Testing a new active learning approach to advance motor learning knowledge and self-efficacy in physical therapy undergraduate education
Abstract Background Motor learning (ML) science is foundational for physical therapy. However, multiple sources of evidence have indicated a science-practice gap. Clinicians report low self-efficacy with ML concepts and indicate that the lack of access to systematic training is a barrier for practic...
Main Authors: | , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2021-01-01
|
Series: | BMC Medical Education |
Subjects: | |
Online Access: | https://doi.org/10.1186/s12909-021-02486-1 |
id |
doaj-68fc3a14d1334fd8a7a1bd06d05dcd0b |
---|---|
record_format |
Article |
spelling |
doaj-68fc3a14d1334fd8a7a1bd06d05dcd0b2021-01-24T12:09:14ZengBMCBMC Medical Education1472-69202021-01-0121111110.1186/s12909-021-02486-1Testing a new active learning approach to advance motor learning knowledge and self-efficacy in physical therapy undergraduate educationDaniela V. Vaz0Erica M. R. Ferreira1Giulia B. Palma2Osnat Atun-Einy3Michal Kafri4Fabiane R. Ferreira5Department of Physical Therapy, Universidade Federal de Minas GeraisDepartment of Physical Therapy, School of Physical Education, Physical Therapy and Occupational Therapy, Universidade Federal de Minas GeraisDepartment of Physical Therapy, School of Physical Education, Physical Therapy and Occupational Therapy, Universidade Federal de Minas GeraisDepartment of Physical Therapy, Faculty of Social Welfare and Health Sciences, University of HaifaDepartment of Physical Therapy, Faculty of Social Welfare and Health Sciences, University of HaifaDepartment of Physical Therapy, Universidade Federal de Minas GeraisAbstract Background Motor learning (ML) science is foundational for physical therapy. However, multiple sources of evidence have indicated a science-practice gap. Clinicians report low self-efficacy with ML concepts and indicate that the lack of access to systematic training is a barrier for practical implementation. The general goal of this preliminary study was to describe the effects of a new educational intervention on physical therapy student’s ML self-efficacy and knowledge. Methods Self-efficacy was assessed with the Physical Therapists’ Perceptions of Motor Learning questionnaire. Data was acquired from third-semester students before their participation in the ML educational intervention. Reference self-efficacy data was also acquired from physical therapy professionals and first and last-semester students. The educational intervention for third-semester students was designed around an established framework to apply ML principles to rehabilitation. A direct experience, the “Learning by Doing” approach, in which students had to choose a motor skill to acquire over 10 weeks, provided the opportunity to apply ML theory to practice in a personally meaningful way. After the intervention self-efficacy was re-tested. ML knowledge was tested with an objective final exam. Content analysis of coursework material was used to determine how students comprehended ML theory and related it to their practical experience. The Kruskal-Wallis and Mann-Whitney U tests were used to compare self-efficacy scores between the four groups. Changes in self-efficacy after the educational intervention were analyzed with the Wilcoxon test. Spearman rank correlation analysis was used to test the association between self-efficacy and final exam grades. Results By the end of the intervention, students’ self-efficacy had significantly increased (p < 0.03), was higher than that of senior students (p < 0.00) and experienced professionals (p < 0.00) and correlated with performance on an objective knowledge test (p < 0.03). Content analysis revealed that students learned to apply the elements of ML-based interventions present in the scientific literature to a real-life, structured ML program tailored to personal objectives. Conclusions Positive improvements were observed after the intervention. These results need confirmation with a controlled study. Because self-efficacy mediates the clinical application of knowledge and skills, systematic, active training in ML may help reduce the science-practice gap.https://doi.org/10.1186/s12909-021-02486-1Motor learningActive learningEducationPhysical therapy |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Daniela V. Vaz Erica M. R. Ferreira Giulia B. Palma Osnat Atun-Einy Michal Kafri Fabiane R. Ferreira |
spellingShingle |
Daniela V. Vaz Erica M. R. Ferreira Giulia B. Palma Osnat Atun-Einy Michal Kafri Fabiane R. Ferreira Testing a new active learning approach to advance motor learning knowledge and self-efficacy in physical therapy undergraduate education BMC Medical Education Motor learning Active learning Education Physical therapy |
author_facet |
Daniela V. Vaz Erica M. R. Ferreira Giulia B. Palma Osnat Atun-Einy Michal Kafri Fabiane R. Ferreira |
author_sort |
Daniela V. Vaz |
title |
Testing a new active learning approach to advance motor learning knowledge and self-efficacy in physical therapy undergraduate education |
title_short |
Testing a new active learning approach to advance motor learning knowledge and self-efficacy in physical therapy undergraduate education |
title_full |
Testing a new active learning approach to advance motor learning knowledge and self-efficacy in physical therapy undergraduate education |
title_fullStr |
Testing a new active learning approach to advance motor learning knowledge and self-efficacy in physical therapy undergraduate education |
title_full_unstemmed |
Testing a new active learning approach to advance motor learning knowledge and self-efficacy in physical therapy undergraduate education |
title_sort |
testing a new active learning approach to advance motor learning knowledge and self-efficacy in physical therapy undergraduate education |
publisher |
BMC |
series |
BMC Medical Education |
issn |
1472-6920 |
publishDate |
2021-01-01 |
description |
Abstract Background Motor learning (ML) science is foundational for physical therapy. However, multiple sources of evidence have indicated a science-practice gap. Clinicians report low self-efficacy with ML concepts and indicate that the lack of access to systematic training is a barrier for practical implementation. The general goal of this preliminary study was to describe the effects of a new educational intervention on physical therapy student’s ML self-efficacy and knowledge. Methods Self-efficacy was assessed with the Physical Therapists’ Perceptions of Motor Learning questionnaire. Data was acquired from third-semester students before their participation in the ML educational intervention. Reference self-efficacy data was also acquired from physical therapy professionals and first and last-semester students. The educational intervention for third-semester students was designed around an established framework to apply ML principles to rehabilitation. A direct experience, the “Learning by Doing” approach, in which students had to choose a motor skill to acquire over 10 weeks, provided the opportunity to apply ML theory to practice in a personally meaningful way. After the intervention self-efficacy was re-tested. ML knowledge was tested with an objective final exam. Content analysis of coursework material was used to determine how students comprehended ML theory and related it to their practical experience. The Kruskal-Wallis and Mann-Whitney U tests were used to compare self-efficacy scores between the four groups. Changes in self-efficacy after the educational intervention were analyzed with the Wilcoxon test. Spearman rank correlation analysis was used to test the association between self-efficacy and final exam grades. Results By the end of the intervention, students’ self-efficacy had significantly increased (p < 0.03), was higher than that of senior students (p < 0.00) and experienced professionals (p < 0.00) and correlated with performance on an objective knowledge test (p < 0.03). Content analysis revealed that students learned to apply the elements of ML-based interventions present in the scientific literature to a real-life, structured ML program tailored to personal objectives. Conclusions Positive improvements were observed after the intervention. These results need confirmation with a controlled study. Because self-efficacy mediates the clinical application of knowledge and skills, systematic, active training in ML may help reduce the science-practice gap. |
topic |
Motor learning Active learning Education Physical therapy |
url |
https://doi.org/10.1186/s12909-021-02486-1 |
work_keys_str_mv |
AT danielavvaz testinganewactivelearningapproachtoadvancemotorlearningknowledgeandselfefficacyinphysicaltherapyundergraduateeducation AT ericamrferreira testinganewactivelearningapproachtoadvancemotorlearningknowledgeandselfefficacyinphysicaltherapyundergraduateeducation AT giuliabpalma testinganewactivelearningapproachtoadvancemotorlearningknowledgeandselfefficacyinphysicaltherapyundergraduateeducation AT osnatatuneiny testinganewactivelearningapproachtoadvancemotorlearningknowledgeandselfefficacyinphysicaltherapyundergraduateeducation AT michalkafri testinganewactivelearningapproachtoadvancemotorlearningknowledgeandselfefficacyinphysicaltherapyundergraduateeducation AT fabianerferreira testinganewactivelearningapproachtoadvancemotorlearningknowledgeandselfefficacyinphysicaltherapyundergraduateeducation |
_version_ |
1724326312833712128 |