Abstract
As educational landscapes evolve, the potential of AI to fuel curiosity and explorative learning among students has sparked growing interest. This study explores how AI-suggested content, student motivation, and Complexity of AI-suggested content drive curiosity and proactive learning behaviours in students. Through exploratory and confirmatory analysis using SPSS and AMOS, it is revealed that AI-suggested content and resources (ACR) and student motivation level (SML) significantly elevate curiosity and engagement. In contrast, certain combinations, such as high content resources and Complexity of AI-suggested content, may unexpectedly hinder exploration. Notably, demographic factors like age, gender, and education showed no significant impact, underscoring the universal potential of AI in personalised learning. These findings highlight the value of tailoring AI resources and fostering motivation to cultivate curiosity, offering a roadmap for educators and developers aiming to unlock the full potential of AI in education.
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