The Impact of Covid-19 Pandemic On Educators In South Africa: Self-Efficacy And Anxiety

Abstract

The Covid-19 pandemic caused unparalleled disruption in the lives of the majority of the world. This included school closures and introduction of Online Learning. In this article we investigated the impact of distance learning on the self-efficacy and anxiety levels experienced by educators in South Africa. We surveyed 60 respondents from Independent Schools using a Likert Scale rating of 0 to 4. The results suggested that despite experiencing moderate anxiety, educators showed a sense of high self-efficacy during distance learning. This was specifically true for those with underlying health concerns. There was no significant difference between how the different genders experienced anxiety and self-efficacy. Further research into the impact on learners' anxiety levels during distance learning will provide policymakers and educators with a better understanding of how the use of technology is influencing the effectiveness of teaching, learning, and assessment.

Full text

The Impact of Covid-19 Pandemic On Educators In South Africa: Self-Efficacy And Anxiety
MOSTERT JACQUES
Independent Institute of Education, South Africa
E-mail: jmostert@advtech.co.za
GULSEVEN OSMAN
Middle East Technical University, Turkey
E-mail: gulseven@metu.edu.tr
WILLIAMS COURTNEY
Grantley College, South Africa
courtneyw@grantleycollege.co.za
Abstract
The Covid-19 pandemic caused unparalleled disruption in the lives of the majority of the world. This
included school closures and introduction of Online Learning. In this article we investigated the impact of
distance learning on the self-efficacy and anxiety levels experienced by educators in South Africa. We
surveyed 60 respondents from Independent Schools using a Likert Scale rating of 0 to 4. The results
suggested that despite experiencing moderate anxiety, educators showed a sense of high self-efficacy during
distance learning. This was specifically true for those with underlying health concerns. There was no
significant difference between how the different genders experienced anxiety and self-efficacy. Further
research into the impact on learners’ anxiety levels during distance learning will provide policymakers and
educators with a better understanding of how the use of technology is influencing the effectiveness of
teaching, learning, and assessment.
Key words: COVID-19; Education; Self-efficacy; Anxiety
Introduction
During the all-encompassing restriction of social interaction - through the South African
government's strict interventions - there was a near-instant change in teaching, learning, and
assessment in South African schools. This research aims provide important insight into the current
efficacy of the curriculum, assessment policies, and pedagogy. We form an understanding of the
self-efficacy with which educators, especially within the special educational teaching and learning
environment, approached the abrupt disruption in traditional teaching and assessment methods to
online teaching methods and platforms. We emphasize how self-efficacy influenced the teaching,
learning, and assessment, and the levels of anxiety experienced during this time. Considering the
current knowledge and understanding, a broader spectrum of consideration is required to understand
the impact of COVID-19 on the independent education sector in South Africa that is evident at first
glance. In terms of both popular media and peer-reviewed approaches, the COVID-19 pandemic
experts have more than a broader understanding of the global impact of the magnitude on social,
economic, and educational spheres of the global society[1]. Before we dive deeper into the subject
matter, it is best to provide a summary of the key concepts used in this research.
The construct of self-efficacy is explicated as an individual’s beliefs in their own capability
to coordinate, implement, and control a required course of action/s that will result in their desired
outcomes[2]. Self-efficacy is resultant from four fundamental sources: performance
accomplishments, vicarious experience, verbal persuasion, and physiological and affective states
[3]. In all spheres of life, self-efficacy may thus be considered a significant indicator of producing
successful outcomes, and thus “the foundation of human performance” [4]. In the same way, it is
thus acceptable to postulate that self-efficacy plays a significant role in the educators' effective

teaching, learning, and assessment (TLA) proficiency. Moreover, one may surmise that the key
ingredient in the successful execution of eLearning, especially during a time of disruption, is the
educator’s self-efficacy: not only in terms of established pedagogical skill; experiences in accessing
and utilizing eLearning tools; but also, in successfully implementing eLearning strategies. However,
self-efficacy beliefs are also reliant on the level of anxiety educator experiences in the process of
online TLA [5]. For educators to successfully transition from in-class traditional TLA pedagogy, the
technology aspect of self-efficacy in online learning is fundamental in achieving effective learning.
For example, an educator’s “computer self-efficacy: internet self-efficacy, information-seeking self-
efficacy; and Learning Management System self-efficacy in online learning environments” [6] are
essential factors in transitioning from traditional methods to online TLA – in many cases overnight.
Insofar as self-efficacy proves to be an imperative component for success in online teaching
and learning, new online pedagogy should be designed with self-efficacy considered from the
creation of the design process [4]. However, in reflection of the abruptness of the disruption in the
international education environment, such considerations were in practical terms not possible.
Therefore, it is essential for policy makers, education leaders and educators to develop a better
understanding of how self-efficacy impacted on educators’ online TLA proficiency.
The degree of positive self-efficacy and experiencing anxiety is established [7], and the
impact of anxiety related to the abrupt transition from traditional in-person TLA to completely
online-based TLA should therefore form a part of understanding how self-efficacy and anxiety
impacted on educator effectiveness.
Anxiety can be defined as the unpleasant psychological or physiological experiences due to a
perceived external threat or aspects [8]. Such aspects can be termed as stressors and have been
identified as student misbehavior; time consuming workload and deadlines; poor learner motivation;
lack of school-based support and encouragement; and value conflicts [8]–[10] . Educator anxiety has
negative consequences and is seen to correlate with absenteeism, reduced job satisfaction, and low
morale [11]. These negative consequences further impact a teacher’s mental health, their learners
and the school [12].
The human service professions that typically involve more human interaction, such as
support and caring, tend to be more susceptible to greater levels of workplace related stress, anxiety
or burnout [13]. In recent years, research has suggested that teaching is one of the most stressful
professions due to the high accumulation of acute anxiety directly related to teacher-specific
stressors in the workplace [14], [15].
The COVID-19 pandemic has been and still is a period of heightened psychological stress
causing teachers to shift to unfamiliar and difficult circumstances with little warning, preparation
and even training. Teachers have been expected to adapt, adjust and continue to deliver online
teaching, lessons and assessments yet, policy decisions and the stress being produced are somewhat
of an afterthought, if considered at all [16].
When educators experience acute anxiety, it implicates their well-being which further
implicates their teaching. High levels of acute anxiety can result in both physical and mental health
problems including depression and anxiety. Anxiety can weaken the immune system resulting in
physical and psychological ailments such as headaches, low mood, sore muscles, and depression.
Educators who have poor coping skills and who experience prolonged levels of acute anxiety can
develop professional burnout [12]. Maslach [17] identifies three dimensions of teacher burnout –
emotional exhaustion, caused by work pressure and loss of energy to face the day;
depersonalizations, cynical and cold attitudes towards people with whom they work and teach; and
lack of personal fulfilment, which is the feeling of negative self-efficacy and decreased successes,
personal skills, and achievements. Educators who experience acute anxiety appear to directly affect
the learning environment and hinder the achievement of educator’s goals, having a negative effect
on the well-being and performance of the learners [11]. Moreover, acute anxiety appears to impair

an educator’s ability to implement innovative and effective classroom practices and thus they
struggle to provide high quality learning environments, whether online or in the traditional in-person
setting resulting in diminished educator-learner relationships, negative learner social and
behavioural outcomes, as well as decreased academic results [12]. Increased educator anxiety also
results in educator absenteeism and even attrition. This is not only costly to the education system but
also further implicates learners due to the disruption and inconsistent teaching, learning and
assessment [18].
The South African Department of Basic Education (DBE) in conjunction with the
Department of Health (DoH) published a directive to educators with pre-existing and historical
health difficulties (referred to a comorbidities) to work from home during the top levels of the social
distancing lockdown [19]. With easing of social restrictions these educators have been encouraged
to return to the classroom, however, increased levels of concerns regarding contraction of COVID-
19 through contact at school, despite stringent integration regulations, were ubiquitous.
Notwithstanding, there is a dearth in the extensive literature regarding the interrelationships between
the health status of individuals, anxiety and depression concerns [20]. Susceptibility to infection and
severity of any such infections on educators with existing health concerns grew dramatically [21].
Research into the correlation between anxiety disorders and physical health conditions found
significant associations in individuals with comorbidity and anxiety [22]. As a matter of fact, there is
a compelling bidirectional association between anxiety (with clinically related disorders) and
comorbid medical conditions [1]. Whereas the prevalence of comorbid anxiety experiences and
associated physical, comorbid conditions are not as well as considered as anxiety or depressive
disorders, in medical research, research indicates correlation between anxiety and physical
comorbidity [1].
Research Problem
With the impact of the abrupt transition to online teaching and learning, one may assume that
increased levels of work-related stressors may contribute to elevated levels of anxiety. In addition,
considering that the South African education landscape has had a slower transition to online
teaching and learning, it is important to understand how the sudden transition to online teaching and
learning may have on educator self-efficacy. Our research aims to determine if educator responses to
the changes:
1) What impact does educator anxiety and self-efficacy have on teaching and learning during the
Covid-19 pandemic?
2) Does educator gender have an impact on educator self-efficacy or anxiety?
3) Does background health concerns impact on anxiety and self-efficacy?
Research Methodology
To see the relationship between health status, anxiety, and self-efficacy, we have conducted
a survey with 60 respondents from Independent Schools in South Africa. All respondents are
involved in educational institutes with a direct teaching role. Twenty-five percent (25%) of
respondents were male, and 45 (75%) were female. The respondents answered several questions
regarding their teaching experience, their affective experiences and self-efficacy during the South
African government imposing of a lockdown period. Since we are specifically interested in the
relationship between self-efficacy and anxiety status, to calculate these factors we asked 11
questions. Thus, our data has 11 answers that define self-efficacy and anxiety levels of the
educators.
The self-efficacy questions were adapted from Beck Self-Concept Test (BST), all the BST’s
items were significantly correlated with the corrected total scores; the coefficient alpha was .82,

indicating good internal consistency. The 1-week and 3-month test–retest reliabilities were .88
and .65, respectively [23]. The adapted survey required respondents to answer 11 questions with 5
options [24]. These options are never, sometimes, often, most of the time, and always. To quantify
these choices, we have created a numerical coding system as follows: Never = 0, Sometimes =1,
Often = 2, Most of the time = 3, Always = 4
Once the above quantification is created, we can either use the mean, median or the mode as
the numerical indicator of self-efficacy. While for most observations, these indicators suggested
close values, we have chosen the arithmetic mean as our self-efficacy indicator. This also keeps the
variety in the self-efficacy factor among educators.
The mean value for self-efficacy is 2.08, and this is lower than the median value of 2.32. The
kurtosis of the self-efficacy is -1.39, thus the self-efficacy has less in the tails than the normal
distribution. The skewness value of -0.09 suggests that the data is also slightly left skewed. The
histogram also shows us that the educators had a high self-efficacy during the pandemic period.
The Beck Anxiety Inventory (BAI) [25] was adapted to measure the educator anxiety during
the pandemic. The Beck Anxiety Inventory (BAI) is a 21-item scale that showed high internal
consistency (α = .92) and test–retest reliability over 1 week [26]. Similar to the self-efficacy
survey, we asked 11 questions that aim at measuring the anxiety levels of the respondents. However,
this time the respondents had 4 choices which are never, sometimes, often, and always. The
respondent answers are re-coded numerically as follows: Never =0, Sometimes =1, Often =2,
Always = 3
The mean value for anxiety is 1.15, which is slightly higher than the median value of 1.09.
The kurtosis of the self-efficacy is 0.5, thus the anxiety variable has more in the tails than the normal
distribution. The skewness value of 0.64 suggests that the data is right-skewed. Thus, there are a few
people who are very concerned with high anxiety levels. We observe that the most educators had
relatively lower values of anxiety during the pandemic period. Once the numerical conversion is
done, we recategorized the anxiety levels as follows: 0 to 1 => No anxiety, 1 to 2 => Anxious, 2 and
above => Severe Anxiety
Twenty-one (21) of the educators (35%) reported an ordinary level of anxiety, between 0 to
1. However, 33 (55%) reported acute anxiety, whereas 6 (10%) reported chronic anxiety levels.
Educators were not concerned much with what others think of them or whether they can get into
trouble. However, there were some concerns regarding the possibility of getting sick. That is why it
was harder for educators to switch off and relax. This also caused some sleeping disorders.
Research Results
First, we test for whether there is any relationship between self-efficacy and anxiety. As per
our data, self-efficacy is quantified as between 0 to 4. For anxiety we have both quantitative and
qualitative measurements. The quantified anxiety level is a number between 0 to 3. First, we check
for correlation between these two factors where anxiety is defined in a similar numerical fashion to
self-efficacy. The computer output suggested a Pearson correlation of -0.006 with a p-value of
0.963. The correlation is negligibly negative, and the p-value is very high. Thus, we do not observe
any direct relationship between self-efficacy and anxiety.
We do the same analysis where anxiety is defined as an ordinal data with three ranked
categories (No anxiety, anxious, severe anxiety). The null hypothesis and alternative are as follows:
H0: No relationship between self-efficacy and anxiety
H1: Some relation between self-efficacy and anxiety.
To be more accurate we conduct multivariate analysis of variance (MANOVA) in order to
test whether there are any self-efficacy differences between different levels of anxiety using Minitab
statistical analysis software. Stat > ANOVA > General MANOVA

Table 1. General Linear Model: Self-efficacy versus Anxiety Status
Test Statistic DF
Criterion F Num Denom P
Wilks’ 0.9729 0.794 2 57 0.457
Lawley-Hotelling 0.0278 0.794 2 57 0.457
Pillai’s 0.0271 0.794 2 57 0.457
Roy’s 0.0278
s = 1 m = 0.0 n = 27.5
We tested for statistically significant difference using Wilks’, Lawley-Hotelling, Pillai’s, and
Roy’s criteria. Based on all of the criteria, there is no statistical difference. We cannot reject H0.
There is no statistically significant relationship between self-efficacy and anxiety status even when
we measure anxiety as a rank variable. Our numerical analysis confirms the similar looking box
plots.
We also tested our data to see if there is any relationship between self-efficacy scale and
gender. Both genders have similar self-efficacy levels. The mean (2.03) and median (2.18) levels
among female participants are slightly lower than that of the male mean (2.22) and median (2.81)
levels. The two-sample t-test null and alternative hypothesis are as follows:
H0: There is no difference in self-efficacy scores of female vs male participants (μ - µ = 0).  
H1: There is a difference in self-efficacy scores of female vs male participants (μ - µ ≠ 0). 
The mean difference is -0.190 but the confidence interval is between -0.808 and 0.429. The
associated t-value is -0.64 and the p-value is 0.532. The t-value of the test is less than any significant
threshold. The corresponding p-value is also very high. Thus, the results show that there is no
statistical difference in the self-efficacy scores between male and female participants. While the
mean self-efficacy score of males is higher (2.22 vs 2.03) than that of females, this is not statistically
significant.
We also conducted a similar exercise to see if gender is a contributing factor in anxiety.
However, since we defined anxiety as a rank variable, we sorted to X-square test for association.
H0: The variables gender and anxiety are independent; no association between variables exists.
H1: The variables are not independent; an association between gender and anxiety exist and
variables are dependent.
Table 2. Chi-Square Test for Association: Gender, Anxiety
Anxious No Anxiety Severe Anxiety All
Female 27 13 5 45
(Expected) 24.75 15.75 4.5
Male 6 8 1 15
(Expected) 8.25 5.25 1.5
All 33 21 6 60
Chi-Square Test
Chi-Square DF P-Value
Pearson 2.961 2 0.228
Likelihood Ratio 2.870 2 0.238

The X-square test results show that actual and expected number of participants in each
anxiety rank is very similar. Both the Pearson (0.228) and Likelihood Ratio (0.238) associated test
suggest p-values in excess of 0.05. Since our p-value > alpha, we can reject the null hypothesis and
conclude that there is no association between gender and anxiety rank.
While we did not find any statistically significant relationship between self-efficacy and
anxiety, we also wanted to confirm whether that also for each gender. This time we used the General
MANOVA testing procedure as follows.
Table 3. MANOVA Tests Self-efficacy versus Anxiety by Gender
Criterion Test Statistic F DF - Num DF - Denom P
Wilks’ 0.97514 0.714 2 56 0.494
Lawley-Hotelling 0.02549 0.714 2 56 0.494
Pillai’s 0.02486 0.714 2 56 0.494
Roy’s 0.02549
s = 1 m = 0.0 n = 27.0
We tested for statistically significant difference using Wilks’, Lawley-Hotelling, Pillai’s, and Roy’s
criteria. The p-values are all higher than 0.05. Based on all of the criteria, there is no statistical
relationship between self-efficacy and anxiety. This result is valid regardless of the gender.
Finally, we tested our data to see if having a background health problem is somewhat related
to the individual self-efficacy and/or anxiety. We divided our data into two groups based on whether
they have any background health problems or not.
H0: Self-efficacy score is same regardless of background health problems.
H1: Self-efficacy score is higher among those with background health problems.
Table 4. T-Test Self-Efficacy by Health Status (Assuming Unequal Variances)
With Health Concerns No health concerns
Mean 1.38 0.97
Variance 0.41 0.40
Observations 26 34
Hypothesized Mean Difference 0
df 53
t Stat 2.48
P(T<=t) one-tail 0.01
t Critical one-tail 1.67
P(T<=t) two-tail 0.02
t Critical two-tail 2.01
Since the p-value is 0.01 < 0.05, the results show that those with background health problems also
have higher self-efficacy levels.
H0: Anxiety level is same regardless of background health problems.
H1: Anxiety level is higher among those with background health problems.
Table 5. T-Test Anxiety by Health Status (Assuming Unequal Variances)
Health Concern No Health Concern
Mean 1.36 0.86

Variance 0.34 0.34
Observations 26 34
Mean Difference 0
df 54
t Stat 3.28
P(T<=t) one-tail 0.00
t Critical one-tail 1.67
P(T<=t) two-tail 0.00
t Critical two-tail 2.00
Since the p-value is 0.00 < 0.05, the results show that those with background health
problems also have higher anxiety levels.
Discussion
Findings show, insofar as self-efficacy [24] educators experienced a high sense of self-efficacy
during the pandemic period, however they did not feel a sense of normality. One might question
whether such high self-efficacy, of educators working in the independent education sector, is based
on the availability of online learning training [7]; the ease of access of the independent education
sector’s eLearning opportunities; wide and sufficient access to data; and smart-technology in
education. The South African independent education sector tends to have better access to, and
availability of, eResources (fundamental contributors to eLearning such as technology, access to
data and educator training) therefore having a beneficial impact on the self-efficacy of educators. It
is important to note that educators within the disadvantaged areas, inner cities and rural communities
will certainly have a different experience of eLearning and may thus present with a different sense
of self-efficacy than measured in this investigation.
Educators’ experiences of anxiety during this time, as indicated by existing research, shows
that teacher stress and anxiety are augmented by a sense of uncertainty and not having a sense of
consistency within the work environment [27]–[29]. The findings indicated that 55% of educators
reported a sense of moderate anxiety, 35% reported normal (situational) anxiety and 10% reported
severe or chronic anxiety, suggesting that educators had relatively lower values of anxiety during the
pandemic period. This could be based on a number of external factors including coping
mechanisms, access to resources, supportive home environments, external support from friends or
health professionals or appropriate self-care routines.
Furthermore, gender-based data of our research shows no differences despite specific
association between emotion regulation and trait anxiety in genders [30]. Research has indicated that
there are distinct gender differences in how emotions impact educator decision-making [31],
suggesting that women were more likely to suffer from significant anxiety or depression [20]. Yet
our research found that gender is not a significant factor in the levels of self-efficacy or anxiety of
educators during the pandemic. This result is also reflected in Atabek’s research [27], where it is
found that there is little to no difference between the genders when considering the mean level of
stress experienced by teachers. However, it must be highlighted that the investigation indicates that
female teachers are more anxious about using educational technology.
The South African Government’s restriction on movement during the 2020 pandemic, which
included a variety of other social restrictions, as well as resulting in school closures and a shift to
online learning, was expected to significantly impact educators during this time. Albeit our research
shows that moderate anxiety was experienced during this time that data also indicates that there is
no relationship between self-efficacy and anxiety levels experienced by educators. This is in
contradiction with similar research into the use of technology in education during times of

conventional in-class teaching and learning, insofar, as [28] suggests that the integration of
technology into teaching and learning practices may result in unpleasant affective states including
“frustration, confusion, anger, anxiety, and similar emotional states” [28].
Even more significantly is that educators with background health problems (in South Africa
referred to as comorbidity) had significantly higher self-efficacy levels compared to those with no
health problems or co-morbidities. When considering peer reviewed investigations, such elevated
self-efficacy is non-consistent [1]. In order to understand this inconsistency, it is important to
appreciate the magnitude, as well as the strength dimensions when evaluating self-efficacy as well
as the findings of this investigation. The construct of self-efficacy is specific to the context or
situation of an individual and emphasises the differentiating between competency and the ability to
perform actions [28]. A possible reason for higher self-efficacy in terms of both dimension and
magnitude among educators with a history of health concerns is the coping mechanism already put
in place to deal with existing health concerns. While most educators returned to work in South
Africa’s Lockdown Level 3, educators with existing health concerns only returned during Level 1
restrictions. This may be an indicator that these educators were motivated to be creative by finding
new ways to teach as well as making use of innovative ways of communicating with learners in
order to protect their own exposure to the Covid-19 virus. Such innovative method to assure
continued teaching and learning included the distribution of worksheets through the ubiquity of
communication platforms such as WhatsApp, Google Classroom and Zoom [32] . These factors may
have also attributed to increased self-efficacy in educators with background health problems.
However, educators with existing health concerns indicated significantly higher anxiety
levels compared to those with no health problems. Research confirms a significant prevalence of
anxiety and depression among individuals with a poor health status [1], [20]. The seemingly
contradictory status of higher self-efficacy and higher anxiety, among those with a history of health
problems, warrants further investigation into how the concerns of contracting COVID-19 These
educators also may have experienced the need to provide continued teaching and learning as a
motivating factor, rather than feelings of low self-efficacy or depression. Thus, to understand the
resilience of educator efficacy and resilience during universal pandemics, one needs to develop a
deeper understanding of the phenomenon of universal educator efficacy.
Conclusions
Education during times of disruption often have a positive impact on the enhancement of
technology and the implementation of technology to enhance learning. However, often the human
impact of abrupt technologically driven change, specifically among educators with less
technological proficiency and professional development and training creates a sense of anxiety and
deficit of proficiency and self-efficacy may prevail [4]. Conversely, in satiations where a personal
sense of health and safety is associated with a sense of health, we may suggest that educators
understand that their purpose as educators, as well as their drive for self-preservation contributes to
a drive of self-efficacy.
This study suggests that the disruption during the COVID-19 pandemic resulted in educators
from schools in the independent education sector in South Africa reported to having high self-
efficacy and relatively lower values of anxiety, although, no relationship was found between the
two. Even though educators had very little time to prepare for online teaching and learning with
minimal training or guidelines on how to adapt to virtual teaching and learning practices, they
appeared to cope with their anxiety under the difficult circumstances. This is augmented by the
increased availability of eLearning resources to those with the financial means to access the
fundamental tools for eLearning. Despite previous research, gender was not found as a significant
factor in self-efficacy or anxiety levels, although, educators with underlying health problems or co-

morbidities appeared to have significantly high self-efficacy and anxiety compared to their
counterparts. Our hope is that this study will provide policymakers, education personnel and
economic leaders with the tools to not only prepare for the resultant future of the COVID-19
disruption in education, but also provide a deeper understanding of the emotional impact. There is a
need for further research into the resilience of educators during universal pandemics and access to
learning to develop an understanding of the phenomenon of educator efficacy.
With more than one “wave” of infections expected, additional governmental interventions
can be expected during the continuous global prevalence of the Covid-19 [33]. Therefore, it is we
expected that lock-down policies and practices, that have an impact on education, will not only
again disrupt traditional teaching methods, but also have a deleterious impact on the health, social
and emotional well-being of learners who are dependent on the school for food, as well as social
support[34]. We suggest that educational administrators and principals consider pre-disruptive-event
critical consideration, planning, preparation and professional development and training opportunities
forms an encapsulating segment of the policies, and standard operating procedures (SOP) of all
schools in anticipation of the world of change we live in. Furthermore, we suggest that investigation
into the phenomenological nature of resilience during educational disruption may provide
policymaker and principals with a deeper understanding into the self-efficacy and professional
development needs of educators.

References
[1] C. Kariuki-Nyuthe and D. J. Stein, “Anxiety and related disorders and physical illness,” Key
Issues Ment. Heal., vol. 179, pp. 81–87, 2015, doi: 10.1159/000365538.
[2] A. Bandura, Self-efficacy: The exercise of control. New York, NY, US: W H
Freeman/Times Books/ Henry Holt & Co, 1997.
[3] A. Bandura, “Self-efficacy: Toward a unifying theory of behavioral change,” Adv. Behav.
Res. Ther., vol. 1, no. 4, pp. 139–161, 1978, doi: 10.1016/0146-6402(78)90002-4.
[4] C. B. Hodges, “Self-efficacy in the context of online learning environments: A review of the
literature and directions for research,” Perform. Improv. Q., vol. 20, no. 3–4, pp. 7–25, 2008,
doi: 10.1002/piq.20001.
[5] E. Alqurashi, “Self-Efficacy In Online Learning,” Contemp. Issues Educ. Res., vol. 9, no. 1,
pp. 45–52, 2016.
[6] K. Jan, Shazia, “The Relationships Between Academic Self-Efficacy, Computer Self-
Efficacy, Prior Experience, and Satisfaction With Online Learning.,” Am. J. Distance Educ.,
vol. 29, no. 1, pp. 30–40, 2015, doi: 10.1080/08923647.2015.994366.
[7] C. M. Brown LA, Wiley JF, Wolitzky-Taylor K, Roy-Byrne P, Sherbourne C, Stein MB,
Sullivan G, Rose RD, Bystritsky A, “Changes in self-efficacy and outcome expectancy as
predictors of anxiety outcomes from the CALM study.,” Depress Anxiety., vol. 31, no. 8, pp.
678–89, 2014, doi: 10.1002/da.22256.
[8] E. M. Skaalvik and S. Skaalvik, “Teacher Stress and Teacher Self-Efficacy as Predictors of
Engagement, Emotional Exhaustion, and Motivation to Leave the Teaching Profession,”
Creat. Educ., vol. 07, no. 13, pp. 1785–1799, 2016, doi: 10.4236/ce.2016.713182.
[9] R. Castillo-Gualda, M. Herrero, R. Rodríguez-Carvajal, M. A. Brackett, and P. Fernández-
Berrocal, “The role of emotional regulation ability, personality, and burnout among spanish
teachers,” Int. J. Stress Manag., vol. 26, no. 2, pp. 146–158, 2019, doi: 10.1037/str0000098.
[10] C. J. McCarthy, “Teacher stress: Balancing demands and resourcesle,” Sage Journals, vol.
101, no. 3, pp. 8–14, 2019.
[11] C. L. Van Tonder and C. Williams, “Exploring the origins of burnout among secondary
educators,” SA J. Ind. Psychol., vol. 35, no. 1, pp. 204–218, 2009, doi:
10.4102/sajip.v35i1.762.
[12] C. L. Eddy, K. C. Herman, and W. M. Reinke, “Single-item teacher stress and coping
measures: Concurrent and predictive validity and sensitivity to change,” J. Sch. Psychol., vol.
76, pp. 17–32, 2019.
[13] H. Figueiredo-Ferraz, E. Grau-Alberola, P. Gil-Monte, and J. García-Juesas, “Burnout and
job satisfaction among nursing professionals,” Psicothema, vol. 24, pp. 271–276, 2012.
[14] R. Bianchi, I. Schonfeld, and E. Laurent, “Burnout-depression overlap: a review,” Clin.
Psychol. Rev., vol. 36, pp. 28–41, 2015.
[15] W. M. Parray, S. Kumar, and P. Awasthi, “Stress among Teachers : A Theoretical
Examination,” Int. J. Indian Psychol., vol. 3, no. 4 No. 57, pp. 1–10, 2016.
[16] P. D. MacIntyre, T. Gregersen, and S. Mercer, “Language teachers’ coping strategies during
the Covid-19 conversion to online teaching: Correlations with stress, wellbeing and negative
emotions,” System, vol. 94, p. 102352, 2020, doi: 10.1016/j.system.2020.102352.
[17] C. Maslach, “What have we learned about burnout and health?,” Psychol. Heal., vol. 16, no.
5, pp. 601–611, 2001.
[18] R. T. Miller, R. J. Murnane, and J. B. Willett, Do teacher absences impact student
achievement? Longitudinal evidence from one urban school district, vol. 30, no. 2. 2008.
[19] M. Manyane, “We’re scared of returning to class as we might get Covid-19, say teachers with
comorbidities,” IOL.co.za, JOhannesburg, Sep. 2020.
[20] G. Gudmundsson et al., “Depression, anxiety and health status after hospitalisation for
COPD: A multicentre study in the Nordic countries,” Respir. Med., vol. 100, no. 1, pp. 87–93,
2006, doi: 10.1016/j.rmed.2005.04.003.
[21] B. Macupe, “High-risk teachers vulnerable to Covid-19 now know how they will be treated,”
Mail&Guardian, Johannesburg, Jun. 2020.
[22] K. M. Scott et al., “Depression-anxiety relationships with chronic physical conditions:
Results from the World Mental Health surveys,” J. Affect. Disord., vol. 103, no. 1–3, pp.

113–120, 2007, doi: 10.1016/j.jad.2007.01.015.
[23] A. T. Beck, R. A. Steer, N. Epstein, and G. Brown, “Beck Self-Concept Test.,” Psychol.
Assess. A J. Consult. Clin. Psychol., vol. 2, no. 2, pp. 191–197, 1990, doi: 10.1037/1040-
3590.2.2.191.
[24] A. Bandura, “Guide for constructing self-efficacy scales,” Self-efficacy beliefs Adolesc., pp.
307–337, 2006, doi: 10.1017/CBO9781107415324.004.
[25] T. Fydrich, D. Dowdall, and D. L. Chambless, “Reliability and validity of the beck anxiety
inventory,” J. Anxiety Disord., vol. 6, no. 1, pp. 55–61, 1992, doi: 10.1016/0887-
6185(92)90026-4.
[26] R. . Beck, A.T., Epstein, N., Brown, G., Steer, “No Title,” J. Consult. Clin. Psychol., vol. 56,
no. 6, pp. 893–897, 1988, doi: https://psycnet.apa.org/doi/10.1037/0022-006X.56.6.893.
[27] O. Atabek, “Associations Between Emotional States, Self-Efficacy For and Attitude Towards
Using Educational Technology,” Int. J. Progress. Educ., vol. 16, no. 2, pp. 175–194, 2020,
doi: 10.29329/ijpe.2020.241.12.
[28] R. Saade and D. Kira, “Computer Anxiety in E-Learning: The Effect of Computer Self-
Efficacy,” Proc. 2009 InSITE Conf., vol. 8, 2009, doi: 10.28945/3386.
[29] V. L. Anderson, E. M. Levinson, W. Barker, and K. R. Kiewra, “The Effects of Meditation on
Teacher Perceived Occupational Stress, State and Trait Anxiety, and Burnout 1,” Sch.
Psychol. Q., vol. 14, no. 1, pp. 3–25, 1999, doi: 10.1037/h0088995.
[30] T. A. Dennis, “Interactions between emotion regulation strategies and affective style:
Implications for trait anxiety versus depressed mood,” Motiv. Emot., vol. 31, no. 3, pp. 200–
207, 2007, doi: 10.1007/s11031-007-9069-6.
[31] J. Mostert and O. Gulseven, “The Role of Gender and Education on Decision-Making,” Stud.
Bus. Econ., vol. 14, no. 3, pp. 117–130, Dec. 2019, doi: 10.2478/sbe-2019-0048.
[32] D. De Korte, “What South Africa’s teachers brought to the virtual classroom during COVID-
19,” eNCA, South Africa, 2020.
[33] O. Gulseven, F. Al Harmoodi, M. Al Falasi, and I. ALshomali, “How the COVID-19
Pandemic Will Affect the UN Sustainable Development Goals?,” SSRN Electron. J., 2020,
doi: 10.2139/ssrn.3592933.
[34] W. Van Lancker and Z. Parolin, “COVID-19, school closures, and child poverty: a social
crisis in the making,” Lancet Public Heal., vol. 5, no. 5, pp. e243–e244, May 2020, doi:
10.1016/S2468-2667(20)30084-0.
Osman Gulseven PhD, Middle East Technical University, Dept. of Economics, Turkey.
E-mail: gulseven@metu.edu.tr
Jacques Mosters PhD, Brand Academic Manager, Niche Brands, International Institute of
Education
E-mail: jmostert@advtech.co.za
Williams Courtney Grantley College, South Africa
E-mail: courtneyw@grantleycollege.co.za