The mediating role of metacognition in the relationship between executive function and self-regulated learning

Background: Researchers have demonstrated significant relations among executive function, metacognition, and self-regulated learning. However, prior research emphasized the use of indirect measures of executive function and did not evaluate how specific executive functions are related to participants’ self-regulated learning. Aims: The primary goals of the current study were to examine and test the relations among executive function, metacognition, and self-regulated learning as well as to examine how self-regulated learning is informed by executive function. Sample: The sample comprised 117 undergraduate students attending a large, Mid-Atlantic research university in the United States. Methods: Participants were individually administered direct and indirect measures of executive function, metacognition, and self-regulated learning. A mediation model specifying the relations among the regulatory constructs was proposed. Results: In multiple linear regression analyses, executive function predicted metacognition and self-regulated learning. Direct measures of inhibition and shifting accounted for a significant amount of the variance in metacognition and self-regulated learning beyond an indirect measure of executive functioning. Separate mediation analyses indicated that metacognition mediated the relationship between executive functioning and self-regulated learning as well as between specific executive functions and self-regulated learning. Conclusions: The findings of this study are supported by previous research documenting the relations between executive function and self-regulated learning, and extend prior research by examining the manner in which executive function and self-regulated learning are linked. The findings provide initial support for executive functions as key processes, mediated by metacognition, that predict self-regulated learning. Implications for the contribution of executive functions to self-regulated learning are discussed.