The Development of Students' Computational Thinking Practices in AI Course Using the Game-Based Learning: A Case Study
Jingsi Ma, Yi Zhang, Hesiqi Bin, Kang Wang, Jinfang Liu, Hanrui Gao · 2022
Promoting the computational thinking of the K12 students through artificial intelligence education is reflected in curriculum standards and academic research. Game-based learning promotes the learning interest and motivation, helps students reinforce computational thinking practices. Based on the input-process-result (IPO) game-based learning model, this study integrated the artificial intelligence instructional content, game-based learning, and the core elements of computational thinking practice to design game-based learning activities that was suitable for promoting computational thinking practices in artificial intelligence courses. In this research, the artificial intelligence course “Challenging Tic-Tac-Toe” was conduct in senior high school. The results showed that the game-based learning in artificial intelligence courses could help students to master artificial intelligence subject knowledge, significantly improved the computational thinking practices, enhanced learning interest, motivation, self-confidence, and reduce cognitive load. Thus, this study provides additional evidence that using the game-based learning strategies is an effective learning method that improves both learning performance and computational thinking practices.