Cultivating computational thinking in a STEM course through the ICDCO instructional model

Abstract Computational thinking, the thinking processes and skills for analyzing and developing computational solutions to solve real-world problems, has been increasingly cultivated through STEM (Science, Technology, Engineering, and Mathematics) programs that integrate programming and non-programming disciplines in authentic problem-solving tasks. To guide students in learning with complex programming tasks, existing studies have employed explicit instructional models (i.e., identifying problems, decomposing programming tasks, coding, and optimizing programs). However, these models are inadequate to support young learners, who often struggle to connect non-programming knowledge to programming processes and accomplish each phase of the complex task. This study proposed the ICDCO instructional model that features (a) incorporating interdisciplinary knowledge acquisition into the task process and (b) providing rules-of-thumb to guide each phase of the task. An action research study was conducted with 136 students from three primary schools in Mainland China and Macau. Results show that after taking a STEM course designed using the ICDCO instructional model, students significantly increased their overall self-perceived computational thinking skills and performed well in decomposing a complex problem. The impact of the approach was affected by class size and students’ educational level but not by gender. The findings suggest that the proposed approach can benefit students’ computational thinking skills and performance in decomposing a complex task. More support should be provided for students in large classes and at lower educational levels. Further research is needed to examine the effects of the ICDCO instructional model and the factors that influence its application in cultivating computational thinking in STEM courses.