With the rapid development of information,digital and intelligent technology in smart agriculture,how to change from"technology-driven"to"data-driven"smart agricultural education reform has become an urgent problem to be solved.In view of the practical problems such as most of the students majoring in agriculture are in a depressed learning state and are not interested in traditional agricultural basic knowledge and production technology.By using the technology of deep learning,this paper makes an innovative exploration on the teaching reform of smart agriculture in the aspects of teaching model,examples,teaching methods and students'learning achievement evaluation.For example,around the key technical issues such as the prevention and control of diseases and insect pests in the smart greenhouse,this paper guides the students to consult the data and puts forward the project and design plan for the prevention and control of diseases and insect pests;guides the students to watch the"micro-courseware"of extracurricular teaching videos and discuss the problems with teachers in real time;collects and organizes agricultural data and materials,establishes a data model,and builds an early warning scheme for pest control.This"data-driven"teaching model creates a diversified learning environment for students,enhances their learning experience,and makes students realize the practical value of mastering advanced science and technology and the knowledge of smart agriculture,so as to improve the"appropriateness"of teaching effect and agriculture-related education.
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