Using Generative Artificial Intelligence to Facilitate Early STEM Learning: A Case Study in a Chinese Kindergarten

The increasing integration of generative artificial intelligence (GenAI) into early learning necessitates critical investigation into its pedagogical implications. This study examined the operationalization of GenAI within child-focused pedagogy and assessed teacher perspectives on its efficacy. Three classrooms, six teachers and their 88 children at a Chinese kindergarten engaged in STEM projects utilizing GenAI. Data triangulation was established through videotaped observations, semi-structured teacher interviews, and artifacts. Research Findings: Evidence revealed that children participated in GenAI-facilitated STEM learning via a pedagogical framework encompassing planning, inquiry iteration with problem scaffolding, creative inquiry, interaction promotion, and sharing/reflection. Teachers held cautiously positive attitudes toward GenAI integration in early STEM, some shifted from initial skepticism to acceptance, and they recognized GenAI as a valuable assistant that supplements their project-related knowledge, provides multimedia materials for children; however, they faced challenges such as children’s limited ability to give prompts, GenAI’s age-inappropriate outputs, and GenAI’s rhetorical questions distracting children, which increased their guidance workload. Practice or Policy: Our findings inform the feasibility of using GenAI to facilitate early STEM learning via a pedagogical framework as practical scaffolding.