Preparing future teachers for AI-enhanced science classrooms: Insights from a study of elementary teacher candidates

Grounded in qualitative data from 30 elementary teacher candidates (ETCs) in the Midwestern U.S., this case study examines ETCs’ readiness for AI-enhanced classrooms and finds that ETCs hold moderate to low confidence in teaching biology, yet express a desire to teach it more engaging for young learners. Although many ETCs had negative or vague prior perceptions of Artificial Intelligence in education (AIEd), guided classroom experiences helped them recognize its potential and limitations. Despite this growth, ETCs continued to demonstrate gaps in AI ethics and technical understanding. The study identifies ETCs’ competencies at an early developmental stage, recommends increased exposure to authentic AIEd applications, scaffolded instruction on AI foundations and ethics, and participation in professional learning communities. These insights contribute to how ETCs conceptualize and adapt to emerging technologies, offering implications for curriculum design and policy development in teacher education.