Category of Work

Article

Publication Title

AI‐Assisted Integration of Computational Thinking: Pre‐service Teachers’ Experiences in Early Childhood Mathematics Education

Abstract

This study examined how pre-service teachers utilize artificial intelligence (AI) tools to integrate computational thinking (CT) in early childhood mathematics education. Through a qualitative case study guided by the TPACK framework, we examined 24 early childhood pre-service teachers enrolled in a mathematics methods course as they developed CT-integrated math lesson plans using AI assistance. Data sources included pre- and post-course open-ended questionnaires, CT exploration assignments, AI interaction documentation, lesson plans, and reflection papers. The findings revealed three patterns in how pre-service teachers leveraged AI as a scaffold: generating initial ideas for CT integration, refining these ideas for specific teaching contexts, and clarifying CT concepts for deeper understanding. Pre-service teachers demonstrated strategic decision-making in their AI use, successfully designing developmentally appropriate CT-integrated activities while maintaining professional judgment in content adaptation. This study highlights the critical need for structured approaches to AI integration in teacher preparation programs that effectively balance technological proficiency with pedagogical integrity. The implications suggest the importance of developing comprehensive frameworks for AI use in early childhood teacher preparation, addressing both theoretical foundations and practical implementation strategies.

First Page

987

Last Page

1015

DOI

https://doi.org/10.1007/s13158-025-00434-4

Publication Date

6-27-2025

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Available for download on Saturday, June 27, 2026

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