Next Article in Journal
An Analysis of the Relationships between Social Capital Levels and Selected Green Economy Indicators on the Example of Polish Voivodeships
Next Article in Special Issue
The Effect of Cognitive Load on Learning Memory of Online Learning Accounting Students in the Philippines
Previous Article in Journal
Assessing the Sustainability of Transport Systems through Indexes: A State-of-the-Art Review
Previous Article in Special Issue
The Impact of the COVID-19 Pandemic on Financial Condition and Mortality in Polish Regions
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sustainability
Volume 16
Issue 4
10.3390/su16041456
sustainability-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Emotions of Educators Conducting Emergency Remote Teaching during COVID-19 Confinement

by
Eneko Tejada Garitano
*,
Javier Portillo Berasaluce
,
Arantzazu López de la Serna
and
Ander Arce Alonso
*
Department of Didactic and School Organisation, Bilbao Faculty of Education, University of the Basque Country, Sarriena S/N, 48940 Leioa, Spain
*
Authors to whom correspondence should be addressed.
Sustainability 2024, 16(4), 1456; https://doi.org/10.3390/su16041456
Submission received: 24 December 2023 / Revised: 3 February 2024 / Accepted: 5 February 2024 / Published: 8 February 2024
(This article belongs to the Special Issue The Impact of COVID-19 Pandemic on Sustainable Development Goals)
Browse Figure
Review Reports Versions Notes

Abstract

:
The home confinement of the population in Spain caused by the COVID-19 pandemic interrupted face-to-face teaching and led teachers of all educational levels to perform their activities remotely. This represented a radical change in daily tasks. The goal of this study is to analyse and understand the emotions teachers experienced while performing Emergency Remote Teaching during home confinement. We performed a descriptive quantitative analysis and a comparison of the means (ANOVA) related to the independent sociodemographic variables (age, gender, and educational stage). The study sample consisted of 4589 teachers from the Basque Country, and represents the largest study with these characteristics conducted in Spain. The results obtained in the research show that, despite suffering great stress, teachers also felt pride in the work they had done. The study concludes that the teachers in the group who suffered the most negative feelings were women, primary school teachers, and middle-aged educators.

1. Introduction

On 14 March 2020, the Government of Spain decreed ‘Alarm State’ [1] throughout its territory, limiting the free movement of the population and establishing mandatory home confinement. The health crisis triggered by the COVID-19 pandemic unexpectedly and urgently led to the entire academic population (i.e., teachers and students) to be confined at home [2].
In order to overcome this situation, the institutions and centres of all levels of education across the various autonomous communities of Spain decided to implement telematic teaching via the Internet [3]. This re-adaptation of the teaching–learning process to an alternative mode of teaching, in an unplanned way, led to the performance of Emergency Remote Teaching (ERT) [4]. This method has nothing to do with the different types and modalities of online training, which tend to have a careful instructional design and proven efficacy [5,6,7].
For a significant amount of time, the current ‘knowledge society’ [8] has allowed teachers to take advantage of technology and perform their educational activities virtually through different interactive and collaborative resources. The Internet allows searching, creating, or sharing educational content [9,10,11]. Thus, during home confinement, it allowed teachers and students to remain in contact. In addition, students could retrieve their learning material from educational platforms and Web 2.0 resources [12]. However, teachers have experienced difficulties and doubts when implementing digital educational resources in teaching–learning processes [13,14,15,16]. Not surprisingly, the training for teaching digital competence has been traditionally linked closely to aspects of a more technical and instrumental nature, and not so much to pedagogical and methodological development [17,18], which was what the situation demanded.
During ERT, a significant part of the educational community, and society in general, disregarded teachers’ conditions, difficulties, and their limitations to perform their educational activities whilst confined. All of the attention was focused on how the teachers taught curricular content, how they assessed the students [4] and the pressures that these activities might entail. Maintaining the demands imposed by teaching may have generated, beyond physical fatigue, emotional exhaustion [19,20].

2. Teachers’ Emotional Experiences

Given the scientific discussion on the conceptualisation of the meaning of emotions [21,22], in the present study we started from the idea coined by [23], based on the following conception: in teachers’ professional field, emotions are constituted of teachers’ emotional states, which are the responses they give to exceptional situations that involve synchronised patterns of experiences, assessments, physiological changes, and expressions and/or behaviour tendencies, whose interpretation depend on the socio-cultural meaning of the context in which they occur [24].
The interconnectedness between emotional well-being and labour performance is widely acknowledged in both scientific and institutional spheres, substantiated by their inclusion in the Sustainable Development Goals (SDGs), particularly the third objective: Health and Wellbeing [25]. Achieving a state of well-being encompassing physical, emotional, and mental health is indispensable for optimal performance in both personal and professional domains. This principle is universally applicable, irrespective of individual characteristics such as race, ethnicity, or gender, and extends to all roles and occupations.
In the realm of education, educators are expected to operate at their highest standards, a commitment underscored by the fourth SDG objective emphasizing Quality Education [25]. Despite the prevalence of negative emotions during the COVID era, teachers expressed satisfaction for their efforts, even amidst emotional and physical challenges [26]. Considering these factors, the fulfilment of teachers’ health and well-being becomes crucial for delivering the quality education necessary for societal development. Whereas these concerns held priority before COVID, the profound implications of the pandemic have underscored the heightened clarity of this imperative.
It is possible for confined teachers, depending on their experience in the development of their professional performance, to experience positive emotions such as pride, satisfaction, enthusiasm, confidence, and relief. Concomitantly, they may experience negative feelings such as insecurity, stress, concern, anger, and frustration [27,28,29].
The fact of unexpectedly having to perform ERT [4] and in an unplanned manner could have led teachers to greater psychological stress and, consequently, influenced their emotional states [30,31]. The forced inclusion of technology as a resource for teaching can cause burnout syndrome in some teachers [32], which is characterised by physical fatigue, loss of motivation, and emotional exhaustion [33,34]. Moreover, this can become exacerbated in a scenario of uncertainty, fear, and insecurity, such as the one which occurred during confinement. However, when teachers perform adequately using technological instruments in education, they tend to value their emotions in a more satisfactory way, and vice versa [35,36].
The COVID-19 pandemic significantly influenced the mental health of those individuals who were overwhelmed by the stressors to which they were exposed [37]. As some studies point out, organisational changes influence the emotional state of teachers [38,39,40,41] and affect some aspects of their professional performance, such as the academic results of students and the quality of the relationships they establish with them [42,43,44]. In this respect, the resistance that some teachers may experience, when they have to change [45] to ERT, can also contribute to their perception of negative emotions.
From the teachers’ perspective, the implications of COVID-19 in education are still scarce. Most of the studies conducted have addressed this topic from the students’ perspective [46,47]. Despite the fact that different authors [48,49,50] emphasise the influence of emotions on learning and technology-mediated teaching, the studies have been mainly limited to analysing the feelings of students in the educational field, the emotions of students related to the teaching-learning process, and how they feel when they are assessed [51,52,53,54].
The analysis of the emotional experience of the confined teachers performing their educational activities through ERT allows us to know their emotional responses, and identify whether negative or positive emotions prevail [53].
Therefore, the interest of the present study is based on knowing the affective states of the teaching staff in terms of emotional experience linked to ERT, within the home confinement context. Moreover, this study also contributes to visualising the efforts made by teaching staff during home confinement while performing telematic teaching.

3. Objectives and Hypotheses

The main goal of the present study is to analyse the emotional response of teachers during home confinement caused by the COVID-19 pandemic in the Basque Country, Spain. To that end, the following research hypotheses (H) was proposed:
H1. 
Teachers consider negative emotions more than positive ones.
As a secondary objective, we want to know the characteristics of the teachers that exhibited the most negative emotional response. The independent variables in the analysis allow for segmenting the population into more homogeneous groups, thus enabling a more detailed and specific study. In this way, gender was analysed under the criteria of equity and social justice. The age of teachers was examined considering generational contexts, and the level at which they teach was explored due to the diversity in pedagogical practices. In this regard, the following research hypotheses (H) were proposed:
H2. 
There are no significant differences in negative emotional responses between men and women.
H3. 
There are significant differences in negative emotional responses depending on age.
H4. 
There are significant differences in negative emotional responses depending on the educational level in which the teachers perform.
In the comparison of variables, a null hypothesis (H0) is presented, which refers to the non-existence of significant differences (0.5% significance level or lower); whereas the alternative hypothesis (H1) refers to the existence of significant differences at the aforementioned significance level. In this way, if H0 was rejected, Cohen’s g would be applied to determine the effect size of such differences [55,56].

4. Method

4.1. Sample

A non-random and non-probabilistic convenience sampling was performed to conduct the present study. We sent a questionnaire to all the teachers that were performing in research fields. The universe of our study was the teaching staff of the Basque Country, Spain (N = 42,772), of which 36,934 were non-university teachers, and 5838 were from the university. With an error of ± 4%, a confidence interval of 99%, and p = q = 0.5, the sample size estimated was 1008 teachers [57,58]. Finally, the sample was composed of 4589 teachers who answered the questionnaire satisfactorily, of which 23.3% were men, 75.5% women, and 0.8% non-binary, with a mean age of 37 years (SD = 6.24).
The surveyed individuals worked professionally as teachers in the following fields: early childhood education stages (10.8); primary education (31.6%); compulsory secondary education (38.3%); vocational training (5.3%); higher education (8.6%); state-owned education and training centres (77.2%); subsidised centres (20.6%); and private centres (2.2%).

4.2. Instrument

The emotional responses of teachers who were performing ERT were measured using a scale composed of ten items. Half measured positive emotions (pride, satisfaction, confidence, enthusiasm, and security) and the other half measured negative emotions (insecurity, stress, concerns, anger, and frustration) [27].
The instrument used was generated by adapting the questionnaire for virtual learning environments (WebCT) proposed by [59], which features an internal consistency of 0.845 according to the Cronbach’s alpha reliability coefficient. In this respect, in order to achieve the objectives proposed in the present study, the scale was adapted to the situation produced by the COVID-19 pandemic.
In order to assess the aspects addressed in each item (IT), we used a Likert-type scale, with response options from 1 (little) to 5 (much). Similarly, the surveyed teachers valued the following items relating to how they felt emotionally during COVID-19 in their professional performance as teachers. On the one hand, the that items related to positive emotions were: (IT1) I am proud of the work done during the confinement; (IT2) I am satisfied with the work performed during the confinement; (IT3) I am confident that my work is adequate; (IT4) I feel encouraged when I finish my work activity; and (IT5) I feel safe when I work in confinement. On the other hand, the items related to negative emotions were: (IT6) I feel stress while teaching; (IT7) My work worries me during confinement; (IT8) I feel irritated doing my job in this situation; (IT9) Working in this situation makes me feel frustrated; and (IT10) Working in this confined situation causes me general stress.
To obtain the sociodemographic data of the teaching staff, an ad hoc tool was created taking into account the defining variables of the profession, such as age, gender, educational stage in which they were working, and profile of the centres in which they worked. The assessment of the validity of the instrument adapted and used to analyse how confined teachers performing ERT felt emotionally was carried out by calculating the factor load of the questionnaire, and through a confirmatory factor analysis [60]. The other tests, which determined the psychometric properties of the questionnaire used, are specified in the results section.

4.3. Process

The distribution of the questionnaire among teachers of different educational levels was carried out by means of bulk sending to their institutional email accounts, which belong to the educational centres of the entire Basque Country. The snowball or recruitment network technique was used through successive steps [61,62], making use of social networks (Facebook, Twitter, and Instagram) and other educational networks articulated through WhatsApp groups. Data collection was performed over three weeks.
We performed a descriptive quantitative analysis and a comparison of means (ANOVA) of the independent variables (age, gender, educational stage) relating to the research topic, i.e., the emotional response of the teaching staff that was performing ERT. The data were exported and adapted to the Statistical Package for the Social Sciences (SPSS) version 24 software to perform the statistical analysis.

4.4. Data Analysis

First, we assessed the psychometric properties of the Workload and Effort Questionnaire. The validity and reliability of the questionnaire was ensured with the methods most used by social researchers [58,63]: Cronbach’s alpha reliability analysis of positive (α = 0.804) and negative emotions (α = 0.868); Cronbach’s alpha if one item is removed, for each item (see Table 1); KMO test (0.835); and Bartlett’s test of factor analysis (p = 0.000), test of the two halves.
The sample was randomly divided into two halves. A parallel analysis was performed with the first subsample (n = 2296) to assess the factorial structure of the instrument. In this case, we used the Factor 10.4.01 software [64]. The procedure selected for determining the number of dimensions was the optimal implementation of the parallel analysis [65]. The parameter estimation method was the diagonal weighted least squares (DWLS), given that it is the best method when the variables analysed are ordinal, as in the case of Likert-type scales [66]. Finally, the rotation method used to find the factorial solution was Direct Oblimin, since the factors were expected to correlate significantly with each other. In this respect, the results of this first analysis suggested a bi-factorial structure, so that the items related to positive emotions were saturated within one factor, and the items related to negative emotions were saturated within another factor.
Based on these first exploratory results, a confirmatory factor analysis was performed with the second subsample (n = 2294). This analysis was carried out using the Lisrel 8.80 software [67] using the DWLS parameter estimation method. Fit quality was assessed using the following goodness-of-fit indices: Root Mean Square Error of Approximation (RMSEA) fit index, whose value should be less than 0.08 [68]; and the Non-Normed Fit Index (NNFI), Comparative Fit Index (CFI), and Goodness-of-Fit Index (GFI), whose values should be greater than 0.90 [69]. The results of this analysis indicated that the two-factor model was a poor fit to the data (RMSEA = 0.13; NNFI = 0.91; CFI = 0.93; GFI = 0.97). Consequently, the adjustment of the bi-factorial model was assessed in two dimensions so the two initial factors (i.e., positive emotions and negative emotions) were maintained, in addition to a third factor common to all items, which was representative of the construct ‘emotions’. In this case, the model achieved a satisfactory fit according to the assessed indices (RMSEA = 0.81; NNFI = 0.97; CFI = 0.98; GFI = 0.99). The results are illustrated in Figure 1. As can be seen in the case of factor 1 (Positive emotions, α = 0.80), the factorial weights with the primary factor ranged between 0.43 (item 5) and 0.83 (item 1); whereas in the case of factor 2 (Negative emotions, α = 0.87), the weights ranged between 0.31 (item 9) and 0.93 (item 6). Regarding the second-order factor, the weights (in absolute terms) ranged between 0.14 and 0.91.

5. Results

5.1. Positive and Negative Emotions

Next, we assessed the descriptive statistics of the items, along with the factors whose results are illustrated in Table 1. The data obtained indicate that the teachers scored more the negative emotions (19.4) than the positive ones (18.32). In this respect, it is possible to accept the first research hypothesis, which states that teachers value the negative emotions more than the positive emotions.
The most highly rated negative emotional response was general stress from working in confinement (4.14), followed by stress in the provision of teaching (4.12), and concern about teacher performance (M = 4). However, it is noted that teachers were proud of the work they did (M = 4.14) while performing emergency remote teaching.
The differences in a series of sociodemographic variables in the two resulting factors were also examined. Specifically, the differences analysed were related to gender, age, and educational level to which teaching was provided. The analyses were carried out by means of ANOVA. Both statistical significance and effect size (η2) were calculated, which was interpreted as follows: values between 0.01 and 0.04 were considered small; between 0.04 and 0.14 medium; and above 0.14, large [70].

5.2. Gender

Concerning the gender, it is observed that women felt more stress, worry, and frustration than men while performing their work, as shown in Table 2. The results indicated a significant and small effect for positive emotions (F [2, 4589] = 6.18, p = 0.002, η2 = 0.01) with men (M = 18.55) scoring above women (M = 18.26). However, in negative emotions (F [2, 4589] = 48.59, p < 0.61001, η2 = 0.16), women (M = 19.74) scored higher than men (M = 18.24) and this is statistically significant. Regarding total emotions (F [2, 4589] = 32.33, p < 0.001, η2 = 0.09) women (M = 1.48) also scored above men (M = −0.31). In this way, with respect to the second research hypothesis, the values obtained allowed rejecting the H0 and accepting the alternative hypothesis related to negative emotional responses, since there were significant differences between men and women.

5.3. Age

Regarding the age, the study of the data shows that middle-aged teachers (36–40 years) were the most stressed (M = 4.22). These teachers felt that working in the confined situation caused them general stress (M = 4.25) and their level of irritability was higher than any other age group (M = 3.51).
In the means comparison analysis, we did not find any significant effect on positive emotions (F [7, 4589] = 1.84, p = 0.075). On the contrary, there was a significant effect on negative emotions (F [2, 4589] = 4.34, p < 0.001, η2 = 0.17), and on the total emotions (F [2, 4589] = 2.77, p = 0.007, η2 = 0.14).
Hochberg’s post hoc test of WG2 reveals significant differences between middle-aged and younger teachers, as seen in Table 3. Thus, the stress in teacher performance (M = 3.87, ng 0.18), the stressful feeling of being confined (M = 3.91, ng 0.045), and the perception of irritability (M = 3.20, ng 0.001) had less incidence among younger teachers.
Regarding the feeling of frustration, middle-aged teachers (36–40 years) also rated the higher (M = 3.88). However, in contrast to the previous emotional states, older teachers (61–70 years; M = 3.44) were significantly less frustrated, as can be seen from Table 3. Despite this, older teachers showed the greatest concern for the work done during confinement (56–60 years; M = 4.12). These data allow us to assume the third alternative hypothesis, which referred to the fact that there might be significant differences in negative emotional responses depending on age.

5.4. Educational Levels

With respect to the educational levels to which teaching was provided, a significant effect of small magnitude was observed in the three variables analysed, namely: positive emotions (F [6, 4560] = 6.19, p < 0.001, η2 = 0.01); negative emotions (F [2, 4589] = 13.39, p < 0.001, η2 = 0.02); and total emotions (F [2, 4589] = 15.75, p < 0.001, η2 = 0.02). The Hochberg’s GT2 post hoc test revealed that, in general terms, primary school teachers (M = 17.98) scored lower in positive emotions than secondary school teachers (M = 18.73) and university teachers (M = 18.98). In the case of negative emotions, primary school teachers (M = 20.25) scored significantly higher than the rest of the educational levels: childhood education (M = 19.08); compulsory secondary education (M = 19.24); baccalaureate (M = 18.83); university (M = 18.72); and vocational training (M = 18.09).
Finally, regarding total emotions, primary education teachers (M = 2.27) also scored higher than teachers of the remaining educational levels: childhood (M = 0.52); compulsory secondary education (M = 1.07); baccalaureate (M = 0.10); university (M = −0.26); and vocational training (M = −0.70). These results allowed us to accept the alternative hypothesis, which stated that there would be significant differences in negative emotional responses depending on the educational level in which the teachers performed.

6. Discussion

The present research has facilitated the understanding of the emotional response of teachers in the Basque Country while performing Emergency Remote Teaching, which was caused by the COVID-19 pandemic. It represents the largest study carried out on teachers in confinement in Spain.
The results obtained in this research show that the teachers had more negative than positive emotions during the abovementioned confinement period. Teachers were basically under great stress while teaching and were concerned about student learning during confinement. It is worth mentioning that different studies have argued that the design of the physical work environment, as well as the scarcity of resources—in this case, teachers’ homes—can enhance that stress [71,72]. Similarly, paradoxically, the study also evidences that the teachers felt pride and satisfaction with the work carried out.
Identification of teachers with more negative emotional responses regarding ERT performed during confinement was also possible. In this regard, it was observed that women had significantly more negative emotions than men, which is consistent with results obtained by other studies [73,74], according to which women tend to have higher rates of fatigue and emotional exhaustion than men. It is worth noting that women suffer greater vulnerability to social stress, because they develop professionally and, at the same time, they are involved in raising or caring for the family to a greater extent than men [75,76]. It is possible that this aspect has increased during the confinement resulting from the health alarm caused by the COVID-19 pandemic. In addition, intra-work conditions—like extra-work conditions—promotes the emergence of stress when, for example, responsibility or excessive work increases [77], as happened during confinement with ERT.
Moreover, women may have experienced more negative than positive feelings due to the fact that they tend to report their emotional states more than men [78]. Similarly, it should be taken into account that women manifest coping strategies based on inter-social competencies [79,80,81] and on the search for social support to overcome stressful situations [82]. It is likely, during confinement, they encountered limitations in supporting their colleagues and being supported themselves.
Furthermore, the study reveals that the age of the teachers had a significant impact on the perception of negative emotions. Specifically, teachers between the ages of thirty and thirty-five suffered the most frustration, irritation, and stress while teaching during confinement. It can be assumed that they found more difficulties to reconcile family care and work activities during confinement. Not surprisingly, this age range is the most common in Spain for having children for the first time, and those activities related to raising children are more demanding at this stage [83].
The youngest teachers (under 30 years of age) had, in general, the least negative feelings; on the contrary, the older ones showed more concern about their teaching performance. The explanation for this issue can be found in the fact that younger teachers have a higher digital competence [16,84] and remote teaching requires of such skills.
Regarding the educational level in which teachers performed, primary education teachers perceived a more negative emotional state than the rest. Similarly, it is necessary to underline that studies addressing teachers who perform in early childhood education is still very scarce [85,86]. In addition, with regards to negative emotions, from the perspective of the type of educational centre, the assessment of teachers were practically the same, so no differences were found.

7. Conclusions

Research on Basque Country teachers who participated in Emergency Remote Teaching (ERT) during the COVID-19 pandemic reveals a predominantly negative emotional response. Levels of worry and stress during the confinement period were high. Despite this, they also expressed pride and satisfaction in the work they performed under these special circumstances.
The study also concluded that women expressed more negative emotions than men because they tend to have more work and family responsibilities, and this situation was aggravated in confinement. Age was another factor that influenced the emotional experiences of the teachers. Those between the ages of thirty and thirty-five suffered the most frustration and stress since they have to reconcile family care and work in addition to facing the situation of confinement. Younger teachers, being more digitally competent, are more adaptable to remote teaching environments, and therefore were likely to have fewer negative feelings and stress than their older peers. This study sheds light on teachers’ emotional responses during emergency remote teaching, providing valuable insights for future educational strategies and development of teachers’ digital competence.
The COVID-19 pandemic presented an unprecedented global challenge, compelling nations and institutions to make decisions that had not been made before, including the imposition of widespread lockdowns. Consequently, a significant shift towards remote work occurred, and even after the lifting of lockdowns, remote work persisted. This transformation has ignited a societal debate on the possibility and efficacy of delivering certain services, traditionally administered by public institutions, through in-person, remote, or hybrid modalities.
In the realm of education, the conducted study highlights that online teaching is not accessible to everyone and remote teaching cannot be successfully implemented in all knowledge areas, educational levels, etc., without negatively affecting the emotions of educators.
Moreover, our research brings to light that women, teachers aged 30 to 35, and those in primary education are particularly vulnerable demographics, experiencing heightened negative emotions in this context. In anticipation of similar situations in the future, it is recommended that administrations and educational institutions formulate action protocols or best practices, with a primary focus on enhancing teacher training in e-teaching and digital teaching competences. Such initiatives are poised to alleviate the negative emotional experiences of educators.
Recognizing that emotional, physical, and mental well-being is intrinsic to optimal professional performance, it is imperative to acknowledge that without adequate training, educators may struggle to adapt to unforeseeable future scenarios, including health emergencies and technological advancements. The holistic care of educators significantly contributes to societies attaining the educational standards they aspire to provide for their citizens.

Author Contributions

Conceptualization, A.L.d.l.S.; Writing—original draft, E.T.G.; Writing—review & editing, J.P.B. and A.A.A. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the University of the Basque Country, grant number GIU 19/010, PPGI19/11 and by the Basque Government, grant number IT1195-19.

Institutional Review Board Statement

The study was approved by the Weblearner Research Group, an established research group identified as IT1686-22 and IT929-16 and supervised by the University of the Basque Country.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data from this research is not publicly available but may be available upon reasonable request to corresponding author.

Acknowledgments

We would like to thank all the teachers who participated in this research during the pandemic and the confinement of COVID-19 and those who contributed to its development.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

References

  1. Real Decreto 476/2020, de 27 de Marzo, por el que se Prorroga el Estado de Alarma Declarado por el Real Decreto 463/2020, de 14 de marzo, por el Quese Declara el Estado de Alarma para la Gestión de la Situación de Crisis Sanitaria Ocasionada por el COVID-19, BOE núm. 86. Available online: https://www.boe.es/boe/dias/2020/03/28/pdfs/BOE-A-2020-4155.pdf (accessed on 23 December 2023).
  2. UNESCO. Adverse Consequences of School Closures. UNESCO´s COVID-19 Education Response. 2020. Available online: https://es.unesco.org/node/320395 (accessed on 23 December 2023).
  3. Moorhouse, B.L. Adaptations to a face-to-face initial teacher education course ‘forced’ online due to the COVID-19 pandemic. J. Educ. Teach. 2020, 46, 609–611. [Google Scholar] [CrossRef]
  4. Hodges, C.; Moore, S.; Lockee, B.; Trust, T.; Bond, A. The difference between emergency remote teaching and online learning. In Educause Review; Educause: Denver, CO, USA, 2020; Available online: https://er.educause.edu/articles/2020/3/the-difference-between-emergency-remote-teaching-and-online-learning (accessed on 23 December 2023).
  5. Czerkawski, B.C.; Lyman, E.W. An Instructional Design Framework for Fostering Student Engagement in Online Learning Environments. TechTrends 2016, 60, 532–539. [Google Scholar] [CrossRef]
  6. Johnson, R.D.; Hornik, S.; Salas, E. An empirical examination of factors contributing to the creation of successful e-learning environments. Int. J. Human-Comput. Stud. 2008, 66, 356–369. [Google Scholar] [CrossRef]
  7. Noesgaard, S.S.; Ørngreen, R. The effectiveness of e-learning: An explorative and integrative review of the definitions, methodologies and factors that promote e-learning effectiveness. Electron. J. e-Learn. 2015, 13, 278–290. [Google Scholar]
  8. Mansell, R.; Tremblay, G. Renewing the Knowledge Societies Vision: Towards Knowledge Societies for Peace and Sustainable Development. In Proceedings of the UNESCO’s First WSIS+10 Review Event, Paris, France, 25–27 February 2013; Available online: http://unesdoc.unesco.org/images/0022/002245/224531E.pdf (accessed on 23 December 2023).
  9. European Commission. Digitally Competent Educational Organisations. DigCompOrg. 2016. Available online: https://ec.europa.eu/jrc/en/digcomporg (accessed on 23 December 2023).
  10. Consejo de la Unión Europea. Recomendación del Consejo, de 18 de Diciembre de 2018, Relativa a las Competencias Clave para el Aprendizaje Permanente; Diario Oficial de la Unión Europea: Luxembourg, 2018. [Google Scholar]
  11. INTEF. Portafolio de la Competencia Digital Docente. Recuperadode. 2018. Available online: http://enlinea.intef.es/courses/course-v1:SPOOC (accessed on 23 December 2023).
  12. Adedoyin, O.B.; Soykan, E. COVID-19 pandemic and online learning: The challenges and opportunities. Interact. Learn. Environ. 2020, 31, 863–875. [Google Scholar] [CrossRef]
  13. Guillén-Gámez, F.D.; Lugones, A.; Mayorga-Fernández, M.J. ICT use by pre-service foreign languages teachers according to gender, age and motivation. Cogent Educ. 2019, 6, 1574693. [Google Scholar] [CrossRef]
  14. Pinto-Llorente, A.M.; Sánchez-Gómez, M.C.; García-Peñalvo, F.J.; Casillas-Martín, S. Students’ perceptions and attitudes towards asynchronous technological tools in blended-learning training to improve grammatical competence in English as a second language. Comput. Hum. Behav. 2017, 72, 632–643. [Google Scholar] [CrossRef]
  15. Sadaf, A.; Newby, T.J.; Ertmer, P.A. An investigation of the factors that influence preservice teachers’ intentions and integration of Web 2.0 tools. Educ. Technol. Res. Dev. 2016, 64, 37–64. [Google Scholar] [CrossRef]
  16. Scherer, R.; Siddiq, F.; Teo, T. Becoming more specific: Measuring and modeling teachers’ perceived usefulness of ICT in the context of teaching and learning. Comput. Educ. 2015, 88, 202–214. [Google Scholar] [CrossRef]
  17. Loveless, A. Technology, pedagogy and education: Reflections on the accomplishment of what teachers know, do and believe in a digital age. Technol. Pedagog. Educ. 2011, 20, 301–316. [Google Scholar] [CrossRef]
  18. Almenara, J.C.; Gimeno, A.M. Las tecnologías de la información y comunicación y la formación inicial de los docentes. Modelos y competencias digitales. Profr. Rev. Curric. Form. Profr. 2019, 23, 247–268. [Google Scholar] [CrossRef]
  19. Chang, M.-L. Emotion Display Rules, Emotion Regulation, and Teacher Burnout. Front. Educ. 2020, 5, 90. [Google Scholar] [CrossRef]
  20. Skaalvik, E.M.; Skaalvik, S. Does school context matter? Relations with teacher burnout and job satisfaction. Teach. Teach. Educ. 2009, 25, 518–524. [Google Scholar] [CrossRef]
  21. Alvandi, E.O. A review on meanings of emotions: Steps to a neural-informational notion of semantics. Cogn. Brain Behav. 2016, 20, 45–63. Available online: https://ehu.idm.oclc.org/login?url=https://www.proquest.com/docview/1776352167?accountid=17248 (accessed on 23 December 2023).
  22. Oatley, K. Emotion: Theories. In Encyclopedia of Psychology; Kazdin, A.E., Ed.; Oxford University Press: Oxford, UK, 2000; pp. 167–171. Volume 3. [Google Scholar]
  23. Niedenthal, P.; Krauth-Gruber, S.; Ric, R. Psychology of Emotion; Psychology Press: London, UK, 2006. [Google Scholar]
  24. Ekman, P. Basic emotions. In Handbook of Cognition and Emotion; Dalgleish, T., Power, M., Eds.; Wiley: Hoboken, NJ, USA, 1999; pp. 45–60. [Google Scholar]
  25. United Nations. The Sustainable Development Goals Report 2023: Special Edition. 2023. Available online: https://unstats.un.org/sdgs/report/2023/ (accessed on 23 December 2023).
  26. Chan, M.-K.; Sharkey, J.D.; Lawrie, S.I.; Arch, D.A.N.; Nylund-Gibson, K. Elementary school teacher well-being and supportive measures amid COVID-19: An exploratory study. Sch. Psychol. 2021, 36, 533–545. [Google Scholar] [CrossRef] [PubMed]
  27. Gondim, S.M.G.; Mutti, C. Affections in learning situations: A study of an entrepreneurship skills development course. J. Work. Learn. 2010, 23, 195–208. [Google Scholar] [CrossRef]
  28. Rajkumar, R.P. COVID-19 and mental health: A review of the existing literature. Asian J. Psychiatry 2020, 52, 102066. [Google Scholar] [CrossRef] [PubMed]
  29. Segura, M.; Arcas, M. Relacionarnos bien. Programas de Competencia Social; Narcea: Madrid, Spain, 2007. [Google Scholar]
  30. Bakker, A.B.; Demerouti, E. The job demands-resources model: State of the art. J. Manag. Psychol. 2007, 22, 309–328. [Google Scholar] [CrossRef]
  31. Mansfield, C.F.; Beltman, S.; Price, A.; McConney, A. “Don’t sweat the small stuff”: Understanding teacher resilience at the chalkface. Teach. Teach. Educ. 2012, 28, 357–367. [Google Scholar] [CrossRef]
  32. Uluyol, C.; Sahin, S.C.; Uluyol, S. Sahin Elementary School Teachers’ ICT Use in the Classroom and Their Motivators for Using ICT. Br. J. Educ. Technol. 2016, 27, 66–75. [Google Scholar] [CrossRef]
  33. Freudenberger, H.J. Staff Burn-Out. J. Soc. Issues 1974, 30, 159–165. [Google Scholar] [CrossRef]
  34. Kim, L.E.; Jörg, V.; Klassen, R.M. A Meta-Analysis of the Effects of Teacher Personality on Teacher Effectiveness and Burnout. Educ. Psychol. Rev. 2019, 31, 163–195. [Google Scholar] [CrossRef] [PubMed]
  35. Valverde, J.; Fernández, M.R.; Revuelta, F.I. El bienestar subjetivo ante las buenas prácticas educativas con TIC: Su influencia en profesorado innovador. Educación XX1 2013, 16, 255–280. [Google Scholar] [CrossRef]
  36. Chigona, A.; Chigona, W.; Davids, Z. Educators’ Motivation on Integration of ICTs into Pedagogy: A Case of Disadvantaged Areas. South Afr. J. Educ. 2014, 34, 1–8. [Google Scholar] [CrossRef]
  37. Besser, A.; Lotem, S.; Zeigler-Hill, V. Psychological stress and vocal symptoms among university professors in israel: Implications of the shift to online synchronous teaching during the COVID-19 Pandemic. J. Voice 2020, 36, 291.e9–291.e16. [Google Scholar] [CrossRef] [PubMed]
  38. Cornejo, R.; Quiñónez, M. Factores asociados al malestar/bienestar docente. Una investigación actual. REICE Rev. Electrónica Iberoam. Sobre Calid. Efic. Cambio En Educ. 2007, 5, 75–80. [Google Scholar]
  39. Marqués, A.; Lima, M.L.; Lopes, A. Fuentes de estrés, burnout y estrategias de coping en profesores portugueses. Rev. Psicol. Trab. Organ. 2005, 21, 123–143. [Google Scholar]
  40. Molina-Jiménez, T.; Gutiérrez-García, A.G.; Hernández-Domínguez, L.; MContreras, C. Psychosocial stress: Some clinical and experimental aspects. An. Psicol./Ann. Psychol. 2008, 24, 353–360. Available online: https://revistas.um.es/analesps/article/view/42951 (accessed on 23 December 2023).
  41. Richards, K.A.R.; Hemphill, M.A.; Templin, T.J. Personal and contextual factors related to teachers’ experience with stress and burnout. Teach. Teach. 2018, 24, 768–787. [Google Scholar] [CrossRef]
  42. Becker, E.S.; Goetz, T.; Morger, V.; Ranellucci, J. The importance of teachers’ emotions and instructional behavior for their students’ emotions. An experience sampling analysis. Teach. Teach. Educ. 2014, 43, 15–26. [Google Scholar] [CrossRef]
  43. Beilock, S.L.; Gunderson, E.A.; Ramirez, G.; Levine, S.C. Female teachers’ math anxiety affects girls’ math achievement. Proc. Natl. Acad. Sci. USA 2010, 107, 1860–1863. [Google Scholar] [CrossRef]
  44. Yan, E.M.; Evans, I.M.; Harvey, S.T. Observing Emotional Interactions Between Teachers and Students in Elementary School Classrooms. J. Res. Child. Educ. 2011, 25, 82–97. [Google Scholar] [CrossRef]
  45. Griffiths, D.; Goddard, T. An explanatory framework for understanding teachers resistance to adopting educational technology. Kybernetes 2015, 44, 1240–1250. [Google Scholar] [CrossRef]
  46. Choi, B.; Jegatheeswaran, L.; Minocha, A.; Alhilani, M.; Nakhoul, M.; Mutengesa, E. The impact of the COVID-19 pandemic on final year medical students in the United Kingdom: A national survey. BMC Med. Educ. 2020, 20, 206. [Google Scholar] [CrossRef]
  47. Du, W.; Yu, J.; Wang, H.; Zhang, X.; Zhang, S.; Li, Q.; Zhang, Z. Clinical characteristics of COVID-19 in children compared with adults in Shandong Province, China. Infection 2020, 48, 445–452. [Google Scholar] [CrossRef]
  48. Binali, H.; Wu, C.; Potdar, V. Computational approaches for emotion detection in text. In Proceedings of the 2010 4th IEEE International Conference on Digital Ecosystems and Technologies (DEST), Dubai, United Arab Emirates, 13–16 April 2010; pp. 172–177. [Google Scholar] [CrossRef]
  49. Lopatovska, I.; Arapakis, I. Theories, methods and current research on emotions in library and information science, information retrieval and human–computer interaction. Inf. Process. Manag. 2011, 47, 575–592. [Google Scholar] [CrossRef]
  50. Halverson, L.R.; Graham, C.R. Learner Engagement in Blended Learning Environments: A Conceptual Framework. Online Learn. 2019, 23, 145–178. [Google Scholar] [CrossRef]
  51. Costa, A.; Faria, L. The impact of emotional intelligence on academic achievement: A longitudinal study in Portuguese secondary. Learn. Individ. Differ. 2015, 37, 38–47. [Google Scholar] [CrossRef]
  52. Pekrun, R.; Perry, R.P. Control-value theory of achievement emotions. In International Handbook of Emotions in Education; Pekrun, R., Linnenbrink-Garcia, L., Eds.; Taylor & Francis: Abingdon, UK, 2014; pp. 120–141. [Google Scholar]
  53. Pekrun, R.; Goetz, T.; Daniels, L.M.; Stupnisky, R.H.; Perry, R.P. Boredom in achievement settings: Exploring control–value antecedents and performance outcomes of a neglected emotion. J. Educ. Psychol. 2010, 102, 531–549. [Google Scholar] [CrossRef]
  54. Pekrun, R.; Hall, N.C.; Goetz, T.; Perry, R.P. Boredom and academic achievement: Testing a model of reciprocal causation. J. Educ. Psychol. 2014, 106, 696–710. [Google Scholar] [CrossRef]
  55. Ellis, P.D. The Essential Guide to Effect Sizes: Statistical Power, Meta-Analysis, and the Interpretation of Research Results; Cambridge University Press: Cambridge, UK, 2010. [Google Scholar]
  56. Hedges, L.V. Distribution theory for Glass’s estimator of effect size and related estimators. J. Educ. Stat. 1981, 6, 107–128. [Google Scholar] [CrossRef]
  57. MacCallum, R.C.; Browne, M.W.; Sugawara, H.M. Power analysis and determination of sample size for covariance structure modeling. Psychol. Methods 1996, 2, 130–149. [Google Scholar] [CrossRef]
  58. McMillan, J.H.; Schumacher, S.; Baides, J.S. Investigación Educativa: Una Introducción Conceptual; Pearson: London, UK, 2005. [Google Scholar]
  59. Rebollo-Catalán, M.A.; García-Pérez, R.; Buzón-García, O.; Vega-Caro, L. Las emociones en el aprendizaje universitario apoyado en entornos virtuales: Diferencias según actividad de aprendizaje y motivación del alumnado. Rev. Complut. Educ. 2013, 25, 69–93. [Google Scholar] [CrossRef]
  60. Podsakoff, P.M.; MacKenzie, S.B.; Lee, J.-Y.; Podsakoff, N.P. Common method biases in behavioral research: A critical review of the literature and recommended remedies. J. Appl. Psychol. 2003, 88, 879–903. [Google Scholar] [CrossRef]
  61. Atkinson, R.; Flint, J. Accessing hidden and hard-to-reach populations: Snowball research strategies. Soc. Res. Update 2001, 33, 1–4. [Google Scholar]
  62. Noy, C. Sampling Knowledge: The Hermeneutics of Snowball Sampling in Qualitative Research. Int. J. Soc. Res. Methodol. 2008, 11, 327–344. [Google Scholar] [CrossRef]
  63. D’ancona, C. Metodología Cuantitativa: Estrategias y Técnicas de Investigación Social; Síntesis: Los Angeles, CA, USA, 1991. [Google Scholar]
  64. Lorenzo-Seva, U.; Ferrando, P.J. Factor 9.2: A comprehensive program for fitting exploratory and semiconfirmatory factor analysis and IRT models. Appl. Psychol. Meas. 2013, 37, 497–498. [Google Scholar] [CrossRef]
  65. Timmerman, M.E.; Lorenzo-Seva, U. Dimensionality assessment of ordered polytomous items with parallel analysis. Psychol. Methods 2011, 16, 209–220. [Google Scholar] [CrossRef]
  66. Mîndrilă, D. Maximum Likelihood (ML) and Diagonally Weighted Least Squares (DWLS) Estimation Procedures: A Comparison of Estimation Bias with Ordinal and Multivariate Non-Normal Data. Int. J. Digit. Soc. 2010, 1, 60–66. [Google Scholar] [CrossRef]
  67. Jöreskog, K.; Sörbom, D. Lisrel 8: User’s Reference Guide; Scientific Software International: Lincolnwood, IL, USA, 1997. [Google Scholar]
  68. Browne, M.W.; Cudeck, R. Alternative ways of assessing fit. In Testing Structural Equation Models; Bollen, K.A., Ed.; Sage: Thousand Oaks, CA, USA, 1993; pp. 136–162. [Google Scholar]
  69. Bentler, P.M.; Bonett, D.G. Significance test and goodness of fit in the analysis of covariance structures. Psychol. Bull. 1980, 88, 588–606. [Google Scholar] [CrossRef]
  70. Cohen, J. Statistical Power Analysis for the Behavioral Sciences, 2nd ed.; Erlbaum: Mahwah, NJ, USA, 1988. [Google Scholar]
  71. Bakker, A.B.; de Vries, J.D. Job Demands-Resources theory and self-regulation: New explanations and remedies for job burnout. Anxiety Stress Coping 2020, 34, 1–21. [Google Scholar] [CrossRef]
  72. Chiang, M.M.; Heredia, S.A.; Santamaría, E.J. Clima organizacional y salud psicológica: Una dualidad organizacional. Dimens. Empres. 2017, 15, 63–76. [Google Scholar]
  73. Arquero, J.L.; Donoso, J.A. Docencia, investigación y burnout: El síndrome del quemado en profesores universitarios de Contabilidad. Rev. Contab. 2013, 16, 94–105. [Google Scholar] [CrossRef]
  74. Sánchez Fernández, M.; Clavería, M. Profesorado universitario: Estrés laboral. Factor de riesgo de salud. Enfermería Glob. 2005, 6, 1–16. [Google Scholar]
  75. Maslach, C. Burnout: The Cost of Caring; Prentice Hall: Upper Saddle River, NJ, USA, 1982. [Google Scholar]
  76. Noh, J.-W.; Kim, K.-B.; Park, J.; Hong, J.; Kwon, Y.D. Relationship between the number of family members and stress by gender: Cross-sectional analysis of the fifth Korea National Health and Nutrition Examination Survey. PLoS ONE 2017, 12, e0184235. [Google Scholar] [CrossRef]
  77. Lemos, M.C.; Arnott, J.C.; Ardoin, N.M.; Baja, K.; Bednarek, A.T.; Dewulf, A.; Fieseler, C.; Goodrich, K.A.; Jagannathan, K.; Klenk, N.; et al. To co-produce or not to co-produce. Nat. Sustain. 2018, 1, 722–724. [Google Scholar] [CrossRef]
  78. Hess, U.; Senécal, S.; Kirouac, G.; Herrera, P.; Philippot, P.; Kleck, R.E. Emotional expressivity in men and women: Stereotypes and self-perceptions. Cogn. Emot. 2000, 14, 609–642. [Google Scholar] [CrossRef]
  79. Chan, D. Emotional intelligence, self-efficacy, and coping among chinese prospective and inservice teachers in Hong Kong. Educ. Psychol. 2008, 28, 397–408. [Google Scholar] [CrossRef]
  80. Mouton, A.; Hansenne, M.; Delcour, R.; Cloes, M. Emotional Intelligence and Self-Efficacy Among Physical Education Teachers. J. Teach. Phys. Educ. 2013, 32, 342–354. [Google Scholar] [CrossRef]
  81. Yin, H. The effect of teachers’ emotional labour on teaching satisfaction: Moderation of emotional intelligence. Teach. Teach. 2015, 21, 789–810. [Google Scholar] [CrossRef]
  82. Greenglass, E.R.; Burke, R.J.; Konarski, R. Components of Burnout, Resources, and Gender-Related Differences. J. Appl. Soc. Psychol. 1998, 28, 1088–1106. [Google Scholar] [CrossRef]
  83. Penit, E. La Encuesta de Fecundidad de 2018. Rev. Estadística Soc. 2019, 7, 6–9. [Google Scholar]
  84. Gudmundsdottir, G.B.; Hatlevik, O.E. Newly qualified teachers’ professional digital competence: Implications for teacher education. Eur. J. Teach. Educ. 2017, 41, 214–231. [Google Scholar] [CrossRef]
  85. Berkovich, I.; Eyal, O. Educational leaders and emotions: An international review of empirical evidence 1992–2012. Rev. Educ. Res. 2015, 85, 129–167. [Google Scholar] [CrossRef]
  86. Yin, H.-B.; Lee, J.C.K.; Zhang, Z.-H.; Jin, Y.-L. Exploring the relationship among teachers’ emotional intelligence, emotional labor strategies and teaching satisfaction. Teach. Teach. Educ. 2013, 35, 137–145. [Google Scholar] [CrossRef]
Sustainability 16 01456 g001
Figure 1. Flowchart of the confirmatory factor analysis of the Emotions Questionnaire.
Figure 1. Flowchart of the confirmatory factor analysis of the Emotions Questionnaire.
Sustainability 16 01456 g001
Table 1. Descriptive statistics of the items and factors of the Emotions Questionnaire (n = 4589).
Table 1. Descriptive statistics of the items and factors of the Emotions Questionnaire (n = 4589).
MSDAsymmetryα of Cronbachα If the Element Is Eliminated
Positive Emotions18.323.87−0.420.804-
(IT1) I am proud of the work done during the confinement. 4.140.89−0.880.77
(IT2) I am satisfied with the work performed during the confinement. 3.890.95−0.640.74
(IT3) I am confident that my work is adequate. 3.840.94−0.570.74
(IT4) I feel encouraged when I finish my work activity. 3.461.28−0.330.82
(IT5) I feel safe when I work in confinement. 2.991.060.070.77
Negative Emotions19.404.47−0.800.868-
(IT6) I feel stress while teaching.4.121.00−1.070.85
(IT7) My work worries me during confinement.4.001.01−0.890.86
(IT8) I feel irritated doing my job in this situation.3.411.25−0.360.84
(IT9) Working in this situation makes me feel frustrated.3.721.19−0.670.82
(IT10) Working in this confined situation causes me general stress. 4.141.05−1.170.82
Total Emotions (Positive—Negative)1.086.79−0.22-
Note. M = mean; SD = standard deviation.
Table 2. Descriptive statistics of the items and factors in the questionnaire on emotions from the point of view of sex (n = 4589).
Table 2. Descriptive statistics of the items and factors in the questionnaire on emotions from the point of view of sex (n = 4589).
SexNMSDFSig
Positive Emotions
(IT1) I am proud of the work done during the confinement. Man10714.110.9120.140.702
Woman34754.150.881
(IT2) I am satisfied with the work performed during the confinement. Man10713.860.9650.920.336
Woman34753.900.942
(IT3) I am confident that my work is adequate. Man10713.850.9550.320.568
Woman34753.830.939
(IT4) I feel encouraged when I finish my work activity. Man10713.631.21417.960.000
Woman34753.421.289
(IT5) I feel safe when I work in confinement. Man10713.101.0949.240.002
Woman34752.971.041
Negative Emotions
(IT6) I feel stress while teaching.Man10713.861.06115.300.000
Woman34754.200.961
(IT7) My work worries me during confinement.Man10713.811.05416.760.000
Woman34754.050.985
(IT8) I feel irritated doing my job in this situation.Man10713.261.2822.750.097
Woman34753.461.234
(IT9) Working in this situation makes me feel frustrated.Man10713.501.24321.760.000
Woman34753.791.166
(IT10) Working in this confined situation causes me general stress.Man10713.821.17246.940.000
Woman34754.240.990
Note. M = mean; SD = standard deviation; F = continuous probability distribution; Sig = significance.
Table 3. Descriptive statistics of the items and factors in the questionnaire on negative emotions from the point of view of sex (n = 4589).
Table 3. Descriptive statistics of the items and factors in the questionnaire on negative emotions from the point of view of sex (n = 4589).
Age RangeNMSDFSig
(IT6) I feel stress while teaching.21–251063.871.0156.2260.000
26–304403.921.034
31–355224.031.077
36–406704.220.925
41–506514.200.958
46–506654.120.941
51–556974.121.018
56–607054.140.991
61–701334.061.057
Total45894.120.997
(IT7) My work worries me during confinement.21–251063.751.0053.1450.003
26–304403.930.958
31–355223.961.013
36–406703.981.020
41–506513.991.006
46–506653.881.020
51–556974.031.013
56–607054.120.976
61–701333.941.140
Total45894.001.007
(IT8) I feel irritated doing my job in this situation.21–251063.231.1973.9700.000
26–304403.201.258
31–355223.341.238
36–406703.511.219
41–506513.481.255
46–506653.411.19
51–556973.371.263
56–607053.471.239
61–701333.381.283
Total45893.411.249
(IT9) Working in this situation makes me feel frustrated.21–251063.611.1094.7530.000
26–304403.771.146
31–355223.751.187
36–406703.881.121
41–506513.761.202
46–506653.611.201
51–556973.591.217
56–607053.671.213
61–701333.441.269
Total45893.721.191
(IT10) Working in this confined situation causes me general stress.21–251063.911.1004.9170.000
26–304404.001.094
31–355224.061.100
36–406704.250.983
41–506514.221.004
46–506651.190.992
51–556974.101.077
56–607054.141.067
61–701333.981.128
Total45894.141.051
Note. M = mean; SD = standard deviation; F = continuous probability distribution; Sig = significance.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Garitano, E.T.; Portillo Berasaluce, J.; de la Serna, A.L.; Arce Alonso, A. Emotions of Educators Conducting Emergency Remote Teaching during COVID-19 Confinement. Sustainability 2024, 16, 1456. https://doi.org/10.3390/su16041456

AMA Style

Garitano ET, Portillo Berasaluce J, de la Serna AL, Arce Alonso A. Emotions of Educators Conducting Emergency Remote Teaching during COVID-19 Confinement. Sustainability. 2024; 16(4):1456. https://doi.org/10.3390/su16041456

Chicago/Turabian Style

Garitano, Eneko Tejada, Javier Portillo Berasaluce, Arantzazu López de la Serna, and Ander Arce Alonso. 2024. "Emotions of Educators Conducting Emergency Remote Teaching during COVID-19 Confinement" Sustainability 16, no. 4: 1456. https://doi.org/10.3390/su16041456

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop