sustainability

Article
Reduction of Academic Burnout in Preservice Teachers:
PLS-SEM Approach
Le Qin 1,2,† , Jie Lu 1,† , Ying Zhou 3, *, Tommy Tanu Wijaya 4 , Yongxing Huang 5, * and Mohammad Fauziddin 6

1 School of Life Sciences, Guangxi Normal University, Guilin 541004, China

2 Ideological and Political Work Research Center, Guangxi Normal University, Guilin 541004, China
3 School of Mathematics and Statistics, Guangxi Normal University, Guilin 541004, China
4 School of Mathematical Sciences, Beijing Normal University, Beijing 100875, China
5 School of Science, Beibu Gulf University, Qinzhou 535011, China
6 Pendidikan Guru Pendidikan Anak Usia Dini, Universitas Pahlawan Tuanku Tambusai,
Kampar 28412, Indonesia
* Correspondence: zhouying66@mailbox.gxnu.edu.cn (Y.Z.); huangyongxing@bbgu.edu.cn (Y.H.)
† These authors contributed equally to this work.

Abstract: Academic stress and burnout are the predominant factors that can negatively affect student
performance and sustainable learning. Therefore, it is important to analyze the factors related to
student academic burnout in preservice teachers in western China. 212 respondents from public
universities in Guangxi Province participated, and the data were analyzed using partial least-squares
structural equation modeling (PLS-SEM) to check reliability, validity, and initial hypothesis testing.
The results show that perfectionism, excessive self-efficacy, and workload are the main factors causing
academic stress and burnout in preservice teachers. These problems can be reduced by increasing
self-efficacy and coping strategies of preservice teachers. In addition, this study provides important
knowledge to universities based on factors related to preservice teachers’ academic stress and burnout,
as well as strategies and solutions to reduce these problems in students.
Citation: Qin, L.; Lu, J.; Zhou, Y.;
Wijaya, T.T.; Huang, Y.; Fauziddin, M.
Keywords: academic stress; academic burnout; coping strategies; workload; self-efficacy
Reduction of Academic Burnout in
Preservice Teachers: PLS-SEM
Approach. Sustainability 2022, 14,
13416. https://doi.org/10.3390/ 1. Introduction
su142013416 Symptoms of stress and depression should be avoided because of their direct nega-
Academic Editor: Guy Hochman
tive effect on student outcomes and sustainable well-being [1,2]. This study proves that
academic burnout can cause a decrease in student learning outcomes and thinking pro-
Received: 8 September 2022 cesses [3,4]. Academic burnout is also predicted to have a positive relationship with other
Accepted: 13 October 2022 symptoms such as depression, anxiety, and stress [4,5]. Meanwhile, high depressive symp-
Published: 18 October 2022
toms were ultimately associated with suicidal intentions [6]. Due to intense competition
Publisher’s Note: MDPI stays neutral in the academic field and the world of work, young people experience stress such as
with regard to jurisdictional claims in symptoms of anxiety [7], depression [8], and panic, affecting academic outcomes in the
published maps and institutional affil- 21st century, where changes are fast and competitive. Recently, the suicides of Chinese
iations. graduate students have become a social discussion [9]. However, graduate students should
have a high level of knowledge and good psychological quality, and their intention to
commit suicide prevents others from comprehending the real issue. A study involving
21,702 graduate students in 2007 indicated that 6.8% experienced academic stress, and
Copyright: © 2022 by the authors.
1.78 had ideas for suicide [9].
Licensee MDPI, Basel, Switzerland.
The study by Furr et al. [10] showed that 53% of university students had experiences
This article is an open access article
with academic burnout such as stress and depression due to unsatisfactory learning out-
distributed under the terms and
comes, finances, interpersonal relationships, and loneliness. The National Health and
conditions of the Creative Commons
Morbidity Survey 2017 [11] reported that out of 284,516 respondents, 50% of students
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
at the university level had experienced psychological stress related to exams, problems
4.0/).
with supervisors or teachers, as well as problems with family and friends. Similarly, the

Sustainability 2022, 14, 13416. https://doi.org/10.3390/su142013416 https://www.mdpi.com/journal/sustainability

Sustainability 2022, 14, 13416 2 of 24

study in China demonstrated that academic stress scores are significantly higher at the
university level. When the expectations are higher and there are no resources or a capacity
to handle stress, university students may develop academic burnout. Lack of awareness of
coping mechanisms and academic burnout have a negative impact on one’s mental and
psychological health [5].
There are many potential solutions and strategies for dealing with academic stress
and burnout in university. However, studies on strategies and countermeasures for aca-
demic burnout do not exist or may be few. The previous study has discussed mental
health problems such as anxiety, stress, and depression [6]. Cheng et al. [9] explained
that educational pressure is one of the major problems, and is the main factor causing
severe stress to students. In China, the pressure on education continues to increase every
year [3,12]. The Chinese government continues to analyze the factors that cause student
stress and depression.
In an era of rapid change and intense competition, students are under intense pres-
sure to achieve academically, which results in them staying up late every night to review
many courses [13]. Marissa Salanova [4] said that the difference in university students’
self-efficacy and interpretation of stress levels would cause differences in academic burnout.
In addition, graduate students who easily adapt to the environment but have poor cop-
ing strategies are negatively affected by academic burnout [14,15]. Therefore, this study
investigates the relationship between workload factors, academic stress, self-efficacy, per-
fectionism, and coping strategies.
According to the 2018 PISA study, China is ranked 1st in the world for PISA scores [16].
In addition, the world mathematics Olympiad was won by students from China [17,18].
With this background, the country may try to maintain existing achievements. Preservice
teachers, also known as teacher candidates, is the term used to describe student teachers
who are enrolled in a teacher education program and are working toward teacher certi-
fication. This causes high pressure for mathematics and preservice teachers, leading to
academic burnout and stress. They should have high knowledge and abilities to improve
mathematical literacy skills, high-order thinking skills and core competencies. There-
fore, there is a need to study factors related to preservice mathematics teachers’ academic
burnout and strategies to overcome the problem.
Prior empirical investigations looked at the correlation between coping mechanisms,
perfectionism, and student burnout among major medical undergraduates in Malaysia [5,19]
and high school students [20]. Research on the context of preservice mathematics teachers
is still very limited to the best of our knowledge, and findings on the relationship between
coping strategies and academic burnout are still inconsistent. Therefore, this study aims to
analyze the factors affecting academic burnout among preservice mathematics teachers in
West China. It provides important information for lecturers, leaders, and related authorities
to understand the potential factors causing academic burnout from the Chinese perspective,
offer solutions, and improve preservice teacher well-being.
To achieve the goal, this study uses sources in the literature review related to academic
burnout and stress. Furthermore, it determines predictors and uses questionnaires to collect
data. Structural equation models are used to test initial hypotheses.
This study is structured as follows: Section 2 describes the literature review and
initial hypotheses; Section 3 presents how to collect data, instruments and methods of data
processing; in Section 4, the validity and reliability of the questionnaire are tested, followed
by hypothesis testing; Section 5 contains the discussion about preservice mathematics
teacher academic burnout in detail; Section 6 is a description of the theoretical and practical
implications; and the last section outlines the conclusions and limitations.

2. Literature Review
Lazarus and Folkman [21,22] put forward the earliest theory of psychological stress
(1984), which is a two-way process of stressors originating from the environment and
individual attitudes. Typically, someone will interpret the stress stimuli concerning the
Sustainability 2022, 14, 13416 3 of 24

surroundings through cognitive evaluation. Lazarus and Folkman [21] explained that
cognitive appraisals strongly affect a person’s stress level. There are primary and secondary
types of cognitive appraisals. Primary appraisal evaluates and recognizes a person’s
stress condition and its relationship with sustainable well-being [5]. Meanwhile, the
cognitive appraisal is defined as a person’s ability to think about how to cope with a
stressful situation [23]. A secondary evaluation is activated when a person perceives the
surrounding environment as threatening or unsettling. It will stimulate cognitive processes
in which the individual will seek coping resources to solve the challenge. Coping strategies
are experiences or knowledge that someone has based on their past experiences [24,25].
For example, a lecturer announced that 10% of the students would fail and should retake
the course next year. The students will start to think and calculate the possibilities of
being included. Based on this condition, the secondary appraisal will be active in the
next step. Students will start thinking about coping resources, as well as their experience
and knowledge to overcome this problem [5]. Therefore, coping with stressful situations
is highly dependent on their self-efficacy on a subject [13,26], which is the experience in
solving similar problems. Based on the theory and initial concepts of academic primary and
secondary cognitive appraisal, this study investigates the factors of preservice mathematics
teachers’ secondary appraisal of their psychological well-being.

2.1. Relationship between Decreased Academic Stress, Academic Burnout, and Sustainability
Although studies have been conducted for more than 30 years, avoiding academic
burnout and attaining sustainable education are goals rarely accomplished. Further study
is needed on the factors that affect stress and burnout in preservice teachers to support
sustainable learning. Based on Abdullah [27], these two variables hinder the learning
sustainable process. Therefore, strategies are needed to reduce stress, especially at the
university level. Fuente [28] suggested a further analysis of coping strategies and self-
efficacy in the education process, where these variables are related to student academic
stress and the sustainability of teaching and learning. Based on this background, the two
objectives are proposed; first, what factors make preservice teacher students experience
academic stress and burnout to interfere with sustainable learning? Second, what factors
can be improved to reduce academic stress and burnout experienced by preservice teachers?

2.2. Definition of Stress

People who experience stress show physiological symptoms such as headaches, high
blood pressure, heart disease, anxiety, and depression, as well as decreased learning
satisfaction and interest in learning [4,29]. Furthermore, such people have behavioral
attitudes such as being easy to refuse, and not attending class. Models in previous studies
describe contextual factors such as environment, workload, organizational and factors
related to individuals potentially affecting a person’s stress level [30,31]. It should be noted
that the stress model has often been used as one of the powerful basic frameworks related
to a person’s psychological well-being in the workplace. However, based on empirical
evidence on stress models and academic burnout [32–34], workload, academic stress,
self-efficacy, perfectionism, and coping strategies should be considered. This study was
developed from the model of stress theory by adding two new predictors, workload [35]
and academic stress [36], which are considered to directly affect preservice mathematics
teachers’ academic burnout. University students experienced high levels of stress and
burnout tend to have symptoms such as high blood pressure, insomnia, fatigue, lack of
self-confidence, being less productive and dropping out of university [37,38]. Therefore, by
using the transactional theory of stress and coping [21] and the model of stress [39], this
study analyzes the effects of workload, academic stress, self-efficacy, perfectionism, and
coping strategies on preservice mathematics teachers’ burnout (Figure 1).
Sustainability 2022, 14, x FOR PEER REVIEW 4 of 25

Sustainability 2022, 14, 13416 4 of 24

analyzes the effects of workload, academic stress, self-efficacy, perfectionism, and coping
strategies on preservice mathematics teachers’ burnout (Figure 1).

StudyFramework.
Figure1.1.Study
Figure Framework.

2.3. Academic Burnout

2.3. Academic Burnout
Burnout can be interpreted as a feeling of losing original purpose and not meeting the
Burnout
demands of the canwork
be interpreted
[40]. It canasbeacharacterized
feeling of losing in the original
context purpose and not
of education as meeting
students
the demands
losing interest ofinthe work [40].
studying andItbeing
can be characterized
unable to fulfill in theresponsibilities
their context of education [26]. Thisas stu-
is a
dents losing interest in studying and being unable to fulfill their
special form of stress in which a person feels mentally and physically tired [41]. Academic responsibilities [26]. This
isburnout
a special canform of stress in which
be interpreted as chronic a person
stress.feels mentally
Students feel and physically
continuous tired frustration
fatigue, [41]. Aca-
demic burnout can be interpreted as chronic stress. Students
and tiredness from the high academic demands. This results in a low attitude and feel continuous fatigue, frus-
not
tration and tiredness from the high academic
wanting to learn and relate to school assignments [4]. demands. This results in a low attitude and
not wanting
Severalto learn and
studies haverelate to school assignments
demonstrated that academic [4].
burnout causes students’ inability
to adjust to school, low academic performance, and inability tocauses
Several studies have demonstrated that academic burnout deal with students’
campus inability
expec-
totations [42,43]. Students always feel that academic achievement is the main goal,expec-
adjust to school, low academic performance, and inability to deal with campus with a
tations [42,43]. Students
high demand, and thereforealways feel thatwith
interferes academic
physical achievement
and mental is readiness,
the main goal, with a
and further-
high demand, and therefore interferes with physical and
more that participation leads to academic burnout. However, other results were found mental readiness, and further-
more that participation
that married leads tohad
medical students academic
a lowerburnout.
academicHowever,burnout [9,44].other Theyresults were
have found
clear and
that married
strong goalsmedical studentsthem
that encourage had amentally
lower academic
to face the burnout
workload [9,44].and They have clear
pressure fromand the
strong
world goals that encourage
of education. Studentsthem at the mentally
tertiary to levelface
withtheinterest
workload and pressure
in their fields have from the
a lower
world
academicof education.
burnout than Students
thoseat the low
with tertiary level[4,45].
interest with interest
However, in the
their fields have
evidence is not a lower
strong
academic burnout than those with low interest [4,45]. However,
enough to prove that interest in the subject or program is a significant predictor affecting the evidence is not strong
enough
academic to prove
burnout. that interest in the subject or program is a significant predictor affecting
academic burnout.
Previous studies have demonstrated that academic burnout is associated with heart dis-
ease,Previous
high blood studies haveand
pressure, demonstrated
various other that academic
diseases burnout
[46,47]. is associated
It is also related to with heart
depression,
disease,
decreased high blood pressure,
academic outcomes,and various
absence fromother
classdiseases
and school [46,47].
dropout It is[5,14,33].
also related to de-
In addition,
a study showed
pression, decreased thatacademic
victims of this condition
outcomes, absence could
from beclass
cynicalandand pessimistic,
school dropoutwhich[5,14,33].can
Intransmit
addition, and affect showed
a study their anxiety and stress
that victims to friends.
of this condition Students
could be with academic
cynical burnout are
and pessimistic,
alwayscan
which physically
transmitand andpsychologically
affect their anxiety weak and and cannot
stress face their
to friends. problems
Students with [4,48].
academicSome
try to hide
burnout aretheir
always problems
physicallyfromand others and show drastic
psychologically weakchangesand cannot in attitudes
face theirinproblems
everyday
life, such
[4,48]. Some as try
cheating,
to hidenot going
their to class,
problems fromandothers
lookingandfor showoutlets for playing
drastic changesgames exces-
in attitudes
insively. Moreover,
everyday students’
life, such attitudes
as cheating, will
not be more
going cynical,
to class, anduncomfortable,
looking for outlets arrogant, moody,
for playing
and even
games paranoidMoreover,
excessively. [49]. Preservice
students’ mathematics
attitudes will teachers
be more arecynical,
prospective professionals
uncomfortable, ar-
who, after graduation, will teach at the K-12 level [50].
rogant, moody, and even paranoid [49]. Preservice mathematics teachers are prospectiveTheir attitude and mentality will
affect the methods and effectiveness of teaching [51,52]. Therefore, examining the factors
affecting the academic burnout of preservice mathematics teachers in China is important.
Sustainability 2022, 14, 13416 5 of 24

2.4. Coping Strategies

Coping strategies are defined as constant changes in attitudes and cognition to over-
come problems and manage internal and external stress that may burden a person and
cause labor effects on individual sustainable well-being [13,53]. Coping is actually a con-
stant cognitive procedure to handle one’s mental as well as psychological wellness [54,55].
Problem solving, as well as psychological techniques, are actually both kinds of these
modifications. The very initial technique handles the resource of tension straight, as well as
focusing on methods to refix issues.
On the other hand, psychological techniques concentrate on feelings, including ef-
ficient approaches like looking for sustenance coming from individuals, soothing down,
ducting, and participating in video games excessively, as well as fleeing to alleviate tension
directly [56,57]. A previous study revealed that waiting on college trainees along with
coping techniques will certainly proactively manage student tension together with issues
as chances for self-development as well as self-growing [58,59]. Another study revealed
that these, along with emotion-focused coping techniques, were actually discovered to
have led to extreme stress and anxiousness as well as scholastic exhaustion [60].
Furthermore, coping can be divided into active coping and disengagement [61]. Active
coping is often associated with problem-focused strategies [62,63]. People with this type of
coping tend to be aware of the stressor and will try to cite negative outcomes. People who
adopt disengagement strategies usually resist and avoid problems. They often engage in
activities to help deny problems such as drinking alcohol, sleeping or self-isolating. Some
university students stay away when their problems are beyond their capabilities and tend
to be resigned and oblivious to their poor academic grades. In addition, they do not spend
much time studying and trying to improve their academic values, resulting in helplessness
and burnout.
University students that embrace energetic coping techniques are more inspired to
take a direct method and handle tension [57]. They will have reduced scholastic exhaustion
experiences while sitting exams [64]. Furthermore, energetic coping suggests a favorable
reinterpretation of difficult occasions, an essential ability required in youths.
There are still inconsistent findings on the effects of coping strategies and academic
burnout [5], and the relationship is largely unexplored but important. Therefore, this study
considers coping strategies as one of the important independent variables in analyzing
preservice mathematics teachers’ academic burnout.

Hypothesis 1. Coping strategies have a significant relationship with academic burnout.

Hypothesis 2. Coping strategies have a significant relationship with academic stress.

2.5. Perfectionism
A perfectionist is a person who always strives for high standards and perfect results,
and perfectionism is often coupled with a tendency to be very critical of the behavior of
oneself or others [65]. It can be categorized into three dimensions: adaptive, maladaptive,
and socially prescribed perfectionism [66,67]. Adaptive perfectionism is a person’s high
individual requirements and confidence in lower production errors [68]. Maladaptive
perfectionism is a person’s extreme attention to errors and questions regarding the activities
of others [69]. On the other hand, socially prescribed perfectionism is referred to as the
stress of being ideal and a sensation of harshness in between assumptions and truth, which
triggers unfavorable reflections on flaws [70,71].
Previous studies stated that perfectionism has three dimensions of self-oriented, so-
cially oriented and other-oriented perfectionism [71,72]. First, self-oriented perfectionism
is more about adhering to one’s strict standards while maintaining a strong intrinsic mo-
tivation to achieve perfection and avoid failure. Second, socially oriented perfectionism
believes others may judge individual behavior with unrealistically high expectations [71,73].
The conceptualization is almost identical to Frost et al.’s [74] definition. An individual with
Sustainability 2022, 14, 13416 6 of 24

high socially driven perfectionism will constantly strongly experience outside stress to
be ideal and think they are assessed by others seriously. Other-oriented perfectionism is
translated as establishing impractical requirements for people and assessing their efficiency
routinely [75].
A significant positive effect has been proven between perfectionism and academic
burnout [5,31,70]. In particular, perfectionism is the main factor in academic burnout
compared to other determinants [76]. University students with adaptive perfectionism tend
to have good academic performance compared to those with maladaptive perfectionism,
who tend to experience academic burnout [77,78]. Furthermore, those with adaptive
perfectionism believe they will succeed and achieve the best academic outcomes, and
overcome existing problems and challenges [68]. Maladaptive perfectionists frequently
seek to prevent failure rather than looking for techniques to conquer problems [79,80].
Likewise, a previous study has revealed that people with high self-oriented perfectionism
have the tendency to accomplish high-performance achievements due to their intrinsic
inspiration [81]. Nevertheless, trainees with this kind of perfectionism have the tendency to
experience scholastic exhaustion since they might establish impractical and unmanageable
objectives [5,45].

Hypothesis 3. Perfectionism negatively affects preservice mathematics teachers’ academic burnout.

2.6. Self-Efficacy
Self-efficacy is an individual’s assessment of their ability to organize and conduct the
actions needed to achieve the specified type of performance [82]. This is a belief which can
overcome the demands of stress and challenges in the social learning theory [12]. Bandura
emphasized that self-efficacy strongly affects individual choices of rules and activities, abil-
ities, efforts made, and persistence in coping when facing problems or challenges [19,83].
People with high self-efficacy tend to survive when going through difficult times related
to tasks [84]. This can simultaneously increase experience and self-efficacy [85]. More-
over, feelings of competition can lead to some stability in reactions to stressful situations,
increasing individuals’ confidence in overcoming and getting through difficult times [25].
Based on previous studies, self-efficacy is an important factor related to academic
burnout [20,86,87]. Students with high self-efficacy tend to select challenging tasks. They
are more persistent and do not despair in completing the given task during many chal-
lenges [88]. In addition, the higher the self-efficacy, the lower the anxiety level [25,89]. It is
assumed that self-efficacy is an important predictor of academic stress and burnout.
According to social cognitive theory (SCT) [90], self-efficacy strongly correlates with
academic burnout [34,46]. In particular, it affects achieving one’s goals (Luszczynska et al.,
2005). It is an emotional regulation mechanism for individuals who experience high stress
and anxiety when doing difficult work. The high level is inversely proportional to one’s
academic burnout [12,89]. Individuals with high levels will be more likely to persevere
in times of adversity or failure since every failure opens new opportunities in the future.
Based on this literature review, this study proposes preliminary hypotheses that:

Hypothesis 4. Self-efficacy has a significant negative effect on preservice mathematics teachers’

academic burnout.

Hypothesis 5. Self-efficacy negatively affects preservice mathematics teachers’ academic stress.

2.7. Workload
The preservice teacher is a job that should combine technological and pedagogical
knowledge [91,92]. These teachers are required to have high creativity when teaching,
with good mathematical knowledge [93]. Pala [30] showed that academic burnout at the
university level increases when students feel a workload with lots of material to review,
assignments and other non-academic activities that take time and energy. Additionally,
Sustainability 2022, 14, 13416 7 of 24

the workload can lead to learning outcomes as a major educational goal [20]. Several
studies showed that it strongly affects burnout compared to other factors. Jensen [94]
stated that students’ many assignments and activities reduce their interest in learning and
motivation. Besides, the style of the lecturer who teaches in a monotonous style makes
it difficult to catch the material in class [95]. Even though students experience economic
problems and physical conditions, the workload can still be low and within acceptable
limits to a certain extent. They can concentrate more on academic performance without
participating in numerous extracurricular activities and organizations. Academic burnout
is caused by workload, which can be translate to a student having a busy schedule and
assignments that should be completed simultaneously [30,96]. In contrast, students do
not have time to pamper themselves and get enough rest [97]. The teaching profession is
closely related to the high workload, and this is because the teachers need much time to
prepare teaching materials, assignments, methods, experiments and games. After class,
they still have to evaluate the teaching and check the student’s homework and assignments.
This preparation often starts with the preservice teachers, which causes many to experience
academic burnout and lower well-being which can interfere with learning sustainability.
Furthermore, Chen [26]’s study showed that students experience burnout when many
courses are taken beyond their physical abilities. Therefore, the initial hypothesis is:

Hypothesis 6. Workload has a significant positive relationship with academic stress.

Hypothesis 7. Workload has a significant positive relationship with academic burnout.

2.8. Academic Stress

Academic stress is more experienced at the university, which causes more burnout
compared to other education levels [98,99]. University students face high pressures associ-
ated with academic success, which ultimately determines their careers and opportunities
after graduation [54]. Mathematics teacher graduates in China are increasing in numbers
yearly, unlike the number of schools. They compete to teach in the best schools with high
salaries, creating excessive pressure. Burnout and stress differ due to the prolonged dura-
tion of stress. At the university level, stress caused by excessive classes, exam difficulties
and the number of exams, part-time jobs, workloads, and participation in many campus
activities is a crucial determinants of burnout [29,100].
Academic grades are also affected by cumulative stress and lead to burnout, a syn-
drome with worrying consequences. Few studies have shown the negative effect on
university-level students, making further studies important to understand this situa-
tion [27,101,102]. The life quality of preservice mathematics teachers is highly dependent
on the ability to handle demands related to study. Academic stress and lack of mental
resilience as preservice mathematics teachers will result in burnout [31,100]. This is an in-
ability to accept education’s burden and learning’s tiredness-inducing qualities. Therefore,
only tough people can control all the knowledge and resources to deal with the burden
of education healthily. This study identifies academic stress, which is divided into three
sub-constructs, namely physical (SF), psychosocial (SPK), and psychological stress (SPS).
The Academic Stress Scale (ASS), developed by James Kohn and Gregory Frazer [103] in
1986, is used to collect data. This study has a preliminary hypothesis:

Hypothesis 8. Academic stress has a significant positive relationship with burnout.

3. Methodology
3.1. Population and Sample
This study aims to determine the factors associated with academic burnout in preser-
vice mathematics teachers at public universities in Guangxi, China. A purposive sampling
method is used where only Chinese preservice teachers can participate. The snowball
sampling method was utilized to divide the questionnaire among the respondent’s acquain-
Sustainability 2022, 14, 13416 8 of 24

tances [31]. Furthermore, the criteria included preservice mathematics teachers pursuing
full-time education at state universities in China. Based on Green’s rule of thumb [5],
the sample size should use the formula N > 50 + 8 m for predictor testing, where N and
M represent the number of participants and independent variables. This study has four
independent variables: workload, self-efficacy, perfectionism, and coping strategies. Since
the original version was adapted from existing results and in English, the questionnaire
in this study was modified and adapted according to the context. The detail is presented
in Appendix A, provided in English and Chinese versions. Therefore, the sample size
is recommended to be greater than 90 participants. According to the principles of the
structural equation model, the recommended number of respondents for a lower error
probability is larger than 200, and R2 can exceed 50%. The respondents are 212, and they
met the sample size criteria with sufficient power to test the initial hypothesis.
This study uses an online questionnaire for data collection purposes. Online ques-
tionnaires are considered safer because they are filled by respondents anonymously [104].
This guarantees that respondents only voluntarily fill out this questionnaire. In addition,
it supports a larger pool of respondents, such as preservice mathematics teachers from
different campuses in Guangxi. The WJX application is an online questionnaire app that is
well known and often used for data collection. Initially, this study stated the purpose and
guaranteed that the data was confidential and only used for research. Informed consent
was obtained from all respondents by oral agreement. The data collected included 212
subjects, consisting of 73 (34.43%) males and 139 (65.56%) females (Table 1). Furthermore,
18 respondents are first-year, 40 respondents are second-year, 53 respondents are third-year,
and 101 respondents are fourth-year students.

Table 1. Demographic respondents.

Item Type Frequency Percentage

gender male 73 34.43%
female 139 65.56%
Level education first-year 18 8.49
second-year 40 18.86
third-year 53 25
fourth-year 101 47.64
Organization experience Never 9 4.25
1 time 30 14.15
2 times 74 34.90
More than 3 times 99 46.70
Have a leisure time never 61 28.77
Rare 117 55.18
Often 34 16.03

3.2. Instrumentation
The questionnaire was adapted and combined from several previous articles to main-
tain high reliability and validity. It uses a 5-point Likert scale from 1 (strongly agree)
to 5 (strongly disagree). Additionally, it is divided into two sections of demographic in-
struments, and a predictor questionnaire which is thought to have a relationship with
preservice mathematics teachers’ academic burnout.

3.3. Data Analysis

Partial least-squares (PLS-SEM) is a traditional SEM-processing method for when the
existing data does not match the assumptions, and is often used to explore the relationship
Sustainability 2022, 14, 13416 9 of 24

between dependent and independent latent variables to find new theories or models [105].
The advantage of PLS-SEM is that it can be used in various conditions without referring
to the sample size and normality of the data; therefore, it can conclude initial hypotheses
in studies with small samples. This technique has also been often used in education
assessment and psychology. It uses smart PLS software for data analysis and the PLS-
SEM technique to examine the validity of the proposed hypothetical model on the factors
that affect academic burnout in preservice mathematics teachers in China. According to
Hair [106], there are two stages, these being the assessment measurement and the structural
assessment model. The assessment measurement model focuses on the loading factor,
composite reliability, Cronbach alpha and AVE value to determine the model’s reliability
and validity. Furthermore, HTMT and Fornell–Larcker [107] measurements were used to
analyze internal consistency. In the structural assessment model, the amount of R2 and
F2 are explained in full before the end of the hypothesis testing by investigating the path
coefficients, t values, and significance.
The structural model in PLS-SEM hypothesis testing with the PLS technique is es-
timated by looking at the path coefficient, t statistic, standard error, and the amount of
R2, which can explain the strength and direction of the relationship. Meanwhile, the t
statistic and standard error are used to analyze the magnitude of the effect [106]. The
value of R2 indicates the amount of variance explained. The variances linked with the
dependent variables determined the suggested model’s explanatory power. This study
uses the 5000 bootstrap resampling technique to produce t statistics, significance, and
standard errors.

4. Results
The result section is divided into descriptive statistics, checking the normality of the
data, analysis of the measurement model, and structural model analysis accompanied by
hypothesis testing.

4.1. Descriptive Statistics

The study starts by checking the normality of the data on the distribution of per
scale indicators using smart PLS software. The descriptive statistics in Table 2 are general
overview data of respondents. There are 22 items from a total of 6 constructs. From the
current mean value, the average respondents answered in 2.5 to 3.5. Normality test data
can be measured by determining the value of skewness and kurtosis, which should be in
the range of −1 to +1 [108]. Therefore, all data items are normally distributed, and the
study can proceed to the measurement model analysis stage.

4.2. Measurement Model Check

Convergent Validity
SPSS 27 and Smart PLS 3.2 are used to analyze and assess the quality of the measure-
ment model. Meanwhile, confirmatory factor analysis (CFA) was adopted to check the
convergent and discriminant validity [109]. The internal reliability of the measurement
model can be analyzed by looking at the Cronbach alpha and composite reliability (CR)
values. Hair [105] stated that internal consistency could be met when the Cronbach alpha
coefficient is more than 0.7. Table 3 shows that the CR value exceeds 0.7, where the highest
and lowest are 0.908 (AS2) and 0.745 (SE1), respectively. Therefore, it can be concluded
that all constructs are above the threshold values. Convergent validity is evaluated by
looking at the AVE value, which is considered to meet the criteria when it is more than
0.5. From Table 3, the AVE value for all constructs is more than 0.5; therefore, all items
reflect the construction. To strengthen the assessment of the construct reliability using PLS,
Rho coefficients are considered. Rho can be interpreted as Cronbach’s alpha to analyze
internal reliability. The rho_A value should also exceed 0.7 to be accepted and continue the
study [110]. Table 3 shows that the Rho coefficient is in the range of 0.782 to 0.872, and the
reliability is quite satisfactory.
Sustainability 2022, 14, 13416 10 of 24

Table 2. Descriptive statistics questionnaire.

Standard Excess
ITEMS Mean Median Min Max Skewness
Deviation Kurtosis
Coping strategies CS1 2.151 2.000 1.000 5.000 0.810 0.906 0.895
CS2 2.226 2.000 1.000 5.000 0.950 0.532 0.864
CS3 2.226 2.000 1.000 5.000 1.012 0.145 0.770
CS4 2.344 2.000 1.000 5.000 1.032 −0.210 0.670
perfectionism P1 3.519 4.000 1.000 5.000 1.062 −0.268 −0.633
P2 3.472 4.000 1.000 5.000 1.122 −0.342 −0.625
P3 3.231 3.000 1.000 5.000 1.161 −0.745 −0.351
Self-efficacy SE1 2.825 3.000 1.000 5.000 1.006 −0.729 0.301
SE2 2.840 3.000 1.000 5.000 1.171 −0.903 0.245
SE3 2.835 3.000 1.000 5.000 1.114 −0.807 0.166
SE4 2.443 2.000 1.000 5.000 0.991 −0.047 0.685
Academic stress AS1 3.354 4.000 1.000 5.000 1.214 −0.752 −0.483
AS2 3.528 4.000 1.000 5.000 1.101 −0.747 −0.243
AS3 3.552 4.000 1.000 5.000 1.038 −0.373 −0.496
workload W1 3.566 4.000 1.000 5.000 1.112 −0.487 −0.489
W2 3.363 4.000 1.000 5.000 1.155 −0.751 −0.319
W3 3.660 4.000 1.000 5.000 1.123 −0.680 −0.466
W4 3.151 3.000 1.000 5.000 1.419 −0.306 −0.150
Academic burnout B1 3.557 4.000 1.000 5.000 0.991 −0.047 −0.685
B2 3.566 4.000 1.000 5.000 1.112 −0.487 −0.489
B3 3.175 3.000 1.000 5.000 1.006 −0.729 −0.301
B4 3.231 3.000 1.000 5.000 1.161 −0.745 −0.351

4.3. Discriminant Validity

Discriminant validity was tested using the Fornell–Larcker criteria [107], which is
the expected level of “difference” between items measuring different factors. To test this
variable, the AVE for each factor is compared with the correlation square. Fornell and
Lacker [107] suggested comparing the AVE for each construct, and the shared variance
between constructs. Macintosh and Lockshin [111] used a matrix of covariance square (PHI
square) between constructs to test discriminant validity. Furthermore, this study uses the
Fornell–Larcker [107] criteria to test discriminant validity, as seen in Table 4, where the
diagonal is replaced with AVE (bold in Table 4). The AVE number on the bolded diagonal
is greater, and the extracted AVE ranges from 0.774 to 0.891. Therefore, the AVE is higher
than the variance shared between constructs’ coefficients.
Some studies thought the Fornell–Larcker criteria were not strong enough to check
discriminant validity. Therefore, this study assessed discriminant validity using the
Heterotrait–Monotrait (HTMT) ratio of correlations [112,113]. The alternative assessment
of the classical criterion can be applied to measure discriminant validity concerning the
threshold level described previously. A good indicator is below 0.9, which is an acceptable
limit [114,115]. As shown in Table 5, the discriminant validity results are confirmed, and it
can be concluded that the value is satisfactory.

4.4. Assessment of Effect Size (f2)

The effect size value analysis strengthens the R2 value used to clarify the latent
variables on the dependent variable. It can be calculated manually using the formula issued
Sustainability 2022, 14, 13416 11 of 24

by Cohen [116], namely R2-included minus R2-excluded, then divided by 1- R2-included

R2-included. The included R2 is the R-squared calculated based on the endogenous latent
variables when predictor exogenous latent variables are used in the structural model. The
omitted R2 is the R-squared calculated on the endogenous latent variable when the predictor
exogenous latent variable is not used in the structural model. Meanwhile, Cohen [117]
explained that the effect size is small when the value is 0.02, with the minimum and
maximum values occurring at 0.15 and 0.35.

Table 3. Analysis Measurement Model (Reliability and Convergent Validity).

Cronbach’s Composite Average Variance

Construct Indicator Factor Loading rho_A
Alpha Reliability Extracted (AVE)
Academic stress AS1 0.877 0.871 0.872 0.921 0.795
AS2 0.908
AS3 0.889
Academic burnout B1 0.790 0.776 0.782 0.857 0.600
B2 0.728
B3 0.738
B4 0.837
Coping strategies CS1 0.748 0.845 0.866 0.895 0.682
CS2 0.873
CS3 0.857
CS4 0.819
Perfectionism P1 0.889 0.805 0.826 0.884 0.718
P2 0.786
P3 0.864
Self-efficacy SE1 0.745 0.817 0.822 0.880 0.647
SE2 0.847
SE3 0.815
SE4 0.807
WORKLOAD W1 0.871 0.854 0.868 0.901 0.695
W2 0.828
W3 0.857
W4 0.777

Table 4. Fornell–Larcker for Discriminant Validity Testing.

Academic Stress Burnout Coping Str Perfect SE Workload

Academic Stress 0.891
Burnout 0.541 0.774
Coping Strategies −0.495 −0.705 0.826
Perfectionism 0.501 0.848 −0.670 0.848
Self-efficacy −0.398 −0.915 0.659 −0.790 0.804
Workload 0.819 0.702 −0.521 0.626 −0.579 0.834

Workload greatly affects preservice mathematics teachers’ academic stress (greater

than 0.35), and coping strategies and self-efficacy have a small effect on academic stress
Sustainability 2022, 14, 13416 12 of 24

of 0.075 and 0.083, respectively. Self-efficacy has the greatest effect on academic burnout,
followed by perfectionism. The full effect sizes of the exogenous latent variables on the
endogenous can be seen in Table 6.

Table 5. Additional Assessment for Discriminant Validity with the Heterotrait–Monotrait (HTMT)
Ratio of Correlations.

Academic Stress Burnout Coping Str Perfect SE Workload

Academic Stress
Burnout 0.659
Coping Strategies 0.557 0.859
Perfectionism 0.597 0.912 0.808
Self-efficacy 0.462 0.878 0.784 0.967
Workload 0.942 0.851 0.583 0.748 0.681

Table 6. Effect Size of predictive Variables.

Academic Stress Academic Burnout

Academic Stress 0.002
Coping Strategies 0.075 0.024
Perfectionism 0.153
Self-efficacy 0.083 1.162
Workload 1.505 0.070

4.5. Coefficient of Determination: R2 Value

The R2 value is obtained from the amount of variance in the dependent variable,
which the independent variable may explain [113]. The R2 value increases the prediction
of the structural model [106]. It is important to ensure that this value is high enough to
describe a structural model. The R2 value is considered sufficient to explain the variance in
the endogenous concept when it is more than 0.10 or 10%. In contrast, the Cohen criteria
stated that the R2 value should be greater than 0.26 or 26% to explain the manner of the
endogenous concept. Chin [118] had other criteria, where R2 should be more than 0.65
or 65%, to explain a model. Table 7 shows the R2 value, where the model can explain the
factors related to academic burnout and stress up to 0.905 or 90.5% and 0.702 or 70.2%,
respectively. In more detail, the R2 value and outer loading can also be seen in Figure 2.
Finally, five variables, including coping strategies, perfectionism, self-efficacy, workload
and academic stress, accounted for 90.5% of the variation in burnout among preservice
mathematics teachers.

Table 7. Explanation Power (R2).

R Square R-Square Adjusted

Academic STRESS 0.702 0.698
Academic BURNOUT 0.905 0.903

4.6. Collinearity Test

The collinearity Test on PLS-SEM can be analyzed by determining the Variance Infla-
tion Factors (VIF) value [119] (Table 8). It can be interpreted as the relationship between
one predictor and another. The purpose of checking the collinearity test is to analyze the
possibility of two or more predictors to measure the components of the concept on the
two types of VIF used. Meanwhile, outer and inner VIF show the collinearity level in and
between the constructs or latent variables.
Sustainability 2022,14,
Sustainability2022, 14,13416
x FOR PEER REVIEW 13 of
13 of 24
25

Figure2.2.Structural
Figure StructuralModel
Modelwith
withR2
R2and
andPath
PathCoefficient.
Coefficient.

Table8.7.Variance
Table Inflation
Explanation PowerFactors-VIF
(R2). value.

Item Outer VIF R Square

Inner VIF to Academic Stress R-Square
Inner VIF to Adjusted
Academic Burnout
Academic STRESS
AS1 2.181 0.702 0.698
3.367
Academic
AS2 BURNOUT
2.709 0.905 0.903
AS3 2.240
4.6. Collinearity Test
B1 1.533
The collinearity Test on PLS-SEM can be analyzed by determining the Variance In-
B2 1.440
flation Factors (VIF) value [119] (Table 8). It can be interpreted as the relationship between
B3 1.511
one predictor and another. The purpose of checking the collinearity test is to analyze the
possibility
B4 of two or more predictors to measure the components of the concept on the
1.829
twoCS1
types of VIF1.675
used. Meanwhile, outer and inner VIF show the collinearity level in and
between the constructs or latent variables.
CS2 2.157 1.864 2.139
CS3
Table 2.058
8. Variance Inflation Factors-VIF value.
CS4 1.900
Inner VIF to Aca- Inner VIF to Aca-
P1 Item 2.253 Outer VIF
demic Stress 3.243
demic Burnout
P2 AS1 1.660 2.181 3.367
P3 AS2 1.744 2.709
SE1 AS3 1.562 2.240
SE2 B1 2.068 1.533 2.042 3.152
B2 1.440
SE3 1.941
B3 1.511
SE4 1.682
B4 1.829
W1 2.181
CS1 1.675
W2 CS2 1.989 2.157 1.586 1.864 4.067 2.139
W3 CS3 2.124 2.058
W4 CS4 1.710 1.900
P1 2.253 3.243
P2 1.660
P3 1.744
Sustainability 2022, 14, 13416 14 of 24

O’Connell and Bowerman [120] and Hair et al. [105] stated that a VIF value greater
than 5 has a problem with collinearity. In this study, the maximum VIF for the item is 2.709
(AS2), and the construct is 4.067 (workload). Thus, it can be concluded that the VIF value
for items and variables is quite low, and the problem of multicollinearity does not exist.

4.7. Importance–Performance Map Analysis (IPMA)

Since the study aims to investigate the main sources of constructs that can provide
explanations, such as academic burnout, PLS-SEM is an appropriate technique because it
is very helpful for achieve this goal. This technique has IPMA to prioritize their actions.
For example, suppose the endogenous target variable is academic stress, and that IPMA
calculates the total effect of the important structural model with the average latent variable
scores. This finding can reveal important determinants with a large overall factor and low
latent variable score [121].
Figure 3 and Table 9 show the IPMA results for the prestigious mathematics teacher
academic burnout. Based on Table 9, perfectionism and academic stresses are of the highest
importance (0.218) and performance (62.119) on preservice mathematics teachers’ academic
Sustainability 2022, 14, x FOR PEER REVIEW
burnout. Figure 3 and Table 9 also show that self-efficacy and coping strategies have 15 of
the25
least important performance variable at 0.584 and 30.909.

Figure3.3.Final
Figure FinalModel
Modelwith
withIPMA
IPMAResult.
Result.

4.8.
4.8.Hypotheses
HypothesesTesting
TestingResults
Results
Hypothesis
Hypothesis testingisisthe
testing thefinal
finalstage
stageininthe
thestructural
structuralmodel
modeltototest
testthe
therelationship
relationship
between constructs. Based on Table 10, this study consists of eight initial hypotheses,
between constructs. Based on Table 10, this study consists of eight initial hypotheses, where
7where
were accepted, and one and
7 were accepted, was one
rejected
was because
rejectedthe p value
because thewas belowwas
p value 0.05. Therefore,
below most
0.05. There-
offore,
the most
path coefficients on the structural
of the path coefficients on themodel are significant.
structural In detail, coping
model are significant. strategies
In detail, coping
strategies were found to be directly negative and significant to academic stress (β = −0.204;
p < 0.001), thereby, confirming Hypothesis 1. This is also directly significant to academic
burnout (β = −0.071; p < 0.05), hence confirming Hypothesis 2. Perfectionism is the biggest
positive factor affecting academic burnout (β = 0.218; p < 0.001), which is appropriate to
Sustainability 2022, 14, 13416 15 of 24

were found to be directly negative and significant to academic stress (β = −0.204; p < 0.001),
thereby, confirming Hypothesis 1. This is also directly significant to academic burnout
(β = −0.071; p < 0.05), hence confirming Hypothesis 2. Perfectionism is the biggest positive
factor affecting academic burnout (β = 0.218; p < 0.001), which is appropriate to Hypothesis
3. Meanwhile, self-efficacy has a significant direct effect on academic burnout (β = 0.224;
p < 0.001) (β = −0.590; p < 0.001), therefore it can confirm Hypotheses 4 and 5. Workload
significantly affects academic stress negatively (β = 0.843; p < 0.001), and academic burnout
(β = 0.164; p < 0.001). Finally, testing Hypothesis 8 shows that academic stress does not
significantly correlate to burnout (β = 0.028; p > 0.05).

Table 9. Importance–Performance Map Analysis Value.

Variable Preservice Mathematics Teacher Academic Burnout

Importance Performances
ACADEMIC STRESS 0.028 62.119
COPING STR −0.076 30.909
PERFECT 0.218 59.909
SE −0.584 42.995
WORKLOAD 0.188 61.759
Notes: Importance is the total effect of structural model = average values of latent variable scores [106].

Table 10. Hypothesis Testing Results.

H Hypothesis β Sample Mean (M) (STDEV) T Statistics p Values

H1 Coping Strategies -> Academic Stress −0.204 −0.207 0.063 3.217 0.001
H2 Coping Strategies -> Academic Burnout −0.071 −0.068 0.033 2.118 0.035
H3 Perfectionism -> Academic Burnout 0.218 0.225 0.042 5.226 0.000
H4 Self-efficacy -> Academic Stress 0.224 0.222 0.063 3.592 0.000
H5 Self-efficacy -> Academic Burnout −0.590 −0.585 0.045 13.086 0.000
H6 Workload -> Academic Stress 0.843 0.840 0.038 22.251 0.000
H7 Workload -> Academic Burnout 0.164 0.166 0.045 3.659 0.000
H8 Academic Stress -> Academic Burnout 0.028 0.028 0.042 0.670 0.503

In summary, seven hypotheses about factors affecting academic burnout are supported
(H1, H2, H3, H4, H5, H6, H7), while H8 is not supported.

5. Discussion
Academic burnout is one of the essential factors in education sustainability. The
study began to attract attention in 1970, as a gradual depletion and loss of motivation
to learn and achieve goals in an educational context developed. Initially, studies on this
variable were focused on the world of work to analyze the level of burnout in workers
due to excessive working hours or high pressure given by superiors in the context of
sustainable well-being. Meanwhile, there is still limited study analyzing preservice teachers’
academic burnout. This study aims to analyze factors related to academic burnout and
obtains a significant negative relationship between coping strategies, academic burnout,
and stress. Furthermore, these findings are consistent with previous studies on students
with good coping and problem-solving strategies, which tend to have less academic stress
and burnout [58,94,122]. The respondents in this study are future mathematics teacher
candidates. Therefore, they have good basic coping strategies when facing problems, and
the results are consistent with the model of stress [54], where a person will use a coping
strategy when experiencing psychological stress in daily life. Students at the university
Sustainability 2022, 14, 13416 16 of 24

level should have problem-solving coping strategies in the face of depression and low
psychological distress [28]. Andrei [57] stated that coping strategies can be interpreted as
always being optimistic, having a positive attitude, exercising diligently, talking to friends
or other people when finding problems, and thinking about the final goal and others.
The study should focus more on the person and further ascertain how the individual
is restrained from dealing with stress, and the factors that may make one feel powerless
when experiencing stressful conditions. This study finds that perfectionism is the biggest
factor responsible for academic stress. The finding is consistent with previous studies,
that students at the university level with high perfectionism often experience academic
stress compared to others [123,124]. In China, there is a hard-working culture with high
expectations to achieve a better life in the future. A hard-working culture is considered
the need of Chinese people, which in turn forms the perception that they need and are
obliged to work hard. According to appraisal theory, stress models refer to human needs
and can describe stressors for more than 20 years. Another theory by Combs et al. explains
that stress is caused by the threat that an individual feels because of the views of other
people’s perceptions. This condition ultimately causes pressure, called stress. Preservice
teachers are carried away by the high expectations of their parents and those around them.
Therefore, the mindset of perfectionism formed is the effect of the people around their
environment, which causes academic stress [80,125]. This circumstance encourages students
to strive to meet their parents’ expectations, resulting in emotional exhaustion, stress and
burnout [5,126]. Therefore, these results are supported by previous studies on perfectionism
which makes preservice mathematics teachers in China experience academic stress.
This study supports the idea that preservice mathematics teachers with high self-
efficacy have low academic burnout. Students with high self-efficacy can make rational
decisions and manage their negative emotions to deal with stress and burnout [83,127]. In
addition, Bandura’s [82] social cognitive theory states that those with high self-efficacy can
analyze and evaluate their past and turn failures into plans to achieve a successful future.
High school mathematics teachers with high self-efficacy are believed to accept pressure
and burnout, encouraging them to achieve their final goals. This finding is supported
by Robbins and Judge’s model of stress [39], where individual differences can affect the
chances of experiencing psychological stress.
A surprising finding is that self-efficacy significantly increases academic stress. This
can be explained by preservice mathematics teachers having excessive self-efficacy. They
are confident to take many courses and participate in school activities, causing them
to be overloaded and exhausted. This is more experienced by students in the first and
second years, where their self-efficacy and enthusiasm are still high. They are unaware
that professional teacher education entails a hefty burden and numerous responsibilities.
Therefore, those who take good courses and many non-academic activities experience
academic stress. Over time, they will realize and not repeat similar mistakes by taking
good courses and attending many non-academic programs in the third and fourth years.
This study adds the workload factor as a predictor of academic stress and burnout.
Based on the literature review, workload significantly correlates to preservice mathematics
teachers’ academic stress and burnout [26,30]. The finding, that workload is a potential
cause of stress and burnout, is also in line with findings on workers [97,128]. Kwaah [97]
suggested that the number of tasks closely affects these variables, where teachers have
many tasks and are tired. They do not have personal time to relax and reduce their stress
levels. Another study found that university students may have higher well-being when
subjected to fewer assignments. However, preservice teachers are aware of the additional
need to perform several tasks, follows several organizations for their achievements, and
applies for scholarships annually. This is an important predictor that can make students
experience academic burnout, drop out of school, and even commit suicide.
Finally, academic stress does not significantly affect burnout. Some students who have
good coping strategies and self-efficacy can turn academic stress into motivation for them
to achieve better performance. This finding supported by the theory that many factors
Sustainability 2022, 14, 13416 17 of 24

potentially cause preservice teachers to experience academic burnout [14,26]. This finding
is supported by several studies, which showed that different factors could affect university
students experiencing burnout [38,129,130].

6. Theoretical and Practical Implication

This study is in line with Lau S et al. [5], which examined the factors associated
with academic burnout. In the context of sustainability in education, coping strategies
and self-efficacy decreased academic burnout, unlike perfectionism, which is strongly
correlated. However, this study develops more predictors related to academic burnout
and stress. The findings differ from Lau’s study, where perfectionism is the main factor
that causes academic stress. Therefore, the workload felt by students due to a large
amount of material provided to preservice teachers is the leading cause of academic stress.
These findings contribute significantly to the model of stress and academic burnout for
students at the university level, especially preservice mathematics teachers. The stress
model explains psychological well-being and academic burnout in education. The initial
model was developed by adding academic stress and workload predictors to investigate
preservice mathematics teachers’ academic burnout. Preservice mathematics instructors
may be considered “occupational” because they are involved in structural organization
and mandatory programs to present their ideas or assignments and complete tasks from
professors to earn high final grades. Due to stress, they tend to have negative learning
outcomes, lack of interest in learning, anxiety, high absenteeism and burnout [131,132].
Therefore, this study aims to contribute to the current literature by creating a model to
examine factors related to academic burnout at the university level, especially for preservice
teachers with different perspectives on the stress model.
This study finds that coping strategies are the best way to overcome academic burnout.
Preservice mathematics teachers with high coping strategies will move systematically and
effectively to deal with and solve problems related to academic stress and burnout by
participating in activities to overcome existing problems. Besides reducing factors that
cause stress, increasing facilitators can also improve performance to prevent academic
burnout. The findings provide important knowledge and information regarding awareness
of academic stress and burnout problems in preservice mathematics teachers. The faculty
or mental health institutions can organize workshops or forums to educate all preservice
mathematic teachers on the importance of coping strategies and self-efficacy. Moreover, they
should support preservice mathematics teachers in training programs such as increasing
self-efficacy, controlling emotions and well-being.
The condition of students who always want to excel and their perfectionist nature in
the academic fields subject them experience academic burnout. Parents always need to focus
on providing counseling to their children. Therefore, feelings of well-being and balance
between learning and playing time might make them more emotionally stable and reduce
academic stress. Furthermore, schoolteachers should remind students that perfectionism
is not the only way to achieve good academic grades. However, many other factors, such
as attitude, broad relations, and different speech styles, are more critical [133–135]. The
collaboration of schools, lecturers, and parents to change the perspective of perfectionist
students can be one practical step to reducing academic stress and burnout for preservice
mathematics teachers.
Preservice mathematics teachers should be more mindful and pay attention to the
negative effects of workload and stress. Furthermore, they should develop the right values
to achieve goals and trust. People around them, such as teachers and supervisors, should
have good resources to reduce student academic burnout, increase self-efficacy and provide
solutions to eliminate problems. Schools in China should have a psychology department
that understands and is professional about stress and burnout symptoms. Therefore,
these efforts are expected to improve teacher–student well-being, leading to maximum
learning outcomes. Educational institutions in China should focus on improving soft
Sustainability 2022, 14, 13416 18 of 24

skills, such as communication, problem-solving, and decision-making, as well as increasing

extracurricular activities that can reduce academic stress.

7. Limitations and Suggestions for Future Study

The results have consequences for preservice mathematics teachers’ academic burnout,
which is very important to identify their perceptions of what factors cause burnout and
stress during four years of education and how to reduce these variables. Therefore, this
study provides knowledge about factors related to academic stress and burnout for fur-
ther understanding.
Concerning the limitations, some teachers may not know the difference between
emotional exhaustion and stress related to their future life and challenges after measuring
academic stress and burnout. The experiment in this study is conducted in a relatively
short period of 3 months. In the future, it is recommended to carry out a longitudinal
analysis to confirm these findings. Furthermore, the sample is relatively small, with less
than 1000 preservice mathematics teachers and respondents from Guangxi Province, China.
Therefore, these findings need to be generalized with caution. Other studies are suggested
to use mixed or qualitative methods to confirm the findings of the factors affecting the
preservice mathematics teachers.

8. Conclusions
The results emphasize the relationship between the five predictors of academic burnout
in preservice mathematics teachers. Coping strategies are one solution that has a significant
effect on reducing academic burnout and academic stress. Meanwhile, the internal factors of
perfectionist students are the main factors responsible for academic burnout. The workload
is also the main problem that causes teachers to experience academic stress, which interferes
with learning performance.
The education of teachers poses a challenge for preservice mathematics teachers
with poor coping strategies and self-efficacy. Many of them in China experience stress,
burnout, and lack of concern for others, feel incompetent in completing assignments, have
a lack of interest in learning, and also find assignments and exams difficult. Stress and
burnout associated with study lead to poor learning outcomes, class absences, and low
learning accomplishment. Preservice mathematics teachers with good coping strategies
and self-efficacy can have lower stress levels and succeed in learning. They enjoy carrying
out study-related tasks, feel less tired or fatigued, and have higher levels of self-efficacy.
Therefore, these students perform better than those with high burnout.
Considering this study is about the negative effect of academic stress and workload
on burnout, universities should support students to increase self-efficacy and reduce
teachers’ workload. This is because students experiencing academic stress often lose sight
of their learning goals and the importance of mastering subjects on campus, causing them
to suffer burnout and to some dropping out of the program they are taking. Building
a comfortable environment for students, with fun learning activities, and a supportive
learning atmosphere is a way to reduce the dangers of stress and burnout for teachers.

Author Contributions: Conceptualization, investigation and collecting data, L.Q., J.L. and T.T.W.;
writing—review and editing, M.F., Y.H., L.Q. and T.T.W.; analysis data and visualization T.T.W., Y.H.
and M.F.; supervising Y.Z. and J.L. All authors have read and agreed to the published version of
the manuscript.
Funding: This research was funded by China National Social sciences project (19BKS147).
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: Not applicable.
Conflicts of Interest: The authors declare no conflict of interest.
Sustainability 2022, 14, 13416 19 of 24

Appendix A
Table A1. Measurement items in the questionnaire.

Variable Construct Question English Version Sources

当我在学习上遇见问题时，我会花时间试 When I had difficulties in my studies, I tried to
Coping strategies [54,55]
图了解到底发生了什么 figure out the cause.
When I encounter a learning problem, several
当我在处理学习上的问题时，我考虑了几
alternative ways of dealing with it
种处理问题的备选方法
are considered.
When I have problems at school, I often use
当我在学校遇见问题时，我经常使用锻
sports, hobbies, or meditation to help me
炼、爱好或冥想来帮助我度过难关
calm down.
当我在学习上遇见问题时，在处理问题 When I have a problem with my study, I often
时，我经常试图记住，问题并不像它看起 try to remember that the situation is not
来那么严重 very serious.
When I have problems with my study, I think it
当我在学习上遇到问题时，可能说明我需
might indicate a change in my quality of life for
要做出更大的生活改变
the better.
Perfectionism 我总是要在校园里取得最好的成就 I always have to achieve the best on campus. [5,54]
I am always more active on campus than
我总是比我的朋友更积极地参加校园活动
my friends.
总体来说，我必须比我的朋友优秀 Overall, I have to be better than my friends.
It is not hard for me to get good grades
Self-efficacy 我在大学取得好成绩并不难 [83,136]
on campus.
我可以掌握校园里的所有科目 I can master all subjects well on campus.
My achievements stand out more than
我成就比我的同学更突出
my classmates.
I will use various strategies to improve my
我会使用各种策略来提高我的学习成绩
academic performance.
Academic stress 我不能接受我成绩 I cannot accept my achievements. [31,137]
对我来说考试总是很难 School exams are always challenging for me.
我认为学习任务太多了 I think there are too many study assignments.
Workload 我有太多的材料要准备上课 I have too much material to review for class. [31,138]
I have participated in too many activities
我在校园里参加了太多的活动
on campus.
我上太多课了 I took too many classes.
The teacher gave me a lot of
我的老师批评我的学习成绩
additional assignments.
Academic burnout 我无法解决学习中出现的问题 I cannot solve problems that arise in my study. [4,83]
对我来说，我不是一个好学生 In my opinion, I am not a good student.
I am not enthusiastic about achieving my
当我达到学习目标时，我不会感到兴奋
study goals.
I feel I did not learn anything interesting during
我在学习期间没有学到任何有趣的东西
my study.
在课堂上，我不相信我能有效地完成学习 In class, I do not believe that I can complete my
任务 study assignments effectively.
Sustainability 2022, 14, 13416 20 of 24

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