Educational Big Data and Digital Literacy: A Study Based on R and Statistical Visualization

Abstract

The rapid digitalization of education has created an urgent need for digitally literate educators capable of integrating big data and emerging technologies into pedagogical practices. This quasi-experimental study investigated digital literacy levels among 50 pre-service teachers from Universidad Peruana del Norte in Trujillo, Peru, and evaluated the effectiveness of a targeted digital literacy intervention. Using R Studio for statistical analysis and visualization, we assessed participants through a 32-item digital knowledge test (Cronbach's α = 0.82) and implemented a pre-test/post-test design. Results revealed moderate baseline digital literacy (M = 24.97/50, SD = 14.84) with significant variability among participants. The intervention proved highly effective, showing substantial improvement in digitalization scores (mean difference = -35.17, p < 2.2e-16). However, commitment levels remained low (19.9% vs. expected 40%, p = 1), and training effectiveness varied significantly across educational levels (ANOVA, p = 0.0019). Despite high academic performance in traditional assessments (M = 80.32/100), the study reveals a critical gap between academic achievement and digital competencies. These findings highlight the need for differentiated digital literacy training and institutional support to prepare educators for data-driven educational environments in Latin America.