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.
| Original language | English |
|---|---|
| Pages (from-to) | 475-487 |
| Number of pages | 13 |
| Journal | Scandinavian Journal of Occupational Therapy |
| Volume | 30 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 19 Sept 2022 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 3 Good Health and Well-being
Fingerprint
Dive into the research topics of 'Predictors of undergraduate occupational therapy students’ academic performance during the Covid-19 pandemic: a hierarchical regression analysis'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver