The combined value of executive functions and self-regulated learning to predict differences in study success among higher education students

Diane Marcia Manuhuwa, Mirjam Snel-de Boer,Debbie Jaarsma,Joke Fleer, Jan Willem De Graaf

FRONTIERS IN PSYCHOLOGY(2023)

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摘要
IntroductionSelf-regulated learning (SRL) has traditionally been associated with study success in higher education. In contrast, study success is still rarely associated with executive functions (EF), while it is known from neuropsychological practice that EF can influence overall functioning and performance. However some studies have shown relationships between EF and study success, but this has mainly been investigated in school children and adolescents. EF refer to higher-order cognitive processes to regulate cognition, behavior, and emotion in service of adaptive and goal-directed behaviors. SRL is a dynamic process in which learners activate and maintain cognitions, affects, and behaviors to achieve personal learning goals. This study explores the added value of including EF and SRL to predict study success (i.e., the obtained credits).MethodsIn this study, we collected data from 315 first-year psychology students of a University of Applied Sciences in the Netherlands who completed questionnaires related to both EF (BRIEF) and SRL (MSLQ) two months after the start of the academic year. Credit points were obtained at the end of that first academic year. We used Structural Equation Modeling to test whether EF and SRL together explain more variance in study success than either concept alone.ResultsEF explains 19.8% of the variance, SRL 22.9%, and in line with our hypothesis, EF and SRL combined explain 39.8% of the variance in obtained credits.DiscussionThese results indicate that focusing on EF and SRL could lead to a better understanding of how higher education students learn successfully. This might be the objective of further investigation.
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关键词
executive functions,self-regulated learning,study success,academic success,higher education,student,structural equation modeling
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