Engagement predicts computational thinking skills in unplugged activity: Analysis of gender differences

Abstract

Engagement is critical to computational thinking and programming education. However, as multi-dimensional variables, when analyzing how different aspects of engagement in computational thinking tasks influence skills development, it becomes crucial to discern precisely which engagement components intersect with the progression of computational thinking skills. This discernment is pivotal because engagement can vary based on the task nature, the context, and the individual's preferences. Therefore, the purpose of this study is to explore the gender differences in engagement and computational thinking skills and the predictive relationships among these sub-dimensions for boys and girls in an unplugged environment. In this study, a quasi-experiment for 90 sixth-grade students from a north Chinese primary school was performed. By partial least squares–structural equation modeling, students’ models of computational thinking skills and engagement were analyzed, and comparisons of boys and girls were made by analysis of covariance statistics. Results indicated that compared with boys, girls reported higher computational thinking performance and more engagement in unplugged contexts. Furthermore, girls’ computational thinking skills were only predicted by their cognitive engagement, whereas boys’ computational thinking skills were predicted by their behavioral, emotional, and cognitive engagement. Teachers can adopt these findings to design computational thinking teaching interventions that combine the advantages of unplugged activity and focus on the engagement of boys and girls.