Predictors of undergraduate occupational therapy students' academic performance during the Covid-19 pandemic: A hierarchical regression analysis

Scand J Occup Ther. 2023 May;30(4):475-487. doi: 10.1080/11038128.2022.2123854. Epub 2022 Sep 19.

Abstract

Background: The rapid switch to online learning in response to the Covid-19 pandemic affected occupational therapy students' education delivery. It is, therefore, important to investigate these impacts.

Aims/objectives: This study investigated the potential predictors of academic performance in undergraduate occupational therapy students after moving to online or blended learning post-Covid-19.

Material and methods: A total of 208 students from three Australian universities completed a demographic questionnaire and the Distance Education Learning Environment Scale (DELES). Hierarchical linear regression analyses were completed to identify significant students' academic performance predictors.

Results: Hierarchical regression explained a cumulative total variance of 24.6% of students' academic performance. The following independent variables were significant predictors: DELES student autonomy (p = 0.033), number of hours per semester week dedicated to indirect online study (p = 0.003), number of hours per semester week dedicated to indirect offline study time (p = 0.034), gender (p = 0.005) and English as a first language (p = 0.045).

Conclusions: The findings add to the knowledge base on the range of factors that have impacted occupational therapy students' academic performance during the Covid-19 pandemic.

Significance: The outcomes will assist faculty in developing supportive and pedagogically sound learning modes across online, hybrid and traditional forms of instruction within occupational therapy curricula.

Keywords: Covid-19; academic performance; health professions education; occupational therapy students; online learning; pandemic.

MeSH terms

  • Academic Performance*
  • Australia
  • COVID-19*
  • Humans
  • Occupational Therapy* / education
  • Pandemics
  • Regression Analysis
  • Students