Application design conversion method and system based on science and technology experience

Abstract

This invention discloses a method and system for application design transformation based on technological experience, relating to the field of digital technology. The method includes: collecting open-source technology product data via the internet to construct a digital technology experience center; providing online technology experiences for students to obtain experience monitoring data; designing online courses based on a technology application creation platform to obtain online teaching courses; teaching students to obtain technology application concept design proposals; conducting simulation verification and evaluation through a mechanism simulation system to obtain simulation evaluation results for the design proposals; presenting the technology application concept design proposals in a roadshow to obtain a design demonstration dataset; conducting online expert evaluation; and transforming the technology application concept design proposals into innovative achievements based on the evaluation results. This addresses the technical problems of limited teaching resources, limited practical scenarios, and restricted technological innovation capabilities in existing science and technology education, achieving the technical effect of enriching technological experiences and enhancing technological innovation capabilities.

Description

Technical Field

[0001] This application relates to the field of digital technology, and in particular to application design transformation methods and systems based on technological experience. Background Technology

[0002] In the field of science and technology education, cultivating students' ability to design and apply technological products is crucial. This not only helps stimulate students' innovative thinking but also supplies the future technology industry with talents possessing practical skills and innovative spirit. Currently, students' technological application design abilities are mainly cultivated through traditional classroom teaching and laboratory practice. However, traditional methods are limited by the finite teaching resources and the monotonous practical environment, making it difficult to provide rich and diverse technological experiences and real-world practical scenarios, thus limiting students' learning outcomes and innovative abilities.

[0003] At present, science and technology education faces challenges such as limited teaching resources, limited practical scenarios, and restricted technological innovation capabilities. Summary of the Invention

[0004] This application provides a method and system for application design transformation based on technological experience. By collecting data from open-source technology products, constructing a digital experience center, students experience the products in the digital experience center, acquiring monitoring data, designing online courses based on the monitoring data, and forming conceptual design plans through online course teaching. The conceptual design plans are then simulated and evaluated. After passing the evaluation, the design plans are presented in a roadshow to acquire demonstration data. After expert evaluation, outstanding design plans are promoted for transformation. These technical means solve the technical problems of limited teaching resources, single practical scenarios, and limited technological innovation capabilities in existing science and technology education, and achieve the technical effect of enriching technological experience and improving technological innovation capabilities.

[0005] This application provides a method for transforming application design based on technological experience, comprising: collecting open-source technology product data via the Internet to construct a digital technology experience center; providing online technology experiences to students based on the digital technology experience center to obtain experience monitoring data; designing online courses based on the experience monitoring data using a technology application creation platform to obtain online teaching courses; teaching students based on the online teaching courses using the technology application creation platform to obtain a technology application concept design; conducting simulation verification and evaluation of the technology application concept design using a mechanism simulation system to obtain simulation evaluation results; presenting the technology application concept design in a roadshow based on the simulation evaluation results to obtain a design demonstration dataset; conducting online expert evaluation based on the design demonstration dataset to obtain design evaluation results; and transforming the technology application concept design into innovative achievements based on the design evaluation results.

[0006] In one possible implementation, open-source technology product data is collected via the Internet to construct a digital technology experience center, and the following processes are performed: open-source technology product data is collected via the Internet to obtain a technology product database; the technology product database is preprocessed in multiple dimensions to obtain a technology dataset; the technology dataset is imported into the digital experience center to generate the digital technology experience center.

[0007] In a possible implementation, the technology product database is preprocessed in multiple dimensions to obtain a technology dataset, and the following processes are performed: duplicate features are removed from the technology product database to obtain a first processed technology database; missing features are compensated for in the first processed technology database to obtain a second processed technology database; and erroneous features are corrected in the second processed technology database to obtain the technology dataset.

[0008] In a possible implementation, based on the experience monitoring data, online courses are designed using a technology application creation platform to obtain online teaching courses, and the following processes are performed: feature recognition is performed based on the experience monitoring data to determine student interest characteristics; based on the student interest characteristics, the course resource library of the technology application creation platform is invoked for course matching to obtain an initial teaching course; the initial teaching course is optimized based on the student ability characteristics to generate the online teaching course.

[0009] In a possible implementation, the initial teaching course is optimized based on the student's ability characteristics to generate the online teaching course, and the following processes are performed: the difficulty of the initial teaching course is adjusted according to the student's ability characteristics to obtain a first adjusted teaching course; the depth of knowledge points in the first adjusted teaching course is adjusted according to the student's ability characteristics to obtain a second adjusted teaching course; and the learning workload of the second adjusted teaching course is adjusted according to the student's ability characteristics to obtain the online teaching course.

[0010] In one possible implementation, the technological application concept design is simulated and evaluated using a mechanism simulation system to obtain simulation evaluation results. The following processes are then performed: the technological application concept design is simulated and verified using the mechanism simulation system to obtain simulation verification data; the technological application concept design is then evaluated for feasibility based on the simulation verification data to generate simulation evaluation results.

[0011] In a possible implementation, based on the simulation evaluation results of the design proposal, a roadshow presentation is conducted on the technological application concept design proposal to obtain a design demonstration dataset. The following processes are then performed: determining whether the simulation evaluation results of the design proposal meet the feasibility constraints of the design proposal; if the simulation evaluation results of the design proposal meet the feasibility constraints of the design proposal, a roadshow presentation instruction is generated; based on the roadshow presentation instruction, the technological application concept design proposal is presented in a roadshow presentation to obtain the design demonstration dataset.

[0012] In a possible implementation, it is determined whether the simulation evaluation result of the design proposal meets the feasibility constraints of the design proposal, and the following processing is performed: if the simulation evaluation result of the design proposal does not meet the feasibility constraints of the design proposal, a design proposal optimization instruction is generated; based on the design proposal optimization instruction, the technology application concept design proposal is optimized and adjusted according to the feasibility constraints of the design proposal.

[0013] In a possible implementation, online expert evaluation is conducted based on the design demonstration dataset to obtain design evaluation results, and the following processes are performed: activating the online evaluation unit of the technology application creation platform, the online evaluation unit including multiple online experts; scoring the design demonstration dataset according to the multiple online experts to obtain an online design scoring sequence; and performing data fusion on the online design scoring sequence to generate the design evaluation results.

[0014] This application also provides a technology experience-based application design transformation system, including: a technology digital experience hall construction module, used to collect open-source technology product data via the Internet to construct a technology digital experience hall; an online technology experience module, used to provide students with online technology experiences based on the technology digital experience hall and obtain experience monitoring data; an online course design module, used to design online courses based on the experience monitoring data and a technology application creation platform to obtain online teaching courses; a teaching module, used to teach students based on the technology application creation platform and the online teaching courses to obtain technology application concept design proposals; a simulation verification and evaluation module, used to perform simulation verification and evaluation of the technology application concept design proposals through a mechanism simulation system to obtain simulation evaluation results; a roadshow presentation module, used to present the technology application concept design proposals in a roadshow based on the simulation evaluation results to obtain a design demonstration dataset; and an online expert evaluation module, used to conduct online expert evaluation based on the design demonstration dataset to obtain design evaluation results, and to transform the technology application concept design proposals into innovative achievements based on the design evaluation results.

[0015] The proposed method and system for application design transformation based on technological experience, as outlined in this application, firstly collects open-source technological product data via the internet to construct a digital technology experience center. Next, students engage in online technological experiences within this center, obtaining experience monitoring data. Then, based on this data, online courses are designed using a technology application creation platform to generate online teaching courses. Following this, students are taught using these online courses through the same platform, resulting in technological application concept design proposals. These proposals are then simulated and evaluated using a mechanism simulation system, yielding simulation evaluation results. Based on these results, the design proposals are presented in a roadshow, generating a design demonstration dataset. Finally, online expert evaluation is conducted using this dataset, resulting in design evaluation results. Based on these results, the technological application concept design proposals are then transformed into innovative achievements. This approach achieves the technical effect of enriching technological experiences and enhancing technological innovation capabilities. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings of the embodiments of the present invention will be briefly described below. Flowcharts are used in this application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, various steps can be processed in reverse order or simultaneously as needed. Furthermore, other operations can be added to these processes, or one or more steps can be removed from these processes.

[0017] Figure 1 This is a flowchart illustrating the application design transformation method based on technological experience provided in an embodiment of this application.

[0018] Figure 2 A schematic diagram of the structure of the application design transformation system based on technological experience provided in the embodiments of this application.

[0019] Explanation of figure labels: Module 10 for building a digital science and technology experience center, Module 20 for online science and technology experience, Module 30 for online course design, Module 40 for teaching, Module 50 for simulation verification and evaluation, Module 60 for roadshow presentation, and Module 70 for online expert evaluation. Detailed Implementation

[0020] The above description is merely an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, specific embodiments of this application are given below.

[0021] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description of this application will be provided in conjunction with the accompanying drawings. The described embodiments should not be considered as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0022] In the following description, references to "some embodiments" describe a subset of all possible embodiments. However, it is understood that "some embodiments" can be the same or different subsets of all possible embodiments and can be combined with each other without conflict. The terms "first" and "second" are used merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules not explicitly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only.

[0023] This application provides an application design transformation method based on technological experience, such as... Figure 1 As shown, the method includes: Step S100: Collect data on open-source technology products via the Internet to build a digital technology experience center.

[0024] Specifically, web crawling techniques, such as the Scrapy framework, are used to scrape source code, design documents, and user manuals from open-source communities and official websites of technology products, including GitHub, Open Source China, and CSDN. Simultaneously, API interfaces are used to obtain some structured data, such as product features and user reviews. The collected data is cleaned to remove duplicate, invalid, and erroneous information. Natural language processing techniques are used to perform word segmentation, part-of-speech tagging, and named entity recognition on the text data for indexing and retrieval. 3D modeling and virtual reality technologies, such as the Unity3D engine, are employed to transform the processed data into 3D models and interactive scenes. WebGL technology is used to display these in 3D within a browser, allowing users to enjoy an immersive experience through VR devices or regular computers.

[0025] In one possible implementation, data on open-source technology products is collected via the internet to construct a digital technology experience center. Step S100 further includes step S110, which involves collecting open-source technology product data via the internet to obtain a technology product database. Specifically, the open-source platform for data collection is determined, such as code hosting platforms like GitHub, GitLab, and Bitbucket, and dataset sharing platforms like Kaggle and the UCI Machine Learning Repository. A web crawler is developed using Python's Scrapy or BeautifulSoup libraries, and crawling rules are written based on the target platform's API interface or webpage structure to automatically crawl the source code, documentation, datasets, and other information of open-source technology products. The crawled data is then stored in a relational or non-relational database to construct the technology product database.

[0026] Step S120 involves performing multi-dimensional preprocessing on the technology product database to obtain a technology dataset. Specifically, multi-dimensional preprocessing includes, but is not limited to, data cleaning, data classification, data annotation, and data transformation. Data cleaning removes duplicate, invalid, and erroneous data from the technology product database to ensure data accuracy and consistency. Data is classified according to dimensions such as the type of technology product, application field, and technical difficulty for subsequent retrieval and use. Key data is annotated, such as adding functional descriptions to source code and labels to datasets, to improve data understandability and usability. Unstructured data, such as text and images, is converted into structured data to facilitate analysis and processing.

[0027] Step S130: Import the technology dataset into the digital experience center to generate the digital technology experience center. Specifically, use 3D modeling software or a game engine to create 3D models based on the product information in the technology dataset. Construct virtual scenes, such as laboratories or exhibition halls, in the digital experience center, place the 3D models within the scenes, and set interactive elements, such as buttons and sliders, allowing users to interact with the models. Bind the information from the technology dataset to the 3D models or interactive elements; when users interact with the models, relevant information is displayed. Deploy the completed digital experience center to a server, enabling access in a browser via Web technology or packaging it into an application for users to download and use.

[0028] In one possible implementation, the technology product database undergoes multi-dimensional preprocessing to obtain a technology dataset. Step S120 further includes step S121, which removes duplicate features from the technology product database to obtain a first processed technology database. Specifically, a hash algorithm is used to calculate the key features of each record in the technology product database to generate a unique hash value. Duplicate records are detected by comparing hash values; records with the same hash value are determined to be duplicate data. According to preset rules, such as retaining the latest or most complete record, duplicate data is removed, thereby obtaining the first processed technology database and ensuring the uniqueness of the data in the database.

[0029] Step S122: Perform missing feature compensation on the first processed scientific and technological database to obtain a second processed scientific and technological database. Specifically, traverse the first processed scientific and technological database to identify records with missing features. For numerical missing features, fill them using the mean, median, or mode based on the data distribution; for categorical missing features, select the category with the highest frequency for filling. If the missing feature is textual, use a text generation model combined with contextual information to generate reasonable text content for filling, thereby completing the missing feature compensation and obtaining the second processed scientific and technological database, ensuring data integrity.

[0030] Step S123 involves correcting errors in the second processed scientific and technological database to obtain the scientific and technological dataset. Specifically, data validation rules and pattern matching techniques are used to detect errors in the second processed scientific and technological database. For numerical errors, it is checked whether they are within a reasonable range; if they exceed the range, they are corrected or marked as abnormal. For categorical errors, it is verified whether they belong to a predefined category set; if not, they are corrected. For textual errors, spell checking tools and grammatical analysis methods are used to correct spelling and grammatical errors. By correcting the errors in the above manner, an accurate and reliable scientific and technological dataset is finally obtained.

[0031] Step S200: Based on the aforementioned digital technology experience center, students will have online technology experiences to obtain experience monitoring and collection data.

[0032] Specifically, the science and technology digital experience center features various interactive modules, such as virtual experiment operation areas and interactive technology product display areas. Students can log in to the experience center platform using computers, tablets, and other devices to operate and experience the products. The center's embedded monitoring system records students' operational behavior data in each module in real time, including operation time, operation steps, and dwell time. Simultaneously, subjective experience data is collected through online questionnaires and instant feedback pop-ups, such as students' level of interest in the technology products and their evaluation of the difficulty of operation. This objective operational data is integrated with subjective experience data to form the experience monitoring and collection data.

[0033] Step S300: Based on the experience monitoring data collected, online courses are designed according to the technology application creation platform to obtain online teaching courses.

[0034] Specifically, the data collected from experience monitoring is analyzed, and data mining algorithms are used to identify students' weaknesses and areas of interest in science and technology experiences. Combining this with the curriculum resource library of the science and technology application creation platform, suitable teaching materials are selected from the library based on the analysis results and student characteristics. Using curriculum design tools, and following a logical framework of teaching objectives, content, methods, and evaluation, the chapter structure, knowledge point explanation order, and interactive elements of the online course are designed, ultimately generating the online teaching course. The curriculum resource library of the science and technology application creation platform contains a wealth of science and technology knowledge courseware, case study videos, experimental demonstration animations, and more.

[0035] In one possible implementation, based on the experience monitoring data, online courses are designed using a technology application creation platform to obtain online teaching courses. Step S300 further includes step S310, which involves feature identification based on the experience monitoring data to determine student interest characteristics. Specifically, association rule mining algorithms and cluster analysis methods from data mining are used to deeply analyze the experience monitoring data. For student operational behavior data in the digital science and technology experience center, the correlation between the frequency and duration of operation of different technology modules is analyzed. For example, students who frequently operate the virtual robot programming module and stay for a long time may have a strong interest in artificial intelligence programming. Through cluster analysis, students with similar operational behavior patterns are grouped together to uncover the interest tendencies of different student groups. For students' subjective experience data, natural language processing technology is used to perform sentiment analysis and keyword extraction on questionnaire feedback and instant evaluation text to identify frequently mentioned and emotionally positive keywords in the technology field, such as "3D printing is very interesting" and "Aerospace technology is amazing." Combining the analysis results of operational behavior and subjective feedback, the interest characteristics of each student and the distribution of interest tendencies of different student groups are determined.

[0036] Step S320: Based on the student's interest characteristics, the course resource library of the technology application creation platform is invoked for course matching to obtain an initial teaching course. Specifically, the course resource library of the technology application creation platform has a rich variety of technology course resources, including course materials from different technology fields, different difficulty levels, and different teaching formats. According to the student's interest characteristics determined in step S310, multi-dimensional filtering conditions are set in the course resource library, such as using the field of interest as the primary filtering condition and the difficulty level as the secondary filtering condition, to locate course resources that match the student's interests. At the same time, using an intelligent recommendation algorithm, relevant popular courses and personalized courses are recommended to the student based on the similarity of the student's interest characteristics. The course resources obtained from the filtering and recommendation are integrated and arranged according to a certain teaching logic and knowledge system to form an initial teaching course that matches the student's interests. This course includes a basic framework such as a course outline, teaching content, and teaching materials.

[0037] Step S330: Optimize the initial teaching course based on students' ability characteristics to generate the online teaching course. Specifically, by analyzing students' past academic performance, homework completion, and project practice performance in science and technology learning, and combining this with psychological assessment tools, students' logical thinking ability, innovative thinking ability, and problem-solving ability are evaluated to determine their ability characteristics. The initial teaching course is then optimized in a differentiated manner for students with different ability levels. For students with strong abilities, the course includes extended content, such as cutting-edge scientific research updates and challenging experimental projects, providing more challenging learning tasks to stimulate their desire for exploration and innovation. For students with average abilities, the course's knowledge explanation methods are optimized, using more vivid, engaging, and easy-to-understand examples and demonstrations to strengthen the practice and consolidation of key knowledge points, ensuring they can solidly master the course content. For students with weaker abilities, basic knowledge tutoring sessions are added, the teaching pace is slowed down, and more learning support and guidance are provided to help them gradually build learning confidence. At the same time, the teaching methods and interaction approaches of the courses are adjusted according to students' learning styles, such as visual, auditory, and kinesthetic learners, to make the courses more in line with students' learning habits and ultimately generate personalized online teaching courses suitable for different students.

[0038] In one possible implementation, the initial teaching course is optimized based on students' ability characteristics to generate the online teaching course. Step S330 further includes step S331, adjusting the difficulty of the initial teaching course based on the students' ability characteristics to obtain a first adjusted teaching course. Specifically, learning analytics is used to analyze students' ability characteristics, dividing them into high, medium, and low levels. For students with strong abilities, more challenging content is added to the initial teaching course. For example, in an artificial intelligence course, more complex algorithm models are introduced, allowing students to try using these advanced algorithms to solve complex problems in real-world scenarios; in a physics and technology course, cutting-edge physics theory extensions are added, such as an introduction to the basic concepts of quantum computing, broadening students' knowledge horizons and increasing the difficulty of the course. For students with medium abilities, the core difficulty of the initial teaching course remains unchanged. For some difficult-to-understand knowledge points, more accessible and easy-to-understand methods are used to explain them, such as vivid animation demonstrations and analogies from real life, to help students better understand abstract concepts, ensuring that the course difficulty matches the students' abilities. For students with weaker abilities, the complex content in the initial teaching course is simplified, and complex theories are broken down into multiple simple steps to guide students' learning step by step. For example, in a programming course, a large programming project is broken down into multiple smaller tasks, starting with basic code writing and gradually transitioning to complete project development. This reduces the difficulty of the course and allows students to master the knowledge step by step. This adjustment results in the first stage of the teaching course.

[0039] Step S332: Based on the students' ability characteristics, the first adjusted teaching course is further adjusted in depth to obtain a second adjusted teaching course. Specifically, for students with strong abilities, the underlying principles and connections of the knowledge points are explored in depth based on the first adjusted teaching course. Taking biotechnology courses as an example, when explaining gene editing technology, not only are the basic operating procedures introduced, but the molecular biological mechanisms behind gene editing and the long-term impact of this technology on biological evolution and ecosystems are also discussed in detail, guiding students to think and explore in depth, and broadening the depth and breadth of their thinking. For students with average abilities, while ensuring mastery of basic knowledge, the application scope of the knowledge points is appropriately expanded. For example, in mathematics courses, after learning the basic properties of functions, students are asked to apply function knowledge to solve some real-life problems, such as cost-profit analysis and simulation of object motion trajectories, to improve their ability to apply knowledge to solve problems. For students with weaker abilities, the focus is on the core knowledge points in the first adjusted teaching course, strengthening the understanding and memorization of basic concepts. For example, in chemistry courses, the learning of chemical reaction equations is taught through repeated practice and comparative analysis, enabling students to master the writing and balancing of common chemical reaction equations. This ensures that students have a solid grasp of the basic knowledge points. After adjusting the depth of the knowledge points, a second adjustment of the teaching course is achieved.

[0040] Step S333: Adjust the learning workload of the second adjusted teaching course according to the student's ability characteristics to obtain the online teaching course. Specifically, the learning workload is allocated using an intelligent scheduling algorithm, taking into account the students' ability level and learning progress. For students with strong abilities, the learning workload is appropriately increased based on the second adjusted teaching course, with more extended reading materials, research-based learning projects, and practical operation tasks arranged. For students with average abilities, an appropriate learning workload is maintained to ensure that students have sufficient time and energy to understand and digest the knowledge. For students with weaker abilities, the learning workload is reduced to avoid students experiencing learning pressure and aversion to learning due to excessive workload. After adjusting the learning workload, an online teaching course suitable for different students is finally obtained.

[0041] Step S400: Based on the technology application creation platform, teach the students according to the online teaching courses to obtain a technology application concept design plan.

[0042] Specifically, an online teaching environment is built on the technology application creation platform, where students log in with their accounts to access corresponding courses. During the teaching process, a combination of teaching methods is employed, including live streaming, pre-recorded playback, digital human-based instruction, and online Q&A. The platform's interactive features, such as group discussions and online voting, enhance student participation. Practical tasks related to technology applications are assigned, guiding students to apply their knowledge to thinking and creating. Concept design templates and tools are provided to students, who, while completing practical tasks, present their technology application ideas through text descriptions, drawings, and simple model building, forming technology application concept design proposals which are then submitted to the platform.

[0043] Step S500: The technological application concept design is simulated and evaluated using a mechanism simulation system to obtain the simulation evaluation results of the design.

[0044] Specifically, student-submitted technological application concept design proposals are imported into a mechanistic simulation system. This system possesses a physics engine and a mathematical model library, capable of simulating physical phenomena and operational laws under various technological application scenarios. Based on the specific content of the technological application concept design proposal, corresponding parameters and boundary conditions are set in the simulation system. The simulation program is then run, generating real-time operational data and visualizations of the technological application concept design proposal in the simulation environment, such as motion trajectory, energy changes, and performance indicators. By comparing and analyzing these data with the expected goals of the technological application concept design proposal, the feasibility, effectiveness, and performance of the design proposal are evaluated, resulting in a simulation evaluation of the design proposal, including scores for each indicator and a comprehensive evaluation opinion.

[0045] In one possible implementation, the technological application concept design is simulated and evaluated using a mechanism simulation system to obtain simulation evaluation results. Step S500 further includes step S510, where the technological application concept design is simulated and verified using the mechanism simulation system to obtain simulation verification data. Specifically, the technological application concept design is analyzed to determine its various components, functional modules, and their interactions. For example, if the technological application concept design is a conceptual design of a new intelligent traffic management system, it is necessary to define key elements such as the types of sensors involved in the system, data transmission methods, the processing logic of the control center, and the connection methods with external devices such as traffic lights and vehicles. Then, the analyzed design parameters are input into the mechanism simulation system, which has a physical model and mathematical algorithms and can simulate various physical phenomena and operating rules in the real world. Taking an intelligent traffic management system as an example, the system simulates road conditions under different time periods and traffic flows, including vehicle speed, acceleration, queue length, etc., while simulating the sensor's collection of traffic information, the data transmission delay in the network, and the entire process of the control center making decisions and issuing instructions based on the received data. During simulation, the mechanism simulation system records various key data in real time, such as system response time, operating efficiency of each module, resource utilization, and the occurrence and frequency of faults. This data is then organized and stored to form the simulation verification data for the design plan.

[0046] Step S520: A feasibility assessment of the technological application concept design is performed based on the simulation verification data of the design proposal, generating the simulation assessment results. Specifically, the simulation verification data of the design proposal is analyzed and processed according to a pre-set evaluation index system. This evaluation index system includes multiple dimensions such as technical feasibility, performance feasibility, and economic feasibility. For example, regarding technical feasibility, it checks whether the technological application concept design can successfully achieve its expected functions during simulation, and whether there are any technical bottlenecks or unsolvable technical problems. For instance, in the simulation of an intelligent traffic management system, if it is found that a certain new type of sensor has extremely low data acquisition accuracy under specific weather conditions, causing the system to malfunction, this indicates that the technological application concept design has certain technical defects. Regarding performance feasibility, it evaluates whether the various performance indicators of the technological application concept design meet actual needs. Continuing with the intelligent traffic management system as an example, it checks whether the system's response time is within an acceptable range, and whether the traffic flow processing capacity can cope with road conditions during peak hours. Regarding economic feasibility, it analyzes the implementation cost and expected benefits of the technological application concept design. The calculation includes the procurement costs of hardware equipment, software development expenses, and system maintenance costs. It also estimates the economic benefits the system will bring after its implementation, such as time savings from reduced traffic congestion and reduced losses from lower traffic accident rates. Through comprehensive analysis of simulation verification data across various evaluation indicators, and using a combination of quantitative and qualitative methods, the feasibility of the technology application concept design is evaluated. The final simulation evaluation results include an overall assessment of the feasibility of the technology application concept design, specific scores for each evaluation indicator, existing strengths and weaknesses, and targeted improvement suggestions.

[0047] Step S600: Based on the simulation evaluation results of the design, the technology application concept design is presented in a roadshow to obtain a design demonstration dataset.

[0048] Specifically, students optimize and improve their technological application concept designs based on the simulation evaluation results. A roadshow presentation activity is organized on the technological application creation platform, where students use the platform's presentation tools, such as PowerPoint, 3D model display software, and animation software, to present their designs in a vivid and engaging way, including design ideas, innovative points, simulation verification results, and future application prospects. During the roadshow, a Q&A session is included, where other students and teachers can ask questions, which the presenting student answers. Using the platform's recording function, the entire roadshow presentation process, including the presentation content and Q&A sessions, is fully recorded, forming a design presentation dataset. This dataset includes video files, presentation documents, and related text records.

[0049] In one possible implementation, based on the simulation evaluation results of the design proposal, the technological application concept design proposal is presented in a roadshow to obtain a design demonstration dataset. Step S600 further includes step S610, determining whether the simulation evaluation results of the design proposal meet the feasibility constraints of the design proposal. Specifically, the feasibility constraints of the design proposal are pre-set at the initial stage of the project, taking into account multiple factors, including technical, economic, and resource dimensions. In the technical dimension, specific performance indicators that the technological application concept design proposal must achieve are specified. For example, for a conceptual design of a new medical testing device, its detection accuracy must reach an industry-leading level, with the error range controlled within an extremely small range; in terms of data transmission speed, it must meet the needs of real-time detection and rapid feedback. In the economic dimension, a cost budget ceiling is set, including R&D costs, manufacturing costs, and marketing costs, to ensure the project is economically feasible and profitable. The resource dimension includes the availability and reasonable allocation of human and material resources, such as the number of required professional and technical personnel and the stability of the supply of key raw materials. The data in the simulation evaluation results of the design plan are compared and analyzed one by one with the pre-set feasibility constraints. The degree of compliance of each indicator is calculated to determine whether the simulation evaluation results of the design plan meet the feasibility constraints of the design plan.

[0050] Step S620: If the simulation evaluation result of the design proposal meets the feasibility constraints of the design proposal, a roadshow presentation instruction is generated. Specifically, when the judgment in step S610 determines that the simulation evaluation result of the design proposal meets the pre-set feasibility constraints in terms of technology, economics, and other aspects, the roadshow presentation instruction generation mechanism is triggered, and a roadshow presentation instruction is generated. The roadshow presentation instruction specifies the content framework of the presentation, including key information such as the core innovation points, technological advantages, market prospects, and business model of the technology application concept design proposal; at the same time, it specifies the form and style of the presentation, such as using multimedia presentation methods and using language for explanation, to ensure that the roadshow presentation can effectively convey the value and feasibility of the design proposal and attract the attention and recognition of the target audience.

[0051] Step S630: Based on the roadshow presentation instruction, the technology application concept design proposal is presented in a roadshow, resulting in the design demonstration dataset. Specifically, according to the roadshow presentation instruction generated in step S620, the technology application concept design proposal is interpreted and presented from different perspectives. During the roadshow presentation, various presentation methods are used, such as PPT presentations, product model displays, and simulated videos of actual operating scenarios, to present the characteristics and advantages of the design proposal comprehensively and from multiple angles. Simultaneously, interactive sessions are set up to facilitate real-time communication and Q&A with the target audience. During the roadshow presentation, data acquisition equipment and technology are used to record and collect data in real time at each stage, including questions from the target audience, feedback, focus areas, emotional reactions, and performance data from the roadshow, such as the fluency of the presentation and the accuracy of the answers. This data is then organized and categorized to form the design demonstration dataset.

[0052] Step S640: If the simulation evaluation result of the design proposal does not meet the feasibility constraints of the design proposal, a design proposal optimization instruction is generated. Specifically, when the judgment result of step S610 shows that the simulation evaluation result of the design proposal does not meet the pre-set feasibility constraints in one or more aspects, the design proposal optimization instruction generation program is started to analyze the specific indicators that do not meet the constraints, and to find the root cause and key influencing factors of the problem. For example, if it is found that the design proposal does not meet the expected indicators in terms of technical performance, further analysis of simulation verification data is used to determine whether there is a defect in a key technical link or whether the overall technical architecture is unreasonable. Based on the analysis results, combined with the actual situation and resource conditions of the project, a targeted and operable design proposal optimization instruction is generated, including the specific content to be optimized, the optimization objectives and expected effects, and corresponding optimization suggestions and reference solutions are provided.

[0053] Step S650: Based on the design optimization instructions, the technological application concept design is optimized and adjusted according to the feasibility constraints of the design. Specifically, after receiving the design optimization instructions, the platform automatically optimizes the design based on intelligent algorithms and preset rules. For example, technically, for parts that do not meet performance requirements, parameters and architecture are adjusted by referring to historical data and cases, and the optimal configuration is determined through multiple rounds of simulation iterations. Economically, cost composition is analyzed by combining cost budget and revenue constraints, and better suppliers are selected through big data comparison to control costs. The process is recorded in real time and an optimization report is generated, providing students with decision-making basis and ensuring that the design meets all feasibility constraints.

[0054] Step S700: Based on the design demonstration dataset, conduct online expert evaluation to obtain design evaluation results, and based on the design evaluation results, transform the technological application concept design into innovative achievements.

[0055] Specifically, a review team composed of experts and scholars in the field of science and technology will be invited to review the design demonstration datasets through the online review system of the science and technology application creation platform. The review team will formulate review criteria based on multiple dimensions, including innovativeness, practicality, feasibility, and technological advancement of the designs. Each expert will independently score each design according to the criteria and write review comments. The expert scores will be statistically analyzed to calculate the comprehensive score for each design, and the designs will be ranked according to their scores to determine the design evaluation results, including different levels such as excellent and good designs. Based on the design evaluation results, for high-value, outstanding science and technology application concept designs, schools or relevant institutions will collaborate with enterprises to provide financial support, technical guidance, and market promotion assistance to promote the transformation of the design from the concept stage to actual products or applications, thus realizing the implementation of innovative achievements.

[0056] In one possible implementation, online expert evaluation is conducted based on the design demonstration dataset to obtain design evaluation results. Step S700 further includes step S710, activating the online evaluation unit of the technology application creation platform. The online evaluation unit includes multiple online experts. Specifically, the technology application creation platform has intelligent functional modules. When entering the design evaluation stage, the system automatically activates the online evaluation unit according to a preset trigger mechanism. This unit has multiple online experts from different fields with rich experience and professional knowledge. The platform ensures that each online expert possesses the corresponding professional capabilities and authority through identity authentication and qualification review mechanisms, enabling them to provide a comprehensive, objective, and professional evaluation of the design demonstration dataset.

[0057] Step S720: Based on the scoring of the design demonstration dataset by the multiple online experts, an online design scoring sequence is obtained. Specifically, after the online evaluation unit is activated, the system presents the design demonstration dataset to each online expert. The online experts, based on their professional knowledge and practical experience, evaluate and score various aspects of the design demonstration dataset according to pre-set scoring standards and indicator systems. After the experts complete their scoring independently, the system automatically collects and organizes this scoring data, arranging it in a certain order to form the online design scoring sequence.

[0058] Step S730: Data fusion is performed on the online design scoring sequence to generate the design evaluation result. Specifically, the original scores in the online design scoring sequence are preprocessed to remove abnormal scores that deviate significantly from a reasonable range, such as extreme values ​​that exceed the preset scoring range or differ greatly from the scores of most other experts, thereby ensuring data quality. Next, based on factors such as the influence of each online expert in their professional field, the accuracy of past evaluations, and the relevance of the professional content involved in this evaluation to the expert's area of ​​expertise, corresponding weights are assigned to each expert's score, with higher weights for experts with higher professional authority and stronger relevance. Then, a weighted average algorithm is used to calculate the preprocessed and weighted scores to obtain a comprehensive score. Finally, based on this comprehensive score and combined with preset evaluation level classification standards, such as setting different scoring segments corresponding to different levels such as excellent, good, qualified, and unqualified, the final design evaluation result of the technology application concept design is determined, and a detailed report containing information such as the comprehensive score, details of each expert's score, and evaluation level is generated.

[0059] This application's embodiments address the technical problems of limited teaching resources, limited practical scenarios, and restricted technological innovation capabilities in existing science and technology education by collecting data from open-source technology products, constructing digital experience centers where students experience and monitor data, designing online courses based on the monitoring data, forming conceptual design plans through online teaching, conducting simulation evaluations of the conceptual design plans, presenting the designs after passing the evaluation, obtaining demonstration data, and promoting the transformation of outstanding design results through expert evaluation. This achieves the technical effect of enriching the science and technology experience and enhancing technological innovation capabilities.

[0060] In the above text, refer to Figure 1 This paper describes in detail an application design transformation method based on technological experience according to embodiments of the present invention. Next, reference will be made to... Figure 2 This invention describes an application design transformation system based on technological experience according to an embodiment of the present invention.

[0061] The application design transformation system based on technological experience according to embodiments of the present invention addresses the technical problems of limited teaching resources, single practical scenarios, and limited technological innovation capabilities in existing science and technology education, thereby enriching technological experiences and enhancing technological innovation capabilities. The application design transformation system based on technological experience includes: a technology digital experience hall construction module 10, an online technology experience module 20, an online course design module 30, a teaching module 40, a simulation verification and evaluation module 50, a roadshow presentation module 60, and an online expert evaluation module 70.

[0062] The system comprises the following modules: a digital technology experience center construction module 10, used to collect open-source technology product data via the internet to construct a digital technology experience center; an online technology experience module 20, used to provide students with online technology experiences based on the digital technology experience center and obtain experience monitoring data; an online course design module 30, used to design online courses based on the experience monitoring data and a technology application creation platform to obtain online teaching courses; a teaching module 40, used to teach students based on the technology application creation platform and the online teaching courses to obtain technology application concept design proposals; a simulation verification and evaluation module 50, used to perform simulation verification and evaluation of the technology application concept design proposals through a mechanism simulation system to obtain simulation evaluation results; a roadshow presentation module 60, used to present the technology application concept design proposals in a roadshow based on the simulation evaluation results to obtain a design demonstration dataset; and an online expert evaluation module 70, used to conduct online expert evaluation based on the design demonstration dataset to obtain design evaluation results and to transform the technology application concept design proposals into innovative achievements based on the design evaluation results.

[0063] The detailed configuration of the technology digital experience hall construction module 10 is explained as follows: As mentioned above, the technology digital experience hall is constructed by collecting open-source technology product data through the Internet. The technology digital experience hall construction module 10 may further include: an open-source technology product data collection unit for collecting open-source technology product data through the Internet to obtain a technology product database; a multi-dimensional preprocessing unit for performing multi-dimensional preprocessing on the technology product database to obtain a technology dataset; and a technology digital experience hall generation unit for importing the technology dataset into the digital experience hall to generate the technology digital experience hall.

[0064] The technology product database is subjected to multidimensional preprocessing to obtain a technology dataset. The multidimensional preprocessing unit may further include: a duplicate feature removal subunit for removing duplicate features from the technology product database to obtain a first processed technology database; a missing feature compensation subunit for compensating for missing features in the first processed technology database to obtain a second processed technology database; and an error feature correction subunit for correcting error features in the second processed technology database to obtain the technology dataset.

[0065] The online course design module 30 is described in detail below: As mentioned above, based on the experience monitoring data, online courses are designed using the technology application creation platform to obtain online teaching courses. The online course design module 30 may further include: an interest feature identification unit for identifying student interest features based on the experience monitoring data; a course matching unit for matching courses based on the student interest features by calling the course resource library of the technology application creation platform to obtain an initial teaching course; and an initial teaching course optimization unit for optimizing the initial teaching course based on student ability features to generate the online teaching course.

[0066] The initial teaching course is optimized based on student ability characteristics to generate the online teaching course. The initial teaching course optimization unit may further include: a difficulty adjustment subunit for adjusting the difficulty of the initial teaching course according to the student ability characteristics to obtain a first adjusted teaching course; a knowledge point depth adjustment subunit for adjusting the knowledge point depth of the first adjusted teaching course according to the student ability characteristics to obtain a second adjusted teaching course; and a learning task volume adjustment subunit for adjusting the learning task volume of the second adjusted teaching course according to the student ability characteristics to obtain the online teaching course.

[0067] The detailed description of the specific configuration of the simulation verification and evaluation module 50 is explained as follows: As mentioned above, the simulation verification and evaluation module 50 performs simulation verification and evaluation on the technology application concept design through the mechanism simulation system to obtain the simulation evaluation result of the design. The simulation verification and evaluation module 50 may further include: a simulation verification unit for performing simulation verification on the technology application concept design according to the mechanism simulation system to obtain simulation verification data of the design; and a feasibility evaluation unit for performing feasibility evaluation on the technology application concept design based on the simulation verification data of the design to generate the simulation evaluation result of the design.

[0068] The specific configuration of the roadshow reporting module 60 is described in detail below: As mentioned above, based on the simulation evaluation results of the design proposal, the technology application concept design proposal is presented in a roadshow to obtain a design demonstration dataset. The roadshow reporting module 60 may further include: a judgment unit for judging whether the simulation evaluation results of the design proposal meet the feasibility constraints of the design proposal; a roadshow reporting instruction generation unit for generating a roadshow reporting instruction if the simulation evaluation results of the design proposal meet the feasibility constraints of the design proposal; and a roadshow reporting unit for presenting the technology application concept design proposal in a roadshow based on the roadshow reporting instruction to obtain the design demonstration dataset.

[0069] Specifically, the roadshow reporting module 60 may further include: a design optimization instruction generation unit for generating a design optimization instruction if the design simulation evaluation result does not meet the design feasibility constraints; and a design optimization adjustment unit for optimizing and adjusting the technology application concept design based on the design optimization instruction and the design feasibility constraints.

[0070] The online expert evaluation module 70 is described in detail below: As mentioned above, online expert evaluation is conducted based on the design demonstration dataset to obtain design evaluation results. The online expert evaluation module 70 may further include: an online evaluation activation unit for activating the online evaluation unit of the technology application creation platform, wherein the online evaluation unit includes multiple online experts; a scoring unit for scoring the design demonstration dataset according to the multiple online experts to obtain an online design scoring sequence; and a data fusion unit for performing data fusion on the online design scoring sequence to generate the design evaluation results.

[0071] The application design transformation system based on technological experience provided in the embodiments of the present invention can execute the application design transformation method based on technological experience provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0072] Although this application makes various references to certain modules in the system according to the embodiments of this application, any number of different modules can be used and run on user terminals and / or servers. The various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy distinction between each other and are not used to limit the scope of protection of this invention.

[0073] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application. In some cases, the actions or steps described in this application can be performed in a different order than that shown in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. An application design and transformation method based on technological experience, characterized in that, The method includes: We collect data on open-source technology products via the internet to build a digital technology experience center. Based on the aforementioned digital technology experience center, students can conduct online technology experiences and obtain experience monitoring and data collection. Based on the experience monitoring data collected, online courses are designed according to the technology application creation platform to obtain online teaching courses; Based on the aforementioned technology application creation platform, the students are taught according to the online teaching courses to obtain technology application concept design schemes; The technological application concept design was simulated and evaluated using a mechanism simulation system to obtain the simulation evaluation results of the design. Based on the simulation evaluation results of the design, the technological application concept design was presented in a roadshow to obtain a design demonstration dataset. Based on the design demonstration dataset, online expert evaluation is conducted to obtain design evaluation results, and the innovative achievements of the technology application concept design are transformed based on the design evaluation results.

2. The application design and transformation method based on technological experience as described in claim 1, characterized in that, By collecting data from open-source technology products via the internet, a digital technology experience center is constructed, including: By collecting open-source technology product data through the Internet, a technology product database can be obtained. The technology product database is preprocessed in multiple dimensions to obtain a technology dataset; Import the aforementioned technology dataset into the digital experience center to generate the technology digital experience center.

3. The application design and transformation method based on technological experience as described in claim 2, characterized in that, The technology product database is preprocessed in multiple dimensions to obtain a technology dataset, including: The database of scientific and technological products is subjected to duplicate feature removal to obtain a first processed scientific and technological database; The first processed technology database is compensated for missing features to obtain the second processed technology database. The second processed science and technology database is subjected to error feature correction to obtain the science and technology dataset.

4. The application design and transformation method based on technological experience as described in claim 1, characterized in that, Based on the experience monitoring data collected, online courses are designed using a technology application creation platform to obtain online teaching courses, including: Based on the experience monitoring data collected, feature identification is performed to determine students' interest characteristics; Based on the students' interest characteristics, the course resource library of the technology application creation platform is called to match courses and obtain initial teaching courses. The initial teaching course is optimized based on the students' ability characteristics to generate the online teaching course.

5. The application design and transformation method based on technological experience as described in claim 4, characterized in that, The initial teaching course is optimized based on students' ability characteristics to generate the online teaching course, including: The difficulty of the initial teaching course is adjusted according to the student's ability characteristics to obtain a first adjusted teaching course; Based on the student's ability characteristics, the first adjusted teaching course is adjusted in depth to obtain the second adjusted teaching course. The learning workload of the second adjusted teaching course is adjusted according to the student's ability characteristics to obtain the online teaching course.

6. The application design and transformation method based on technological experience as described in claim 1, characterized in that, The technological application concept design was simulated and evaluated using a mechanism simulation system to obtain simulation evaluation results, including: The technological application concept design is simulated and verified using the mechanism simulation system to obtain simulation verification data of the design. Based on the simulation verification data of the design proposal, a feasibility assessment of the technological application concept design proposal is conducted, and the simulation assessment results of the design proposal are generated.

7. The application design and transformation method based on technological experience as described in claim 1, characterized in that, Based on the simulation evaluation results of the aforementioned design, the technological application concept design is presented in a roadshow to obtain a design demonstration dataset, including: Determine whether the simulation evaluation results of the design plan meet the feasibility constraints of the design plan; If the simulation evaluation results of the design proposal meet the feasibility constraints of the design proposal, a roadshow presentation instruction will be generated. Based on the roadshow presentation instruction, the technology application concept design proposal is presented in a roadshow, and the design demonstration dataset is obtained.

8. The application design and transformation method based on technological experience as described in claim 7, characterized in that, Determining whether the simulation evaluation results of the design proposal meet the feasibility constraints includes: If the simulation evaluation results of the design proposal do not meet the feasibility constraints of the design proposal, an optimization instruction for the design proposal will be generated. Based on the design optimization instructions, the technology application concept design is optimized and adjusted according to the feasibility constraints of the design.

9. The application design and transformation method based on technological experience as described in claim 1, characterized in that, Based on the aforementioned design demonstration dataset, online expert evaluation was conducted to obtain design evaluation results, including: Activate the online evaluation unit of the technology application creation platform, which includes multiple online experts; Based on the scoring of the design demonstration dataset by the multiple online experts, an online scoring sequence for the design is obtained; The online scoring sequence of the design is fused to generate the design evaluation result.

10. An application design transformation system based on technological experience, characterized in that, The system is used to implement the application design and transformation method based on technological experience as described in any one of claims 1-9, and the system includes: The technology digital experience hall building module is used to collect data on open-source technology products via the Internet and build a technology digital experience hall. The online technology experience module is used to provide students with online technology experiences based on the aforementioned digital technology experience hall and to obtain experience monitoring and data collection. The online course design module is used to design online courses based on the experience monitoring data and the technology application creation platform to obtain online teaching courses. The teaching module is used to teach the students based on the technology application creation platform and the online teaching courses, and to obtain technology application concept design schemes. The simulation verification and evaluation module is used to perform simulation verification and evaluation on the technological application concept design through a mechanism simulation system, and obtain the simulation evaluation results of the design. The roadshow presentation module is used to present the technological application concept design based on the simulation evaluation results of the design, and obtain a design demonstration dataset. The online expert evaluation module is used to conduct online expert evaluation based on the design demonstration dataset, obtain design evaluation results, and transform the innovative achievements of the technology application concept design based on the design evaluation results.

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