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Abstract

Purpose: An understanding of the learning strategies most accurately predictive of success has become increasingly important as health professional education programs scale the utilization of online learning in the wake of COVID-19. The purpose of this study was to examine the predictive relationship between The Learning and Study Strategies Inventory (LASSI) and cumulative professional GPA (cpGPA) in hybrid-online physical (PT) and occupational therapist (OT) education. Methods: A convenience sample collected N=149 entry-level PT and OT students from three campuses across Florida, Texas, and California. A total N(%) of 89(59.7%) PT and 60(40.3%) OT students were included for analysis [48(32.2%) male; 101(67.8%) female]. A cross-sectional and predictive correlational study design was utilized. Participants self-administered the LASSI and cpGPA was collected in Spring 2020. Standard multiple linear regression analyses were conducted. Results: Neither the LASSI scales, R2 = 0.05 [F(10, 138) = 0.71, p = 0.71], nor the LASSI components, R2 = 0.01 [F(3, 145) = 0.56, p = 0.64], were able to accurately predict cpGPA. These findings contradict many prior studies in health professions education where anxiety, attitude, motivation, test strategies, and time management have been significant predictors. Conclusion: This study should be repeated due to a threat to internal validity, the COVID-19 pandemic, which may have influenced outcomes to an unknown degree. The predictive nature of this measure under more natural conditions remains unknown for this population of learners.

Author Bio(s)

Evan M. Pucillo, PT, DPT, EdD is an Assistant Professor of Physical Therapy at the University of St. Augustine for Health Sciences in St. Augustine, FL where he teaches evidence-based practice and clinical neuroscience.

Ellen Lowrie Black, EdD is a Professor in the School of Education at Liberty University where she is a nationally recognized speaker and author.

Acknowledgements

The authors would like to acknowledge Dr. Kurt Michael, PhD, of Liberty University, for his contributions to the methodological integrity of this study. We would also like to acknowledge the student participants who donated their time to research and helped to make this work possible.

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