RT Journal Article
T1 Analysis of teachers’ pedagogical digital competence: identification of factors predicting their acquisition
A1 Guillén-Gamez, F. David
A1 Mayorga-Fernández, M. José
A1 Bravo Agapito, Javier
A1 Escribano-Ortiz, David
A2 Ifenthaler, Dirk
AB The current technological revolution has reached all social classes and its educative use by teachers has not gone unnoticed. The introduction of 2.0 tools has become a reality in many classrooms. In order to evaluate the digital competence of teachers, different dimensions must be considered, including knowledge and educative use. The first objective of this research is to find out whether there are any differences between the knowledge and use of teaching staff of ICT, specifically regarding different 2.0 tools, as well as different modules on the Moodle virtual platform, using the t-Student test. The second objective is to analyse, through a multiple linear regression model, which factors have an effect on the level of digital competence: gender, age and educational stage. With this aim, a non-experimental, ex post facto type of research has been carried out with a study population of 81 teachers from the community of Madrid (Spain). The results have shown that there are statistically significant differences between the knowledge and use of 2.0 tools and Moodle Modules. In addition, the results have found that the variables age and gender have an effect on the prediction of the level of pedagogical digital competence of the teaching staff, while the educational stage in which they teach has no effect. The conclusions derived from this study can help to develop educational interventions focused on improving the unfavourable digital competence of eachers.
PB Springer
SN 2211-1662
YR 2021
FD 2021
LK https://hdl.handle.net/20.500.14352/98381
UL https://hdl.handle.net/20.500.14352/98381
LA eng
NO Guillén-Gamez, F.D., Mayorga-Fernández, M.J., Bravo-Agapito, J., Escribano-Ortiz, D. (2021). Analysis of teachers’ pedagogical digital competence: identification of factors predicting their acquisition. Technology, Knowledge and Learning, 26, 481-498.
DS Docta Complutense
RD 27 abr 2025