Abstract
This research is located at the exciting juncture of Artificial Intelligence (AI) and education, with the specific aim of understanding how AI technologies, including Machine Learning (ML), Natural Language Processing (NLP), and Robotics affect the innovative behavior of Educarist, guided by Rogers' Theory of Innovation. It uses the theoretical underpinnings of innovation in education and the burgeoning role of AI in shaping pedagogical approaches. The study used a survey-based method to gather and analyze data from 205 Educarists in Guangdong province, China. This data underwent rigorous statistical scrutiny, including structural equation modeling, to discern the relationships between various AI technologies and innovative behaviors in early childhood education. The key findings show that NLP and Robotics play a significant role in stimulating innovative behavior among Educarists. Interestingly, despite the growing application of ML in education, its influence on innovative behavior was found to be statistically insignificant. Additionally, the analysis uncovers intriguing interrelationships among the AI technologies themselves, showing a possible synergistic effect of these technologies on innovative behavior. This research contributes to the expanding literature that explores the intersection of AI and education, supplying valuable insights into how specific AI technologies can mold innovative teaching practices. The novelty of this research lies in its empirical investigation into the impact of three different AI technologies and their interrelationships on the innovative behavior of Educarists. Nevertheless, it acknowledges its scope and generalizability limitations due to the specific sample of Educarists involved. The unexpected finding concerning the role of ML in fostering innovation presents an intriguing avenue for further research. It needs a deeper exploration into the contextual factors that influence this relationship.