Comparison of the teaching of digital competences between health science faculties in Andalusia and Catalonia

ORIGINAL ARTICLE Comparison of the teaching of digital competences between health science faculties in Andalusia and Catalonia Juan-José Boté-Vericad a,⁎ , Antonio Palacios-Rodríguez b , Montse Gorchs-Molist c , Carmen Cejudo-Llorente b a Facultat d’Informació i Mitjans Audiovisuals & Centre de Recerca en Informació, Comunicació i Cultura. Universitat de Barcelona, Spain b Department of Didactic and Educational Organization, Faculty of Education, University of Seville, Spain c Catalonia Emergency Medical System, Universitat de Barcelona, Spain Received 2 November 2022; accepted 4 January 2023 Available online xxxx KEYWORDS Digital competence; Digital Skills; DigCompEdu; Higher education; questionnaire; Health Sciences Abstract Introduction: Covid-19 brought great restrictions to face-to-face classes throughout the university system in Spain. In the field of health sciences, face-to-face teaching has been transformed into a virtual format. In most cases, teaching activities could not be prepared or planned, leading to unprecedented challenges for students and teachers, making it clear that some teachers have not developed an optimal level of digital skills. Materials and methods: This descriptive-comparative study aims to analyse the level of digital teaching competence among the university health sciences teaching staff in two Spanish autonomous communities: Andalusia and Catalonia. 561 teachers participated in the study and answered the DigCompEdu check-In questionnaire. Results: The results show how, in general, the level of their professed digital skills is basic, without significant differences between the participating communities. Further, technological mastery appears to be greater than pedagogical mastery with respect to one of the classroom technologies. The lack of technological training is highlighted and there is a discussion of the structuring of personalized learning itineraries by competences. Conclusions: With regard to possible limitations of the research, we could reflect on the different areas for improvement and how comparative studies between future works with similar characteristics should be approached. One of the main weaknesses lies in the types of samples used, since the intentional sampling method indicates that it is not random, therefore, the results found should be considered non-extrapolatable to other areas of knowledge. ⁎Corresponding author. E-mail addresses: [email protected] (J.-J. Boté-Vericad), [email protected] (A. Palacios-Rodríguez), [email protected] (M. Gorchs-Molist), [email protected] (C. Cejudo-Llorente). www.elsevier.es/edumed Educación Médica 24 (2023) 100791 https://doi.org/10.1016/j.edumed.2023.100791 1575-1813/© 2023 The Authors. Publicado por Elsevier España, S.L.U. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/). Incorporating probabilistic samples for each area to be studied in future studies will allow the collection of more representative data that can be extrapolated globally. © 2023 The Authors. Publicado por Elsevier España, S.L.U. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). PALABRAS CLAVE Competencia Digital; Habilidades digitales; DigCompEdu; Educación Superior; Ciencias de la Salud Comparación de la enseñanza de las competencias digitales entre las Facultades de Ciencias de la Salud de Andalucía y Cataluña Resumen Introduction: Covid-19 trajo importantes restricciones a las clases presenciales en todo el sistema universitario español. En ciencias de la salud, la enseñanza presencial se transformó en un formato virtual. En la mayoría de los casos, no ha sido posible planificar las actividades docentes, lo que ha supuesto un reto para alumnado y profesorado, en el que algunos docentes no han desarrollado un nivel óptimo de competencias digitales. Materials and Methods: Este estudio descriptivo-comparativo analiza el nivel de competencia digital docente de los profesores universitarios de ciencias de la salud de dos comunidades autónomas españolas: Andalucía y Cataluña. Participaron 561 profesores que respondieron al cuestionario DigCompEdu check-In. Resultados: Los resultados muestran que, en general, el nivel de competencias digitales impartidas es básico, sin diferencias significativas entre las comunidades participantes. El dominio tecnológico parece ser mayor que el pedagógico con respecto a una de las tecnologías del aula. Se debate sobre la estructuración de los itinerarios de aprendizaje personalizados por competencias. Conclusiones: En cuanto a las posibles limitaciones de la investigación, podríamos reflexionar sobre las diferentes áreas de mejora y cómo se deben abordar los estudios comparativos entre futuros trabajos de similares características. Una de las principales debilidades radica en los tipos de muestras utilizadas, ya que el método de muestreo intencional indica que no es aleatorio, por lo tanto, los resultados encontrados deben considerarse no extrapolables a otras áreas del conocimiento. La incorporación de muestras probabilísticas para cada área a estudiar en futuros estudios permitirá recopilar datos más representativos y extrapolables a nivel mundial. © 2023 The Authors. Publicado por Elsevier España, S.L.U. Este es un artículo Open Access bajo la licencia CC BY-NC-ND (http://creativecommons.org/licenses/by-nc-nd/4.0/). Introduction The teaching of digital competences is a matter of discussion in scientific literature. Digital competence in teaching is the framework under which teachers have to actively exercise their profession by using digital tools. However, digital competence does not only enable them to teach better, it also empowers them in their personal lives as digital citizens. However, the acquisition of digital competence in teaching does not happen all at once, it is a process that requires continuous training. The evolution of technology itself and the emergence of new pedagogical methodologies implies that there is an evolution in the acquisition of digital competences. In 2013 the European Commission published the Digital Competence Framework for citizens, based on five areas and 21 competences in which reference is made to digital literacy. 1 This framework describes the different competences needed for a fully digital society. In 2017, the joint research centre (JCR) of the European Commission published the European Digital Competence Framework for Teachers "DigCompEdu". 2 The objective of DigCompEdu was to define specific digital competences for teachers at all educational levels, based on 6 areas and 22 competences. The 6 areas are: 1. Professional commitment: the ability to use digital technologies to improve professional interaction, including communication with the organization, students, and families, and network collaboration with other teachers. 2. Digital resources: the ability to use digital resources for teaching, as well as to create and co-create, modify, organize, protect and share these resources. 3. Digital pedagogy: the ability to integrate digital technologies throughout the different stages of a studentcentred teaching-learning process. 4. Evaluation and feedback, focused on the use of digital tools and strategies to improve different evaluation approaches 5. Empower students, related to accessibility, inclusion and personalization, in addition to the active participation of students. 6. Facilitate the digital competence of students to be digital citizens. J.-J. Boté-Vericad, A. Palacios-Rodríguez, M. Gorchs-Molist, et al. 2 Several authors discuss the different existing international frameworks widely cited in the scientific literature. 3,4 The UNESCO ICT Competency Framework, 5 the mentioned DigCompEdu or the Common Framework of Digital Competence for Teachers in Spain 6 are some of these frameworks. All of these frameworks, and others, evaluate an instructor’s familiarity with the digital landscape across different areas such as technology confidence, experience, information literacy, or security awareness. These frameworks also indicate that teachers and other professionals as well as the wider population should acquire digital literacy. During the COVID-19 lockdown period, it was observed that many of the teaching staff of higher education institutions in several different fields lacked adequate training and digital competences to switch to distance learning. This lack of training and competences affected the design of classes, repeating the same face-to-face model and the nongeneration of digital materials suitable for distance learning. Students were also unsatisfied with these teaching models. 7,8 However, the scientific literature tends to focus on digital competences among students who will become teachers or current teachers in the field of education, such as future teachers, 9 primary school teachers 10 or secondary school teachers. 11 However, it also concerns other teachers who will work as specialists at higher education institutions. These teachers are not in a faculty of education, so digital competences should have a broader framework across all fields of knowledge, such as foreign language teachers 12 or health sciences teachers in Andalusian universities. 13 Nevertheless, these studies are still scarce, especially those focused on students, 14 and there is a need for studies in fields other than Education. This article aims to determine whether there are differences in the level of digital competences shown by professors of health sciences at Andalusian universities and Catalan universities. Our research questions are: RQ1 What are the digital teaching competences of Andalusian and Catalan university instructors in health sciences? RQ2 What are the differences between Andalusian and Catalan health science teachers? The article is composed of the following sections: Section 2 presents a literature review based on digital teaching competences in higher education, specifically in health sciences. Section 3 then describes the methods and materials used in this article. Section 4 shows the results. Finally, section 5 shows the discussion and conclusions and recommendations for future research on the development of digital competence in teaching in health sciences. Digital competences in professors Professors in all fields need to acquire digital competences and transmit them to their students. There are some studies in health sciences as a discipline or specifically in nursing. In relation to health sciences, 15 performed a study of Andalusian universities (Spain) with health sciences professors (N=300) using DigCompEdu Check-in translated into Spanish. 16 The goal of their study was to ascertain the differences concerning gender, teaching experience, and the domain of information and communication technologies. They found that younger professors had stronger digital competences than older professors, and females tend to teach virtually with a higher level of digital teacher competence (DTC). Those with between 4 and 14 years of teaching experience had a higher level of DTC. In Perú, 17 performed a study of health sciences teachers at a private university. They assessed the digital teacher competence (DTC) with a sample of 34 professors using the DTC version from. 18 They found no differences related to the gender of professors, and the lowest assessed area was digital security. They assessed the areas of information literacy, communication in virtual environments, digital security practices, and problem solving. Materials and methods Objectives This research aims to: 1. Validate the DigCompEdu model in the context of health sciences at universities (O1). 2. To understand the level of digital competence of professors of health sciences at two Spanish public universities (O2). 3. Identify whether there are significant differences between the levels of the Teaching of Digital Competence (TDC) at two Spanish public universities (O3). Sample 561 professors from public universities in the autonomous communities of Andalusia and Catalonia participated in the research, including 148 women and 113 men from Catalan universities were included in the research, along with 158 women and 142 men from Andalusian universities, all of whom are university professors in the field of health sciences. Their age and years of experience are presented in Table 1. In terms of the years of use of technologies among the professors from Andalusia, the majority of users have 10-14 Table 1 Percentages of age and teaching experience of the participants. Dimension Descriptor Andalusia Catalonia Age under 25 years old 0.7% 0.0% 25-29 years old 5.3% 0.8% 30-39 years old 16.0% 12.3% 40-49 years old 22.7% 33.0% 50-59 years old 35.3% 38.3% More than 60 years old 20.0% 15.7% Experience 1-3 years 13.3% 7.7% 4-5 years 10.0% 15.3% 6-9 years 8.0% 17.2% 10-14 years 15.3% 19.2% 15-19 years 10.7% 12.3% More than 20 years 42.7% 28.4% Educación Médica 24 (2023) 100791 3 years (22%) of experience while in Catalonia the largest group has between 1-3 years (23.8%) of experience (Table 2). The results seem to indicate that professors of Health Science in Catalonia have fewer years of experience with the use of technologies. Information collection instrument The information collection instrument was the "DigCompEdu Chek-in" questionnaire, 19 an analysis instrument of the European Framework for Digital Competence in Teaching DigCompEdu validated by. 20 This competence framework is considered to be the most suitable for assessing the TDC of university teaching staff through expert judgement. 13 The instrument is comprised of twenty-two items, which refer to the six areas of competence analysed by DigCompEdu and presented above: a) professional engagement (four items), b) digital resources (three items), c) digital pedagogy (four items), d) assessment and feedback (three items), e) empowering learners (three items), and f) facilitating learners' digital competence (five items). Note that the authors of the model consider that the first area of competence refers to professional competence; the areas of digital resources, digital pedagogy, assessment and feedback and learner empowerment to pedagogical competence; and the last one, facilitating learners' digital competence, to learner competence. Each of the items measures the different components of the competence framework: A Organisational communication; A2 Professional collaboration; A3 Reflective practice; A4 Digital continuing professional development; B1 Selecting digital resources; B2 Creating and modifying digital resources; B3 Managing, protecting and sharing digital resources; C1 Teaching; C2 Guiding; C3 Collaborative learning; C4 Self-directed learning; D1 Assessment strategies; D2 Evidence analysis; D3 Feedback and planning; E1 Accessibility and inclusion; E2 Differentiation and personalisation; E3 Active student participation; F1 Information and media literacy; F2 Digital communication and collaboration; F3 Digital content creation; F4 Well-being; and F5 Digital problem solving. At the same time, the questionnaire asks teachers to rank their self-perceived level of digital competence: when they start the questionnaire (pre) and when they finish it (post). The ranking system is as follows: Novice (A1), Explorer (A2), Integrator (B1), Expert (B2), Leader (C1) and Pioneer (C2). Data collection and analysis procedure The questionnaire was carried out in digital format, through the "Eu Survey" platform. The survey was sent from January to February 2022, and the data was collected in March 2022. The anonymity of the participants was always guaranteed. All the professors of each university were invited to participate by sending an institutional email. The reliability, discriminant validity and convergent validity of the questionnaire were calculated using Cronbach's Alpha, McDonald's Omega, Composite Reliability (CR), Average Variance Extracted (AVE) and Maximum Shared Variance (MCV) coefficients. In addition, and in order to compare these results, the method of inferential analysis between items and dimensions is used. For this purpose, the bivariate correlational analysis technique uses Spearman's ρcorrelation coefficient. The construct validity of the test was obtained by means of an exploratory factor analysis (EFA). The principal components method was used for factor selection. The factors obtained are orthogonally rotated using the Varimax method with Kaiser normalisation. Once the number of factors has been determined, a confirmatory factor analysis (CFA) is performed to check whether the theoretical measures of the model are consistent by modelling diagrams and using structural equations. 21 In other words, we test whether the data fit the hypothesised measurement model yielded by the exploratory factor analysis. The method used to test the theoretical model was weighted least squares (WLS), which provides consistent estimates in samples that do not conform to normality criteria. 21 For the latter procedure, AMOS software was used, which is capable of revealing hypothetical complex relationships between variables through structural equation modelling (SEM). In parallel, the non-normality of the data distribution was checked by a descriptive study considering skewness and kurtosis. The Kolmogorov-Smirnov goodness-of-fit test confirmed this conclusion, with a significance (p-value) equal to .000 for all elements (non-normal distribution). Results Reliability and validity The reliability of the questionnaire has been calculated using Cronbach's Alpha and McDonald's Omega coefficients. The results show excellent reliability levels in both Alpha (.972) and Omega (.960). An exploratory factor analysis (Table 3) was used to obtain the construct validity of the test. Previously, the applicability of factor analysis has been confirmed through the KMO test, with a statistically significant coefficient of .989 and Bartlett's sphericity test, with significance (pvalue) equal to .000 (factor analysis can be applied). The results, which explain 74.86% of the variance, determine the 6 theoretical factors proposed. The theoretical model that proposes exploratory factor analysis (EFA) is contrasted through confirmatory factor analysis (CFA). The factorial loads of the dimensions are between .75 and .96. These values denote high levels of correlation. In the Table 2 Years of use of technologies. Dimension Descriptor Andalusia Catalonia ICT time of use I don't use technology as an educational tool 1.3% 16.1% Less than 1 year 2.7% 20.7% 1-3 years 16.7% 23.8% 4-5 years 6.7% 19.5% 6-9 years 17.3% 8.4% 10-14 years 22.0% 0.0% 15-19 years 18.0% 0.0% 20 years or older 15.3% 11.5% J.-J. Boté-Vericad, A. Palacios-Rodríguez, M. Gorchs-Molist, et al. 4 same way, most levels of relationship between the different factors are also high, with an average of .62. The following indicators confirm the theoretical model proposed in accordance to 22 : Chi-Square (CMIN=398.128), goodness of fit index (GFI=.959), parsimonic goodness of fit index (PGFI=.785), normalized adjustment index (NFI=.960) and parsimonic normalized adjustment index (PNFI=.759). Overall, the Composite Reliability (CR), Average Variance Extracted (AVE) and Maximum Shared Variance (MSV) coefficients are calculated. Table 4 shows the results, as well as the reference values, taken for model fitting. 23 All the figures obtained fit with the reference values. Therefore, the reliability of the model (CR), as well as its convergent (AVE) and discriminant (MSV) validity, are demonstrated. Description of the digital teaching competences For a correct interpretation of the results, it should be considered that the response interval ranges from 0 to 4. Regarding the mean scores, Table A1 presents the mean values and standard deviations reached by the teachers in the different questions, by dimensions and globally. In terms of digital competence in the Autonomous Community of Andalusia, the values range from basic (1.18) to intermediate (2.33). In particular, teachers show problems (basic level) when teaching pupils to behave safely and responsibly online; using digital technologies to provide pupils with personalised learning opportunities; and analysing all available data to identify pupils in need of additional support. The competences that stand out (intermediate level) are using different digital channels systematically to improve communication; creating their own digital resources and modifying existing ones to suit their needs as a teacher; and using digital technologies to acquire and document knowledge when learners work in teams. Again, in the case of the universities of the Autonomous Community of Catalonia, the values are between the basic level (1.07), somewhat lower than in the Autonomous Community of Andalusia, and the intermediate level (2.41), somewhat higher than the maximum level in Andalusia. In particular, the least developed competences in the autonomous community of Catalonia are using digital Table 3 Rotated component matrix. Item Professional commitment Digital resources Digital pedagogy Evaluation and feedback Empowering students Facilitate students' digital competence A1 0.769 A2 0.706 A3 0.785 A4 0.605 B1 0.769 B2 0.719 B3 0.678 C1 0.769 C2 0.742 C3 0.671 C4 0.758 D1 0.772 D2 0.761 D3 0.768 E1 0.711 E2 0.721 E3 0.740 F1 0.749 F2 0.748 F3 0.828 F4 0.710 F5 0.729 Table 4 Convergent and discriminant validity of the model. Dimension CR AJUSTMENT AVE AJUSTMENT MSV AJUSTMENT A .739 CR > .7 .681 AVE > .5 .551 MSV < AVE B .758 .685 .554 C .812 .652 .557 D .810 .675 .440 E .798 .642 .538 F .828 .647 .405 Educación Médica 24 (2023) 100791 5 technologies to provide learners with personalised learning opportunities; teaching learners to behave safely and responsibly online and analysing all available data to identify learners in need of additional support. On the other hand, the competences that stand out are systematically using different digital channels to improve communication with learners and peers; participating in online training courses and creating their own digital resources and modifying existing ones to adapt them to the needs of teaching. It is very significant that in both Communities the competences that stand out are in the first two areas (technical mastery), while the least developed competences correspond to areas in which evaluation of the teaching-learning process (area 4), attention to diversity (area 5) and the development of digital citizenship (area 6) predominate. Specifically, the mean value achieved in the overall instrument for the Autonomous Community of Andalusia is 1.95 points with a standard deviation of 0.69. This indicates that, in general, the level of competence is basicintermediate. In the case of Catalonia, the mean value achieved for the instrument as a whole is 1.87 points with a standard deviation of 0.68, a result very similar to that of Andalusia. Therefore, in general, teachers have basic levels of TDC although they consider themselves more competent in professional engagement and digital resources in both Andalusia and Catalonia. This latter assumption is very significant. Finally, we checked whether there are statistically significant differences between the scores of the two regions. For this purpose, we applied the Mann-Whitney U test. The results can be seen in Table 5. The results confirm that there are no statistically significant differences in the overall level of Digital Competence in Teaching between the two Autonomous Communities. The same phenomenon occurs in almost all dimensions. The only dimension in which statistically significant differences are found at 95% (p<.005) is "Empowering learners". In this case, the analysis of the mean rank reveals differences in favour of the Community of Andalusia. However, after calculating Cohen's D, these differences are considered very small (d=0.1). Therefore, for a better understanding of the phenomenon, reference is again made to Table 5 (mean and standard deviation of items, dimensions and digital competence) for the specifics of each Autonomous Community. Discussion In our study, we have observed different phenomena. First, we have observed in the results section that the level of digital teaching competence in both autonomous communities in health sciences is basic-intermediate and that there are no significant differences among the autonomous communities. Second, in regard to the DigCompEdu model, our study reports data validity with the structured equation modelling in Health Sciences. Thus, this model was also validated for higher education by a related study. 19 Similarly, other studies performed other validations such as 13 where DigCompEdu was tested by the peer-groups method and the discrimination capacity was validated. Another model was also validated in the case of Andalusian universities, but only reliability was validated. 24 Our study has served to provide an insight into the teaching profile of Health Sciences in Higher Education in the Autonomous Communities of Andalusia and Catalonia, with a comparison between the scores obtained in the DigCompEdu Check-In questionnaire. 13 In both communities, teachers report a high mastery of technical competences, such as communication with other teachers or participation in online courses. The results coincide with those of, 25,26 who place the technical level of medical teachers above the pedagogical level. It shows that the participating teaching staff obtain scores that place them at basic-intermediate levels of Digital Teaching Competence, as does the research by 27,28 carried out for all university teaching staff. Similar results are obtained in a more recent study by 13 within Andalusian universities. This study recommended carrying out studies focused on specific branches of knowledge in order to adapt university teacher training plans, as is done in the present research with the Health Sciences branch. With regard to possible limitations of the research, we could reflect on the different areas for improvement and how comparative studies between future works with similar characteristics should be approached. One of the main weaknesses lies in the types of samples used, since the intentional sampling method indicates that it is not random, therefore, the results found should be considered nonextrapolatable to other areas of knowledge. Incorporating probabilistic samples for each area to be studied in future studies will allow the collection of more representative data that can be extrapolated globally. Funding Design, production and evaluation of t-MOOC for the acquisition of digital skills of university teachers. Reference: US-1260616. Junta de Andalucía (Consejería de Economía y Conocimiento) Declaration of competing interest The authors have not competing interests. We did not need the permission of the ethics committee because we did not store personal data of any kind and the questionnaires were anonymous. Table 5 U of Mann-Whitney for the scores of the two Autonomous Communities. Mann-Whitney U Wilcoxon W Z Sig. asymptotic (bilateral) A 37416.000 82566.000 -0.910 0.363 B 36840.000 71031.000 -1.217 0.224 C 36636.000 70827.000 -1.317 0.188 D 36703.000 70894.000 -1.293 0.196 E 33427.000 67618.000 -3.006 0.003 F 38073.000 72264.000 -0.564 0.573 TOTAL 36508.000 70699.000 -1.380 0.168 J.-J. Boté-Vericad, A. Palacios-Rodríguez, M. Gorchs-Molist, et al. 6 Appendix Table A1 Mean and standard deviation of items, dimensions and digital competence. Andalusia Catalonia Total Avg SD Avg SD Avg SD A1. I systematically use different digital channels to improve communication with students and my classmates. For example: emails, Whatsapptype messaging applications, blogs, the faculty website… 2.29 0.718 2.30 0.824 2.30 0.769 A2. I use digital technologies to work with my peers inside and outside my educational organization. 2.16 0.897 2.21 0.974 2.18 0.933 A3. I use digital technologies to work with my peers inside and outside my educational organization. 2.16 1.086 2.02 1.191 2.09 1.137 A4. I use digital technologies to work with my peers inside and outside my educational organization. 2.05 1.178 2.35 1.201 2.19 1.197 B1. I use digital technologies to work with my peers inside and outside my educational organization. 2.19 1.004 2.01 0.924 2.10 0.971 B2. I create my own digital resources and modify existing ones to adapt them to my needs as a teacher. 2.32 0.928 2.41 0.893 2.36 0.912 B3. I create my own digital resources and modify existing ones to adapt them to my needs as a teacher. 2.05 1.105 1.91 1.265 1.98 1.183 C1. I carefully consider how, when and why to use digital technologies in class, to ensure that their added value is exploited. 2.03 1.106 1.84 1.105 1.94 1.109 C2. I oversee my students' activities and interactions in the online collaboration environments we use. 2.08 1.165 2.04 1.088 2.06 1.129 C3. When my students work in groups or teams, they use digital technologies to acquire and document knowledge. 2.33 1.159 2.22 1.238 2.28 1.197 C4. I use digital technologies to enable students to plan, document and assess their learning on their own. For example: self-assessment tests, digital portfolio, blogs, forums… 1.91 1.066 1.87 1.052 1.89 1.059 D1. I use digital assessment strategies to monitor student progress. 1.75 0.946 1.77 0.972 1.76 0.958 D2. I use digital assessment strategies to monitor student progress. 1.58 0.913 1.31 0.944 1.45 0.936 D3. I use digital technologies to provide effective feedback. 1.78 0.809 1.80 0.884 1.79 0.844 E1. When I propose digital tasks, I consider and address possible problems such as equal access to digital devices and resources; compatibility problems or a low level of digital competence of students. 2.02 1.336 1.81 1.263 1.92 1.306 E2. I use digital technologies to offer students personalized learning opportunities. For example: assignment of different digital tasks to address individual learning needs, take into account preferences and interests… 1.42 1.330 1.07 1.156 1.26 1.263 E3. I use digital technologies so that students actively participate in class. 2.15 0.886 1.98 0.909 2.08 0.900 F1. I teach students how to assess the reliability of information searched online and how to identify erroneous and/or biased information. 1.87 0.977 1.79 1.147 1.83 1.059 F2. I propose tasks that require students to use digital media to communicate and collaborate with each other or with an outside audience. 1.81 0.899 1.85 0.968 1.83 0.931 F3. I propose tasks that require students to create digital content. For example: videos, audios, photos, presentations, blogs, wikis… 1.93 1.116 1.91 1.157 1.92 1.134 F4. I teach students how to behave safely and responsibly online. 1.18 0.940 1.15 0.926 1.17 0.933 F5. I encourage students to use digital technologies creatively to solve specific problems. For example, overcoming obstacles or emerging challenges in your learning process. 1.81 0.945 1.61 1.004 1.72 0.976 Area 1. Professional commitment 2.17 0.743 2.22 0.819 2.19 0.779 Area 2. Digital resources 2.18 0.772 2.11 0.775 2.15 0.773 Area 3. Teaching and learning 2.09 0.874 1.99 0.884 2.04 0.879 Area 4. Evaluation and feedback 1.70 0.754 1.63 0.791 1.67 0.772 Area 5. Empower students 1.86 0.973 1.62 0.898 1.75 0.946 Area 6. Develop students' digital competence 1.72 0.776 1.66 0.797 1.69 0.785 Total digital competence 1.95 0.691 1.87 0.689 1.92 0.690 Educación Médica 24 (2023) 100791 7 References 1. Ferrari A. DIGCOMP: a framework for developing and understanding digital competence in Europe.Joint Research Centre, Institute for Prospective Technological Studies; 2013 [Internet]. Available from: https://publications.jrc.ec.europa. eu/repository/bitstream/JRC83167/lb-na-26035-enn.pdf. 2. Redecker C, Punie Y. European framework for the digital competence of educators: DigCompEdu.JRC Publications Repository [Internet]; 2017 https://doi.org/10.2760/178382. 3. Basilotta-Gómez-Pablos V, Matarranz M, Casado-Aranda LA, Otto A. Teachers’digital competencies in higher education: a systematic literature review. Int J Educ Technol High Educ [Internet]. 2022 Feb 10;19(1):1–16 [cited 2023 Jan 2]. Available from: https://educationaltechnologyjournal.springeropen. com/articles/10.1186/s41239-021-00312-8. 4. Paz Saavedra LE, Gisbert Cervera M, Usart Rodríguez M. Competencia digital docente, actitud y uso de tecnologías digitales por parte de profesores universitarios. Pixel-Bit [Internet]. 2022;63:91–130 [cited 2023 Jan 2]. Available from: https://institucional.us.es/revistas/PixelBit/63/4_91652.pdf. 5. UNESCO. Education for Sustainable Development Goals: learning objectives [Internet] [cited 2022 Dec 18]. Available from: https://unesdoc.unesco.org/ark:/48223/pf0000247444. page=23 2017. 6. INTEF. Marco Común de Competencia Digital Docente [Internet] [cited 2023 Jan 2]. Available from: http://educalab.es/documents/10180/12809/MarcoComunCompeDigiDoceV2.pdf 2017. 7. Marchwacka MA, Kugler J, Schaal T, Tolks D. Digitale hochschullehre im ersten covid-19-semester. Ergebnisse einer befragung von lehrenden in public health, medizin und pflege. Präv Gesundheitsf [Internet]. 2022 Mar 20 [cited 2023 Jan 2]; Available from: https://link.springer.com/10.1007/s11553- 022-00937-1. 8. Boté-Vericad JJ. Perceived barriers for distance teaching in higher education during the COVID-19 crisis: “I never did a video before”. EFI [Internet]. 2021 Sep 29;37(3):377–97 [cited 2023 Jan 2]. Available from: https://doi.org/10.3233/EFI-200418. 9. Robles Moral FJ, Fernández Díaz M. Future primary school teachers’digital competence in teaching science through the use of social media. Sustainability [Internet]. 2021 Mar 5;13(5): 2816 [cited 2023 Jan 2]. Available from: https://www.mdpi. com/2071-1050/13/5/2816. 10. Mercader C, Gairin J. The perception of teachers’digital competence of preservice pre-primary and primary education teachers. The influence of degree and entrance path. IEEE R Iberoamericana Tecnologias Aprendizaje [Internet]. 2021 Feb;16(1):100–6 [cited 2023 Jan 2]. Available from: https:// ieeexplore.ieee.org/document/9328332/. 11. Dias-Trindade S, Moreira JA, Ferreira AG. Evaluation of the teachers’digital competences in primary and secondary education in Portugal with DigCompEdu CheckIn in pandemic times. Acta Sci Technol [Internet]. 2021 Sep 23:43 [cited 2023 Jan 2]. e56383. Available from: https://periodicos.uem.br/ojs/ index.php/ActaSciTechnol/article/view/56383. 12. Smagulova GZ, Sarzhanova GB, Tleuzhanova GK, Stanciu N. The development of future foreign language teachers’digital competences in creating multimedia tutorials. Obraz nauka [Internet]. 2021 Jun 18;23(6):216–45 [cited 2023 Jan 2]. Available from: https://www.edscience.ru/jour/article/view/2217. 13. Cabero-Almenara J, Barroso-Osuna J, Gutiérrez-Castillo JJ, Palacios-Rodríguez A. The teaching digital competence of health sciences teachers. A study at andalusian universities(Spain). IJERPH [Internet]. 2021 Mar 4;18(5):2552 [cited 2023 Jan 2]. Available from: https://www.mdpi.com/1660-4601/18/5/2552. 14. Fernández-Batanero JM, Román-Graván P, Montenegro-Rueda M, López-Meneses E, Fernández-Cerero J. Digital teaching competence in higher education: a systematic review. Educat Sci [Internet]. 2021 Oct 29;11(11):689 [cited 2023 Jan 2]. Available from: https://www.mdpi.com/2227-7102/11/11/689. 15. Cabero-Almenara J, Barroso-Osuna J, Palacios-Rodríguez A. Estudio de la competencia digital docente en Ciencias de la Salud. Su relación con algunas variables. Educación Médica [Internet]. 2021 Mar;22(2):94–8 [cited 2023 Jan 2]. Available from: https:// linkinghub.elsevier.com/retrieve/pii/S1575181320301959. 16. Cabero-Almenara J, Palacios-Rodríguez A. Marco europeo de competencia digital docente «digcompedu». Traducción y adaptación del cuestionario «digcompedu check-in». EDMETIC [Internet]. 2020 Jan 1;9(1):213–34 [cited 2023 Jan 2]. Available from: https://www.uco.es/ucopress/ojs/index.php/edmetic/ article/view/12462[16. 17. De Los Ángeles Sánchez Trujillo M, Rodríguez Flores E. Digital competence in teachers of health sciences in a private university in Lima. Revista Cubana de Educación Médica Superior [Internet]. 2021;35(1):1–16 [cited 2023 Jan 2] Available from: https://wwwmedigraphic.com/cgi-bin/new/ resumenI.cgi?IDARTICULO=105039. 18. Tourón J, Martín D, Navarro Asencio E, Pradas S, Íñigo V. Validación de constructo de un instrumento para medir la competencia digital docente de los profesores (CDD). REP [Internet]. 2018 Jan 1;76(269) [cited 2023 Jan 2]. Available from: https://revistadepedagogia.org/lxxvi/no-269/validacion-de- constructo-de-un-instrumento-para-medir-la-competencia-digital- docente-de-los-profesores-cdd/101400035295/. 19. Cabero-Almenara J, Barroso-Osuna J, Palacios-Rodríguez A, Llorente-Cejudo C. Marcos de Competencias Digitales para docentes universitarios: su evaluación a través del coeficiente competencia experta. REIFOP [Internet]. 2020 Apr 13;23(2) [cited 2023 Jan 2]. Available from: https://revistas.um.es/ reifop/article/view/413601. 20. Ghomi M, Redecker C. Digital competence of educators (digcompedu): development and evaluation of a self-assess- ment instrument for teachers’digital competence.Joint Research Center [Internet]; 2018. Available from: https://jointresearch-centre.ec.europa.eu/digcompedu_en. 21. Ruiz M, Pardo A, San Martín R. Structural equation models. Papeles Del Psicólogo. 2010;31(1):34–5 [Internet]. [cited 2023 Jan 2]. Available from: https://www2.papelesdelpsicologo.es/ English/1794.pdf. 22. Lévy Mangin J-P, Varela Mallou J, González Abad, Julio. Modelización con estructuras de covarianzas en ciencias sociales: Temas esenciales, avanzados y aportaciones especiales. Netbiblo; 2006. 23. Hair JF, Black W, Babin BJ, Anderson RE. Multivariate Data Analysis.(Ed. 7th). Harlow: Pearson Education; 2010. 24. Cabero-Almenara J, Barroso-Osuna J, Rodríguez-Gallego M, Palacios-Rodríguez A. La Competencia Digital Docente. El caso de las universidades andaluzas. AULA_ABIERTA [Internet]. 2020 Dec 31;49(4):363–72 [cited 2023 Jan 2]. Available from: https://reunido.uniovi.es/index.php/AA/article/view/15112. 25. Humanante-Ramos P, Solís-Mazón ME, Fernández-Acevedo J, Silva-Castillo J. Las competencias TIC de los estudiantes que ingresan en la universidad: una experiencia en la Facultad de Ciencias de la Salud de una universidad latinoamericana. Educación Médica [Internet]. 2019 May;20(3):134–9 [cited 2023 Jan 2]. Available from: https://linkinghub.elsevier.com/ retrieve/pii/S1575181318300810. 26. Kingsley KV, Kingsley K. A case study for teaching information literacy skills. BMC Med Educ [Internet]. 2009 Dec;9(1):7 [cited 2023 Jan 2]. Available from: https://bmcmededuc. biomedcentral.com/articles/10.1186/1472-6920-9-7. 27. Solís de Ovando Calderón J, Jara Jara V. Competencia digital de docentes de Ciencias de la Salud de una universidad chilena. Pixel-Bit [Internet]. 2019;56:193–211 [cited 2023 Jan 2]. J.-J. Boté-Vericad, A. Palacios-Rodríguez, M. Gorchs-Molist, et al. 8 Available from: https://institucional.us.es/revistas/PixelBit/5 6/10_71091.pdf. 28. Mora-Cantallops M, Inamorato Dos Santos A, Villalonga-Gómez C, Lacalle Remigio JR, Camarillo Casado J, Sota Eguizábal JM, Velasco JR, Ruiz Martínez PM. Competencias digitales del profesorado universitario en España: Un estudio basado en los marcos europeos DigCompEdu y OpenEduThe Digital Competence of Academics in Spain: a study based on the European frameworks DigCompEdu and OpenEdu [Internet]. LU: Publication s Office; 2022 [cited 2023 Jan 2]. Available from: https:// data.europa.eu/doi/10.2760/541915. Educación Médica 24 (2023) 100791 9