Exploring the Impact of the Learning Sequence of Computational Thinking and Programming on Learning Outcomes

The primary objective of this research was to investigate effective learning sequences starting with computational thinking, programming, or both. We experimented with and analyzed the learning sequence of students from the Department of Computer Engineering, Information Management, and Mechanical Engineering. The findings indicated that the students of the Department of Computer Engineering possessed prior experiences in programming or computational thinking. Their learning sequences limitedly impacted learning outcomes. Conversely, for the students of the Department of Information Management, learning computational thinking before programming did not result in better learning outcomes, emphasizing the need for coherence in courses. The students of the Department of Mechanical Engineering showed the practical value of computational thinking in non-IT disciplines, particularly in using specialized software such as MATLAB. For students with foundational knowledge, the learning sequence between learning computational thinking and programming was less significant. However, for beginners or those from non-IT backgrounds, effective learning required the coherence and integration of courses. Thus, it is required to maintain cross-course coherence and establish links between computational thinking and programming skills to offer a more in-depth learning experience.