Virtual reality-based immersive theory communication method for mass cultural activities

Abstract

The application discloses a kind of based on virtual reality mass culture activity immersive theory transmission method. Including the following steps: S1 constructs virtual mass culture activity scene, generates and generates immersive three-dimensional scene including interactive virtual object and schedulable non-player character, and the entity space of mass culture activity is reproduced with activity element;S2 configuration embodiment practice task, set activity task from the perspective of activity organizer, open whole-process operation authority from site layout, personnel mobilization to activity execution, end summary to user;S3 real-time sensing operation behavior, collect the interactive input and pose data of user in virtual scene, identify the practice operation action that user has completed.The mass culture activity immersive theory transmission method based on virtual reality of the application embodiment, by modular scene construction, nodal process control, low code content management, greatly reduce the cost of scheme landing and operation threshold, adapt to the popularization of scale of grass-roots public cultural scene.

Description

Technical Field

[0001] This application relates to the fields of virtual reality applications and mass cultural education dissemination technology, and in particular to an immersive theoretical dissemination method for mass cultural activities based on virtual reality. Background Technology

[0002] The current dissemination and popularization of theories on mass culture mainly adopts conventional methods such as offline centralized lectures, document presentations, graphic displays, and online video courses. These methods primarily rely on one-way knowledge transmission, with learners in a passive receiving state. It is difficult for them to establish a corresponding connection between abstract theories and actual mass cultural activities, resulting in low efficiency in understanding and memorization, and weak ability to apply these theories in practice.

[0003] With the promotion and application of virtual reality technology, some VR-based cultural education solutions have emerged in the industry. However, these solutions are mostly observational experiences based on scene roaming and fixed voice explanations. They only achieve a visual upgrade in the form of display, but do not establish a linkage mechanism between user operation behavior and theoretical knowledge points. Users' practical operations in the scene cannot trigger corresponding theoretical explanations. The theoretical content and practical actions are separated from each other, and it is impossible to strengthen theoretical cognition through embodied practice, resulting in limited improvement in learning effectiveness. Summary of the Invention

[0004] This application aims to at least partially address one of the technical problems in the related art.

[0005] Therefore, the first objective of this application (if there is only one objective, the word "first" should be removed) is to provide an immersive theoretical dissemination method for mass cultural activities based on virtual reality. This method triggers corresponding theoretical content through practical operations in virtual scenarios, achieving the learning effect of "understanding through practice". At the same time, through modular scenario construction, node-based process control, and low-code content management, the method significantly reduces the implementation cost and operation and maintenance threshold of the solution, making it suitable for large-scale promotion in grassroots public cultural scenarios.

[0006] To achieve the above objectives, the first aspect of this application proposes an immersive theoretical dissemination method for mass cultural activities based on virtual reality, comprising the following steps: S1 constructs virtual scenes of mass cultural activities, generating immersive 3D scenes that include interactive virtual objects and schedulable non-player characters, and reproducing the physical space and activity elements of mass cultural activities; S2 configures embodied practice tasks, setting up event tasks from the perspective of event organizers, and granting users full-process operation permissions from venue setup and personnel mobilization to event execution and closing summary. S3 senses user behavior in real time, collects user interaction input and pose data in virtual scenes, and identifies the user's completed practical actions. S4 dynamically matches theoretical content, based on a pre-built mapping relationship library between practical actions and mass culture theoretical knowledge points, and matches the mass culture theoretical knowledge points corresponding to the user's current completed action; S5's immersive spatial presentation presents the matched theoretical knowledge points next to the operation objects corresponding to the practical operation actions in the virtual scene, and simultaneously outputs the corresponding voice explanation information. S6 Learning Review and Evaluation: After completing a single activity task, all theoretical knowledge points involved in the task are summarized, and a learning review report and mastery assessment results are generated based on user operation behavior.

[0007] In addition, the immersive theoretical dissemination method for mass cultural activities based on virtual reality proposed in this application may also have the following additional technical features: In one embodiment of this application, in step S1, the virtual mass cultural activity scene is constructed using a modular assembly method, and at least two sets of general basic scene templates are pre-constructed, corresponding to a modern digital cultural hall and a traditional rural cultural courtyard respectively, with each template divided into fixed functional areas. A reusable interactive material library is pre-built, which includes cultural symbol props, activity equipment props, crowd character models and spatial audio materials. All materials have a unified interactive interface. When generating the target scene, select the corresponding basic scene template, retrieve matching materials from the material library, and place them into the corresponding functional area to complete the scene construction.

[0008] In one embodiment of this application, in step S2, the activity task is broken down into multiple sequentially connected task nodes, and each task node is equipped with a key trigger action that can be detected and identified. In step S3, a finite state machine is used to manage the progress of the task nodes. When it is detected that the user has completed all the key triggering actions of the current node, the next task node is automatically unlocked.

[0009] In one embodiment of this application, the key triggering action includes placement actions, interaction actions, and selection actions; The placement action involves grabbing a specified virtual object and placing it within a target area. The interactive actions are either completing a preset dialogue process with a designated non-player character, or triggering the start / stop operation of a designated device. The selection action is to select an activity process or personnel division configuration item from multiple preset schemes.

[0010] In one embodiment of this application, in step S4, the mapping relationship library adopts a three-level mapping structure of task nodes, key actions, and a list of theoretical knowledge points, and is stored in a relational database. The matching process retrieves the corresponding theoretical knowledge points by looking up a table locally, and all matching logic is executed locally on the virtual reality terminal.

[0011] In one embodiment of this application, in step S5, a three-level presentation mechanism is set up for the presentation of theoretical knowledge points; Action cards respond instantly to the user completing a single key-triggered action, and then interact with the target device. Within a preset distance range, simplified concept cards are displayed, and a complete theoretical explanation is displayed in response to the triggered operation; the node summary panel is displayed in front of the user's field of vision when the user completes a single task node, and automatically collapses after a preset time. The active query panel responds to the user's specified key press operation and brings up a list of all knowledge points for the current task.

[0012] In one embodiment of this application, an immersion protection mechanism is set in step S5 to pause active push during continuous user operation and trigger the presentation of theoretical content only during the pause in operation. Configure an active push notification shutdown mode, in which all active push notifications are disabled, and only the active query function is retained; Theoretical cards are displayed semi-transparently by default, so as not to obstruct the user's field of vision.

[0013] In one embodiment of this application, the method further includes the steps of performing content configuration and data management through a visual management backend, performing addition, editing and deletion operations on knowledge points of mass culture theory, and adjusting the level of detail of the knowledge points; Visualize the mapping relationship between practical actions and theoretical knowledge points, and adjust the trigger timing parameters; Modify task node descriptions and node order, and update task objectives; Batch retrieve user learning data and output standardized statistical reports.

[0014] In one embodiment of this application, the method is configured with a dual-end operating architecture; The virtual reality terminal operates based on an integrated head-mounted display device, enabling immersive interaction throughout the entire process from a first-person perspective, corresponding to in-depth training scenarios; The universal browser terminal runs on desktop or mobile browsers and reproduces the complete task execution logic and theoretical presentation mechanism from a fixed third-person perspective, corresponding to lightweight and popular scenarios. The user learning data of the virtual reality terminal and the general browser terminal are synchronized bidirectionally and kept consistent.

[0015] In one embodiment of this application, the user's task progress and knowledge point learning status are locally persisted. When performing theoretical knowledge point matching, filter out knowledge points that have been marked as mastered, and only push related knowledge points that have not been learned; After a preset interval, the system pushes retest content for the corresponding knowledge points and generates long-term memory assessment results. Beneficial effects

[0016] According to the embodiments of this application, the immersive theoretical dissemination method for mass cultural activities based on virtual reality opens up full-process operation permissions from the perspective of the activity organizer, binds abstract theories with practical actions one by one, and allows users to complete embodied cognition through physical operation, realizing the leap from "memorization" to "practical understanding", effectively improving the depth of theoretical understanding and long-term memory effect, and solving the core pain point of the disconnect between traditional training theory and practice.

[0017] Modular scene construction significantly reduces implementation costs. Adopting a modular development model of "basic templates + material library," it avoids modeling a single scene from scratch, reducing the development cycle and cost of a single scene by more than 50%. It can quickly adapt to the needs of different types of mass cultural activities and fit the limited project budgets at the grassroots level.

[0018] Node-based triggering and three-tiered presentation balance immersion and learning. By managing the task flow through a finite state machine and combining a three-tiered presentation mechanism of real-time action, node summary, and proactive query, the timing of theoretical pushes is precisely matched with the rhythm of operation. This ensures that learning content is output synchronously with practice without disrupting the immersive experience of virtual reality, solving the problem of traditional pop-up learning interrupting the operation rhythm.

[0019] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0020] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart of a method for disseminating immersive theories of mass cultural activities based on virtual reality, according to an embodiment of this application. Detailed Implementation

[0021] Embodiments of this application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application. Rather, embodiments of this application include all variations, modifications, and equivalents falling within the spirit and scope of the appended claims.

[0022] The following is in conjunction with the appendix Figure 1 This application describes an immersive theoretical dissemination method for mass cultural activities based on virtual reality, according to embodiments of the present application.

[0023] The immersive theoretical dissemination method for mass cultural activities based on virtual reality includes the following steps: S1 constructs virtual scenes of mass cultural activities, generating immersive 3D scenes that include interactive virtual objects and schedulable non-player characters, and reproducing the physical space and activity elements of mass cultural activities; S2 configures embodied practice tasks, setting up event tasks from the perspective of event organizers, and granting users full-process operation permissions from venue setup and personnel mobilization to event execution and closing summary. S3 senses user behavior in real time, collects user interaction input and pose data in virtual scenes, and identifies the user's completed practical actions. S4 dynamically matches theoretical content, based on a pre-built mapping relationship library between practical actions and mass culture theoretical knowledge points, and matches the mass culture theoretical knowledge points corresponding to the user's current completed action; S5's immersive spatial presentation presents the matched theoretical knowledge points next to the operation objects corresponding to the practical operation actions in the virtual scene, and simultaneously outputs the corresponding voice explanation information. S6 Learning Review and Evaluation: After completing a single activity task, all theoretical knowledge points involved in the task are summarized, and a learning review report and mastery assessment results are generated based on user operation behavior.

[0024] The specific implementation process is explained below: Corresponding to step S1, an immersive 3D scene of a modern digital cultural hall is constructed based on the Unity engine. The scene includes pre-set interactive promotional display boards, red lanterns, sound equipment, LED screens and other virtual objects, as well as 3 dispatchable volunteer non-player characters. It fully replicates the spatial structure of the physical cultural hall, including the main stage area, audience seating area, promotional display wall area, and other core activity elements such as event materials and participants.

[0025] Corresponding to step S2, the entire process of the promotional event is configured from the first-person perspective of the event organizer. Users are given full access to the operation of the entire process, including venue material arrangement, volunteer job allocation, event process initiation, on-site scheduling, and event closing summary. Users can independently decide the execution order and specific implementation plan.

[0026] Corresponding to step S3, the user's head six-degree-of-freedom pose data, controller spatial coordinates and button input data are collected in real time through the integrated VR headset and interactive controller. Combined with the scene collision detection and state comparison mechanism, the user's various practical operation actions such as prop placement, character dialogue and scheme selection are identified.

[0027] Corresponding to step S4, the local pre-built mapping relationship library between practical actions and theoretical knowledge points of mass culture is called. When a user completes a certain operation, the corresponding theoretical knowledge point is matched with the action identifier as an index; for example, the action of placing a theme exhibition board corresponds to the relevant knowledge point of the application of visual symbols for grassroots theoretical dissemination.

[0028] Corresponding to step S5, a spatially anchored semi-transparent annotation interface is generated 0.8 meters to the side of the manipulated object in the virtual scene, displaying the core content of the matched theoretical knowledge points and synchronously playing the pre-recorded corresponding voice explanation; the annotation interface is bound to the spatial position of the manipulated object, and its relative position remains unchanged as the scene view moves.

[0029] In step S6, once all the tasks of the entire lecture activity are completed, the system automatically summarizes all the theoretical knowledge points triggered by this task, and combines the user's total operation time, number of attempts at each node, knowledge point viewing time and other operation behavior data to generate a learning review report that includes task execution details and knowledge point coverage, and outputs the corresponding theoretical mastery assessment results.

[0030] In one embodiment of this application, in step S1, the virtual mass cultural activity scene is constructed using a modular assembly method, and at least two sets of general basic scene templates are pre-constructed, corresponding to a modern digital cultural hall and a traditional rural cultural courtyard respectively, with each template divided into fixed functional areas. A reusable interactive material library is pre-built, which includes cultural symbol props, activity equipment props, crowd character models and spatial audio materials. All materials have a unified interactive interface. When generating the target scene, select the corresponding basic scene template, retrieve matching materials from the material library, and place them into the corresponding functional area to complete the scene construction.

[0031] The specific implementation method is described below: Two sets of general-purpose basic scene templates were pre-created using a 3D modeling engine. The modern digital cultural hall template recreates the interior space structure of a standard grassroots cultural station, dividing it into five fixed functional areas: a main stage area, an audience seating area, a propaganda display wall area, an equipment control room, and an entrance hall. The walls and floors of each area serve as fixed base models, and standardized coordinate anchor points and collision detection boundaries are reserved within each area. The total number of faces in a single template is controlled within 450,000, and basic lighting and navigation meshes are pre-baked to adapt to the performance of integrated VR terminals. The traditional rural cultural courtyard template recreates the layout of a rural public activity courtyard, dividing it into four fixed functional areas: a traditional opera stage area, a blackboard area, a courtyard activity area, and a farm tool display area. It also pre-sets uniformly standardized anchor points and physical collision rules.

[0032] A pre-built reusable interactive material library is constructed, with materials standardized into four categories, all pre-configured with unified interactive interfaces. Cultural symbol props include individual items such as lanterns, slogan boards, gongs and drums, and red silk ribbons; event equipment props include individual items such as speakers, LED screens, microphones, tables, and chairs; each prop has pre-defined collision detection and placement interaction logic. Crowd character models include three categories: ordinary villagers, volunteers, and staff, with corresponding basic actions and pre-defined dialogue branches. Spatial audio materials include three categories: ambient background sound, operation sound effects, and narration voice, supporting spatial orientation playback. All materials are uniformly configured with standardized interface fields for material ID, type tag, collision parameters, and executable interaction types, directly adapting to the mounting rules of two sets of basic templates.

[0033] When generating the target scene, the operator selects a basic scene template that matches the activity theme in the management backend, and then selects the corresponding theme material resources from the material library; the system automatically instantiates the materials and places them into the preset anchor point positions of the corresponding functional areas; after the material arrangement is completed, the global illumination and dynamic navigation grid of the scene are uniformly baked, and finally the target activity scene that can be run directly is generated.

[0034] In one embodiment of this application, in step S2, the activity task is broken down into multiple sequentially connected task nodes, and each task node is equipped with a key trigger action that can be detected and identified. In step S3, a finite state machine is used to manage the progress of the task nodes. When it is detected that the user has completed all the key triggering actions of the current node, the next task node is automatically unlocked.

[0035] This embodiment takes the Spring Festival civilized practice publicity campaign as an example to illustrate the specific implementation method of task node decomposition and finite state machine progress control as follows: The complete outreach event was broken down into four sequentially linked task nodes, each configured with key trigger actions that could be detected and identified by the system. Node 1 was venue setup, with key trigger actions including placing themed display boards, hanging promotional banners, and turning on the LED screen; Node 2 was personnel assignment, with key trigger actions including completing a dialogue with three volunteers and confirming their roles; Node 3 was event execution, with key trigger actions including starting the outreach process and triggering the interactive Q&A session; and Node 4 was event summary, with key trigger actions including submitting the event closing record.

[0036] The system employs a finite state machine to manage the progress of task nodes, pre-setting three states for each node: "Unlocked," "In Progress," and "Completed." At the initial stage of task startup, only node 1 is in the "In Progress" state, while all other nodes are in the "Unlocked" state. The system verifies the completion markers of all key trigger actions for the currently progressing node in real time. When collision detection and interaction event statistics confirm that all key trigger actions for the current node have been completed, the state machine automatically updates the current node to the "Completed" state and simultaneously switches the next node from "Unlocked" to "In Progress," thus automatically unlocking the next task node. The system synchronously records the state change timestamp when a node's state changes and writes it to a local learning data file.

[0037] In one embodiment of this application, the key triggering action includes placement actions, interaction actions, and selection actions; The placement action involves grabbing a specified virtual object and placing it within a target area. The interactive actions are either completing a preset dialogue process with a designated non-player character, or triggering the start / stop operation of a designated device. The selection action is to select an activity process or personnel division configuration item from multiple preset schemes.

[0038] This embodiment, in the context of promoting civilized practices during the Spring Festival, explains the specific implementation and detection methods for three types of key triggering actions as follows: Placement-type actions take the placement of a themed display board as a typical example. Users pick up the virtual object of the themed display board in the scene using the interactive handle and move it to the target placement area in the promotional display wall area. The system uses UnityXR interactive components to detect three states in real time: the handle triggers the pick-up command, the display board collider enters the judgment range of the target area, and the user releases the pick-up button. When all three states are met, the placement-type action is determined to be completed.

[0039] Interactive actions are implemented in two forms: the first is non-player character dialogue interaction. Taking volunteer job matching as an example, after the user triggers a dialogue with the volunteer character, he / she needs to complete the preset dialogue branches and confirm the job information. When the system detects that the dialogue process has reached the end node, it determines that the interactive action is completed. The second is device start / stop interaction. Taking turning on the LED screen as an example, the user uses the controller to ray-click the virtual switch control corresponding to the screen. After the system receives the button click interaction event, it determines that the interactive action is completed.

[0040] Selection-type actions take personnel division of labor configuration as a typical example. The system interface displays three preset job allocation schemes. The user selects one of the configuration options from the scheme list and clicks to confirm and submit. After receiving the selection confirmation instruction, the system records the selected scheme identifier and determines that the selection-type action is completed.

[0041] In one embodiment of this application, in step S4, the mapping relationship library adopts a three-level mapping structure of task nodes, key actions, and a list of theoretical knowledge points, and is stored in a relational database. The matching process retrieves the corresponding theoretical knowledge points by looking up a table locally, and all matching logic is executed locally on the virtual reality terminal.

[0042] This embodiment, combined with the scenario of promoting civilized practices during the Spring Festival, explains the specific implementation of the construction of the three-level mapping relationship database and the local matching logic as follows: The mapping database is stored locally on the virtual reality terminal as an SQLite relational database file, without relying on cloud services. The database contains three interconnected tables, forming a three-level mapping structure of task nodes, key actions, and theoretical knowledge points: The first table is the task node table, storing fields such as node ID, node name, scene identifier, and preceding node ID. For example, node ID "node01" corresponds to the "venue setup" node, belonging to the Spring Festival Civilization Practice Publicity scene. The second table is the key action table, storing fields such as action ID, action type, belonging node ID, detection parameters, and completion status marker. For example, action ID "act001" corresponds to the action of placing a themed exhibition board, belonging to node "node01". The third table is the theoretical knowledge point table, storing fields such as knowledge point ID, core concept text, practical explanation text, audio resource path, and mastery status marker. For example, knowledge point ID "kn003" corresponds to "the principle of visual symbol attention guidance in grassroots theoretical dissemination". The key action table and the knowledge point table are linked through a one-to-many foreign key relationship via action IDs, with a single action corresponding to 1 to 3 related knowledge points.

[0043] During theoretical matching, all matching logic is completed locally on the virtual reality terminal without initiating network requests. When the system detects the completion of a key action, it reads the corresponding action ID and performs a table lookup operation in the local database using the action ID as the search condition to retrieve all associated theoretical knowledge point data. After simultaneously filtering out knowledge point entries marked as mastered, the remaining knowledge point data is transferred to the content presentation module, triggering interface display. A single round of matching computation takes no more than 10 milliseconds.

[0044] In one embodiment of this application, in step S5, a three-level presentation mechanism is set up for the presentation of theoretical knowledge points; Action cards respond instantly to the user completing a single key-triggered action, and then interact with the target device. Within a preset distance range, simplified concept cards are displayed, and a complete theoretical explanation is displayed in response to the triggered operation; the node summary panel is displayed in front of the user's field of vision when the user completes a single task node, and automatically collapses after a preset time. The active query panel responds to the user's specified key press operation and brings up a list of all knowledge points for the current task.

[0045] Specifically, after a user completes a single key trigger action to place a themed display board, the system generates a simplified concept card at a preset distance of 0.8 meters to the right of the display board. The card is bound to the display board object through spatial anchoring technology and moves synchronously with the position of the display board. The default size of the card is 20cm×15cm, and the transparency is set to 70%, displaying only the core concept text of the knowledge point. When the user triggers the click interaction of the card through the handle ray, the card size expands to 40cm×30cm, simultaneously displaying the complete theoretical explanation and practical guidance content.

[0046] Once a user completes a single task node in the site setup, the system generates a summary panel of knowledge points for that node 2 meters directly in front of the user's field of vision. The panel moves with the user's head's main perspective, but does not follow slight head movements in real time to avoid visual fatigue. The panel lists the core concepts of the three related knowledge points in this node, and automatically fades away after a preset duration of 3 seconds. Users can also actively click on the panel to fix it to the side of their field of vision for continuous viewing.

[0047] When the user presses the designated button on the gamepad's menu, the system brings up a list panel of all knowledge points for the current task. The panel is fixed to the left side of the field of view and displays the names of all knowledge points involved in the task in the form of an item list. The user can click on any item to expand and view the complete content of the corresponding knowledge point. Pressing the same button again will automatically close and collapse the list panel.

[0048] In one embodiment of this application, an immersion protection mechanism is set in step S5 to pause active push during continuous user operation and trigger the presentation of theoretical content only during the pause in operation. Configure an active push notification shutdown mode, in which all active push notifications are disabled, and only the active query function is retained; Theoretical cards are displayed semi-transparently by default, so as not to obstruct the user's field of vision.

[0049] This embodiment, in conjunction with a Spring Festival civilized practice promotion scenario, explains the specific implementation method of the immersion protection mechanism as follows: The system determines the operation status by statistically analyzing the frequency of interactive input events per unit of time. When two or more pick-up, placement, or click operations are detected within one second, it is determined to be a continuous operation state, and the active push of all theoretical content is paused. When the detected operation pause duration reaches 0.8 seconds, the active push logic is resumed. For example, during the process of a user sequentially placing a display board, hanging a banner, and turning on the large screen, the system does not pop up theoretical cards temporarily. After the user completes the series of actions and the operation pauses, the corresponding knowledge points are presented sequentially.

[0050] The system has a built-in active push-off mode, which users can switch in the scene settings panel. Once switched on, all automatic push logic triggered by action completion or node completion is disabled, retaining only the query function triggered by user-activated button presses. For example, if a user needs to focus on the activity organization process and does not require theoretical prompts, this mode can be enabled, with no automatic pop-up interruptions throughout, and the knowledge point list can only be viewed when a designated button on the controller is pressed.

[0051] All theoretical cards are displayed with a semi-transparent effect of 70% transparency by default. The card generation position is set to the side of the object being operated on by default. The system calculates the angle between the card plane and the center of the user's line of sight in real time to ensure that the angle is not less than 15°, avoiding the user's main line of sight. For example, when the user places a themed display board, the theoretical card is generated in the right side area of ​​the display board, which will not obstruct the user's line of sight to the placement area and will not interfere with the accuracy of operation.

[0052] In one embodiment of this application, the method further includes the steps of performing content configuration and data management through a visual management backend, performing addition, editing and deletion operations on knowledge points of mass culture theory, and adjusting the level of detail of the knowledge points; Visualize the mapping relationship between practical actions and theoretical knowledge points, and adjust the trigger timing parameters; Modify task node descriptions and node order, and update task objectives; Batch retrieve user learning data and output standardized statistical reports.

[0053] Specifically, administrators log in to the visual management backend via a desktop browser and access the management interface corresponding to their permissions. In the knowledge point management module, administrators can add, edit, and delete knowledge points on mass culture theory through a form-based editing interface. When adding a knowledge point, administrators fill in the core concept, practical explanation, and extended content fields in sequence, select the level of detail for the knowledge point content, and upload the corresponding audio narration resources. After editing, the administrator submits and saves the data, which is automatically synchronized to the local database on each terminal.

[0054] In the mapping configuration module, the left side of the interface displays a list of key actions for each scenario, and the right side displays a knowledge point resource library. Administrators can visualize the relationship between practical actions and theoretical knowledge points by dragging and dropping lines. At the same time, the trigger timing parameters can be adjusted. For example, the card trigger delay after the action is completed can be adjusted from 0.5 seconds to 1 second, and the dwell time of the node summary panel can be adjusted from 3 seconds to 4 seconds. The effect can be previewed in real time after the parameters are adjusted, and it can be published and taken effect after confirmation.

[0055] In the task management module, administrators can modify the text descriptions of each task node, adjust the order of nodes, add or delete task nodes, and update the overall goals of the activity tasks. After adjustments, the complete task process can be previewed online, and the node unlocking logic can be synchronized to the terminal after verification.

[0056] In the data statistics module, administrators can retrieve user learning data in batches according to conditions such as administrative region, time range, and scenario type. The system automatically summarizes indicators such as the number of learners, task completion rate, and average mastery rate of knowledge points, and generates standardized statistical reports. It supports exporting to Excel format files. The reports include fixed fields such as personnel identification, learning scenario, learning duration, number of completion nodes, and mastery level rating, which can be directly used for training effectiveness statistics and work assessment.

[0057] In one embodiment of this application, the method is configured with a dual-end operating architecture; The virtual reality terminal operates based on an integrated head-mounted display device, enabling immersive interaction throughout the entire process from a first-person perspective, corresponding to in-depth training scenarios; The universal browser terminal runs on desktop or mobile browsers and reproduces the complete task execution logic and theoretical presentation mechanism from a fixed third-person perspective, corresponding to lightweight and popular scenarios. The user learning data of the virtual reality terminal and the general browser terminal are synchronized bidirectionally and kept consistent.

[0058] Specifically, the system is configured with a dual-end architecture, with both terminals sharing the same core business logic and knowledge data resources, differing only in rendering mode and interaction method.

[0059] The virtual reality terminal uses an integrated head-mounted display device as its operating platform. Based on the Unity engine, it is packaged into an executable program and deployed locally on the terminal. During runtime, it presents a first-person perspective, supports six degrees of freedom spatial interaction, fully loads three-dimensional scene resources, executes full-process motion detection, theoretical matching, and spatial presentation logic, providing an immersive operating environment for grassroots cultural backbones to conduct in-depth practical training.

[0060] The universal browser terminal packages the core business logic into a web application based on WebGL technology, which can run directly in desktop and mobile browsers without the need for additional client installation. During runtime, it performs lightweight rendering from a fixed third-person perspective, adapts to non-VR interaction methods such as mouse clicks and touch screen selections, and fully retains the core mechanisms of task node control, action triggering theory matching, theoretical content display, and learning evaluation, providing a lightweight and accessible learning portal for the general public.

[0061] Both ends share a unified user account system, and the system achieves bidirectional synchronization and consistency of user learning data through cloud services. The system adopts an incremental synchronization mechanism, which only synchronizes the progress of changed tasks, the completion status of nodes, and the mastery of knowledge points. The virtual reality terminal supports offline operation, and the locally cached learning data is automatically uploaded and synchronized after the terminal is connected to the Internet, ensuring that users can continue their learning progress by logging in on any terminal.

[0062] In one embodiment of this application, the user's task progress and knowledge point learning status are locally persisted. When performing theoretical knowledge point matching, filter out knowledge points that have been marked as mastered, and only push related knowledge points that have not been learned; After a preset interval, the system pushes retest content for the corresponding knowledge points and generates long-term memory assessment results.

[0063] Specifically, the system uses a local SQLite database to persistently store the user's task progress and knowledge point learning status. The stored content includes data such as the completion status of each node, action completion markers, knowledge point mastery level, and learning timestamps. Each time a task node is completed or a knowledge point is viewed, the system automatically writes the status data to the local storage file. When the user exits the scene midway and re-enters, the system automatically reads the status data stored locally and restores the task to the node progress at the time of exit, without having to start from the beginning.

[0064] When executing the theoretical knowledge point matching logic, the system first reads the knowledge point mastery status flags stored locally, automatically filters out knowledge point entries that have been marked as "mastered", and only pushes related knowledge points with a status of "not learned". For example, when a user places a theme display board for the first time, the corresponding knowledge point is pushed. After the knowledge point is marked as mastered, it will not be pushed again when the same placement action is performed again, so as to avoid redundant information interference.

[0065] The system has two preset retest cycles of 7 days and 30 days, starting from the time when the user first learns the corresponding knowledge point. When the user's login time meets the preset cycle, the system will automatically push retest questions for the corresponding knowledge point. The question types include concept memorization and scenario application. After the user completes the retest, the system will calculate the forgetting rate based on the accuracy of the answers, generate long-term memory assessment results, and update the mastery status markers of the knowledge points in a synchronous manner.

[0066] This embodiment provides an immersive theory dissemination system for implementing the above method. The system adopts a layered modular architecture, which is deployed on an integrated head-mounted display terminal and a cloud server. Each module communicates through a standardized data interface to collaboratively complete all business processes.

[0067] The system consists of a scene construction module, a task management module, a behavior perception module, a knowledge matching module, a content presentation module, a data evaluation module, and a management backend module. Among them, the six core modules from scene construction to data evaluation are deployed locally on the virtual reality terminal, the management backend module is deployed on a cloud server, and the core business logic is reused on the general browser terminal, which is only adapted to lightweight rendering and non-VR interaction interfaces.

[0068] The scene construction module has two built-in basic scene template resources and a standardized, reusable interactive material library. It stores basic 3D spatial models of modern digital cultural halls and traditional rural cultural courtyards, as well as four types of material resources: cultural symbol props, activity equipment, crowd characters, and spatial audio. The module supports receiving configuration instructions from the management backend, selecting basic templates and retrieving corresponding materials, completing the instantiation and mounting of materials through preset anchor points, automatically baking lighting and navigation meshes, and generating target activity scenes that can be run directly.

[0069] The task management module has a built-in finite state machine component that can load configured task node data and maintain three states for each node: unlocked, in progress, and completed. The module receives action completion signals uploaded by the behavior perception module in real time, verifies whether all key trigger actions of the current node have been completed, and automatically updates the node status after verification, unlocks the next task node, and records the timestamp of the node status change.

[0070] The behavior perception module interfaces with the head posture sensor and interactive handle input component of the integrated head-mounted device to collect data such as head posture, handle spatial coordinates, button triggering, and collision status in real time. The module has three types of action detection logic built in, which identify the completion status of placement, interaction, and selection actions through collision comparison, interaction event statistics, and command confirmation, respectively, and transmit the action completion signal to the task management module and knowledge matching module in real time.

[0071] The knowledge matching module has a built-in local SQLite database that stores a three-level mapping relationship library of task nodes, key actions, and theoretical knowledge points. After receiving an action completion signal, the module performs a local table lookup using the action ID as the search condition to obtain the associated knowledge point data, synchronously filters the items marked as mastered, and transmits the filtered knowledge point data to the content presentation module.

[0072] The content presentation module is equipped with a three-level rendering component and immersion protection logic. After receiving knowledge point data, it generates a spatially anchored semi-transparent annotation interface on the side of the object being operated on, and simultaneously calls the corresponding audio resources to play the explanation. The module can generate three types of interfaces according to the triggering time: action cards, node summary panels, and active query lists. At the same time, it detects the frequency of user operations and the angle of vision in real time, and executes immersion protection logic such as pausing push for continuous operation and avoiding vision.

[0073] The data evaluation module is responsible for persistent local data storage and learning effect evaluation. It writes the user's task progress, action completion status, and knowledge point viewing records to local storage in real time. After the entire set of tasks is completed, the module summarizes all knowledge points and operation behavior data of this task, calculates various indicators, and generates a learning review report and mastery assessment results. The module has built-in interval retesting logic, pushes retest questions according to preset cycles, and generates long-term memory assessment results. The module supports incremental data synchronization, uploading local learning data to the cloud when connected to the network to achieve data consistency between the two ends.

[0074] The management backend module is deployed on a cloud server and adopts a B / S architecture to provide a web management interface. It includes four major functional units: knowledge point management, mapping configuration, task management, and data statistics. Administrators can add, delete, and modify knowledge points, drag and drop actions to bind knowledge points, and adjust task nodes through a browser. The configuration results are synchronously sent to the terminals. The module can batch summarize the learning data reported by each terminal, generate multi-dimensional statistical indicators, and support the export of standardized assessment reports.

[0075] Specifically, the complete execution flow of this method, from content creation and user learning to effect evaluation and continuous maintenance, is as follows: I. Pre-configuration phase (system deployment and content initialization).

[0076] This stage is the preparation phase before user use, completing the standardized construction of scenarios, tasks, and knowledge systems: Modular scene construction: Two sets of general basic scene templates are pre-made, one for a modern digital cultural hall and the other for a traditional rural cultural courtyard. Each template is divided into fixed functional areas and has reserved standardized mounting anchor points. Simultaneously, a reusable interactive material library containing cultural symbols, props, activity equipment, audience characters, and spatial audio is built, with all materials having a pre-defined unified interactive interface. When generating the target activity scene, the corresponding basic template is selected, matching materials are retrieved from the material library and placed into the corresponding functional areas, and lighting and navigation meshes are uniformly baked to complete the immersive 3D scene construction.

[0077] Task Node Decomposition: The complete mass cultural activity is decomposed into multiple sequentially connected task nodes. Each node is configured with a key trigger action that can be detected and identified. The action types cover three categories: placement, interaction, and selection. Based on a finite state machine, node flow rules are established, setting three node states: "unlocked - in progress - completed". It is clear that the next node can only be unlocked after all actions are completed.

[0078] Three-level mapping library construction: Construct a relational mapping library with a three-level structure of "task node - key action - theoretical knowledge point", and establish a one-to-many relationship between a single action and multiple knowledge points; the mapping library is deployed on the virtual reality terminal in the form of a local database and supports offline table lookup and calling.

[0079] II. Immersive Interactive Learning Phase (Core User Experience Flow).

[0080] This stage is the core execution phase of the method, enabling embodied cognitive learning of "practical actions triggering theoretical explanations": Task initialization: The user logs in and enters the target scene while wearing an all-in-one VR headset. The system loads the 3D scene resources, initializes the finite state machine, and the first task node switches to the "in progress" state, while the remaining nodes remain locked.

[0081] Real-time perception of operation behavior: The system collects the user's head six-degree-of-freedom pose data, controller spatial coordinates and button input data in real time. Through collision detection, interaction event statistics and command confirmation, it identifies the completion status of key trigger actions of placement, interaction and selection, and marks the action completion timestamps in real time.

[0082] Local matching of theoretical content: After the key action is identified, the system performs a table lookup and matching on the terminal with the action ID as the search condition to obtain all related theoretical knowledge points; at the same time, it reads the local learning status, filters out the knowledge points marked as "mastered", and retains only the content to be learned.

[0083] Spatialized hierarchical presentation: Theoretical content is output using a three-level presentation mechanism, with accompanying immersion protection rules. Action Instant Card: A semi-transparent, simplified card is generated at a preset distance to the side of the object being operated on. When the user clicks on it, a complete theoretical explanation is displayed and the corresponding voice narration is played simultaneously. Node Summary Panel: After all actions of a single task node are completed, a summary panel of knowledge points for this node will pop up in front of the user's field of view and will automatically collapse after a preset time. Active query panel: Responds to user-defined key presses, bringing up a list of all knowledge points for the current task, allowing for self-service browsing. Throughout the process, three rules—pausing push notifications with continuous operations, adjusting viewing angles, and using semi-transparent display—are implemented to prevent theoretical content from disrupting the immersive experience.

[0084] Automatic node transition: Once all key trigger actions of the current node are marked as completed, the finite state machine automatically sets the current node to "completed", and the next node switches to "in progress" and unlocks; the operation perception-theoretical matching-content presentation process is executed in a loop until all task nodes are completed.

[0085] III. Review, Evaluation, and Long-Term Learning Phase (Learning Effectiveness Closed Loop)

[0086] This stage quantifies learning outcomes and strengthens long-term memory, forming a complete learning loop: Learning review and mastery assessment: After all tasks in a single activity are completed, the system automatically summarizes all theoretical knowledge points involved in the task, and combines user operation time, number of trial and error at each node, knowledge point viewing time and viewing rate and other operation behavior data to generate a learning review report that includes task details, knowledge point coverage and behavior analysis, and outputs the theoretical mastery assessment results through weighted calculation.

[0087] Persistent learning status: The system persistently stores data such as user task progress, node completion status, and knowledge mastery level in the terminal's local database; when the user exits midway and re-enters the scene, the progress node at the time of exit can be automatically restored without having to start from the beginning.

[0088] Deduplication and interval retesting: When users repeatedly perform similar actions, the system automatically filters out knowledge points that have already been mastered and only pushes content that has not been learned, avoiding interference from redundant information; the system presets two retesting cycles of 7 days and 30 days. After the cycle is reached, the corresponding knowledge point retest questions are automatically pushed. After the user completes the questions, the accuracy rate and forgetting rate are calculated, long-term memory assessment results are generated, and the knowledge point mastery status is updated.

[0089] IV. Back-end Operation and Maintenance and Multi-terminal Collaboration Phase (System Support and Expansion).

[0090] This phase ensures continuous updates to the content and coverage across multiple application scenarios: Visualized backend operation and maintenance: Administrators can use the web-based visual management backend to add, edit, delete, and adjust the content detail of mass culture theory knowledge points; they can also use drag-and-drop operations to visually configure the mapping relationship between actions and knowledge points, and adjust parameters such as trigger timing and display duration; they can modify task node descriptions, adjust node order, and update task objectives; and they can batch retrieve user learning data by region and time to generate and export standardized statistical reports.

[0091] Dual-end operation and data synchronization: The system is configured with a dual-end architecture. The virtual reality terminal runs on an all-in-one headset, providing a first-person, fully immersive, in-depth training experience. The general-purpose browser terminal runs on desktop or mobile browsers based on WebGL technology, employing lightweight rendering and non-VR interaction to reproduce the complete task logic and theoretical presentation mechanism, making it accessible to the general public in a lightweight manner. Both ends share a unified account system, and incremental bidirectional synchronization of learning data is achieved through cloud services. The VR end supports offline caching and automatic synchronization after connecting to the internet, ensuring consistency in progress and status between the two ends.

[0092] In summary, the immersive theoretical dissemination method for mass cultural activities based on virtual reality in this application provides full-process operation permissions from the perspective of the activity organizer, binding abstract theories with practical actions one by one. Users complete embodied cognition through physical operation, realizing the leap from "memorization" to "practical understanding", effectively improving the depth of theoretical understanding and long-term memory effect, and solving the core pain point of the disconnect between traditional training theory and practice.

[0093] Modular scene construction significantly reduces implementation costs. Adopting a modular development model of "basic templates + material library," it avoids modeling a single scene from scratch, reducing the development cycle and cost of a single scene by more than 50%. It can quickly adapt to the needs of different types of mass cultural activities and fit the limited project budgets at the grassroots level.

[0094] Node-based triggering and three-tiered presentation balance immersion and learning. By managing the task flow through a finite state machine and combining a three-tiered presentation mechanism of real-time action, node summary, and proactive query, the timing of theoretical pushes is precisely matched with the rhythm of operation. This ensures that learning content is output synchronously with practice without disrupting the immersive experience of virtual reality, solving the problem of traditional pop-up learning interrupting the operation rhythm.

[0095] In the description of this specification, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0096] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0097] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A method for immersive theoretical dissemination of mass cultural activities based on virtual reality, characterized in that: Includes the following steps: S1 constructs virtual scenes of mass cultural activities, generating immersive 3D scenes that include interactive virtual objects and schedulable non-player characters, and reproducing the physical space and activity elements of mass cultural activities; S2 configures embodied practice tasks, setting up event tasks from the perspective of event organizers, and granting users full-process operation permissions from venue setup and personnel mobilization to event execution and closing summary. S3 senses user behavior in real time, collects user interaction input and pose data in virtual scenes, and identifies the user's completed practical actions. S4 dynamically matches theoretical content, based on a pre-built mapping relationship library between practical actions and mass culture theoretical knowledge points, and matches the mass culture theoretical knowledge points corresponding to the user's current completed action; S5's immersive spatial presentation presents the matched theoretical knowledge points next to the operation objects corresponding to the practical operation actions in the virtual scene, and simultaneously outputs the corresponding voice explanation information. S6 Learning Review and Evaluation: After completing a single activity task, all theoretical knowledge points involved in the task are summarized, and a learning review report and mastery assessment results are generated based on user operation behavior.

2. The immersive theoretical dissemination method for mass cultural activities based on virtual reality according to claim 1, characterized in that, In step S1, the virtual mass cultural activity scene is constructed using a modular assembly method, with at least two sets of general basic scene templates pre-built, corresponding to a modern digital cultural hall and a traditional rural cultural courtyard, respectively, and each template is divided into fixed functional areas; A reusable interactive material library is pre-built, which includes cultural symbol props, activity equipment props, crowd character models and spatial audio materials. All materials have a unified interactive interface. When generating the target scene, select the corresponding basic scene template, retrieve matching materials from the material library, and place them into the corresponding functional area to complete the scene construction.

3. The immersive theoretical dissemination method for mass cultural activities based on virtual reality according to claim 1, characterized in that, In step S2, the activity task is broken down into multiple sequentially connected task nodes, and each task node is equipped with a key trigger action that can be detected and identified. In step S3, a finite state machine is used to manage the progress of the task nodes. When it is detected that the user has completed all the key triggering actions of the current node, the next task node is automatically unlocked.

4. The immersive theoretical dissemination method for mass cultural activities based on virtual reality according to claim 3, characterized in that, The key trigger actions include placement actions, interaction actions, and selection actions; The placement action involves grabbing a specified virtual object and placing it within a target area. The interactive actions are either completing a preset dialogue process with a designated non-player character, or triggering the start / stop operation of a designated device. The selection action is to select an activity process or personnel division configuration item from multiple preset schemes.

5. The immersive theoretical dissemination method for mass cultural activities based on virtual reality according to claim 3, characterized in that, In step S4, the mapping relationship library adopts a three-level mapping structure of task nodes, key actions, and theoretical knowledge point lists, and is stored in a relational database. The matching process retrieves the corresponding theoretical knowledge points by looking up a table locally, and all matching logic is executed locally on the virtual reality terminal.

6. The immersive theoretical dissemination method for mass cultural activities based on virtual reality according to claim 1, characterized in that, In step S5, a three-level presentation mechanism is set up for the theoretical knowledge points; Action cards respond instantly to the user completing a single key-triggered action, and then interact with the target device. A simplified concept card is presented within a preset distance range of the image, and a complete theoretical explanation is unfolded in response to the trigger operation; The node summary panel responds to the user's completion of a single task node by displaying a summary panel of all knowledge points for that node in front of the user's field of view, and automatically collapses after a preset time. The active query panel responds to the user's specified key press operation and brings up a list of all knowledge points for the current task.

7. The immersive theoretical dissemination method for mass cultural activities based on virtual reality according to claim 6, characterized in that, In step S5, an immersion protection mechanism is set up to pause active push notifications during continuous user operation and only trigger the presentation of theoretical content during the pause in operation. Configure an active push notification shutdown mode, in which all active push notifications are disabled, and only the active query function is retained; Theoretical cards are displayed semi-transparently by default, so as not to obstruct the user's field of vision.

8. The immersive theoretical dissemination method for mass cultural activities based on virtual reality according to claim 1, characterized in that, It also includes steps for configuring and managing content and data through a visual management backend, allowing for the addition, editing, and deletion of knowledge points in mass culture theory, and adjusting the level of detail in the knowledge points. Visualize the mapping relationship between practical actions and theoretical knowledge points, and adjust the trigger timing parameters; Modify task node descriptions and node order, and update task objectives; Batch retrieve user learning data and output standardized statistical reports.

9. The immersive theoretical dissemination method for mass cultural activities based on virtual reality according to claim 1, characterized in that, The method configures a dual-end operating architecture; The virtual reality terminal operates based on an integrated head-mounted display device, enabling immersive interaction throughout the entire process from a first-person perspective, corresponding to in-depth training scenarios; The universal browser terminal runs on desktop or mobile browsers and reproduces the complete task execution logic and theoretical presentation mechanism from a fixed third-person perspective, corresponding to lightweight and popular scenarios. The user learning data of the virtual reality terminal and the general browser terminal are synchronized bidirectionally and kept consistent.

10. The immersive theoretical dissemination method for mass cultural activities based on virtual reality according to claim 1, characterized in that, The system continuously stores the user's task progress and knowledge learning status locally. When performing theoretical knowledge point matching, filter out knowledge points that have been marked as mastered, and only push related knowledge points that have not been learned; After a preset interval, the system pushes retest content for the corresponding knowledge points and generates long-term memory assessment results.

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