Integrating AI Simulations and Computational Grounded Theory to Explore Biodynamic Education in Science Museums

This study investigates how science museums can serve as catalysts for public understanding of biodynamic agriculture by integrating AI-generated simulations and an AI-augmented grounded theory (CGT) approach. Forty-nine elementary school teachers in Taiwan participated in a workshop featuring six biodynamic-themed simulation videos created with Mootion AI, depicting insect, bird, and amphibian ecologies within biodynamic frameworks. Participants wrote reflective journals, and twelve were interviewed in focus groups. The study employed Lin et al.’s (2025) CGT model, incorporating traditional inductive coding with computational techniques such as term frequency-inverse document frequency (tf-idf) and N-gram analysis to analyze participants’ interpretive responses. Results identified eight interconnected dimensions—including cognitive clarity, affective engagement, instructional relevance, and ethical reflection—that constitute a conceptual model titled “Human-Centered Biodynamics.” Findings show that digitally mediated exhibits enhance comprehension of biodynamic principles and foster emotional and pedagogical resonance. Participants reported a shift from perceiving biodynamics as abstract to viewing it as relevant and actionable, suggesting science museums can be transformative platforms for ecological literacy when empowered by creative technologies. This study contributes to the literature on informal science education, sustainability communication, and AI-assisted qualitative research by offering a replicable framework for integrating digital storytelling and grounded theory in ecological pedagogy.