# Research on the Teaching Method of Environmental Landscape Design Practice Based on IoT Network and Digital VR Technology

Authors: Bo Yang; Liu Huadong
Journal: Security and Communication Networks
 (2022)

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## Abstract

The traditional practical teaching methods are based on teachers’ narration and demonstration, with few practical opportunities for students, lack of interactivity in teaching, low interest of students in teaching, and poor teaching effect. In order to improve the teaching effect of environmental landscape design and enhance students’ learning enthusiasm, a practical teaching method of environmental landscape design based on IoT network and digital VR technology will be studied. After guiding students to carry out the cognitive construction of environmental landscape design, VR technology is used to establish virtual teaching scenes for students. To create effective virtual reality engagement in the teaching process and enable students to better grasp important design information, gesture recognition technology is employed to recognize students’ landscape design operations. After the application of the proposed teaching method in teaching was verified through examples, the students’ learning interest was significantly increased, and the excellent rate of students’ design works was increased by about 16.6%, with good teaching effect.


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## Body

## 1. Introduction

With the continuous acceleration of urbanization, especially the goal of building a harmonious society, the pace of construction of ecological civilization is also moving forward. And, with the rapid environmental landscape planning development, more and more employment opportunities are provided, and many universities and related majors begin open environmental landscape design courses. In the process of teaching environmental landscape design courses, the current status quo of landscape design education in China mostly exists in the way that teachers’ teaching is presented in the way of “speaking” and students’ learning is presented in the way of “listening.” In the classroom, traditional teaching only pays attention to the indoctrination of book knowledge and the unity of teaching, resulting in students can only accept knowledge passively. Also, purely theoretical teaching of environmental landscape design cannot achieve a better teaching effect; students must go through a lot of practice, including actual practice of a variety of different design projects, focusing on training students according to the actual situation to carry out environmental landscape design ability, in order to establish a more solid foundation for future engagement in environmental green space planning, construction, and management work. Students are required to master the knowledge of environmental landscape design and the basic theory and skills of planning and design in a comprehensive and systematic way and improve theoretical quality, aesthetic awareness, and image thinking ability after completing this course [1]. The traditional single teaching method teaches the theoretical knowledge of environmental landscape design through teachers, and with the assistance of computer 3D design software, students can try to build and design environmental landscapes. This traditional teaching method cannot help students experience the realism of environmental landscape design, and students’ practical design works cannot be processed in detail, which leads to the failure of students’ practical ability improvement.. In the literature [2], POE (Predict-Observe-Explain) techniques are used to teach experimental courses to help teachers review learners’ prior knowledge and their perspectives, monitor their learning progress, and achieve their teaching goals. The literature [3] employs BTL technologies to design a course teaching approach with 3D presentation and realistic presentation of practical examples, ensuring low computer energy consumption and reducing environmental waste during example demonstration. The literature [4, 5] describes instructional approaches for improving student learning interaction, which may promote students’ general engagement in the classroom and their self-assessed learning. Oriana Skylar [6] developed an educational strategy based on policy memoranda, in which each session receives a full exposition of the main methodological principles used, which aids students in learning abstract information. Liao and Tang [7] investigated the process and outcomes of the creative constructive method using real-world teaching examples to demonstrate the benefits of the constructive teaching style. A research on extended learning, a teaching-learning strategy used by architecture students who are new to the topic of landscape sensitization, was published in the literature [8]. Using this technique, students may learn to identify and understand natural values, landscape narratives, and landscape and human interactions. All of the above methods can enhance the teaching and learning of some courses or disciplines, but there are still limitations to the pedagogical application as they cannot provide a good environment for students to interact with practice when applied to teaching environmental landscapes.VR technology has the advantages of good immersion and conceptual advancement, and some environmental landscape design companies at home and abroad have developed software platforms for landscape design technology based on VR kernel and applied them in practice [9]. By means of simulation, virtual reality technology provides users with a realistic simulated three-dimensional environment that can interact with each other, thus establishing a virtual world. In this platform, the user can communicate and interact with the objects of the virtual world, thus creating the feeling of immersion [10]. The main characteristics of virtual reality technology are interactivity, integrity, and immersion. The use of digital VR technology in the education of environmental landscape design reduces the space restrictions of paper drawings and the faults that occur between the integrated assessment model and the environment. The use of virtual reality technology in the classroom not only serves to modernize and informatize Chinese education but also aids in teaching reform, the creation of a new environment for the nurturing of innovative talents, and the improvement of the cultivation impact of innovative talents. Environmental landscape design courses need a lot of practice, and thus this paper will look at how to teach environmental landscape design practice using digital VR technology to make it simpler for students to do practical research and take benefit of it.


## 2. Research on the Teaching Method of Environmental Landscape Design Practice Based on IoT Network and Digital VR Technology

### 2.1. Students’ Cognitive Constructs in the Teaching of Environmental Landscape Design

Environmental landscape design is not an abstract course, in which the cultivation of spatial awareness requires students to understand the specific relationships between people and things, people and people, and things and things arranged in space. The practical training course of landscape facility design is the main course of environmental landscape design, which plays an important role in the cultivation of professional ability and is an important knowledge reserve to promote the improvement of professional ability. In order to strengthen students’ spatial awareness, teachers can use VR technology to construct a virtual practice environment in environmental landscape design teaching in order to enhance students’ learning enthusiasm while strengthening their mastery of space [7, 11, 12]. Therefore, students need to be led to construct a cognitive understanding of environmental landscapes. A deeper understanding of the new cognitive constructs of landscape form will help to better understand and accept the new forms of landscape in order to further complement and improve the traditional methods of creating landscape forms.In the process of environmental landscape design, students’ morphological logic construction for landscape includes three kinds of thinking logic, including morphogenetic selection, morphological functional reasoning, and morphological pattern complementation. Among them, the morphogenetic preference logic should be based on experiential design thinking, which is realized through subjective experience with clear objectives and objective quantitative evaluation, under the combined effect of technical analysis and design view. Therefore, in the teaching process, students should be led to experience the actual environmental landscape design projects and students should be helped to theoretically adjust the preferential selection of parameters in the overall landscape design with the combination of visual data illustration and VR technology. Morphological functional reasoning requires students to have reasoning conforming to nonlinear and complex natural laws of thinking [13]. With the use of suitable mathematical tools, students should be guided to think in a dynamic manner, process the design, sequence the occurrences, and define the correlations between the parameters of the factors impacting morphology. When used in practical instruction, digital VR technology may assist students in understanding the logic of morphological pattern complementarity on two levels [14]. Students use VR devices to create corresponding landscape design projects in virtual space, are guided by teachers to make adjustments, and feel the differences before and after the adjustments with external feedback, thus gradually establishing a complete morphological pattern complementary logic. Students’ cognitive construction needs to be synchronized with teaching activities using VR technology and be practiced in VR virtual scenes after establishing a theoretical knowledge foundation for them.


### 2.2. Environmental Landscape Design VR Teaching Interactive Scene Design Construction

In order to fully grasp the conditions of landscape design, it is necessary to conduct a comprehensive analysis of the project’s objectives, safety, concepts, needs, and other factors in terms of functional positioning, architectural form, economic strength, and time duration in order to have a clear grasp of the entire landscape design process. The potential limitations and issues in it can be seen by the digital VR technology. Therefore, some conditions and requirements must be clarified when conducting environmental landscape design and simulated and analyzed through digital VR technology. The use of digital VR technology in the environmental landscape design process is essentially the use of the expressive power of the machine to replace the painted expression. And the expressive power gains tremendous progress, from flat to three-dimensional and stillness to dynamics. Interactive scenes for teaching environmental landscape design VR were designed and constructed using Unity3D software [15].Unity3D supports three scripting languages, JavaScript, C#, and Python, which have access to the underlying NET library. Also, the same object allows scripts from all three languages to execute simultaneously. All three languages execute at the same speed in Unity3D since Unity3D’s JavaScript version is compiled to native machine code using JIT. Unity3D, on the other hand, includes several self-contained resource packages, such as skyboxes, human controllers, terrain, water, and other really helpful and handy resources. The first-person controller in this system is created using the human controller resource package [16].Unity3D will import the person controller resource package into the project folder if you choose Assets-Import Package-Character Controller from the menu bar. The camera view in Unity3D’s third-person controller is set to the top of the character’s back. The camera view is placed at the character’s eyes in the first-person controller, and mouse swipes control the rotation of the camera [17]. Also, if there is terrain or surface, the axis of the object will be automatically attached to the target surface, at the same height as the target surface. The first-person controller comes with a main view camera, and we can adjust the height of this camera individually according to demand. Also, the first perspective of the teaching VR interactive scene is based on the camera import data arranged in the actual teaching space. The information collected by the camera in the real teaching space will be mapped to the virtual space through the steps of data transfer, coordinate transformation, and 3D modeling [18, 19].The camera is placed in the real teaching space in a certain attitude. The general world coordinate system and the camera coordinate system do not completely coincide, and there is rotation and translation relationship. The image plane coordinates represent the projection position of 3D field attractions on the imaging plane. In the computer, a two-dimensional matrix is used to represent an image, with pixel as the unit, and one point corresponds to one pixel [20]. Generally, the origin is the lower left corner of the plane, and the coordinates u,v of each pixel are the number of columns and rows of the pixel in the image, respectively. According to the conversion relationship between real space and camera coordinate system and between camera coordinate system and imaging plane coordinate system, the final relationship between real teaching space coordinate system and imaging plane coordinate system can be obtained [21]:(1)Zpuv1=f/dx0u000f/dyv0000000010RT01xryrzr1,where Zp is the z-axis direction vector of the imaging plane coordinate system; f is the camera’s focal length; R is the rotation transformation vector; T is the translation transformation vector; dx and dy are the width and height of each pixel, respectively, corresponding to the aspect ratio of the lens; and u0,v0 is the coordinate of the image center.For the interaction problem of using digital VR technology for teaching, in order to make students feel more intuitively the difference between the environmental landscape designed before and after the teacher’s instruction, the interaction needs to be done with the help of a joystick. Through the HTCVive grip, the corresponding animation appears after touching the contact points designed in the scene and pressing the relevant button to rotate and other actions to imitate the human hand’s effect. This approach allows for simple imitation, but the feedback to the system is not based on the real movements of the human hand, which can greatly reduce the immersion of VR device users [22]. Therefore, Leap Motion-based gesture motion recognition for feedback between the environmental landscape scene and the device user can maximize the immersion of VR technology. Therefore, in this paper, some basic gesture movements will be trained and recognized to improve the experience of students in VR teaching.


### 2.3. Realizing the Teaching of Environmental Landscape Design Practice

When students use the handles to practice environmental landscape design in virtual space, they need timely feedback on operational adjustments in order to improve the realism of teaching and learning. The feature vector utilized in this research is made up of single-finger features and two-finger features since the depth data frame provided by the Leap Motion sensor is made up of finger position, palm position, scale data, data frame timestamp, rotation, and other information. The single-finger features are the fingertip distance and fingertip angle; the two-finger features are the adjacent fingertip distance and adjacent fingertip angle. After determining the dynamic features of the gestures during the teaching interaction, the hidden Markov model is used for recognition.The task of dynamic gesture recognition in this paper is to learn a mapping from feature vector sequence to dynamic gesture label. Assume that the given input feature vector sequenceI and the predicted output o are required, where o is a dynamic gesture label of all dynamic gesture label set O, and the feature vector sequence I=in1,in2,…,inm is represented as input sequence I. In different dynamic gesture sequences, the number of elements m of feature vector sequence is not fixed but variable.Given dynamic gesture labelo, feature vector sequence I, and hidden state sequence h, the hidden conditional random field model is expressed as a conditional probability model, namely [23]:(2)Po,h|I,θ=expφo,h,I;θ∑i=1mexpφo,h,I;θm,where θ is the model parameter of hidden Markov conditional random field and φo,h,I;θ is the potential function determined by the model parameters. The hidden state layer composed of hidden variables h=h1,h2,…,hm, which is the hidden state sequence that cannot be observed in the training process of the hidden conditional random field model. Each variable hi can correspond to a substructure in the feature vector. The potential function φo,h,I;θ can be defined as [24](3)φo,h,I;θ=∑i=1m∑1lFl1i,o,hi,Iθl1+∑∑1lFl2j,k,o,hj,hk,Iθl2,where Fl1 and Fl2 are the characteristic functions of the hidden conditional random field model. The model parameters are composed of θl1 and θl2. In the hidden layer, the single hidden state variable of function Fl1 is hi, while the characteristic function Fl2 depends on the two hidden state variables hj and hk in the hidden layer. The quasi-Newton method is used to estimate the optimal parameters of the hidden conditional random field model, and the optimal parameters are obtained by maximizing the objective function. VR interactive devices record students’ operations throughout the teaching process and provide relevant feedback in the virtual teaching scene based on the actions, allowing students to better absorb the subject given.In the practice environment, students can use the VR interactive equipment to carry on the design contents and the interaction of the real world, to verify the feasible for students’ environment landscape design scheme, which is more helpful for teachers to guide students intuitively. Enhance the impact of environmental landscape design as a practical teaching tool. Through the above process and the application of digital VR technology, the research on the practice teaching method of environmental landscape design based on IoT network and digital VR technology is completed.


## 2.1. Students’ Cognitive Constructs in the Teaching of Environmental Landscape Design

Environmental landscape design is not an abstract course, in which the cultivation of spatial awareness requires students to understand the specific relationships between people and things, people and people, and things and things arranged in space. The practical training course of landscape facility design is the main course of environmental landscape design, which plays an important role in the cultivation of professional ability and is an important knowledge reserve to promote the improvement of professional ability. In order to strengthen students’ spatial awareness, teachers can use VR technology to construct a virtual practice environment in environmental landscape design teaching in order to enhance students’ learning enthusiasm while strengthening their mastery of space [7, 11, 12]. Therefore, students need to be led to construct a cognitive understanding of environmental landscapes. A deeper understanding of the new cognitive constructs of landscape form will help to better understand and accept the new forms of landscape in order to further complement and improve the traditional methods of creating landscape forms.In the process of environmental landscape design, students’ morphological logic construction for landscape includes three kinds of thinking logic, including morphogenetic selection, morphological functional reasoning, and morphological pattern complementation. Among them, the morphogenetic preference logic should be based on experiential design thinking, which is realized through subjective experience with clear objectives and objective quantitative evaluation, under the combined effect of technical analysis and design view. Therefore, in the teaching process, students should be led to experience the actual environmental landscape design projects and students should be helped to theoretically adjust the preferential selection of parameters in the overall landscape design with the combination of visual data illustration and VR technology. Morphological functional reasoning requires students to have reasoning conforming to nonlinear and complex natural laws of thinking [13]. With the use of suitable mathematical tools, students should be guided to think in a dynamic manner, process the design, sequence the occurrences, and define the correlations between the parameters of the factors impacting morphology. When used in practical instruction, digital VR technology may assist students in understanding the logic of morphological pattern complementarity on two levels [14]. Students use VR devices to create corresponding landscape design projects in virtual space, are guided by teachers to make adjustments, and feel the differences before and after the adjustments with external feedback, thus gradually establishing a complete morphological pattern complementary logic. Students’ cognitive construction needs to be synchronized with teaching activities using VR technology and be practiced in VR virtual scenes after establishing a theoretical knowledge foundation for them.


## 2.2. Environmental Landscape Design VR Teaching Interactive Scene Design Construction

In order to fully grasp the conditions of landscape design, it is necessary to conduct a comprehensive analysis of the project’s objectives, safety, concepts, needs, and other factors in terms of functional positioning, architectural form, economic strength, and time duration in order to have a clear grasp of the entire landscape design process. The potential limitations and issues in it can be seen by the digital VR technology. Therefore, some conditions and requirements must be clarified when conducting environmental landscape design and simulated and analyzed through digital VR technology. The use of digital VR technology in the environmental landscape design process is essentially the use of the expressive power of the machine to replace the painted expression. And the expressive power gains tremendous progress, from flat to three-dimensional and stillness to dynamics. Interactive scenes for teaching environmental landscape design VR were designed and constructed using Unity3D software [15].Unity3D supports three scripting languages, JavaScript, C#, and Python, which have access to the underlying NET library. Also, the same object allows scripts from all three languages to execute simultaneously. All three languages execute at the same speed in Unity3D since Unity3D’s JavaScript version is compiled to native machine code using JIT. Unity3D, on the other hand, includes several self-contained resource packages, such as skyboxes, human controllers, terrain, water, and other really helpful and handy resources. The first-person controller in this system is created using the human controller resource package [16].Unity3D will import the person controller resource package into the project folder if you choose Assets-Import Package-Character Controller from the menu bar. The camera view in Unity3D’s third-person controller is set to the top of the character’s back. The camera view is placed at the character’s eyes in the first-person controller, and mouse swipes control the rotation of the camera [17]. Also, if there is terrain or surface, the axis of the object will be automatically attached to the target surface, at the same height as the target surface. The first-person controller comes with a main view camera, and we can adjust the height of this camera individually according to demand. Also, the first perspective of the teaching VR interactive scene is based on the camera import data arranged in the actual teaching space. The information collected by the camera in the real teaching space will be mapped to the virtual space through the steps of data transfer, coordinate transformation, and 3D modeling [18, 19].The camera is placed in the real teaching space in a certain attitude. The general world coordinate system and the camera coordinate system do not completely coincide, and there is rotation and translation relationship. The image plane coordinates represent the projection position of 3D field attractions on the imaging plane. In the computer, a two-dimensional matrix is used to represent an image, with pixel as the unit, and one point corresponds to one pixel [20]. Generally, the origin is the lower left corner of the plane, and the coordinates u,v of each pixel are the number of columns and rows of the pixel in the image, respectively. According to the conversion relationship between real space and camera coordinate system and between camera coordinate system and imaging plane coordinate system, the final relationship between real teaching space coordinate system and imaging plane coordinate system can be obtained [21]:(1)Zpuv1=f/dx0u000f/dyv0000000010RT01xryrzr1,where Zp is the z-axis direction vector of the imaging plane coordinate system; f is the camera’s focal length; R is the rotation transformation vector; T is the translation transformation vector; dx and dy are the width and height of each pixel, respectively, corresponding to the aspect ratio of the lens; and u0,v0 is the coordinate of the image center.For the interaction problem of using digital VR technology for teaching, in order to make students feel more intuitively the difference between the environmental landscape designed before and after the teacher’s instruction, the interaction needs to be done with the help of a joystick. Through the HTCVive grip, the corresponding animation appears after touching the contact points designed in the scene and pressing the relevant button to rotate and other actions to imitate the human hand’s effect. This approach allows for simple imitation, but the feedback to the system is not based on the real movements of the human hand, which can greatly reduce the immersion of VR device users [22]. Therefore, Leap Motion-based gesture motion recognition for feedback between the environmental landscape scene and the device user can maximize the immersion of VR technology. Therefore, in this paper, some basic gesture movements will be trained and recognized to improve the experience of students in VR teaching.


## 2.3. Realizing the Teaching of Environmental Landscape Design Practice

When students use the handles to practice environmental landscape design in virtual space, they need timely feedback on operational adjustments in order to improve the realism of teaching and learning. The feature vector utilized in this research is made up of single-finger features and two-finger features since the depth data frame provided by the Leap Motion sensor is made up of finger position, palm position, scale data, data frame timestamp, rotation, and other information. The single-finger features are the fingertip distance and fingertip angle; the two-finger features are the adjacent fingertip distance and adjacent fingertip angle. After determining the dynamic features of the gestures during the teaching interaction, the hidden Markov model is used for recognition.The task of dynamic gesture recognition in this paper is to learn a mapping from feature vector sequence to dynamic gesture label. Assume that the given input feature vector sequenceI and the predicted output o are required, where o is a dynamic gesture label of all dynamic gesture label set O, and the feature vector sequence I=in1,in2,…,inm is represented as input sequence I. In different dynamic gesture sequences, the number of elements m of feature vector sequence is not fixed but variable.Given dynamic gesture labelo, feature vector sequence I, and hidden state sequence h, the hidden conditional random field model is expressed as a conditional probability model, namely [23]:(2)Po,h|I,θ=expφo,h,I;θ∑i=1mexpφo,h,I;θm,where θ is the model parameter of hidden Markov conditional random field and φo,h,I;θ is the potential function determined by the model parameters. The hidden state layer composed of hidden variables h=h1,h2,…,hm, which is the hidden state sequence that cannot be observed in the training process of the hidden conditional random field model. Each variable hi can correspond to a substructure in the feature vector. The potential function φo,h,I;θ can be defined as [24](3)φo,h,I;θ=∑i=1m∑1lFl1i,o,hi,Iθl1+∑∑1lFl2j,k,o,hj,hk,Iθl2,where Fl1 and Fl2 are the characteristic functions of the hidden conditional random field model. The model parameters are composed of θl1 and θl2. In the hidden layer, the single hidden state variable of function Fl1 is hi, while the characteristic function Fl2 depends on the two hidden state variables hj and hk in the hidden layer. The quasi-Newton method is used to estimate the optimal parameters of the hidden conditional random field model, and the optimal parameters are obtained by maximizing the objective function. VR interactive devices record students’ operations throughout the teaching process and provide relevant feedback in the virtual teaching scene based on the actions, allowing students to better absorb the subject given.In the practice environment, students can use the VR interactive equipment to carry on the design contents and the interaction of the real world, to verify the feasible for students’ environment landscape design scheme, which is more helpful for teachers to guide students intuitively. Enhance the impact of environmental landscape design as a practical teaching tool. Through the above process and the application of digital VR technology, the research on the practice teaching method of environmental landscape design based on IoT network and digital VR technology is completed.


## 3. Case Study

The actual application of the teaching method and the display of the teaching effect have a direct impact on the real application value of the teaching method, so this section will test the feasibility of the application of the proposed teaching method of environmental landscape design practice based on IoT network and digital VR technology in the actual teaching work as well as the application effect in the form of example verification.


### 3.1. Case Study Protocol Design

In order to understand the practical effects of teaching methods in teaching environmental landscape design, suitable experimental indicators are selected to carry out the study in a targeted manner. The experimental control method was used to reflect the teaching effect of the practical application of the teaching method. The experimental class adopts the teaching method proposed in this paper, while the control class adopts the traditional teaching method. The subjects of the study are sophomore to senior students (300) of a university offering environmental landscape design courses. The class 1 each year is set as the control class, the class 2 is set as the experimental class, and the number of students in each class is set as 50. Other factors affecting the students were ignored during the validation of the teaching method example. After the teaching task is completed, different examination questions are set according to the differences of students’ grades. The students’ environmental landscape design works were evaluated, and the excellent rate of students’ works in the experimental class and the control class were compared to visually compare the teaching effect of the teaching method.The questionnaire was used to collect students’ satisfaction with the teaching methods. The most widely used 5-level Likert scale was chosen for the questionnaire, with five levels of satisfaction corresponding to scores of 1, 2, 3, 4, and 5 from low to high, so the score of 3 was adopted as the theoretically moderate intensity observation value in this survey. Meanwhile, an evaluation group consisting of experts in the same field, practitioners of environmental landscape design, and teachers with the same teaching tasks was formed to evaluate the teaching effectiveness of different teaching methods during the teaching process. The evaluation results are summarized in a weighted form, in which the evaluation weight of experts is 0.40, the evaluation weight of practitioners of environmental landscape design is 0.25, and the evaluation weight of teachers of the same teaching task is 0.35. The ratings of the evaluation subjects through different identities are averaged as the corresponding evaluation values. All the above data are combined to verify whether the proposed teaching method has practical use value.


### 3.2. Case Validation Results and Analysis

The results of the tests, in terms of students’ work rated as excellent work and passing the skill assessment, are shown in Tables1–3.Table 1
Distribution of the number of scores in the theoretical knowledge assessment of environmental landscape design.
OutstandingQualifiedFailureExperimental classes577716Control class336750Table 2
Number distribution of the special assessment for environmental landscape space design.
OutstandingQualifiedFailureExperimental classes657411Control class387339Table 3
Distribution of the number of people in the assessment of environmental landscape design effect drawing performance techniques.
OutstandingQualifiedFailureExperimental classes65741Control class388647Tables1–3 show that the experimental class students perform marginally better than the control class while using various teaching approaches. The effect drawing performance technique test is the most obvious, followed by the spatial special assessment test and the landscape design basic test, all of which indicate that students in the experimental class taught using this paper’s method perform better in projects with a high practical ratio. At the same time, it was discovered that teaching using the technique described in this study dramatically boosted students’ motivation and initiative in learning, as well as the degree of skill mastery, teamwork, and autonomous invention capacity. The bulk of the pupils who were in the school’s exceptional work show were from the experimental class. The passing rate of the experimental class in the school’s teaching evaluation is likewise higher than that of the control class. In the complete evaluation, the average excellent rate of students in the experimental class was 91.1 percent, whereas the average excellent rate of students in the comparison class was 74.5 percent, and the excellent rate of students in the experimental class increased by 16.6%.SPSS was used to statistically analyze the outcomes of students’ satisfaction with various teaching approaches, and the findings are given in Figure1. From Figure 1, it can be seen that the students are more satisfied with the teaching method of this paper, and they recognize the teaching method proposed in this paper more than the traditional method.Figure 1
Comparison of teaching method satisfaction score.Table4 shows the results of the comparison of the ratings of the two teaching methods by the different status of the evaluation subjects.Table 4
Comparison of the results of objective evaluation of teaching methods.
ProjectsRating weightingMethodology of this articleTraditional methodExpert evaluation0.408.77.2Practitioner evaluation0.257.57.3Peer review0.357.66.8Total score—8.0157.085Table4 shows that the evaluation scores of the teaching method in this paper are higher than those of the traditional method for each scoring object. In terms of the weighted total score, this method has higher score than the traditional method. It means that from the perspective of different evaluation objects, the teaching effect of this paper’s method applied to the actual teaching is better than that of the traditional method.Students’ comprehensive ability in the direction of environmental landscape design has been significantly improved, students’ enthusiasm for participating in the practical teaching activities of the course has been enhanced, and they can now apply the IoT network and digital VR technology-based teaching method proposed in this paper in the process of teaching environmental landscape design. Environmental landscape design now has a better educational impact. When applied to the teaching of environmental landscape design in practice, the teaching approach described in this work has a better impact than the standard teaching method.


## 3.1. Case Study Protocol Design

In order to understand the practical effects of teaching methods in teaching environmental landscape design, suitable experimental indicators are selected to carry out the study in a targeted manner. The experimental control method was used to reflect the teaching effect of the practical application of the teaching method. The experimental class adopts the teaching method proposed in this paper, while the control class adopts the traditional teaching method. The subjects of the study are sophomore to senior students (300) of a university offering environmental landscape design courses. The class 1 each year is set as the control class, the class 2 is set as the experimental class, and the number of students in each class is set as 50. Other factors affecting the students were ignored during the validation of the teaching method example. After the teaching task is completed, different examination questions are set according to the differences of students’ grades. The students’ environmental landscape design works were evaluated, and the excellent rate of students’ works in the experimental class and the control class were compared to visually compare the teaching effect of the teaching method.The questionnaire was used to collect students’ satisfaction with the teaching methods. The most widely used 5-level Likert scale was chosen for the questionnaire, with five levels of satisfaction corresponding to scores of 1, 2, 3, 4, and 5 from low to high, so the score of 3 was adopted as the theoretically moderate intensity observation value in this survey. Meanwhile, an evaluation group consisting of experts in the same field, practitioners of environmental landscape design, and teachers with the same teaching tasks was formed to evaluate the teaching effectiveness of different teaching methods during the teaching process. The evaluation results are summarized in a weighted form, in which the evaluation weight of experts is 0.40, the evaluation weight of practitioners of environmental landscape design is 0.25, and the evaluation weight of teachers of the same teaching task is 0.35. The ratings of the evaluation subjects through different identities are averaged as the corresponding evaluation values. All the above data are combined to verify whether the proposed teaching method has practical use value.


## 3.2. Case Validation Results and Analysis

The results of the tests, in terms of students’ work rated as excellent work and passing the skill assessment, are shown in Tables1–3.Table 1
Distribution of the number of scores in the theoretical knowledge assessment of environmental landscape design.
OutstandingQualifiedFailureExperimental classes577716Control class336750Table 2
Number distribution of the special assessment for environmental landscape space design.
OutstandingQualifiedFailureExperimental classes657411Control class387339Table 3
Distribution of the number of people in the assessment of environmental landscape design effect drawing performance techniques.
OutstandingQualifiedFailureExperimental classes65741Control class388647Tables1–3 show that the experimental class students perform marginally better than the control class while using various teaching approaches. The effect drawing performance technique test is the most obvious, followed by the spatial special assessment test and the landscape design basic test, all of which indicate that students in the experimental class taught using this paper’s method perform better in projects with a high practical ratio. At the same time, it was discovered that teaching using the technique described in this study dramatically boosted students’ motivation and initiative in learning, as well as the degree of skill mastery, teamwork, and autonomous invention capacity. The bulk of the pupils who were in the school’s exceptional work show were from the experimental class. The passing rate of the experimental class in the school’s teaching evaluation is likewise higher than that of the control class. In the complete evaluation, the average excellent rate of students in the experimental class was 91.1 percent, whereas the average excellent rate of students in the comparison class was 74.5 percent, and the excellent rate of students in the experimental class increased by 16.6%.SPSS was used to statistically analyze the outcomes of students’ satisfaction with various teaching approaches, and the findings are given in Figure1. From Figure 1, it can be seen that the students are more satisfied with the teaching method of this paper, and they recognize the teaching method proposed in this paper more than the traditional method.Figure 1
Comparison of teaching method satisfaction score.Table4 shows the results of the comparison of the ratings of the two teaching methods by the different status of the evaluation subjects.Table 4
Comparison of the results of objective evaluation of teaching methods.
ProjectsRating weightingMethodology of this articleTraditional methodExpert evaluation0.408.77.2Practitioner evaluation0.257.57.3Peer review0.357.66.8Total score—8.0157.085Table4 shows that the evaluation scores of the teaching method in this paper are higher than those of the traditional method for each scoring object. In terms of the weighted total score, this method has higher score than the traditional method. It means that from the perspective of different evaluation objects, the teaching effect of this paper’s method applied to the actual teaching is better than that of the traditional method.Students’ comprehensive ability in the direction of environmental landscape design has been significantly improved, students’ enthusiasm for participating in the practical teaching activities of the course has been enhanced, and they can now apply the IoT network and digital VR technology-based teaching method proposed in this paper in the process of teaching environmental landscape design. Environmental landscape design now has a better educational impact. When applied to the teaching of environmental landscape design in practice, the teaching approach described in this work has a better impact than the standard teaching method.


## 4. Conclusion

China’s landscape design profession started very late but developed very rapidly, and many colleges and universities offer such courses. However, the development in teaching lags behind and cannot keep up with the needs of society. Environmental design contains knowledge of garden, architecture, painting, and other types, which are strong theoretically and practically. Although practical teaching has made significant progress in the teaching of several disciplines, research and practice in the teaching of landscape design courses is still in its infancy, with little theoretical direction and practical experience. The current environmental landscape design teaching method can only rely on direct lectures from teachers, and the improvement of students’ environmental landscape design level is more limited by their personal ability and a lack of sufficient practice opportunities, resulting in poor learning effects and students’ practical ability not being able to meet the demand of environmental landscape design work. Because of the good interactivity of digital VR technology, this paper proposes a practical teaching method of environmental landscape design based on IoT network and digital VR technology. The example verification of the teaching method in the actual universities offering environmental landscape design courses proves that the teaching method in this paper has good teaching effect, and the application of the method can effectively teach professional knowledge to students and enhance their practical ability of environmental landscape design.



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*Source: 8080197-2022-03-07.xml*