Suitability of Artificial Intelligence Supported Lesson Plans from the Perspective of Science Education Experts

Abstract The growing integration of Artificial Intelligence (AI) in education has brought increased interest in using AI-supported platforms for lesson planning. However, concerns remain regarding the pedagogical validity and theoretical alignment of AI-generated plans. This study examines the instructional quality of lesson plans created by two AI platforms—one general-purpose and one education-focused—through expert evaluation. Utilizing a case study design, lesson plans based on the Engineering Design-Based Learning (EDBL) approach were generated for a sixth-grade science unit, incorporating four skill dimensions from the revised Turkish science curriculum. Eleven science education experts assessed each plan using a standardized rating scale and open-ended feedback. Findings reveal that while both platforms support key competencies such as conceptual and social-emotional skills, they fall short in fully capturing the iterative and reflective processes of EDBL. The education-focused platform demonstrated higher alignment with curriculum goals and instructional sequencing. Experts emphasized that AI-generated plans can serve as useful drafts but require pedagogical adaptation and teacher judgment for effective classroom use. The study highlights the promise and limitations of AI tools in science instruction, offering insights for educators, AI developers, and curriculum designers aiming to integrate AI meaningfully into teaching practice.