Consumer right protection-oriented meta-universe immersive teaching system

Abstract

The application discloses a meta-universe immersive teaching system for consumer rights protection, which integrates a meta-universe immersive scene construction module, a case library and element extraction module, a scene-case fusion engine, a user interaction and role playing interface and a teaching logic and feedback module, can reconstruct real-time updated real rights protection case data into an interactive virtual consumer scene, and supports learners to practice in highly simulated scenario deduction in different role identities; the application solves the problems of disconnection between theory and practice, lagging teaching content and single training mode in traditional rights protection education through the fusion of cases and scenes, multi-role confrontation drill and real-time intelligent feedback based on behavior analysis.

Description

Technical Field

[0001] This invention relates to the field of digital education technology, and in particular to a metaverse immersive teaching system for consumer rights protection. Background Technology

[0002] Currently, consumer rights awareness and skills training are mainly conducted through traditional methods such as text and image case analysis, video teaching, offline lectures, and some web-based or simple animation-based simulation programs. Meanwhile, with the advancement of information technology, some educational applications have begun to introduce virtual reality or augmented reality technologies to build experiential scenarios. Furthermore, the construction of legal and case databases has become relatively mature, providing a large number of court documents and case search services.

[0003] Traditional educational methods (text, images, videos) lack immersion and interactivity, leaving learners in a passive state and making it difficult to deeply understand and master the practical skills required in the rights protection process, such as proactive evidence collection, on-site communication, and procedural responses. Meanwhile, existing VR / AR experiences are mostly pre-set, fixed scenarios with slow content updates, failing to keep pace with real-time, diverse consumer dispute cases. This results in a significant disconnect between teaching content and practical rights protection, with a clear lag. Although existing methods have independent case databases, they are isolated from immersive learning environments. Case data exists in static text form, preventing learners from concretely practicing key elements (evidence, legal provisions, dialogue) within an interactive and operational virtual context.

[0004] Therefore, in response to the problems mentioned above, this invention proposes a metaverse immersive teaching system for consumer rights protection. Summary of the Invention

[0005] To overcome the problems of weak immersion, outdated teaching content, and disconnect between case teaching and practical exercises in existing consumer rights protection education methods, this invention proposes a teaching system that deeply and intelligently integrates a dynamically updated real consumer rights protection case library with a reconfigurable metaverse immersive scenario. Through multi-role and highly realistic situational interaction and intelligent guidance, it achieves efficient teaching that combines theory and reality.

[0006] The technical solution of this invention is: a metaverse immersive teaching system for consumer rights protection, comprising: The Metaverse Immersive Scene Construction Module is used to generate and render virtual consumption scenes with physical attributes and spatial logic, wherein the virtual consumption scenes include at least virtual shopping malls, virtual online shopping interfaces, virtual service venues, and virtual administrative / judicial mediation and arbitration tribunals; The case library and element extraction module are connected to the database of consumer rights protection regulatory agencies and the open judicial case library. They are used to obtain real consumer rights protection case data in real time or periodically, and to analyze the case data through natural language processing technology to extract key case elements. These key case elements include the type of goods / services involved, the merchant's behavior pattern, the focus of the infringement dispute, the consumer's evidence materials, the applicable legal provisions, the processing process nodes, and the processing results. The scene-case fusion engine communicates and connects with the metaverse immersive scene construction module and the case library and element extraction module, respectively. Based on the selected case elements, the engine drives the metaverse immersive scene construction module to dynamically reconstruct a virtual consumption scene that matches the case, and embeds the evidence materials, dialogue texts and process links in the case into the corresponding spatiotemporal nodes of the scene in the form of interactive virtual objects. The user interaction and role-playing interface provides users with virtual avatars and features multiple role selection functions. Users can choose to play the roles of consumers, merchants, mediators, arbitrators, or judges, and engage in immersive and story-driven interactive operations in virtual scenarios, including simulated evidence collection, negotiation, complaint, evidence presentation, and debate. The interface supports multiple terminal access modes, including VR headsets, AR glasses, and traditional flat terminals. The teaching logic and feedback module includes teaching logic rules based on a consumer rights protection knowledge graph. It monitors users' interactive behavior and decision-making path in virtual scenarios in real time, compares them with the original case processing flow and legal rules, and provides instant prompts, error warnings and legal provisions guidance. It also generates an evaluation report after the simulation session, pointing out behavioral deviations and knowledge gaps. The simulated confrontation training module supports multiple users to access the same virtual scene via the network, play different roles, and conduct real-time rights protection process confrontation simulations, with the system or a third-party senior user acting as the referee. The blockchain-based evidence storage and teaching module is used to store key user interaction steps in a virtual scenario on the blockchain, simulating the process of fixing and tracing electronic teaching evidence. The interface for real-time updates of laws and policies ensures that the knowledge graph and evaluation rules in the teaching logic and feedback modules are synchronized with the latest laws, regulations, judicial interpretations and departmental rules.

[0007] Preferably, the teaching logic and feedback module will adjust the intensity of the merchant's virtual role's confrontation, the depth of evidence concealment, or the complexity of the program rules in real time based on the user's grasp of the key points of the case.

[0008] Preferably, the case library and element extraction module allow authorized users or organizations to submit new typical cases or local rights protection handling examples after anonymization, which are then reviewed and added to the library for expansion and updating.

[0009] Preferably, the evaluation report generated by the teaching logic and feedback module includes a comparison graph of the user's decision path and the optimal path, a score of mastery of the relevant legal provisions, and related recommendations of other similar or advanced cases to be learned.

[0010] Preferably, the virtual administrative / judicial mediation and arbitration tribunal scene generated by the metaverse immersive scene construction module integrates a virtual digital human character based on historical data in the case library. This digital human character can simulate real mediators or arbitrators with different styles and interact with users.

[0011] Preferably, when reconstructing a virtual consumption scenario, the scenario-case fusion engine can call the corresponding 3D model library and material library based on the geographical location and merchant scale information in the case elements to generate a scenario with regional characteristics and commercial features.

[0012] The beneficial effects of this invention are: 1. This invention acquires and analyzes real cases in real time through a case library and element extraction module, and then reconstructs them through a metaverse immersive scene construction module driven by a scene-case fusion engine. This solves the problem of traditional teaching content being outdated and disconnected from rights protection practices, enabling teaching scenarios to reflect the latest forms of consumer disputes and handling rules in a synchronized manner, and greatly improving the timeliness and relevance of teaching content.

[0013] 2. This invention, through its teaching logic and feedback module, enables the system to analyze user interaction behavior in real time and automatically adjust parameters such as the adversarial intensity and evidence concealment depth of virtual characters. This overcomes the problems of fixed warning and challenge thresholds in traditional teaching, which prevent individualized instruction. It achieves adaptive matching between teaching difficulty and user ability, thereby providing personalized advancement paths and significantly improving training accuracy and learning efficiency.

[0014] 3. This invention, through the collaboration of a simulated adversarial training module and a blockchain evidence preservation teaching module, seamlessly integrates practical teaching of electronic evidence fixation procedures in highly simulated multi-role adversarial exercises, solving the problem of the disconnect between knowledge instruction and practical execution in traditional teaching. Attached Figure Description

[0015] Figure 1 The diagram shown is a schematic representation of the system framework of this invention. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Please see Figure 1 This invention provides an embodiment of a metaverse immersive teaching system for consumer rights protection, comprising: In this embodiment, the immersive scene construction module of the metaverse is described in detail: This module's scene resource library contains four main categories of 3D models, textures, sound effects, and interactive logic templates for basic scenes, including virtual shopping malls, virtual online shopping interfaces, virtual service venues, and virtual administrative / judicial venues. (1) The virtual mall includes templates of different sizes and formats, such as large shopping centers, community supermarkets, and specialty stores. The internal product model library is linked to the real product database and supports the dynamic mounting of tag information (price, specifications, place of origin).

[0018] (2) The virtual online shopping interface simulates the UI / UX interaction process of mainstream e-commerce platforms, including the entire chain interface such as product browsing, customer service chat, order placement, payment simulation, logistics tracking, and reviews.

[0019] (3) Virtual service venues include gyms, training institutions, construction sites, tourist attractions and restaurant kitchens, focusing on the visualization of the service process and the highlighting of key links.

[0020] (4) Virtual administrative / judicial venues include the complaint reception room of the Market Supervision Administration, the mediation room of the Consumer Association, the arbitration tribunal, and the virtual courtroom of the Internet Court. The venues integrate dedicated virtual tools such as electronic evidence display screens, legal provision query screens, and transcript generators.

[0021] This module integrates a physics engine to simulate effects such as object collisions and gravity. It also includes a consumption logic engine, defining basic rules for consumption behavior, such as "acquiring ownership upon payment," "service commitments constituting a contractual offer," and "advertising page content can be considered an invitation to offer," serving as the underlying logical basis for all interactive behaviors within all scenarios. Based on instructions from the fusion engine, this module can quickly call and combine elements from the resource library to generate specific scenarios that meet the needs of the case study.

[0022] In this embodiment, the dynamic case library and the element extraction module are described in detail: This module is responsible for drawing inspiration from the external world and transforming it into digital teaching materials that the system can understand. It collaborates with institutions through API interfaces and data channels to capture, in real time or on a schedule, administrative penalty cases published by market supervision departments at all levels, typical cases of rights protection released by consumer organizations, consumer litigation judgments published on the China Judgments Online website, and consumer infringement incidents exposed by mainstream media. All data enters a buffer pool for cleaning and desensitization.

[0023] Then, intelligent element extraction is performed, using an NLP model trained on legal texts to conduct in-depth analysis of the full case text. Specifically: (1) Automatically identify and label the main entities such as “consumer”, “merchant (brand / store)”, “product / service name”, “regulatory department”, and “adjudication body”.

[0024] (2) Identify relationships such as “complaint about…”, “based on…legal provisions…determined…”, and “submit…evidence to prove…”, and construct a case logic diagram.

[0025] (3) Automatically populate the following structured fields with unstructured text examples: The elements involved are: type of goods / services (smartphones, gym memberships), brand, and price range.

[0026] Behavioral elements include merchant infringements (false advertising, product quality defects, refusal to fulfill warranty obligations) and consumer demands (refund, compensation, apology).

[0027] The procedural elements include the rights protection path (negotiation, complaint, arbitration, litigation), the time nodes of each stage, and the list of evidence to be submitted (chat screenshots, invoices, test reports).

[0028] Regulatory elements include the laws cited (Consumer Rights Protection Law, Food Safety Law) and specific provisions and discretionary standards.

[0029] Outcome elements include the outcome (support / partial support / rejection) and the amount of compensation / penalty.

[0030] The structured cases are tagged by field, type of infringement, difficulty, and region, forming a dynamically updated knowledge graph of rights protection cases. Certified legal professionals and educational institutions are also allowed to upload verified, typical localized cases, enriching the diversity of the database.

[0031] In this embodiment, the scenario-case fusion engine will be described in detail: This engine is responsible for arranging case elements on a virtual scene. Its mapping rule base has a large number of preset "IF-THEN" mapping rules, such as: If the case type is “7-day no-reason return dispute” and the focus of the dispute is “whether the goods are intact”, then the virtual online shopping interface scenario will be invoked, and the “goods unpacking and inspection process” and “chat interface with customer service arguing about the standards of goods being intact” will be generated.

[0032] If the processing stage = "litigation", then the virtual court scene will be invoked, and the images and documents in the evidence list will be automatically converted into viewable files on the court evidence display screen.

[0033] Based on the procedural elements of the case, the engine automatically generates a main storyline for rights protection that includes multiple key decision points. For example, it might progress from "discovering a quality problem" -> "negotiating with the merchant" -> "complaining to the platform" -> "submitting to the regulatory authorities" -> "participating in mediation" -> "court hearing." Each node corresponds to a state transition and the issuance of an interactive task. Based on the merchant's behavioral elements in the case, the engine drives the virtual merchant NPC to exhibit specific behavioral patterns, such as "evasive," "aggressive," or "compromising." The dialogue content and ruling tendencies of mediators, arbitrators, and other NPCs are generated based on legal and outcome elements.

[0034] In this embodiment, the user interaction and role-playing interfaces are described in detail: This interface is compatible with multiple terminals. For VR / AR terminals, it provides a fully immersive experience, allowing learners to interact naturally by using VR controllers to grab products, browse virtual contracts, and raise their hands to speak in a virtual courtroom. In AR mode, a virtual complaint interface can be overlaid on real product packaging for learning. For traditional terminals (PC / mobile), it provides a third-person perspective or a sophisticated 3D interface, allowing interaction via mouse, keyboard, or touchscreen.

[0035] Users can customize their virtual avatars and choose a role before starting a case study. Choosing the "Consumer" role means successfully protecting one's rights; choosing the "Merchant" role means reasonably addressing and controlling risks within the legal framework; choosing the "Mediator / Arbitrator" role means clarifying the facts, correctly applying the law, and making a fair judgment. The task objectives, available information views, and operational permissions are completely different for each role.

[0036] In this embodiment, the intelligent teaching logic and feedback module will be described in detail: This module incorporates a "consumer rights protection knowledge graph," which includes an idealized rights protection process model and a legal rule base. It tracks the user's action sequence in real time: for example, did the user check the merchant's qualifications before payment? Did they save evidence immediately upon discovering a problem? Does the compensation claim have a clear legal basis? The system compares the user's behavior path with the optimal path in the knowledge graph in real time.

[0037] When a user gets stuck or deviates significantly from the key procedures, the system will display a gentle prompt in the form of a virtual assistant, such as "You can try checking the product details page for relevant promises." When a user engages in clearly erroneous behavior, the system will issue a red warning and display relevant legal provisions explaining the consequences.

[0038] This module adjusts the challenge difficulty in real time based on user performance. For example, the merchant NPC may be more accommodating to new users; for experienced users, the system will activate an "evidence hiding" mode, requiring users to conduct more detailed scene investigations or ask more precise questions to discover key evidence.

[0039] In the simulated adversarial training module, multiple users take on the roles of consumers, merchants, and lawyers online. This module monitors the entire adversarial process and can automatically or through mentor users acting as referees to determine the winner according to preset rules, focusing on the application of law and procedural legitimacy.

[0040] After the case study exercise, the system will generate a multi-dimensional evaluation report. The report includes a visualization comparing the behavioral path with the standard path, a radar chart of mastery of key legal knowledge points, time efficiency analysis, and a list of follow-up learning cases intelligently recommended based on weaknesses.

[0041] During the teaching process, when users reach key procedural nodes such as "submitting evidence" and "filing a formal complaint", the blockchain evidence preservation teaching module will generate a data package containing the action, time and content of the operation, and call the blockchain evidence preservation service to put it on the chain, thereby vividly demonstrating the entire process of electronic evidence preservation to learners and strengthening their awareness of evidence preservation.

[0042] This invention provides a comparative example: This study recruited 120 learners with basic consumer knowledge but no systematic training in consumer rights protection. They were randomly divided into three groups of 40 each. Experimental group 1 used this invention. Experimental group 2 used a simplified version of the system (containing only three fixed, preset VR consumer rights protection scenarios, lacking a dynamic case library and intelligent guidance, offering only scenario roaming and simple interaction). Control group 3 used traditional teaching methods (watching two hours of carefully selected video lectures by consumer rights protection experts and reading textual and graphic case analysis materials).

[0043] The learning content in this example focuses on the theme of "protecting rights in disputes over the quality of goods purchased online", covering three core aspects: negotiation, platform complaints, and reporting to 12315.

[0044] Experimental procedure: First, all participants completed a questionnaire on their knowledge of rights protection, procedural awareness, and self-confidence (out of 100 points). Then, each group spent two hours learning in a designated manner. Finally, a post-test and practical assessment were conducted, with the written test and post-test consisting of the same questionnaire.

[0045] The practical assessment simulated a completely new, unexplored case of "electronic products purchased via livestream not matching the description." Participants were required to independently complete the entire process from evidence collection to complaint submission within a simulated environment provided by the system (a simplified web form simulation interface was provided for experimental group 2 and control group 3). Two senior consumer mediators (blind reviewers) scored the participants based on various indicators (out of 100), including completeness of operation (whether key steps were omitted (e.g., capturing livestream promises, saving chat logs, requesting invoices)), correctness of procedure (whether the order of operations conformed to legal procedures), standardization of documentation (whether the complaint was clear and well-documented), and time efficiency.

[0046]

[0047] As shown in the table above, Experimental Group 1 scored significantly higher than the other two groups in both post-test knowledge and comprehensive practical skills, demonstrating that the teaching model combining dynamic cases and immersive scenarios with intelligent feedback has significant advantages in knowledge transfer and skill transformation. While Experimental Group 2 also offered a sense of immersion, its lack of diverse real-world cases and AI guidance resulted in no substantial improvement over Control Group 3; in fact, it performed worse in some practical projects due to the complexity of the interface. The high scores of Experimental Group 1 in "Procedure Correctness" and "Document Standardization" indicate that the system, through real-time correction of teaching logic and feedback modules and the strong replication of legal procedures by the scenario-case fusion engine, effectively helps learners internalize abstract rules into correct operational intuition.

[0048] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A metaverse-based immersive teaching system for consumer rights protection, characterized in that: Including: The Metaverse Immersive Scene Construction Module is used to generate and render virtual consumption scenes with physical attributes and spatial logic, wherein the virtual consumption scenes include at least virtual shopping malls, virtual online shopping interfaces, virtual service venues, and virtual administrative / judicial mediation and arbitration tribunals; The case library and element extraction module are connected to the database of consumer rights protection regulatory agencies and the open judicial case library. They are used to obtain real consumer rights protection case data in real time or periodically, and to analyze the case data through natural language processing technology to extract key case elements. These key case elements include the type of goods / services involved, the merchant's behavior pattern, the focus of the infringement dispute, the consumer's evidence materials, the applicable legal provisions, the processing process nodes, and the processing results. The scene-case fusion engine communicates and connects with the metaverse immersive scene construction module and the case library and element extraction module, respectively. Based on the selected case elements, the engine drives the metaverse immersive scene construction module to dynamically reconstruct a virtual consumption scene that matches the case, and embeds the evidence materials, dialogue texts and process links in the case into the corresponding spatiotemporal nodes of the scene in the form of interactive virtual objects. The user interaction and role-playing interface provides users with virtual avatars and features multiple role selection functions. Users can choose to play the roles of consumers, merchants, mediators, arbitrators, or judges, and engage in immersive and story-driven interactive operations in virtual scenarios, including simulated evidence collection, negotiation, complaint, evidence presentation, and debate. The teaching logic and feedback module includes teaching logic rules based on a consumer rights protection knowledge graph. It monitors users' interactive behaviors and decision-making paths in virtual scenarios in real time, compares them with the original case processing flow and legal rules, and provides instant prompts, error warnings and legal provisions guidance. After the simulation session, it generates an evaluation report that points out behavioral deviations and knowledge gaps.

2. The metaverse immersive teaching system for consumer rights protection as described in claim 1, characterized in that: The teaching logic and feedback module will adjust the intensity of the merchant's virtual role's confrontation, the depth of evidence concealment, or the complexity of the program rules in real time based on the user's grasp of the key points of the case.

3. The metaverse immersive teaching system for consumer rights protection as described in claim 1, characterized in that: The case library and element extraction module allow authorized users or organizations to submit new typical cases or local rights protection handling examples after anonymization. After review, these cases are added to the library to expand and update it.

4. The metaverse immersive teaching system for consumer rights protection as described in claim 1, characterized in that: The system also includes a simulated adversarial training module, which supports multiple users to access the same virtual scene via the network, play different roles, and conduct real-time rights protection process adversarial simulations, with the system or a third-party senior user acting as the referee.

5. The metaverse immersive teaching system for consumer rights protection as described in claim 1, characterized in that: The evaluation report generated by the teaching logic and feedback module includes a comparison graph of the user's decision path and the optimal path, a score of mastery of the relevant legal clauses, and related recommendations of other similar or advanced cases to be learned.

6. The metaverse immersive teaching system for consumer rights protection as described in claim 1, characterized in that: The virtual administrative / judicial mediation and arbitration tribunal scene generated by the metaverse immersive scene construction module integrates a virtual digital human character based on historical data in the case library. This digital human character can simulate real mediators or arbitrators with different styles and interact with users.

7. The metaverse immersive teaching system for consumer rights protection as described in claim 1, characterized in that: The system also includes a blockchain-based evidence storage and teaching module, which stores key user interaction steps in a virtual scenario on the blockchain to simulate the process of fixing and tracing electronic teaching evidence.

8. The metaverse immersive teaching system for consumer rights protection according to any one of claims 1-7, characterized in that: When reconstructing virtual consumption scenarios, the scenario-case fusion engine can call the corresponding 3D model library and material library based on the geographical location and merchant scale information in the case elements to generate scenarios with regional characteristics and commercial features.

9. The metaverse immersive teaching system for consumer rights protection as described in claim 8, characterized in that: The system is also connected to a real-time update interface for laws and policies, ensuring that the knowledge graph and evaluation rules in the teaching logic and feedback module are synchronized with the latest laws, regulations, judicial interpretations and departmental rules.

10. The metaverse immersive teaching system for consumer rights protection as described in claim 1, characterized in that: The user interaction and role-playing interface supports multiple terminal access modes, including VR headsets, AR glasses, and traditional flat-panel terminals.

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