Metacosmic digital intelligent teaching system, construction method and teaching method

Abstract

The invention discloses a meta universe digital intelligent teaching system, a construction method and a teaching method. The meta universe digital intelligent teaching system comprises a cloud server side, a teacher side and a student side, the cloud server comprises a data storage module, a map construction module and a teaching application operation module, and the data storage module comprises a primitive database, a teaching database and a map database; the atlas construction module comprises a text generation module and an atlas generation module; the text generation module generates a corresponding primitive text for each piece of primitive data, and the map generation module generates a teaching map and stores the generated teaching map into a map database; and the teaching application operation module receives an instruction of the teacher end, performs permission operation on data of the primitive database, the teaching database and the atlas database, receives an instruction of the student end, and performs permission operation on teaching data. According to the method, the cloud server side is used for dividing the primitive data, meanwhile, the map of the primitive data is constructed, and rich and convenient digital resources are provided for subsequent teaching activities.

Description

Technical Field

[0001] The present invention belongs to the field of digital teaching technology, and in particular relates to a metaverse digital intelligent teaching system, a construction method and a teaching method. Background Art

[0002] As we all know, according to the degree of technology application, current teaching activities are mainly divided into the following forms: Form 1: Traditional teaching: mainly relying on blackboard, textbooks and face-to-face interaction between teachers and students; Form 2: Multimedia teaching: mainly using PPT, video, audio and other tools to assist in explanation; After a long period of practice, it is found that the above two forms of teaching activities have their own advantages and disadvantages; among them: Regarding the first form, due to the limitations of physical space and time, teachers can only teach students in fixed places and fixed time periods, resulting in low utilization of teaching resources and a small coverage area; For the second form, also limited by physical space and time, teachers can only teach students in fixed places and fixed time periods. At the same time, multimedia teaching needs to rely on a large number of multimedia equipment, such as sound systems, projectors and other related audio-visual equipment. The introduction of these equipment makes the teaching process more vivid and intuitive. However, these devices are usually expensive and require regular maintenance and updates. Therefore, multimedia teaching is mainly suitable for centralized on-site classroom environments to a large extent; In recent years, with the rapid development of digital technology and information technology (such as the Internet, artificial intelligence, big data, virtual reality, etc.), it is of great significance to design and develop a digital teaching form that can break through the limitations of time and space and realize digital presentation, interactive delivery and personalized learning of teaching content through online platforms, intelligent tools and multimedia resources. Summary of the invention

[0003] The purpose of the present invention is to provide a metaverse digital intelligent teaching system, construction method and teaching method, which are constructed using digital technology and metaverse information technology. First, the primitive data are divided into the smallest granularity, and then the correlation between the data is constructed through the teaching map. Finally, teaching interaction is carried out in the form of a metaverse. Such an intelligent teaching system, on the one hand, makes it easy for teachers to efficiently find teaching materials and then complete the production of teaching courseware. On the other hand, it makes it easy for students to complete online teaching without being restricted by time and space.

[0004] In order to achieve the above object, the present invention provides the following technical solutions: The first object of the present invention is to provide a metaverse digital intelligent teaching system, including a cloud service end, a teacher end and a student end; the cloud service end includes a data storage module, a graph construction module and a teaching application operation module, wherein: The data storage module includes a primitive database, a teaching database and a graph database; The primitive database is divided into a legend database, a video database, a model database, a two-dimensional interaction database, a three-dimensional interaction database and a question database according to primitive data types; The teaching database is divided into a teaching material database, a courseware database, a course database and a teaching plan database according to the type of teaching data; The graph construction module includes a text generation module and a graph generation module; the text generation module generates corresponding primitive texts from each primitive data, and the graph generation module generates a teaching graph using a single primitive text or multiple primitive texts, and stores the generated teaching graph in the graph database; The teaching application operation module receives instructions from the teacher side to perform permission operations on the data in the primitive database, teaching database and atlas database, and receives instructions from the student side to perform permission operations on the teaching data. The teacher end and the student end construct a metaverse virtual scene that is compatible with the target teaching content through a virtual scene construction module, and display the target teaching content in the metaverse virtual scene.

[0005] Preferably, the primitive text includes legend text, video text, model text, two-dimensional interactive text, three-dimensional interactive text and test text; the text generation module includes: The graphic text generation unit generates the graphic text corresponding to each graphic legend according to the graphic content by using the graphic text generation model; The video text generation unit uses the image-text generation model to generate the video text corresponding to each video segment based on the video content; Model text generation part: the teacher generates the model text corresponding to each model according to the content of the model; A two-dimensional interactive text generation unit generates two-dimensional interactive text corresponding to each two-dimensional interactive data according to the two-dimensional interactive data by using a picture-text generation model; A three-dimensional interactive text generation unit generates three-dimensional interactive text corresponding to each three-dimensional interactive data according to the three-dimensional interactive data by using a graphic-text generation model; The test text generation unit generates the test text corresponding to each test data according to the test data by using the image-text generation model.

[0006] Preferably, the video-text generation unit first extracts a frame sequence of video data, then processes each frame of the image using a graphic-text generation model to obtain a frame sequence text, and finally generates a video text based on the frame sequence text.

[0007] Preferably, the primitive text includes a text content module and a text keyword module. The text content module describes the content information of the primitive data through text, and the text keyword module is a keyword obtained through a semantic analysis model. The keywords include: First-level keywords, used to identify the subject category to which the base text applies; Secondary keywords, used to identify the target name involved in the primitive text; The third-level keywords are used to identify the characteristics of each target in the primitive text.

[0008] Preferably, the graph generation module first uses a clustering algorithm to perform initial clustering on each level of keywords of a single primitive text or multiple primitive texts to obtain a step-by-step clustering matrix, and then performs secondary clustering on the step-by-step clustering matrix to obtain a teaching graph.

[0009] Preferably, the cloud service end also includes a data standardization module, which converts the uploaded video data into MP4 format, converts the uploaded document data into PDF and / or JPG format, converts the uploaded 3D model data into GLB format, and converts the uploaded online resource data into ZIP format.

[0010] Preferably, the teacher terminal and the student terminal perform data interaction with the cloud server terminal based on a Web browser.

[0011] Preferably, the teacher terminal includes: The first data interaction module establishes a data link with the teaching application operation module, and is used to read the primitive database, the teaching database and the atlas database, the primitive text and the teaching atlas; An editor module, for editing the primitive database, teaching database and atlas database, primitive text and teaching atlas; Demonstration teaching module, used to create and manage live classes, display teaching content, and conduct communication and interaction between teachers and students; The teaching feedback module is used to view personal feedback reports, class feedback reports and teaching feedback reports.

[0012] Preferably, the student terminal includes: The second data interaction module establishes a data link with the teaching application operation module to read the teaching content and the teacher-student communication and interaction content in the demonstration teaching module; Classroom learning module, used for classroom learning and teaching interaction; Self-study module, used for after-class self-study; Collaborative Learning modules for participating in group discussions and collaboration; Practice and assessment module, used to complete exercises and assessments; Learning Feedback module, used to view personal feedback reports.

[0013] A second object of the present invention is to provide a method for constructing a Metaverse digital intelligent teaching system, which is used to construct the above-mentioned Metaverse digital intelligent teaching system, and the construction method includes: S101, constructing a primitive database: collecting or uploading primitive data, and dividing the primitive data into a legend database, a video database, a model database, a two-dimensional interaction database, a three-dimensional interaction database, and a question database according to the primitive data type; S102, constructing a graph construction module, the graph construction module includes a text generation module and a graph generation module; the text generation module generates a corresponding primitive text from each primitive data, the graph generation module generates a teaching graph using a single primitive text or multiple primitive texts, and stores the generated teaching graph into a graph database; S103, constructing a teaching application operation module, and establishing a data interaction protocol between the teaching application operation module and the Internet; S104, constructing a teaching database: the teacher first uses the teaching map to obtain relevant primitive data, then uses the primitive data to construct teaching data, and finally divides the teaching data into teaching material data, courseware data, tutorial data and lesson plan data according to the type of teaching data, thus completing the construction of the teaching material database, courseware database, tutorial database and lesson plan database.

[0014] Preferably, the teaching application operation module includes: The primitive data editing module is used to edit the permissions of the primitive data as needed; The teaching data editing module is used to edit the permissions of teaching data as needed.

[0015] The third object of the present invention is to provide a Metaverse digital intelligent teaching method, based on the above-mentioned Metaverse digital intelligent teaching system, performing the following steps: S201, the teacher first uses the teaching map to obtain relevant primitive data, then uses the primitive data to construct teaching data, and finally imports the teaching data into a teaching material database or a courseware database or a tutorial database or a teaching plan database according to the type of teaching data; S202, the teacher creates a live classroom; S203. During a preset time period, the teacher and the student enter the live classroom, display the teaching content in the form of a metaverse, and interact with each other.

[0016] Preferably, it also includes: S204. The student submits a personal feedback report.

[0017] Compared with the prior art, the present invention has the following beneficial effects: One of the cores of the present invention is to carry out a meticulous and detailed minimum granular division of the primitive data for teaching. Specifically, the primitive data is subdivided into different categories such as legend data, video data, model data, two-dimensional interactive data, three-dimensional interactive data and test questions. Such a division enables each data type to have its specific application scenario, which is convenient for data search. Next, the present invention converts each primitive data into a corresponding primitive text through the function of the text generation module. This process ensures that the characteristics and information of the data are accurately expressed. On this basis, the atlas generation module plays its role. It can use these single primitive texts, or combine multiple primitive texts, and then generate a teaching atlas with rich teaching information. In the process of making teaching courseware, teachers can use these teaching atlases to quickly and accurately locate the various primitive data required, thereby efficiently constructing courseware that meets teaching needs. Finally, through the form of online classroom, teachers and students can transcend the limitations of time and space and realize flexible and diverse teaching interactive courses.

[0018] In the present invention, the process of constructing the teaching map is systematic and orderly. First, the text generation module processes each primitive data and generates corresponding primitive texts. These texts are detailed descriptions of the characteristics of the primitive data. The primitive texts include a text content module and a text keyword module. The text content module describes the content information of the primitive data through text. Teachers can quickly grasp the specific content of the primitive data by reading the content information. The text keyword module is a keyword obtained by a semantic analysis model. Teachers can further quickly grasp the core content of the primitive data through keywords. Subsequently, the map generation module takes over these primitive texts, whether single or multiple combinations, and can quickly weave them into a complete teaching map. It is worth noting that in the present invention, each primitive data corresponds to a specific primitive text, because the primitive text can more accurately capture and express the essential characteristics of the primitive data, thereby providing great convenience in the subsequent data processing and map construction process. This design not only improves the efficiency of data processing, but also enhances the accuracy of the teaching map and the convenience of retrieval.

[0019] In the present invention, the cloud server uses a data standardization module to standardize the uploaded video data, document data, three-dimensional model data and online resource data, so that the teacher and student ends can interact with the cloud server based on a Web browser and a Metaverse device (AR or VR, etc.) without building a new APP.

[0020] Under the framework of the present invention, the primitive text is not just a simple data description, it also contains keywords of different levels. These keywords are arranged according to a certain hierarchical structure, so that corresponding teaching maps can also be constructed between different levels. In this way, teachers can select keywords of different levels for indexing according to teaching needs, so as to obtain primitive data of different quantities. Usually, the amount of primitive data associated with the highest-level keywords (first-level keywords) is the least, and as the keyword level decreases, the amount of associated primitive data gradually increases. This design enables teachers to flexibly select keywords for efficient data retrieval and integration of teaching resources according to the specific amount of required primitive data. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 is a structural block diagram of a preferred embodiment of the present invention; Figure 2 It is a structural block diagram of a primitive database in a preferred embodiment of the present invention; Figure 3 It is a structural block diagram of a text generation module in a preferred embodiment of the present invention; Figure 4 This is a workflow diagram of the visual text generation unit in a preferred embodiment of the present invention; Figure 5 This is a workflow diagram of the graph generation module in the preferred embodiment of the present invention; Figure 6 It is a structural block diagram of the teacher's terminal in the preferred embodiment of the present invention; Figure 7 It is a structural block diagram of the student terminal in the preferred embodiment of the present invention; Figure 8 A flowchart of a system construction method in a preferred embodiment of the present invention; Fig. 9 This is a flow chart used for system teaching in a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0022] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. All other embodiments obtained by ordinary technicians in the field without making creative work based on the embodiments of the present invention shall fall within the scope of protection of the present invention.

[0023] like Figure 1-Figure 7 As shown: First preferred embodiment: A Metaverse digital intelligent teaching system mainly includes three parts: a cloud service end, a teacher end and a student end; the cloud service end includes a data storage module, a graph construction module and a teaching application operation module, wherein: The data storage module includes a primitive database, a teaching database and a graph database; The primitive database is divided into a legend database, a video database, a model database, a two-dimensional interaction database, a three-dimensional interaction database and a question database according to primitive data types; The teaching database is divided into a teaching material database, a courseware database, a course database and a teaching plan database according to the type of teaching data; The graph construction module includes a text generation module and a graph generation module; the text generation module generates corresponding primitive texts from each primitive data, and the graph generation module generates a teaching graph using a single primitive text or multiple primitive texts, and stores the generated teaching graph in the graph database; The teaching application operation module receives instructions from the teacher side to perform permission operations on the data in the primitive database, teaching database and atlas database, and receives instructions from the student side to perform permission operations on the teaching data. The teacher end and the student end construct a metaverse virtual scene that is compatible with the target teaching content through a virtual scene construction module, and display the target teaching content in the metaverse virtual scene.

[0024] The intelligent teaching system described in this embodiment adopts a front-end and back-end separation architecture design pattern. This design pattern mainly includes two core parts: a cloud server as a back-end and a front-end application based on a Web browser and a Metaverse device. Specifically, the front-end application is mainly responsible for displaying teaching content and using a Web browser and / or a Metaverse device to interact with teaching content, while the back-end cloud server is mainly responsible for processing data and business logic. Specifically: The front-end application includes two main user terminals: the teacher terminal and the student terminal. The teacher terminal allows teachers to conveniently interact with the cloud server terminal through a web browser and / or a Metaverse device to upload, download, edit and manage teaching resources. At the same time, the student terminal provides students with a friendly web browsing interface and a Metaverse virtual scene that is not restricted by space (students can move around freely indoors or outdoors with the help of Metaverse devices). Students can access course materials published by teachers, complete homework submissions, and participate in online learning tests.

[0025] In the present invention, the design of the cloud service end includes multiple key modules, which work together to provide efficient teaching services. Specifically, the cloud service end mainly includes the following three core modules: data storage module, graph construction module and teaching application operation module. Each module plays an indispensable role, and together ensures the smooth operation of the system and the effective management of teaching content. Specifically: The data storage module is the foundation of the entire system, and it is responsible for storing and managing various types of data. This module is further divided into three sub-databases: primitive database, teaching database, and atlas database. The primitive database is where primitive data (basic teaching elements) are stored. It is further divided into multiple specialized databases according to the type of primitive data, including legend database, video database, model database, 2D interactive database, 3D interactive database, and question database. These databases each store different types of educational content, such as legends, videos, models, 2D and 3D interactive content, and questions, to meet diverse teaching needs.

[0026] The teaching database is divided according to the type of teaching data, which includes teaching material database, courseware database, tutorial database and lesson plan database. These databases store teaching resources such as teaching materials, courseware, tutorials and lesson plans, providing teachers and students with rich learning materials.

[0027] The graph construction module is the key part of the system responsible for generating and managing teaching graphs. It includes a text generation module and a graph generation module. The function of the text generation module is to convert each primitive data into the corresponding primitive text, providing a basis for the generation of the graph. The graph generation module uses these primitive texts, whether single or in combination, to construct teaching graphs. These graphs are visual representations of teaching content, which make it easy for teachers to quickly find primitive data related to building teaching courseware, and help students better understand and master knowledge. The generated teaching graph will eventually be stored in the graph database for use by the teaching application operation module.

[0028] In the teaching application operation module of the present invention, it has a dual function, which can respond to instructions from the teacher's end and process requests from the student's end. Specifically, when the teacher's end issues an instruction, the operation module will process the received instruction, and then perform corresponding permission operations on the data in the primitive database, teaching database and atlas database. Such permission operations may include but are not limited to reading, modifying, adding or deleting data. At the same time, the operation module can also receive instructions from the student's end, and perform corresponding permission operations on the teaching data according to these instructions, ensuring that students can access and use teaching resources according to established rules and permissions. This design not only ensures the security of teaching resources, but also improves the flexibility and interactivity of teaching applications.

[0029] On the basis of the above preferred embodiments, the following non-limiting technical features may also be included: In order to quickly select specific primitive data, index information can be built for the stored primitive data: that is, a unique identifier is assigned to each primitive data, keywords that can represent the content of the primitive data are extracted, classification tags are added, and storage location information is recorded, so that these primitive data can be quickly and accurately retrieved and called later; In the present invention, the primitive text mentioned covers various types of text content, including legend text, video text, model text, two-dimensional interactive text, three-dimensional interactive text and test text. These text types are common in specific education or information display scenarios. In order to generate these texts, the text generation module is designed to include multiple specialized generation departments, each department is responsible for a specific type of text generation work.

[0030] The image and text generation unit is an important part of the text generation module. It uses the advanced technical means of image and text generation model to accurately generate legend text that matches each legend according to the provided legend content. This kind of legend text can not only describe the information in the legend in detail, but also enhance learners' understanding of the legend content.

[0031] The video text generation unit also uses the image-text generation model. Its task is to generate corresponding video text based on the video content. Video text is a text description of the video content. It can help learners understand the main information and details of the video by reading the text without watching the video.

[0032] The model text generation part focuses on the generation of model texts, which is mainly operated by the teacher. Teachers can write corresponding model texts for each model based on the specific content of the model. These texts can explain in detail the structure, function and role of the model in practical applications, thereby helping learners better understand the model.

[0033] The two-dimensional interactive text generation unit is responsible for generating corresponding two-dimensional interactive text according to the two-dimensional interactive data. This text can convert the two-dimensional interactive data into easy-to-understand text descriptions, so that learners can grasp the information expressed by the two-dimensional interactive data through reading.

[0034] The working principle of the 3D interactive text generation department is similar to that of the 2D interactive text generation department, but it focuses on 3D interactive data. By utilizing the image-text generation model, this department is able to generate 3D interactive text corresponding to the 3D interactive data, thereby helping learners better understand the data content in 3D space.

[0035] The test text generation department is responsible for generating test texts based on test data. These test texts are designed for specific test data and can describe the requirements, content, and problem-solving steps of the test in detail, providing learners with clear problem-solving guidance.

[0036] Through the collaborative work of the above-mentioned generation departments, the text generation module can efficiently provide rich and accurate text content for various education and information display scenarios, greatly improving the efficiency and quality of information transmission.

[0037] In the present invention, the visual text generation unit is responsible for performing a series of complex processing steps to achieve the goal of extracting text information from video data. First, the visual text generation unit extracts a series of continuous frame sequences from the input video data. These frame sequences are the basic building blocks of video data, and each frame is a static image at a certain moment in the video.

[0038] Next, the visual text generation department will use an efficient image-text generation model to perform in-depth processing and analysis on these continuous frame images. This model is specially designed to process image data and can identify and extract key information from images. Through the processing of the model, each frame of the image will be converted into a corresponding text description, thus forming a frame sequence text.

[0039] Finally, the video text generation department will comprehensively consider the content of the entire frame sequence text and use advanced text generation technology to integrate and transform this text information into a coherent video text. This video text is a refinement and summary of the original video content, which can convey the main information and storyline of the video in the form of text.

[0040] In the present invention, each primitive data includes multiple attributes, such as: Basic attributes: name, creation time, modification time, file size, etc. of primitive data; Technical attributes: file format, encoding method, resolution, duration (video), etc. Teaching attributes: applicable subjects, applicable grades, teaching objectives, instructions for use, etc.; Management properties: uploader information, review status, usage permissions, etc.

[0041] In order to facilitate the construction of standardized primitive text, the following rules can be formulated. The primitive text includes a text content module and a text keyword module. The text content module describes the content information of the primitive data through text, and the text keyword module is a keyword obtained through a semantic analysis model. The keyword may include: First, the primary keyword plays a key role in clearly identifying the subject category to which the primitive text applies. These subject categories can be diverse, such as mechanical engineering, chemical science, electronic technology, etc., thus providing a basis for the classification and retrieval of text content. It should be noted that a single primitive text may be applicable to multiple disciplines; Secondly, the secondary keywords further refine the scope of the text content and are used to clearly indicate the specific target names involved in the primitive text. These target names can be various professional terms or the names of specific items, such as engines, beakers, temperature sensors, etc. They help teachers and students quickly locate the specific objects discussed in the text.

[0042] Finally, the third-level keywords provide a deeper level of detailed description of the text content and are used to clearly identify the characteristics of each target object in the text. These characteristics can be specific attributes such as working parameters, size, color, etc. They provide teachers and students with detailed information about the target object and help them understand the text content in depth.

[0043] In the process of constructing the teaching map, the map generation module plays a vital role. First, the module uses a clustering algorithm to process a series of primitive texts, which can be a single text or a collection of multiple texts. Through the application of the clustering algorithm, the module performs a preliminary clustering analysis on each level of keywords in these texts to generate a hierarchical clustering matrix. These matrices are the basis for map generation, and they record in detail the similarities and correlations between keywords. Next, the map generation module will further analyze and process these hierarchical clustering matrices, and further refine and optimize the correlation of keywords by performing secondary clustering operations. Finally, through this series of processing steps, the map generation module can construct a structured and hierarchical teaching map, which can not only reflect the intrinsic connection between knowledge, but also provide strong support and guidance for teaching activities.

[0044] The cloud service end also includes a data standardization module, which converts the uploaded video data into MP4 format, converts the uploaded document data into PDF and / or JPG format, converts the uploaded 3D model data into GLB format, and converts the uploaded online resource data into ZIP format. Taking the 3D model as an example, open the uploaded 3D model file, use the threejs framework and the corresponding loader (OBJLoader, FBXLoader, FBXLoader, etc.) to parse the model file, and obtain all the data of the model, including vertex information, position information, angle information, scaling information, surface effect, structure, material, color, etc.; finally, according to the GLB format rules, the parsed information is reorganized and rendered to obtain a 3D model file in GLB format.

[0045] Through the data standardization, the teacher and student terminals can interact with the cloud server terminal based on a web browser and / or a Metaverse device without building a professional APP.

[0046] In the present invention, the cloud service end also includes a data standardization module, which has the function of converting the uploaded video data into MP4 format. In addition, it can also convert the uploaded document data into PDF format and / or JPG format to facilitate document viewing and sharing. For the uploaded 3D model data, the data standardization module can convert it into GLB format, which is a widely supported 3D model file format that is convenient for display and interaction on different devices and platforms. For the uploaded online resource data, the module is responsible for converting it into ZIP format, which can effectively compress and package resources for easy storage and transmission.

[0047] By implementing these functions of the data standardization module, it is possible to ensure that different types of media and data files are uniformly processed and formatted on the cloud server, so that users on the teacher and student sides can seamlessly interact with the cloud server through ordinary web browsers and / or Metaverse devices. This design avoids the need for users to download and install special applications (APPs) to access and process these data, greatly reducing the usage threshold and improving the user experience.

[0048] In the present invention, the functions and components of the teacher's terminal are described in detail as follows: First, the teacher end includes a first data interaction module, the main function of which is to establish a stable data link with the teaching application operation module. Through this data link, the first data interaction module can effectively read and access information in the primitive database, teaching database, and atlas database. In addition, it can also obtain primitive texts and teaching atlases, thereby providing teachers with rich teaching resources.

[0049] Secondly, the teacher side also contains an editor module, the main responsibility of which is to edit and manage the primitive database, teaching database and atlas database. Through the editor module, teachers can modify, update and optimize the primitive text and teaching atlas to ensure the accuracy and timeliness of the teaching content.

[0050] Furthermore, the teacher side also has a demonstration teaching module, the main function of which is to create and manage live classes. Through the demonstration teaching module, teachers can display teaching content and communicate and interact between teachers and students, thereby improving the interactivity and fun of teaching.

[0051] Finally, the teacher side also includes a teaching feedback module, the main function of which is to collect and analyze feedback information during the teaching process. Through the teaching feedback module, teachers can view personal feedback reports, class feedback reports, and teaching feedback reports to evaluate and improve teaching effectiveness.

[0052] The student terminal includes: The second data interaction module is mainly responsible for establishing a stable data link with the teaching application operation module. Its main function is to read and obtain the teaching content in the demonstration teaching module and the communication and interaction content between teachers and students; The classroom learning module mainly supports students to learn and participate in teaching interactions in the classroom to improve learning efficiency and interactivity; The self-learning module helps students to study independently after class by providing necessary learning resources and tools so that students can complete their learning tasks independently. Collaborative learning module, which encourages students to participate in group discussions and collaborative learning, and improve learning outcomes and problem-solving abilities through teamwork; The practice and assessment module is used for students to complete various exercises and assessment tasks, and to test their learning outcomes and understanding through these exercises and assessments; The learning feedback module provides a way to view personal feedback reports, through which students can understand their learning status and areas for improvement.

[0053] The cloud server provides data services and computing support for front-end applications through API interfaces; The data storage module also includes an account database, a teaching process database, and an evaluation database. The account database is used to save teacher, student, and class account data. The account data includes teacher information, student information, and class information; the teaching process data includes attendance records, homework submission and correction records, classroom interaction data, and learning progress records; the evaluation data includes test scores, course evaluations, learning behavior data, teaching effectiveness feedback, etc.

[0054] 2D interactive resources include Flash resources and HTML5 resources, 3D interactive resources include Web browser-based WebGL resources and independent application resources; image formats include ipg, jpeg, png, bmp, tif, tiff, gif, ico, jfif, webp, svg, tga and dcm. Flash resources, HTML5 resources and WebGL resources are directly parsed and executed by the browser; independent application resources (including .exe and .apk files) are loaded and run through the virtual machine module to ensure resource compatibility and operational stability.

[0055] The courseware database is specially used to store digital courseware, which contains a variety of basic data so that it can be read and used on various electronic devices.

[0056] The main function of the textbook database is to save digital textbooks. These digital textbooks integrate a variety of basic data, which include not only text and images, but also multimedia elements such as audio and video. These textbooks can be read and used on various electronic devices, providing learners with a richer and more interactive learning experience.

[0057] Model database, used to store 3D models of digital research and development. These 3D models are designed for practical teaching and contain a variety of digital 3D model resources used to simulate real-world objects or scenes. Through these models, students can use Metaverse devices to more intuitively understand complex concepts and structures, thereby improving learning efficiency and interest.

[0058] Course database, which is used to store digital courses. These digital courses integrate a variety of basic data and are provided to teachers and students through online platforms, allowing teachers and students to learn anytime and anywhere. These courses include not only traditional video lectures and reading materials, but also interactive tests, discussion areas, and real-time Q&A elements, providing learners with a comprehensive online education experience.

[0059] Video formats include mp4, mp3, avi, mov, fiv, wav, rm, webm, ts, rm, mkv, mpeg, obg, mpg, rmvb, wm; Document formats include pdf, doc, docx, xls, xlsx, xlsm, ppt, pptx, csv, tsv, dotm, xlt, xltm, dot, dotx, xlam, xla, xmind, dwg, dxf, visio, dcm, drawio, ofd, epub, wps, vsdx, xml, md.jsp, ison; 3D model file formats include: 3mf, dae, xml, blend, bvh, 3ds, ase, glTF, fbx, ply, dxf, ifc, nff, smd, vta, mdl, md2, md3, pk3, mdc, md5mesh, md5anim, md5camera, x, q3o, q3s, raw, ac, ac3d, stl, irrmesh, irr, off, obj, ter, hmp, mesh.xml, skeleton.xml, material, ogex, ms3d, lwo, lws, lxo, csm, cob, scn; The teaching feedback module includes individual evaluation unit, class evaluation unit and teaching evaluation unit; The teaching feedback module is one of the core components of the teaching system. Its main responsibility is to analyze learning outcomes and provide suggestions for improvement. It conducts comprehensive evaluation from three aspects: individual learning, class overall, and teaching quality. By deeply analyzing the various data generated during the teaching process, it provides a scientific basis for the optimization of teaching activities.

[0060] The personal assessment unit is responsible for implementing the personal learning assessment model, and generates a personal feedback report through weighted analysis based on the data of students in classroom learning, independent learning, collaborative learning, and practice assessment. The report covers personal comprehensive learning scores, module score analysis, knowledge mastery heat map, learning behavior report, and learning improvement suggestions; Personal learning assessment focuses on each student's learning process and results. This assessment dimension covers multiple aspects such as classroom performance, after-class independent learning, group collaboration participation, and completion of exercise assessments. Through in-depth analysis of these data, the system can provide each student with a personalized learning assessment report to help students fully understand their own learning status and provide targeted improvement suggestions.

[0061] The class assessment unit is responsible for executing the class learning assessment model, integrating each student's personal learning data, group activity data, battle practice data, and resource usage data; through data processing, a class feedback report is obtained, which includes a class score distribution chart, knowledge mastery matrix, learning progress chart, group effectiveness evaluation, and class learning report; Class learning assessment examines the learning situation of the class from a macro perspective. It focuses on the overall learning level, progress, knowledge mastery, and effectiveness of group learning activities of the class. Through class-level assessment and analysis, teachers can clearly grasp the overall learning situation of the class, identify differences between students, and adjust teaching strategies in a targeted manner.

[0062] The teaching evaluation unit is responsible for executing the teaching quality evaluation model, and generates a teaching feedback report through weighted analysis based on the teacher's individual teaching process data, each student's learning effect data, and student feedback data. The report includes a teaching quality score, a teaching analysis report, and a list of improvement suggestions.

[0063] Teaching quality evaluation focuses on analyzing the effectiveness of teaching activities. It mainly includes classroom teaching process, learning effect achievement, student learning experience feedback, and the effect of teaching resource use. Through the systematic evaluation of teaching quality, teachers can timely discover the advantages and disadvantages in teaching, obtain specific improvement suggestions, and continuously improve the teaching level.

[0064] The present invention evaluates from three dimensions, which together constitute a comprehensive teaching evaluation system. Through this multi-dimensional evaluation feedback, it can help students optimize their learning methods, assist teachers in improving their teaching strategies, and ultimately achieve the goal of improving teaching quality. The real-time update of the evaluation results ensures that teachers and students can continuously grasp the latest teaching status and continuously promote teaching improvement.

[0065] The front-end application covers the teacher side and the student side, both of which are implemented based on the Web browser and the Metaverse device; The teacher side includes: an editor module for editing teaching resources in standard formats, a demonstration teaching module for creating and managing live classes, displaying teaching content and teacher-student communication and interaction, and a teaching feedback module for viewing personal feedback reports, class feedback reports and teaching feedback reports; The editor module contains: Digital courseware editor, which can produce digital courseware containing various primitive data online through a web browser and / or Metaverse device; A digital textbook editor, which produces digital textbooks containing various primitive data online through a web browser and / or a Metaverse device; A digital course editor for creating digital courses containing multiple primitive data online via a web browser and / or a Metaverse device; Digital test question and paper editor, which can create and edit test questions and papers containing various primitive data online through a web browser and / or Metaverse device; Digital model editor, which can be used to edit digital R&D 3D models online through a web browser and / or Metaverse devices; the digital model editor is divided into structure series editor, principle series editor, disassembly series editor, maintenance series editor, overhaul series editor and usage series editor for teaching purposes; Taking the car model as an example, the structural series editor is mainly used to edit and display the basic structural composition of each car system, including the spatial layout and connection relationship of core components such as the engine, gearbox, chassis, etc. Teachers can use the editor to create a three-dimensional structural model to display the position, shape and assembly relationship of parts. Students can observe and understand the structural composition of each car system from multiple angles, laying the foundation for subsequent learning.

[0066] The principle series editor focuses on the display of the working principles of various systems in the car. Teachers can edit dynamic motion processes, workflows, etc. For example, the four-stroke working process of the engine, the shifting principle of the gearbox, the working mechanism of the braking system, etc. Through dynamic simulation and interactive display, it helps students deeply understand the operating mechanism and working principle of each system.

[0067] The disassembly and assembly series editor focuses on the editing of parts disassembly and assembly training content, and can design disassembly and assembly steps and processes for different models and systems. Teachers can edit disassembly and assembly paths, key operating points, precautions, and other content, set prompts and checkpoints for key steps, and help students master the correct disassembly and assembly sequence and techniques, and improve their practical operation capabilities.

[0068] The maintenance series editor is used to edit the operation content related to the daily maintenance and care of the car, including regular maintenance items, checkpoint settings, maintenance standards, etc. Through this editor, teachers can design a complete maintenance process, edit the specific requirements and standards of each maintenance operation, and ensure that students master standardized maintenance skills.

[0069] The maintenance series editor focuses on the editing of fault diagnosis and maintenance processes. Teachers can design various fault phenomena, diagnostic steps and maintenance plans. By editing typical fault cases, fault diagnosis ideas, maintenance operation requirements and other content, it helps students master scientific fault diagnosis methods and maintenance skills and improve their ability to solve practical problems.

[0070] The series editor is mainly used to edit the correct use and operation specifications of the vehicle, including driving operation instructions, function usage instructions, safety precautions, etc. Teachers can edit various usage scenarios, design function operation demonstrations, explain the correct use and precautions, ensure that students understand the correct use of the vehicle, and cultivate safety awareness and standardized operation habits.

[0071] The digital courseware editor is an important tool in the system for courseware production and editing, providing teachers with a fully functional courseware production environment. The basic functions of the digital courseware editor include accessing the material database, creating new courseware or importing existing courseware, and inserting various primitive data. Teachers can easily select the required teaching resources from the material database, insert them into the courseware, and adjust the position, size and angle of the primitive data according to teaching needs. The digital courseware editor also provides a layer management function. Teachers can edit multiple switchable layers containing primitive data to achieve richer courseware display effects. For three-dimensional models, the editor is equipped with a special model editor that supports the display and editing of the exploded view of the model, making the display of three-dimensional teaching content more intuitive. To ensure that the teacher's editing work will not be lost, the editor has designed a complete automatic synchronization mechanism. The system will automatically trigger synchronization based on multiple conditions such as the number of operations, the importance of operations, the time interval, the network status, etc., and teachers can also save manually at any time. This multiple protection mechanism not only ensures data security, but also avoids the system burden caused by excessive synchronization. After editing, the courseware will be saved in the cloud courseware database in a standard format for subsequent call and use. During the entire editing process, the system will provide timely operation feedback and synchronization status prompts, allowing teachers to clearly understand the current work status.

[0072] The demonstration teaching modules include: The classroom establishment unit creates a virtual classroom environment based on the course information set by the teacher, and realizes synchronous sharing between the teacher and the student through the cloud server; The classroom demonstration unit uses a web browser and / or a Metaverse device to display teaching content based on the courseware produced by the teacher, the primitive data in the material database, and real-time teaching needs. The teaching content includes text, primitive data, and 3D model resources; The classroom interaction unit is used to display real-time classroom data, student feedback and teaching progress, and realize interaction between teachers and students. The interactive content includes online questions, voting, group discussions and instant tests.

[0073] The student side includes: a classroom learning module for classroom learning and interaction, an independent learning module for after-class independent learning, a collaborative learning module for participating in group discussions and collaboration, an exercise and assessment module for completing exercises and assessments, and a learning feedback module for viewing personal feedback reports.

[0074] The classroom learning module includes a live learning unit for receiving and displaying teaching content and a teacher-student interaction unit for realizing teacher-student interaction during live learning. The classroom learning module mainly serves real-time online classroom learning. This module can receive and display live teaching content from the teacher's end, including teacher videos, courseware presentations, and audio explanations. Students can participate in classroom interactions through this module, such as asking questions online, participating in voting, joining group discussions, and completing instant tests. The module supports custom adjustment of the screen layout and provides multiple display modes to ensure that students get the best classroom learning experience.

[0075] The self-learning module focuses on personal learning activities after class. Students can access various learning resources through this module, including courseware, teaching materials, 3D models, etc. The module manages students' access to resources according to the permissions set by the teacher, and records the learning process data to help students master their own learning situation.

[0076] The collaborative learning module supports mutual learning activities among students. Students can form or join study groups through this module and communicate with classmates in real time via voice and video. The module provides note sharing and document collaboration functions, making it easier for group members to complete learning tasks together. The system will intelligently recommend suitable discussion groups and provide a search function for historical discussion content.

[0077] The practice and assessment module provides a platform for students to consolidate their knowledge and improve their abilities. The module provides a variety of practice forms, including individual practice and battle mode. In battle practice, the system will intelligently match opponents according to the students' levels, calculate scores in real time and generate rankings to stimulate learning enthusiasm. All practice records will be saved for students to review later.

[0078] The learning feedback module helps students understand their personal learning status. This module receives personal feedback reports from the teaching feedback module and helps students discover their strengths and weaknesses in learning. Students can adjust their learning strategies based on the feedback results to improve their learning outcomes.

[0079] These five modules work together to support students' participation in real-time classroom teaching and provide comprehensive support for independent learning after class, forming a complete learning closed loop. Data sharing and analysis between modules enable students to fully understand their learning situation and achieve more effective learning.

[0080] Second preferred embodiment: like Figure 8 As shown, a method for constructing a Metaverse digital intelligent teaching system is used to construct the Metaverse digital intelligent teaching system of the first preferred embodiment above, and the construction method includes: S101. Construct primitive database: collect or upload primitive data, and divide the primitive data into legend database, video database, model database, two-dimensional interactive database, three-dimensional interactive database and question bank according to the primitive data type; in addition, ensure the accuracy and completeness of the data to facilitate the subsequent teaching map construction and teaching application operations.

[0081] It should be noted that: in order to ensure the security of the system, it is necessary to perform basic checks on the uploaded primitive data. The basic checks include: verifying whether the file size exceeds the system limit, confirming the availability of the file format, and verifying the integrity of the file by calculating the file hash value. If any of the above items fails, the reason for failure will be recorded and an upload failure notification will be sent to the uploader. If all of the above checks pass, proceed to the next step; reasons for failure include: file size exceeds the limit, file format is unavailable, and file is incomplete, etc. At the same time, it is necessary to perform a security check on the uploaded primitive data; the security check includes: performing virus detection. After the virus detection passes, regular expressions are used to quickly screen obvious illegal content, and then the BERT model is used for deep content analysis. If any of the above items fails, the reason for failure will be recorded and an upload failure notification will be sent to the uploader. If all of the above checks pass, proceed to the next step; reasons for failure include: virus detection failed, illegal content quick screening failed, content analysis failed, etc. S102. Construct a graph construction module, which includes a text generation module and a graph generation module; the text generation module generates corresponding primitive texts from each primitive data to ensure the accuracy and comprehensibility of the text, so as to facilitate the use of the graph generation module; the graph generation module generates teaching graphs using a single primitive text or multiple primitive texts, and these graphs will be used to assist teaching and learning, improve teaching efficiency and learning effects, and store the generated teaching graphs in a graph database to ensure the accessibility and security of the graphs.

[0082] S103. Construct a teaching application operation module and establish a data interaction protocol between the teaching application operation module and the Internet; this includes defining the data transmission format, data encryption method and data interaction process to ensure data security and stability, while providing a user-friendly operation interface for easy use by teachers and students.

[0083] S104, constructing a teaching database: The teacher first uses the teaching map to obtain relevant primitive data, and then uses the primitive data to construct teaching data. Finally, according to the type of teaching data, the teaching data is divided into teaching material data, courseware data, tutorial data and lesson plan data, completing the construction of the teaching material database, courseware database, tutorial database and lesson plan database, ensuring the richness and diversity of teaching resources and meeting the needs of different teaching scenarios.

[0084] In the present invention, the teaching application operation module described includes the following components: The primitive data editing module allows users to edit the permissions of primitive data according to specific needs to ensure the security and suitability of the data; for example, teachers can select specific pictures, models or videos according to the needs of courseware production, and then use the primitive data editing module to adaptively modify, assemble and perform other operations on the selected pictures, models or videos.

[0085] The teaching data editing module is designed to edit the permissions of teaching data according to teaching needs, so as to make the management of teaching content more flexible and efficient; for example, teachers can choose specific teaching materials according to the needs of courseware production, and then use the teaching data editing module to make adaptive modifications to the teaching materials.

[0086] like Fig. 9 As shown, a Metaverse digital intelligent teaching method is based on the Metaverse digital intelligent teaching system of the first preferred embodiment above, and performs the following steps: S201, the teacher side will first use the teaching map to obtain relevant primitive data. These primitive data are the basis for building teaching content, and they contain key information and knowledge points required in the teaching process. Then, the teacher side will use these primitive data to build teaching data. This step involves the integration and processing of primitive data to form a data structure suitable for teaching. Finally, according to the type of teaching data, the teacher side will import these teaching data into the corresponding database, which may include teaching material database, courseware database, tutorial database or lesson plan database, to ensure that the teaching data can be effectively managed and used.

[0087] S202, the teacher is responsible for creating a live classroom, which usually involves setting parameters of the live classroom, such as classroom theme, time, participants, etc., and ensuring that all functions of the live platform are running normally so that subsequent teaching activities can proceed smoothly.

[0088] S203, the teacher and the student will enter the live classroom within the preset time period. In the live classroom, the teacher will display the teaching content, which may include teaching materials in various forms such as video, audio, pictures, and text. At the same time, the student can watch the teaching content in real time, and communicate and interact with the teacher through the live platform, ask questions, and participate in discussions, thereby achieving instant communication and feedback between teachers and students.

[0089] S204: After participating in the live class, the student will submit a personal feedback report. This report contains information such as the student's understanding of the teaching content, feedback on the teaching methods, and feelings about classroom interaction. The teacher can evaluate the teaching effect and understand the students' learning situation by collecting and analyzing these feedback reports, and adjust the teaching strategy accordingly to improve the teaching quality and students' learning effect.

[0090] In S201, according to the requirement of editing teaching courseware, the primitive data in the standard format may be edited by a digital courseware editor; the specific editing process may include: Import pptx files or create new courseware through the courseware editor, so you can easily use existing presentation resources or build new teaching content from scratch; Select the basic data for making courseware in the material database. These basic data include text, pictures, charts and other types, which provide the basis for the richness and interactivity of courseware. Insert the selected primitive data into the pptx file or the newly created courseware. In this way, the resources in the material database can be combined with the courseware content to enhance the expressiveness of the courseware. According to the courseware display requirements, adjust the position, size and angle of the inserted primitive data to ensure the visual effect of the courseware and the accuracy of information transmission; Edit several switchable layers containing different primitive data. By switching the layers, the courseware content can be dynamically displayed, which improves the teaching interactivity and students' learning interest. Call the digital model editor to edit the 3D model. Editing content includes: expanding the exploded view to clearly show the parts of the complex structure; adding handouts to provide detailed explanations and instructions for the 3D model; adding labels to facilitate quick location and reference of specific parts of the model during teaching; The edited courseware is saved in a standard format and stored in the courseware database of the cloud server. This not only facilitates the management and sharing of courseware, but also ensures the long-term preservation and timely updating of teaching resources.

[0091] In S202, a live classroom is established through the classroom establishment unit of the teacher's end, and network synchronous teaching is carried out for students; the specific steps are as follows: Through the classroom establishment unit on the teacher side, a virtual classroom environment is created based on the course information set by the teacher; The streaming media module and message queue module of the cloud server are used to realize synchronous sharing between the teacher and the student, and to provide students with online synchronous teaching; specifically, it includes: Perform audio and video acquisition and encoding, specifically: collect microphone input through the system audio driver; collect teacher portrait images through the camera driver; collect desktop images through the system screen capture API; use AAC encoding for audio and H.264 / H.265 encoding for video for real-time compression; Perform media streaming, specifically: use RTMP or WebRTC protocol for real-time transmission; UDP-based transmission channel to ensure low latency; use streaming media server for stream distribution; support adaptive bit rate adjustment in weak network environment; Implement audio and video synchronization mechanism, specifically: use unified timestamps to mark audio and video frames; perform buffer control through audio and video synchronization queues at the receiving end; synchronize video playback based on the audio clock; dynamically adjust the buffer size to balance latency and fluency; Perform mixed stream processing, specifically: perform screen layout synthesis on the server or client side; overlay the teacher's head portrait as a small window on the screen sharing picture; support dynamic adjustment of the position and size of each picture; provide a variety of preset layout templates; Perform bandwidth optimization, specifically: dynamically adjust video bitrate and resolution according to network conditions; perform motion detection on screen sharing content and reduce update frequency in static areas; support key frame request mechanism to quickly restore the picture; implement packet loss retransmission and forward error correction.

[0092] In S203, the student terminal receives and displays teaching content through the classroom learning module, which specifically includes: Perform media stream reception and decoding, receive media stream data from the cloud server; decode audio and video data; play audio and video synchronously according to timestamp information; Execute screen rendering and layout, render the decoded video screen according to the preset layout; support students to customize the screen layout; provide full screen, picture-in-picture and other display modes; Execute audio playback control and play the decoded audio stream through the system audio interface; support volume adjustment and mute control; provide audio device selection function; Perform local optimization processing and adjust the decoding strategy according to the performance of the terminal device; adaptively adjust the buffer strategy according to different network conditions; support live playback and progress control; and provide a fault recovery mechanism when the network is abnormal.

[0093] The interaction between teachers and students is achieved through the classroom interaction unit on the teacher side and the teacher-student interaction unit on the student side. The content of the interaction includes online questions, voting, group discussions, and instant tests.

[0094] Implement online questioning function, specifically: students can raise text questions; teachers can view and answer questions in real time; support question queuing and priority management; record question and answer history; The specific implementation process of the online question function is as follows: both the teacher and student sides are based on Web browsers and Metaverse devices, and a WebSocket real-time communication channel is established through the cloud server; data interaction adopts a layered design, including: the transport layer uses TLS 1.3 protocol to ensure data security; the session layer uses JWT (JSON Web Token) for identity authentication; the application layer uses a custom message protocol, and the message body uses Protocol Buffers format to reduce the amount of data transmitted. Among them, the student side provides a text input box and an audio collection button, and the question content and student identity information are packaged and sent to the cloud; the teacher side implements the question list display, priority sorting and answer interface; the cloud server is responsible for message forwarding, question queue management and historical record storage to ensure the real-time nature of the question-answering interaction between teachers and students.

[0095] The specific implementation of the voting function is as follows: the teacher side provides a voting creation interface, which supports setting parameters such as voting type, option content, time limit, etc.; data interaction adopts the publish-subscribe mode, and the real-time distribution of messages is realized through the Redis Pub / Sub mechanism; voting data is stored in a Hash structure, and the atomicity of counting is ensured through Redis transactions; a two-way data synchronization mechanism is adopted, and the client's local storage (LocalStorage) is synchronized with the server data in real time. The student side displays the voting options and collects the selection results; the cloud service side is responsible for the summary statistics of the voting data, and pushes the real-time results to the teacher side and the student side; the teacher side displays the statistical results in the form of charts, and the student side can view the voting progress, realizing real-time interactive feedback in the classroom.

[0096] Implement group discussion functions, specifically: support automatic or manual grouping; provide voice and video communication within the group; support text and whiteboard collaboration; teachers can patrol and guide between groups; The specific implementation of the group discussion function is as follows: the teacher side provides a group management interface, which can be used for random grouping or manual adjustment; data interaction adopts a distributed architecture and uses ZooKeeper for distributed session management; real-time data within the group is transmitted through a message queue (RabbitMQ) to ensure reliable message delivery; according to the dynamic adjustment of resource allocation strategies on the cloud server side, the system automatically adjusts computing and storage resources according to the actual load (such as the number of online groups, the number of concurrent users, data traffic, etc.); when the load is small, maintain single-node operation to save costs, such as when a single class is used; when the load increases, it automatically expands to a multi-node distributed architecture to ensure system performance and availability, such as when multiple classes are online at the same time; the student side automatically joins the corresponding group based on the teacher's random / manual grouping results, and enables audio and video interaction and whiteboard collaboration functions; the cloud server side maintains the group status and forwards the audio and video streams and collaboration data within the group; the teacher side has the function of switching between groups, which can quickly enter each group to view the discussion status in real time, and realize the complete process of online group discussion.

[0097] Execute the instant test function, specifically: support online tests of various question types; collect answer data in real time; automatically perform statistical analysis on test results; and provide personalized explanations for wrong questions.

[0098] The specific implementation of the instant test function is as follows: the teacher side provides a test question editing and publishing interface; the data interaction adopts the RESTful API architecture; the answer data adopts distributed transaction processing to ensure data consistency; Redis is used to cache hot data to improve query efficiency; an asynchronous message processing mechanism is adopted to achieve asynchronous analysis of answer results through message queues. The student side displays the test content and collects answer information; the cloud service side collects and analyzes the answer data, pushes the answer statistics to the teacher side, and pushes personalized explanations of wrong questions to the student side; the teacher side can view the overall answer status of the class in real time, and the student side can immediately obtain answer feedback, realizing instant evaluation of classroom tests.

[0099] Outside of class, students can study independently through the student terminal and participate in group discussions and / or battle exercises with other students; Under the after-class self-study function, students access the public resources of the courseware database, teaching material database, model database and course database through the student terminal. The system controls the permissions set by the teacher and only allows students to view and use the authorized public content. The system records students' access to various resources and learning data for analyzing learning behavior and evaluating learning effects.

[0100] With the after-class group discussion function, students can independently form or join study groups: the system recommends suitable discussion groups for students based on their learning progress and interest tags; group members can conduct real-time voice and video communication to facilitate instant discussion of learning difficulties; study notes and related learning materials can be shared within the group; group members can collaborate on editing the same document and complete learning tasks together; the system will store discussion content by topic for easy subsequent review; students can retrieve historical discussion content by keywords, time and other dimensions.

[0101] Under the after-class practice function, the system provides online question practice: intelligent matching of practice opponents based on students' knowledge level; practice question types include multiple-choice questions, fill-in-the-blank questions, and other forms; during the battle, the system keeps time in real time and calculates scores based on the accuracy and speed of answering questions; records the data of each battle, generates personal ability levels and rankings; supports initiating practice challenges to friends; and saves complete battle records for students to review and summarize.

[0102] In S204, a personal feedback report, a class feedback report and a teaching feedback report are generated based on the behavior data generated by the students in each learning link through the teaching feedback module; Through the personal assessment unit, a personal learning assessment model is adopted to obtain a personal feedback report after weighted analysis based on the student's personal classroom learning data, independent learning data, collaborative learning data and practice evaluation data. The personal feedback report includes the individual's comprehensive learning score, module score analysis, knowledge mastery heat map, learning behavior report and learning improvement suggestions; providing students with a basis for learning improvement.

[0103] The data inputs to the personal learning assessment model include: Classroom learning data, including: class attendance records, real-time interaction, class concentration, etc.; Self-study data, including: video viewing time, learning resource access, number of note annotations, etc. Collaborative learning data, including: number of speeches in the discussion area, group contribution, number of resource sharing, etc.; Practice assessment data, including: practice completion rate, question answering accuracy rate, knowledge point mastery, etc.

[0104] The weight distribution of the personal learning evaluation model is: Class performance accounts for 30%, of which attendance accounts for 10%, interaction accounts for 10%, and concentration accounts for 10%; After-class learning accounts for 40%, of which video learning accounts for 15%, resource use accounts for 15%, and note-taking accounts for 10%; Collaborative discussion accounted for 15%, of which participation accounted for 8% and contribution accounted for 7%; The practice score accounts for 15%, of which the accuracy accounts for 8% and the completion accounts for 7%.

[0105] The outputs of the personal learning assessment model include: Comprehensive learning score, using a 100-point scoring standard; Module score analysis, showing the specific scores of each learning module; Knowledge mastery heat map, showing the mastery level of each knowledge point; Learning behavior report, analyzing learning characteristics and behavior patterns; Learning improvement suggestions: provide targeted learning improvement suggestions.

[0106] By continuously updating personal learning data, students can understand their own learning situation in a timely manner, adjust their learning methods according to the evaluation results, and continuously improve their learning effects.

[0107] Through the class assessment unit, a class learning situation assessment model is adopted to integrate the personal learning data, group activity data, battle practice data and resource usage data of each student in the class; after data processing, a class feedback report is obtained, which includes a class score distribution map, a knowledge mastery matrix learning progress chart, a group effectiveness evaluation and a class learning situation report; providing a basis for teachers to grasp the overall learning situation of the class.

[0108] The data input of the class learning assessment model includes: Personal learning data, including: each student’s attendance rate, class participation, homework completion rate, test scores, etc.; Group activity data, including: group discussion frequency, member contribution, collaborative project completion, etc.; Battle practice data, including participation rate, accuracy rate, completion speed, progress, etc. Resource usage data, including: number of visits to learning materials, video viewing time, amount of notes taken, etc.

[0109] The data processing method of the class learning situation assessment model includes: Calculate the class mean and find the class average level for each indicator data; Analyze data distribution, calculate standard deviation and distribution range, and identify class differences; Draw a knowledge map to show the class's mastery of knowledge points; Generate a progress curve to track the overall learning progress of the class.

[0110] The output results of the class learning assessment model include: Class score distribution chart, showing the overall score level and distribution of the class; Knowledge mastery matrix, showing the mastery degree of each knowledge point; Learning progress chart to track the class's progress and compliance with the plan; Group effectiveness evaluation, analyzing the collaborative performance of each learning group; Class learning report, summarizing the class learning characteristics and providing suggestions for improvement.

[0111] Class learning data is updated regularly so that teachers can understand the overall situation of the class in a timely manner, adjust teaching strategies in a targeted manner, and improve the overall level of the class.

[0112] Through the teaching evaluation unit, a teaching quality evaluation model is adopted. Based on the teacher's personal teaching process data, each student's personal learning effect data and student feedback data, a teaching feedback report is obtained after weighted analysis. The teaching feedback report includes a teaching quality score, a teaching analysis report and a list of improvement suggestions; providing teachers with a basis for teaching improvement.

[0113] The data inputs of the teaching quality assessment model include: Teaching process data, including: classroom questions and interactions, students’ correct answers, classroom activity, teaching progress completion, etc. Learning effect data, including: homework completion rate on time, average test score, knowledge point mastery, learning progress, etc. Student feedback data, including: student satisfaction score, class concentration, number of problem feedback, etc.; resource usage data, including: courseware resource utilization rate, learning material coverage, etc.

[0114] The weight distribution of the teaching quality evaluation model is: The teaching process data accounted for 40%, of which classroom questions and interactions accounted for 15%, correct answer rate accounted for 10%, classroom activity accounted for 10%, and teaching progress accounted for 5%; Learning effect data accounted for 35%, of which homework completion rate accounted for 10%, test scores accounted for 10%, knowledge point mastery accounted for 10%, and improvement accounted for 5%; Student feedback data accounts for 15%, of which satisfaction score accounts for 5%, class concentration accounts for 5%, and problem feedback accounts for 5%; resource usage data accounts for 10%, of which courseware usage rate accounts for 5% and material coverage rate accounts for 5%.

[0115] The output results of the teaching quality evaluation model include: The teaching quality score is scored on a 100-point scale, with 90 points or above being excellent, 80-89 points being good, 70-79 points being qualified, and below 70 points being in need of improvement; Teaching analysis report, including analysis of teaching strengths, diagnosis of weak links, teaching progress evaluation, distribution of key and difficult points, etc.; A list of improvement suggestions is provided, which puts forward targeted suggestions for adjusting teaching strategies and specific improvement measures.

[0116] Evaluation standards are regularly updated based on the latest teaching data. Teachers can adjust teaching plans in a timely manner based on evaluation results, and continuously improve teaching quality through a cycle of teaching quality evaluation, improvement, and re-evaluation.

[0117] Digital model editor, including: The 3D model editing module is used to fully edit and configure the 3D model, including basic information, background, material, post-processing, exploded view, lighting, animation, auxiliary lines / axes, labels, handouts and operation prompts. The edited 3D model is saved in the database. It includes: Basic information editing unit for setting model name and uploading model logo; Background editing unit for selecting background color / image and adjusting background effects; A material editing unit for adjusting the material, color, transparency and texture of each component of the 3D model; Post-processing unit for adjusting glow effects and tonal exposure; Exploded view cells for automatic explosion and custom explosion position settings; Light editing unit for setting light source planes, adjusting ambient light, setting parallel light, point light and spot light; Animation editing unit for animating models, configuring animation parameters, and animating axes; Auxiliary line / axis configuration unit for adjusting model axis rotation, position, controlling skeleton display and setting auxiliary lines; A tag editing unit for adding, editing, and deleting tags; Handout editing unit for adding, editing, deleting and positioning handouts; A section setting unit for setting sections of a three-dimensional model and displaying internal structures; A help setting unit for setting 3D operation prompts and function operation prompts in the model viewing interface; The method for implementing the label adding function in the digital model editor includes: Model loading and display: reading the 3D model data and rendering and displaying the 3D model in the 3D model editing module; wherein the 3D model is composed of one or more sub-models, each of which has independent geometric structure and material information; Label object generation: calling the CSS2DRenderer renderer and CSS2DObject tool class in the Three.js library to generate a label object for displaying label content; the label object supports HTML and CSS styles, and can flexibly customize the appearance and content of the label; Label positioning and adding: S31, receiving a click operation from the user, and obtaining the two-dimensional screen coordinates of the click position; S32, based on the two-dimensional screen coordinates, using the ray detection technology of Three.js, generating a ray starting from the camera viewpoint and passing through the click position; S33, calculating the intersection of the ray and the three-dimensional model, and determining the specific sub-model object clicked by the user; S34, converting the two-dimensional screen coordinates into corresponding three-dimensional world coordinates as the positioning coordinates of the tag; S35, associating the label object with the sub-model object determined in S33, and assigning the three-dimensional world coordinates obtained in S34 to the label object, so as to achieve accurate positioning of the label.

[0118] The method for implementing the label editing function in the digital model editor includes: Step 1: Edit the label content; S11, adding an editable text input box to each label object; S12, implement an event listener for double-clicking a tag to trigger the edit mode; S13, in edit mode, displaying a text input box and filling it with the current label content; S14, add focus loss or enter event listeners to update the label content when the user completes editing; Step 2: Edit the label position and implement the label dragging function, allowing users to adjust the label position directly in the 3D scene; S21, uses Raycaster and plane projection technology of Three.js to convert the 2D movement of the mouse on the screen into position changes in 3D space; S22, updating the position attribute of the label in real time during the dragging process.

[0119] The method for realizing the display and hiding control function of the label in the digital model editor includes: Create a global switch button or checkbox and add event listeners to the control to toggle the visibility of all labels.

[0120] Iterate over all label objects and set their visible properties to true or false.

[0121] Add category attributes to tags to achieve batch control of tag status; Create a category list, each category item contains a checkbox; Add an event listener to each category checkbox and display or hide the label of the corresponding category according to the selected state; Individual control tab states: Add a small show / hide button to each tab, and click the button to toggle the visibility of the individual tab.

[0122] The method for realizing the explosion function of a model in a digital model editor includes: Obtain model data in the database according to the current network status through the 3D model editing module; When the network condition is good, obtain the complete data of the model, including the initial model data and the preset explosion processing data; When the network condition is poor, only the initial model data is obtained; and the model is displayed in the three-dimensional model editing module; the model is composed of multiple sub-models; The user automatically decomposes the model through the model decomposition slider, and receives the user's explosion operation instructions through the 3D model editing module; If complete data has been obtained, each sub-model is directly separated according to the preset rules; If only the initial data is obtained, the explosion operation instruction is transmitted to the cloud server, and the cloud server automatically explodes the original model according to the preset explosion rules, and separates each sub-model according to the preset rules; The user activates the explosion model position adjustment switch, and the model returns to the original model state. The user makes fine adjustments to the separable sub-model by dragging, including position dragging and angle adjustment. The three-dimensional model editing module converts the user's adjustment operation into corresponding instructions and transmits them to the cloud processor for execution. The cloud processor saves the explosion status data of the model adjusted by the user to the database and ensures the consistency between the data in the database and the data displayed by the 3D model editing module; Taking the original model as the starting point and the saved model explosion state data as the end point, set the duration of the model explosion process. Based on the duration, generate a demonstration file that can execute the model explosion in a dynamic gradient manner in the 3D model viewing interface.

[0123] Digital courseware editor, including: User Interface Module: Provides an intuitive web-based operating interface that allows users to access and use all editing functions through a browser and / or Metaverse device; including: System integration interface, used to interact with digital model editors, digital research and creation editors, etc.; including 3D model editing interface, which connects with the model editor and supports exploded view display and in-depth editing of 3D models; The data interaction unit is responsible for communicating with the cloud server, accessing and managing resources such as the material database and courseware database, uploading operation instructions, receiving feedback results and displaying them.

[0124] Cloud processing module, including: Import unit: supports importing existing pptx format files and creating new courseware files.

[0125] Insert unit: supports the insertion of virtual unit exercises, online resources, and model resources; realizes the integration and display of diversified teaching resources.

[0126] Editing unit: provides basic editing functions such as position adjustment, size scaling and angle rotation for inserted primitive data.

[0127] Layer Unit: Supports the creation and editing of multiple layers containing different primitive data, and allows switching between these layers.

[0128] A digital courseware editing method, comprising: Create or import courseware; If a new courseware is created, a new courseware file is created through the import unit of the cloud processing module; If you want to import existing courseware, you can import the pptx format file through the import unit of the cloud processing module; Edit courseware content; Insert teaching resources by inserting units, including virtual unit exercises, online resources, model resources, etc.; Users drag teaching resources (such as 3D models or virtual simulation exercises) from the database module to the canvas through the system integration interface; when the user starts to drag resources, the system records the type of resources; when the user drags the resources to the canvas and releases the mouse, the system creates a new element at the location where the mouse is released, displaying the type of resource inserted; and intuitively placing various teaching resources at the desired location.

[0129] Use the editing unit to perform basic editing on the inserted primitive data, such as position adjustment, size scaling, and angle rotation; Specifically, take the primitive data scaling function as an example: the user interface module allows users to adjust the size of elements by dragging. There is a small blue square in the lower right corner of the element as a resize handle. When the user presses this handle and moves the mouse, the width and height of the element will change with the movement of the mouse; the size of teaching resources can be easily adjusted to suit different teaching needs.

[0130] Use layer units to create, edit, and switch between multiple layers containing different primitive data; Specifically, users control the visibility of different layers through check boxes. In the layer panel, each layer has a corresponding check box. When the user checks or unchecks the check box of a layer, the system will display or hide the content of the layer on the canvas accordingly, realizing the layered display of different layers.

[0131] 3D model editing; Connect with the model editor through the 3D model editing interface in the system integration interface; Perform exploded view display and in-depth editing of 3D models; Save and Export: Save the edited courseware to the database module; Export to formats suitable for different devices and platforms as needed.

[0132] Digital and paper-based integrated textbook editor and viewer, including: User interface module, including: The textbook editing interface is used to provide textbook editing functions, including automatic typesetting tools, multimedia resource embedding tools, layout setting tools, and catalog generation tools; The automatic typesetting tool and the catalog generation tool respectively implement automatic typesetting and catalog generation of teaching materials by calling the automatic typesetting algorithm and the catalog generation algorithm of the teaching material processing unit; The textbook reading interface provides users with personalized reading methods, including single / double-page reading interface, full-screen reading interface, directory / thumbnail jump, bookmarks, notes, and viewing embedded resources; The textbook reading interface loads and displays textbook content and resources by calling the courseware database of the database module; The textbook mall interface is used to provide textbook browsing, searching, and purchasing / downloading functions; the resource library display interface is used to provide resource browsing and switching functions; The textbook mall interface acquires and displays the textbook list by calling the courseware database of the database module; System integration interface, used to interact with digital model editors, digital research and creation editors, etc.; including 3D model editing interface, which connects with the model editor and supports exploded view display and in-depth editing of 3D models; Cloud processing module, including: Teaching material processing unit, used to execute automatic typesetting algorithm, catalog generation algorithm and resource conversion processing; cloud storage system, used to store teaching materials, resources and user data; Print service module, used to manage print queues, generate QR codes, and convert non-printable resources; Printing method: When a user initiates a print request in the textbook editing interface or reading interface, the print service module receives the request; Manage print queues; Add the received print request to the print queue; Manage print queues based on a first-in-first-out (FIFO) principle or other priority strategy; Analyze the content of the textbooks to be printed and identify different types of resources such as text, pictures, videos, models, etc. Convert non-printable resources; Generate thumbnails or representative static images of assets; If the original resource has not been uploaded, upload the original resource to the cloud storage system; Generates a unique URL pointing to a cloud resource.

[0133] Generate a QR code; Generate a corresponding QR code image based on the cloud URL of the non-printable resource; Combining the generated QR code image with the resource thumbnail to form a printable image unit; Recombine the original printable content (such as text, pictures) with the converted non-printable resources (thumbnails + QR codes) to form a complete printable teaching material.

[0134] Convert the reorganized teaching material content into a file format suitable for printing (such as PDF).

[0135] Print execution; Send the generated print file to the printing device; Monitor printing progress and update print queue status; When printing is complete, a notification is sent to the user.

[0136] Save relevant information of the printing task (such as printing time, number of pages, resource conversion status, etc.) to the cloud storage system for subsequent statistics and analysis.

[0137] Teaching material creation process: Set basic information of the textbook, including determining the textbook name, writing the textbook introduction, selecting the textbook category, and setting the training level.

[0138] Design the appearance of the textbook, including setting the textbook layout, designing the textbook cover, configuring the textbook spine, and making the textbook back cover.

[0139] The system automatically generates a directory based on the textbook content structure.

[0140] Arrangement of teaching materials content: Support text typesetting, including but not limited to the settings of font, font size, line spacing, and paragraph style; Provides text editing functions such as insert, delete, copy, paste, etc.

[0141] Embedded teaching resources; Image resource embedding: Select the image file; Adjust the image size and position; Add a caption for the image.

[0142] Video resource embedding; Upload a video file or enter a video link; Set the video player size and position; Configure video playback parameters, such as automatic playback, loop playback, etc.

[0143] Document resource embedding; Select the document file; Set how the document will be displayed, such as inline or linked.

[0144] Model resource embedding; Import 3D model files; Set model display parameters, such as initial viewing angle, zoom ratio, etc.

[0145] Embed 2D interactive resources; Import 2D interactive resource files or codes; Configure the interactive area size and position.

[0146] Three-dimensional interactive resource embedding; Import 3D interactive resource files or scenes; Set interaction scene parameters, such as interaction mode, trigger conditions, etc. Embedding of R&D resources; Select resources in the R&D platform; Set how resources are displayed and interacted with in the teaching material.

[0147] Content review and optimization; Check the overall structure and content integrity of the teaching materials; Optimize resource layout and typesetting effects; Ensure the normal display and operation of various embedded resources.

[0148] Textbook preservation and publication; Save the edited content of the textbook; Generate a preview version of the teaching material; Set access permissions for textbooks; Publish teaching materials to designated platforms or systems.

[0149] Print teaching materials.

[0150] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When the use is implemented in whole or in part in the form of a computer program product, the computer program product includes one or more computer instructions. When the computer program instructions are loaded or executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL) or wireless (e.g., infrared, wireless, microwave, etc.)). The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk SolidState Disk (SSD)), etc.

[0151] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Any simple modification, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention are within the scope of the technical solution of the present invention.

Claims

1. A Metaverse digital intelligent teaching system, comprising a cloud service end, a teacher end and a student end; characterized in that: The cloud service end includes a data storage module, a graph construction module and a teaching application operation module, wherein: The data storage module includes a primitive database, a teaching database and a graph database; The primitive database is divided into a legend database, a video database, a model database, a two-dimensional interaction database, a three-dimensional interaction database and a question database according to primitive data types; The teaching database is divided into a teaching material database, a courseware database, a course database and a teaching plan database according to the type of teaching data; The graph construction module includes a text generation module and a graph generation module; the text generation module generates corresponding primitive texts from each primitive data, and the graph generation module generates a teaching graph using a single primitive text or multiple primitive texts, and stores the generated teaching graph in the graph database; The teaching application operation module receives instructions from the teacher side to perform permission operations on the data in the primitive database, teaching database and atlas database, and receives instructions from the student side to perform permission operations on the teaching data. The teacher end and the student end construct a metaverse virtual scene that is compatible with the target teaching content through a virtual scene construction module, and display the target teaching content in the metaverse virtual scene.

2. The Metaverse digital intelligent teaching system according to claim 1 is characterized in that: The primitive texts include legend text, video text, model text, two-dimensional interactive text, three-dimensional interactive text and test text; The text generation module comprises: The graphic text generation unit generates the graphic text corresponding to each graphic legend according to the graphic content by using the graphic text generation model; The video text generation unit uses the image-text generation model to generate the video text corresponding to each video segment based on the video content; Model text generation part: the teacher generates the model text corresponding to each model according to the content of the model; A two-dimensional interactive text generation unit generates two-dimensional interactive text corresponding to each two-dimensional interactive data according to the two-dimensional interactive data by using a picture-text generation model; A three-dimensional interactive text generation unit generates three-dimensional interactive text corresponding to each three-dimensional interactive data according to the three-dimensional interactive data by using a graphic-text generation model; The test text generation unit generates the test text corresponding to each test data according to the test data by using the image-text generation model.

3. The Metaverse digital intelligent teaching system according to claim 2 is characterized in that: The video text generation unit first extracts the frame sequence of the video data, then processes each frame of the image using the image-text generation model to obtain the frame sequence text, and finally generates the video text according to the frame sequence text.

4. The Metaverse digital intelligent teaching system according to claim 1 is characterized in that: The primitive text includes a text content module and a text keyword module. The text content module describes the content information of the primitive data through text, and the text keyword module is a keyword obtained through a semantic analysis model. The keywords include: First-level keywords, used to identify the subject category to which the base text applies; Secondary keywords, used to identify the target name involved in the primitive text; The third-level keywords are used to identify the characteristics of each target in the primitive text.

5. The Metaverse digital intelligent teaching system according to claim 4 is characterized in that: The graph generation module first uses a clustering algorithm to perform initial clustering on each level of keywords of a single primitive text or multiple primitive texts to obtain a level-by-level clustering matrix, and then performs secondary clustering on the level-by-level clustering matrix to obtain a teaching graph.

6. The Metaverse digital intelligent teaching system according to claim 1, characterized in that: The cloud service end also includes a data standardization module, which converts the uploaded video data into MP4 format, converts the uploaded document data into PDF and / or JPG format, converts the uploaded 3D model data into GLB format, and converts the uploaded online resource data into ZIP format.

7. The Metaverse digital intelligent teaching system according to claim 6 is characterized in that: The teacher and student terminals interact with the cloud server terminal based on a Web browser.

8. The Metaverse digital intelligent teaching system according to claim 6, characterized in that: The teacher terminal includes: The first data interaction module establishes a data link with the teaching application operation module, and is used to read the primitive database, the teaching database and the atlas database, the primitive text and the teaching atlas; An editor module, for editing the primitive database, teaching database and atlas database, primitive text and teaching atlas; Demonstration teaching module, used to create and manage live classes, display teaching content, and conduct communication and interaction between teachers and students; The teaching feedback module is used to view personal feedback reports, class feedback reports and teaching feedback reports.

9. The Metaverse digital intelligent teaching system according to claim 8, characterized in that: The student terminal includes: The second data interaction module establishes a data link with the teaching application operation module to read the teaching content and the teacher-student communication and interaction content in the demonstration teaching module; Classroom learning module, used for classroom learning and teaching interaction; Self-study module, used for after-class self-study; Collaborative Learning modules for participating in group discussions and collaboration; Practice and assessment module, used to complete exercises and assessments; Learning Feedback module, used to view personal feedback reports.

10. A method for constructing a metaverse digital intelligent teaching system, characterized in that: Used to construct the Metaverse digital intelligent teaching system according to any one of claims 1 to 9, the construction method comprises: S101, constructing a primitive database: collecting or uploading primitive data, and dividing the primitive data into a legend database, a video database, a model database, a two-dimensional interaction database, a three-dimensional interaction database, and a question database according to the primitive data type; S102, constructing a graph construction module, the graph construction module includes a text generation module and a graph generation module; the text generation module generates a corresponding primitive text from each primitive data, the graph generation module generates a teaching graph using a single primitive text or multiple primitive texts, and stores the generated teaching graph into a graph database; S103, constructing a teaching application operation module, and establishing a data interaction protocol between the teaching application operation module and the Internet; S104, constructing a teaching database: the teacher first uses the teaching map to obtain relevant primitive data, then uses the primitive data to construct teaching data, and finally divides the teaching data into teaching material data, courseware data, tutorial data and lesson plan data according to the type of teaching data, thus completing the construction of the teaching material database, courseware database, tutorial database and lesson plan database.

11. The method for constructing a Metaverse digital intelligent teaching system according to claim 10, characterized in that: The teaching application operation module includes: The primitive data editing module is used to edit the permissions of the primitive data as needed; The teaching data editing module is used to edit the permissions of teaching data as needed.

12. A metaverse digital intelligent teaching method, characterized in that: Based on the Metaverse digital intelligent teaching system according to any one of claims 1 to 9, the following steps are performed: S201, the teacher first uses the teaching map to obtain relevant primitive data, then uses the primitive data to construct teaching data, and finally imports the teaching data into a teaching material database or a courseware database or a tutorial database or a teaching plan database according to the type of teaching data; S202, the teacher creates a live classroom; S203. During a preset time period, the teacher and the student enter the live classroom, display the teaching content in the form of a metaverse, and interact with each other.

13. The Metaverse digital intelligent teaching method according to claim 12, characterized in that: Also includes: S204. The student submits a personal feedback report.

Images