Research on the Influencing Factors and Mechanisms of Preservice Teachers' Human-Machine Collaborative Instructional Design Abilities

Generative artificial intelligence(GenAI) like ChatGPT has been widely integrated into education, thereby empowering educators and gaining attention for human-machine collaborative education. The human-machine collaborative teaching ability has become one of the essential core competencies for teachers. There is an urgent need to explore the factors and mechanism to assist teachers in collaborating with GenAI more efficiently. This study carried out an empirical research, collecting multidimensional performances such as technological experience, technological beliefs, higher-order thinking, and prior knowledge from 44 preservice teachers. Based on the results of multiple linear regression analysis, we found that higher-order thinking and prior knowledge had a significant impact on the level of human-machine collaborative instructional design(H-M CID), while there was a negative impact relationship between technological beliefs and the level of higher-order thinking, as well as the technological experience. Those findings could lay the foundation for cultivating teachers’ H-M CID abilities.