Against the background of new quality productivity, knowledge graphs, and AI technology have opened up new paths for higher education reform, promoting the transformation of traditional teaching models to “smart classrooms.” Taking the “Botany” course as the research object, this paper explores the path of constructing a blended online-offline teaching model using AI + knowledge graphs to address the problems of a fragmented knowledge system, static teaching resources, and a single learning path in traditional teaching. Based on the technological characteristics and educational application value of AI and knowledge graphs, a “Knowledge Graph + AI Scenario Practice + BOPPPS” model is proposed: a knowledge graph is constructed by extracting knowledge points and sorting out knowledge relationships to help students consolidate basic knowledge; scenario-based practice tasks are released through an AI course assistant to stimulate students’ learning interest, and full-process blended teaching activities of “pre-class—in-class—post-class” progressive exploration are carried out, aiming to enhance students’ independent learning, communication, and teamwork abilities. Research results show that this blended teaching model can effectively realize the systematic organization and visual presentation of botanical knowledge, significantly improving students’ learning efficiency and deep learning capabilities.
Ma WL, Wang YF, Li HQ, et al., 2022, Botany (3rd). Higher Education Press, Beijing.
Zhang LN, 2025, Research on Blended Teaching Mode Based on Knowledge Graph. Inland Science and Technology, 2025(5): 128–130.
Li Z, Zhou DY, Wang Y, 2019, Research of Education Knowledge Graph from the Perspective of “Artificial Intelligence +” Connotation, Technical Framework and Application. Journal of Distance Education, 37(4): 42–53.
Zhang LC, Yang DZ, Gao HB, et al., 2025, Integrated Project Development of Artificial Intelligence Based on Knowledge Graph and BOPPPS Blended Teaching Design. Smart Education and Equipment, 2025(6): 43–45.
Li DF, Zhang Y, Ye JH, et al., 2023, A Preliminary Study on the Use of Plant Identification App to Assist in the Reform of Botany Practice Teaching. Frontier of Higher Education, 6(8): 131–132.
Zhao DD, Wang YJ, Liu Y, et al., 2024, Construction of Intelligent Q&A System for Medicinal Plant Based on Multimodal Knowledge Graph. Knowledge Management Forum, 9(5): 487–504.
Feng PY, Du CY, Huang XG, et al., 2025, Research on the Construction of Knowledge Graph of “Color Science and Technology” Course from the Perspective of OBE Professional Certification. Printing and Digital Media Technology Study, 2025(3): 127–133.
Tan M, Le QV, 2019, EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. International Conference on Machine Learning. PMLR, 2019(97): 6105–6114.
Gong SF, Fang YY, Hu HH, et al., 2025, Innovation and Practice of Blended Teaching Mode in Course “Environmental Engineering Microbiology”. Research and Exploration in Laboratory, 44(9): 75–82.
Liang N, Zhang QY, Zhang XQ, et al., 2025, Application of Knowledge Graph with the BOPPPS Model in Teaching Perioperative Nursing. Journal of Nursing Science, 40(16): 1–6.
Hou ZW, Jing WL, Qin CZ, et al., 2025, Prospects for Mangrove Knowledge Services in the Intelligent Era: From Plant Maps to Knowledge Maps. Science China Press, 55(1): 111–125.
Zhu HF, Yao H, Shi HF, et al., 2025, Exploration on the Construction of Grass Breeding and Biotechnology Curriculum Group Based on Knowledge Graphs. Grassland and Prataculture, 37(1): 35–38.
Wang YQ, 2021, Construction Research and Application of Plant Knowledge Graph PlantKG, thesis, Guizhou University.
Xie LN, He WS, 2025, Impact and Enhancement of Biochemical Blended Learning on Students’ Ability for Independent Innovation in the AI Era. Strait Pharmaceutical Journal, 37(7): 52–56.