Self-Perceived Teacher Digital Competence Among University Teachers: A Gender-Based Analysis in Accredited Colombian Universities
DOI:
https://doi.org/10.54104/papeles.v19n37.2424Keywords:
Digital competence, higher education, professional training, educational technology, genderAbstract
Introduction: Teacher Digital Competence (TDC) has become increasingly recognized as a component of educational quality in digitalized university contexts. However, evidence on factors associated with its development and self-perception, particularly regarding gender, remains limited in Latin America. This study examines gender differences in self-perceived TDC among faculty at Colombian universities with High-Quality Accreditation and whether these differences vary by age, teaching experience, and institutional type. Method: A cross-sectional design was employed with 765 teachers who completed the SELFIE for Teachers instrument, aligned with the DigCompEdu framework. Independent-samples t-tests examined gender differences in overall TDC and in six competence areas. Factorial General Linear Models assessed whether gender differences varied according to contextual and professional variables. Results:The study found a general pattern of gender parity in self-perceived TDC. No statistically significant differences emerged in the overall score or in five of the six DigCompEdu areas, and the observed effect sizes were trivial. The only notable difference was a small advantage for women in Facilitating Learners’ Digital Competence (d = −0.15), concentrated among less experienced teachers. Institutional type showed modest associations with TDC levels, suggesting that institutional context may be relevant for understanding variation in self-perceived TDC. Conclusions: These findings challenge assumptions of inherent gender gaps in TDC. Within the analyzed accredited university context, gender showed minimal association with self-perceived TDC. Faculty development strategies should prioritize age group and institutional conditions over gender-based approaches, while also considering str
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