58
Views
0
CrossRef citations to date
0
Altmetric
Report

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

ORCID Icon, &
Received 21 Feb 2024, Accepted 26 Mar 2024, Published online: 03 Apr 2024
 

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.

Disclosure statement

No potential conflict of interest was reported by the author(s).

CRediT authorship contribution statement

Dilek Nam: Writing – review & editing, Visualization, Formal analysis, Supervision, Investigation.

Barış Horzum: Writing – original draft, Methods, Writing – review & editing, Conceptualization.

Data availability statement

The datasets analysed during this study are available from the corresponding author on reasonable request.

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 387.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.