Teaching method and system based on generative AI and element universe

Abstract

The invention belongs to the technical field of universe. The invention provides a teaching method and system based on generative AI and element universe. The method comprises the following steps: determining a plurality of pieces of virtual teaching material attribute information according to teaching plan information; performing matching analysis on the attribute information of the virtual teaching materials and first virtual teaching materials stored in a database, acquiring corresponding teaching material data by accessing the Internet for attribute information of a plurality of second virtual teaching materials which fail in matching, and generating the second virtual teaching materials according to the teaching material data; putting the first virtual teaching material and the second virtual teaching material corresponding to the successfully matched first virtual teaching material attribute information into a teaching material pool; and obtaining a real-time teaching process, sequentially calling the adaptive first virtual teaching material or second virtual teaching material from the teaching material pool according to the real-time teaching process, and displaying the first virtual teaching material or the second virtual teaching material in the universe teaching system. According to the invention, automatic acquisition and generation of virtual teaching resources in meta universe teaching are realized.

Description

Technical Field

[0001] The present invention relates to the field of metaverse technology, and in particular to a teaching method and system based on generative AI and metaverse. Background Art

[0002] Metaverse-based teaching is an emerging educational method that uses virtual reality (VR), augmented reality (AR) and other digital technologies to create an immersive learning experience. This teaching model simulates real environments and situations, allowing students to understand knowledge more intuitively and deeply, improving learning efficiency and interest.

[0003] The existing Metaverse-based teaching is to arrange the pre-set teaching content in the Metaverse system, and the teacher manually switches to realize the display of the virtual display scene corresponding to the teaching content. This method will impose great restrictions on the teacher's teaching. For example, when the teacher needs to display the virtual teaching content about a certain physical experiment, the Metaverse system may not have the data preset, resulting in the inability to achieve full immersive teaching, which seriously affects the teaching effect. The solution of the present invention is to effectively solve or improve this technical problem. Summary of the invention

[0004] In this regard, the present invention provides a teaching method, system, electronic device, computer storage medium and computer program product based on generative AI and metaverse to solve the above-mentioned technical problems.

[0005] The present invention discloses a teaching method based on generative AI and metaverse, which is applied to a communication control device built based on generative AI. The method comprises the following steps: obtaining teaching plan information, and determining a number of virtual teaching material attribute information according to the teaching plan information; matching and analyzing each of the virtual teaching material attribute information with each of the first virtual teaching materials stored in a database to obtain a number of first virtual teaching material attribute information that successfully matches and a number of second virtual teaching material attribute information that fails to match; accessing the Internet based on each of the second virtual teaching material attribute information, crawling out corresponding teaching material data, and converting the teaching material data into second virtual teaching materials in a format adapted to a metaverse teaching system; putting each of the first virtual teaching materials and each of the second virtual teaching materials corresponding to the number of first virtual teaching material attribute information that successfully matches into a teaching material pool; obtaining a real-time teaching process, and sequentially retrieving the adapted first virtual teaching material or the second virtual teaching material from the teaching material pool according to the real-time teaching process, and displaying them in the metaverse teaching system.

[0006] In some embodiments, the obtaining of teaching plan information includes: the communication control device receiving the teaching plan information manually entered by the teacher, and / or automatically obtaining the teaching plan information corresponding to the current time period from the teaching affairs system.

[0007] In some embodiments, the matching and analyzing of the attribute information of each virtual teaching material with the first virtual teaching materials stored in the database includes: using the BERT model to perform semantic analysis on each of the first virtual teaching materials stored in the database to obtain corresponding teaching material semantic attribute information; performing semantic similarity analysis on the attribute information of each virtual teaching material and the semantic attribute information of each teaching material, if the semantic similarity is higher than the similarity threshold, it is determined that the corresponding attribute information of the virtual teaching material is matched successfully, otherwise, it is determined that the corresponding attribute information of the virtual teaching material is matched unsuccessfully.

[0008] In some embodiments, the accessing of the Internet based on each second virtual teaching material attribute information to crawl out the corresponding teaching material data includes: predicting the first display start time corresponding to each second virtual teaching material attribute information based on the teaching plan information, and calculating the time difference between the current time and the first display start time; calculating the crawl quantity corresponding to each second virtual teaching material attribute information based on the time difference and a positive correlation function; accessing the Internet according to each second virtual teaching material attribute information and the corresponding crawl quantity, and crawling out each teaching material data.

[0009] In some embodiments, before accessing the Internet based on each of the second virtual teaching material attribute information and crawling out the corresponding teaching material data, the method also includes: parsing the teaching plan information to obtain the teaching start time and the teaching end time; decomposing the teaching plan information into a number of teaching sub-segments in chronological order, and obtaining the corresponding teaching duration based on the teaching content evaluation corresponding to each of the teaching sub-segments, and determining the expected start time of each of the teaching sub-segments based on the teaching start time and the teaching duration; if the expected start time is later than the teaching end time, deleting the second virtual teaching material attribute information corresponding to the teaching sub-segment, that is, no longer accessing the Internet based on the second virtual teaching material attribute information to crawl out the corresponding teaching material data.

[0010] In some embodiments, the putting each of the second virtual teaching materials into the teaching material pool includes: predicting the second expected display time of each of the second virtual teaching materials according to the real-time teaching progress and the remaining teaching time corresponding to each of the teaching sub-segments; if the second expected display time is later than the teaching end time, the second virtual teaching material will not be put into the teaching material pool.

[0011] The present invention also discloses a teaching system based on generative AI and metaverse, which is applied to a communication control device built based on generative AI, and the system includes a receiving module, a matching analysis module, a material generating module, a material delivery module, and a display control module; the receiving module is used to obtain teaching plan information, and determine a number of virtual teaching material attribute information according to the teaching plan information; the matching analysis module is used to match and analyze each of the virtual teaching material attribute information with each of the first virtual teaching materials stored in the database, and obtain a number of first virtual teaching material attribute information that successfully matches and a number of second virtual teaching material attribute information that fails to match; the material generating module The block is used to access the Internet based on the attribute information of each second virtual teaching material, crawl out the corresponding teaching material data, and convert the teaching material data into the second virtual teaching material in a format suitable for the Metaverse teaching system; the material delivery module is used to put each of the first virtual teaching materials and each of the second virtual teaching materials corresponding to the attribute information of several first virtual teaching materials that have been successfully matched into a teaching material pool; the display and control module is used to obtain the real-time teaching progress, and according to the real-time teaching progress, sequentially retrieve the adapted first virtual teaching material or the second virtual teaching material from the teaching material pool, and display them in the Metaverse teaching system.

[0012] The present invention also discloses an electronic device, comprising: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor executes the computer program to implement the method described in any of the preceding items.

[0013] The present invention also discloses a computer storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement any of the above methods.

[0014] The present invention also discloses a computer program product, comprising a computer program stored on a non-transitory computer-readable medium, wherein the computer program implements any of the above methods when executed by a processor.

[0015] The beneficial effect of the present invention is that compared with the traditional method of pre-setting virtual teaching materials, when certain virtual teaching materials are missing in the database, the present invention can crawl the corresponding teaching material data through communication interaction with the Internet and convert it into a data format that can be read by the metaverse teaching system, thereby ensuring that there are more virtual teaching materials available for display during the metaverse teaching process, effectively improving the teaching effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 It is a flowchart of a teaching method based on generative AI and metaverse disclosed in an embodiment of the present invention.

[0018] Figure 2 It is a schematic diagram of the corresponding relationship between each teaching sub-segment and the attribute information of the virtual teaching material disclosed in the embodiment of the present invention.

[0019] Figure 3 It is a structural diagram of a teaching system based on generative AI and metaverse disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0020] The following is a description of the implementation of the present application by specific specific embodiments. People familiar with the technology can easily understand other advantages and effects of the present application from the contents disclosed in this specification. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0021] In addition, the technical features involved in the different embodiments of the present application described below can be combined with each other as long as they do not conflict with each other.

[0022] like Figure 1As shown, an embodiment of the present invention discloses a teaching method based on generative AI and metaverse, which is applied to a communication control device constructed based on generative AI, and the method includes the following steps: obtaining teaching plan information, and determining a number of virtual teaching material attribute information according to the teaching plan information; matching and analyzing each of the virtual teaching material attribute information with each of the first virtual teaching materials stored in the database to obtain a number of first virtual teaching material attribute information that successfully matches and a number of second virtual teaching material attribute information that fails to match; accessing the Internet based on each of the second virtual teaching material attribute information, crawling out the corresponding teaching material data, and converting the teaching material data into the second virtual teaching material in a format adapted to the metaverse teaching system; putting each of the first virtual teaching materials and each of the second virtual teaching materials corresponding to the first virtual teaching material attribute information that successfully matches into a teaching material pool; obtaining a real-time teaching process, and sequentially retrieving the adapted first virtual teaching material or the second virtual teaching material from the teaching material pool according to the real-time teaching process, and displaying them in the metaverse teaching system.

[0023] When it is necessary to use the Metaverse teaching system for immersive teaching, the communication control device first obtains the teaching plan information of this time, decomposes and analyzes the teaching plan information, and can obtain the attribute information of several virtual teaching materials needed for this teaching. At the same time, some first virtual teaching materials are pre-stored in the database. The attribute information of each virtual teaching material determined above is matched and analyzed with these first virtual teaching materials, so that several first virtual teaching material attribute information that successfully matches and several second virtual teaching material attribute information that fail to match can be obtained. For several first virtual teaching material attribute information that successfully matches, the first virtual teaching material that matches it is directly put into the teaching material pool; for several second virtual teaching material attribute information that fail to match, the corresponding teaching material data is crawled from the Internet through network crawling technology, and then these teaching material data are converted into a data format that can be recognized and executed by the Metaverse teaching system, and then also put into the teaching material pool. After this teaching is started, the communication control device can retrieve the adapted first virtual teaching material or second virtual teaching material from the teaching material pool in turn according to the real-time teaching process, and display it in the Metaverse teaching system, thereby realizing immersive teaching based on the Metaverse.

[0024] Therefore, compared with the traditional method of pre-setting virtual teaching materials, when certain virtual teaching materials are missing in the database, the above-mentioned scheme of the present invention can crawl the corresponding teaching material data through communication interaction with the Internet and convert it into a data format that can be read by the metaverse teaching system, thereby ensuring that there are more virtual teaching materials available for display during the metaverse teaching process, effectively improving the teaching effect.

[0025] In some embodiments, the obtaining of teaching plan information includes: the communication control device receiving the teaching plan information manually entered by the teacher, and / or automatically obtaining the teaching plan information corresponding to the current time period from the teaching affairs system.

[0026] The above teaching plan information can be manually input by the teacher, for example, the teacher sends the electronic version of the teaching plan information to the communication control device through a wired connection or a wireless connection. If the above teaching plan information manually input by the teacher is not obtained, the teaching system can be directly accessed to search for the teaching plan information corresponding to the current period from the teaching system.

[0027] Of course, the above two methods can also be carried out at the same time, and the teaching plan information obtained from the two methods can be compared. If there is a deviation, relevant prompt information can be output for the teacher to choose.

[0028] In some embodiments, the matching and analyzing of the attribute information of each virtual teaching material with the first virtual teaching materials stored in the database includes: using the BERT model to perform semantic analysis on each of the first virtual teaching materials stored in the database to obtain corresponding teaching material semantic attribute information; performing semantic similarity analysis on the attribute information of each virtual teaching material and the semantic attribute information of each teaching material, if the semantic similarity is higher than the similarity threshold, it is determined that the corresponding attribute information of the virtual teaching material is matched successfully, otherwise, it is determined that the corresponding attribute information of the virtual teaching material is matched unsuccessfully.

[0029] The multiple first virtual teaching materials stored in the database are video data in the corresponding data format, and the video data is the virtual content used for display in the metaverse teaching system in the future. The virtual teaching material attribute information is text data, which is used to describe what teaching materials are needed for this teaching, such as "a video showing the relationship between buoyancy and displacement volume", "a video showing the principle of pinhole imaging of light", etc. Obviously, the virtual teaching material attribute information in text format cannot directly calculate the similarity with the first virtual teaching material, and the matching calculation cannot be realized. In this regard, the present invention chooses to use the BERT model to perform semantic analysis on each first virtual teaching material stored in the database to obtain the corresponding teaching material semantic attribute information, such as converting a certain first virtual teaching material into "optical principle analysis of pinhole imaging", so as to realize the conversion of the first virtual teaching material into text data. At this point, the semantic similarity between the virtual teaching material attribute information and the teaching material semantic attribute information can be directly calculated by semantic analysis. When the semantic similarity is higher than the similarity threshold, the virtual teaching material attribute information is judged as a successful match, that is, it becomes the first virtual teaching material attribute information, otherwise it is judged as a failed match, that is, it becomes the second virtual teaching material attribute information. Among them, the above semantic similarity can also be achieved through the above BERT model, which will not be described in detail.

[0030] In some embodiments, the accessing of the Internet based on each second virtual teaching material attribute information to crawl out the corresponding teaching material data includes: predicting the first display start time corresponding to each second virtual teaching material attribute information based on the teaching plan information, and calculating the time difference between the current time and the first display start time; calculating the crawl quantity corresponding to each second virtual teaching material attribute information based on the time difference and a positive correlation function; accessing the Internet according to each second virtual teaching material attribute information and the corresponding crawl quantity, and crawling out each teaching material data.

[0031] The teaching plan information includes multiple second virtual teaching material attribute information corresponding to different display start times, and it takes a certain amount of time to convert the crawled teaching material data, so it is necessary to configure the number of teaching material data to be crawled for the second virtual teaching material attribute information corresponding to different display start times.

[0032] Specifically, the time difference between the first display start time and the current time corresponding to each second virtual teaching material attribute information is calculated. The smaller the time difference, the more urgent the second virtual teaching material attribute information is to be used in the teaching process. At this time, it is set to crawl a smaller amount of teaching material data from the Internet, which can effectively reduce the time consumption of data crawling, thereby increasing the probability that the corresponding second virtual teaching material is put into the teaching material pool for call before the teaching starts. On the contrary, the larger the time difference, the lower the urgency of the second virtual teaching material attribute information to be used in the teaching process. Since there is sufficient crawling time, it is set to crawl more teaching material data from the Internet at this time, which is conducive to screening out more suitable teaching material data to generate more suitable second virtual teaching materials.

[0033] In some embodiments, before accessing the Internet based on each of the second virtual teaching material attribute information and crawling out the corresponding teaching material data, the method also includes: parsing the teaching plan information to obtain the teaching start time and the teaching end time; decomposing the teaching plan information into a number of teaching sub-segments in chronological order, and obtaining the corresponding teaching duration based on the teaching content evaluation corresponding to each of the teaching sub-segments, and determining the expected start time of each of the teaching sub-segments based on the teaching start time and the teaching duration; if the expected start time is later than the teaching end time, deleting the second virtual teaching material attribute information corresponding to the teaching sub-segment, that is, no longer accessing the Internet based on the second virtual teaching material attribute information to crawl out the corresponding teaching material data.

[0034] like Figure 2 As shown, based on the teaching plan items in the teaching plan information, the teaching plan information can be decomposed into several teaching sub-segments in chronological order, and then the corresponding teaching duration is obtained based on the teaching content evaluation corresponding to each teaching field, for example, the teaching duration of the buoyancy chapter is 20 minutes, and the teaching duration of the optics chapter is 25 minutes. Based on the teaching start time parsed from the teaching plan information, the estimated start time of each teaching sub-segment can be determined.

[0035] When the estimated start time is later than the teaching end time (also parsed from the teaching plan information), it means that the teaching content corresponding to the teaching sub-segment will not be displayed in time during the current teaching process (that is, the teaching plan specified by the teacher has some time deviations). At this time, the second virtual teaching material attribute information corresponding to the teaching sub-segment will be deleted, that is, the corresponding teaching material data will no longer be crawled from the Internet. This can reduce the communication and data processing load between the communication control device and the Internet.

[0036] It should be noted that the method for determining the estimated start time listed in this embodiment can be used for determining the first display start time mentioned above, for example, directly determining the estimated start time as the first display start time mentioned above.

[0037] In some embodiments, the putting each of the second virtual teaching materials into the teaching material pool includes: predicting the second expected display time of each of the second virtual teaching materials according to the real-time teaching progress and the remaining teaching time corresponding to each of the teaching sub-segments; if the second expected display time is later than the teaching end time, the second virtual teaching material will not be put into the teaching material pool.

[0038] The aforementioned embodiment is to choose not to obtain the teaching material data corresponding to some second virtual teaching materials that cannot be used this time through the above prediction of the teaching plan information before generating the second virtual teaching materials.

[0039] However, in this embodiment, after the teaching begins, the current teaching process is continuously analyzed in real time. According to the real-time teaching process and the teaching duration corresponding to the remaining teaching sub-segments, the second estimated display time of each second virtual teaching material that has been generated can be roughly determined. If the second estimated display time is later than the teaching end time of the teaching, there is no need to put the corresponding second virtual teaching material into the teaching material pool. Because it is impossible to complete all the teaching contents in the teaching plan information this time, it is useless to put all the second virtual teaching materials into the teaching material pool. Of course, some of the first virtual teaching materials previously put into the teaching material pool may not be used and can be deleted later. Such a setting can also reduce the data processing load of the communication control device and reduce the data volume of the teaching material pool. When the teaching material pool is shared by multiple teaching tasks, it can also reduce the time consumed by the communication control device to retrieve the corresponding virtual teaching materials in the teaching material pool, thereby improving the fluency and efficiency of metaverse teaching.

[0040] like Figure 3As shown, an embodiment of the present invention further discloses a teaching system based on generative AI and metaverse, which is applied to a communication control device built based on generative AI, and the system includes a receiving module, a matching analysis module, a material generating module, a material delivery module, and a display control module; the receiving module is used to obtain teaching plan information, and determine a number of virtual teaching material attribute information according to the teaching plan information; the matching analysis module is used to match and analyze each of the virtual teaching material attribute information with each of the first virtual teaching materials stored in the database, and obtain a number of first virtual teaching material attribute information that successfully matches and a number of second virtual teaching material attribute information that fails to match; the material A generation module is used to access the Internet based on the attribute information of each second virtual teaching material, crawl out the corresponding teaching material data, and convert the teaching material data into the second virtual teaching material in a format suitable for the Metaverse teaching system; the material delivery module is used to put each first virtual teaching material and each second virtual teaching material corresponding to several first virtual teaching material attribute information that are successfully matched into a teaching material pool; the display and control module is used to obtain the real-time teaching progress, and according to the real-time teaching progress, sequentially retrieve the adapted first virtual teaching material or the second virtual teaching material from the teaching material pool, and display them in the Metaverse teaching system.

[0041] An embodiment of the present invention further discloses an electronic device, comprising: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, characterized in that: the processor executes the computer program to implement the method described in the above embodiment.

[0042] An embodiment of the present invention further discloses a computer storage medium, wherein the computer storage medium stores a computer program, and is characterized in that: the computer program is executed by a processor to implement the method described in the above embodiment.

[0043] An embodiment of the present invention further discloses a computer program product, including a computer program stored on a non-transitory computer-readable medium, wherein the computer program implements any of the above methods when executed by a processor.

[0044] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0045] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0046] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0047] The above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention.

Claims

1. A teaching method based on generative AI and metaverse, applied to a communication control device built based on generative AI, characterized in that The method includes the following steps: obtaining teaching plan information, and determining a number of virtual teaching material attribute information based on the teaching plan information; matching and analyzing each of the virtual teaching material attribute information with each of the first virtual teaching materials stored in the database to obtain a number of first virtual teaching material attribute information that successfully matches and a number of second virtual teaching material attribute information that fails to match; accessing the Internet based on each of the second virtual teaching material attribute information, crawling out the corresponding teaching material data, and converting the teaching material data into the second virtual teaching material in a format that is adapted to the metaverse teaching system; putting each of the first virtual teaching materials and each of the second virtual teaching materials corresponding to the first virtual teaching material attribute information that successfully matches into a teaching material pool; obtaining the real-time teaching process, and sequentially retrieving the adapted first virtual teaching material or the second virtual teaching material from the teaching material pool according to the real-time teaching process, and displaying them in the metaverse teaching system.

2. A teaching method based on generative AI and metaverse according to claim 1, characterized in that: Acquiring teaching plan information includes: the communication control device receiving the teaching plan information manually entered by the teacher, and / or automatically acquiring the teaching plan information corresponding to the current time period from the teaching affairs system.

3. A teaching method based on generative AI and metaverse according to claim 1, characterized in that: Matching and analyzing the attribute information of each virtual teaching material with the first virtual teaching materials stored in the database, including: using the BERT model to perform semantic analysis on each of the first virtual teaching materials stored in the database to obtain corresponding teaching material semantic attribute information; performing semantic similarity analysis on the attribute information of each virtual teaching material and the semantic attribute information of each teaching material, if the semantic similarity is higher than the similarity threshold, it is determined that the corresponding attribute information of the virtual teaching material is matched successfully, otherwise, it is determined that the corresponding attribute information of the virtual teaching material is matched unsuccessfully.

4. A teaching method based on generative AI and metaverse according to claim 3, characterized in that: Based on each of the second virtual teaching material attribute information, the Internet is accessed to crawl and obtain the corresponding teaching material data, including: based on the teaching plan information, the first display start time corresponding to each of the second virtual teaching material attribute information is predicted, and the time difference between the current time and the first display start time is calculated; based on the time difference and the positive correlation function, the crawl quantity corresponding to each of the second virtual teaching material attribute information is calculated; according to each of the second virtual teaching material attribute information and the corresponding crawl quantity, the Internet is accessed to crawl and obtain the teaching material data.

5. A teaching method based on generative AI and metaverse according to claim 4, characterized in that: Before accessing the Internet based on each of the second virtual teaching material attribute information to crawl out the corresponding teaching material data, the method also includes: parsing the teaching plan information to obtain the teaching start time and the teaching end time; decomposing the teaching plan information into a number of teaching sub-segments in chronological order, obtaining the corresponding teaching duration based on the teaching content evaluation corresponding to each of the teaching sub-segments, and determining the expected start time of each of the teaching sub-segments based on the teaching start time and the teaching duration; if the expected start time is later than the teaching end time, deleting the second virtual teaching material attribute information corresponding to the teaching sub-segment, that is, no longer accessing the Internet based on the second virtual teaching material attribute information to crawl out the corresponding teaching material data.

6. A teaching method based on generative AI and metaverse according to claim 5, characterized in that: Putting each of the second virtual teaching materials into a teaching material pool includes: predicting the second expected display time of each of the second virtual teaching materials according to the real-time teaching progress and the remaining teaching time corresponding to each of the teaching sub-segments; if the second expected display time is later than the teaching end time, then the second virtual teaching material will not be put into the teaching material pool.

7. A teaching system based on generative AI and metaverse, applied to a communication control device built based on generative AI, the system comprising a receiving module, a matching analysis module, a data generation module, a data delivery module, and a display control module; characterized in that: The receiving module is used to obtain teaching plan information, and determine a number of virtual teaching material attribute information according to the teaching plan information; the matching analysis module is used to match and analyze each of the virtual teaching material attribute information with each of the first virtual teaching materials stored in the database, and obtain a number of first virtual teaching material attribute information that successfully matches and a number of second virtual teaching material attribute information that fails to match; the material generation module is used to access the Internet based on each of the second virtual teaching material attribute information, crawl out the corresponding teaching material data, and convert the teaching material data into the second virtual teaching material in a format that is suitable for the metaverse teaching system; the material delivery module is used to deliver each of the first virtual teaching materials and each of the second virtual teaching materials corresponding to the first virtual teaching material attribute information that successfully matches into the teaching material pool; The display control module is used to obtain the real-time teaching progress, and retrieve the adapted first virtual teaching material or the second virtual teaching material from the teaching material pool in sequence according to the real-time teaching progress, and display it in the metaverse teaching system.

8. An electronic device comprising: At least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor executes the computer program to implement the method according to any one of claims 1 to 6.

9. A computer storage medium storing a computer program, characterized in that: The computer program is executed by a processor to implement the method according to any one of claims 1 to 6.

10. A computer program product comprising a computer program stored on a non-transitory computer readable medium, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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