Background: Atomic models are typically taught using abstract and rote methods, which limit students' conceptual understanding and reasoning skills. This study addresses these challenges through an AI-based interactive simulation that integrates the historical development of atomic models within a technological and pedagogical framework via scientific dialogues, promoting inquiry, participation, and meaningful learning in chemistry education. Aims: This study aims to evaluate the effectiveness of AI-based simulation in developing high school students' conceptual understanding, participation, and scientific reasoning skills regarding atomic models. Methods: The study utilized the design and development research method. The simulation was created on the Replit platform using a scientific dialogue approach supported by GPT-4.0. Fifty 9th-grade students volunteered for the study. Data were collected through open-ended questions and analyzed quantitatively and qualitatively using usability, user experience, and cognitive load scales. Results: Students rated the simulation as having high usability (M=4.07), good user experience (M=3.76), and low cognitive load (M=2.36). Qualitative feedback emphasized that the scientific dialogues were enjoyable and easy to use. Findings showed increased participation, improved conceptual understanding, and positive learning experiences. Discussion: Results suggest that the simulation effectively increased students' understanding and engagement in learning atomic models. Findings are consistent with previous studies highlighting the role of digital simulations in enhancing conceptual learning. AI-supported feedback and interactive dialogues encouraged motivation and scientific reasoning. Conclusions: Simulation increases student motivation and conceptual understanding by integrating historical, pedagogical, and technological elements. It supports meaningful learning and can be expanded with broader applications in future studies.
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