Early Artificial Intelligence Education: Effects of Cooperative Play and Direct Instruction on Kindergarteners' Computational Thinking, Sequencing, Self-Regulation and Theory of Mind Skills

Background: While the integration of robot-based learning in early childhood education has gained increasing attention in recent years, there is still a lack of evidence regarding the impact of AI robots on young children's learning. Objectives: The study explored the effectiveness of two AI education approaches in advancing kindergarteners' computational thinking, sequencing, self-regulation and theory of mind skills. Methods: An experiment was conducted with 90 kindergarteners (ages 5-6) randomly assigned to either a direct instruction (DI), cooperative play (CP) or control group. Results: Results show that (1) children in all three groups had significant improvements on computational thinking, sequencing and self-regulation; (2) both early AI education approaches (CP and DI) significantly enhance young children's computational thinking, sequencing, self-regulation and theory of mind skills; (3) the DI group had significant higher improvement than the CP group on computational thinking; (4) the CP group exhibited greater enhancements in theory of mind skills than the DI group. Conclusion: These findings jointly demonstrate that each AI educational approach has unique strengths, underscoring the significance of designing new pedagogies to expand children's skills.