2026 ASEE Annual Conference & Exposition

This pilot study explores the development and implementation of EcoView, an AI-enhanced mobile application designed to support K–12 students in learning Biologically Inspired Design (BID). Rooted in the structure-function-mechanism (SFM) framework, BID enables learners to analyze nature’s evolved strategies for solving engineering challenges. However, students often struggle to grasp complex biological concepts without hands-on support. To address this, EcoView integrates artificial intelligence to analyze user-submitted animal images and automatically generates educational insights that bridge biology and engineering. The app’s three-part design: Educate, Explore, and Extrapolate, scaffolds users’ understanding of BID by combining a curated knowledge base, real-time image analysis using AI, and interactive feedback features such as quizzes. A mixed-methods study involving surveys and interviews assessed the app’s usability, engagement, and educational impact. Findings indicate that students found the app easy to navigate and engaging, with interactive features enhancing motivation and learning. While AI effectively supported conceptual understanding among users with limited prior knowledge, the results also revealed the need to simplify content for younger learners and to improve instructional clarity. Overall, this research highlights the potential of AI-driven educational apps to make complex interdisciplinary topics, such as BID, more accessible, personalized, and engaging for learners in STEM and engineering education.