Journal of Education and Learning (EduLearn)
Vol 20, No 4: November 2026

Digital information competence: a predictive model in schoolchildren

Teresa Fernández-Bringas (Cayetano Heredia Peruvian University)
Francisco Sandoval-Arteta (Cayetano Heredia Peruvian University)
Cristóbal Suárez-Guerrero (University of Valencia)



Article Info

Publish Date
01 Nov 2026

Abstract

Digital information competence (DIC) is essential for schoolchildren facing an increasingly complex and misinformative online environment, a challenge that intensified during the pandemic. In Peru, no prior studies have examined jointly the educational, psychological, and sociodemographic predictors of DIC. This study aimed to validate a structural equation model (SEM) in 502 secondary school students, aged 15 to 17, from two Peruvian cities. Results showed that motivation is the strongest predictor of DIC, followed by mother’s educational level, virtual interaction, and school-related information and communication technology (ICT) tasks, respectively. Interaction had both direct and indirect effects on DIC through motivation. Subsequently, we achieved a partial factor invariance by gender and school type, suggesting differences in DIC scores and the strength of predictors across groups. Findings suggest that pedagogical interventions should prioritize student motivation and virtual interaction to enhance DIC, highlighting the need for educational policies tailored to these specific sociocultural and psychological predictors.

Copyrights © 2026






Journal Info

Abbrev

EduLearn

Publisher

Subject

Humanities Education Library & Information Science Social Sciences Other

Description

Journal of Education and Learning (EduLearn) ISSN: 2089-9823, e-ISSN 2302-9277 is a multi-disciplinary, peer-refereed open-access international journal which has been established for the dissemination of state-of-the-art knowledge in the field of education, teaching, development, instruction, ...