Predictive factors of academic motivation in virtual education: validation and modeling in high school during COVID-19.

Abstract

This study developed and psychometrically validated a scale of perceived online academic success among high school students in Baja California during COVID-19. Multiple regression analysis identified predictors that explained the variance in academic motivation: perceived usefulness of learning, perceived personal academic success, interest in academic activities, perceived teacher engagement, and perceived job readiness. Structural equation modeling confirmed three key predictors: perceived usefulness, academic interest, and teacher engagement. The findings provide empirical evidence for designing effective virtual educational interventions, prioritizing the practical relevance of learning and teacher support in upper secondary education contexts. The research offers a solid conceptual framework for understanding motivational factors in emergency virtual environments.