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.

Authors:
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

About the Presenter(s)
Professor Yu-chu Yeh is a University Professor/Principal Lecturer at National Chengchi University in Taiwan

Connect on Linkedin
https://www.linkedin.com/in/yu-chu-yeh-8ba911110/

Connect on ResearchGate
https://www.researchgate.net/profile/Yu-Chu-Yeh

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