## 4 Content and Results of Research
### Content of Research
#### 4.1.3 Course Flow Design
Teachers utilize these data, combined with the teaching objectives of the plant cultivation and maintenance course, to assess students' learning progress through data mining and intelligent analysis techniques. By understanding students' mastery of plant cultivation and maintenance, teachers can tailor teaching designs and guidance, providing personalized learning support to students. By integrating the content of the plant cultivation and maintenance course into prelearning tasks, students' learning effectiveness and practical abilities can be enhanced more effectively, enabling them to gain a deeper understanding and application of the knowledge learned in class. The digital twin learning system automatically groups students with different learning situations and assigns subdivided tasks to suitable students. Finally, based on students' prelearning results, the system automatically pushes teachers' preuploaded learning resources of different difficulty levels and differentiated content. The digital twin learning system visualizes learners' prelearning data (Figure 10b). With the visualization of data, teachers can diagnostically assess students' prelearning effectiveness and mastery of knowledge points, providing a basis for classroom teaching design. 2. In-class project implementation and evaluation. In the depth of the project-based learning, students will delve into the growth and development patterns of landscing plants and their adaptability to the environment. They will apply acquired knowledge to real design projects. Teachers will highlight the challenges in courtyard landscape design, such as the need to consider various factors like size, shape, light, and moisture, ensuring the rationality and feasibility of design plans. Students are required to demonstrate systematic thinking, analytical skills, and innovative thinking in proposing technical ideas and designing solutions. Through collaborative teamwork, they will collectively complete project tasks. Teachers will form study groups of four based on students' individual circumstances to discuss and analyze project requirements and devise corresponding solutions collaboratively. Based on these solutions, group members will divide tasks and conduct on-site inspections in designated training areas on campus to select a practical courtyard site for design and practice. Each group of students will be allocated a 4 \(\times\) 5 m area in the training area by the teacher, who will also determine the location and size of the courtyard. Students, working in groups, will choose a courtyard project based on the results of on-site inspections, such as renovating an old courtyard or creating a leisure garden. Based on on-site inspection results and theoretical knowledge, students will conduct virtual landscape design and plan optimization, including plant maintenance, landscape layout, and greening construction (Figure 11). Figure 10: Digital twin learning system prelesson interface. (**a**) Students view teacher-created projects; (**b**) visualization of student precourse preparation data. Taking the example of a student team designing a public landscape space, the team consists of four vocational high school students majoring in landscaping. Each student is responsible for designing one module of the public landscape space model (Figure 12). During the design process, each student can upload their design data to the digital twin platform at any time. The design data automatically generate a three-dimensional digital twin model for visualization. Consequently, as long as any student submits updated data, all students can instantly view the latest-generated landscape space model along with its detailed design parameters. They can even simulate its operation in different environments using the digital twin. Furthermore, every historical update state of the digital twin is meticulously recorded. Students can backtrack to any state in the design process and review the digital twin model parameters and performance at that state.