Simulation engineering practice education method, device, equipment and medium

Abstract

The invention relates to the technical field of data processing, in particular to a simulation engineering practice education method and device, equipment and a medium. The method comprises the steps that personalized experience is provided for students through identity recognition, a multi-agent role model is loaded through a role simulation instruction, and the students are helped to understand engineering cooperation from different role perspectives; role answers and initial product demand documents are generated based on user demands, and demand analysis and management capabilities are cultivated; user decisions are received in real time, a decision effect is generated, and decision practice feedback is enhanced; iterative optimization and critical thinking are improved by correcting documents and independently evaluating decisions. And finally, a corrected document and an evaluation result are visualized, knowledge integration and reflection are promoted, a complete practice closed loop is formed, and the comprehensive ability of students to solve complex engineering problems is effectively improved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method, device, equipment and medium for simulating engineering practice education. Background Art

[0002] Engineering education currently faces significant challenges, particularly in cultivating students' practical engineering skills. According to relevant reports, over 70% of engineering graduates nationwide find themselves lacking practical experience and problem-solving skills upon entering the workforce. This problem not only impacts graduates' employability but also hinders innovation and development in engineering education at universities.

[0003] To address these challenges, the education sector has explored various approaches to improve engineering practice education. For example, offline project-based training involves students in real engineering projects to enhance their practical skills, while role-playing teaching methods involve setting up scripts and assigning roles, allowing students to complete tasks in simulated scenarios. While these approaches have alleviated resource shortages to some extent, they still have many limitations.

[0004] Existing technologies still have significant shortcomings in addressing the shortage of resources for engineering practice education. First, offline project training requires a significant investment of human and material resources, making it difficult to meet the needs of large-scale teaching. Second, role-playing teaching methods lack personalized support, making it difficult to fully mobilize students' initiative and creativity. These issues make it difficult for students to obtain sparring opportunities with key roles such as high-level architects, product managers, and project managers. They also limit their opportunities to interact with experts in various fields, affecting the development of their comprehensive abilities. These shortcomings seriously restrict the development of students' engineering practice abilities, making it difficult to meet the comprehensive engineering competence requirements of engineering education certification. Summary of the Invention

[0005] In order to improve students' comprehensive ability to solve complex engineering problems, this application provides a simulated engineering practice education method, device, equipment and medium.

[0006] In a first aspect, the present application provides a method for simulating engineering practice education, which adopts the following technical solutions: A simulated engineering practice education method, including: Obtain the user identity of the current user, which can be a student or a teacher; When the user is a student, a role simulation instruction corresponding to the current user is received, and a target role model corresponding to the role simulation instruction is loaded. The role simulation instruction is used to trigger the current user to select multiple agents to be called, with one agent corresponding to one role model; receiving user requirements input by the current user, and generating role answers corresponding to each target role model based on the user requirements, and generating an initial product requirement document based on the user requirements and the role answers; receiving the user decision input by the current user in real time, and generating a decision effect corresponding to the user decision; Based on the user decision and the decision effect, the initial product requirement document is revised to obtain a revised product requirement document; Based on each decision effect and the modified product requirement document, each user decision is independently evaluated to obtain an independent evaluation result, and the revised product requirement document and independent evaluation result are displayed.

[0007] By adopting the above technical solutions, personalized experiences are provided to students through identity recognition, and multi-agent role models are loaded using role simulation instructions to help students understand engineering collaboration from different role perspectives; role answers and initial product requirement documents are generated based on user needs to cultivate demand analysis and management capabilities; user decisions are received in real time and decision effects are generated to enhance decision-making practice feedback; iterative optimization and critical thinking are improved through document revision and independent decision evaluation; and finally, the revised documents and evaluation results are visualized to promote knowledge integration and reflection, forming a complete practice closed loop, and effectively improving students' comprehensive ability to solve complex engineering problems.

[0008] In a possible implementation, the receiving in real time the user decision input by the current user and generating a decision effect corresponding to the user decision includes: receiving a user decision of the current user; Extracting key decision parameters in each user decision based on the user needs and user decisions; Analyze the impact parameters of each user decision on subsequent stages based on the pre-built engineering impact model; Based on the decision-making key parameters and the influencing parameters, at least two virtual project progress paths are generated, corresponding to engineering results under different decision combinations respectively, and problem decision nodes are marked based on the engineering results, and decision effects are generated.

[0009] In a possible implementation, after obtaining the revised product requirement document, the method further includes: receiving a document generation instruction from the current user and determining the completeness of the revised product requirement document; Based on the completeness, determining whether a final product requirement document can be generated; When it is determined that the final product requirement document can be generated, the final product requirement document corresponding to the current user is generated.

[0010] In one possible implementation, after independently evaluating each user decision to obtain an independent evaluation result, the method further includes: Based on the user needs and the user decisions, collecting evidence of the current user's contribution in the process of generating the product requirement document; Calling engineering training expert agents to generate agent scores and improvement suggestions based on multiple engineering capability dimensions; Receive the teacher's score, and modify the agent's score based on the teacher's score to obtain a comprehensive score, and output the comprehensive score.

[0011] In a possible implementation, generating a role answer corresponding to each target role model based on the user's needs includes: Identifying key information in the user demand, where the key information includes at least one of product information, action information, and demand information; Based on the key information, determine the scope of responsibilities and interaction guidance degree corresponding to each target role model, where the interaction guidance degree is a parameter that represents the ratio between the agent's guidance behavior and direct output behavior during the conversation; Based on the interaction guidance degree, scope of responsibilities and key information corresponding to each target role model, the corresponding intelligent agent domain knowledge base is triggered to generate a professional response to obtain the role answer corresponding to each target role model.

[0012] In a possible implementation, the method further includes: Obtain the exclusive functional tasks corresponding to each intelligent agent; Based on the user needs and the exclusive functional tasks, determine the recommended intelligent agent.

[0013] In a possible implementation, after obtaining the user identity of the current user, the method further includes: When the user is a teacher, obtaining a user instruction corresponding to the current user, wherein the user instruction is used to issue a training task, set an evaluation standard, and modify a manual score; When the user instruction is for manual scoring correction, the training information corresponding to the current user is obtained and displayed, the training information including the input content of each student, the called agent, and the evaluation result; Receive the student rating input by the current user, and include the student rating in the teacher rating of the corresponding student.

[0014] In a second aspect, the present application provides a simulated engineering practice education device, which adopts the following technical solution: A simulated engineering practice education device, comprising: An acquisition module is used to obtain the user identity of the current user, where the user identity is a student or a teacher; A loading module is used to receive a role simulation instruction corresponding to the current user when the user identity is a student, and load a target role model corresponding to the role simulation instruction, wherein the role simulation instruction is used to trigger the current user to select multiple agents to be called, with one agent corresponding to one role model; A receiving module, configured to receive user requirements input by the current user, generate role answers corresponding to each target role model based on the user requirements, and generate an initial product requirement document based on the user requirements and the role answers; A generating module, configured to receive the user decision input by the current user in real time and generate a decision effect corresponding to the user decision; A modification module, configured to modify the initial product requirement document based on the user decision and the decision effect, to obtain a modified product requirement document; The display module is used to independently evaluate each user decision based on each decision effect and the modified product requirement document to obtain an independent evaluation result, and to display the modified product requirement document and the independent evaluation result.

[0015] In a third aspect, the present application provides an electronic device, which adopts the following technical solution: An electronic device, comprising: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the method described in any one of the first aspects above.

[0016] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium, comprising: storing a computer program that can be loaded by a processor and execute any one of the methods described in the first aspect above.

[0017] In summary, this application has the following beneficial technical effects: Through identity recognition, students are provided with a personalized experience, and multi-agent role models are loaded using role simulation instructions to help students understand engineering collaboration from different role perspectives; role answers and initial product requirement documents are generated based on user needs to cultivate demand analysis and management capabilities; user decisions are received in real time and decision effects are generated to enhance decision-making practice feedback; iterative optimization and critical thinking are improved through document revision and independent decision evaluation; and finally, the revised documents and evaluation results are visualized to promote knowledge integration and reflection, forming a complete practice closed loop, and effectively improving students' comprehensive ability to solve complex engineering problems. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a flow chart of a simulated engineering practice education method provided in an embodiment of the present application; Figure 2 1 is a block diagram of a simulated engineering practice education device provided in an embodiment of the present application; Figure 3 This is a schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0019] The following is combined with Figure 1 -Attached Figure 3 This application is described in further detail.

[0020] To make the purpose, technical solutions, and advantages of the embodiments of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0021] In order to facilitate understanding of the technical solutions proposed in this application, several elements that will be introduced in the description of this application are first introduced here. It should be understood that the following introduction is only for the convenience of understanding these elements, so as to understand the content of the embodiments of this application, and does not necessarily cover all possible situations.

[0022] Currently, engineering education in my country faces severe challenges: over 70% of engineering graduates lack practical skills upon employment, severely impacting the quality of talent development and their competitiveness in the workforce. This predicament stems primarily from four bottlenecks: a severe shortage of engineering practice resources, including insufficient hardware and funding; a lack of personalized guidance for high-level engineering roles (such as architects and product managers); an incomplete interdisciplinary training system that limits students' access to experts in multiple fields; and traditional practical training, constrained by time and space, fails to meet the core competencies required by engineering education accreditation standards (such as the 11 competency requirements outlined in the "Engineering Education Accreditation Standards (2024)"), such as complex engineering problem solving and multidisciplinary collaboration.

[0023] To overcome these bottlenecks, the MAESTRO Multi-Agent Engineering Simulation and Training for Real-world Operations model was proposed. Specifically, this model uses multi-agent collaboration to simulate complex engineering roles and processes, enabling students to engage in engineering role-playing and interaction, gaining comprehensive engineering cognition and competency training on a single platform. This platform, which requires no real-person presence and is accessible to every student at a low cost, provides a completely new, ground-up solution for engineering competency training and assessment.

[0024] The present application embodiment provides a method for simulating engineering practice education, such as Figure 1 As shown, the method provided in the embodiment of the present application is performed by an electronic device, on which a simulated engineering practice education platform is installed, and the simulated engineering practice education method is applied to the simulated engineering practice education platform. The electronic device can be a server or a terminal device, wherein the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smart phone, tablet computer, laptop computer, desktop computer, etc., but is not limited thereto. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, which is not limited in the embodiment of the present application. The method includes steps S101 to S106, wherein: Step S101: Obtain the user identity of the current user.

[0025] Among them, the user identity is student or teacher.

[0026] Specifically, when the current user enters the simulated engineering practice education platform, he or she generally enters his or her account and password. When the electronic device receives the account and password entered by the current user, it identifies the identity of the current user based on the account, verifies the correctness of the account and password, and allows the current user to access the simulated engineering practice education platform after verifying that the account and password are correct. More specifically, the account and the corresponding identity in the preset database can be identified to obtain the identity of the current user corresponding to the current user. Among them, the simulated engineering practice education platform is installed on an electronic device to provide students with a simulation platform to help students understand engineering collaboration from different role perspectives.

[0027] More specifically, the simulated engineering practice education platform provides multiple trained agents. After entering the simulated engineering education platform, students can select an agent and interact with the selected agent to experience the entire process from demand analysis, design and development, test deployment to delivery. During this process, students can switch between multiple cross-disciplinary and cross-domain agents, and gain an in-depth understanding of the logic and relevance of each engineering link from different responsibilities. Among them, the agents are trained through the combination of large models and domain knowledge bases so that the trained agents can independently complete tasks within their responsibilities. For example, the project manager agent can display the project schedule, and the test engineer agent can analyze code performance and generate test reports.

[0028] Step S102: When the user identity is a student, receive a role simulation instruction corresponding to the current user, and load a target role model corresponding to the role simulation instruction.

[0029] The role simulation instruction is used to trigger the current user to select multiple agents to be called, and each agent corresponds to a role model. For example, the role model corresponding to the test engineer agent is the test engineer model, and the role model corresponding to the project manager agent is the project manager model. More specifically, the intelligent agents may include: module implementation planning engineers, who are responsible for development environment configuration, task decomposition, development specification formulation, risk prediction and response; module implementation engineers, who are responsible for module coding implementation, API encapsulation, unit test writing, and annotation specifications; module test tuning engineers, who are responsible for unit / interface test design and execution, bug location and repair, code / design refactoring, and performance optimization; module integration acceptance engineers, who are responsible for module-level integration, interface joint debugging, function demonstration, and review participation; module implementation planning mentors, who are responsible for guiding environment configuration and specification formulation, reviewing the rationality of task decomposition, guiding risk identification and analysis, and sharing practical experience and best practices; module implementation guidance mentors, who are responsible for reviewing key codes and designs, providing implementation method guidance, analyzing technical difficulties and solutions, and organizing / participating in code reviews and design reviews; test tuning guidance mentors, who are responsible for guiding automated test design, guiding problem analysis and location, providing optimization and refactoring ideas, and reviewing test coverage and quality; module integration guidance mentors, who are responsible for assisting in solving cross-module interface problems and guiding integration test design Design, organize / participate in final acceptance review, provide document specifications and feedback; development engineers, responsible for providing software code writing, testing, and debugging support; development engineers, responsible for providing hardware implementation, testing, and debugging support; development engineers, responsible for providing data processing and model implementation support; system architects, responsible for providing overall system architecture design support; module designers, responsible for providing detailed design support for individual modules; product managers, responsible for defining product requirements and features, and evaluating implementation results; QA / test engineers, responsible for designing test strategies and use cases, executing tests, and reporting issues; DevOps engineers, responsible for setting up development and testing environments, and establishing CI / CD processes; integration engineers, responsible for coordinating interface docking and integration between different modules; operations engineers, responsible for system deployment and operation and maintenance; security experts, responsible for reviewing security risks in code and design; technical documentation engineers, responsible for providing document templates and standards, and reviewing the quality of technical documentation; user experience designers, responsible for providing user interface design specifications, and evaluating user interaction experience; data engineers, responsible for providing data models and data flow design.

[0030] After students log in to the simulated engineering practice education platform, they generally select an intelligent agent first, and then enter their own needs or doubts so that the selected intelligent agent can answer. That is, when the user identity of the current user is obtained and the current user is identified as a student, the role simulation instruction of the current user is received, and the intelligent agent in the role simulation instruction is identified, and the role model corresponding to each intelligent agent is loaded, so as to obtain the target role model corresponding to the role simulation instruction.

[0031] Step S103: receiving the user requirements input by the current user, and generating role answers corresponding to each target role model based on the user requirements, and generating an initial product requirement document based on the user requirements and the role answers.

[0032] After the target role model corresponding to the current user is loaded (that is, after the student has completed the role model call), a text input box appears in the center of the simulated engineering practice education platform's interface, allowing students to enter specific user requirements, such as "Design a smart fitness app for young people with social features." Upon receiving the student's user requirements, the electronic device distributes them to each of the loaded target role models. Each agent, based on its role characteristics and built-in knowledge, uses natural language processing algorithms to generate a corresponding role response. For example, the product manager agent might respond, "The overall architecture should include user modules, fitness course modules, social interaction modules, data analysis modules, etc., with social features prioritized for ease of use." The programmer agent responds, "From a technical implementation perspective, the backend adopts a cloud server architecture, the front end incorporates the React Native framework for cross-platform development, and the social features utilize mature instant messaging APIs." The electronic device then integrates these role responses and automatically generates an initial product requirements document according to a pre-set document template. This document covers the project background, target users, functional requirements, and initial technical concepts, and is displayed as structured text in the interface's sidebar for easy review and modification by students.

[0033] More specifically, a possible implementation of the embodiment of the present application generates a role answer corresponding to each target role model based on user needs, including: Identify key information in user needs, where the key information includes at least one of product information, action information, and demand information; Based on the key information, the scope of responsibilities and interaction guidance degree corresponding to each target role model are determined. The interaction guidance degree is a parameter that measures the ratio between the agent's guidance behavior and direct output behavior during the dialogue process. Based on the interaction guidance degree, scope of responsibilities and key information corresponding to each target role model, the corresponding intelligent agent domain knowledge base is triggered to generate professional responses to obtain the role answers corresponding to each target role model.

[0034] Specifically, when an electronic device receives a user's input of a user's needs, it will first pre-process the text content of the user's needs, such as removing irrelevant punctuation marks and special characters to make the text content more regular. Then, using the lexical analysis and syntactic analysis tools in natural language processing technology, the text content is broken down into individual words and phrases, and the grammatical relationships between them are analyzed. Next, through a pre-set keyword library and semantic understanding model, it is determined whether the text contains key information related to product information (such as product name, type, features, etc.), action information (such as development, design, optimization, etc.), and demand information (such as functional requirements, performance requirements, time requirements, etc.). For example, if the user's need is to "design a smart watch", the electronic device will recognize that "smart watch" is product information and "design" is action information, and there is no demand information.

[0035] After identifying key information, the electronic device matches it with the attributes and capabilities of each target role model. For each target role model (such as product manager, marketing manager, programmer, etc.), the electronic device pre-stores the corresponding responsibilities. For example, a product manager's responsibilities include product planning, demand analysis, and resource coordination; a programmer's responsibilities include code writing, technical implementation, and problem debugging. By comparing key information with the responsibilities of each role model, the primary responsibilities of each target role model are determined based on the current user demand scenario.

[0036] When determining the scope of responsibility, the electronic device determines the degree of interaction guidance based on the target role model and the complexity of the current key information. For complex requirements that require in-depth user thought and participation, such as designing innovative product features, the product manager role model may set a higher degree of interaction guidance, encouraging more reflection and discussion rather than providing direct answers. For relatively clear technical implementation issues, the programmer role model may directly provide technical solutions, with a lower degree of interaction guidance. Specifically, when the user requirement is less complete (e.g., describing only the product name or core features but lacking technical constraints), the interaction guidance level increases, and the agent prioritizes actively guiding the user to provide additional information through open-ended questions, option lists, or hypothetical scenarios. When the input information is more complete (e.g., a clear feature list, user profile, and performance indicators are already defined), the interaction guidance level decreases, and the agent switches to directly providing technical solutions, architecture designs, or execution instructions. More specifically, for the required fields of the user requirement (product information, action information, and requirement information), the percentage of completed fields is calculated. For example: In the above example, the filled fields are product information and action information, and the unfilled fields are demand information, so the filled fields account for 2 / 3, and the interaction guidance degree is 1 / 3.

[0037] Furthermore, based on each target role model's interaction guidance, responsibilities, and key information, the corresponding agent domain knowledge base is found. Based on the interaction guidance, the agent determines how to retrieve information from the knowledge base and generate responses. Each target role model has its own dedicated domain knowledge base, which stores the role's expertise, experience, and case studies in the relevant field.

[0038] Specifically, if the degree of interaction guidance is high, the electronic device can extract some guiding questions, ideas, or suggestions from the knowledge base to guide users to further think and discuss. For example, the product manager role model may extract questions such as "What are the outstanding features of smart watches" from the knowledge base to guide users. If the degree of interaction guidance is low, specific solutions, technical solutions, or suggestions that match the key information are directly retrieved from the knowledge base and organized into a suitable language form for output. Furthermore, the information obtained from the knowledge base is filtered and organized according to the scope of responsibilities to ensure that the output content is consistent with the responsibilities of the role in the current scenario. The generated professional responses are presented to the user as the role answers corresponding to each target role model.

[0039] Step S104: receiving the user decision input by the current user in real time, and generating a decision effect corresponding to the user decision.

[0040] After the initial product requirements document is generated, it is displayed. After viewing the initial product requirements document, students will again input requirements or questions, and the input at this time can be unified into user decisions. The electronic device receives the user decisions entered by the current user in real time and can combine real-time data analysis and simulation technology to display different results of project progress based on user decisions, thereby providing feedback on the effectiveness of students' decisions. This allows students to understand the impact of their decisions throughout the entire engineering lifecycle. For example, if a student chooses an unreasonable technical solution during the architecture design phase, the electronic device will reflect the impact of this decision in the form of performance issues or quality defects during the subsequent development and testing phases.

[0041] Specifically, a possible implementation of the embodiment of the present application is to receive the user decision input by the current user in real time in this step, and generate a decision effect corresponding to the user decision, including: Receive the user decision of the current user; Based on user needs and user decisions, extract the key decision parameters in each user decision; Analyze the impact parameters of each user decision on subsequent stages based on the pre-built engineering impact model; Based on the key decision parameters and influencing parameters, at least two virtual project progress paths are generated, corresponding to the engineering results under different decision combinations. The problem decision nodes are marked based on the engineering results, and the decision effects are generated.

[0042] After receiving a user decision, the input can be preprocessed, for example, by removing extra spaces and special characters to standardize the format. Natural language processing techniques are then used to analyze the input text and extract key information to determine key decision parameters, such as product information, action information, and requirements. Real-time data analysis is also performed, combining the initial product requirements document with other relevant data stored in the system (such as industry standards and historical project data). For example, the difference between the user's decision and the original requirements can be compared to assess the potential impact of the decision on project cost, schedule, and technical difficulty.

[0043] Furthermore, a pre-built engineering impact model can be used to input the extracted key decision parameters into the corresponding engineering impact model. This engineering impact model can be a specialized simulation model based on different engineering fields (such as software engineering, hardware engineering, and construction engineering). For example, for a software engineering project, the engineering impact model may include submodules such as software architecture simulation, code writing simulation, and testing process simulation. The engineering impact model simulates the progress of the project at different stages based on user decisions and outputs the impact parameters of each user decision on subsequent stages, such as increased development difficulty, extended testing time, and increased launch risk probability, recorded quantitatively or qualitatively. During the simulation process, the engineering impact model considers the interactions and influences between various factors, such as the impact of technical solution selection on development efficiency and the impact of changes in development progress on testing time. The simulation process can be presented to students through visualization, such as animations and charts, allowing students to intuitively see how the project performs under different decisions.

[0044] Furthermore, based on the extracted key decision parameters and the analyzed influencing parameters, a path generation algorithm is applied to generate at least two virtual project progress paths. For example, one path follows the user's current decision, while the other maintains the original plan. During path generation, the logical relationships and chronological order between each stage are considered to simulate the actual project progress under different decision combinations. For each virtual project progress path, the simulation results can be used to determine whether problems or risks have occurred. If a decision node leads to project delays, cost overruns, or quality degradation, the node is marked as a problem node. The system presents the generated virtual project progress paths to the user in a visual format, such as a flowchart or Gantt chart. A detailed description is provided for each problem node, including the problem type, cause, and specific impact on the project. A summary report of the decision results is generated in text and charts, clearly presenting the project results under different decision combinations and helping users intuitively understand the impact of their decisions on the project.

[0045] Step S105: Based on the user's decision and the decision effect, the initial product requirement document is revised to obtain a revised product requirement document.

[0046] After viewing the decision-making effect display, the current user, i.e., the student, can modify the decision content directly in the original decision input box if he / she believes that the current decision needs to be adjusted and optimized. The electronic device will regenerate a new decision effect based on the received signal and compare the changes before and after. Based on the latest user decision and its effect, the text processing algorithm is used to update the relevant sections and clauses in the initial product requirements document, such as adjusting the priority of functional modules, refining technical implementation details, modifying project time nodes, etc. The modified complete product requirements document will be re-displayed in the sidebar, replacing the original initial version, and the document version change information will be recorded for easy retrospective review. If the student does not enter the modified decision content, the initial product requirements document will be supplemented directly based on the user decision and the decision effect to obtain the modified product requirements document.

[0047] Step S106: Based on each decision effect and the modified product requirement document, each user decision is independently evaluated to obtain an independent evaluation result, and the modified product requirement document and the independent evaluation result are displayed.

[0048] In addition to the vertical waterfall process, the simulated engineering practice education platform also includes a horizontal assessment module. This module reviews each student's user decision and generates an analysis report to provide guidance and improvement suggestions for each step. This module covers multiple dimensions of expert consulting engineering competency certification: economic decision-making, environmental, legal, ethical, and user perspectives. Through consultation, students can modify engineering documents based on inspiring and valuable expert advice. Specifically, after each user decision is entered and the revised product requirements document is obtained, the horizontal assessment module scores each user decision based on its corresponding decision effect and the current final product requirements document. These dimensions include, but are not limited to, technical feasibility (e.g., whether the selected technology is mature and can be implemented), economic rationality (whether it exceeds the budget and resource utilization), time adaptability (whether the project schedule requirements are met), and user needs satisfaction (whether it meets the initial user needs and subsequent adjustments). Each dimension is assigned a certain weight, and a weighted calculation is used to produce an independent evaluation result for each user decision, which is presented as a score or grade (e.g., excellent, good, qualified, and unqualified).

[0049] Furthermore, the revised product requirement document is fully displayed, and each user decision and its corresponding independent evaluation results are listed in a list on the right side of the document, so that students can summarize their experiences and lessons and provide reference for the next round of simulation practice.

[0050] The embodiments of the present application provide a method for simulating engineering practice education, which provides students with a personalized experience through identity recognition, uses role simulation instructions to load multi-agent role models, and helps students understand engineering collaboration from different role perspectives; generates role answers and initial product requirement documents based on user needs to cultivate demand analysis and management capabilities; receives user decisions in real time and generates decision effects to enhance decision-making practice feedback; improves iterative optimization and critical thinking through document revision and independent decision evaluation; and finally visualizes the revised documents and evaluation results to promote knowledge integration and reflection, forming a complete practice closed loop, and effectively improving students' comprehensive ability to solve complex engineering problems.

[0051] In another possible implementation of the embodiment of the present application, after obtaining the user identity of the current user in step S101, the method further includes: When the user is a teacher, obtain the user instruction corresponding to the current user. The user instruction is used to issue a training task, set evaluation criteria, or modify manual scoring. When the user instruction is manual scoring correction, the training information corresponding to the current user is obtained and displayed. The training information includes the input content of each student, the called agent, and the evaluation results; Receive the student rating entered by the current user and add the student rating to the corresponding student's teacher rating.

[0052] When the current user is identified as a teacher and the account password is correct, the teacher enters the simulation engineering practice education platform. A function option panel is presented on the interface of the simulation engineering practice education platform, and the three main function buttons of "Publish training tasks", "Set evaluation standards" and "Manual score correction" are clearly listed on the panel. The teacher can input user instructions by clicking the corresponding button with the mouse. When the teacher clicks a button, the electronic device pops up the corresponding detailed operation window according to the received signal. For example, clicking the "Publish training task" button will pop up a window containing input boxes such as task title, task description, task requirements, deadline, etc., in which the teacher can fill in the relevant information of the training task in detail; clicking the "Set evaluation standards" button will display an editable evaluation indicator system interface, in which the teacher can add, modify or delete evaluation indicators and set the weight of each indicator; clicking the "Manual score correction" button will enter the manual score correction operation page and wait for subsequent operations.

[0053] Furthermore, upon receiving a user instruction indicating that the teacher has selected "manual scoring correction," the system searches the backend database for training information for all students assigned to that teacher. This information includes requirements analysis documents, design plans, and decision-making records submitted at different stages. It also obtains information about the agents invoked by the students during training, such as the role models (product manager, programmer, etc.), the number of invocations, and the duration of these invocations. The system also automatically generates evaluation results, including scores, grades, and descriptions of the students' completion of each task. The electronic device organizes and categorizes this training information, displaying it clearly on the user interface in a table or list format, making it easy for teachers to review and compare each student's progress. Teachers can further review and manipulate the displayed information using scroll bars and filtering functions.

[0054] Furthermore, after displaying each student's training information, the electronic device will control the simulated engineering practice education platform to set a rating input box next to each student's information entry, where the teacher can enter the student's rating. The rating can be a specific score (such as a percentage, a ten-point scale, etc.) or a grade (such as excellent, good, average, pass, fail, etc.). After the teacher enters the rating, clicks the "Confirm" or "Submit" button, and the electronic device will receive the student's rating entered by the teacher in real time. The electronic device will then associate the rating with the corresponding student identity information and store it in the corresponding teacher rating field in the background database. The electronic device can also provide a rating record viewing function, so that teachers can review the ratings they have given at any time and modify and adjust them if necessary.

[0055] Furthermore, if the teacher selects the user instruction of "Publish Training Task", the electronic device will control the simulation engineering practice education platform to pop up a detailed task creation window. Teachers can select targeted questions from the system's built-in question bank. These questions are classified according to different engineering ability dimensions, such as system analysis ability, project management ability, etc. Teachers can also edit the content of the questions themselves and clearly define the training goal as improving one or several engineering abilities of students. At the same time, teachers can set task deadlines, task descriptions, the form of results to be submitted, and other information. The system will synchronize this task information to the student end in real time, and students can see new training tasks on their own operation interface.

[0056] If the teacher selects the "Set Evaluation Criteria" user instruction, the electronic device will control the Simulated Engineering Practice Education Platform to display an editable evaluation indicator system interface. Teachers can adjust the evaluation indicators and their weights based on different engineering capability dimensions. For example, for tasks that focus on cultivating system design capabilities, teachers can increase the weight of indicators related to system design and control the Simulated Engineering Practice Education Platform to store these evaluation criteria in the backend database for evaluation after students complete the task.

[0057] Another possible implementation of the embodiment of the present application, after generating the role answer corresponding to each target role model in step S103, further includes: Obtain the exclusive functional tasks corresponding to each intelligent agent; Determine the recommended agent based on user needs and exclusive functional tasks.

[0058] When the electronic equipment is initialized on the simulated engineering practice education platform, it reads the specific functional task information corresponding to each agent from the built-in agent configuration database. The agent configuration database is pre-built and maintained based on the division of labor and responsibilities of different engineering roles in actual projects. For example, the specific functional tasks of the product manager agent include but are not limited to market research, competitive product analysis, product planning, demand definition and priority sorting; the specific functional tasks of the programmer agent cover code writing, software architecture design, algorithm optimization, debugging and maintenance; the specific functional tasks of the marketing manager agent include market positioning, target customer group analysis, brand promotion strategy formulation, marketing channel expansion, etc. When a user initiates a demand, the agent configuration platform can accurately extract the specific functional task text description corresponding to each agent based on the currently activated agent list, and make associated tags in the background to facilitate subsequent processing.

[0059] Furthermore, after obtaining the user demand text, natural language processing technology is used to analyze it and extract key demand information, such as the product types involved, the functional goals expected to be achieved, the technical challenges faced, the required marketing direction, etc., and the matching degree of these key demand information is calculated with the exclusive functional tasks of each intelligent agent obtained in the previous step, and the intelligent agent with a high matching degree with the user demand is determined as the recommended intelligent agent, which is presented to the user on the operation interface in a highlighted manner (such as bright icons, bold font annotations, etc.) or ranked at the top of the recommendation list, so that the user can refer to the answers of these intelligent agents first to solve the problem.

[0060] In another possible implementation of the embodiment of the present application, after obtaining the revised product requirement document in step S105, the method further includes: Receive document generation instructions from the current user and determine the completeness of the revised product requirement document; Based on the completeness, determine whether the final product requirement document can be generated; When it is determined that the final product requirement document can be generated, the final product requirement document corresponding to the current user is generated.

[0061] After students receive the revised product requirements document, a "Generate Final Document" button appears on the Simulated Engineering Practice Education Platform. Clicking this button is considered issuing a document generation instruction, and the electronic device receives the document generation instruction in real time. Upon receiving the document generation instruction, the electronic device controls the Simulated Engineering Practice Education Platform to initiate the integrity assessment process. Specifically, the Simulated Engineering Practice Education Platform will check the revised product requirements document based on a set of pre-set degree measurement standards. These degree measurement standards cover many aspects, such as whether the functional requirements are clear and comprehensive, including the core functions and auxiliary functions that the product should have, as well as the interaction logic between each function; whether the performance requirements are detailed, such as indicators such as response time, throughput, and stability; whether the user experience requirements are mentioned, such as interface friendliness and ease of operation; and whether a preliminary plan for technical implementation exists, involving basic information such as the selected technical architecture and development language. The Simulated Engineering Practice Education Platform checks and scores these key points one by one, and finally comprehensively determines the completeness value of the document.

[0062] Furthermore, if the completeness reaches or exceeds a pre-set threshold (e.g., a high completeness score of 80 or above), the Simulated Engineering Practice Education Platform determines that the final product requirements document can be generated. At this point, a prompt box will pop up on the Simulated Engineering Practice Education Platform interface, informing the current user that "the current document completeness meets the requirements and the final product requirements document can be generated." If the completeness does not meet the standard, the Simulated Engineering Practice Education Platform will pop up a warning box stating "the document is not complete enough and the final product requirements document cannot be generated." It will also list the missing or weak parts in detail, such as "mobile terminal adaptation performance requirements are missing, please supplement them," and guide the user back to the document revision stage to continue optimization.

[0063] Furthermore, once the simulated engineering practice education platform determines that the final product requirements document can be generated, the electronic device automatically initiates the document generation process. Specifically, the simulated engineering practice education platform optimizes the format of the revised product requirements document, standardizing fonts, font sizes, paragraph spacing, and other aspects for a more standardized and professional appearance. Content is then integrated according to a pre-defined document template, ensuring the proper order of each section. For example, the opening section begins with a project overview, followed by functional requirements, performance requirements, technical implementation solutions, and project schedules, resulting in the final product requirements document for the current user.

[0064] In another possible implementation of the embodiment of the present application, after independently evaluating each user decision to obtain an independent evaluation result in step S106, the method further includes: Based on user needs and user decisions, collect evidence of the current user's contribution to the product requirement document generation process; Calling engineering training expert agents to generate agent scores and improvement suggestions based on multiple engineering capability dimensions; Receive the teacher's score, and modify the agent's score based on the teacher's score to obtain a comprehensive score, and output the comprehensive score.

[0065] Among them, contribution evidence is the relevant information and basis that records the user's influence on the document content during the product requirement document generation process. It is used to measure the user's contribution in the process and is an important basis for evaluating the user's role in the project.

[0066] Specifically, when the user inputs user requirements and makes a series of user decisions, the electronic device records the user operations of the current user in the process of generating the product requirement document in real time. User operations include text editing behaviors (such as adding / modifying functional requirements and non-functional requirements), intelligent agent interactions (adopted suggestions, rejected proposals) and decision-making time points (such as actively proposing technical constraints during the requirement review stage), and counts the percentage of newly added / modified requirement items in the user operations in the complete requirement document (such as increasing from the initial 20 to 35, a coverage increase of 75%). Based on the newly added / modified requirement items and coverage, evidence of the current user's contribution to the product requirement document generation process is obtained.

[0067] After collecting evidence of contribution, the electronic device invokes an engineering training expert agent and, combining the evaluation results of multiple engineering training patent agents, generates an agent scoring report. This system visually displays the student's score distribution across various engineering competency dimensions using a radar chart, accompanied by textual explanations detailing strengths and areas for improvement, enabling students to gain a comprehensive understanding of their engineering proficiency. The engineering training expert agent encompasses multiple specialized agents encompassing economic decision-making, environmental, legal, ethical, and user perspectives. Each agent operates based on pre-built industry standards, professional knowledge systems, and evaluation algorithms. For example, the economic decision-making agent deeply explores the details of the user's decision-making regarding resource allocation, cost budgeting, and benefit estimation. It then combines market trends, industry cost averages, and other big data to quantitatively score the rationality of the user's economic decision. Furthermore, it analyzes the shortcomings of the user's existing strategy by comparing it to best practices and provides practical improvement suggestions, such as "Optimizing procurement channels can reduce raw material costs by approximately [X]%." The environmental agent focuses on the potential impact of the project on the ecology, reviews user solutions from the perspectives of energy consumption, waste emissions, and the selection of sustainable materials, gives scores based on green engineering standards, and proposes energy-saving alternatives for high-energy-consuming links. The legal compliance agent compares user designs with current laws, regulations, and industry standards, marking potential risk points for violations. It uses rigorous interpretation of legal provisions to help students comply with regulations and ensure that the project is carried out within the legal framework. The moral and ethical agent examines whether the project involves ethical issues such as privacy infringement, data abuse, and lack of social responsibility, and guides students to establish correct values. The user perspective agent simulates the end-user usage scenario, experiences product design from the aspects of interactive convenience, visual comfort, and functional usability, and proposes optimization paths to improve user satisfaction.

[0068] Furthermore, teachers can log in to the Simulated Engineering Practice Education Platform to provide a teacher rating. The Simulated Engineering Practice Education Platform captures the teacher's input scores in real time and combines them with the agent's scores based on a pre-set weighting algorithm. For example, if the teacher's score is weighted 40% and the agent's score is weighted 60%, and the teacher's score is 85 points and the agent's overall score is 78 points, the overall score = 85 × 40% + 78 × 60% = 80.8 points.

[0069] After obtaining the comprehensive score, the simulation engineering practice education platform can use a bar chart to compare the agent score, teacher score and comprehensive score, and attach improvement suggestions given by the agent and teacher from different perspectives, so that students can gain a comprehensive understanding of their own performance and accurately anchor the direction of subsequent efforts.

[0070] The above embodiment introduces a simulated engineering practice education method from the perspective of method flow, and the following embodiment introduces a simulated engineering practice education device from the perspective of virtual modules or virtual units. Please refer to the following embodiment for details.

[0071] See also Figure 2 The simulated engineering practice education device 20 may specifically include: an acquisition module 201, a loading module 202, a receiving module 203, a generation module 204, a modification module 205, and a display module 206, wherein: A simulated engineering practice education device 20, comprising: The acquisition module 201 is used to obtain the user identity of the current user, which can be a student or a teacher; The loading module 202 is used to receive the role simulation instruction corresponding to the current user and load the target role model corresponding to the role simulation instruction when the user identity is a student. The role simulation instruction is used to trigger the current user to select multiple agents to be called, and one agent corresponds to one role model; The receiving module 203 is configured to receive user requirements input by the current user, generate role answers corresponding to each target role model based on the user requirements, and generate an initial product requirement document based on the user requirements and the role answers; The generating module 204 is used to receive the user decision input by the current user in real time and generate the decision effect corresponding to the user decision; A modification module 205 is used to modify the initial product requirement document based on the user's decision and the decision effect to obtain a modified product requirement document; The display module 206 is used to independently evaluate each user decision based on each decision effect and the modified product requirement document to obtain an independent evaluation result, and display the modified product requirement document and the independent evaluation result.

[0072] In one possible implementation of the embodiment of the present application, the generation module 204 receives the user decision input by the current user in real time and generates a decision effect corresponding to the user decision, specifically for: Receive the user decision of the current user; Based on user needs and user decisions, extract the key decision parameters in each user decision; Analyze the impact parameters of each user decision on subsequent stages based on the pre-built engineering impact model; Based on the key decision parameters and influencing parameters, at least two virtual project progress paths are generated, corresponding to the engineering results under different decision combinations. The problem decision nodes are marked based on the engineering results, and the decision effects are generated.

[0073] In a possible implementation of the embodiment of the present application, the simulated engineering practice education device 20 further includes a first determination module, specifically configured to: Receive document generation instructions from the current user and determine the completeness of the revised product requirement document; Based on the completeness, determine whether the final product requirement document can be generated; When it is determined that the final product requirement document can be generated, the final product requirement document corresponding to the current user is generated.

[0074] In a possible implementation of the embodiment of the present application, the simulated engineering practice education device 20 further includes a calling module, specifically configured to: Based on user needs and user decisions, collect evidence of the current user's contribution to the product requirement document generation process; Calling engineering training expert agents to generate agent scores and improvement suggestions based on multiple engineering capability dimensions; Receive the teacher's score, and modify the agent's score based on the teacher's score to obtain a comprehensive score, and output the comprehensive score.

[0075] In one possible implementation of the embodiment of the present application, when the receiving module 203 generates a role answer corresponding to each target role model based on user needs, it is specifically configured to: Identify key information in user needs, where the key information includes at least one of product information, action information, and demand information; Based on the key information, the scope of responsibilities and interaction guidance degree corresponding to each target role model are determined. The interaction guidance degree is a parameter that measures the ratio between the agent's guidance behavior and direct output behavior during the dialogue process. Based on the interaction guidance degree, scope of responsibilities and key information corresponding to each target role model, the corresponding intelligent agent domain knowledge base is triggered to generate professional responses to obtain the role answers corresponding to each target role model.

[0076] In a possible implementation of the embodiment of the present application, the simulated engineering practice education device 20 further includes a second determination module, specifically configured to: Obtain the exclusive functional tasks corresponding to each intelligent agent; Determine the recommended agent based on user needs and exclusive functional tasks.

[0077] In one possible implementation of the embodiment of the present application, the simulated engineering practice education device 20 further includes a scoring module, specifically configured to: When the user is a teacher, obtain the user instruction corresponding to the current user. The user instruction is used to issue a training task, set evaluation criteria, or modify manual scoring. When the user instruction is manual scoring correction, the training information corresponding to the current user is obtained and displayed. The training information includes the input content of each student, the called agent, and the evaluation results; Receive the student rating entered by the current user and add the student rating to the corresponding student's teacher rating.

[0078] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0079] The embodiment of the present application also introduces an electronic device from the perspective of a physical device, such as Figure 3 As shown, Figure 3 The electronic device 300 shown includes a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, for example, via a bus 302. Optionally, the electronic device 300 may further include a transceiver 304. It should be noted that in actual applications, the number of transceivers 304 is not limited to one, and the structure of the electronic device 300 does not constitute a limitation on the embodiments of the present application.

[0080] Processor 301 can be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic device, transistor logic device, hardware component, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 301 can also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0081] Bus 302 may include a path for transmitting information between the above components. Bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. Bus 302 may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, Figure 3 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0082] The memory 303 may be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0083] The memory 303 is used to store application code for executing the solution of the present application, and the execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the content shown in the above method embodiment.

[0084] Among them, electronic devices include but are not limited to: mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc., and can also be servers, etc. Figure 3 The electronic device shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0085] An embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding contents of the aforementioned method embodiment.

[0086] It should be understood that although the steps in the flowcharts of the accompanying drawings are shown in sequence as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the flowcharts of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0087] The above are only some of the implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A simulated engineering practice education method, characterized in that: include: Obtain the user identity of the current user, which can be a student or a teacher; When the user is a student, a role simulation instruction corresponding to the current user is received, and a target role model corresponding to the role simulation instruction is loaded. The role simulation instruction is used to trigger the current user to select multiple agents to be called, with one agent corresponding to one role model; receiving user requirements input by the current user, and generating role answers corresponding to each target role model based on the user requirements, and generating an initial product requirement document based on the user requirements and the role answers; receiving the user decision input by the current user in real time, and generating a decision effect corresponding to the user decision; Based on the user decision and the decision effect, the initial product requirement document is revised to obtain a revised product requirement document; Based on each decision effect and the modified product requirement document, each user decision is independently evaluated to obtain an independent evaluation result, and the revised product requirement document and independent evaluation result are displayed.

2. The simulated engineering practice education method according to claim 1, characterized in that: The receiving in real time the user decision input by the current user and generating a decision effect corresponding to the user decision includes: receiving a user decision of the current user; Extracting key decision parameters in each user decision based on the user needs and user decisions; Analyze the impact parameters of each user decision on subsequent stages based on the pre-built engineering impact model; Based on the decision-making key parameters and the influencing parameters, at least two virtual project progress paths are generated, corresponding to engineering results under different decision combinations respectively, and problem decision nodes are marked based on the engineering results, and decision effects are generated.

3. The simulated engineering practice education method according to claim 1 or 2, characterized in that: After obtaining the revised product requirement document, the method further includes: receiving a document generation instruction from the current user and determining the completeness of the revised product requirement document; Based on the completeness, determining whether a final product requirement document can be generated; When it is determined that the final product requirement document can be generated, the final product requirement document corresponding to the current user is generated.

4. The simulated engineering practice education method according to claim 3, characterized in that: After independently evaluating each user decision to obtain an independent evaluation result, the method further includes: Based on the user needs and the user decisions, collecting evidence of the current user's contribution in the process of generating the product requirement document; Calling engineering training expert agents to generate agent scores and improvement suggestions based on multiple engineering capability dimensions; Receive the teacher's score, and modify the agent's score based on the teacher's score to obtain a comprehensive score, and output the comprehensive score.

5. The simulated engineering practice education method according to claim 1, characterized in that: Generating a role answer corresponding to each target role model based on the user needs includes: Identifying key information in the user demand, where the key information includes at least one of product information, action information, and demand information; Based on the key information, determine the scope of responsibilities and interaction guidance degree corresponding to each target role model, where the interaction guidance degree is a parameter that represents the ratio between the agent's guidance behavior and direct output behavior during the conversation; Based on the interaction guidance degree, scope of responsibilities and key information corresponding to each target role model, the corresponding intelligent agent domain knowledge base is triggered to generate a professional response to obtain the role answer corresponding to each target role model.

6. The simulated engineering practice education method according to claim 5, characterized in that: The method further comprises: Obtain the exclusive functional tasks corresponding to each intelligent agent; Based on the user needs and the exclusive functional tasks, determine the recommended intelligent agent.

7. The simulated engineering practice education method according to claim 1, characterized in that: After obtaining the user identity of the current user, the method further includes: When the user is a teacher, obtaining a user instruction corresponding to the current user, wherein the user instruction is used to issue a training task, set an evaluation standard, and modify a manual score; When the user instruction is for manual scoring correction, the training information corresponding to the current user is obtained and displayed, the training information including the input content of each student, the called agent, and the evaluation result; Receive the student rating input by the current user, and include the student rating in the teacher rating of the corresponding student.

8. A simulated engineering practice education device, characterized in that: include: An acquisition module is used to obtain the user identity of the current user, where the user identity is a student or a teacher; A loading module is used to receive a role simulation instruction corresponding to the current user when the user identity is a student, and load a target role model corresponding to the role simulation instruction, wherein the role simulation instruction is used to trigger the current user to select multiple agents to be called, with one agent corresponding to one role model; A receiving module, configured to receive user requirements input by the current user, generate role answers corresponding to each target role model based on the user requirements, and generate an initial product requirement document based on the user requirements and the role answers; A generating module, configured to receive the user decision input by the current user in real time and generate a decision effect corresponding to the user decision; A modification module, configured to modify the initial product requirement document based on the user decision and the decision effect, to obtain a modified product requirement document; The display module is used to independently evaluate each user decision based on each decision effect and the modified product requirement document to obtain an independent evaluation result, and to display the modified product requirement document and the independent evaluation result.

9. An electronic device, characterized in that: The electronic device includes: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the simulated engineering practice education method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed in a computer, the computer is caused to execute the simulated engineering practice education method according to any one of claims 1 to 7.

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