Trying to define and label what people do with digital technologies has always been an interesting area to address. A literature review of this topic goes beyond the classic definition of digital natives proposed by Presky (2012), and it includes the work of Blank and Groselj (2014), who indicate that the use of Internet could be organized in three dimensions: amount of use, variety of different uses and types of use. The type or purpose of use is highly relevant nowadays due to the autonomous use of Internet available on laptops and smartphones. This is especially significant for student teachers, who as many other university students, take personal decisions about how to use technologies with several purposes, not only in activities related to learning and teaching (Cerda et al., 2022b).

The Chilean education system has a long tradition of integrating digital technologies in initial teacher education (Brun & Hinostroza, 2014). However, remote learning due to COVID-19 lockdown forced even more the adoption of digital technologies use. As in other countries, the commonly called “emergency remote teaching period” at higher education institutions represented, for professors and students, an immeasurable spent of energy in order to take  concrete advantages of the potential that digital technologies offer (Sum & Oancea, 2022). The academic community demanded, from technology specialists, effective solutions to the challenge that remote teaching represented. Concerning student teachers, they had to deal with the enforced use of digital technologies for academic purposes in paralell with other personal purposes of uses of these tools.

Although the relevance of the topic, a few research has been done on understanding the implicit contribution in the development of digital competences during the emergency remote teaching period. Research of digital competences has mainly followed the development of generic digital competences (Carretero et al., 2017; Ferrari, 2013) and digital competences for educators (Redecker, 2017). In the case of student teachers, a few research has considered both frameworks (Reisoglu & Cebi, 2020). In Chile, several studies have replicated this trend, separating both frameworks, mainly due to the fact that not all the universities that deliver degrees in education have strong policies to explicitly promote computer literacy, general digital competences or digital competences for educators (Tapia et al., 2020).

The goal of this study is twofold. First, to compare the level of academic use of digital technologies between student teachers with limited experience in remote learning with those who spent four academic semesters learning in that academic environment. Second, to analyse the effect of interaction among variables related to academic digital competences (periods of measurement, sex, number of years in the student teacher program). The results of this study showed relevant information to better understand how the virtual learning experience supported the development of digital competences in student teachers during the COVID-19 lockdown.

A total number of 1,338 student teachers participated in this study (43.3% men and 56.6% women) divided in two periods of measurement. The first measurement considered 615 participants (35.9% men and 64.1% women) with limited experience in remote learning. It was taken during the first semester of the year 2020. The second measurement considered 723 students (49.7% men and 50.3% women), with almost two years experiencing remote learning. It was taken during the second semester of the year 2022. The emergency remote teaching period, due to COVID-19 lockdown, took place in Chile since March 2020 until December 2021 (four academic semesters). The information was gathered using a 17 items scale about academic use of digital technologies. This instrument, which is part of the Scale of Purposes of Use and Digital Competences, measures frequently of use of digital technologies with academic, entertainment, social and economic purposes (Cerda et al., 2022a). The items for each purpose of use were based in the following five digital competences defined by DIGCOMP (Ferrari, 2013) A = Browsing, searching and filtering data, information and digital content; B = Managing data, information and digital content; C = Interacting through digital technologies; D = Sharing through digital technologies; E = Developing digital content. Two strategies to collect data were used in this study. The information collected from the first measurement (in 2020) was obtained digitally through QuestionPro. The information collected from the second measurement (in 2022) was paper-based. In both cases, participants received information related to the objective of the study and the relevance of their voluntary participation. To participate, the student teachers had to read and sign an informed consent form approved by the university’s Scientific Ethics Committee. Data analysis of the two measurements considered several steps. First, the collected information was examined in terms of accuracy of data entry and missing values. Second, after reaching adequate level of internal consistency, five variables were created considering the digital competences declared. Third, the variables were assessed in terms of normality, reviewing their level of skewness and kurtosis following the criteria (-1 to +1) suggested by Muthen and Kaplan (1985). Fourth, the independent t Student test was used to compare the two measurements within the five academic use variables. Finally, a MANOVA test was used to explore if there was a relationship between the measuring time periods and years in the program, and the measuring time and sex by the type of digital competences.

Results from t Student tests showed differences in all the digital competences. Regarding Browsing, searching and filtering data, information and digital content, participants in 2022 got higher scores (M = 3.74, SD = 0.90) than the ones in 2020 (M = 3.50, SD = 0.99), t(1336) = -4.765, p < .001. Cohen’s d (-0.261). The same happened with others variables: Managing data, information and digital content (M = 3.74, SD = 0.96 versus M = 3.63, SD = 1.03), t(1336)= -2.014, p 0.04. Cohen’s d (-0.111), Interacting through digital technologies (M = 4.19, SD = 0.87 versus M = 391, SD = 1.05), t(1336)=-5.234, p < .001. Cohen’s d (-0.287), Sharing through digital technologies (M = 3.31, SD = 1.15 versus M = 2.90, SD = 1.17), t(1336)= -6.409, p < .001. Cohen’s d (-0.352) and Developing digital content (M = 3.30, SD = 1.10 versus M 2.85, SD = 1.13), t(1336)= -7.455, p < .001. Cohen’s d (-0.409). MANOVA test could not find any interaction effect among variables considered. In conclusion, it can be stated that the emergency remote teaching period experienced for student teachers during four academic semesters allowed them to develop a few digital competences that can be used with academic purposes. Even though it is highly complicated to establish a cause-effect relationship among variables, the experience obtained for them during the remote teaching period might triggered new ways to use digital technologies for academic purposes. During this period, student teachers and professors did not receive any specific training in general digital competences or digital competences for teaching. All the strategies used were the result of personal initiatives implemented to experience an equivalent type of traditional on-site teaching. As Sum and Oancea (2022) establish, the scenario is not different to other contexts under similar circumstances.

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