Not Magic but Manageable: Generative AI and Instructional Decision‐Making in Structured Reading Intervention

Planning reading interventions often calls for working within a research‐aligned program while tailoring instruction for student needs. We explored how generative artificial intelligence (GenAI) can support educators in reading intervention planning by examining how two novice teachers in a university‐based intervention program used GenAI tools to generate materials, customize texts, and refine lessons. Using the Technological Pedagogical Content Knowledge (TPACK) framework and a sociocognitive lens, we examined how teachers' use of GenAI evolved from basic prompting to strategic pedagogical reasoning. Planning became a space for professional learning, where tutors honed content and pedagogical understanding, refined decision‐making, and grew more confident in instructional adaptation. When embedded in collaborative systems, GenAI use surfaced instructional judgment and supported responsive adaptation, though it did not replace the need for human oversight. We offer implications for teacher educators, interventionists, and school leaders seeking to integrate GenAI in ways that strengthen pedagogical growth and instructional responsiveness.