Teachers’ Digital Competence as a Predictor of Formative m-Learning Experiences in Higher Education
DOI:
https://doi.org/10.37843/rted.v19i1.795
Article Sidebar
Main Article Content
Abstract
Faculty digital competence has established itself as a key factor in the design of educational experiences mediated by mobile technologies in higher education, owing to its direct influence on the pedagogical integration of digital resources and on the quality of learning. In this regard, the present study aimed to analyze the relationship between faculty digital competence and educational experiences based on mobile learning (m-learning), while also considering cognitive variables associated with learning self-regulation, sustained attention, and cognitive load. The research was framed within the positivist paradigm, employing a quantitative approach and a non-experimental, correlational, and cross-sectional design based on the hypothetico-deductive method. A structured questionnaire was administered to a convenience sample of 60 university faculty members. The instrument was developed based on the DigCompEdu framework and on validated scales regarding m-learning experiences and cognitive processes; it demonstrated adequate levels of internal consistency (α = 0.81–0.93). The results revealed positive and statistically significant relationships between faculty digital competence and the quality of m-learning-based educational experiences (r > 0.60; p < 0.01), as well as significant differences based on the mode of instruction. Furthermore, exploratory regression analysis identified faculty digital competence as a significant predictor of educational experiences mediated by mobile devices, explaining a substantial proportion of the model's variance. It is concluded that strengthening faculty digital competence is crucial for enhancing more effective, innovative, and cognitively sustainable mobile pedagogical practices within the university context, and for fostering learning environments adapted to current technological demands and to the cognitive processes involved in autonomous learning.
Downloads
Metrics
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Those authors who have publications in our journal accept the following terms:
- When a work is accepted for publication, the author retains rights of reproduction, distribution of his/her article for exploitation in all countries of the world in the format provided by our magazine and any other magnetic medium, optical, and digital.
- Authors will retain their copyright and guarantee the journal the right first to publish their work, which will be simultaneously subject to the Creative Commons Acknowledgment License (Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)). That allows third parties to copy and redistribute the material in any medium or format, under the following conditions: Acknowledgment - You must properly acknowledge authorship, provide a link to the license, and indicate if any changes have been made. You may do so in any reasonable way, but not in a way that suggests you have the licensor's endorsement or receive it for your use. NonCommercial - You may not use the material for a commercial purpose. NoDerivatives - If you remix, transform, or build from the material, you cannot broadcast the modified material. There are no additional restrictions - You cannot apply legal terms or technological measures that legally restrict you from doing what the license allows.
- Authors may adopt other non-exclusive license agreements to distribute the published version of the work (e.g., deposit it in an institutional archive or publish it in a monographic volume) provided that the initial publication in this journal is indicated.
- Authors are allowed and recommended to disseminate their work through the Internet (e.g., in institutional telematic archives, repositories, libraries, or their website), producing exciting exchanges and increasing the published work's citations.
- Request of withdrawal an article has to be done in writing by the author to the Editor, becoming effective after a written response from the Editor. For this purpose, the author or authors will send correspondence via e-mail: [email protected].
- The author will not receive financial compensation for the publication of his work.
- All Docentes 2.0 Journal publications are under the Open Journal System (OJS) platform at: https://ojs.docentes20.com/.
Citaciones del Artículo
References
Arias, F. G. (2016). El proyecto de investigación: Introducción a la metodología científica (7.ª ed.). Episteme.
Cabero-Almenara, J., & Palacios-Rodríguez, A. (2020). Marco europeo de competencia digital docente «DigCompEdu»: Traducción y adaptación del cuestionario «DigCompEdu Check-In». EDMETIC, 9(1), 213–234. https://doi.org/10.21071/edmetic.v9i1.12462
Cabero-Almenara, J., Barroso-Osuna, J., Gutiérrez-Castillo, J.-J., & Palacios-Rodríguez, A. (2021). The teaching digital competence of health sciences teachers: A study at Andalusian universities (Spain). International Journal of Environmental Research and Public Health, 18(5), 2552. https://doi.org/10.3390/ijerph18052552
Castelo Barreno, L. F. (2024). Dispositivos móviles y aplicaciones educativas para el desarrollo de competencias digitales en estudiantes de educación superior. Gestión I+D, 9(1), 210–223. https://saber.ucv.ve/ojs/index.php/rev_GID/article/view/27641
Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). SAGE.
Cuba-Vilca, L., Teves-Ccanre, R., & Saavedra-Carrion, N. (2024). Apropiación tecnológica y uso de aplicativos móviles de los docentes. Revista Tecnológica-Educativa Docentes 2.0, 17(2), 345–354. https://doi.org/10.37843/rted.v17i2.532
Ghasemy, M., Teeroovengadum, V., Becker, J.-M., & Ringle, C. M. (2020). This fast car can move faster: A review of PLS-SEM application in higher education research. Higher Education, 80(6), 1121–1152. https://doi.org/10.1007/s10734-020-00534-1
Gutiérrez-Pineda, S. J., Torres-Andrade, C. A., Noguera-Galeano, D. C., Mazzo-Pérez, J. J., & Vargas-Ortega, G. A. (2025). Competencias transversales docentes en la educación universitaria virtual: Percepción y relevancia en la enseñanza. Revista Tecnológica-Educativa Docentes 2.0, 18(2), 393–401. https://doi.org/10.37843/rted.v18i2.714
Hernández-Sampieri, R., & Mendoza, C. (2018). Metodología de la investigación: Las rutas cuantitativa, cualitativa y mixta. McGraw-Hill.
Hilario García, E. (2025). Incidencia del m-learning como estrategia de apoyo al proceso de enseñanza y aprendizaje. Pedagogical Constellations, 4(1), 218–238. https://doi.org/10.69821/constellations.v4i1.92
Kerlinger, F. N., & Lee, H. B. (2002). Investigación del comportamiento: Métodos de investigación en ciencias sociales (4.ª ed.). McGraw-Hill.
Kukulska-Hulme, A., Bossu, C., & Coughlan, T. (2022). Mobile learning in higher education: Conceptual challenges and future directions. International Journal of Educational Technology in Higher Education, 19(1), 1–17. https://doi.org/10.1186/s41239-022-00323-y
Kukulska-Hulme, A., Wise, A., Coughlan, T., Biswas, G., Bossu, C., Burriss, S., Charitonos, K., Crossley, S., Enyedy, N., Ferguson, R., FitzGerald, E., Gaved, M., Herodotou, C., Hundley, M., McTamaney, C., Molvig, O., Pendergrass, E., Ramey, L., Sargent, J., & Whitelock, D. (2024). Innovating pedagogy 2024: Open University innovation report 12. The Open University.
Lagos, G. G. (2018). El m-learning, un nuevo escenario en la educación superior del Ecuador. INNOVA Research Journal, 3(10.1), 114–122. https://doi.org/10.33890/innova.v3.n10.1.2018.859
Mayer, R. E. (2020). Multimedia learning (3rd ed.). Cambridge University Press. https://doi.org/10.1017/9781316941355
Mosleh, S. M., Kasasbeha, M. A., Aljawarneh, Y. M., Alrimawi, I., & Saifan, A. R. (2022). The impact of online teaching on stress and burnout of academics during the transition to remote teaching from home. BMC Medical Education, 22(1), 475. https://doi.org/10.1186/s12909-022-03496-3
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
Otzen, T., & Manterola, C. (2017). Técnicas de muestreo sobre una población a estudio. International Journal of Morphology, 35(1), 227–232. https://doi.org/10.4067/S0717-95022017000100037
Popper, K. (2008). La lógica de la investigación científica. Tecnos.
R Core Team. (2023). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.r-project.org/
Redecker, C. (2020). European framework for the digital competence of educators: DigCompEdu. Publications Office of the European Union. https://doi.org/10.2760/159770
Tamayo & Tamayo, M. (2004). El proceso de la investigación científica (4.ª ed.). Limusa.
Unesco. (2021). Reimagining our futures together: A new social contract for education. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000379707.locale=en
Zawacki-Richter, O., & Latchem, C. (2020). Exploring four decades of research in Computers & Education. Computers & Education, 146, 103808. https://doi.org/10.1016/j.compedu.2019.103808