Abstract:

Introduction:
Both executive functions (EF) and self-regulated learning (SRL) are associated with successful studying. However, educational research barely focuses on their combination, whereas there is a clear link between the concepts. EF refer to higher-order cognitive functions that enable adaptive and goal-directed behaviour, especially working memory, inhibition, cognitive flexibility, and metacognitions such as planning and organising. SRL refers to the metacognitive, motivational, and behavioural processes to attain learning goals systematically. EF play an essential role in addition to SRL. EF can be seen as the brain’s supervisory system that adapts to new, complex, and challenging learning situations; SRL is about the concrete strategies a student deploys to learn knowledge and skills.
To express SRL in teaching, students' SRL styles are regularly classified into group profiles, but there is little research on clustering students based on both EF and SRL. One advantage of clustering is its practical value, namely that it allows education to address these groups, with room for individual differences within them.
This study aims to:
(a) identify clusters of students with different EF and SRL
(b) examine how these clusters predict study success.

Methods:
In November 2020, 327 and a year later, 269 first-year Applied Psychology students completed questionnaires about their perceived EF problems (Behavioral Rating Inventory Executive Function-BRIEF and perceived self-regulated learning (Motivated Strategies Learning Questionnaire-MSLQ). After exploratory factor analysis, we analysed the results through hierarchical cluster analysis. Next, we compared the clusters via one-way ANOVA tests with study success operationalised in obtained credits, grade average, and the number of resits after one year of study.

Results:
As a result of the analyses, we identified three clusters:
1. Highest EF problems, moderate SRL-learning strategies, less SRL-motivated strategies (n = 162);
2. Moderate EF problems, moderate SRL (n = 225);
3. Higher EF metacognition problems, average EF behavioural problems, less SRL-learning strategies, moderate SRL-motivated strategies (n = 209).
Three conclusions emerge from the correlation analyses of study success with the three clusters. First, the groups differed in credits earned after one year of study with a small effect size (F = 16.72; df = 2, 595; p < .001; η2 = 0.05), with cluster 1 having significantly fewer obtained credits than clusters 2 and 3, and cluster 3 less than cluster 2. Second, the clusters also differed in mean grade, again with a similar small effect size (F = 16.27; df = 2,595; p < .001; η2 = 0.05). Here too, students in cluster 1 have a significantly lower grade average than clusters 2 and 3 (p < .001), but cluster 3 has lower grades than cluster 2. Finally, cluster 1 had significantly more resits than clusters 2 and 3, but there were no significant differences between clusters 2 and 3 (F = 8.33; df = 2,595; p < .001; η2 = 0.03).`1

Conclusion:
These results show that different groups of students can be identified based on EF and SRL. The students who report the highest EF problems combined with average use of SRL strategies demonstrate worse study results.

Future directions:
In a follow-up study, we will explore how to tailor to these different groups of students when designing blended learning environments. We will then formulate design principles that consider EF-fit learning environments.

Keywords:

Executive functions, self-regulated learning, study success, higher education.