Computer user profiles in early adolescence and digitally assessed mathematics: A latent class analysis

Abstract

This study aimed at exploring the pattern of computer usage among early adolescents in Italy, about one year before the spread of the COVID-19 pandemic. The study also aimed at developing and testing models on the associations between socio-demographic characteristics, computer-user profiles, and mathematics achievement. A three-step estimation of Latent Class Analysis models and auxiliary variable models was applied to data collected on a sample of 1155 students attending grade 8 in Italy in the school year 2018–19. Four subpopulations were uncovered, which differ both with regards to their activities with computers (desktop, laptop, and tablet computers) and the likelihood of being daily users. Students’ socioeconomic and cultural background and gender predicted their pattern of computer usage, which in turn predicted digitally assessed mathematics. The main results suggested that excessive and almost exclusive use of computers for entertainment and communication purposes may depict an “at-risk'' profile in young adolescents, with possible negative consequences for their learning achievements. This profile was more likely to be found among students from more disadvantageous backgrounds and males, at least before the COVID-19 pandemic started.

Keywords

• Socioeconomic background
• Gender
• Latent class analysis
• Computer-based testing
• Mathematics achievement
• Computer-user profile