroom which are appropriate to each of the four basic perceptual learning styles.
Design elements within child care facilities are thought to have important effects on children’s behavior. Empirical studies that examine features of the physical environment, such as color, wall surfaces, and vertical space, and how they affect development are sparse. Using Gibson’s Ecological Theory of Visual Perception, this study investigated the impact that differentiated space, including changes in ceiling height and wall color, has on children’s cooperative behavior. Thirty preschool children experienced four different spatial conditions in small groups. Multivariate repeated-measures analyses of variance indicated that differentiation in ceiling height or wall color were related to higher levels of cooperative behavior among preschool children. As well, developmental level and gender were significant predictors of children’s cooperative behavior between spatial conditions. Findings from this study can benefit preschool administrators and designers concerned with developing children’s environments that encourage cooperative behavior in preschool children.
Three experiments examine the hypothesis that subtle cues of approach orientation facilitate access to higher order information, whereas subtle cues of avoidance orientation impede it. To test these predictions, in two studies, a backward-masking paradigm thought to measure access to higher order information at early perceptual stages was used, and arm positions of arm flexion versus arm extension were unobtrusively manipulated to induce interoceptive approach or avoidance situations. In a third study, using a procedural priming paradigm, exteroceptive cues associated with benign versus danger situations were manipulated and metaphor understanding served as a dependent variable. As predicted, although the diverse manipulations did not elicit different mood states, interoceptive and exteroceptive approach cues enhanced going beyond the information given, whereas avoidance cues impaired it. Implications are discussed.