1 Introduction
In the spring of 2020, COVID-19 lockdowns worldwide forced face-to-face teaching and learning activities to shift to remote learning (Meinck et al.,
2022). Almost overnight, across school levels and teaching subjects, various forms of delivering instruction emerged, the majority of which saw technological tools take a central stage and often revealed a lack of teachers’ knowledge and skills for using technology for teaching online (Ferri et al.,
2020; Marshall et al.,
2020). Initial studies report that inservice teachers encountered technical difficulties, challenges in motivating and engaging students (Ewing & Cooper,
2021) and lowered sense of self-efficacy (Ávalos et al.,
2022; Cardullo et al.,
2021; Pressley & Ha,
2021) frequently leading to negative views towards online teaching during lockdown (DeCoito & Estaiteyeh,
2022). Yet the experiences of the pandemic were not only negative: Teachers reported remote teaching to also be related to heightened flexibility and extension of their pedagogical repetoire to include a range of different resources and ways to support learners, which are not possible in physical classrooms (Cardullo et al.,
2021). Similarly, other studies found teachers stating the shift forced them to become more creative and develop new digital skills (DeCoito & Estaiteyeh,
2022; Shamir-Inbal & Blau,
2021). In fact, despite encountering challenges, in their study, DeCoito and Estaiteyeh (
2022) found teachers to report intending to integrate more digital elements into their teaching in the coming year. Along these lines, multiple studies conclude that the “new normal” of teaching and learning will be inherently hybrid (e.g., blended learning, flipped classroom), aiming to optimally balance the advantages offered by face-to-face and online learning (Bäcklund et al.,
2022; Marek et al.,
2021; Shamir-Inbal & Blau,
2021).
Additionally, from the perspective of student achievement, the literature reports contrasting effects of remote learning, ranging from negative (e.g., König & Frey,
2022) to neutral (Tomasik et al.,
2021) to positive (e.g., Cavanaugh et al.,
2022; Schramm et al.,
2021). Particularly with regard to K-12 education, a few studies have found positive outcomes of remote learning on student achievement to be related to 1) students’ familiarity with learning apps and online environments prior to lockdown (König & Frey,
2022) as well as to 2) teachers’ abilities to design high-quality remote instruction (e.g., Clark et al.,
2021). Thus, even in returning to “normality”, the road ahead seems to lie in further integration of educational technologies into teaching and learning settings combined with equipping both teachers and students with the knowledge and skills for their use.
The findings described until this point have emphasized the central role of the teacher for effectively adapting to educational disruptions such as the COVID-19 pandemic (e.g., Clark et al.,
2021; DeCoito & Estaiteyeh,
2022). Even under “normal” conditions, findings on the integration of technology into educational settings reinforce the centrality of the teachers’ role (e.g., Hixon & Buckenmeyer,
2009; Spiteri & Chang Rundgren,
2020; Tondeur et al.,
2017a). Thus, the increasing presence of technologies as both pedagogical tools and practices (i.e., educational technologies) as well as curricular content (i.e., developing students’ knowledge of and skills for using technology; UNESCO,
2021) will naturally reflect on the roles and identities of future teachers. This places a significant focus on understanding how to best prepare current preservice teachers experiencing this transition to the “new normal”. To date, few studies have investigated the impact of the pandemic on how preservice teachers view their professional future. One study among preservice English as a foreign language (EFL) teachers observing online teaching found that preservice teachers reported changes in their identity beliefs for online contexts, as well as heightened appreciation for developing technology integration abilities, and negative views towards online teaching (Gündogdu & Alkayalar,
2021). Romero-Tena et al. (
2021) found that students enrolled in an early childhood education course during the pandemic had lower self-reported teaching digital competencies (as described by the authors’ adaptation of the DigCompEdu framework; Redecker,
2017) compared to those having attended the same course the year prior to the pandemic.
Considering the ideal future of education to consist in optimizing the potential of both face-to-face and online teaching and learning, it becomes ever more crucial that post-pandemic teacher training institutions need to prepare prospective teachers for both settings (M. Jin,
2022) and attend to the factors influencing their technology integration, such as their attitudes and beliefs, knowledge and skills, access, and experiences (e.g., Farjon et al.,
2019). The literature generally outlines two types of barriers towards technology integration: first order barriers (i.e., challenges related to extrinsic factors and resources such as infrastructure, access, as well as teachers’ knowledge) and second order barriers (i.e., intrinsic obstacles such as teachers’ beliefs; Ertmer,
1999). The present study investigates the relations between the pandemic and relevant teacher-related factors addressing the following research question: How did the pandemic affect preservice teachers’ knowledge (first order barriers) and beliefs (second order barriers) related to teaching with technology? The findings are relevant for teacher training institutions, offering further insight into adequate preparation of future teachers for effectively integrating technology and teaching in the “new normal” educational landscape.
4 Results
Investigating our research question for potential effects of the pandemic on preservice teachers’ self-reported TPACK and beliefs, we conducted ANOVAs to assess main effects of cohort and experience as well as the interaction between the two. Regarding our first hypothesis expecting lower scores for pedagogy- and technology- related domains (H1), we found that compared to the TPACK of preservice teachers assessed prior to the pandemic, during lockdown mean ratings were lower on three subscales (i.e., TK, PCK, and TPK; see Table
1). Yet ANOVAs and respective post-hocs tests revealed none of these differences to be significant. Thus, our first hypothesis is rejected.
Table 1
TPACK and beliefs variables descriptives by cohort and by experience
PK | All experience levels | - | 3.69 (0.61) | 3.73 (0.55) | 3.76 (0.58) |
novice | 3.59 (0.57) | 3.52 (0.57) | 3.68 (0.53) | 3.62 (0.57) |
experienced | 4.00 (0.60) | 4.00 (0.71) | 3.84 (0.59) | 4.03 (0.51) |
CK | All experience levels | - | 4.19 (0.61) | 4.24 (0.59) | 4.22 (0.64) |
novice | 4.14 (0.63) | 4.15 (0.60) | 4.34 (0.51) | 4.10 (0.67) |
experienced | 4.33 (0.59) | 4.25 (0.62) | 4.07 (0.71) | 4.46 (0.51) |
TK | All experience levels | - | 3.38 (0.98) | 3.22 (0.93) | 3.55 (0.86) |
novice | 3.38 (0.92) | 3.36 (1.00) | 3.10 (0.98) | 3.46 (0.84) |
experienced | 3.58 (0.91) | 3.42 (0.96) | 3.44 (0.79) | 3.74 (0.86) |
PCK | All experience levels | - | 3.87 (0.63) | 3.80 (0.52) | 3.91 (0.60) |
novice | 3.81 (0.58) | 3.78 (0.59) | 3.88 (0.54) | 3.81 (0.59) |
experienced | 4.02 (0.61) | 4.04 (0.67) | 3.66 (0.47) | 4.10 (0.56) |
TPK | All experience levels | - | 3.79 (0.71) | 3.63 (0.82) | 3.73 (0.60) |
novice | 3.77 (0.64) | 3.76 (0.67) | 3.62 (0.74) | 3.81 (0.59) |
experienced | 3.91 (0.70) | 3.86 (0.77) | 3.85 (0.78) | 3.97 (0.63) |
TCK | All experience levels | - | 3.26 (1.00) | 3.29 (0.92) | 3.35 (0.88) |
novice | 3.30 (0.91) | 3.31 (0.94) | 3.25 (0.88) | 3.31 (0.89) |
experienced | 3.32 (0.98) | 3.17 (1.10) | 3.37 (1.02) | 3.44 (0.86) |
TPCK | All experience levels | - | 3.55 (0.77) | 3.63 (0.82) | 3.73 (0.60) |
novice | 3.60 (0.68) | 3.50 (0.73) | 3.56 (0.84) | 3.68 (0.59) |
experienced | 3.74 (0.73) | 3.63 (0.83) | 3.74 (0.79) | 3.84 (0.62) |
Beliefs_utility | All experience levels | - | 3.69 (0.80) | 3.72 (0.66) | 3.71 (0.71) |
novice | 3.71 (0.68) | 3.68 (0.74) | 3.71 (0.64) | 3.75 (0.64) |
experienced | 3.71 (0.85) | 3.71 (0.90) | 3.72 (0.72) | 3.70 (0.84) |
Beliefs_resp | All experience levels | - | 4.45 (0.66) | 4.38 (0.60) | 4.36 (0.70) |
novice | 4.43 (0.64) | 4.48 (0.64) | 4.37 (0.60) | 4.40 (0.65) |
experienced | 4.34 (0.73) | 4.40 (0.70) | 4.41 (0.63) | 4.27 (0.77) |
We did find significant cohort main effects for TK (
F(1) = 3.62,
p = 0.028) as well as for TPCK (
H(1) = 6.67,
p = 0.036). Post-hoc tests revealed these to arise from significantly higher post- compared to both pre- and during-lockdown cohorts for TK and between pre- with post-lockdown cohorts for TPCK (see Table
2). The increase in these two domains is consistent with and partially confirms our second hypothesis (H2), for which we expected higher scores in technology-related domains among our post-lockdown cohort compared to the other two groups. In addition, we found main effects of experience. Experienced preservice teachers scored higher than their novice counterparts on all seven domains (see Table
1), among which their scores on five domains were significantly higher: PK (
F(1) = 23.97,
p < 0.001), CK (
H(1) = 11.15,
p = 0.001), TK (
F(1) = 4.24,
p = 0.040), TPK (
H(1) = 5.75,
p = 0.017), and TPCK (
H(1) = 4.52,
p = 0.033).
Table 2
Summary of significant effects of cohort, experience, and their interaction
Cohort | TK | Post | > | Pre | p = 0.032 | pTukey | = 0.082 |
| | > | During | p = 0.031 | pTukey | = 0.079 |
TPCK | Post | > | Pre | p = 0.011 | pBonferroni | = 0.033 |
Experience | PK | Exp | > | Inexp | p < 0.001 | pTukey | < 0.001 |
CK | Exp | > | Inexp | p < 0.001 | pBonferroni | < 0.001 |
TK | Exp | > | Inexp | p = 0.040 | pTukey | = 0.040 |
TPK | Exp | > | Inexp | p = 0.017 | pBonferroni | = 0.017 |
TPCK | Exp | > | Inexp | p = 0.038 | pBonferroni | = 0.038 |
Cohort*Experience | CK | Post-exp | > | Pre-inexp | p < 0.001 | pBonferroni | = 0.004 |
| | > | Post-inexp | p < 0.001 | pBonferroni | < 0.001 |
| | > | Pre-exp | p = 0.029 | pBonferroni | = 0.432 |
| | > | During-exp | p = 0.002 | pBonferroni | = 0.227 |
PCK | Pre-exp | > | Pre-inexp | p = 0.007 | pTukey | = 0.073 |
| | > | Post-inexp | p = 0.011 | pTukey | = 0.114 |
| | > | During-exp | p = 0.021 | pTukey | = 0.189 |
| Post-exp | > | Pre-inexp | p < 0.001 | pTukey | = 0.005 |
| | > | Post-inexp | p < 0.001 | pTukey | = 0.009 |
| | > | During-exp | p = 0.006 | pTukey | = 0.070 |
Subsequently, investigating the interaction between cohort and experience, findings showed experienced preservice teachers to have the highest scores across TPACK domains, among which we found significant effects for the domains of CK and PCK. For CK, post-hoc tests showed that experienced preservice teachers reported significantly higher scores after lockdown compared to novice preservice teachers pre- and post-lockdown, as well as compared to experienced preservice teachers’ scores pre- and during-lockdown (see Table
2). With regard to PCK, findings showed that although novice preservice teachers tended to rate themselves higher during lockdown compared to their ratings prior to and after lockdown (see Table
1), overall, their scores were not significantly affected. In contrast, lockdown appeared to affect experienced preservice teachers, who showed significantly lower ratings during lockdown compared to both pre- and post-lockdown cohorts (see Table
2). Thus, our third hypothesis expecting stronger effects of lower pedagogy- and technology-related domains during lockdown for experienced compared to novice preservice teachers (H3), is partially confirmed for the domain of PCK. A final observation regarding TPACK: The only domain for which no effects of any predictors were found, was for that of TCK.
With regard to preservice teachers’ technological beliefs, no effects of cohort or experience emerged for either utility or responsibility beliefs (see Table
1). Interestingly, investigating the single items for group differences we found that only one item on the utility beliefs scale (i.e., “By using digital technologies, I can improve the quality of my teaching”; see Appendix
2, item bp1) showed a significant main effect of cohort (
F(2) = 3.910,
p = 0.021), with post-hoc tests showing this difference to arise from the comparison of pre- and post-lockdown scores (
p = 0.006,
pTukey = 0.015).
5 Discussion
The COVID-19 pandemic caused undeniable disruptions to education worldwide. Yet despite the struggles and challenges, the experience also resulted in some positive consequences, increasing insight into the potential of technologies for education across contexts (e.g., DeCoito & Estaiteyeh,
2022; Elçiçek,
2021). In this study we aimed to shed more light on how the pandemic affected preservice teachers’ evaluations of their professional knowledge for teaching in the digital era as well as their beliefs on the utility of technology for education and the responsibility of education systems for developing learners technological competences. Overall, four main findings emerged from our study. First, we found that, compared to preservice teachers prior to the pandemic, after the experience of lockdown, both novice and experienced preservice teachers appear more confident in their general technological knowledge (i.e., TK) as well as in their subject-specific knowledge for teaching with technology (i.e., TPCK). Second, consistent with the literature (e.g., Tai & Crawford,
2014; Wang et al.,
2018), we replicated findings of the positive effects of experience on preservice teachers’ TPACK, showing that, except for the domains PCK and TCK, those with experience had significantly higher TPACK scores compared to inexperienced novices. Third, we found initial evidence of experience-related advantages for CK and PCK, as post-lockdown experienced preservice teachers’ ratings for these domains were significantly higher than those of pre- and post-lockdown novices. Finally, the pandemic does not appear to have impacted preservice teachers’ beliefs on technology in educational contexts.
Our first finding of a significant cohort effect on TPACK relates to our first two hypotheses. Firstly, compared to prior to the pandemic, we expected preservice teachers during lockdown to experience challenges to their technology- and pedagogy-related domains, resulting in lower scores for these domains (H1). This hypothesis was rejected, as we found no significant decreases in TPACK domains between pre- and during-lockdown scores. Nevertheless, it is interesting to note, that although these differences did not quite reach significance, experienced preservice teachers revealed patterns in line with this first hypothesis, as the during-lockdown cohort showed a drop in PK, CK, and PCK. In contrast, inexperienced novices showed inverse tendencies across cohorts, revealing slight increases in these domains among the during- compared to pre- and post-lockdown cohorts. Drawing on research investigating inservice and preservice teachers’ teaching experiences during lockdown, several studies found that in addition to technological challenges, teachers mentioned pedagogy-related challenges such as engaging and motivating students (DeCoito & Estaiteyeh,
2022; M. Jin,
2022; Marshall et al.,
2020), integrating collaborative learning approaches (Mohamad Nasri et al.,
2020), as well as assessing and holding students accountable for their work (DeCoito & Estaiteyeh,
2022; Marshall et al.,
2020; Mohamad Nasri et al.,
2020). These findings could suggest that preservice teachers with previous teaching experience may be more susceptible to the interdependent complexity of educational settings and perceive shifts that appear to be predominantly technology-related to give rise to pedagogical challenges. In contrast, given their lack of experience in educational settings from a teachers’ perspective, novices may yet lack this sophisticated understanding of the strong interrelations between contextual factors and practice (see Brianza et al.,
2022; Mishra & Warr,
2021).
Our second hypothesis expected preservice teachers post-lockdown to have gained new technological knowledge and thus report higher scores on their technology-related domains (H2). This hypothesis could be partially confirmed, as we found fundamental technology-related domains (TK and TPCK) to be higher in the post-lockdown cohort compared to in the pre-lockdown. Interestingly, no effects of lockdown were found for TCK and TPK. This finding is in line with the conception of TPACK as a transformative construct (e.g., Angeli & Valanides,
2005; Mishra & Koehler,
2006; Schmid et al.,
2020) consisting of unique knowledge domains, with its hybrid domains being more than the summation of the core factors. In relation to this transformative view, the fact that we did not find effects of the experience of lockdown on TCK and TPK may be related on one hand, to the specificity of this experience—during which teachers mostly applied technology and pedagogy to their teaching subject (i.e., TPCK)—and, on the other hand, to the limited duration of this experience—proving too short to accumulate a wider range of experiences for developing more generic understandings of technology’s value for pedagogy (i.e., TPK) and content (i.e., TCK).
As a final point regarding the effects of the experience of lockdown, although these findings are only cross-sectional rather than longitudinal and are thus limited in their interpretation (see Section
6 for further discussion), they present initial evidence suggesting that preservice teachers may have drawn some benefits for their technology-related knowledge from the experience of remote learning. Several further studies report similar findings of the experience of lockdown to have been an opportunity for both inservice (e.g., DeCoito & Estaiteyeh,
2022) as well as preservice teachers (e.g., Bäcklund et al.,
2022; Elçiçek,
2021) to extend their knowledge of technological tools and resources, as well as being forced to develop new designs and approaches in their teaching. Taken together, evidence presents the experience of lockdown as an event giving rise to a period effect (i.e., experience similarly affecting all groups within a population; see Altman,
2014) and thus of relevance for comparative research as well as for the professional development of preservice and inservice teachers having experienced lockdowns.
With regard to our third hypothesis (i.e., expecting the effects of lockdown to be stronger among experienced preservice teachers compared to novices), we only found effects of the interaction between cohort and experience for the domains of CK and PCK, suggesting that experienced preservice teachers drew benefits from the experience of lockdown that novice preservice teachers did not grasp (partially confirming H3). In contrast and partially rejecting our hypothesis, no effects emerged for the technology-related domains. This indicates that the higher scores on TK and TPCK among preservice teachers having experienced lockdown were unrelated to prior teaching experience. Considering that the literature generally describes teaching experience to benefit preservice teachers’ knowledge development through supporting them in making connections between theory and practice (e.g., Darling-Hammond,
2006; Korthagen & Kessels,
1999), our findings align with this assumption with regard to preservice teachers’ knowledge of their subject matter (i.e., CK) and how to teach it (i.e., PCK). From this perspective, the unusual teaching and learning circumstances of lockdown might have challenged experienced preservice teachers to critically consider their CK and PCK from different perspectives and draw connections with their previously developed knowledge. Novices, in contrast, did make connections between the experience of remote education and more distal knowledge domains, but rather only matched their experienced counterparts in grasping the “surface” aspects related to technology.
Finally, addressing our fourth hypothesis on the stability of preservice teachers’ technological pedagogical beliefs across cohorts, our findings confirmed this expectation showing no changes across cohorts in self-rated beliefs. Contrary to our expectations, there was no difference between experience groups. These findings are particularly interesting for several main reasons: Firstly, from a methodological perspective, finding different patterns of effects for knowledge compared to belief measures reflects the nature of these constructs reported in the literature and thus supports these constructs as distinct as well as the validity of our measures. Secondly, it suggests that, although lockdowns drastically disrupted education on a global level, despite the significant challenges of this period our future teachers’ beliefs towards educational technology and their high regard for technology’s role in education remained intact, reflecting the nature of beliefs as relatively stable and not easily changed personal constructs (see Pajares,
1992). This is important given that research presents technological pedagogical beliefs to be related to aspects of technology use in educational settings (e.g., Bahcivan et al.,
2019; Kim et al.,
2013).
Overall, considering that in educational settings technology will only become increasingly more present (Dishon,
2021), future teachers need to develop the respective knowledge and beliefs for supporting effective integration of technologies into their teaching and learning activities (Starkey,
2020). Given that teacher training plays a crucial role for developing teachers’ TPACK (e.g., Wang et al.,
2018), shaping their beliefs (e.g., Nelson et al.,
2020), and preparing them to teach with technology (Tondeur et al.,
2012), it is positioned at the frontline of advancing teaching and learning within the “new normal”. Furthermore, the need for specialized and continuous training to keep up with the pace of technological developments or possible future disruptions is echoed even among inservice teachers by findings such as those of Scherer et al. (
2023), who found a curvilinear relationship between prior online teaching experience and teachers’ readiness to teach online during the COVID-19 pandemic. Thus, it is no longer sufficient for teacher education to prepare preservice teachers for face-to-face instruction, but rather it also needs to incorporate sufficient experiences with current technologies and their relevant discussions in educational settings.
6 Limitations and future research
The findings of this study need to be interpreted under the lens of several main limitations. First, this study did not use longitudinal data, thus we cannot make direct inferences on the effects of lockdown experiences on knowledge and beliefs, but rather these need to be viewed as cross-sectional comparisons. Second, for both constructs we relied on self-reported data, which in addition to the gaps between self-reported both TPACK and beliefs in relation to teaching practice noted above, are subject to an array of biases (Paulhus & Vazire,
2007). This point is particularly important to consider with regard to knowledge constructs (Park et al.,
1988), as an individual’s ability to report on one’s own knowledge is unavoidably affected by the very level of one’s knowledge (see Dunning-Kruger effect, Kruger & Dunning,
1999). Third, particularly with respect to beliefs, the literature emphasizes the importance of the quality of experiences for shaping one’s beliefs (e.g., Nelson & Hawk,
2020). In this study we were not able to investigate aspects related to the quality of our preservice teachers’ lockdown experience and thus, we cannot exclude that accounting for differences in the quality of experiences may have revealed other effects on beliefs. Finally, among experienced preservice teachers it was again not possible to control for the type or quality of their prior teaching experiences or for whether they were actively teaching during lockdowns. Future research is required to address these four points and more carefully investigate the mechanisms that support preservice teachers in assimilating professional knowledge through observing teaching and experiencing learning in exceptional situations.
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