Teachers’ adaptations to COVID-19: perceived preparedness for distance education, frequency of teacher-student contact, and resources in ICT

ABSTRACT

The post-COVID The Great Online Transition requires more support for teaching with information and communications technology (ICT) than ever. The present study investigated teachers’ psychological (perceived preparedness for distance education) and behavioural (frequency of teacher – student contact) adaptations to distance education in relation to job (training, collaboration, and equipment) and personal (self-efficacy) resources in the area of ICT during the first wave of school closings in 2020. We surveyed 1103 teachers in German-speaking regions via newsletters and X (formerly Twitter). Results from the recursive path model showed that all job resources were positively associated with teachers’ perceived preparedness, but the actual frequency of contact was only significantly related to ICT collaboration. Lastly, ICT self-efficacy mediated the associations between job resources and teachers’ adaptations. Our findings highlighted policymaking and school administration applications in which focus should be placed on fostering ICT resources, particularly collaboration.

KEYWORDS:

• In-service teacher
• remote teaching
• technology
• school closure
• continuing professional development

Introduction

As the unprecedented COVID-19 pandemic caused comprehensive school closings in the spring of 2020, teachers around the globe were facing an unfamiliar yet pivotal job demand – utilizing any available information and communications technologies (ICT) to maintain contacts with students and provide distance education (OECD 2020b). This job demand remains significant and enduring even in times post-COVID, as school instruction has been reshaped to shift from face-to-face to hybrid instruction after the Great Online Transition (GOT) of 2020 (Tondeur et al. 2023).

In contrast to other conventional job demands such as managing classrooms and grading homework (Kyriacou 2001), teachers were mostly unaccustomed to the new job demand of applying ICT for distance education. Facing the challenge of hastily adapting to this new job demand, teachers have reported a high level of anxiety, worrying, and a general feeling of unpreparedness during school closings caused by COVID-19 (Moorhouse 2021; OECD 2020c; Pressley 2021). Teachers who feel unprepared for the job are found to be less likely to make adaptive pedagogical decisions (O’Neill and Stephenson 2012) and are prone to burnout due to constant stress (Pas, Bradshaw, and Hershfeldt 2012). Unable to adapt to the new job demand, teachers were also found to have much fewer contacts with students (Hamilton, Kaufman, and Diliberti 2020; Josephson, Kilic, and Michler 2021). Given the significance of teacher – student contacts for students’ learning (Korthagen, Attema-Noordewier, and Zwart 2014; Ye et al. 2021), the sharp decrease raises worries about a widening achievement gap (Kuhfeld et al. 2020). In order to mitigate the effect of job demands posed by distance education and support teachers’ needs in an increasingly digitalized world, it is paramount to examine factors that enhance teachers’ adaptations to distance education, both in terms of their feelings of preparedness for distance education and of their contacts with students.

Teachers’ adaptations to the work environment are the focus of the Job Demands-Resources (JD-R) theory (Demerouti et al. 2001). JD-R essentially explicates the connections between job characteristics, including job demands and job resources, and job outcomes, such as well-being and performance (for a review, see Taris, Leisink, and Schaufeli 2017). According to JD-R, adaptation to the challenges in the work environment is keenly determined by the resources available to teachers (Bakker and Bal 2010). These valuable resources are derived from both the work environment (e.g., training opportunities, social support, and infrastructure) and the teachers themselves (e.g., self-efficacy), also referred to as job resources and personal resources (Bakker and Demerouti 2017). Given our present interest in how well teachers adapt to the newly imposed job demands, we thus adopted the JD-R theory and conceptualised teachers’ preparedness to provide ICT-facilitated distance education, as well as their actual frequency of contact with students, as adaptations to the pandemic’s new job demands. JD-R further stipulated that the job and personal resources available to teachers may have an effect on such adaptations.

As all forms of instructions and communications rely heavily on ICT during school closings (König, Jäger-Biela, and Glutsch 2020), it is reasonable to suspect that teachers’ adaptations to distance education could be related to job and personal resources in the area of ICT. Past research has already highlighted resources that are directly or indirectly linked to teachers’ ICT usage, including their prior training in ICT (Gill et al. 2015), peer collaboration using ICT (Welling, Lorenz, and Eickelmann, 2016), available ICT equipment in school (Albion et al. 2015), and beliefs about their ICT efficacy (Hatlevik and Hatlevik, 2018).

What remains unclear is whether the aforementioned ICT-related resources are also relevant to teachers’ psychological adaptation (perception of preparedness for distance education) and behavioural adaptation (frequency of teacher – student contact) to ICT-facilitated distance education, and thus the goal of the current study.

Teachers’ perceived preparedness for distance education and frequency of teacher – student contact during COVID-19

The COVID-19 outbreak caused school closings in around 190 countries at the peak of the crisis and continues to affect over 94% of the world’s student population (OECD 2020b; United Nations 2020). During the lockdown, schools around the globe have switched to full or partial distance education with means such as television or radio programming, real-time lessons on virtual meeting platforms, self-paced formalised lessons or educational content, and online support services for parents and students (Darling-Hammond and Hyler 2020; Schleicher 2020). Facing the unaccustomed job demands posed by ICT-facilitated distance education, teachers may feel unprepared and encounter challenges in maintaining contact with students. These psychological and behavioural inadaptations are likely to hinder teachers’ instructional quality and students’ outcomes in the long run (Josephson, Kilic, and Michler, 2021; Schult et al. 2022). Moreover, the work on teachers’ digital competences conducted independent of COVID-19 has emphasised the prominence and necessity of incorporating ICT into the classroom in order to educate students for a digitalised future (Backfisch et al. 2021; Lachner et al. 2021). Therefore, investigating teachers’ psychological and behavioural adaptations to ICT-facilitated distance education would be paramount to promoting technology integration in classrooms, regardless of the pandemic epoch.

Teachers’ perceived preparedness are self-estimates of readiness to teach in certain situations (Housego 1990; O’Neill and Stephenson 2012), and they represent the affective domain of teaching competence (Brown, Lee, and Collins 2015). This construct has been seen as an important indicator of how effectively teachers would be able to handle the demands of the profession (Kee 2012). On the other hand, teachers’ initial feelings of unpreparedness have been found to be predictive of burnout symptoms later in the school year (Pressley 2021). Perceived preparedness has been linked to job resources such as training experience. For instance, Boe et al. (2007) found that increased participation in pedagogy and practice seminars led to greater feelings of preparedness among beginning teachers in both general and special education. Similarly, O’Neill and Stephenson (2012) found that the completion of classroom management courses was associated with stronger feelings of preparedness to handle various categories of problematic behaviours.

Although perceived preparedness has been traditionally investigated among student or beginning teachers, there are repeated indications that in-service teachers are also feeling highly unprepared for the abrupt change into distance education due to school closings (e.g., Barlovits et al. 2021; Moorhouse, 2021). Research not conducted against the backdrop of COVID-19 has also shown that when it comes to teaching with ICT, preservice and in-service teachers are not substantially different in their preparedness to incorporate technology into their instruction (Knezek et al. 2023; Moore-Hayes and Moore-Hayes, 2011). Given the widely reported sense of unpreparedness during COVID-19, it is critical to investigate job and personal resources that may improve teachers’ perceived preparedness for distance education during school closings. Despite existing evidence concerning the links between preparedness and teacher training in general, no research has been conducted to date on the relationships between perceived preparedness to teach remotely and ICT-related resources, including ICT training.

Another crucial adaptation that teachers must make during school closings is to maintain teacher – student contact via ICT (Carrillo and Flores 2020). Teacher – student contact could be defined as the momentary ‘encounter in the here-and-now’ between teachers and students (Korthagen, Attema-Noordewier, and Zwart 2014, 23). Despite the nature of momentariness, teacher – student contact could build up to a positive and enduring teacher – student relationship over time (Andrzejewski and Davis 2008). Korthagen et al. (2014) showed that good teacher – student contacts promoted students’ active learning behaviour, self-assurance, autonomy, and engagement. The few studies published during the school closings have also highlighted the central role of teacher – student contact in distance education. For instance, according to a survey conducted in Germany, Austria, and Switzerland in March 2020, students who spent the longest hours on learning and school tasks during lockdown reported that their teachers were regularly monitoring learning tasks (Huber and Helm 2020). In a sample of 733 Chinese middle school students, Ye et al. (2021) found that teacher – student contact during school closings predicted higher academic engagement and fewer mental health issues. It also served as a protective factor that moderated the negative relationships between cyberbullying and mental health, as well as the link between difficulties with online learning and academic engagement.

Despite its significance, it has been widely reported that maintaining teacher – student contact was difficult during school closings. Josephson et al. (2021) used longitudinal survey data from Ethiopia, Malawi, Nigeria, and Uganda to examine the frequency of teacher – student contacts before (2018–2019) and after (May–August to August 2020) the outbreak of COVID-19. They found that teacher – student contacts dropped sharply from 96% to 17% among households with school-aged children (Josephson, Kilic, and Michler 2021). Similarly, a survey conducted with over 1000 parents in Germany demonstrated that the time students spent on school activities dropped from 7.4 to 3.6 hours per day during the school closing, along with the sharp decrease in teacher – student contact (Wößmann et al. 2020). More alarmingly, low-achieving students were particularly affected by the lack of teacher support (Engzell, Frey, and Verhagen 2020; Schult et al. 2022). To summarise, during the school closing, teachers have faced the challenge of maintaining contacts with students while also providing high-quality distance education that is critical to students’ development.

Given the crucial role teachers are playing in maintaining education continuity during the pandemic (Engzell, Frey, and Verhagen 2020), it is critical to investigate job and personal resources associated with their psychological (perceived preparedness for distance education) and behavioural adaptations (frequency of teacher – student contact) to distance education. Due to the ubiquity of ICT applications in distance education, it is plausible but unconfirmed that widely recognised resources related to teachers’ ICT usage might also be linked to teachers’ perceived preparedness for distance education and frequency of contact. In particular, we are going to cover training, collaboration, available equipment in schools, and teachers’ self-efficacy as resources in the area of ICT that may contribute to teachers’ adaptations to distance education.

Job and personal resources in ICT

The Job Demands-Resources (JD-R) theory distinguished two categories of resources – job and personal resources – that might initiate a motivational process that leads to high job performance (Bakker and Costa 2014), as well as buffering the detrimental effects of job demands on well-being and performance (Xanthopoulou et al. 2007). The job resources are ‘physical, psychological, social, or organisational aspects of the job that are either/or (a) functional in achieving work goals, (b) reduce job demands and the associated physiological and psychological costs, and (c) stimulate personal growth, learning, and development’ (Bakker and Demerouti 2007, 312). Past research has identified various job resources that lead to positive outcomes, such as participation in professional training (Crowe et al. 2020), social climate and collaborative culture (Louis 2006), and adequate access to equipment and facilities (Rousseau and Aubé 2010), among others (for a review, see Hakanen, Bakker, and Schaufeli 2006).

Personal resources, on the other hand, are individuals’ beliefs about their capacities to influence and control their environment (Hobfoll, 2002; Xanthopoulou et al. 2007). Self-efficacy has been identified as a prominent personal resource in the recent development of JD-R theory (Bakker and Demerouti 2017). Self-efficacy not only shares a similar role as job resources (e.g., Xanthopoulou, Bakker, and Fischbach 2013), but also mediates the relationship between job resources and outcome variables such as work engagement. For example, Llorens et al. (2007) discovered that job resources (control) promote self-efficacy, which in turn increases positive outcomes (work engagement). Similarly, Xanthopoulou et al. (2007) found that job resources predicted self-efficacy, and self-efficacy was positively linked to work engagement, especially when demands were high.

The outcome variable we are interested in in the present study is teachers’ adaptations to distance education via ICT, namely their perceived preparedness for distance education and the frequency of teacher – student contact during school closings. As a result, in the following sections, we will focus on job and personal resources that promote ICT usage.

Professional training with ICT

Teachers who have attended ICT-related training as part of their initial education or in-service professional development activities have been found to be more inclined to incorporate ICT in their teaching (Eickelmann and Drossel 2020), demonstrating the potential role of ICT training as a valuable job resource. Teachers have also expressed pressing needs for more ICT-related training (Richter et al. 2019). König et al. (2020), for example, discovered in a survey conducted in May and June 2020 that German teachers’ opportunities to acquire digital competence during initial teacher education significantly predicted teachers’ contact with students in distance education. In another survey focused on schooling during COVID-19, the teachers expressed their wish for more support in working with ICT through continuing professional development offerings (Huber and Helm 2020).

In contrast to the significance of expanding professional training offerings in the field of ICT, research consistently shows a scarcity of such opportunities. Despite a strong self-reported need to learn more about the use of ICT in the classroom, only a small percentage of the teachers surveyed globally had attended ICT training in the previous two years, according to the International Computer and Information Literacy Study (ICILS) 2018 (Gerick, Eickelmann, and Labusch 2019). According to another recent German survey of teachers’ teaching and learning during the school closing, 20.4% of those polled said they had never attended ICT training courses or workshops in the past two years (Runge, Rubach, and Lazarides 2021). A study conducted in Small Island Developing States during COVID-19 school closings showed that less than half of those polled received regular ICT training, and even fewer thought it was sufficient (26.4%) (Seetal, Gunness, and Teeroovengadum 2021). The apparent disparity between demand and supply in ICT training might therefore affect the frequency of teacher – student contact and overall preparedness for distance education during the school closing.

Collaboration experiences with ICT

Besides individual training pertaining to ICT, teacher collaboration also constitutes a prominent job resource for the successful implementation of ICT (Albion et al. 2015). For instance, in a study of 130 Hong Kong schools, Li and Choi (2014) found positive effects of the existence of peer networks for accessing innovative information on changes in teachers’ pedagogical use of ICT. Similarly, another study of 116 Norwegian schools reported that collegial collaboration among teachers had a positive association with the use of ICT in their teaching practice (Hatlevik and Hatlevik 2018). Beyond local communities around schools, other studies have also found that engagement in online communities that enable information sharing promotes teachers’ ICT integration (Ertmer and Ottenbreit-Leftwich 2013; Twining et al. 2013). Furthermore, ICT-related collaboration not only facilitates teachers’ experimentation with innovative technologies but also sustains their implementation (Dexter, Seashore, and Anderson 2002). Drossel et al. (2017) argued that teachers were more motivated to use innovative technology and more likely to overcome obstacles if mutual exchange and collaboration with peers were possible. Based on these findings, teachers who actively collaborate with colleagues using ICT might feel more prepared for distance education.

ICT equipment in schools

Another important job resource relating to teachers’ ICT usage is their access to ICT equipment in schools. As one of the foundational enabling conditions for ICT integration, the existence of ICT equipment in schools is the prerequisite for all digital teaching and learning (Albion et al. 2015). Sang et al. (2010) argued that the capacity of resources and sustainability of the infrastructure affect the adoption of ICT in classrooms. Indeed, in a survey conducted during early school closings, König et al. (2020) identified access to computer programs for direct teaching as a significant predictor for maintenance of social contact, provision of online lessons, and task differentiation. Vrasidas (2015) also reported that teachers would not use ICT if schools had little to no funding for ICT equipment, despite their belief that ICT has the potential to change education and their willingness to use it. Similarly, the Programme for International Student Assessment (PISA) demonstrated that a quarter of school principals admitted that the shortages or inadequacy of digital technology were ‘hindering learning quite a bit’ or ‘a lot’ in their schools (OECD 2020b). In a more recent survey conducted among 1031 teachers in Germany and Spain during school closings, two-thirds claimed that their schools were not or inadequately equipped for distance education (Barlovits et al. 2021). Access to ICT equipment allows teachers to become acquainted with ICT, which may be related to the frequency of teachers’ contact with their students and their perceived preparedness for distance education during school closing.

Teachers’ ICT self-efficacy

Aside from these three ICT job resources, teachers’ beliefs about their ability to ‘organise and execute the courses of action’ necessary to be effective in particular situations, also known as self-efficacy (Bandura 1997, 3), can be another ‘decisive resource’ for teachers making rapid changes to teach remotely using ICT during school closings (König, Jäger-Biela, and Glutsch 2020) and a prominent personal resource according to the JD-R theory (Bakker and Demerouti 2017). Teachers’ ICT self-efficacy includes beliefs about their ability to use ICT for instructional purposes (Hatlevik 2017). A well-established theoretical framework that conceptualises teachers’ ICT competence is the Technological Pedagogical Content Knowledge (TPACK) model, which captures teachers’ professional knowledge of technology integration in the classroom (Mishra and Koehler 2006). According to the TPACK model, teachers’ self-efficacy in performing tasks with ICT is closely connected with their actual pedagogical practices using ICT (Elstad and Christophersen 2017; Knezek, Christensen, and Furuta 2019). Empirical studies have found that teachers’ beliefs about ICT do, in fact, influence their ICT-related adaptive pedagogical decisions (e.g., Ertmer et al. 2012). Teachers’ future actions, such as the implementation of ICT in school-related learning environments, are also predicted by their ICT self-efficacy (Hatlevik and Hatlevik 2018).

Not only is ICT self-efficacy related to teachers’ use of ICT for instructional reasons due to its role as a personal resource, but it is also associated with other ICT-related job resources as described by the JD-R theory. For instance, previous studies have indicated associations between attending professional training on ICT and ICT self-efficacy: Teachers who have taken part in training courses involving ICT report higher self-efficacy in this area (e.g., Goos and Bennison 2008). Teacher collaboration also has a positive association with teachers’ ICT self-efficacy for instructional purposes (Hatlevik and Hatlevik 2018). Similarly, ICT self-efficacy is tied to access to school equipment (Eickelmann and Drossel 2020). JD-R theory further claimed that self-efficacy as a personal resource could mediate the relationships between job resources and outcomes such as exhaustion and engagement (Xanthopoulou et al. 2007).

Taken together, in accordance with Bandura’s 1997 social cognitive theory and the JD-R theory (Bakker and Demerouti 2017), ICT job resources might precede teachers’ ICT self-efficacy in shaping their adaptations to distance education. Therefore, teachers’ ICT self-efficacy as a personal resource may serve as a mediator between the associations between various ICT job resources and teachers’ adaptations to distance education.

The present study

As reviewed earlier, teachers’ perceived preparedness for distance education and the frequency of teacher – student contact are indicative of educational outcomes. Due to the fact that teaching and communication depend crucially on ICT during school closings, it is reasonable to suspect that job and personal resources related to teachers’ ICT use would be associated with their psychological and behavioural adaptations to the new job demands of distance education. However, there is a scarcity of research examining the potential role of ICT resources that might contribute to perceived preparedness for distance education and the frequency of teacher – student contact.

The aggregation of research evidence we surveyed so far pointed to potential positive associations between ICT-related resources––training, collaboration, school equipment, and self-efficacy in the area of ICT––and teachers’ perceived preparedness for distance education as well as the frequency of teacher – student contact during COVID-19 (visually represented in Figure 1). ICT self-efficacy as a personal resource also appears to play a mediating role in the relationship between ICT job resources (training, collaboration, equipment), and the frequency of teacher – student contact, as well as teachers’ perceived preparedness for distance education. Although each path of the schematic model was supported by existing empirical evidence, this model has not been investigated to date mainly due to a lack of records on teachers’ experience with distance education during the COVID-19 pandemic, as well as reports on their prior ICT-related experiences.

Figure 1. Schematic structural equation model.

Note. Control variables include school level, school type, teachers’ gender, and work experience.

In sum, we are interested in both the direct effects of ICT-related job and personal resources on perceived preparedness for distance education and the frequency of teacher – contact, and the indirect effects of ICT self-efficacy among these associations. Therefore, we will specifically examine the following hypothesis:

Hypothesis 1.

Teachers’ frequency of contact with students and perceived preparedness for distance education are positively associated with the number of professional training courses (ICT training), collaboration with colleagues (ICT collaboration), and access to equipment in schools (ICT equipment) in the area of ICT.

Hypothesis 2.

Teachers’ frequency of contact with students and perceived preparedness for distance education are positively associated with the amount of ICT training, collaboration, and equipment through their ICT self-efficacy.

We included school level, school type, teachers’ gender, and work experience as control variables in the model. These variables might be related to teachers’ adaptations to distance education in general (e.g. Tschannen-Moran et al. 1998), and are therefore included as covariates in the present study.

Method

Participants

The present study draws on data from an online survey carried out in German-speaking countries from May to June 2020 during the school closing related to the COVID-19 pandemic. The online survey was composed in German and circulated via a teacher training website’s newsletters and X. The survey was designed in accordance with APA Ethics Code (American Psychological Association 2002) and included an introduction with comprehensive information regarding the survey’s content, purpose, and responsible organisation and personnel, allowing participants to make an informed decision about participation. We noted explicitly in the survey’s introduction that the study was examining teachers’ opinions of digitisation processes in schools and classrooms, as well as the usage of digital media in teaching. The survey focused on teachers’ self-perceived digital competencies, school resources, teaching strategies, and online teaching. We also guaranteed confidentiality and anonymity to maintain the trust of participants. Although we cannot confirm that all participants were in fact practicing teachers, it is highly unlikely that others participated in the study because the survey was only delivered to teacher-only groups. In total, N = 1103 teachers participated in the survey (M_age = 45, SD_age = 11; female = 72.5%; primary school = 23.5%, secondary school = 67.7%, Gymnasium = 29.6%; missing = 8.8%). The most common subjects taught by participating teachers were German (40.4%), Mathematics (36.6%), and English (22.7%). Teachers had on average 17.1 years of teaching experience in schools (SD = 11.64). The sample was biased towards German population as the majority of the participants were from Germany (82.4%), 1.4% were from Austria, and 0.5% from Switzerland (15.7% missing). Furthermore, all 16 federal states of Germany were represented in our sample, with most teachers from Bavaria (37.6%, n = 339) and Saxony-Anhalt (22.1%, n = 199). In Austria, seven states were represented in our sample, with most teachers (26.7%, n = 4) from Steiermark and another 26.7% from Tirol. In Switzerland, 66.7% (n = 4) were from Zürich, one teacher was from Fribourg and another from Appenzell Innerrhoden. No information on teachers’ socio-economic status was available.

In a larger context, the language, school characteristics, as well as the COVID-19 policies were akin in Germany, Austria, and Switzerland. These countries had comparable timetables and procedures for closing and reopening schools during the first wave of COVID-19 lockdown in Spring 2020. For example, in Germany, the school shutdown started from March 13 was generally consistent throughout federal states (Stage et al. 2021). Similarly, all educational institutions closed from March 16 in both Austria (Zartler, Dafert, and Dirnberger 2021) and Switzerland (Tomasik, Helbling, and Moser 2021). The total closure days during the first wave of COVID-19 were also alike, with 104 days in Germany, 111 days in Austria and 133 days in Switzerland (OECD 2020a).

Instruments

We measured our construct with a single item, due to the fact that the participating teachers were facing high workloads and had limited time available to them. According to Gogol et al. (2014), single-item measures may represent psychometrically sound alternatives when long scales are not applicable.

Perceived preparedness for distance education

Teachers’ perceived preparedness for distance education are teachers’ self-estimates of readiness to teach during school closings. It was assessed with a single-item measure on a four-point Likert scale: ‘How prepared do you feel for the current situation concerning distance learning during school closings?’ (1 = ‘not at all prepared’ to 4 = ‘well prepared’).

Frequency of teacher – student contact

Teacher – student contact during school closings are momentary virtual encounters between teachers and students. Teachers reported the frequency of their contact with students during the school closing by answering ‘How often do you currently have contact with your students?’ The item was measured on a five-point Likert scale ranging from ‘1 = not at all’ to ‘5 = every day’.

Professional training in ICT

Teachers’ self-reported professional training in ICT was assessed with a single-item measure asking for the number of professional training courses that teachers had attended in the last two years on ICT-related topics, not including the time of school closings caused by COVID-19. The original wording was ‘Before COVID-19, how many professional training courses or workshops have you attended in the last two years that were directly related to digital technologies?’ with an open response format.

Collaboration experiences with ICT during COVID-19

Teachers’ collaboration with colleagues in the area of ICT during school closings caused by COVID-19 was assessed with a three-item measure from Bos et al. (2016). The established measure included the following anchor item: ‘How often does the following situation occur in your school during the COVID-19 pandemic?’ An example item was ‘I meet with colleagues in my school to systematically promote the use of digital media in the classroom’, with responses ranging from ‘1 = never’ to ‘5 = at least once a week’ (see Appendix for all the items). The measure has good reliability with α = .84.

ICT equipment in schools

We measured ICT equipment in schools on a scale adapted from Breiter et al’. work (Breiter, Welling, and Stolpmann 2010). The scale measured the accessibility of the following seven different technologies in schools with a dichotomous response format (yes/no): stationary computer, laptop classroom set, tablet classroom set, projector, interactive whiteboard, digital camera, wireless LAN. We summed up the responses and used the sum score for the present analysis. The responses ranged from 0 technology to all seven technologies accessible.

Teachers’ ICT self-efficacy

Teachers’ ICT self-efficacy was assessed with a well-established scale capturing teachers’ self-assessment, i.e. competence belief, regarding their technological pedagogical content knowledge (TPACK) (Koehler and Mishra 2009). We used an existing and validated German version of this scale (Bos et al. 2016). The six-item measure ranged from ‘1 = do not agree at all’ to ‘5 = completely agree’. A sample item was ‘I have the technical skills I need to use digital media in my classroom’ (see Appendix for the complete scale). The measure has good reliability with α = .93.

Data analysis

We tested our hypotheses with a recursive path model (Figure 1), in which we included ICT training, ICT collaboration, and ICT equipment as independent variables. Teachers’ frequency of contact with students and their perceived preparedness for distance education served as dependent variables and ICT self-efficacy was modelled as the mediator between the independent and dependent variables. We estimated both the direct and indirect effects together with inferential tests (Hayes 2017; Imai, Keele, and Tingley 2010). We also controlled for the school level (primary or secondary school), school type (Gymnasium¹ or non-Gymnasium) teacher’s gender, and work experience in the model. Observed variables were normalised before entering the analysis conducted with lavaan 0.6–7 (Rosseel 2012) running in R 3.6.2 (R Core Team 2019). The results were later confirmed with Mplus 7.0 (Muthén and Muthén 2010). In terms of goodness of fit, we included global fit indices commonly used in the field (Hu and Bentler 1999; McDonald and Ho 2002): the Yuan-Bentler scaled chi-square (mean-adjusted test statistic robust to non-normality), comparative fit index (CFI), Tucker and Lewis index (TLI), goodness-of-fit index (GFI), root mean square of approximation (RMSEA), and standardised root mean residual values (SRMR). CFI, TLI, and GFI values greater than .95, RMSEA smaller than .06, and SRMR smaller than .08 are commonly regarded as indicators of a good fit.

Our survey responses contain a relatively high number of missing values due to early termination of the online survey. We decided to keep these cases because the estimators were fitted with maximum likelihood robust standard errors (MLR). MLR has been found to result in unbiased parameter estimates even with a high percentage of missing data (Enders 2001). Analyses of missing data showed that secondary school teachers had a higher percentage of missing data on frequency of teacher – student contact (r = −.10, p < .001) and perceived preparedness for distance education (r = .11, p < .001) than primary school teachers. Teachers with more years of teaching experience had more missing data on the contact scale (r = .10, p < .001). However, the effect sizes were small and we did not find a systematic bias due to the missing data. Therefore, missing data was handled with the full information maximum likelihood approach (FIML) to preserve the greatest amount of information (Savalei and Rhemtulla 2012).

Results

Descriptive statistics and intercorrelations

Descriptive statistics of all observed variables (centred but not normalised) are presented in Table 1. Results showed that the frequency of teacher – student contact was significantly and positively associated with ICT training (r = .14, p < .001) and ICT collaboration (r = .24, p < .001), as well as ICT equipment (r = .10, p < .01). In the same direction, teachers’ perceived preparedness for distance education was positively and significantly correlated with ICT training (r = .21, p < .001), ICT collaboration (r = .32, p < .001), and ICT equipment (r = .26, p < .001). ICT self-efficacy was positively related to all other variables (see Table 1). We found no intergroup variations among German, Austrian, and Swiss teachers for all the observed variables.

Table 1. Descriptive statistics and intercorrelations for observed variables.

Variables	M(SD)/%	Range/Category	Missing	2	3	4	5	6	7	8	9	10
1. ICT training	3.90 (4.16)	0–22 (times)	255 (23%)	.22***	.14***	.24***	.14***	.21***	.06	−.04	−.04	.04
2. ICT collaboration	2.76 (1.33)	1–5	501 (45%)		.18***	.30***	.24***	.32***	−.07	−.05	.03	−.02
3. ICT equipment	4.43 (1.46)	0–7	382 (35%)			.20***	.10**	.26***	.21***	.16***	−.12*	.06
4. ICT self-efficacy	3.53 (.93)	1–5	350 (32%)				.24***	.41***	.11*	.11**	−.10	−.17***
5. Frequency of contact	2.27 (1.03)	1–5	162 (15%)					.21***	.12**	.14***	−.00	.04
6. Perceived preparedness	2.28 (1.18)	1–5	69 (6%)						.11**	.17***	−.12**	−.11**
7. School level	75.36% secondary	0 (primary)/1 (secondary)	129 (12%)							.35***	−.22***	−.06
8. School type	29.57% Gymnasium	0 (non-Gymnasium)/1 (Gymnasium)	129 (12%)								−.15***	−.04
9. Gender	72.54% female	0 (male)/1 (female)	167 (15%)									.01
10. Work experience	17.10 (11.64)	0–45 (years)	177 (16%)

Note. Observed variables were centred. *p < .05; **p < .01; ***p < .001.

Teachers’ perceived preparedness for distance education and the frequency of teacher – student contact: associations with ICT training, collaboration, and equipment

We first examined the overall goodness-of-fit of the model shown in Figure 2. The model demonstrated good fit with the data: χ² (4, N = 1077) = 9.91, p < .05. CFI = .99, TLI = .95, RMSEA = .03, GFI = .99, SRMR = .01. The paths of the model are depicted in Figure 2.

Figure 2. Empirical structural equation model.

Note. All coefficients are standardised and significant at p < .05. Non-significant paths remained in the model, but are not displayed. Interested and control variables were differentiated with line weights

Regarding the direct paths between independent variables and teachers’ adaptations during the pandemic, we found that the frequency of teacher – student contact was significantly associated with ICT collaboration (b = .19, 95% CI [.11, .27], p < .001), but not with ICT training (b = .06) and equipment (b = .01). On the other hand, teachers’ perceived preparedness for distance education during the pandemic was significantly associated with all three job resource variables: the number of ICT training courses that teachers attended (b = .09, 95% CI [.03, .16], p = .005), the level of ICT-related collaboration (b = .21, 95% CI [.13, .28], p < .001), and access to ICT-related equipment in schools (b = .15, 95% CI [.08, .21], p < .001).

Indirect effects through ICT self-efficacy

Next, we tested the indirect effects of ICT self-efficacy in order to examine whether ICT self-efficacy as a personal resource partially explained the relationships between ICT-related job resources (training, collaboration, equipment), and perceived preparedness as well as the frequency of teacher – student contact. As shown in Figure 2, ICT training courses (b = .18, 95% CI [.11, .25], p < .001), collaboration with colleagues on ICT (b = .25, 95% CI [.17, .32], p < .001), and their access to ICT-related equipment (b = .11, 95% CI [.04, .18], p = .004) were significantly and positively associated with higher levels of self-efficacy. ICT self-efficacy, in turn, was related to the frequency of teacher – student contact (b = .15, 95% CI [.07, .22], p < .001) and perceived preparedness (b = .26, 95% CI [.19, .33], p < .001). Significant indirect effects showed that teacher self-efficacy in ICT partially explained relations between ICT training and the frequency of teacher – student contact (b_ind = .03, 95% CI [.01, .04], p = .002), as well as between ICT training and perceived preparedness (b_ind = .05, 95% CI [.02, .07], p < .001). Similarly, teachers’ ICT-related collaborations were indirectly and significantly related to the frequency of teacher – student contact (b_ind = .04, 95% CI [.02, .06], p < .001) and perceived preparedness (b_ind = .07, 95% CI [.04, .09], p < .001) through ICT self-efficacy. Lastly, teachers’ access to ICT-related equipment in schools was associated with the frequency of teacher – student contact (b_ind = .02, 95% CI [.00, .03], p = .02) and perceived preparedness (b_ind = .03, 95% CI [.01, .05], p = .007) through ICT self-efficacy.

Discussion

The current study investigated the relationships between ICT job resources (training, collaboration, and equipment), ICT personal resource (self-efficacy), and teachers’ frequencies of contact with their students, as well as their perceived preparedness for distance education during the school closing. We discovered that teachers’ experiences on collaborating with colleagues regarding ICT during school closings were positively related to their perceived distance education preparedness, as well as the frequency of teacher – student contact with students. ICT training and equipment were only relevant to perceived preparedness but not to the frequency of teacher – student contact. Our findings indicate that the strength of relationships between different factors concerning ICT and teachers’ psychological and behavioural adaptations to ICT-facilitated distance education varies. Finally, we identified that ICT self-efficacy as a personal resource mediated the associations between ICT job resources and teachers’ perceived preparedness for distance education and the frequency of teacher – student contact. These findings will be discussed in the sections that follow.

Recent studies have shown that, in the face of the pandemic, teachers have expressed a desire for more support in working with ICT through continuing professional development offerings (e.g. Huber and Helm 2020). For instance, Moorhouse (2021) found that new teachers were feeling unprepared to begin teaching during COVID-19, due to insufficient preparations related to online teaching and remote working. Our findings extend such work by showing that past ICT training is indeed relevant for teachers’ perceptions of their preparedness to use ICT for distance education, especially in critical times. This finding was in line with the larger body of evidence about the positive associations between teacher preparedness and teacher training (e.g. Boe, Shin, and Cook 2007; Brown, Lee, and Collins 2015; O’Neill and Stephenson 2012). But, more intriguingly, after taking teachers’ ICT efficacy into account, the number of ICT training courses attended was not found to be directly related to teachers’ actual behaviours––their frequency of contact with students during the school closing. This finding is similar to previous studies that examined the intricate relationships between teacher training, self-efficacy, and actual pedagogical actions (e.g. Sang et al. 2010). For instance, Zhao and Bryant (2006) found that state-mandated technology integration training alone did not lead to higher levels of technology integration among a sample of American teachers. One possible explanation for this might be that, despite the positive impact of professional training on teachers’ beliefs about their ICT competence (e.g. Giles and Kent 2016), teachers might still need actual hands-on experience and project-based team work using ICT to be able to implement new technologies in everyday teaching (e.g. Paraskeva, Bouta, and Papagianni 2008).

Our findings also highlight the relevance of teacher-reported collaborative experiences for both the frequency of their actual contact with students and their perceived preparedness for distance education. This is in line with previous studies investigating the importance of having a network of colleagues, either within schools or in professional communities, that teachers engage with on topics of adopting ICT-based instructional practices (e.g. Dexter, Seashore, and Anderson 2002; Hatlevik 2017). Similarly, a recent mixed-method study discovered that connecting with colleagues had been one of the most prominent job resources for Dutch teachers during COVID-19 (Kupers, Mouw, and Fokkens-Bruinsma 2022).

Additionally, we found that ICT equipment was, similar to ICT training, positively associated with teachers’ perceived preparedness for distance education, but not with the actual frequency of teacher – student contact. In this sense, ICT equipment may be a distal factor for teachers’ actual behaviour. Accordingly, other studies have also shown that the mere existence of ICT infrastructure in schools will not affect teachers’ ICT usage for instructional purposes if the teachers are not confident enough to make use of them (Mumtaz 2000). The results of International Computer and Information Literacy Study (ICILS) 2013 also showed that ICT equipment at school were mostly not associated with the frequency of computer use for instructional purposes (Drossel, Eickelmann, and Gerick 2017). Along with these findings, our results indicated that the access to ICT equipment alone is insufficient for utilising ICT to maintain contact with students.

Lastly, as we found that ICT self-efficacy was positively associated with all three ICT job resources, as well as with teachers’ perceived preparedness for distance education and the frequency of teacher – student contact, the present study illustrates the key role of ICT self-efficacy in bridging job resources and teachers’ adaptations to distance education using ICT. This finding is in line with the key propositions of the JD-R theory: Personal resource such as self-efficacy, not only directly contributes to the positive outcomes (e.g. engagement, performance, adaptation), but also mediates the relationships between the job resources and outcome variables (e.g. Xanthopoulou et al. 2007). For instance, Llorens et al. (2007) found that Job resources (control over time and task) have a favourable influence on self-efficacy, which has a delayed effect on engagement among university students working with ICT. Many empirical studies have already emphasised the prominent contribution of self-efficacy to teachers’ actual instructional practices using ICT (e.g. Drossel, Eickelmann, and Schulz-Zander 2017). The current study not only reconfirms such findings, but also positions ICT self-efficacy in relation to ICT job resources and teachers’ psychological and behavioural adaptations to distance education.

Limitations

Although the current findings were among the first to untangle the relevant ICT job resources involved in teachers’ psychological and behavioural adaptations to distance education during the school closings, it also suffered from four inevitable issues. First, the majority of our sample were teachers from Germany. The ICT-related infrastructures in German schools were found to be lacking compared to U.S. counterparts (e.g. Gerick, Eickelmann, and Labusch 2019). Furthermore, the realisation and implementation of distance education during the school closing were completely up to each school in Germany (Klieme 2020). The lack of technical infrastructure combined with the great diversity in the practices of distance education in Germany may lead to generalisability issues in our findings. Although we did not identify any significant intergroup variations among German, Austrian, and Swiss teachers in our sample, a replication study conducted with other countries or regions would be crucial to further establish the findings of the present study.

Second, our data were cross-sectional with only one time point. The causal paths between ICT-related resources and perceived preparedness and the frequency of teacher – student contact cannot be established with the current design. The results should be interpreted with caution, as there may exist reciprocal effects among our examined independent and dependent variables, such as that teachers with high self-efficacy might attend more training courses. Despite the promising findings regarding the associations between ICT-related job resources, the frequency of teacher – student contact, and perceived preparedness via ICT self-efficacy as a personal resource, further research utilising a longitudinal design with multiple points of measurement would be required to investigate the causal links.

Third, teachers’ adaptations to distance education were measured with single-item instruments, due to concerns about time constraints teachers were facing during school closings. Although single-item measures may provide psychometrically sound substitutes when extensive scales are not available (Gogol et al. 2014), we acknowledge a more extensive scale designed to measure how prepared teachers felt in dealing with distance education will be more desirable. Future investigations into teachers’ psychological and behavioural adaptations to difficult teaching situations should develop comprehensive scales that better met the psychometric requirements of validity”.

Forth, we lacked information regarding the school where teachers were working, thus we could not account for school-level variations in the analyses. A multilevel model would be appropriate for variables such as ICT collaboration which has a nested source of variability – collaborations often take place within one institution. Since it is likely that variability exists both between teachers and between schools, the conclusion maybe fragmentary as a source of variability has been neglected (Gelman and Hill 2006; Snijders and Bosker 2012).

Finally, our study relied solely on teacher self-reports as we were primarily interested in teachers’ beliefs and behaviours during school closings. This method may raise concerns regarding the accuracy of their estimates of the frequency of teacher – student contact with their students or their preparedness for distance education. Apart from social desirability effects, shared method variance might also have biased our results (Podsakoff and Organ 1986). Future research should therefore validate our findings by including other sources of information, such as student reports or classroom video data. However, considering the lack of research on how relevant job and personal resources in ICT influenced teachers’ adjustments to distance education during COVID-19, we would conclude that the merits of our study outweighed the shortcomings.

Implications and future directions

The post-COVID Great Online Transition (GOT) urgently call for supporting educators in the area of distance education more than ever (Tondeur et al. 2023). Our findings point to two factors that might support teachers’ adaptations regarding distance education: teacher collaboration and ICT self-efficacy.

First, the present findings accentuated the critical role of teacher collaboration for both the frequency of teacher – student contact and teachers’ perceived preparedness for distance education during school closings. Both our study and others have identified that teacher collaboration had a great impact on teachers’ motivations to use innovative technology and perseverance to overcome obstacles in challenging times (Li and Choi 2014, 20; Strudler and Hearrington 2008). Despite the benefits of teacher collaboration, German teachers rarely make use of this opportunity. In a national investigation, Welling et al. (2016) found that only about 37% of the teachers in Germany had exchanged materials with colleagues that support the use of digital tools during instruction. Similarly, only a minority of the teachers (32%) reported that they had used a learning management system (LMS) that all teachers could store their instructional materials (Welling, Lorenz, and Eickelmann 2016). The lack of teacher collaboration in the area of ICT combined with evidence about the importance of collaboration emphasised the necessity of cultivating a strong professional network that supports each member for using ICT innovatively and effectively (Dexter, Seashore, and Anderson 2002).

Second, we found that the associations between the frequency of teacher – student contact and ICT job resources are only significant through ICT self-efficacy (except for ICT collaboration), marking ICT self-efficacy as an essential mediator, similar with the proposition of the JD-R theory. Bandura (1997) stated that individuals’ self-efficacy was key to their performance in a specific area, for reasons that self-efficacy could affect their thought processes, levels of persistence, degrees of motivation and affective states regarding tasks within the same area, thereby influencing individuals’ performances. JD-R theory also posited that self-efficacy may buffer the negative impact of job demands on long-term health and performance (Bakker and Demerouti 2017). Moreover, this buffering effect could be particularly influential when job demands are high (Kyriacou 2001), such as the case with teaching during COVID-19. Therefore, it is important to provide training opportunities and resources that promote teachers’ ICT self-efficacy. As the current findings indicate, ICT training, collaboration, and equipment were all significantly associated with ICT self-efficacy, making them powerful candidates for both supporting teachers in the field during the pandemic and preparing pre-service teachers who will enter the profession in the near future. Recent advances in evaluating multidimensional ICT self-efficacy (e.g. Rubach and Lazarides 2021) would also be a foundational step towards cultivating teachers’ ICT competency beliefs.

As the current findings exhibited great overlaps with the research evidence on the factors affecting teacher’s ICT usage and adoption (e.g. Backfisch et al. 2021; Drossel, Eickelmann, and Gerick 2017), it might be indicative that teachers’ instructional beliefs and behaviours could be studied more closely through the lens of ICT integration. For instance, examine teachers’ instructional behaviours during school closings through the Technology Acceptance Model (TAM) (Davis 1989; Scherer and Teo 2019) – a framework that describes the technology integration as a function of motivational variables as well as external variables such as social norms and facilitating conditions (Taherdoost 2018).

We would also like to point out a few future directions for this line of research. First, both the present and previous studies have focused on the mere frequency of teacher – student contact, while little is known about the quality of these interactions. Investigations into the content and quality of teacher – student contact, as well as the actual academic and psychosocial outcomes of this contact would be highly relevant to supporting students at risk. Second, as teachers get more experience with online education post-COVID, the relationships between ICT resources and their adaptations may change over time. Therefore, longitudinal expansions of the present research, grounded in experiences of teachers and students, might render developing patterns obvious.

Acknowledgments

We would like to thank Jennifer Quast who supported the data assessment decisively.

Disclosure statement

In accordance with Taylor & Francis policy and our ethical obligations as researcher, we are reporting this research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. No financial interest or benefit has arisen from the direct applications of this research.

Data availability statement

Sample dataset and analysis script are free and openly available at the project’s OSF page: https://osf.io/8b5gp/?view_only=b7f434b6b29d4de3bda18a9f5f51f662.

Additional information

Funding

This work was supported by the Deutsche Forschungsgemeinschaft [491466077].

Notes on contributors

Yizhen Huang

Yizhen Huang is a postdoctoral researcher in the Department of Education at the University of Potsdam in Germany. She received her Ph.D. in Education and Psychology from the University of Michigan’s Combined Program in Education and Psychology in Ann Arbor. Her research interests include visual representation and observational learning, expertise development, and the use of eye-tracking and virtual reality technologies in educational settings.

Rebecca Lazarides

Rebecca Lazarides is a professor of School and Instructional Research at University of Potsdam, Germany. Her current research focuses on teaching quality, student motivation and emotion, teacher education research, teacher competencies, and teaching and learning in heterogeneous groups.

Dirk Richter

Dirk Richter is a professor of Educational Research in the Educational Sciences at University of Potsdam, Germany. His research interests include professional competencies of teachers, professional development, collaboration of teachers, and virtual reality in teacher training.

Notes

1. In Germany, the Gymnasium is the academic secondary school from grades 5 to 12 or 13.

Appendix

Teachers’ ICT self-efficacy

1. I have the technical skills I need to use digital media in my classroom.

2. I can select digital media that can be used to better teach the subject content of my lessons.

3. I can select digital media that enhance student learning.

4. I can design my lessons to appropriately combine the content of my subject, the digital media used, and teaching methods applied.

5. I can select digital media for my instruction that enhance both what I teach and how I teach as well as what students learn.

6. I have strategies that integrate subject content, digital media, and teaching methods that I have learned about to use them together in my teaching.

Collaboration experiences with ICT during COVID-19

How often does the following occur since school closings in the course of the spread of the COVID-19 at your school?

1. I share materials that involve the use of digital media in the classroom with colleagues at my school. [Exchange]

2. I make arrangements with colleagues on how we can design lessons using digital media based on division of labour. [Synchronization]

3. I meet with colleagues at my school to systematically promote the use of digital media in the classroom. [Co-construction]