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Self-regulatory and demographic predictors of grades in online and face-to-face university cohorts: A multi-group path analysis
Authors:Kate Talsma  Andrew Chapman  Allison Matthews
Institution:1. School of Psychological Sciences, University of Tasmania, Hobart, Tasmania, Australia;2. Australian College of Applied Professions, Northbridge, Western Australia, Australia
Abstract:Predictors of academic success at university are of great interest to educators, researchers and policymakers. With more students studying online, it is important to understand whether traditional predictors of academic outcomes in face-to-face settings are relevant to online learning. This study modelled self-regulatory and demographic predictors of subject grades in 84 online and 80 face-to-face undergraduate students. Predictors were effort regulation, grade goal, academic self-efficacy, performance self-efficacy, age, sex, socio-economic status (SES) and first-in-family status. A multi-group path analysis indicated that the models were significantly different across learning modalities. For face-to-face students, none of the model variables significantly predicted grades. For online students, only performance self-efficacy significantly predicted grades (small effect). Findings suggest that learner characteristics may not function in the same way across learning modes. Further factor analytic and hierarchical research is needed to determine whether self-regulatory predictors of academic success continue to be relevant to modern student cohorts.

Practitioner Notes

What is already known about this topic
  • Self-regulatory and demographic variables are important predictors of university outcomes like grades.
  • It is unclear whether the relationships between predictor variables and outcomes are the same across learning modalities, as research findings are mixed.
What this paper adds
  • Models predicting university students' grades by demographic and self-regulatory predictors differed significantly between face-to-face and online learning modalities.
  • Performance self-efficacy significantly predicted grades for online students.
  • No self-regulatory variables significantly predicted grades for face-to-face students, and no demographic variables significantly predicted grades in either cohort.
  • Overall, traditional predictors of grades showed no/small unique effects in both cohorts.
Implications for practice and/or policy
  • The learner characteristics that predict success may not be the same across learning modalities.
  • Approaches to enhancing success in face-to-face settings are not automatically applicable to online settings.
  • Self-regulatory variables may not predict university outcomes as strongly as previously believed, and more research is needed.
Keywords:grades  higher education  online learning  self-efficacy  self-regulation
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