Making Invisible Ecological Processes Visible Through Technology-Enhanced Place-Based Science Learning

Many of the most important processes in nature are hidden from direct view. For example, students can see a milkweed plant, but they cannot normally watch its underground roots spread, observe microscopic interactions between plants and microbes, or see pollination and seed dispersal processes unfold on demand. As a result, outdoor science learning often emphasizes what students can observe rather than helping them understand how ecological systems work. This project will explore how emerging technologies can make these “invisible worlds” visible, tangible, and easier to discuss in real outdoor learning environments. The research team will co-design four place-based science learning modules with educators and disciplinary experts and implemented with middle and high school learners at an outdoor learning facility operated by the Lubbock Independent School District Agricultural Science, Technology, Engineering, and Mathematics (LISD AgriSTEM) program. The modules will integrate augmented and mixed reality visualizations, artificial intelligence-supported inquiry dialogue, and three-dimensional fabricated biological models to reveal processes such as root growth, plant-microbe interactions, pollination, and seed dispersal. These tools will allow middle and high school learners to visualize hidden ecological processes, interact with physical models, and engage in guided scientific questioning while studying real plants and habitats. By connecting advanced technologies with local nature, the project seeks to deepen scientific understanding, strengthen engagement, and broaden students' awareness of technology-driven careers in science, agriculture, and environmental fields. The project will also produce adaptable learning resources for schools, parks, botanical gardens, and other community learning settings, helping transform everyday urban nature spaces into accessible places for scientific discovery and learning. The project will investigate how overlapping visual, conversational, and tactile technologies (virtual reality (VR), augmented reality (AR), artificial intelligence (AI), and three-dimensional printed models) influence learning in place-based science contexts. A randomized comparative study will examine technology-enhanced and traditional field-based learning using pre-tests, post-tests, and delayed post-tests to assess knowledge retention and concept formation. The study will also use spatial behavior mapping, video analysis, extended reality interaction analytics, artificial intelligence conversational records, and user experience measures to examine students' active learning engagement and inquiry interactions. Quantitative analyses will include covariance and mixed-model approaches, while qualitative and sequence analyses will examine patterns of interaction and scientific sense-making across data sources. The research will draw on embodied and situated cognition, representational modeling, and dialogic learning to develop a theoretical explanation of how multimodal technologies may jointly support perception, reasoning, and mechanistic understanding in authentic environments. Findings will contribute empirical evidence, design principles, and open-access learning modules for technology-enhanced place-based science education, with broader potential for adaptation across science, engineering, medical, and design learning contexts. This project is funded by the Research on Innovative Technologies for Enhanced Learning (RITEL) program that supports early-stage exploratory research in emerging technologies for teaching and learning. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.