Profiles of student ICT use and their relations to background, motivational factors, and academic achievement

Abstract

The primary aim of this study is to identify the characteristics of the students’ profiles regarding information and communications technology (ICT) use and their relations to background, motivational factors, and academic achievement. A sample of 4,838 U.S. students from PISA 2018 data was used. Latent profile analysis on ICT use for different purposes at different settings identified two distinct student subgroups. Logistic regression revealed that perceived ICT competence, gender, and SES predicted students' profile membership. Linear regression showed that students who use ICT moderately across all aspects performed better academically than the students who use ICT heavily for entertainment. Our study shows the need to investigate ICT use at a finer granularity to better distinguish different types of ICT use and to provide insights into characteristics of the U.S. students' subgroups.

Keywords:

• LPA
• ICT use
• academic achievement
• PISA

Additional information

Funding

This study is funded by Henan Province Philosophy and Social Science Planning Project (No. 2019CJY031).

Notes on contributors

Feiya Xiao

Dr. Feiya Xiao is an assistant professor in the School of Education at Henan Normal University in China. She received her PhD in educational psychology from Texas Tech University. Dr. Feiya Xiao’s research focuses on academic motivation and affection, mathematic achievement, and ICT use in education.

Li Sun

Dr. Li Sun earned a PhD in biology and master’s degree in statistics from Texas Tech University. His research interest concerns the application of statistical methods in educational psychology.