Title: The Application of Virtual Simulation and Large Model in Forestry Education in China
Time: Thur. June 26, 2025, 6–7 PM PDT (Vancouver)
Speaker: Prof. Juan Shi
Beijing Forestry University
Forestry Protection with a Ph.D. in Forestry Sciences
Profile:
My research focuses on utilizing advanced technologies, including risk analysis, eco-friendly pest control, and drone-based early warning systems, to prevent invasive or quarantine forest pests. Specifically, I analyze the genetic structure and functional genes of invasive forest pests, investigate their invasion mechanisms and proliferation patterns, and conduct risk assessments and traceability studies. These efforts aim to achieve earlier detection, smarter prevention, and more sustainable control of invasive pests, thereby safeguarding forest ecosystems.
At Beijing Forestry University, I teach Invasion Biology, General Entomology, and Animal and Plant Quarantine. I have also served as the Deputy Dean of the School of Forestry.
Abstract:
As educational informatization advances, forestry education is transitioning from “emphasizing knowledge over practice” to “integrating knowledge with action.” This report highlights the convergence path of virtual simulation + large language models (LLMs), exploring the practical application of new technologies in forestry education.
Virtual simulation employs 3D modeling and interactive animations to recreate fieldwork scenarios, addressing challenges in traditional training, such as high-risk operations and difficulty in replication. Meanwhile, LLMs enhance text-image comprehension and intelligent Q&A, enabling AI-powered forestry teaching assistants that provide full-process assessment and personalized feedback.
The report demonstrates case studies from multiple forestry universities in courses such as Forest Mensuration, Entomology, and Forest Fire Management. Students can conduct high-difficulty experiments in virtual environments, such as tree harvesting, insect morphology observation, and wildfire suppression, significantly improving accessibility and safety in practical training.
Additionally, intelligent systems like the Niu Xingxing virtual assistant and the Forest Dragon industry LLM have upgraded teaching from knowledge delivery to evaluation and feedback, fostering an immersive educational framework characterized by virtual-physical integration, teaching-assessment unity, and human-AI collaboration. This provides an innovative paradigm for cultivating forestry talent in the new era.