Mastery Experience Bridges Computational Thinking and Self-Efficacy in Programming Among Non-Computer Science Majors



Author Information

Wen-Shyong Tzou, National Taiwan Ocean University, Taiwan
Yu-chu Yeh, National Chengchi University, Taiwan
Chia-Hsiang Ma, National Chengchi University, Taiwan
Xingzi Yu, National Chengchi University, Taiwan

Abstract

In today’s digital age, programming is a vital skill that fosters problem-solving, automation, and innovation across various disciplines. Moreover, computational thinking is a problem-solving approach that helps develop logical thinking and problem-solving across disciplines. It’s especially important in this artificial intelligence age. To help non-computer science majors bridge foundational programming knowledge with practical application, we developed a 18-week experimental course integrating hands-on learning, problem-based learning, project-based learning, scaffolding instruction, and digital learning strategies. This study examined the relationships among computational thinking, mastery experience in programming, and self-efficacy in programming among 44 college students enrolled in the course. A process model analysis revealed a significant positive relationship between computational thinking and mastery experience, while mastery experience strongly predicted self-efficacy in programming after taking the experimental course. Notably, computational thinking did not directly influence self-efficacy, suggesting that mastery experience fully mediates this relationship. These findings highlight the importance of enhancing computational thinking and the critical role of mastery experience in enhancing students’ programming confidence.


Paper Information

Conference: PCE2025
Stream: Learning Experiences

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Posted by James Alexander Gordon