Digital competence in research work: predictors that have an impact on it according to the type of university and gender of the Higher Education teacher
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Keywords

Teacher qualifications
Information literacy
Scientific research
Higher education
Information technology Competencias del docente
alfabetización informacional
Investigación científica
Educación superior
Tecnologías de la información

How to Cite

Guillén-Gámez, F. D., Gómez-García, M., & Ruiz-Palmero, J. (2024). Digital competence in research work: predictors that have an impact on it according to the type of university and gender of the Higher Education teacher. Pi­xel-Bit. Media and Education Journal, (69), 7–34. https://doi.org/10.12795/pixelbit.99992

Abstract

Digital integration in research work will allow knowledge to be updated and increased thanks to access to digital information in a much faster and more accessible way than years ago. Being this study part of a doctoral thesis, the main purpose was to assess the level of digital competence of teaching staff in research work. The specific objectives were: 1) to compare the level of competence according to the type of university (public and private) and according to gender (male and female); 2) to identify predictors for each type of teaching staff and gender. For this purpose, an ex post facto design and a sample of 1740 Higher Education teachers from all over Spain were used. The results showed that the level of competence was satisfactory, being slightly higher and significant in male teachers and those working in public universities. For teachers working in public universities, the level of creativity was identified as a significant predictor in both genders, while for female teachers working in private universities, predictors such as creativity, attitude towards new changes, percentage of time devoted to research and teaching experience were found. These findings highlight the need for Higher Education institutions, especially private ones, to develop training plans to improve digital competences, taking into account all the predictors that interfere with this research competence.

https://doi.org/10.12795/pixelbit.99992
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