Immersive education method and system based on virtual reality technology, medium and equipment

Abstract

The invention relates to an immersive education method and system based on a virtual reality technology, a medium and equipment, and relates to the technical field of virtual reality, and the method comprises the steps: obtaining a target portrait and a learning task type of a target user; on the basis of at least one target learning resource under the learning task type and at least one corresponding target interaction node, determining a suitable learning resource matched with the target user from each target learning resource; determining a suitable interaction node in the suitable learning resource, and displaying the suitable learning resource to the target user through the VR device based on the suitable interaction node; and after the suitable learning resources are displayed, determining training task nodes matched with the target user from the learning task nodes of the suitable learning resources, and performing targeted training on the target user through the VR equipment based on the training task nodes. The effect of immersive education can be improved.

Description

Technical Field

[0001] The present application relates to the field of virtual reality technology, and in particular to an immersive education method, system, medium and equipment based on virtual reality technology. Background Art

[0002] Virtual Reality (VR) is a computer simulation system that can create and experience a virtual world. It uses computers to generate an environment that simulates reality and immerses users in it. Immersive education is a new learning and education model that helps learners understand and master knowledge more deeply and improve learning outcomes through a highly simulated and highly interactive learning environment. With the continuous advancement of virtual reality technology, VR has been widely used in many fields such as gaming entertainment, architectural design, and medical training. It has also begun to show great potential in the education industry. Traditional classroom learning and education are gradually being replaced by immersive education based on virtual reality.

[0003] At present, the existing immersive education usually adopts the following method: based on pre-recorded general learning video content and simple interactive design, VR devices are used to provide users with an immersive learning environment. However, different users have different needs for learning video content and interaction. The general learning video content and simple interactive design used in this method cannot meet the needs of different users well, resulting in poor results in immersive education. Summary of the invention

[0004] In order to improve the effect of immersive education, the present application provides an immersive education method, system, medium and equipment based on virtual reality technology.

[0005] In a first aspect of the present application, an immersive education method based on virtual reality technology is provided, which specifically includes: Obtaining a target profile and a learning task type of a target user, wherein the target user is a user wearing a VR device to learn; Based on at least one target learning resource under the learning task type and at least one corresponding target interaction node, determine a suitable learning resource matching the target user from each of the target learning resources, wherein the target learning resource is a learning resource that the historical users of the target portrait are easy to choose to learn, and the target interaction node is a learning task node that the historical users of the target portrait are easy to initiate interaction with when viewing the target learning resource, and the learning task node is a learning point introduced in the target learning resource; Determine a suitable interactive node in the suitable learning resource, and based on the suitable interactive node, display the suitable learning resource to the target user through the VR device, wherein the suitable interactive node is a learning task node in the suitable learning resource that is suitable for interacting with the target user; After the suitable learning resources are displayed, the training task nodes matching the target user are determined from the learning task nodes of the suitable learning resources, and based on the training task nodes, the target user is trained through the VR device.

[0006] By adopting the above technical solution, after obtaining the target user's target portrait and learning task type, based on the target learning resources and the corresponding target interaction nodes, the target user's likelihood of interest in each target learning resource is analyzed and determined, and then the appropriate learning resources adapted to the target user's needs are determined more accurately. Then, the learning task nodes suitable for the target user to interact with in the process of learning the appropriate learning resources are determined, and in combination with this suitable interaction node, the appropriate learning resources are displayed to the target user through the VR device, so that the target user can obtain an immersive learning atmosphere with strong interactivity and improve the learning effect. Finally, after the target user learns the appropriate learning resources, the VR device is used to provide the target user with simulation exercises for the training task nodes, further enhancing the target user's learning effect on the learning task type, thereby improving the effect of immersive education.

[0007] Optionally, the determining, based on at least one target learning resource under the learning task type and at least one corresponding target interaction node, a suitable learning resource matching the target user from each target learning resource specifically includes: Acquire historical learning resources selected for learning by historical users of the target profile under the learning task type, count the first occurrence times of each of the historical learning resources, and select a first number of historical learning resources from each of the historical learning resources in descending order of the first occurrence times to determine as target learning resources; Obtain historical interaction nodes of historical users of the target portrait initiating interactions when viewing a single target learning resource, count the second number of occurrences of each of the historical interaction nodes, and select a second number of historical interaction nodes from each of the historical interaction nodes in descending order of the second number of occurrences to determine as target interaction nodes of the corresponding target learning resource; Determine a first weight for each of the target learning resources, and determine a second weight for each of the target interactive nodes corresponding to each of the target learning resources, wherein the first weight is a ratio of a first occurrence number of each target learning resource to a sum of first occurrence numbers of all target learning resources, and the second weight is a ratio of a second occurrence number of a single target interactive node corresponding to a target learning resource to a sum of second occurrence numbers of all corresponding target interactive nodes; According to the first weight and the corresponding second weights, a suitable learning resource matching the target user is determined from the target learning resources.

[0008] By adopting the above technical solution, the larger the first occurrence number, the easier it is for the target profile user to choose the corresponding historical learning resource to watch and learn when learning the learning task type, and then determine the target learning resource; the larger the second occurrence number, the easier it is for the target profile user to interact at the corresponding historical interaction node when learning a single target learning resource, which means that the corresponding historical interaction node is more likely to arouse the interest of the target profile user, and then determine the target interaction node. Finally, combining the first weight and the corresponding second weight, analyze and determine the possibility of the target user's interest in each target learning resource, and then more accurately determine the appropriate learning resources that are adapted to the needs of the target user.

[0009] Optionally, determining a suitable learning resource matching the target user from the target learning resources according to the first weight and the corresponding second weights specifically includes: Calculate a first product of a first weight of each target learning resource and a second weight of each corresponding target interactive node; Summing each of the first products to obtain a sum of the first products of the corresponding target learning resources; A maximum sum of first products is selected from the sums of the first products, and a target learning resource corresponding to the maximum sum of first products is determined as a suitable learning resource matching the target user.

[0010] By adopting the above technical solution, the larger the first product is, the easier it is to initiate interaction at the corresponding target interaction node when learning the target learning resource. Then, the sum of the first products of the corresponding target learning resources is obtained. The larger the sum of the first products is, the more likely the user of the target profile is to initiate interaction in the learning of the corresponding target learning resource, and the easier it is to be interested in the corresponding target learning resource. Finally, the maximum sum of the first products is selected from the sums of the first products, and the target learning resource corresponding to the maximum sum of the first products, that is, the learning resource that the target user is most likely to be interested in, is determined as the appropriate learning resource matching the target user.

[0011] Optionally, the determining a suitable interactive node in the suitable learning resource specifically includes: Calculate a second product of the first weight of each target learning resource and the second weight of each corresponding target interactive node; Summing the second products corresponding to the same target interactive node to obtain the sum of the corresponding second products; Comparing the sum of the second products with a preset first threshold, and if the sum of the second products exceeds the first threshold, determining the corresponding target interaction node as the target user's to-be-interacted node; Determine a suitable interactive node in the suitable learning resource from each of the nodes to be interacted with.

[0012] By adopting the above technical solution, the larger the sum of the second products, the greater the possibility that the user of the target profile will initiate interaction at the corresponding target interaction node when learning the learning task type, and the more interested in the corresponding target interaction node. If the sum of the second products exceeds the first threshold, it means that the target user is more likely to be interested in the corresponding target interaction node, then the corresponding target interaction node is determined as the target user's to-be-interacted node. Subsequent interaction with the target user at the to-be-interacted node can achieve in-depth interaction with the part that the target user is interested in, making the learning experience and effect better.

[0013] Optionally, determining a suitable interactive node in the suitable learning resource from the nodes to be interacted with specifically includes: Obtaining historical virtual scenes in which errors occurred during simulation training of the historical user of the target portrait, counting the first occurrence frequency of each of the historical virtual scenes, and selecting a third number of historical virtual scenes from each of the historical virtual scenes in descending order of the first occurrence frequency to determine as target virtual scenes, wherein the historical virtual scenes are three-dimensional virtual scenes created for immersive learning of historical users by the VR device; Obtaining historical learning task nodes in which historical user training errors occurred for the target portrait in a single target virtual scene, counting the second occurrence frequency of each of the historical learning task nodes, and selecting a fourth number of historical learning task nodes from each of the historical learning task nodes in descending order of the second occurrence frequency to determine as target nodes of the corresponding target virtual scene; Determine a third weight of each of the target virtual scenes, and determine a fourth weight of each of the target nodes corresponding to each of the target virtual scenes, wherein the third weight is a ratio of a first occurrence frequency of each target virtual scene to a sum of first occurrence frequencies of all target virtual scenes, and the fourth weight is a ratio of a second occurrence frequency of a single target node corresponding to the target virtual scene to a sum of second occurrence frequencies of all corresponding target nodes; Based on the third weight and the corresponding fourth weights, a suitable interactive node in the suitable learning resource is determined from the nodes to be interacted with.

[0014] By adopting the above technical solution, the greater the first occurrence frequency, the more likely the target profile user is to make mistakes when simulating practice in the corresponding historical virtual scene, and thus the target virtual scene is determined; the greater the second occurrence frequency, the more likely the user is to make mistakes in the practice of the corresponding historical learning task node when simulating training in the target virtual scene, and thus the target node is determined. Finally, combined with the third weight and the corresponding fourth weight, the probability of error in the practice of each node to be interacted with for the target user is analyzed, and then the appropriate interaction node is determined more accurately.

[0015] Optionally, the determining, based on the third weight and the corresponding fourth weights, a suitable interactive node in the suitable learning resource from the nodes to be interacted with specifically includes: Calculating a third product of a third weight of each of the target virtual scenes and a fourth weight of each of the corresponding target nodes; Summing the third products corresponding to the same target node to obtain a sum of the corresponding third products; If the sum of the third products exceeds a preset second threshold, the corresponding target node is determined as a reference interactive node, and each reference interactive node is intersected with each to-be-interacted node to obtain a suitable interactive node in the suitable learning resource.

[0016] By adopting the above technical solution, the larger the sum of the third products is, the more likely it is that the target user will make mistakes in the corresponding target node when performing simulation exercises through the VR device after watching and learning the appropriate learning resources. If the sum of the third products exceeds the preset second threshold, it means that the target user is more likely to make mistakes in the practice of the corresponding target node, and then determine the reference interaction node. Finally, each reference interaction node and each node to be interacted with are intersected to obtain the appropriate interaction node in the process of the target user learning this appropriate learning resource. Interacting with the target user at this appropriate interaction node can not only enhance the target user's learning effect on the part of interest, but also reduce the risk of errors in subsequent simulation exercises.

[0017] Optionally, determining the training task node matching the target user from the learning task nodes of the suitable learning resources specifically includes: Determining a suitable interactive node among each learning task node of the suitable learning resource as a training task node matched to the target user; Based on each of the training task nodes, performing targeted training on the target user through the VR device specifically includes: If there is at least one training task node in each target node corresponding to the target virtual scene, the corresponding target virtual scene is determined as a key virtual scene; Calculating a fourth product of the third weight of each of the key virtual scenes and the fourth weight of each corresponding training task node, and summing each of the fourth products to obtain a corresponding sum of the fourth products; Selecting a maximum sum of the fourth products from the sums of the fourth products, determining a key virtual scene corresponding to the maximum sum of the fourth products as a training virtual scene for the target user, and setting the three-dimensional virtual scene in the VR device as the training virtual scene; The sum of the second product and the sum of the third product corresponding to each of the training task nodes are summed to obtain a sum result, and the training order of the corresponding training task nodes is determined according to the sum result, and the larger the sum result, the earlier the training order; According to each of the training sequences, the target user is trained on the corresponding training task nodes through the VR device.

[0018] By adopting the above technical solution, the larger the sum of the fourth products, the greater the possibility that the target user will make mistakes during the simulation practice in the corresponding key virtual scene, and the higher the necessity of the practice. Finally, the key virtual scene corresponding to the maximum sum of the fourth products is determined as the training virtual scene for the target user's simulation practice. Performing simulation practice in this training virtual scene can better improve the effect of the target user's simulation practice. Furthermore, the larger the sum result, the greater the possibility that the target user is interested in and / or makes mistakes during practice for the corresponding training task node, the higher the training order of the corresponding training task node, and the higher the priority of training, which helps to improve the effect of the simulation practice and the learning effect of the learning task type.

[0019] In a second aspect of the present application, an immersive education system based on virtual reality technology is provided, which specifically includes: An information acquisition module, used to acquire a target profile and a learning task type of a target user, wherein the target user is a user wearing a VR device to learn; A resource matching module, for determining, from each of the target learning resources, a suitable learning resource that matches the target user based on at least one target learning resource under the learning task type and at least one corresponding target interactive node, wherein the target learning resource is a learning resource that the historical users of the target profile can easily select for learning, the target interactive node is a learning task node that the historical users of the target profile can easily initiate interaction with when viewing the target learning resource, and the learning task node is a learning point introduced in the target learning resource; A resource display module, used to determine a suitable interactive node in the suitable learning resource, and based on the suitable interactive node, display the suitable learning resource to the target user through the VR device, wherein the suitable interactive node is a learning task node in the suitable learning resource that is suitable for interacting with the target user; The simulation training module is used to determine the training task node matching the target user from each learning task node of the suitable learning resource after the suitable learning resource is displayed, and to perform targeted training on the target user through the VR device based on each training task node.

[0020] By adopting the above technical solution, the information acquisition module obtains the target user's target portrait and learning task type. Then the resource matching module determines the appropriate learning resources that match the target user from various target learning resources. Then, the resource display module displays the appropriate learning resources to the target user through VR devices based on appropriate interactive nodes. Finally, the simulation training module determines the training task nodes, and conducts targeted training for the target user through VR devices according to each training task node.

[0021] In a third aspect of the present application, a computer-readable storage medium is provided, in which a computer program is stored. When the computer program is loaded and executed by a processor, the method steps described in any one of the first aspects are performed.

[0022] In a fourth aspect of the present application, an electronic device is provided, specifically comprising: A processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the processor is used to load and execute the computer program stored in the memory so that the electronic device performs the method as described in any one of the first aspects.

[0023] In summary, the present application includes at least one of the following beneficial technical effects: Based on the target learning resources and the corresponding target interactive nodes, the target user is analyzed to determine the possibility of being interested in each target learning resource, and then the appropriate learning resources adapted to the needs of the target user are determined more accurately. Then, the learning task nodes suitable for the target user to interact with in the process of learning the appropriate learning resources are determined, and in combination with this suitable interactive node, the appropriate learning resources are displayed to the target user through the VR device, so that the target user can obtain an immersive learning atmosphere with strong interactivity and improve the learning effect. Finally, after the target user learns the appropriate learning resources, the VR device provides the target user with simulation exercises for the training task nodes, further enhancing the target user's learning effect on the learning task type, thereby improving the effect of immersive education. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a flowchart of an immersive education method based on virtual reality technology provided in an embodiment of the present application; Figure 2 It is a structural diagram of an immersive education system based on virtual reality technology provided in an embodiment of the present application.

[0025] Explanation of the accompanying drawings: 11. Information acquisition module; 12. Resource matching module; 13. Resource display module; 14. Simulation training module. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0027] In the description of the embodiments of the present application, words such as "illustrative", "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "illustrative", "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "illustrative", "for example" or "for example" is intended to present related concepts in a concrete way.

[0028] In the description of the embodiments of the present application, the term "and / or" is only a kind of association relationship describing the associated objects, indicating that there may be three kinds of relationships, for example, A and / or B, which can represent: A exists alone, B exists alone, and A and B exist at the same time. In addition, unless otherwise specified, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" can explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0029] See also Figure 1 The embodiment of the present application discloses a flowchart of an immersive education method based on virtual reality technology, which can be implemented by a computer program or run on an immersive education system based on virtual reality technology based on the von Neumann system. The computer program can be integrated into an application or run as an independent tool application, specifically including: S101: Obtain the target profile and learning task type of the target user.

[0030] Specifically, in an embodiment of the present application, the target user is a user who wears a VR device for immersive learning. The target user may be a user who studies in a vocational training scenario. In other embodiments, the target user may also be a user who studies in a school education scenario. The learning task type is the type of content that the target user learns through the VR device. The target portrait is a user portrait of the target user, that is, a representative user model abstracted based on various feature information such as the user's interests, hobbies, age, etc. Exemplarily, if the target user is a user who undergoes vocational training as a chef, then the corresponding learning task type is a type related to culinary learning. If the target user is a user who studies in a school education scenario, then the corresponding learning task type may be a geography learning type. Among them, the VR device may be a VR pair of glasses or a head-mounted VR device.

[0031] Furthermore, the executor of an immersive education method of virtual reality technology disclosed in an embodiment of the present application may be a server, and the server is wirelessly connected to a VR device. A client related to immersive education is installed in the VR device, and the server may be a background server of the client, specifically an independent physical server or a server cluster composed of multiple physical servers. In other embodiments, the executor of an immersive education method of virtual reality technology may also be the VR device itself. Furthermore, a feasible way to obtain a target portrait of a target user is to obtain the registration information of the target user in the client with the authorization and consent of the target user, and the registration information includes but is not limited to occupation, age, interests, hobbies, gender and other information. This registration information is input into a preset portrait prediction model to obtain the corresponding target portrait. The portrait prediction model may be a decision tree model, and in other embodiments, it may also be a recurrent neural network model.

[0032] S102: Based on at least one target learning resource under the learning task type and at least one corresponding target interaction node, determine a suitable learning resource matching the target user from each target learning resource.

[0033] Specifically, the target learning resource is a learning resource that the historical users of the target portrait can easily choose to learn, the target interactive node is a learning task node that the historical users of the target portrait can easily initiate interaction with when watching the target learning resource, and the learning task node is the learning point introduced in the target learning resource. In an embodiment of the present application, the learning resource is a VR learning video that matches this learning task type. Among them, VR video is a video in a special format played in a VR device, which provides an immersive experience for users by simulating a real environment. Exemplarily, if the learning task type is a cooking learning type, then the corresponding learning resource is a cooking learning video, and the learning task nodes included in the learning resource can be a knife learning part, a seasoning learning part, or a cooking skills learning part.

[0034] Further, the historical learning resources selected for learning by the historical user of the target portrait under this learning task type are obtained, and the first occurrence number of each historical learning resource is counted. The larger the first occurrence number, the easier it is for the user of the target portrait to choose the corresponding historical learning resource for viewing and learning when learning the learning task type, and the first number of historical learning resources are selected from each historical learning resource in the order of the first occurrence number from large to small to determine the target learning resource, wherein the historical user is the user who is learning the learning task type. Next, the historical interaction nodes where the historical user of the target portrait has initiated interaction when watching and learning the target learning resource are obtained, and the second occurrence number of each historical interaction node is counted. The larger the second occurrence number, the easier it is for the user of the target portrait to interact in the corresponding historical interaction node when learning a single target learning resource, indicating that the corresponding historical interaction node is more likely to arouse the interest of the user of the target portrait, and then the second number of historical interaction nodes are selected from each historical interaction node in the order of the second occurrence number from large to small to determine the target interaction node corresponding to the target learning resource. It should be noted that in the embodiment of the present application, when the user watches the learning resource, the way to initiate interaction can be to send comments or questions of interest, etc.

[0035] Further, the first weight of each target learning resource is determined, the first weight is the ratio of the first occurrence of each target learning resource to the sum of the first occurrences of all target learning resources, and then the second weight of each target interactive node corresponding to each target learning resource is determined, the second weight is the ratio of the second occurrence of a single target interactive node corresponding to the target learning resource to the sum of the second occurrences of all corresponding target interactive nodes. Then, based on the first weight and the corresponding second weights, the appropriate learning resource that is more matched with this target user is determined from each target learning resource. A feasible determination method is: calculate the first product of the first weight of each target learning resource and the second weight of the corresponding target interactive node. The larger the first product, the easier it is to initiate interaction at the corresponding target interactive node when learning the target learning resource. Then, sum the first products to obtain the sum of the first products of the corresponding target learning resources. The larger the sum of the first products, the greater the possibility that the user of the target profile initiates interaction in the learning of the corresponding target learning resource, and the easier it is to be interested in the corresponding target learning resource. Finally, the maximum sum of first products is selected from the sums of the first products, and the target learning resource corresponding to the maximum sum of first products, that is, the learning resource that the target user is most likely to be interested in, is determined as the appropriate learning resource matching the target user.

[0036] S103: Determine appropriate interactive nodes in appropriate learning resources, and based on the appropriate interactive nodes, display appropriate learning resources to target users through VR devices.

[0037] Specifically, after the appropriate learning resources are determined, the appropriate learning resources are played through the VR device worn by the target user, thereby providing the target user with a personalized and immersive learning experience. In addition, in order to enhance the interactivity of the target user when watching and learning the appropriate learning resources, it is necessary to determine the appropriate interactive nodes that are suitable for the target user to interact with during the viewing of the appropriate learning resources, that is, the learning task nodes in the appropriate learning resources that are suitable for interacting with the target user. In the embodiment of the present application, a feasible determination method is: calculate the second product of the first weight of each target learning resource and the second weight of each corresponding target interactive node, and sum the second products corresponding to the same target interactive node to obtain the sum of the second products of the corresponding target interactive nodes. The larger the sum of the second products, the greater the possibility that the user of the target portrait initiates interaction at the corresponding target interactive node when learning the learning task type, and the more interested in the corresponding target interactive node.

[0038] Further, the sum of each second product is compared with a preset first threshold value. If the sum of the second products exceeds the first threshold value, it means that the target user of the corresponding target interactive node is more likely to be interested, and then the corresponding target interactive node is determined as the target user's corresponding node to be interacted. Among them, by interacting with the target user at the node to be interacted, in-depth interaction with the part of interest to the target user can be achieved, so that the learning experience and effect are better. Finally, a suitable interactive node for interacting with the target user in the appropriate learning resource is determined from each node to be interacted. A feasible determination method is: retrieve the error statistics record of targeted historical simulation training through VR equipment from the database, and the error statistics record includes but is not limited to the virtual scene and learning task node of the training error when the historical users of different portraits after learning the learning resources are simulated. Exemplarily, after the user has learned the learning resources related to cooking, a virtual kitchen scene is provided for him through the VR device, and the user can perform simulation exercises related to knife skills in the kitchen scene, that is, simulation training, so as to enhance the learning effect. Based on the above error statistics, obtain the historical virtual scenes where errors occurred during the historical user simulation training of the target portrait, count the first occurrence frequency of each historical virtual scene, and select a third number of historical virtual scenes from each historical virtual scene in order of the first occurrence frequency from large to small to determine as the target virtual scene, that is, the virtual scene where the target user is prone to make mistakes. Further, obtain the historical learning task nodes where the historical user training of the target portrait made mistakes in a single target virtual scene, count the second occurrence frequency of each historical learning task node, and select a fourth number of historical learning task nodes from each historical learning task node in order of the second occurrence frequency from large to small to determine as the target node corresponding to the single target virtual scene, that is, the learning task nodes where the user of the target portrait is prone to make mistakes when practicing in the target virtual scene.

[0039] Determine a third weight for each target virtual scene, the third weight being the ratio of the first occurrence frequency of each target virtual scene to the sum of the first occurrence frequencies of all target virtual scenes. Then determine a fourth weight for each target node corresponding to each target virtual scene, the fourth weight being the ratio of the second occurrence frequency of a single target node corresponding to the target virtual scene to the sum of the second occurrence frequencies of all corresponding target nodes.

[0040] Further, the third product of the third weight of each target virtual scene and the fourth weight of each corresponding target node is calculated. The larger the third product is, the easier it is for the target user to make mistakes in the practice of the corresponding target node in the target virtual scene. Then, the third products corresponding to the same target node are summed to obtain the sum of the third products of the corresponding target node. The larger the sum of the third products is, the easier it is for the target user to make mistakes in the corresponding target node when performing simulation exercises through the VR device after watching and learning the appropriate learning resources. Finally, if the sum of the third products exceeds the preset second threshold, it means that the target user is more likely to make mistakes in the practice of the corresponding target node, then the corresponding target node is determined as a reference interaction node, and each reference interaction node and each to-be-interacted node are intersected to obtain the appropriate interaction node in the process of the target user learning this appropriate learning resource, and the corresponding interaction questions are set in each appropriate interaction node. Interacting with the target user at this appropriate interaction node can not only enhance the learning effect of the target user for the part of interest, but also reduce the risk of errors in subsequent simulation exercises. For example, suitable learning resources related to cooking learning include learning task nodes such as knife skills and seasoning. If the suitable interactive node is knife skills, then when watching the part introducing knife skills in the suitable learning resources, interact with the target user according to preset interactive questions.

[0041] S104: After the appropriate learning resources are displayed, a training task node matching the target user is determined from each learning task node of the appropriate learning resources, and based on each training task node, targeted training is performed on the target user through a VR device.

[0042] Specifically, after the target user immerses himself in learning appropriate learning resources through VR equipment, he needs to perform simulation exercises after learning. Then, the training task node matched by the target user is determined from each learning task node of the appropriate learning resource, that is, the learning task node for the simulation exercise. In the embodiment of the present application, a feasible determination method is: directly determine the above-mentioned appropriate interactive node as the training task node. Then, if there is at least one training task node in each target node corresponding to the target virtual scene, the corresponding target virtual scene is determined as the key virtual scene. Calculate the fourth product of the third weight of each key virtual scene and the fourth weight of each corresponding training task node, and then sum each fourth product to obtain the sum of the fourth products of the corresponding key virtual scene. The larger the sum of the fourth products, the greater the possibility that the target user will make mistakes in the simulation exercise in the corresponding key virtual scene, and the higher the degree of necessity for the exercise, then select the maximum sum of the fourth products from the sum of each fourth product, and determine the key virtual scene corresponding to the maximum sum of the fourth products as the training virtual scene for the target user's simulation exercise, and set the three-dimensional virtual scene provided to the target user by this VR device as the training virtual scene. Conducting simulation exercises in this training virtual scenario can better improve the effect of simulation exercises for target users.

[0043] Furthermore, the sum of the second product and the sum of the third product corresponding to each training task node are summed to obtain a sum result. The larger the sum result, the greater the probability that the target user is interested in the corresponding training task node and / or makes mistakes during practice. Then, according to the sum result, the training order of the corresponding training task node in the training virtual scene is determined. The larger the sum result, the higher the training order of the corresponding training task node, and the higher the priority for training. Finally, according to each training order, the corresponding training task node is trained for the target user through the VR device, which helps to improve the effect of the simulation exercise and the learning effect of the learning task type.

[0044] The implementation principle of the immersive education method based on virtual reality technology in the embodiment of the present application is: based on the target learning resources and the corresponding target interactive nodes, analyze and determine the possibility of the target user's interest in each target learning resource, and then more accurately determine the appropriate learning resources that are adapted to the needs of the target user. Then determine the learning task nodes that are suitable for the target user to interact with in the process of learning the appropriate learning resources, and combine this suitable interactive node to display the appropriate learning resources to the target user through the VR device, so that the target user can obtain an immersive learning atmosphere with strong interactivity and improve the learning effect. Finally, after the target user learns the appropriate learning resources, the VR device provides the target user with simulation exercises for the training task nodes, further enhancing the target user's learning effect on the learning task type, thereby improving the effect of immersive education.

[0045] The following is a system embodiment of the present application, which can be used to execute the method embodiment of the present application. For details not disclosed in the system embodiment of the present application, please refer to the method embodiment of the present application.

[0046] See also Figure 2 , which is a schematic diagram of the structure of an immersive education system based on virtual reality technology provided in an embodiment of the present application. The immersive education system based on virtual reality technology can be implemented as all or part of the system through software, hardware or a combination of both. The system includes an information acquisition module 11, a resource matching module 12, a resource display module 13 and a simulation training module 14.

[0047] The information acquisition module 11 is used to obtain the target profile and learning task type of the target user, where the target user is a user wearing a VR device to learn; A resource matching module 12 is used to determine a suitable learning resource that matches a target user from each target learning resource based on at least one target learning resource under a learning task type and at least one corresponding target interaction node, wherein the target learning resource is a learning resource that a historical user of the target profile can easily select for learning, the target interaction node is a learning task node that a historical user of the target profile can easily initiate interaction with when viewing the target learning resource, and the learning task node is a learning point introduced in the target learning resource; The resource display module 13 is used to determine suitable interactive nodes in suitable learning resources, and based on the suitable interactive nodes, display the suitable learning resources to the target user through the VR device, where the suitable interactive nodes are learning task nodes in the suitable learning resources that are suitable for interaction with the target user; The simulation training module 14 is used to determine the training task nodes matching the target user from the learning task nodes of the suitable learning resources after the suitable learning resources are displayed, and to perform targeted training on the target user through the VR device based on the training task nodes.

[0048] Optionally, the resource matching module 12 is specifically used for: Obtain historical learning resources selected for learning by historical users of the target profile under the learning task type, count the first occurrence times of each historical learning resource, and select the first number of historical learning resources from each historical learning resource in descending order of the first occurrence times to determine as target learning resources; Obtain historical interaction nodes of historical users of the target profile initiating interactions when viewing a single target learning resource, count the second occurrence times of each historical interaction node, and select a second number of historical interaction nodes from each historical interaction node in descending order of the second occurrence times to determine as target interaction nodes of the corresponding target learning resource; Determine a first weight for each target learning resource, and determine a second weight for each target interactive node corresponding to each target learning resource, the first weight being the ratio of the first number of occurrences of each target learning resource to the sum of the first number of occurrences of all target learning resources, and the second weight being the ratio of the second number of occurrences of a single target interactive node corresponding to the target learning resource to the sum of the second number of occurrences of all corresponding target interactive nodes; According to the first weight and the corresponding second weights, a suitable learning resource matching the target user is determined from the target learning resources.

[0049] Optionally, the resource matching module 12 is specifically used for: Calculate a first product of a first weight of each target learning resource and a second weight of each corresponding target interactive node; Sum each first product to obtain the sum of the first products of the corresponding target learning resources; A maximum sum of first products is selected from the sums of the first products, and a target learning resource corresponding to the maximum sum of first products is determined as a suitable learning resource matching the target user.

[0050] Optionally, the resource display module 13 is specifically used for: Calculate the second product of the first weight of each target learning resource and the second weight of each corresponding target interactive node; The second products corresponding to the same target interaction node are summed to obtain the sum of the corresponding second products; The sum of the second products is compared with a preset first threshold value, and if the sum of the second products exceeds the first threshold value, the corresponding target interaction node is determined as the target user's to-be-interacted node; Determine a suitable interactive node in a suitable learning resource from each node to be interacted with.

[0051] Optionally, the resource display module 13 is specifically used for: Obtain historical virtual scenes in which errors occurred during simulation training of historical users of the target portrait, count the first occurrence frequency of each historical virtual scene, and select a third number of historical virtual scenes from each historical virtual scene in descending order of the first occurrence frequency to determine as target virtual scenes, where the historical virtual scenes are three-dimensional virtual scenes created for immersive learning of historical users through VR devices; Obtaining historical learning task nodes in which historical user training errors occurred for target portraits in a single target virtual scene, counting the second occurrence frequency of each historical learning task node, and selecting a fourth number of historical learning task nodes from each historical learning task node in descending order of the second occurrence frequency to determine as target nodes of the corresponding target virtual scene; Determine a third weight of each target virtual scene, and determine a fourth weight of each target node corresponding to each target virtual scene, the third weight being a ratio of a first occurrence frequency of each target virtual scene to a sum of first occurrence frequencies of all target virtual scenes, and the fourth weight being a ratio of a second occurrence frequency of a single target node corresponding to the target virtual scene to a sum of second occurrence frequencies of all corresponding target nodes; Based on the third weight and the corresponding fourth weights, a suitable interactive node in the suitable learning resource is determined from the nodes to be interacted with.

[0052] Optionally, the resource display module 13 is specifically used for: Calculating a third product of a third weight of each target virtual scene and a fourth weight of each corresponding target node; The third products corresponding to the same target node are summed to obtain the sum of the corresponding third products; If the sum of the third products exceeds a preset second threshold, the corresponding target node is determined as a reference interaction node, and each reference interaction node is intersected with each to-be-interacted node to obtain a suitable interaction node in the suitable learning resource.

[0053] Optionally, the simulation training module 14 is specifically used for: Determine the appropriate interactive node among each learning task node of the appropriate learning resource as the training task node matched with the target user; If there is at least one training task node in each target node corresponding to the target virtual scene, the corresponding target virtual scene is determined as the key virtual scene; Calculate the fourth product of the third weight of each key virtual scene and the fourth weight of each corresponding training task node, and sum each fourth product to obtain the corresponding sum of the fourth products; Selecting a maximum sum of the fourth products from the sums of the fourth products, determining a key virtual scene corresponding to the maximum sum of the fourth products as a training virtual scene for the target user, and setting the three-dimensional virtual scene in the VR device as the training virtual scene; The sum of the second product and the sum of the third product corresponding to each training task node are summed to obtain a sum result, and the training order of the corresponding training task node is determined according to the sum result. The larger the sum result, the earlier the training order; According to each training sequence, the target user is trained on the corresponding training task nodes through VR equipment.

[0054] It should be noted that the immersive education system based on virtual reality technology provided in the above embodiment only uses the division of the above functional modules as an example when executing the immersive education method based on virtual reality technology. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the immersive education system based on virtual reality technology provided in the above embodiment and the immersive education method embodiment based on virtual reality technology belong to the same concept. The implementation process is detailed in the method embodiment, which will not be repeated here.

[0055] An embodiment of the present application further discloses a computer-readable storage medium, and the computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, an immersive education method based on virtual reality technology of the above embodiment is adopted.

[0056] Among them, the computer program can be stored in a computer-readable medium, the computer program includes computer program code, the computer program code can be in the form of source code, object code, executable file or certain middleware, etc. The computer-readable medium includes any entity or device that can carry the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the computer-readable medium includes but is not limited to the above-mentioned components.

[0057] Among them, through this computer-readable storage medium, an immersive education method based on virtual reality technology in the above embodiment is stored in a computer-readable storage medium, and is loaded and executed on a processor to facilitate the storage and application of the above method.

[0058] An embodiment of the present application further discloses an electronic device, wherein a computer program is stored in a computer-readable storage medium, and when the computer program is loaded and executed by a processor, the above-mentioned immersive education method based on virtual reality technology is adopted.

[0059] The electronic device may be a desktop computer, a laptop computer, a cloud server or other electronic device, and the electronic device includes but is not limited to a processor and a memory. For example, the electronic device may also include input and output devices, a network access device, and a bus.

[0060] Among them, the processor can adopt a central processing unit (CPU). Of course, according to actual usage, other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. can also be adopted. The general-purpose processor can adopt a microprocessor or any conventional processor, etc., and this application does not impose any restrictions on this.

[0061] Among them, the memory can be an internal storage unit of the electronic device, such as a hard disk or memory of the electronic device, or it can be an external storage device of the electronic device, such as a plug-in hard disk, a smart memory card (SMC), a secure digital card (SD) or a flash memory card (FC) equipped on the electronic device. Moreover, the memory can also be a combination of an internal storage unit and an external storage device of the electronic device. The memory is used to store computer programs and other programs and data required by the electronic device. The memory can also be used to temporarily store data that has been output or is to be output, and this application does not impose any restrictions on this.

[0062] Among them, through this electronic device, an immersive education method based on virtual reality technology in the above embodiment is stored in the memory of the electronic device, and is loaded and executed on the processor of the electronic device for easy use.

[0063] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. This application is intended to cover any variation, use or adaptive change of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field that are not recorded in the present disclosure. The description and examples are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. An immersive education method based on virtual reality technology, characterized in that: The method comprises: Obtaining a target profile and a learning task type of a target user, wherein the target user is a user wearing a VR device to learn; Based on at least one target learning resource under the learning task type and at least one corresponding target interaction node, determine a suitable learning resource matching the target user from each of the target learning resources, wherein the target learning resource is a learning resource that the historical users of the target portrait are easy to choose to learn, and the target interaction node is a learning task node that the historical users of the target portrait are easy to initiate interaction with when viewing the target learning resource, and the learning task node is a learning point introduced in the target learning resource; Determine a suitable interactive node in the suitable learning resource, and based on the suitable interactive node, display the suitable learning resource to the target user through the VR device, wherein the suitable interactive node is a learning task node in the suitable learning resource that is suitable for interacting with the target user; After the suitable learning resources are displayed, the training task nodes matching the target user are determined from the learning task nodes of the suitable learning resources, and based on the training task nodes, the target user is trained through the VR device.

2. The immersive education method based on virtual reality technology according to claim 1 is characterized in that: The determining, based on at least one target learning resource under the learning task type and at least one corresponding target interaction node, a suitable learning resource matching the target user from each target learning resource specifically includes: Acquire historical learning resources selected for learning by historical users of the target profile under the learning task type, count the first occurrence times of each of the historical learning resources, and select a first number of historical learning resources from each of the historical learning resources in descending order of the first occurrence times to determine as target learning resources; Obtain historical interaction nodes of historical users of the target portrait initiating interactions when viewing a single target learning resource, count the second number of occurrences of each of the historical interaction nodes, and select a second number of historical interaction nodes from each of the historical interaction nodes in descending order of the second number of occurrences to determine as target interaction nodes of the corresponding target learning resource; Determine a first weight for each of the target learning resources, and determine a second weight for each of the target interactive nodes corresponding to each of the target learning resources, wherein the first weight is a ratio of a first occurrence number of each target learning resource to a sum of first occurrence numbers of all target learning resources, and the second weight is a ratio of a second occurrence number of a single target interactive node corresponding to a target learning resource to a sum of second occurrence numbers of all corresponding target interactive nodes; According to the first weight and the corresponding second weights, a suitable learning resource matching the target user is determined from the target learning resources.

3. The immersive education method based on virtual reality technology according to claim 2 is characterized in that: The determining, according to the first weight and the corresponding second weights, a suitable learning resource matching the target user from the target learning resources specifically includes: Calculate a first product of a first weight of each of the target learning resources and a second weight of each of the corresponding target interactive nodes; Summing each of the first products to obtain a sum of the first products of the corresponding target learning resources; A maximum sum of first products is selected from the sums of the first products, and a target learning resource corresponding to the maximum sum of first products is determined as a suitable learning resource matching the target user.

4. The immersive education method based on virtual reality technology according to claim 2 is characterized in that: The determining of the appropriate interactive node in the appropriate learning resource specifically includes: Calculate a second product of the first weight of each target learning resource and the second weight of each corresponding target interactive node; Summing the second products corresponding to the same target interactive node to obtain the sum of the corresponding second products; Comparing the sum of the second products with a preset first threshold, and if the sum of the second products exceeds the first threshold, determining the corresponding target interaction node as the target user's to-be-interacted node; Determine a suitable interactive node in the suitable learning resource from each of the nodes to be interacted with.

5. The immersive education method based on virtual reality technology according to claim 4 is characterized in that: The determining of a suitable interactive node in the suitable learning resource from each of the nodes to be interacted with specifically includes: Obtaining historical virtual scenes in which errors occurred during simulation training of the historical user of the target portrait, counting the first occurrence frequency of each of the historical virtual scenes, and selecting a third number of historical virtual scenes from each of the historical virtual scenes in descending order of the first occurrence frequency to determine as target virtual scenes, wherein the historical virtual scenes are three-dimensional virtual scenes created for immersive learning of historical users by the VR device; Obtaining historical learning task nodes in which historical user training errors occurred for the target portrait in a single target virtual scene, counting the second occurrence frequency of each of the historical learning task nodes, and selecting a fourth number of historical learning task nodes from each of the historical learning task nodes in descending order of the second occurrence frequency to determine as target nodes of the corresponding target virtual scene; Determine a third weight of each of the target virtual scenes, and determine a fourth weight of each of the target nodes corresponding to each of the target virtual scenes, wherein the third weight is a ratio of a first occurrence frequency of each target virtual scene to a sum of first occurrence frequencies of all target virtual scenes, and the fourth weight is a ratio of a second occurrence frequency of a single target node corresponding to the target virtual scene to a sum of second occurrence frequencies of all corresponding target nodes; Based on the third weight and the corresponding fourth weights, a suitable interactive node in the suitable learning resource is determined from the nodes to be interacted with.

6. The immersive education method based on virtual reality technology according to claim 5 is characterized in that: The determining, based on the third weight and the corresponding fourth weights, a suitable interactive node in the suitable learning resource from the nodes to be interacted with specifically includes: Calculating a third product of a third weight of each of the target virtual scenes and a fourth weight of each of the corresponding target nodes; Summing the third products corresponding to the same target node to obtain a sum of the corresponding third products; If the sum of the third products exceeds a preset second threshold, the corresponding target node is determined as a reference interactive node, and each reference interactive node is intersected with each to-be-interacted node to obtain a suitable interactive node in the suitable learning resource.

7. The immersive education method based on virtual reality technology according to claim 6 is characterized in that: The determining of the training task node matched with the target user from the learning task nodes of the suitable learning resources specifically includes: Determining a suitable interactive node among each learning task node of the suitable learning resource as a training task node matched to the target user; Based on each of the training task nodes, performing targeted training on the target user through the VR device specifically includes: If there is at least one training task node in each target node corresponding to the target virtual scene, the corresponding target virtual scene is determined as a key virtual scene; Calculating a fourth product of the third weight of each of the key virtual scenes and the fourth weight of each corresponding training task node, and summing each of the fourth products to obtain a corresponding sum of the fourth products; Selecting a maximum sum of the fourth products from the sums of the fourth products, determining a key virtual scene corresponding to the maximum sum of the fourth products as a training virtual scene for the target user, and setting the three-dimensional virtual scene in the VR device as the training virtual scene; The sum of the second product and the sum of the third product corresponding to each of the training task nodes are summed to obtain a sum result, and the training order of the corresponding training task nodes is determined according to the sum result, and the larger the sum result, the earlier the training order; According to each of the training sequences, the target user is trained on the corresponding training task nodes through the VR device.

8. An immersive education system based on virtual reality technology, characterized in that: include: An information acquisition module (11) is used to acquire a target profile and a learning task type of a target user, wherein the target user is a user wearing a VR device to study; A resource matching module (12) is used to determine, based on at least one target learning resource under the learning task type and at least one corresponding target interaction node, a suitable learning resource matching the target user from each target learning resource, wherein the target learning resource is a learning resource that the historical user of the target profile can easily select for learning, the target interaction node is a learning task node that the historical user of the target profile can easily initiate interaction with when viewing the target learning resource, and the learning task node is a learning point introduced in the target learning resource; A resource display module (13), used for determining a suitable interactive node in the suitable learning resource, and based on the suitable interactive node, displaying the suitable learning resource to the target user through the VR device, wherein the suitable interactive node is a learning task node in the suitable learning resource that is suitable for interacting with the target user; A simulation training module (14) is used to determine, after the suitable learning resource is displayed, a training task node matching the target user from each learning task node of the suitable learning resource, and to perform targeted training on the target user through the VR device based on each training task node.

9. A computer-readable storage medium having a computer program stored therein, characterized in that: When the computer program is loaded and executed by a processor, the method according to any one of claims 1 to 7 is adopted.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that: When the processor loads and executes the computer program, the method according to any one of claims 1 to 7 is adopted.

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