Predicting fourth grade digital reading comprehension: A secondary data analysis of (e)PIRLS 2016

Abstract

This study examined how digital reading comprehension of elementary students can be predicted by individual differences, home-school resources, and instructional support. We conducted multilevel regressions with two levels (student and school) using datasets for the United States of America from (e)PIRLS 2016. Data analysis at the student level indicated that the participating fourth graders' digital reading comprehension was predicted substantively by their proficiency in print reading comprehension in conjunction with direct and indirect effects of individual differences in student motivation (e.g., reading self-concept) and home resources. At the school level, however, neither digital resources nor instructional support were significant predictors of students' digital reading comprehension. These findings contribute to our understanding of what factors affect children's development of digital literacy.