Teaching Experience as a Key Factor in Dealing with Digital Teaching Stress

Abstract

Digital pandemic stress among university faculty has become a key issue in the contemporary era, marked by the rapid transition to online teaching. This study conducts a quantitative investigation into the teaching experience as a key explanatory variable in explaining the levels of such stress. For this purpose, a validated instrument has been used, which has been answered by a sample of 1240 university professors. The results show that, although the participating professors do not express high self-concepts of their digital competence or professional aspects, they do not express high levels of digital stress due to the pandemic. However, strong divergences have been identified between the levels of digital pandemic stress of more experienced professors and those of younger professors. Specifically, more experienced professors report lower levels of stress than younger professors, although there are no significant differences in their respective digital competencies. Consequently, the results suggest that teaching experience mitigates teaching digital stress, even when this greater experience does not concur with greater digital competence. It has also been found that the evolution of ratings with teaching experience depends on whether the professor is a specialist in scientific–technical or humanistic–social areas. Specifically, professors in scientific–technical areas with 15 to 25 years of experience are those who suffer more digital stress. Moreover, the digital stress of professors in scientific–technical areas increases between 10 and 25 years of experience, while it decreases among professors with less than 10 years of experience. In contrast, among professors in humanistic–social areas, the trend in the evolution of digital stress is the opposite: it increases among those with less than 10 years of experience and decreases among those with more than 10 years of experience.

1. Introduction

The outbreak of the COVID-19 pandemic led to the need for containment and confinement policies throughout the world, affecting a wide range of social activities [1,2,3]. In the educational field, it was necessary to implement emergency remote teaching using available means and devices [4]. The continuity of education through digital tools faced challenges due to insufficient competence and inadequate technology that led to heterogeneous access and implementation [5], making visible the inequalities that lurk at the bottom of our societies [6]. Professors had to adapt to online teaching, revealing the weaknesses of the face-to-face-based educational system [7] and generating a disruption of classical pedagogy methods [8], with consequent stress and emotional exhaustion in the teaching staff [9].

Teaching is traditionally recognized as one of the most stressful professions due to high workloads, multiplicity of tasks, time constraints [10], increased responsibility of ensuring a quality education capable of forming professionals of the future, continuous participation in research, enactment of management responsibilities [11], tensions with colleagues and managers, role ambiguity, a lack of social support in the workplace, classroom management difficulties [12], the burden of emotional labor, fear of losing control of the classroom, fear of evaluation, and low professional self-esteem, among others [13]. This leads us to consider the emergence of disorders among professors, such as chronic stress, emotional burnout, or burnout syndrome [14]. The latter is a disorder determined by negative psychological experiences and maladaptive behaviors, caused by prolonged tensions, manifested through unfavorable feelings and emotional attitudes towards work and students [15], and generates negative consequences for the educational institution, such as absenteeism [16]. The burnout generated is a response to chronic emotional and interpersonal stressors at work, in a profession in which the relationship with students is key, being a highly emotional type of service [17].

The COVID-19 pandemic generated an online work context that increased anxiety in people conditioned by previous stress in their lives [18], reducing their perception of well-being and creating concern about their professional future [19]. In relation to digital stress, the triggers of these high levels of professional anxiety have been the increase in working hours, the difficulties due to the lack of physical contact, the problems of reconciling personal and work life [20,21], the complexity of digital migration due to technical circumstances [19], the inadequate equipment for online teaching, the limited digital competence of professors and students [5], the absence of competencies for the evaluation of educational practice [22], the weakness of the infrastructure, the environment not conducive to learning at home for some students, and the way in which all this affected academic equity and excellence [23].

University professors had to recognize a low or medium–low digital competence justified by the inability to solve problems using ICTs (Information and Communication Technologies), to show ability in working with a network of contacts, to make use of 2.0 tools to evaluate, and to lack strategies to evaluate their educational practice [22]. This leads us to consider that university professors are a clear example of the digitization effort to provide a professional response to the circumstances that arise [19] in a high-stress scenario.

Therefore, COVID-19 evidenced in university professors’ somatic symptoms, stress and emotional exhaustion [9], in addition to low levels of demand in teaching, affecting the instructional dialogue [24], linked to exhaustion, lack of professional commitment [13,25], personal discomfort [26], constituting a pedagogical limitation [27] that, in some cases, made them consider leaving their jobs [28]. The level of stress among Latin American professors increased when they felt that the training received from their institutions to integrate new technologies into their work environment was insufficient [29].

From this situation, university teachers were forced to use different resources as they faced the acceptance of the new work scenario, the use of new digital tools, adaptation to the domestic context, technological and organizational demands, and a new type of interaction with students [30]. Work time increased, designing their own resources to teach online with little technological training [31]. The interactions with students and the anxiety generated in these [32,33], the new form of communication [34], and the use of new methodologies caused practices in virtual classrooms to be radically modified [35,36]. The psychological effects of the pandemic depended on the relationship between work demands, available resources, levels of professor resilience, and the fatigue generated by the situation [25], causing somatic repercussions, stress, and emotional exhaustion [9]. The difficult educational situation generated by the pandemic, the need to quickly develop a high level of digital competence, and the impact on professors and university students were evident, affecting the occupational health and stress of professors [8,37].

Similarly, COVID-19 highlighted the need for relevant, interactive, and user-friendly digital teaching content, which was a turning point in the development of online tools [38]. Studies on digital transformation in universities focus on strengthening specific strategies and reinforcing the use of technologies as part of the digital agenda of Latin America and the Caribbean [39], the study of which is the subject of this paper. In this work, university professors and the digital competencies that this task requires are directly involved.

The accelerated technological development in education required the adaptation of professors, transforming their knowledge and skills [40]. Their role in improving education through the inclusion of technologies in their work is unquestionable [41]. Therefore, digital competence acquires prominence, and the impulse of the digitization of education as a result of COVID-19 has materialized in the university context [22]. This digital competence implies several changes in professors (Figure 1): (i) adaptation to virtual learning environments (VLEs), applying physical and digital resources that provide innovative solutions to current and future challenges of society [42]; (ii) capacity for online communication, able to build knowledge, learn to respond to needs in daily practice, recognize the need for such information and transform it into knowledge, transmitting it to students in a clear and concise manner [43]. This purpose requires collaboration and cooperation skills, promoting exchange, in addition to teamwork [44,45]; (iii) interaction between content, pedagogy, and technological knowledge [46] using ICTs with good pedagogical judgment and knowledge of the implications for students’ learning strategies and digital training [47]; (iv) professor leadership to ensure the implementation of online skills in students [48]. Thus, a vital factor is the vision of their professors as networked leaders, as digital transformation is determined by the strategy employed to change ideas and practices [49]. This networked leadership involves overcoming inadequacies related to one’s own technological knowledge and skills, providing appropriate guidance, and facilitating the adjusted use of technology within the learning environment [50]; (v) high emotional intelligence that compensates for the anxieties that the experience of incorporating new technologies into their practice may arouse [51].

This series of changes in the skills and knowledge of teachers, derived from educational digitalization, involved emotional coping that could be qualified if the areas in which the professors taught are considered, since professors in the humanistic–social areas showed a higher degree of motivation and social skills than the teachers in the scientific–technical areas when it came to coping with the situation [52]. These results could be justified based on the degree of self-knowledge of their soft skills [53], the perception of their digital competence, and the realism with which they evaluate their own capabilities [52].

The circumstances that university professors in Latin America and the Caribbean have faced since the pandemic have justified the existence of occupational psychosocial factors and damage to their health [54]. The need to modify their teaching practices has implied the confrontation of anxieties, as they have been forced to use online tools, adapting to an imposed digitalization process [51,55]. Therefore, it is advisable to intensify the efforts of universities to improve the digital competence of professors [38], to promote their pedagogical adaptation through various tools, adjusting to each area of knowledge taught [56], as well as to develop interventions that promote their mental comfort, facilitating emotional regulation and the development of digital skills [57]. This implies that educational administrations, governments, and authorities should seek funding options to keep their technological infrastructures updated for the benefit of students and professors [58]. Thus, although the technological gap highlights the social inequality of this Latin American region, there is a capacity for university professors to restructure and adapt to the virtual context, as their teaching experience has shown [59].

In view of the above context, it is pertinent to address the study of the above-mentioned aspects and delve into the stress levels of university professors in adapting to the virtual context in Latin America as a result of the pandemic, as well as to assess those professional requirements linked to the process of digitization of higher education as a result of COVID-19. Thus, the general objective of the present work is to quantitatively analyze the pandemic stress generated among Latin American university professors caused by the process of digitalization of higher education as a result of the COVID-19 pandemic. Specifically, this research seeks to achieve the following specific research questions:

• Q1: What are the changes that the pandemic generated in the self-concept of digital competence of the participating teachers, as well as on their assessment of the professional aspects linked to the process of digitization of teaching and their self-perceived levels of digital stress?
• Q2: How does the teaching experience of the professors influence the above assessments?
• Q3: How does the knowledge area (scientific–technical areas or humanistic–social areas) influence the ratings expressed?

2. Materials and Methods

2.1. Participants and Data Collection

In the present research, the target population was made up of practicing university professors working in universities located in the Latin American and Caribbean regions. Specifically, the criteria for inclusion in this study are as follows: (i) working as a university professor in a university in Latin America and the Caribbean; and (ii) having registered for and attended a training course given by the authors on digitization in higher education. The course was given as a 2-hour master class, repeated every 15 days between January and June 2023. This training session dealt with the different teaching activities in which digital tools can be included and the use of these technologies according to the teaching activity. Therefore, the research process was conducted once the pandemic and its restrictive effects on higher education were completely overcome. However, the questions asked in the questionnaire explicitly asked for assessments of the digital pandemic stress suffered during the pandemic. Pandemic digital stress is a complex phenomenon that reflects how forced and rapid adaptation to a digitized environment can have significant consequences for people’s mental health and general well-being [60].

The training session had the following didactic objectives: (i) to explain the meaning of digital competence for university professors; (ii) to explain different ways of exercising digital competence and different digital tools for different teaching uses, and to exemplify this in different areas of knowledge; and (iii) to establish terminology related to the different dimensions of digital teaching stress and the professional aspects related to the digitization process. After the development of the training session, professors were invited to complete the questionnaire that was used as a research instrument. Therefore, a positive distortion of the sample is to be expected as only professors who are interested in digitization would register for this training session. In any case, the sampling process was non-probabilistic by convenience. At all times, the participants were informed in writing of the research purposes of their responses and that in no case would data be collected that could lead to their identification, which made it possible to comply with ethical requirements in relation to the research process. Consequently, participation was free, voluntary, and anonymous. Of the 1568 professors registered in total in the different editions of the training session, a total of 1240 responded validly (i.e., completely) to the questionnaire, which constituted the total sample used in this research. The research design was cross-sectional, and the participants filled the questionnaire used as a research instrument once after the completion of the training session.

2.2. Research Variables

The main explanatory variable used in this research was the length of university teaching experience of the participants (Figure 2). This time of teaching experience was grouped into six ranges of 5 years each: less than or equal to 5 years; 6 to 10 years; 11 to 15 years; 16 to 20 years; 21 to 25 years; and more than 25 years of teaching experience. Consequently, the explanatory variable was considered, for the purposes of the statistical analysis performed, as a nominal polytomous variable. The secondary explanatory variable was the area of knowledge, which is defined as a dichotomous variable whose possible values are (Figure 2): scientific–technical areas (including pure sciences, physical, natural, health, engineering, and architecture) and humanistic–social areas (including philology, philosophy, history and humanities, law, economics, education, and social sciences).

Likewise, the following three explained variables were considered, with all of them being quantitative (Figure 2): (i) the self-concept assessment of the participants’ digital competence after the pandemic experience; (ii) the assessment of the professional aspects linked to the process of digitalization of higher education derived from the pandemic (i.e., the support provided by the university in relation to the teaching digitization process in terms of equipment and training); and (iii) the level of stress perceived by the participants in relation to the process of digitalization of their teaching work due to the COVID-19 pandemic. All of these variables were measured on Likert scales from 1 to 5, where 1 means a very low rating, 2 is low, 3 is moderate, 4 is high, and 5 means a very high rating. It can be assumed that there were no biases in the evaluations expressed due to possible divergences in the concepts that each participant has of the contents of the questions since the training session served to homogenize these concepts.

2.3. Instrument

In this research, a standardized and validated instrument, which has been used in previous work [10,51], was used to measure the self-concept of the digital competence of university professors, their assessment of the different professional aspects related to the teaching activity and linked to the digitization process, and the different affective and emotional dimensions that influence the development of teaching stress due to the digitization process caused by the pandemic. This questionnaire consisted of 22 Likert-type questions ranging from 1 to 5, where 1 corresponds to the lowest rating and 5 corresponds to the highest rating.

The exploratory factor analysis carried out on this questionnaire [53] revealed the existence of three families of questions that explained 63.9% of the variance of the responses. The three families identified in the theoretical model arising from the factor analysis [53] correspond exactly to the three explained variables that are the objects of interest of the present study: (i) self-concept of digital concept (questions 1 to 11, on digital skills, adaptation to the use of digital learning environments, and assessment of continuous digital learning, the self-concept of communication skills, creativity when using digital tools, assessment of network leadership, knowledge of information management, orientation to students, teamwork, resilience, and strategic vision; e.g., assess your digital skills for the use of digital tools in higher education); (ii) assessment of professional aspects related to the digitalization of teaching (questions 12 to 14, on the assessment of the support of the university, the technical equipment, and the training received on the use of digital tools and the development of digital skills; e.g., assess the training you have received from your university for improving your digital skills); and (iii) the self-concept of digital pandemic stress (items 15 to 22, on the assessment of anxiety, feeling that difficulties are increasing, insecurity, irritability, nervousness, feeling of inability to achieve the necessary objectives of digitization of teaching processes, fear of contagion, and feeling of not being in control of the situation caused by the pandemic; e.g., assess the level the level of anxiety you felt during the pandemic about having to use digital tools for teaching). The factor weights obtained varied between 0.62 and 0.89 for the first factor, between 0.69 and 0.82 for the second factor, and between 0.62 and 0.86 for the third factor [51]. To verify the significance of the results obtained here in relation to the theoretical model obtained in the validation of the instrument carried out in [51], in the present work, the model was confirmed through a confirmatory factor analysis.

Likewise, in [51], the internal reliability of the instrument was measured through Cronbach’s alpha and composite reliability parameters, both being higher than 0.79 for each of the three families of questions of the theoretical model.

2.4. Statistical Analysis

In this work, a quantitative investigation has been carried out based on the statistical analysis of the answers given by the participants to the questionnaire used as a research instrument. The validity of this standardized instrument was tested by means of confirmatory factor analysis statistics and the computation of the main reliability parameters, specifically Cronbach’s alpha and composite reliability parameters. For the analysis of the responses, the main descriptive statistics were computed, and the Kruskal–Wallis nonparametric test was used to contrast the degree of statistical significance of the differences observed in the responses according to the different teaching experiences of the participants. To analyze whether the evolution of the ratings expressed as teaching experience increases depends on the participants’ area of knowledge, multifactor analysis of variance was used. All tests were performed at the 0.05 level of significance.

3. Results

3.1. Distribution of Participants

This study involved 1240 professors from different areas of knowledge and universities located in the Latin American and Caribbean region (43.23% males and 56.77% females; mean age: 47.90 years old, standard deviation: 11.04). There are 20 countries of origin represented, although the distribution of participants by country of origin is strongly non-homogeneous, with Argentina, Ecuador, Mexico, Peru, and Venezuela being the most represented countries (

Table 1. Distribution of the participating professors (%) by their country of origin.

Country	Proportion of the Sample (%)
Argentina	21.29
Bolivia	1.29
Brazil	1.94
Chile	1.29
Colombia	9.68
Costa Rica	0.65
Cuba	1.29
Dominican Republic	1.29
Ecuador	15.48
El Salvador	1.29
Guatemala	0.32
Honduras	1.29
Mexico	15.16
Nicaragua	1.61
Panama	1.29
Paraguay	0.65
Peru	10.97
Puerto Rico	1.29
Uruguay	0.65
Venezuela	11.29

; chi-square = 1947.60, p < 0.0001).

Likewise, the distribution of participants by ranks of teaching experience is not homogeneous. On the contrary, the participants are distributed in such a way that the central ranks are the most represented, but not symmetrically because the overrepresentation of the rank with the highest teaching experience breaks the symmetry of the distribution (Figure 3; chi-square = 91.46, p < 0.0001).

Among the participants, 51.93% are from humanistic–social areas and 48.07% are from scientific–technical areas, without it being possible to assume that there are significant differences between the distributions by areas of knowledge. The distribution of participants according to their teaching experience depends significantly on their area of knowledge (chi-square = 41.76, p < 0.0001). Specifically, the proportion of more experienced professors is higher among professors from humanistic–social areas, while among professors from scientific–social areas, the proportion of less experienced professors is higher (Figure 4).

3.2. Instrument Validity

To complete the exploratory factor analysis of the original validation of the instrument [51], a confirmatory factor analysis was carried out that established that the findings are statistically significant. Indeed, the statistics of the confirmatory factor analysis carried out on the obtained responses are consistent with the theoretical model of three families of questions that describe the research instrument [51]. Indeed, the incremental fit indices are good (adjusted goodness-of-fit index = 0.9078; NFI = 0.9566; TLI = 0.9504; CFI = 0.9666; IFI = 0.9668), and the absolute fit indices are also appropriate (GFI = 0.9535; SRMR = 0.0512; AIC = 2600.654).

Internal reliability parameters have also been computed to check the internal reliability of the instrument. This internal reliability has been analyzed through the Cronbach alpha and composite reliability parameters, which are optimal since all of them exceed 0.70 (

Table 2. Cronbach alpha and composite reliability parameters.

Factor	Cronbach’s Alpha	Composite Reliability
Digital competence	0.9474	0.9372
Professional aspects	0.7870	0.7647
Digital stress	0.8548	0.8329

).

3.3. Analysis of Responses

The participants express intermediate levels of digital competence and evaluations of the professional aspects linked to the digitalization of higher education (between 3 and 4 out of 5) after the pandemic (

Table 3. Average responses and standard deviations (out of 5) of the different families of questions of the survey.

Factor	Mean	Standard Deviation
Digital competence	3.87	0.94
Professional aspects	3.44	1.18
Digital stress	2.56	1.24

). In this sense, the greatest homogeneity in the responses is found in the assessment of digital competence because it is the one with the lowest standard deviation (Table 3). It could be said that the average level of digital stress perceived by the participants is rated as intermediate–low (between 2 and 3 out of 5), although the deviation of these ratings is the highest of all, which shows that there is more variation in the levels of perceived digital stress than in the rest of the ratings made (Table 3).

The post-pandemic digital competence rating of the participating professors reaches maximum vales in the ranges between 5 and 15 years of teaching experience, but minimum values in younger professors and in professors with more than 15 years of experience (Figure 5). This gap is statistically significant, as evidenced by the Kruskal–Wallis test statistics (chi-square = 62.12, p < 0.0001). In contrast, the evaluation of the professional aspects linked to the digitization process due to the pandemic follows an increasing trend as teaching experience increases until reaching 10 years of experience, at which point it begins to decrease and does not increase again until 25 years of experience, and this increase is significant (Figure 5).

Thus, it can be noted that the lowest ratings correspond to the least experienced participants. Again, these differences are significant (chi-square = 24.15, p = 0.0002). The digital stress derived from the pandemic is, in general, decreasing with teaching experience, except for the slight increase it undergoes in the passage between the ranges of 11 to 15 and 16 to 20 years of experience (Figure 3). This trend is again statistically significant, as evidenced by the Kruskal–Wallis test statistics (chi-square = 25.14, p = 0.0001).

The evolution of the ratings analyzed with teaching experience depends on the area of knowledge of the professors. Specifically, the digital competence of professors in humanistic–social areas decreases as teaching experience increases, while among professors in scientific–technical areas, it increases when teaching experience is less than 15 years (Figure 6). The valuation of professional aspects is notably higher as teaching experience increases among professors in scientific–technical areas, but this growth is not as pronounced among professors in humanistic–social areas (Figure 7).

The levels of digital stress of professors with between 15 and 25 years of experience are higher among professors in scientific–technical areas than among those in humanistic–social areas (Figure 8). Digital stress among professors in scientific–technical areas increases between 10 and 25 years of teaching experience (central ranges of experience), while among professors in humanistic–social areas, it decreases in the central ranges of experience and increases among recently hired professors and among the most experienced (Figure 8), these differences being significant both for the factor on teaching competence (F = 10.02, p < 0.0001), professional aspects (F = 3.03, p = 0.0099), and digital stress (F = 5.21, p < 0.0001). This means that the perception of the digital stress suffered during the pandemic is significantly different according to the professors’ knowledge area.

4. Discussion

The results show that the variables under study (Figure 2) are influenced by the experience that supports the work of professors in a context such as that of the Latin American region, which, as the previous literature has shown, was immersed in a digital transformation effort following the pandemic [39,40,41,51]. A comparison of the results obtained in the present research with those obtained in previous studies helps validate and generalize the results obtained from the findings.

The professors in this region reflect average levels of self-concept of digital competence, a fact that contrasts with previous studies that reveal a certain incapacity determined by the effective use of ICTs and their pedagogical use in the reality of teaching [19,22]. In spite of this, different perceptions are observed, determined by the age of the teaching staff, with the youngest and oldest professors in this study acknowledging lower competence in the inclusion of technologies in their professional performance. It is likely that the effort to adapt to virtual environments [42], the ability to communicate using online resources [43], the skills of interaction and cooperative work [44,45], the ability to interconnect pedagogical and technological aspects [46], the knowledge of teaching strategies facilitated by ICTs [47], and social leadership skills with respect to their students [48] are very much determined, in one case, by the reduced teaching experience, as they do not have effective resources to make their task successful, or, in another, by the limited capacity for involvement, linked to a long experience, which reveals levels of fatigue as they are at the end of their professional career.

In relation to the assessment of the professional aspects linked to digitization, the teaching population reflects average levels. This implies that professors actively accepted (i) this digitization effort [19]; (ii) the change in context and work tools, as well as the new form of interaction with students [30,34]; (iii) the increase in working time [31]; and (iv) the creation and implementation of new methodologies and online resources [35,36]. These results can be nuanced if we delve into the different perceptions of professors according to their age, and this translates into the fact that younger and less experienced professors are those who recognize the lowest valuation in terms of professional aspects linked to digitization. As the previous literature reveals, this population was the most aware of their pedagogical limitations [27], negatively determining their professional commitment [13,25] as a result of their work inexperience.

In terms of perceived stress, Latin American professors, as reflected in previous studies, as well as the rest of the workers in the educational field [18], showed stress levels derived from the new situation that the pandemic forced them to face [14]. The procedures of teaching were affected [23], as they were forced to make use of new resources to adapt to digitalization, influencing their health [52,53]. However, in this study, variations are observed in relation to the assessment of the perceived level of stress with respect to the results present in the preceding literature. Specifically, it can be considered that Latin American professors assume that their stress levels reached moderate levels, in contrast to the previous literature consulted, in which symptoms of somatic character, emotional exhaustion, lack of work commitment, discomfort, and general stress were high in professors in this region [16,29].

The results of this study have shown that self-perceived stress among university professors in Latin America has presented different levels conditioned by teaching experience. Thus, it has been shown that the greater the professional experience, the lower the perception of stress, and that those professors with fewer years of teaching experience recognized a greater affectation and emotional exhaustion. Possibly, the fact that they had little work experience meant that this unforeseen situation, derived from the pandemic, constituted a pedagogical limitation [27] since they did not have alternative tools that their previous practice could facilitate. On the other hand, not having received adequate training in the technological field from their institutions [29] did not favor the implementation of innovative resources that could alleviate this difficult educational situation. From all of this, it can be deduced that the capacity of veteran professors and the experience accumulated in a profession typically recognized as stressful by multiple factors [10,13,17] facilitated greater emotional adjustment, reducing the perception of emotional exhaustion and stress.

When evaluating the results obtained in the analysis of the three variables under study (Figure 2), it can be considered that all of them are conditioned by teaching experience (Figure 9). Professors with more years of teaching experience have shown that, despite reporting limited digital competence and low appreciation of the professional aspects linked to digitization, they have shown adequate skills to cope emotionally with the situation, controlling their stress levels. On the contrary, the most novice professors have recognized insufficient digital training, a minimal valuation of the professional aspects related to the use of technology, and their stress levels have been the most evident. Furthermore, according to the results obtained, there are no significant differences in teaching experience between the average values of digital competence and the assessment of professional changes linked to digitalization, but there are significant differences between the mean values of pandemic digital stress. This would show that there must be extraneous variables, other than digital competence or the availability of training and technical equipment, that can influence the levels of digital stress. These extraneous variables include factors such as workload, access to appropriate technological resources, social and family support, and even personal and professional expectations. Thus, given the importance of these variables, their identification is therefore an interesting line of future research.

All of this allows us to consider that, although the technological gap in this Latin American region is evident and requires an updating of faculty competencies [57], in addition to an improvement in technological infrastructures [56], the high level of teaching experience could compensate for the tensions derived from this disadvantageous situation, limiting the levels of stress that the pandemic generated in university faculty. In addition, the present study has shown that the area of knowledge (scientific–technical or humanistic–social) influences the way in which evaluations evolve with teaching experience. The most evident gap occurs in the middle brackets of teaching experience (between 10 and 25 years). Specifically, in terms of digital teaching stress (Figure 10), professors in scientific–technical areas increase their stress as experience increases. Among professors in humanistic–social areas, digital stress decreases. The previous literature has shown that the areas of knowledge are explanatory variables of certain influential characteristics in the behavior of university professors, such as soft skills [52,53]. Specifically, it has been shown that professors from humanistic–social areas express better self-concepts of their skills than professors from scientific–technical areas. However, the influence of the area of knowledge on the evolution of these evaluations had never been studied until now [52,53]. Here, it has been found that digital stress decreases, in general terms, as teaching experience increases. However, it has been shown that there must be extraneous variables that condition this influence. Here, it has been shown that the influence of teaching experience is roughly inverse in professors from scientific–technical areas with respect to those from humanistic–social areas. Thus, in future research, it would be convenient to delve deeper into the identification of these extraneous variables, particularly in the way in which the specific area of knowledge influences.

In relation to the limitations of this study, this research was conducted completely after the pandemic and thus captured retrospective estimations of a former situation. This could affect the assessments made by the participants, especially since the authors do not have data prior to the pandemic. The need for longitudinal studies is also a limitation of our research. Likewise, in this study, some variables that may eventually affect digital faculty stress have not been controlled for, among them the technical equipment and the concrete support by the university, the measures taken by the different countries or universities to reduce infections and fight the pandemic, the teaching load or the number of courses per professor, and the subjective meaningfulness of the teaching task for each professor. Finally, the fact that the participants are professors interested in participating in training on digitization could cause a bias in the sample since the sample would not represent the entire population of university professors but rather those interested in increasing their training on digital skills.

As the main lines of future research, the following can be pointed out: (i) increasing the size of the sample of professors, with the purpose of strengthening the representativeness of the results; (ii) expanding the sample in terms of the homogeneous number of participants from each of the countries represented in order to avoid possible biases that could arise when, as in the present study, the distribution of participants by country of origin is not homogeneous; (iii) complementing the quantitative analysis with a qualitative study that delves into the strategies employed by professors with greater experience to manage their stress levels; and (iv) further study of the influence of professors’ field of knowledge on their digital stress.

5. Conclusions

It has been shown that the variables analyzed are strongly influenced by the professors’ teaching experience. Specifically, the results suggest that the level of digital stress due to the pandemic decreases as teaching experience increases. Indeed, it is observed that the most experienced professors express pandemic digital stress lower than that expressed by the youngest ones. However, the self-concept of digital competence and the assessment of the professional aspects linked to digitalization increase with teaching experience only up to 11–15 years of teaching experience and decrease again among more experienced professors. It can be deduced from this that there is a digital divide that negatively affects older professors and probably a lack of training that affects new professors. However, the digital divide that affects older people does not translate into an increase in digital stress, probably because their professional prospects cushion that impact.

In relation to the influence of the area of knowledge on digital stress, this paper provides two original scientific contributions. On the one hand, it has been shown that the digital stress of professors in scientific–technical areas with medium teaching experience (between 10 and 25 years) is greater than that of professors in humanistic–social areas. On the other hand, the evolution of digital stress among professors in scientific–technical areas with medium experience is increasing, while that of professors in humanistic–social areas is decreasing.

In summary, the results obtained allow us to conclude that, even though teaching experience does not lead to a greater ability to use digital technologies, it does lead to a decrease in the digital stress of university professors. All of this implies that teaching experience provides university professors with the tools to face potentially stressful situations in a more effective way. Proof of this is that the digital stress caused by a situation as serious and abrupt as the COVID-19 pandemic has been lower among those who had more experience. New professors are, therefore, those most in need of specific support from their universities to make up for their weak capacity to face unforeseen situations that compromise their teaching activity.

Consequently, universities are recommended to increase digital training and the development of techno-pedagogical skills for new professors and design specific training plans to digitally integrate older professors. It is also advisable to continue researching the identification of explanatory variables of professors’ digital stress levels. Finally, it is recommended that the above training be adapted to the specific needs of the professors in the different areas of knowledge.