Integrating ChatGPT in Teacher Education: Examining Early Childhood and Elementary Pre-Service Teachers’ Experiences in AI-Assisted Math Lesson Planning

This study examines how pre-service teachers in early childhood education (ECE) and elementary education (ELE) integrate ChatGPT into mathematics lesson planning. Using a mixed-methods case study framed by the Technological Pedagogical Content Knowledge (TPACK) with Contextual Knowledge (XK) framework and AI literacy, we analyzed the experiences of 44 pre-service teachers (24 ECE, 20 ELE) in mathematics method courses at a university in the Midwestern United States. Data sources included pre- and post-assessments, documentation of ChatGPT interactions, lesson plans, and reflection papers. Findings reveal significant gains in participants’ knowledge of and confidence in using ChatGPT, with increased willingness to incorporate generative AI tools into their teaching practices. Thematic analysis identified six categories of ChatGPT use in lesson planning, from content generation to final refinement, while highlighting challenges in adapting AI-generated content to meet developmentally appropriate practices and specific classroom needs. While both ECE and ELE groups followed similar patterns in ChatGPT usage, their approaches varied based on grade-level contexts. This study demonstrates how the development of integrated TPACK-XK competencies and AI literacy supports effective ChatGPT integration in math lesson planning. Findings contribute to understanding how teacher education programs can prepare future educators to integrate generative AI technologies while maintaining pedagogical integrity.