Tailoring AI agents for early learning: The Creative Project Approach

This paper explores the integration of AI agents within the Project Approach in early childhood education (ECE) to enhance children’s creative learning in the digital age. Addressing the current lack of guidance in this area, the paper conceptualizes how AI agents can be specifically tailored to foster creativity in young learners. Drawing upon theoretical foundations and empirical evidence, it proposes a “Creative Project Approach” that integrates generative AI and robotics in ECE. A pedagogical framework is developed, consisting of five key steps: (1) identifying learning needs, (2) facilitating child-robot interaction with teacher guidance, (3) situating AI and robot use in various learning contexts, (4) determining the appropriate level of automation and creativity, and (5) evaluating learning outcomes. The paper suggests that leveraging generative AI and robotics within the Creative Project Approach holds significant promise for fostering engagement and creativity in AI-native children. • Proposes the Creative Project Approach integrating generative AI and robotics in early childhood education. • Develops 5-step pedagogical framework for AI-agent-enhanced creative learning. • Highlights physical robots’ superiority over screens for young children’s engagement. • Shows coding robots/social robots foster computational thinking and social-emotional skills via cases. • Discusses tech limitations and calls for teacher training in AI-robot integration.

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Publication Details

Journal
Computers and Education Artificial Intelligence
Published
2025-09-05
DOI
https://doi.org/10.1016/j.caeai.2025.100473
Citations
5
Primary Topic
Reinforcement Learning in Robotics
Type
article
Field-Weighted Citation Impact
12.40
Controls
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article

Tailoring AI agents for early learning: The Creative Project Approach

Weipeng Yang, John Chi‐Kin Lee, Hui Li
5 citations
Computers and Education Artificial Intelligence
Reinforcement Learning in Robotics
12.40
article

Tailoring AI agents for early learning: The Creative Project Approach

Weipeng Yang, John Chi‐Kin Lee, Hui Li
article en
5 citations

Abstract

This paper explores the integration of AI agents within the Project Approach in early childhood education (ECE) to enhance children’s creative learning in the digital age. Addressing the current lack of guidance in this area, the paper conceptualizes how AI agents can be specifically tailored to foster creativity in young learners. Drawing upon theoretical foundations and empirical evidence, it proposes a “Creative Project Approach” that integrates generative AI and robotics in ECE. A pedagogical framework is developed, consisting of five key steps: (1) identifying learning needs, (2) facilitating child-robot interaction with teacher guidance, (3) situating AI and robot use in various learning contexts, (4) determining the appropriate level of automation and creativity, and (5) evaluating learning outcomes. The paper suggests that leveraging generative AI and robotics within the Creative Project Approach holds significant promise for fostering engagement and creativity in AI-native children. • Proposes the Creative Project Approach integrating generative AI and robotics in early childhood education. • Develops 5-step pedagogical framework for AI-agent-enhanced creative learning. • Highlights physical robots’ superiority over screens for young children’s engagement. • Shows coding robots/social robots foster computational thinking and social-emotional skills via cases. • Discusses tech limitations and calls for teacher training in AI-robot integration.

Computers and Education Artificial IntelligenceVol. 9
Education University of Hong Kong (HK)
Openalex Percentile: Top 2%
Reinforcement Learning in Robotics
12.40
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