Enhancing Conceptual Learning in Chemical Engineering and Nanotechnology Through the Flipped-Classroom Model and AI-Curated Modules

As artificial intelligence (AI) tools become more effective at supporting instructional preparation, their use in science, technology, engineering, and mathematics (STEM) education has gained increasing practical value. This study investigates how AI-curated video illustrations can support student learning in conceptually demanding fields, such as chemical engineering and nanotechnology. Over 15 weeks, students from a large public university in New York engaged with short, AI-selected animations prior to and during class time of a nanotechnology course, utilizing a flipped-classroom instructional model. Weekly surveys captured perceptions of comprehension, clarity, engagement, and retention, while final grades were compared with two prior cohorts (2023 and 2024) who received traditional lecture-based instruction. Results showed consistent increases in comprehension and retention scores, a statistically significant improvement in final grades over the traditional cohorts, and reduced grade variability. Thematic analysis of student feedback highlighted appreciation for visual clarity and brevity, alongside critiques of artificial narration and conceptual abstraction. Taken together, these findings suggest that, when paired with interactive instruction, AI-curated content can sharpen conceptual understanding and elevate pedagogical delivery in advanced STEM education.