Available via license: CC BY 4.0
Content may be subject to copyright.
buildings
Article
The Influence of Learning Styles on Perception and Preference
of Learning Spaces in the University Campus
Shiqi Wang * and Chenping Han
Citation: Wang, S.; Han, C. The
Influence of Learning Styles on
Perception and Preference of
Learning Spaces in the University
Campus. Buildings 2021,11, 572.
https://doi.org/10.3390/
buildings11120572
Academic Editors: Pamela Woolner
and Paula Cardellino
Received: 25 October 2021
Accepted: 22 November 2021
Published: 23 November 2021
Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims in
published maps and institutional affil-
iations.
Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
School of Architecture and Design, China University of Mining and Technology, Xuzhou 221116, China;
hanchenping@cumt.edu.cn
*Correspondence: wangshiqi@cumt.edu.com
Abstract:
Good academic performance will occur when learning spaces match or support individual
preference and needs. This effect depends on environmental characteristics and individual attributes.
Learning styles (LSs) have been used as a tool to capture the behavioral and psychological charac-
teristics of learners in the process of learning activities, which provide instructions to address their
learning needs. However, few have focused on the perceptual characteristics of learning space from
the view of distinct learning styles. The research aims to identify which kinds of learning spaces
in university campus have been preferred by students with different learning styles respectively
and the spatial characteristics which have significant influence on the distinct evaluation results;
the research consists of 178 college students’ LSs measurement conducted by the Index of Learning
Styles questionnaire and their subjective assessment to five typical learning spaces obtained by
5-point Likert-type scale. Then, the key spatial influencing factors were identified by the focus group
interviews; the results firstly ranked the learning spaces according to their satisfaction evaluation
and restorative potential. The self-study rooms are rated highest, followed by professional classroom,
traditional classroom, and multimedia classroom. Then, two dimensions of learning styles were
proved as having considerable effects on perception. Specifically, there are significant differences
between visual and verbal learners’ evaluations of multimedia classrooms and traditional classrooms,
and between global and sequential learners’ evaluations of multimedia classrooms, informal learning
spaces, and learning buildings. The other two dimensions including perceiving and remembering
have no obvious impacts on learners’ perception of any learning spaces. At last, the important
influence factors of perceptions of five typical learning spaces were identified, respectively, and
their different effects on various groups were discussed. For example, the serious atmosphere in
traditional classrooms was regarded as a motivation for sensing learners but a stress for intuitive
learners. The studies emphasize the perceptual difference on learning space in terms of students’
unique learning styles and key points for each kind of learning space with regard to satisfaction of
personalized needs. However, before it can be used by designers as tools, more research is needed.
Keywords:
built environment of education; learning space; innovative learning environments;
restorative perception; learning style
1. Introduction
For the past decade, much attention has been paid on the influence of building spaces
on people’s cognitive activities [
1
–
4
]. Some special spatial characteristics will stimulate the
operations of the undirected attention and make it rest, which results in positive changes
of mind and body, including mental restoration, stress recovery, efficient cognitive process,
good emotions, and so on [
5
–
7
]. This has become a hotspot especially on the research
of official or learning spaces, where people engage in plentiful brain work and suffer
from mental fatigue more easily [
8
–
10
]. In a transitional stage of physical and mental
growth, undergraduates have weaker abilities to identify and process the environmental
information, which leads to more mind confusion and exhaustion than adults [
11
–
13
]. In
Buildings 2021,11, 572. https://doi.org/10.3390/buildings11120572 https://www.mdpi.com/journal/buildings
Buildings 2021,11, 572 2 of 13
developing countries, like China, college students are suffering from emotional problems
and peer pressure [
14
]. Therefore, there is a pressing need to identify the effect of learning
space on college students’ psychology and behaviors in order to provide building design
strategies at the aim of health promoting and efficient cognitive activities.
The relationship between learning spaces and students’ self-development and well-
being has been studied for a long time [
15
–
17
]. Many spatial elements have been proved
to effect students’ learning behaviors, learning outcomes, self-reported life quality and
well-being, including physical conditions (lighting, airflow, temperature, etc.), facilities
or furniture, accessibility, spatial scales, and so on [
18
–
23
]. Moreover, it has been demon-
strated that the greenness (such as potted plant, flowers, natural window view, green wall
paintings, etc.) in the learning space offers high restorative quality, which is beneficial
for efficient cognitive tasks and innovations [
24
–
27
]. However individual perception and
understanding of the surrounding environment may differ considerably among persons
with distinct characters, such as gender, age, education level, life experience, thinking ways,
cultural background, or some other personal attributes [28–32].
The LS describes individual features closely related to learning activities, which
supplies a potential variable affecting the perception of learning spaces. However, it will
be involved in a confused and expanding area, because how the learning styles would
be measured accurately and utilized and how much it could affect learning outcomes is
controversial [
33
]. Although the inconsistent opinions result in its limitation in Educational
Science research, the LS have indeed been proved as reflecting the personality including
the preferred information and preferred decision-making ways [
34
], which could supply
a perspective or method of understanding the preference for the learning spaces. We
focus more on individual difference represented by it and the resulting impacts on spatial
perception, rather than the learning style itself.
Thus, the model based on personality rather than fixed trait was selected in the present
study, according to which the learning style is conceptualized as a kind of comprehensive
personal characteristic related to learning activities, cognitive traits, and psychological
behaviors, remains stable within a certain period of time, and will be affected or changed
gradually and slowly by the environment [
35
]. According to Felder-Silverman learning
style model (FSLSM), there were four dimensions to describe the learning styles cover-
ing processing, perceiving, remembering, and understanding information [
36
,
37
]. Each
dimension contains two opposing categories (Table 1). Compared with other measuring
methods, this model provides more detailed definition of how students prefer and con-
duct their learning activities, according to which, 16 learning styles are deduced by the
Index of Learning Styles (ILS) questionnaire consisting of 44 items [
38
]. It has been widely
used in related studies in China. For example, it has been proved that the learning styles
preferences would affect students’ academic performance, choices, and mood [
39
,
40
]. In
addition, more advanced teaching methods and more efficient courses were explored with
its assistance [41].
To sum up, through literature reviewing it is suggested that the learning space has a
significant influence on students’ behavior and mind, which varies because of individual
perception. As an important variable, the LS provides more definite and explicit identifica-
tion of students’ characters which should be used for exploring the effects of individual
attributes on the spatial perception more deeply. Then, from this perspective rather than
other ordinary demographic variables, specialized and well-targeted directions will be
put forward to guide the design of campus space with the aim of optimizing academic
outcome and promoting psychological health. In spite of increasing research and focus, it
is still absent from related analysis [42–44].
Buildings 2021,11, 572 3 of 13
Table 1. The description of four learning styles.
Dimension Classification Description
Process Active (A) Prefer trying things out and putting ideas into practice directly, like to
discuss with others and learn new knowledge by working in group.
Reflective (R) Prefer thinking things through alone and be good at organizing the
material and summarizing the information.
Perceive Sensing (Sen) Prefer concrete learning materials, often deal with problems with
standard approaches and show more patience with details.
Intuitive (I) Do well in facing abstract knowledge and like to try new things, tend
to be more innovative and creative.
Remember Visual (Vis) Easier to remember what they have seen, including pictures, charts,
and flow-diagrams.
Verbal (Ver)
Specialize in obtaining information from text contents whether they are
spoken or written.
Understand Sequential (Seq)
Like to follow an established logic and grasp knowledge step by step,
they often focus more on details and could explain how they
understand it clearly.
Global (G)
Prefer to start with holistic framework of knowledge, they usually learn
material randomly without thinking about connection among each part
and get a clear understanding after absorbing enough materials.
Therefore, our study draws on the effects of LS on the perception of five typical
learning spaces in university colleges, which have been centered on frequently in previous
studies [
45
–
49
], including (1) traditional classroom (hold 100–200 students, support face-
to-face teaching and learning, characterized by rows of fixed desks, tables and chairs all
facing the instructor at one end of a rectangular room, usually used for a large and public
class); (2) multimedia classroom (hold 20–30 students, equipped with advanced electrical
facilities supporting visualization and data retrieval, like computers or projectors, which
students are free to utilize, usually for small special teaching, discussions or meetings);
(3) professional classroom (places where students can use professional instruments to
conduct academic experiments or professional exercises, usually for students who major in
science and engineering, arts or design and be utilized by a fixed group, such as laboratory,
painting room, and model making room, students usually have exclusive positions there);
(4) self-study room (usually existing in specialized learning buildings, like a library and
a learning center, support self-directed learning activities without teachers’ involvement,
such as searching for paper or electronic materials and discussion in groups); (5) informal
learning spaces (places where student self-directed learning activities happened out of
class, usually do not specifically target learning and have other functions, characterized by
social support, such as social hubs, internal student streets, atrium spaces, or reimaging
corridors). The examples of learning spaces are shown in Figure 1.
Buildings 2021, 11, x FOR PEER REVIEW 3 of 14
Intuitive (I)
Do well in facing abstract knowledge and like to try new things, tend
to be more innovative and creative.
Remember
Visual (Vis)
Easier to remember what they have seen, including pictures, charts,
and flow-diagrams.
Verbal (Ver)
Specialize in obtaining information from text contents whether they
are spoken or written.
Under-
stand
Sequential
(Seq)
Like to follow an established logic and grasp knowledge step by step,
they often focus more on details and could explain how they under-
stand it clearly.
Global (G)
Prefer to start with holistic framework of knowledge, they usually
learn material randomly without thinking about connection among
each part and get a clear understanding after absorbing enough materi-
als.
To sum up, through literature reviewing it is suggested that the learning space has a
significant influence on students’ behavior and mind, which varies because of individual
perception. As an important variable, the LS provides more definite and explicit identifi-
cation of students’ characters which should be used for exploring the effects of individual
attributes on the spatial perception more deeply. Then, from this perspective rather than
other ordinary demographic variables, specialized and well-targeted directions will be
put forward to guide the design of campus space with the aim of optimizing academic
outcome and promoting psychological health. In spite of increasing research and focus, it
is still absent from related analysis [42–44].
Therefore, our study draws on the effects of LS on the perception of five typical learn-
ing spaces in university colleges, which have been centered on frequently in previous
studies [45–49], including (1) traditional classroom (hold 100–200 students, support face-
to-face teaching and learning, characterized by rows of fixed desks, tables and chairs all
facing the instructor at one end of a rectangular room, usually used for a large and public
class); (2) multimedia classroom (hold 20–30 students, equipped with advanced electrical
facilities supporting visualization and data retrieval, like computers or projectors, which
students are free to utilize, usually for small special teaching, discussions or meetings); (3)
professional classroom (places where students can use professional instruments to con-
duct academic experiments or professional exercises, usually for students who major in
science and engineering, arts or design and be utilized by a fixed group, such as labora-
tory, painting room, and model making room, students usually have exclusive positions
there); (4) self-study room (usually existing in specialized learning buildings, like a library
and a learning center, support self-directed learning activities without teachers’ involve-
ment, such as searching for paper or electronic materials and discussion in groups); (5)
informal learning spaces (places where student self-directed learning activities happened
out of class, usually do not specifically target learning and have other functions, charac-
terized by social support, such as social hubs, internal student streets, atrium spaces, or
reimaging corridors). The examples of learning spaces are shown in Figure 1.
Traditional classroom
Multimedia classroom
Professional classroom
Self-study room
Informal learning space
Figure 1. The examples of five typical learning spaces.
Our hypotheses can be summarized in the following two statements: (1) students
with distinct learning styles have different evaluations about five typical learning spaces
Figure 1. The examples of five typical learning spaces.
Our hypotheses can be summarized in the following two statements: (1) students
with distinct learning styles have different evaluations about five typical learning spaces
when considering the suitability for learning activities; (2) some spatial qualities have more
significant effects on perception of learning spaces for different learning style owners.
The aim of the study is to identify: (1) how students characterized by different learning
styles evaluate learning spaces when taking efficient learning and preference into account;
Buildings 2021,11, 572 4 of 13
(2) which spatial characters affect the perception of learning spaces with regard to diverse
learning styles.
2. Materials and Methods
2.1. Survey of Students’ Learning Styles and Their Preference
For the first aim, an online survey was conducted to collect students’ data about
learning styles and preference for spaces. The questionnaire consists of three parts. The
first part is to obtain demographic information including gender, age, major, and the
contact information if they desire to participate in further experiment. The second part is
the Chinese version of ILS to definite participants’ learning patterns containing 44 items.
The last part is to acquire their evaluations of 5 typical types of learning spaces with regard
to their preference and spatial restorative potential, which was obtained by 2 questions,
including: (1) “I could pay attention to my task easily and there is no distraction here”. (2) “I
like here and feel comfortable and pleasure here”. Additionally, a 5-point Likert-type scale
was utilized to show answers (1 = totally disagree, 5 = totally agree). The questionnaire
was pre-tested by 10 college students to ensure its clearness and logicality.
2.2. Identifying Spatial Characteristics Affecting the Perception
Considering the lack of related studies, the method of focus group interviews (FGIs)
was selected to find out the influence factors of spatial characteristics. This method is good
at identifying meaningful factors from people’s subjective feelings and life experiences and
is suitable for the initial stage of study [
50
]. The interview focused on 2 core questions:
(1) negative
spatial characteristics causing distraction, boredom, or confusion;
(2) positive
ones encouraging mental restoration, calm thinking, or preference. Each interview con-
sisted of 2 stages: (1) participants were encouraged to write their thoughts freely and
alone to avoid similar answers caused by other interference; (2) group discussions were
performed, and participants were allowed to add new ideas to their answers. Researchers
were responsible for recording the discussion and breaking the ice in conversations.
2.3. Sampling
Electronic questionnaires were firstly distributed in the range of researchers’ social
circles by e-mail or media platform (such as Wechat or Microblog). Then, respondents were
asked to spread questionnaires in their social circles after completion which brought about a
snowball effect to expand the scope of investigation. Finally, 200 college students majoring
in 3 kinds of disciplines were recruited to accomplish the questionnaires. They came from
6 universities located in various regions of China. In total, 178 valid questionnaires were
taken into account with exclusion of obviously thoughtless answers with too short answer
time. Table 2shows the distribution of respondents’ individual features.
Table 2. The distribution of respondents’ individual features.
Individual Features Classification Numbers Proportion
Gender Male 82 46%
Female 96 54%
Grade
First year undergraduate 37 21%
Second year undergraduate 43 24%
Third year undergraduate 32 18%
Last year undergraduate 43 24%
Postgraduate students 23 13%
Major
Natural sciences 69 39%
Engineering and technology 75 42%
Arts and social sciences 34 19%
The participants who expressed intentions of further experiment were invited to FGIs
considering the uniform distribution of the gender, grade, discipline, and learning styles.
Buildings 2021,11, 572 5 of 13
Five students with distinct LSs were assigned to the same group. Each learning space
became the discussion object, respectively. Therefore, five groups were identified. For
very few responds with unusual learning styles, advanced interviews were conducted to
recognize their favorite or least favorite learning space. Their choices determined which
group they were assigned to so that more detailed descriptions would be obtained. The
time of each interview was limited between half an hour and 40 min and comfortable
meeting spaces were ensured.
2.4. Analysis
SPSS 22.0 software was used for data analysis. Firstly, the reliability of questionnaire
was checked by Cronbach’s alphas. Secondly, descriptive statistics were conducted to show
the distribution of respondents’ demographic characteristics and LS. Subsequently, for each
dimension, means and standard deviations were calculated, respectively, which provided
an initial description of students’ preferences. Thirdly the one-way ANOVA analysis was
used to identify the significant differences in preference evaluation of the same space of
different groups.
Finally, the Nvivo 11 software was used to deal with the data of FGIs. The answers
from interviews were firstly translated into English and input into the software. The
keywords related to research focus were picked up and converted into professional terms,
which formed a list of coded words. Then, words with the same meaning were deleted. At
last, the occurrence frequency of each keyword was recorded to identify its importance
and universality.
3. Results
3.1. Overall Description of Learning Styles
The Cronbach’s alphas of spatial scores and the questionnaire were 0.862 and 0.895,
respectively, which indicated a good internal reliability. Figure 2shows the total feature of
respondents’ learning styles. For the dimension of processing information, 49.4% of stu-
dents were found to have an active preference, 50.6% had a reflective preference. Regarding
perceiving information, 63% were classified as sensing and others tended to be intuitive.
Additionally, 83.1% preferred to remember visual information, while 16.9% obtained verbal
information more easily. Moreover, there were 67.4% students evaluated as sequential
and 32.6% showed global features when considering the progress of understanding in-
formation. Some LSs had significantly more owners than others, such as A-Sen-Vis-Seg
(23.5%), R-Sen-Vis-Seg (18%), A-I-Vis-Seg (9%), and R-I-Vis-Seg (6.8%). Some LSs such as
R-Sen-Ver-G (1%), R-Sen-Ver-Seg (1%), A-I-Ver-Seg(1%), A-Sen-Ver-G (1%), and R-I-Ver-Seg
(1%) belonged to very few respondents.
1
Figure 2. The percentage of responds’ preferred manners for each dimension.
Buildings 2021,11, 572 6 of 13
3.2. Perception and Preference of Learning Spaces
According to Table 3, the self-study room was rated as the most popular and restora-
tive place followed by the professional classroom, the traditional classroom, the multimedia
classroom, and the informal learning space. The results from one-way ANOVA analysis in-
dicated the significant differences between visual learners’ scores and verbal learners’ scores
of multimedia classrooms and traditional classrooms (multimedia classroom:
F = 5.980
,
p= 0.016
; traditional classroom: F = 7.583, p= 0.006). Moreover, between sequential par-
ticipants and global ones, the preference scores of self-study rooms (F = 5.876,
p= 0.017
),
informal learning spaces (F = 4.317, p= 0.041), and multimedia classrooms (F = 4.836,
p= 0.031
) all differed significantly. Specifically, verbal learners regarded traditional class-
rooms as places beneficial for focusing attention while visual learners prefer multimedia
classrooms. Global learners’ preferences for multimedia classrooms and informal learning
spaces are higher than sequential learners. However, sequential learners’ preferences for
self-study rooms are higher than global learners.
Table 3. Average scores for learning spaces by students with different learning styles.
Traditional
Classroom
Multimedia
Classroom
Professional
Classroom Self-Study Room Informal Learning
Space
Pre Res Pre Res Pre Res Pre Res Pre Res
Active (n = 88) 3.46 3.60 3.71 3.84 4.00 3.96 4.14 4.14 3.46 3.27
Reflective (n = 90) 3.56 3.63 3.57 3.40 3.84 3.76 3.96 4.04 3.42 3.20
Sensing (n = 112) 3.68 3.66 3.45 3.48 4.00 3.89 4.18 4.23 3.46 3.20
Intuitive (n = 66) 3.21 3.58 3.46 3.24 3.79 3.79 3.82 3.85 3.39 3.30
Visual (n = 148) 3.47 3.58 3.80 3.55 3.65 3.68 4.12 4.15 3.45 3.22
Verbal (n = 30) 3.67 3.87 3.33 3.33 3.80 3.73 3.67 3.80 3.40 3.33
Sequential (n = 58) 3.68 3.72 3.40 3.58 4.03 4.00 4.22 4.27 3.33 3.20
Global (n = 120) 3.14 3.45 3.52 3.67 3.69 3.55 3.69 3.72 3.76 3.31
3.3. The Influence of Spatial Characteristics on Preference and Restorative Perception
3.3.1. Group 1: The Traditional Classroom
The common requirements about positive perception are as follows (numbers indi-
cate the frequency of mention): learning atmosphere (5), positive psychological hint (4),
silence (5)
. While, the negative spatial characteristics which have the possibility to interfere
with learning and reduce the visiting desire are nervous atmosphere (5), uncomfortable
sitting (3)
, absence of space division (2), fixed seat (2), narrow personal space (3), poor air
quality (4), limited supply hubs (2), chaotic people flow (3), smell of food (1). Examples of
sentences are shown below:
A1 (male, second year undergraduate, engineering major, R-I-Vis-Seg): I feel the place
has overly serious atmosphere which brings back memories of hard lessons. It is hard for
me to decide where to sit here because chairs are not suitable for sitting for a long time and
there is no sense of being surrounded.
A2 (female, first year of master, engineering major, A-Sen-Vis-Seg): I have narrow
personal space although when it is a large room. I can’t use my laptop here because of the
limited supply hubs. Students may even argue about taking seats. But the nervous learning
atmosphere will drive me devote myself to work. So I visit here when facing urgent tests.
A3 (male, fourth year undergraduate, science major, A-I-Vis-G): There are many
students working hard here. This makes me feel stressful and motivated. And I will come
across new friends here, which is regarded as a novel experience to aspire to.
A4 (male, first year undergraduate, arts major, R-Sen-Ver-Seg): I think it is a pure
learning space without other additions and decorations. The electronic devices often
distract me so their absence is a good thing for my learning.
Buildings 2021,11, 572 7 of 13
3.3.2. Group 2: The Multimedia Classroom
The key themes related to positive experience contain visualization equipment (5),
flexible furniture (5), decoration (2), clear vision of screen (3). The distractions are includ-
ing electronic devices (4), disordered furniture (2), narrow space (2), bad ventilation (3).
Examples of sentences are shown below:
B1 (female, first year of master, engineering major, A-Sen-Vis-G): I like here because
the smaller space increases sense of security. I can see the screen clearly even when sitting
back. My works could be presented more conveniently here with the help of equipment.
B2 (male, second year undergraduate, science major, R-Sen-Ver-Seq): I seldom take it as an
ideal learning space because the laptop, projector or other advanced electrical equipment
often distract me and are unnecessary for my learning.
B3 (male, third year undergraduate, social science major, A-I-Vis-Seq): I don’t like the
space. The tables wrapped around in a circle are more suitable for extracurricular social
activities rather than formal learning activities in my opinions. And the room is so small
that I can’t take a fresh breath.
B4 (female, second year undergraduate, engineering major, A-Sen-Vis-Seq): This place
is occupied by electronic equipment and seems cold and emotionless. I don’t think I belong
to this place. I often feel tight in my chest when surrounded by computers or screens.
3.3.3. Group 3: The Professional Classroom
The positive factors are familiarity (6), access to facilities (5), bright light (3), teacher
guidance (2), practical activity (2). The distractive or boring factors are excessive communi-
cation with acquaintance (3), disorderly furnishings (4), teachers visiting (1), bad hygienic
conditions (2). Examples of sentences are shown below:
C1 (female, second year undergraduate, natural science major, R-Sen-Ver-G): I am
familiar with the environment. Moreover I can keep some personal things here and set the
desktop or chairs according to my habits or preferences. These all make me feel comfortable
and safe.
C2 (male, second year of master, medicine major, A-I-Vis-Seq): I could conduct ex-
periments to consolidate knowledge. Most of my innovative works are also done here. I
could concentrate on myself more easily because there is nothing unrelated to learning
around me.
C3 (female, third year undergraduate, engineering major, R-Sen-Vis-G): I seldom come
here to study because I often indulge in chatting with classmates and waste much time
there. Sometimes teachers will come here which makes me nervous.
C4 (male, fourth year undergraduate, engineering major, R-Sen-Vis-Seq): My profes-
sional classroom is furnished disorderly and optionally and every corner is crammed with
personal belongings, which make me feel whiny.
3.3.4. Group 4: The Self-Study Room
Participants paid more attention to these spatial features with regard to preference or
restorative experience, including: comfortable temperature (3), learning
atmosphere (4)
,
rest areas (2), silent environment (5), digital resources (5), WIFI support (3), good
facilities (6)
,
spacious (2), green plants (3), colorful chairs (2), beautiful view from window (2). Ad-
ditionally, negative factors are noise (5), peer pressure (6), low accessibility (2), worry
about having a seat (3), close interpersonal distance (2), other people’s movements (4)
when considering distraction or aversion. Some descriptions of the self-study rooms from
participants are presented below as examples:
D1 (male, second year master, engineering major, R-I-Vis-Seq): I like to study here
because it is spacious and I have a higher field of vision. I feel this place well designed and
equipped because of pot plants, orderly arranged chairs and desks, which allow me think
intently and deeply.
Buildings 2021,11, 572 8 of 13
D2 (female, third year undergraduate, natural science major, R-Sen-Vis-G): The place
brings me learning atmosphere without seriousness. Compared with familiar classmates,
there are less acquaintances around me which makes me more relaxed.
D3 (female, first year undergraduate, engineering major, R-I-Ver-Seq): There are too
much people concentrating on their studies which forms the peer pressure and makes
me feel nervous and worried. And too quiet environment makes me sleepy and agitated
especially when I am trying to remember something.
D4 (male, fourth year undergraduate, liberal art major, A-I-Ver-G): Too quiet environ-
ment makes me overcautious and I am always worried about making noise or disturbing
others. If I tend to visit there, I have to bring plenty of study materials like books or laptop.
I think it is very inconvenient.
3.3.5. Group 5: The Informal Learning Space
The positive factors reflect in relaxed atmosphere (3), free to talk (3), high
accessibility (1)
,
food support (2) and the distractive elements include flow of people (3), noise (2), pets (3),
absence of furniture (1), dim light (3), money cost (2), and children at play (2). Partial views
are below as an example:
E1 (male, second year undergraduate, engineering major, A-I-Ver-G): I prefer to learn
here because of its more relaxed atmosphere. I will not worry about disturbing others even
if I discuss with companions or recite texts in a whisper. I usually listen to light music with
headphones on, under the circumstance, the white noise around me has become helpful
for my learning.
E2 (female, second year undergraduate, liberal art major, A-I-Ver-Seq): I often visit
there to review my lessons because it is close to my dormitory and I can buy cakes, coffee
or lunch there. So I would do studies immediately after eating.
E3 (female, second year undergraduate, natural science major, R-Sen-Vis-G): I seldom
do my learning here because it contains many uncertain elements, such as noisy parties,
lovers’ meeting or the sudden appearance of cats. So I can’t engaging in learning here. and
there are not tables big enough to put my books or laptop on.
E4 (male, first year master, natural science major, R-Sen-Vis- Seq): I think there are
too many elements distracting me here, like playing children, background music, food
temptation, crowed people. Moreover the dim light makes me sleepy and the daily table is
not suitable for writing.
4. Discussion
4.1. The Whole Feature of Learning Styles
According to results, there are more active, sensing, visual, and sequential participants
in our sample, which reflects the features of Chinese campus students. It may be explained
by the education system in China and the aim of good examination scores. The knowledge
is input into students directly, which results in the weak abilities of thinking things through
alone and organizing the materials. Thus, more active learners occur, who like to discuss
with and learn from others. In addition, students usually understand knowledge by
practicing and memorizing repeatedly. Therefore, most choose to learn things step by step,
which explains the high frequency of sequential learners. Additionally, Felder and Spurlin
(2005) stated that there is a moderate correlation between the dimensions of perceive and
understand. The sequential learners organize information gradually and tend to be sensing.
This finding supports the combination of sequential and sensing. At last, more visual
learners may be due to more legibility and vividness of picture information than words,
especially for complicated knowledge in university courses. Understanding the proportion
of distinct learning styles helps to know the preference of most people, which is useful for
designing the suitable learning spaces for different groups.
Buildings 2021,11, 572 9 of 13
4.2. The Influence of Learning Styles on Perception and Preference
The present study tells us that two dimensions of LS have an influence on perception
of learning spaces (Table 4). The dimension of understanding has a relationship with
the evaluation of self-study rooms, informal learning spaces, and multimedia classrooms.
Specifically, when it comes to self-study rooms, sequential learners have given a higher
rating than global learners. This may be due to the fact that the environment supplies
particular information which they prefer and understand easily. It is generally agreed that
sequential learners usually follow a linear and successive thinking path and are guided
more easily in similar ways [
51
]. Therefore, the standard and specialized facilities or
settings, like neatly arranged tables and settled chairs, fit with their logical habitat better.
Secondly, the informal learning spaces seem more suitable for global learners. According
to Pasheler et al. (2009), global learners seldom undertake the rote learning manners so
that they have lower requirements for silence or facilities [
52
]. Moreover, the relaxed and
informal environment give them more freedom to think. Thirdly, sequential students
encode the information successively and continuously and global ones tend to synthesize
the separate parts into a whole [
52
]. Therefore, the electrical equipment in multimedia
classroom supporting clear visualization of knowledge becomes a positive factor for the
global learners.
Table 4. The relationship between dimensions of learning styles and perceptions of learning spaces.
The Dimension
of Learning
Styles
The Type of Learning Spaces
Traditional
Classroom
Multimedia
Classroom
Professional
Classroom Self-Study Room Informal Learning
Space
Processing
Verbal > Visual
Verbal < Visual / / /
Perceiving / / / / /
Remembering / / / / /
Understanding /
Sequential < Global /
Sequential > Global
Sequential < Global
Note: “
” shows the dimension has significant effects on the perception of this learning space, listed below is the comparison of preference
of distinct styles.
The dimension of processing proved to be related with participants’ perceptions
of multimedia classrooms and the traditional classroom. Verbal learners reported a
lower degree of focus in the multimedia classrooms because of too much unacceptable
graphic information [
53
]. Additionally, according to Silberman (2002), the multimedia
classroom achieves visual presentation of most learning materials to satisfy the need of
visual learners [54].
4.3. Influence Factors of Restorative Perception and Preference
Participants with distinct LS attach importance to various aspects of space. Some
spatial features are regarded as positive for one group while negative for others. In line with
previous research, some characteristics of traditional classrooms are widely recognized
as negative for learning activities, such as the poor facilities, absent support for mobile
learning, narrow personal space [
55
,
56
]. However, it is controversial if the serious learning
atmosphere and silence here are positive for learning activities or not. In our studies,
sensing learners seem to regard it as positive encouragement while intuitive learners think
it brings too much stress or displeasure. This can be explained in terms of intuitive learners’
need or preference for abstract and innovative environmental stimulation which traditional
classrooms cannot supply [
51
]. While, sensing learners focus more on perception than
intuition which will be innovated better by normative and classical environments. It further
emphasized the importance of a combination of traditional classrooms and new learning
spaces, which is consistent with Park and Choi [57].
Buildings 2021,11, 572 10 of 13
The advocates of multimedia classrooms obtained satisfaction from characteristics
including flexible furniture, visualization of learning material, and smaller spatial scales.
The dissenters regarded the electronic equipment and removable desks as distraction more
than effective tools. As mentioned earlier, the visualization of learning materials is not
beneficial for all students, especially for verbal learners, who obtain more information
from words than pictures [
38
]. Moreover, active learners have more possibilities to give
a positive evaluation because they like communicating with companions and improve
themselves by cooperating with others, which will be supported better in multimedia
classrooms [57].
The positive aspects of professional classrooms in terms of restoration and preference
are mainly focused on the familiarity with environment settings and freedom to use
facilities, which bring better control over the environment. This phenomenon has been
obviously reflected on reflective learners who like studying alone, because the small
familiar environment will offer them more personal space and feelings of safety. Moreover,
for intuitive learners, the professional classrooms are equipped with professional facilities
which meet their needs of practicing and doing experiments. Otherwise, visual learners
consider classmates, teachers, and disorderly furnishings as distractions for them. This may
be explained by their perceptive features in terms of sensibility to graphic information [
38
].
Research on self-study rooms obtain consistent results with previous studies. On
the whole, the space revealed a wide satisfaction depending on its comfortable and silent
environment, digital resources, good facilities, nice decorations, and so on. Then, more
details were presented. Reflective learners usually focus on theories in books and are in
no hurry to practice, so lots of references stored in the libraries may attract them. On the
contrary, the silent environment and standardizing system in most learning buildings will
be a kind of barrier or rigid control for active learners who remain outgoing in the process
of learning and always try to discuss with others.
In informal learning spaces, there are some distractive environmental characteristics
adding the cognitive loads such as noise, playing children. However, it seems that some
people are able to adapt to these and enjoy the benefits from this space, like delicious
food and easy visiting. It may be explained by Felder and Spurlin’s conclusions (2005)
that active learners like group discussion and verbal learners are less sensitive to graphic
information. Therefore, they could ignore the disadvantages of informal learning space.
However, it is easier for sensing learners to pay attention to the irrelevant elements, so they
suffer much interference here.
4.4. Implications for Designers, Planners, and Stakeholders
The present findings prove that the preference for learning spaces in campus and the
perception of spatial elements differ from LS, which identifies the key points of designing
or optimizing the learning spaces. Personalized spatial settings should be considered to
satisfy the needs of different groups in order to enhance their preference and visiting desire.
Meanwhile, the studies supply instructions for campus administrators to plan and allocate
learning spaces.
4.5. Limitations of the Study
The relatively small number of participants presents limitations with regards to gen-
eralizing the findings to a larger group. Additionally, the regional culture, learning en-
vironment, and majors all have effects on learning styles. Therefore, results may differ
when samples change. Some demographic characteristics may affect the perception of
the space and the assessment of individual LS, such as gender, age, major, familiarity of
environment, environmental value orientation, which will be explored in further research.
In addition, the related spatial elements could be identified preliminarily by the method
of focus group interviews. More investigations and assessment should be conducted to
explore the degree of its effect. At last, considering the inconsistence in the measurement
of LS, another evaluation method instead of Felder-Silverman learning style model may
Buildings 2021,11, 572 11 of 13
result in distinct results. One’s LS may change as he or she interacts with the environ-
ment, so the results could only reflect individual preferences in the current period of time.
As a whole, we tried to explore the effects of personality on spatial perception from the
view of LS. Although this is an alterable and debatable attribute, it can to some extent
represent the characteristics of one person within some specified period. Additionally,
the findings provided preliminary indicators describing the relationship between LS and
learning space perception, which need further studies with larger and detailed samples
and more comprehensive measurements before they could be used to guide the design.
5. Conclusions
The effects of built environment on individual behaviors have been widely concerned
in architecture design. In addition to spatial features, the demographic characteristics have
also been proved to affect the perception of learning spaces, such as gender, grade, and
major. However, unlike recreational experiences, the individual factors have more impacts
on learning activities, especially for students. For example, people could stop visiting
a park if its landscape is not beautiful. However, students still have to visit a learning
space even if they do not like it. Therefore, the ordinary demographic characteristics are
not enough to express the individual differences in the process of learning. Due to the
differences in intelligence, talents, habits, and ways of thinking, people will make distinct
responses to the learning spaces, even if they belong to the same gender or grade. Studies
on LS supply a tool to evaluate them. The learning spaces in line with students’ LSs would
motivate better task performance, more efficient learning actions, and higher desires to
visit. Therefore, the deep understanding of the relationship between LS and the perception
of learning spaces is of great importance to develop design strategies.
Our results firstly ranked the preference degree for five typical learning spaces. Then,
we compared the preference of different style owners for each learning space, respectively.
The significant differences were identified. Specifically, the preference of verbal learners and
visual learners for traditional classrooms and multimedia classrooms are distinct. The same
goes for the preference of sequential learners and global learners for multimedia classrooms,
self-study rooms, and informal learning spaces. This indicates that two dimensions of
LS have significant a influence on perception and preference for some typical learning
spaces in the university campus, including processing and understanding. At last, certain
spatial elements were discussed and their impacts on preference perception were evaluated
qualitatively. Although there was no statistical difference in the perception of learning
space among individuals with style differences in the other two dimensions, some special
spatial elements caused dissension from participants of each learning style. For example,
the serious learning atmosphere and silent sound environment in traditional classrooms
are positive for sensing learners, but negative for intuitive ones. This result puts emphasis
on detailed consideration about satisfaction of personalized needs and calls for larger
and wider samples to explore the correlativity further. Additionally, there is no such
person as a pure style in nature. The measurement result of LS just indicates the frequency
of which they behave in the specific style. Therefore, more comprehensive and deeper
studies are required to explore how students with distinct features perceive and cognize
the learning spaces.
Author Contributions:
Conceptualization, S.W.; methodology, S.W.; software, S.W.; validation, S.W.;
formal analysis, S.W.; investigation, S.W.; resources, S.W.; data curation, S.W.; writing—original draft
preparation, S.W.; writing—review and editing, S.W.; visualization, S.W.; supervision, C.H.; project
administration, S.W. and C.H.; funding acquisition, S.W. and C.H. All authors have read and agreed
to the published version of the manuscript.
Funding:
This research was funded by the Fundamental Research Funds for the Central Universities,
China grant number 2021QN1039.
Informed Consent Statement:
Informed consent was obtained from all subjects involved in
the study
.
Data Availability Statement: Data is contained within this article.
Buildings 2021,11, 572 12 of 13
Conflicts of Interest:
The authors declare no conflict of interest. The funders had no role in the design
of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or
in the decision to publish the results.
References
1.
Higuera-Trujillo, J.L.; Llinares, C.; Macagno, E. The Cognitive-Emotional Design and Study of Architectural Space: A Scoping
Review of Neuroarchitecture and Its Precursor Approaches. Sensors 2021,21, 2193. [CrossRef] [PubMed]
2.
Hu, M.; Simon, M.; Fix, S.; Vivino, A.A.; Bernat, E. Exploring a sustainable building’s impact on occupant mental health and
cognitive function in a virtual environment. Sci. Rep. 2021,11, 5644. [CrossRef]
3. Tanner, C.K. The influence of school architecture on academic achievement. J. Educ. Adm. 2000,38, 309–330. [CrossRef]
4.
Kumar, R.; O’Malley, P.M.; Johnston, L.D. Association between physical environment of secondary schools and student problem
behavior: A national study, 2000–2003. Environ. Behav. 2008,40, 455–486. [CrossRef]
5.
Kaplan, R.; Kaplan, S. The Experience of Nature: A Psychological Perspective; Cambridge University Press: New York, NY, USA,
1989; p. 90.
6.
Ulrich, R.S. Aesthetic and affective response to natural environment. In Human Behavior and Environment; Altman, I., Wohlwill,
J.F., Eds.; Plenum: New York, NY, USA, 1983; pp. 85–125.
7.
Hartig, T.; Anders, B.; Garvill, J.; Olsson, T.; Gärling, T. Environmental influences on psychological restoration. Scand. J. Psychol.
1997,37, 378–393. [CrossRef]
8.
Okogbaa, O.G.; Shell, R.L.; Filipusic, D. On the investigation of the neurophysiological correlates of knowledge worker mental
fatigue using the EEG signal. Appl. Ergon. 1994,25, 355–365. [CrossRef]
9.
Choi, H.H.; VanMerriënboer, J.J.G.; Paas, F. Effects of the physical environment on cognitive load and learning: Towards a new
model of cognitive load. Educ. Psychol. Rev. 2014,26, 225–244. [CrossRef]
10.
Kim, H.; Hong, T.; Kim, J.; Yeom, S. A psychophysiological effect of indoor thermal condition on college students’ learning
performance through EEG measurement. Build. Environ. 2020,184, 107223. [CrossRef]
11.
Liu, Q.; Zhang, Y.; Lin, Y.; You, D.; Zhang, W.; Huang, Q.; van den Bosch, C.C.K.; Lan, S. The relationship between self-rated
naturalness of university green space and students’ restoration and health. Urban For. Urban Green.
2018
,34, 259–268. [CrossRef]
12.
Yu, Y.; Wan, C.; Huebner, E.S.; Zhao, X.; Zeng, W.; Shang, L. Psychometric properties of the symptom check list 90 (SCL-90) for
Chinese undergraduate students. J. Ment. Health 2019,28, 213–219. [CrossRef]
13.
Kitzrow, M.A. The Mental Health Needs of Today’s College Students: Challenges and Recommendations. J. Stud. Aff. Res. Pract.
2009,41, 167–181. [CrossRef]
14.
Yu, J.; Jan, V.; Catherine, B. Students’ learning patterns and learning spaces in higher education: An empirical investigation in
China. High. Educ. Res. Dev. 2021,40, 868–883. [CrossRef]
15.
Strange, C.; Banning, J. Educating by Design: Creating Campus Learning Environments That Work; Jossey-Bass: Hoboken, NJ,
USA, 2001.
16.
Byers, T.; Imms, W.; Hartnell-Young, E. Making the Case for Space: The Effect of Learning Spaces on Teaching and Learning.
Curric. Teach. 2014,29, 5–19. [CrossRef]
17.
Tanner, C.K. Explaining relationships among student outcomes and the school’s physical environment. J. Adv. Acad.
2008
,19,
444–471. [CrossRef]
18.
Earthman, G.I. School Facility Conditions and Student Academic Achievement; UCLA’s Institute for Democracy, Education and Access:
Los Angeles, CA, USA, 2002; pp. 1–18.
19.
CABE. Design with DIstinction: The Value of Good Building Design in Higher Education; Commission for Architecture and the Built
Environment: London, UK, 2005; ISBN 1846330017.
20. Schneider, M. Do School Facilities Affect Academic Outcomes? National Clearinghouse for Educational Facilities: Washington, DC,
USA, 2002.
21.
Entwistle, N.; Peterson, E. Conceptions of learning and knowledge in higher education: Relationships with study behaviour and
influences of learning environments. Int. J. Educ. Res. 2004,41, 407–428. [CrossRef]
22.
Brooks, C. Space matters: The impact of formal learning environments on student learning. Br. J. Educ. Technol.
2001
,42, 719–726.
[CrossRef]
23.
Ellis, R.A.; Goodyear, P. Models of learning space: Integrating research on space, place, and learning in higher education. Rev.
Educ. 2016,4, 149–191. [CrossRef]
24.
Hipp, J.; Gulwadi, G.; Alves, S.; Sequeira, S. The Relationship between Perceived Greenness and Perceived Restorativeness of
University Campuses and Student-Reported Quality of Life. Environ. Behav. 2015,48, 1292–1308. [CrossRef]
25.
Gulwadi, G.B.; Mishchenko, E.D.; Hallowell, G.; Alves, S.; Kennedy, M. The restorative potential of a university campus: Objective
greenness and student perceptions in turkey and the united states. Landsc. Urban Plan. 2019,187, 36–46. [CrossRef]
26.
Yi, Y.K. Restorative effects of natural landscape on university students’ stress reduction and cognitive enhancement. Environ.
Behav. 2015,43, 127–137.
27.
Amicone, G.; Petruccelli, I.; de Dominicis, S.; Gherardini, A.; Costantino, V.; Perucchini, P.; Bonaiuto, M. Green Breaks: The
Restorative Effect of the School Environment’s Green Areas on Children’s Cognitive Performance. Front. Psychol.
2018
,9, 1579.
[CrossRef]
Buildings 2021,11, 572 13 of 13
28. Bell, S. Landscape. In Pattern, Perception and Process; E&FN Spon: New York, NY, USA, 1999.
29.
Strumse, E. Demographic differences in the visual preference for agrarian landscapes in Western Norway. J. Environ. Psychol.
1996,16, 17–31. [CrossRef]
30.
Yu, K. Cultural variations in landscape preference: Comparisons among Chinese sub-groups and western design experts. Landsc.
Urban Plan. 1995,32, 107–126. [CrossRef]
31.
Svobodova, K.; Sklenicka, P.; Molnarova, K.; Salek, M. Visual preferences for physical attributes of mining and post-mining
landscapes with respect to the sociodemographic characteristics of respondents. Ecol. Eng. 2012,43, 34–44. [CrossRef]
32.
Wang, R.; Zhao, J.; Meitner, M.J.; Hu, Y.; Xu, X. Characteristics of urban green spaces in relation to aesthetic preference and stress
recovery. Urban For. Urban Green. 2019,41, 6–13. [CrossRef]
33.
Donggun, A.; Martha, C. Learning styles theory fails to explain learning and achievement: Recommendations for alternative
approaches. Personal. Individ. Differ. 2017,116, 410–416.
34.
Hall, E.; Moseley, D. Is there a role for learning styles in personalized education and training? Int. J. Lifelong Educ.
2005
,24,
243–255. [CrossRef]
35.
Park, C.C. Learning Style Preferences of Armenian, African, Hispanic, Hmong, Korean, Mexican, and Anglo Students in American
Secondary Schools. Learn. Environ. Res. 2001,4, 175. [CrossRef]
36. Felder, R.M.; Silverman, L.K. Learning and Teaching Styles in Engineering Education. Eng. Educ. 1988,78, 674–681.
37.
Felder, R.M.; Soloman, B.A. Index of Learning Styles Questionnaire. Available online: http://www.engr.ncsu.edu/learningstyles/
ilsweb.html (accessed on 6 February 2006).
38.
Felder, R.M.; Spurlin, J.E. Applications, reliability and validity of the index of learning styles. Int. J. Contin. Eng. Educ. Life-Long
Learn. 2005,21, 103–112.
39.
Zywno, M.S.; Waalen, J.K. The effect of hypermedia instruction on achievement and attitudes of students with different learning
styles. In Proceedings of the 2001 Annual ASEE Conference, ASEE, Albuquerque, NM, USA, 24–27 June 2001.
40. Buxeda, R.; Moore, D.A. Using learning styles data to design a microbiology course. J. Coll. Sci. Teach. 1999,29, 159–164.
41.
De Vita, G. Learning styles, culture and inclusive instruction in the multicultural classroom: A business and management
perspective. Innov. Educ. Teach. Int. 2001,38, 165–174. [CrossRef]
42.
Cleveland, B.; Fisher, K. The evaluation of physical learning environments: A critical review of the literature. Learn. Environ. Res.
2014,17, 1–28. [CrossRef]
43. Edwards, B. University Architecture; Spon Press: London, UK, 2000.
44. Tempe, P. Learning Spaces for the 21st Century: A Review of the Literature; Higher Education Academy: York, UK, 2007.
45. Temple, P. Learning spaces in higher education: An under-researched topic. Lond. Rev. Educ. 2008,6, 229–241. [CrossRef]
46.
Jamieson, P. Reimagining Space for Learning in the University Library; Matthews, G., Walton, G., Eds.; University Libraries and Space
in the Digital World, Ashgate: Farnham, UK, 2013; pp. 142–154.
47. Brown, M.B.; Lippincott, J.K. Learning spaces: More than meets the eye. Educ. Q. 2003,26, 14–16.
48.
Matthews, K.E.; Andrews, V.; Adams, P. Social learning spaces and student engagement. High. Educ. Res. Dev.
2011
,30, 105–120.
[CrossRef]
49.
Huang, R.; Spector, J.; Yang, J. Learning Space Design: A Primer for the 21st Century; Springer: Berlin/Heidelberg, Germany, 2019.
[CrossRef]
50.
Kitzinger, J. The methodology of focus groups: The importance of interaction between research participants. Sociol. Health Illn.
1994,16, 103–121. [CrossRef]
51.
Das, J.P. Simultaneous-successive processing and planning, Ch. 5. In Learning Strategies and Learning Styles; Schmeck, R.R., Ed.;
Plenum Press: New York, NY, USA, 1988.
52.
Pashler, H.; Aniel, M.M.; Rohrer, D.; Bjork, R. Learning Styles: Concepts and Evidence. Learn. Styles
2009
,9, 105–119. [CrossRef]
[PubMed]
53.
Aljojo, N. In-Depth Analysis of the Arabic Version of the Felder-Silverman Index of Learning Styles. Am. J. Inf. Syst.
2015
,3,
22–30. [CrossRef]
54. Silverman, B.K. Upside-down brilliance: The visual spatial learner. Adults 2002,34, 15–20. [CrossRef]
55.
Harrison, A.; Hutton, L. Design for the Changing Educational Landscape: Space, Place and the Future of Learning; Routledge: London,
UK, 2013; ISBN 9780203762653.
56.
Beckers, R.; van der Voordt, T.; Dewulf, G. Why do they study there? Diary research into students’ learning space choices in
higher education. High. Educ. Res. Dev. 2016,35, 142–157. [CrossRef]
57.
Park, E.L.; Choi, B.K. Transformation of classroom spaces: Traditional versus active learning classroom in colleges. High. Educ.
2014,68, 749–771. [CrossRef]
