Artificial Intelligence Empowers Botany Field Course in Higher Education: Model Exploration and Practical Pathways

Abstract

With the in-depth advancement of the educational digitalization strategy, artificial intelligence (AI) technology provides crucial support for the reform and innovation of botany internship teaching in higher education. Focusing on the theme of "AI empowering botany field course," this paper systematically explores the application models and practical pathways of AI technology in botany field course. It analyzes the limitations of traditional botany field course in terms of teaching content, resources, methods, and assessment, and elaborates on how AI technology, through various forms such as intelligent recognition, knowledge graphs, virtual simulation, electronic specimens, QR code learning, and intelligent assessment, promotes the transformation of botany internship teaching towards intelligence, personalization, and efficiency. Drawing on practical cases from multiple universities, the paper summarizes the implementation pathways and principles of AI-empowered botany field course and analyzes its role in enhancing teaching effectiveness, optimizing resources, and reforming assessment. Simultaneously, it points out current challenges in AI application, including high student dependency, insufficient teacher digital literacy, and high technical costs, proposing corresponding solutions. Future development directions involving multi-technology integration and adaptive learning systems are also discussed. Research indicates that the deep integration of AI technology and botany field course helps construct a new internship teaching model characterized as student-centered, combining virtual and real experiences, and fully intelligentized throughout the process, providing theoretical reference and practical guidance for the digital transformation of botany practical teaching in higher education.