Online learning barriers and its relationship to gender, age, work status, and chronotype in university student

Abstract

ABSTRACT Students’ biological clock and online learning barriers can complicate training. This study aims to find the factors that chronotype, age, gender, and employment status can predict online learning barriers in university students. The participants of the study were 668 students studying at a university in Turkey during the COVID-19 period. The research was carried out through anonymous and voluntary participation over the internet. The data were analysed with SPSS 24 using correlation and regression analyses. It can be said that chronotypes are a significant predictor of administrative/faculty problems and technical skills. In addition, social interaction, academic skills, technical skills, student motivation, time and support for studying, and technical problems were found to be significant predictors of students having a job other than studying. It was determined that the student’s employment status and chronotype preference are learning barriers. These variables should be taken into account in online learning processes.