Fostering Students' Computational Thinking Through Experiential Learning in Artificial Intelligence Course

In the era of artificial intelligence, the importance of computational thinking has become more and more prominent. This study aims to explore the effective path toward the cultivation of computational thinking in artificial intelligence course. This study took Kolb's experiential learning circle (concrete experience, reflective observation, abstract conceptualization, active experiment) as the theoretical guiding basis to construct a learning model oriented to the cultivation of computational thinking. Based on this, this study carried out an empirical study to verify the effectiveness of the framework in an elementary school artificial intelligence course, and the results showed that experiential learning can effectively promote students' computational thinking and the level of the four elements of decomposition, abstraction, algorithmic thinking, and testing and debugging. This study provides a valuable reference for the practice of teaching computational thinking in primary AI courses.