Advancing Translational Science Through AI-Enhanced Teacher Learning for Early Language and Composing

Abstract

Composing in early childhood classrooms offers a critical opportunity to strengthen children’s language skills, yet many teachers feel underprepared to provide this instruction. This study examines whether an AI-enhanced digital platform (L4C) can serve as a sustainable, community-based professional development model that bridges theory and practice. Twenty-nine teachers in the southeastern United States engaged with L4C, a professional learning model designed to integrate principles from the Science of Literacy, Learning, and Instruction into a cohesive platform that links teachers’ content and pedagogical knowledge-building with lesson planning and reflective practice. Data sources included surveys, pre- and post-lesson plans, and AI usage logs from the lesson planning tool. Findings showed that teachers initially reported significant barriers to composing instruction and sought professional learning responsive to their classroom needs. After using L4C, teachers demonstrated notable growth in their knowledge of language components and the quality of their composing lesson designs. Teachers evaluated the platform positively, particularly valuing the linked videos and scripted lesson tools for making theoretical concepts actionable. These findings suggest that AI-driven platforms like L4C can advance teacher learning in practical, individualized, and contextually relevant ways, offering a promising pathway for professional development in early literacy instruction.