Self-Perceived Digital Competencies in Educational Online Migration Due to COVID-19 Confinement

Abstract

Objectives: The purpose of the study was to validate a measurement scale to assess self-perceived digital competencies of Mexican university students who have migrated from a mixed school-digital system to a fully digitalized educational environment because of COVID-19 confinement. The instrument was based on the European Union Digital Competence Framework. Method: 1,118 participants aged between 18 and 47 years completed the assessment. This included 677 females (60.6%) and 429 males (38.4%). Confirmatory factor analysis (CFA) was used to assess scale structure. Results: Results of the CFA showed an excellent fit to the data, C2/df = 3.27, p = .01, comparative fit index (CFI) = 0.97, root-mean-square error of approximation (RMSEA) = 0.05. Cronbach’s a values for the scale and subscales ranged from .78 to .83. Three of the four subscales predicted number of assignments completed and submitted, a measure of predictive validity. Conclusions: The Digital Competence Scale for Online Migration is a valid scale for Mexican students and demonstrates predictive validity. Implication for Theory and/or Practice: The scale may be useful in planning activities for the reinforcement of digital competencies and to identify difficulties and support specific pedagogy for online teaching/learning processes.