SBIR Phase I: MedMicroMaps A Novel e-Learning Platform and Immersive Experience in the Microbial Metaverse for Life Science Learners

The broader/commercial impact of this SBIR Phase I project is to advance science education in microbiology through an interactive, virtual microbe world. This innovation will make complex scientific concepts more accessible to diverse learners, including those traditionally underrepresented in STEM. The application allows students to explore microscopic organisms at various scales, enhancing understanding of microbiology, immunology, and public health.

By providing immersive, hands-on experiences, it brings textbook concepts to life, potentially improving comprehension and retention. The project targets educational institutions offering life science programs, particularly undergraduate medical education, with plans to expand to other disciplines and secondary education markets. This technology addresses the growing need for engaging, technology-enhanced learning tools in STEM education.

By improving science literacy on microbial infections, vaccines, and antibiotics, the project serves the national interest in advancing health and scientific understanding. The business model focuses on institutional licensing, with potential for individual subscriptions. This approach could significantly impact how students learn about and interact with the microbial world, fostering a deeper appreciation for life sciences.

This Small Business Innovation Research (SBIR) Phase I project addresses the challenge of effectively teaching complex microbiology concepts to undergraduate medical students. The research objectives focus on leveraging extended reality (XR) technology and artificial intelligence to enhance the learning experience of infectious diseases and microbes.

The proposed research involves developing a novel XR application using the Meta SDK platform within the Unity game engine, incorporating 3D microbial assets created with Blender and Adobe software. These assets will feature realistic textures based on microscopy images, ensuring scientific accuracy. The system will employ a bacteriophage AI-assist to adapt content delivery based on individual learning styles, including auditory, visual, kinesthetic, and text-based approaches.

The anticipated technical results include a cross-platform accessible WebGL build compatible with XR headsets, mobile devices, and personal computers. This innovative approach aims to significantly improve learning outcomes for both traditional and non-traditional students by providing an immersive, interactive, and personalized educational experience.

The project's scope encompasses the development, testing, and evaluation of this XR-based learning system, with the potential to positively impact microbiology education in undergraduate medical curricula.

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.