İnal Özgü, Özkan Esma, Göktaş Ayşe
Faculty of Gülhane Physiotherapy and Rehabilitation, Department of Neurologic Physiotherapy-Rehabilitation, University of Health Sciences Turkey, Ankara, Turkey.
Faculty of Gülhane Health Sciences, Department of Occupational Therapy, University of Health Science Turkey, Ankara, Turkey.
Br J Occup Ther. 2023 Aug;86(8):577-586. doi: 10.1177/03080226231172333. Epub 2023 May 14.
Many of the studies on learning have focused on face-to-face or online learning, and information on hybrid learning is limited. The aim of this study is to examine the predictors of perceived learning in occupational therapy students in terms of different variables in the hybrid education process.
This study, which was planned in descriptive cross-sectional design, was carried out online using Google Forms. Attentional Control Scale, Academic Motivation Scale, and Perceived Learning Scale were used in this study. Multiple linear regression analysis was performed with the stepwise variable selection method.
The coefficient of the Academic Motivation Scale Amotivation variable, which made the greatest contribution to the variance rate explained by the regression model, was -0.407. A one-unit increase in the Academic Motivation Scale Intrinsic Motivation and Academic Motivation Scale Extrinsic Motivation variables caused an increase in the Perceived Learning Scale total score of 0.198 and 0.364 standard deviations (SDs), and a one-unit increase in the Academic Motivation Scale_Amotivation variable caused a decrease in the Perceived Learning Scale total score of 0.407 SD.
The most important predictor of perceived learning is amotivation. We suggest that improving the intrinsic and extrinsic motivation and reducing amotivation in students studying at universities offering hybrid learning can be used as a strategy that increases attentional control and perceived learning.
许多关于学习的研究都集中在面对面学习或在线学习上,而关于混合式学习的信息有限。本研究的目的是在混合式教育过程中,从不同变量的角度考察职业治疗专业学生感知学习的预测因素。
本研究采用描述性横断面设计,通过谷歌表单在线进行。本研究使用了注意力控制量表、学业动机量表和感知学习量表。采用逐步变量选择法进行多元线性回归分析。
对回归模型解释的方差率贡献最大的学业动机量表无动机变量的系数为-0.407。学业动机量表内在动机和学业动机量表外在动机变量每增加一个单位,感知学习量表总分分别增加0.198和0.364个标准差(SDs),学业动机量表无动机变量每增加一个单位,感知学习量表总分降低0.407个标准差。
感知学习的最重要预测因素是无动机。我们建议,对于在提供混合式学习的大学学习的学生,提高其内在和外在动机并减少无动机,可以作为一种增加注意力控制和感知学习的策略。