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

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 pretest/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.