This study explored the relationships among programming self-efficacy, learning strategies, and computational thinking on the basis of self-regulation theory. This study also investigated whether the cognitive styles moderated the structural relationships among the factors through the comparison between analytical and intuitive learners. The participants were 487 high school students enrolled in a computer programming course. Through partial least squares–structural equation modeling, this study confirmed that self-regulated learning strategies influenced computational thinking regardless of the cognitive styles. Programming self-efficacy also influenced self-regulated learning strategies. This study implied that self-efficacy is a prerequisite for self-regulated learning strategies for computer programming. However, the direct effects of programming self-efficacy on computational thinking were observed only in the intuitive students. Programming self-efficacy had an indirect impact on computational thinking through self-regulated learning strategies in analytical students. The self-regulated learning strategies, including metacognitive self-regulation and effort regulation, should be facilitated to improve the computational thinking of analytical students. In addition, this study suggested offering tailored instruction to cater to students with different cognitive styles, ultimately enhancing the effectiveness of computational education and positive programming behavior.
Li et al. (2025) studied this question.