An environmental design digital teaching resource sharing guidance platform

Abstract

The present application belongs to the field of resource sharing platform, and discloses an environmental design digital teaching resource sharing guidance platform, which comprises a digital resource standardization module, a user hierarchical portrait modeling module, a resource sharing matching module, an entrepreneurship guidance module, an entrepreneurship project simulation incubation module, a school-enterprise linkage service module, a data storage and encryption module, and an entrepreneurship community interaction module. The technical solution realizes standardization, structuring and fine management of the resource system, improves resource retrieval efficiency, and matches corresponding teaching resources or track exclusive entrepreneurship resources and customized entrepreneurship guidance services for different levels of users, thereby realizing deep integration and precise adaptation of professional teaching empowerment and industry entrepreneurship guidance. The platform has both teaching resource sharing function and entrepreneurship empowerment function, and can provide professional entrepreneurship guidance, thereby realizing integrated processing of teaching and entrepreneurship.

Description

Technical Field

[0001] This invention relates to the field of resource sharing platforms, and more particularly to a digital teaching resource sharing and guidance platform for environmental design. Background Technology

[0002] Art and design is an independent art discipline. It is a professional term that mainly includes specializations such as environmental design, graphic design, visual communication, and product design. Its research content and target audience differ from traditional art categories. At the same time, art and design is also a highly comprehensive discipline that involves many factors such as society, culture, economy, market, and technology. Its aesthetic standards also change with the changes in these factors.

[0003] Environmental art design is a branch of art design; it is a comprehensive applied major integrating art design, engineering technology, and spatial planning. It encompasses multiple sub-fields such as interior design, landscape design, and public space renovation. Furthermore, the industry has low barriers to entry, strong creative attributes, and broad market demand, making it a key area supported by higher education institutions' innovation and entrepreneurship education. Currently, with the popularization of digital education, various teaching resource sharing platforms are emerging. However, existing sharing platforms still have the following problems in practical use: First, existing teaching resource sharing platforms suffer from severe resource fragmentation and low standardization. Because environmental design teaching resources include a large number of unstructured digital resources such as 3D models, rendering files, construction drawings, and creative cases, traditional platforms cannot achieve unified processing, accurate classification, and tagging management of multi-format resources, resulting in low resource retrieval efficiency for teachers and students. Second, existing platforms lack professional entrepreneurship guidance functions, leading to a serious disconnect between teaching and entrepreneurship. General-purpose teaching resource platforms focus only on knowledge sharing and fail to build a dedicated service system tailored to the entrepreneurial characteristics of the environmental design industry. They cannot provide targeted guidance such as interpretation of industry entrepreneurial policies and project incubation. On the other hand, general-purpose entrepreneurial guidance platforms lack professional resources in environmental design, resulting in poor professionalism and practicality. Consequently, the overall effectiveness of these platforms is poor. Summary of the Invention

[0004] The present invention aims to provide a digital teaching resource sharing and guidance platform for environmental design to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: A digital teaching resource sharing and guidance platform for environmental design, comprising: A digital resource standardization module is used to collect teaching resources, design cases, and multi-source digital materials; at the same time, it standardizes the collected unstructured resources to build a standardized and structured resource database specifically for environmental design. User hierarchical profiling modeling module; the user hierarchical profiling modeling module is used to collect user information, classify user information, and locate user needs; Resource sharing and matching module; the resource sharing and matching module is used to push corresponding resource information based on user profile; The entrepreneurship guidance module includes an environmental design entrepreneurship knowledge base, an entrepreneurship policy analysis unit, an entrepreneurship planning guidance unit, and a risk warning unit. It is used to provide users with exclusive entrepreneurship knowledge popularization, interpretation of university and local entrepreneurship policies, personalized entrepreneurship plan customization, and entrepreneurship risk prediction and avoidance guidance services. Startup project simulation incubation module; The startup project simulation incubation module is used to simulate startup projects, while providing guidance on project modification and optimization, and completing the online polishing and pre-incubation of startup projects; The university-enterprise collaboration service module is used to connect entrepreneurs with physical entrepreneurial space resources and establish a communication channel between entrepreneurs and physical spaces. Data storage and encryption module; the data storage and encryption module is used to store all data of the platform, and at the same time establishes encryption procedures to ensure data security.

[0006] Preferably, the digital resource standardization module performs the following steps for standardizing resources: S11. Collect resources from the entire domain; collect digital resources through web crawling, university and enterprise uploading, and industry cooperation import. Digital resources include 3D modeling resources for environmental design, landscape design schemes, commercial real-world project resources, and digital renderings. S12. Resource standardization processing: Perform unified format conversion on the collected multi-format resources and remove damaged and redundant resources; S13. Labeling: Label the standardized resources from six dimensions: professional direction, difficulty level, applicable scenarios, teaching purpose, entrepreneurial suitability, and copyright attributes. S14. Hierarchical rights confirmation: Classify all resources into free teaching and sharing resources, paid commercial resources, and authorized trial resources, generate resource copyright traceability codes, and realize full traceability of resource sharing.

[0007] Preferably, the user tiered profiling modeling module also collects users' different resource usage frequencies, entrepreneurial intentions, and practical experience, dividing users into ordinary learning users, entrepreneurial prospective users, and startup users; among them, ordinary learning users are college students or industry beginners who have no clear entrepreneurial intentions and whose core needs are professional course learning, practical training, and skills improvement; entrepreneurial prospective users are college teachers and students and industry practitioners who have entrepreneurial planning intentions and are preparing entrepreneurial projects or learning entrepreneurial knowledge; startup users are employees of startup entities who have registered studios and are carrying out small-scale entrepreneurial operations.

[0008] Preferably, the digital resource standardization module incorporates a resource entrepreneurship adaptation quantification model, which uses a resource entrepreneurship adaptation quantification formula to quantitatively distinguish between ordinary teaching resources and entrepreneurship empowerment resources; the resource entrepreneurship adaptation quantification formula is: in, The environmental design resource suitability score for entrepreneurship is given, with a value range of 1-100. To match the resource with commercial application scenarios, To improve the practical reusability of resources industry practices, It provides auxiliary value for the implementation of resource projects. , , , is the resource obsolescence and decay coefficient, and is the weight correction coefficient obtained from big data training based on the sub-tracks of interior design, landscape design, and public space renovation. The sum of the four coefficients is 1.

[0009] Preferably, the user tiered profiling modeling module incorporates a user entrepreneurial potential scoring model, which accurately classifies users into different tiers using a user entrepreneurial potential scoring formula. The user entrepreneurial potential scoring formula is as follows: in, A comprehensive score is given to users' entrepreneurial potential, with a value range of 1-100; The platform quantifies and generates metrics to measure users’ mastery of professional skills through practical training assessments and resource learning. To increase user activity in entrepreneurial activities; User project practical experience points; The risk factor for entrepreneurship is the minimum threshold. , , , These are normalized weighting coefficients used for the automatic rigid partitioning of user levels.

[0010] Preferably, the resource sharing matching module adopts an improved collaborative filtering algorithm, equipped with an intelligent matching weight quantification calculation model, and combines user history browsing, downloading, collection and operation records to build a resource demand prediction model to achieve accurate push; The intelligent resource matching weight formula achieves a dynamic weight balance between learning needs and entrepreneurial needs, enabling differentiated and precise resource delivery. The intelligent resource matching weight formula is as follows: in, The matching weight value between users and resources is determined by the weight value; the higher the weight value, the higher the push priority. Matching the user's basic learning needs; This represents the entrepreneurial demand bias coefficient.

[0011] Preferably, the entrepreneurial project simulation incubation module includes a practical training and assessment unit. The practical training and assessment unit is used to set up environment design entrepreneurial practical test questions, project bidding simulation and customer negotiation simulation scenarios, record user training data, generate entrepreneurial ability assessment reports, and provide data support for users to optimize their entrepreneurial abilities and improve their entrepreneurial projects.

[0012] Preferably, the school-enterprise collaboration service module can automatically filter the best entrepreneurial space resources based on the scale of the user's entrepreneurial project, the design track, the office equipment requirements, and the regional requirements, while providing a one-stop online service for entrepreneurial space application, qualification review, venue reservation, and school-enterprise cooperation project matching.

[0013] Preferably, it also includes an entrepreneurial community interaction module, which is used to build an environment design entrepreneurial exchange community, supporting users to share resources, exchange entrepreneurial experiences, and connect with project partners.

[0014] Preferably, the user tiered profile modeling module is configured with a rigid tiered mechanism based on a score threshold, using the user's comprehensive entrepreneurial potential score P as the criterion: when P < 30, the user is judged as an ordinary learning user; when 30 ≤ P ≤ 70, the user is judged as a potential entrepreneurial user; and when P > 70, the user is judged as a startup user.

[0015] The beneficial effects of this technical solution compared to existing technologies are as follows: (1) This technical solution sets up a digital resource standardization module; builds a four-level serial resource processing link and a six-dimensional intelligent labeling system, and at the same time provides a subdivided track differentiated screening mechanism and copyright traceability coding architecture, constructing a dual-scenario layered resource pool including a teaching shared resource layer and an entrepreneurial commercial resource layer; through multi-source differentiated collection, heterogeneous resource standardization cleaning, refined label mounting, and hierarchical copyright confirmation, the unstructured and fragmented digital resources in environmental design are uniformly organized, classified, stored, and accurately screened. Based on the track-specific screening rules, basic teaching resources and commercial entrepreneurial resources are distinguished, realizing the standardization, structuring, and refined management of the resource system; improving resource retrieval efficiency, and at the same time improving the regularity and usability of environmental design professional resources.

[0016] (2) This technical solution sets up a dedicated quantitative calculation model adapted to the environment design industry, builds a user-layered quantitative architecture and a dual-demand dynamic balance calculation system based on the model, and provides a multi-track discrete dedicated entrepreneurship database; through the quantitative model, users' learning needs and entrepreneurship needs are accurately divided, and the differentiated resource push link is switched based on the dynamic bias coefficient. Corresponding teaching resources or track-specific entrepreneurship resources and customized entrepreneurship guidance services are matched for users at different levels, so as to achieve deep integration and precise adaptation of professional teaching empowerment and industry entrepreneurship guidance; so that the platform has the function of sharing teaching resources while also having the function of entrepreneurship empowerment, and can provide professional entrepreneurship guidance opinions, realizing the integrated processing of teaching and entrepreneurship.

[0017] (3) This technical solution sets up a startup project simulation incubation module and a school-enterprise linkage service module, constructs an industry-specific project quantitative evaluation architecture, a training data collection architecture, and a spatial resource multi-dimensional parameter index matching architecture, and opens up a closed-loop data link between online project pre-incubation and offline space landing; it completes qualification review, venue matching, school-enterprise project and investment and financing matching in one stop, reducing the resource acquisition and offline landing costs of startup teams; it effectively solves the problems of insufficient industry experience of startup practitioners in the field of environmental design, difficulty in obtaining high-quality entrepreneurial resources, poor adaptability of entrepreneurial venues, high project landing costs, and high-quality entrepreneurial projects dying halfway due to resource scarcity. Attached Figure Description

[0018] Figure 1 A schematic diagram of the platform provided by this invention; Detailed Implementation The following is a reference to the accompanying drawings in the instruction manual. Figure 1 The present invention will be further described in detail below with reference to the embodiments: A digital teaching resource sharing and guidance platform for environmental design, comprising: Digital resource standardization module; This module is used to collect teaching resources, design cases, and multi-source digital materials; At the same time, it standardizes the collected unstructured resources to build a standardized and structured resource database specifically for environmental design. The digital resource standardization module performs the following steps in standardizing resources: S11. Collect resources from the entire domain; collect digital resources through web crawling, university and enterprise uploading, and industry cooperation import. Digital resources include 3D modeling resources for environmental design, landscape design schemes, commercial real-world project resources, and digital renderings. S12. Resource standardization processing: Perform unified format conversion on the collected multi-format resources and remove damaged and redundant resources; the resources include videos, pictures, documents, models, source files, etc. S13. Labeling: Label the standardized resources from six dimensions: professional direction, difficulty level, applicable scenarios, teaching purpose, entrepreneurial suitability, and copyright attributes. S14. Hierarchical rights confirmation: Classify all resources into free teaching and sharing resources, paid commercial resources, and authorized trial resources, generate resource copyright traceability codes, and realize full traceability of resource sharing.

[0019] User segmentation and profiling modeling module; This module is used to collect user information, classify it, and identify user needs. The resource sharing and matching module pushes relevant resource information based on user profiles. The user tiered profile modeling module also collects data on users' resource usage frequency, entrepreneurial intentions, and practical experience, categorizing users into general learners, aspiring entrepreneurs, and startup users. General learners are students or industry newcomers with no clear entrepreneurial intentions, whose core needs are professional course learning, practical training, and skills enhancement. Aspiring entrepreneurs are students, teachers, and industry professionals with entrepreneurial plans, currently preparing entrepreneurial projects or learning entrepreneurial knowledge. Startup users are employees of startup entities that have registered studios and are conducting small-scale entrepreneurial operations. Specifically, general learners are provided with suitable teaching materials, practical training materials, course videos, and other basic teaching resources, while aspiring entrepreneurs and startup users are targeted with entrepreneurial empowerment resources such as business design cases, entrepreneurial practice tutorials, industry pricing standards, and project bidding templates, achieving differentiated and precise sharing of teaching resources.

[0020] The Entrepreneurship Guidance Module includes an environmental design entrepreneurship knowledge base, an entrepreneurship policy analysis unit, an entrepreneurship planning guidance unit, and a risk warning unit. It provides users with exclusive entrepreneurship knowledge popularization, interpretation of university and local entrepreneurship policies, personalized entrepreneurship plan customization, and entrepreneurship risk prediction and avoidance guidance services. The startup project simulation incubation module is used to simulate startup projects and provides guidance on project modification and optimization, completing online polishing and pre-incubation of startup projects. The startup project simulation incubation module includes a training and assessment unit, which is used to set up environment design for entrepreneurial practice test questions, project bidding simulation and customer negotiation simulation scenarios, record user training data, generate entrepreneurial ability assessment reports, and provide data support for users to optimize entrepreneurial ability and improve startup projects. The university-enterprise collaboration service module connects entrepreneurs with physical startup space resources, establishing a communication channel between entrepreneurs and physical spaces. It can automatically filter the best startup space resources based on the scale of the user's startup project, design track, office equipment needs, and geographical requirements. At the same time, it provides a one-stop online service for startup space application, qualification review, venue reservation, and university-enterprise cooperation project matching.

[0021] Data storage and encryption module; The data storage and encryption module is used to store all data on the platform, and at the same time establishes encryption procedures (hierarchical encryption, access control, and data anonymization) to ensure data security; The Entrepreneurship Community Interaction Module is used to build an environment for entrepreneurial exchange and communication, supporting users to share resources, exchange entrepreneurial experiences, and connect with project partners.

[0022] The digital resource standardization module incorporates a resource-based entrepreneurship adaptation quantification model. This model uses a formula to quantitatively differentiate between general teaching resources and entrepreneurship empowerment resources, enabling precise selection of entrepreneurial resources. The resource-based entrepreneurship adaptation quantification formula is as follows: in, The environmental design resource suitability score for entrepreneurship is given, with a value range of 1-100. To match the resource with commercial application scenarios, To improve the practical reusability of resources industry practices, It provides auxiliary value for the implementation of resource projects. Resource obsolescence and degradation coefficient; , , , The S-score represents the resource obsolescence and decay coefficient, while the S-score represents the weighted correction coefficient obtained from big data training based on the sub-tracks of interior design, landscape design, and public space renovation. The sum of these four coefficients is 1, used to automate the stratified screening of resources. A higher S-score indicates that the resource can be used for commercial order taking, project implementation, and entrepreneurial practice; a lower S-score indicates that the resource is only suitable for classroom learning and introductory practice, and is not suitable for commercial use.

[0023] Specifically, the matching degree of resource commercial application scenarios can be obtained from the platform's pre-stored environmental design sub-track commercial scenario tag library. By comparing the overlap between the current resource tags and real commercial order scenarios (home decoration, commercial decoration, landscape renovation, municipal projects), the more overlapping scenarios, the better. The higher the value, the better the pure classroom practice resources. Automatically set to low, with a value range of 0-100; The resource industry's practical reuse rate is obtained based on the platform's historical big data statistics. By analyzing the frequency with which past entrepreneurial users have commercially downloaded, reused, and applied these resources, high-frequency reuse business cases are identified. The value is too high; this applies to homework resources. The value is too low; The auxiliary value of resource projects is determined based on a structured assessment of resource types, while construction drawings, budget lists, construction specifications, and complete solutions are considered. High value, for simple renderings or reference materials, etc. The value is low; The resource obsolescence attenuation coefficient is obtained iteratively from the platform's built-in dynamic time attenuation model. The older the release date, the more outdated the industry standards and design style, the higher the coefficient. The larger the value, the range is 0-20; The weight coefficients are obtained by training with large datasets of samples from specific market segments and processing them using the Analytic Hierarchy Process (AHP). These are the optimal fixed weights after the industry sample training has converged; where: Optimal weighting for the interior design track: =0.35, =0.30, =0.25, =0.1; Optimal weighting for the landscape design track: =0.30, =0.35, =0.25, =0.1; Optimal weighting for the public space renovation track: =0.35, =0.25, =0.30, =0.1; The user profiling module incorporates a user entrepreneurial potential scoring model, which accurately categorizes users into different levels using a user entrepreneurial potential scoring formula. The user entrepreneurial potential scoring formula is as follows: in, A comprehensive score is given to users' entrepreneurial potential, with a value range of 1-100; The platform quantifies and generates metrics to measure users’ mastery of professional skills through practical training assessments and resource learning. To increase user activity in entrepreneurial activities; User project practical experience points; The risk factor for entrepreneurship is the minimum threshold. , , , These are normalized weighting coefficients used for the automatic rigid partitioning of user levels.

[0024] The user tiered profile modeling module is configured with a rigid tiered mechanism based on a score threshold, using the user's comprehensive entrepreneurial potential score P as the criterion: when P < 30, the user is judged as an ordinary learning user; when 30 ≤ P ≤ 70, the user is judged as a potential entrepreneurial user; and when P > 70, the user is judged as a startup user. Specifically, the user's mastery of professional skills is obtained by a structured and quantitative summary of the user's platform course completion rate, practical training score, model assignment score, and exam score; the value range is 0-100. User entrepreneurial activity level is quantified by statistical analysis of user behavior, including the number of times they browse the entrepreneurial zone, the duration of learning entrepreneurial courseware, the number of simulation exercises, and the frequency of entrepreneurial consultations; the value ranges from 0 to 100. User project practical experience value is quantified by the number of design schemes uploaded by the user, the number of times they participated in simulated projects, the number of times they optimized and iterated the schemes, and the training rating, with a value range of 0-100. The startup risk deficiency coefficient is quantified by the lack of specific characteristics; lack of project experience, lack of business acumen, lack of pricing knowledge, and lack of compliance knowledge are all considered deficiencies. The higher the value; The normalized weighting coefficients are fixed optimal coefficients obtained from machine learning fitting of the entrepreneurial samples, where, =0.40 (Skill weight is the highest, core of the design industry). =0.25 (Entrepreneurial Activity Level) =0.25 (practical experience). =0.1 (risk deduction coefficient).

[0025] The resource sharing and matching module adopts an improved collaborative filtering algorithm, equipped with an intelligent matching weight quantification calculation model, and combines users' historical browsing, downloading, collection and operation records to build a resource demand prediction model to achieve accurate push; The intelligent resource matching weight formula achieves a dynamic weight balance between learning needs and entrepreneurial needs, enabling differentiated and precise resource delivery. The intelligent resource matching weight formula is as follows: in, The matching weight value between users and resources is determined by the weight value; the higher the weight value, the higher the push priority. Matching the user's basic learning needs; The entrepreneurship-oriented demand bias coefficient is close to 0 for general learners and close to 1 for aspiring entrepreneurs and early-stage startups. This coefficient is used to dynamically balance the dual needs of learning and entrepreneurship and to construct differentiated data push logic. Highly commercially relevant practical resources are prioritized for entrepreneurial users, while also supporting user-defined resource sharing permissions to enable compliant sharing and paid trading of personal original teaching resources and design works.

[0026] Specifically, the matching degree of a user's basic learning needs is obtained by matching the teaching attributes of resources based on the user's major and year of study, learning progress, courses already taken, and tags indicating weak knowledge points. For example, if a user is a second-year interior design student, second-year course resources will be prioritized. If the difficulty of the resource far exceeds the user's learning stage, then... The value decreases; the value range is 0-100. The entrepreneurial demand bias coefficient is a comprehensive score of users' entrepreneurial potential. Dynamic mapping shows that when P < 30, the user is classified as a regular learner. As the value approaches zero, the system becomes completely biased towards matching learning resources, and the weighting for entrepreneurship becomes ineffective; when 30 ≤ P ≤ 70, the user is judged as a potential entrepreneur. Linear interpolation of 0.3–0.7 is used, and the system simultaneously pushes learning and entrepreneurial resources; when P > 70, the user is identified as a startup user. As it approaches 1, the system becomes completely biased towards the weighting of entrepreneurial and commercial resources.

[0027] The specific implementation process is as follows: Step 1: Through the standardized digital resource module, batch collect teaching materials, training models, course videos, and graduation project cases of environmental design from universities. At the same time, connect with industry enterprises to collect commercial design schemes, project bidding cases, construction drawings, and entrepreneurial operation materials. Complete the format unification, deduplication and noise reduction, multi-dimensional tagging and copyright classification of all resources, and build a dedicated structured database containing teaching resources, training resources, entrepreneurial resources, and commercial case resources to provide data support for subsequent resource sharing and entrepreneurial empowerment.

[0028] Step 2: After completing real-name authentication and registration on the platform, users fill in basic information such as professional background, learning stage, entrepreneurial intention and work experience. The platform automatically collects user behavior data such as browsing, downloading, training and consulting resources. Through the user hierarchical profile modeling module, users are divided into three categories: ordinary learning users, entrepreneurial preparatory users and start-up users. The platform dynamically updates user profile tags to accurately identify users' core needs.

[0029] Step 3: The resource sharing and matching module executes a differentiated resource push strategy based on user profile type and real-time scoring data. It filters high-value teaching and entrepreneurial resources using a resource entrepreneurship adaptation metric formula, dynamically updates user levels and needs attributes using a user entrepreneurial potential scoring formula, and calculates push priority using a resource intelligent matching weight formula. For general learners, it pushes free teaching resources such as courseware, basic modeling tutorials, and introductory training materials to meet their professional learning and skills enhancement needs. For aspiring entrepreneurs, it pushes preparatory resources such as basic entrepreneurial tutorials, industry pricing standards, small project cases, and business plan templates. For startups, it targets users with high-end business cases, project operation plans, customer development techniques, and industry compliance documents, while also supporting users to upload original resources, set sharing permissions and transaction models, and achieve resource sharing and compliant monetization.

[0030] Step 4: Aspiring and early-stage entrepreneurs can access services such as specialized entrepreneurial knowledge learning, precise interpretation of local and university entrepreneurial policies, personalized entrepreneurial plan customization, and entrepreneurial risk prediction through the entrepreneurial guidance module. The platform matches relevant industry operational data, profit models, and competitor analysis reports based on the user's entrepreneurial track (interior design / landscape design / public space renovation), addressing the issue of insufficient professionalism in general entrepreneurial guidance.

[0031] Step 5: Users upload their personal business plan, project proposal, and designed business creation. The business project simulation incubation module uses a built-in industry big data model to conduct a comprehensive assessment of the project's market feasibility, profit potential, and potential risks, and automatically generates project optimization suggestions. At the same time, it provides practical scenarios such as entrepreneurial training, simulated bidding, and customer negotiation, records training data, and generates capability assessment reports to help users refine and improve their business projects and complete online pre-incubation.

[0032] Step 6: For startups with physical operation needs, the university-enterprise collaboration service module intelligently matches users with space resources such as university incubation bases, social design entrepreneurship industrial parks, and shared design studios based on the scale of the user's startup project, track type, venue and equipment requirements, and regional preferences. It automatically completes the qualification review, on-site reservation, and project matching process. At the same time, it connects with platform cooperation resources to provide investment and financing matching and university-enterprise cooperation project implementation services for high-quality startup projects, realizing a closed loop from online incubation to offline implementation of startup projects.

[0033] Step 7: Users can participate in industry entrepreneurship exchanges, resource sharing, and project cooperation negotiations through the entrepreneurship community interaction module. The platform will regularly invite industry designers, entrepreneurship mentors, or business practitioners to conduct online Q&A sessions and entrepreneurship lectures, and continuously update the entrepreneurship knowledge base and resource library to achieve dynamic iteration and optimization of platform services.

[0034] The above descriptions are merely embodiments of the present invention, and common knowledge such as specific technical solutions and / or characteristics are not described in detail here. It should be noted that those skilled in the art can make various modifications and improvements without departing from the technical solutions of the present invention, and these should also be considered within the scope of protection of the present invention. These modifications and improvements will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. A digital teaching resource sharing and guidance platform for environmental design, characterized in that, include: Digital resource standardization module; The digital resource standardization module is used to collect teaching resources, design cases, and multi-source digital materials; at the same time, it standardizes the collected unstructured resources to build a standardized and structured resource database specifically for environmental design. User hierarchical profiling modeling module; the user hierarchical profiling modeling module is used to collect user information, classify user information, and locate user needs; Resource sharing and matching module; the resource sharing and matching module is used to push corresponding resource information based on user profile; The entrepreneurship guidance module includes an environmental design entrepreneurship knowledge base, an entrepreneurship policy analysis unit, an entrepreneurship planning guidance unit, and a risk warning unit. It is used to provide users with exclusive entrepreneurship knowledge popularization, interpretation of university and local entrepreneurship policies, personalized entrepreneurship plan customization, and entrepreneurship risk prediction and avoidance guidance services. Startup project simulation incubation module; The startup project simulation incubation module is used to simulate startup projects, while providing guidance on project modification and optimization, and completing the online polishing and pre-incubation of startup projects; The university-enterprise collaboration service module is used to connect entrepreneurs with physical entrepreneurial space resources and establish a communication channel between entrepreneurs and physical spaces. Data storage and encryption module; the data storage and encryption module is used to store all data of the platform, and at the same time establishes encryption procedures to ensure data security.

2. The digital teaching resource sharing and guidance platform for environmental design as described in claim 1, characterized in that, The digital resource standardization module performs the following steps in standardizing resources: S11. Collect resources from the entire domain; collect digital resources through web crawling, university and enterprise uploading, and industry cooperation import. Digital resources include 3D modeling resources for environmental design, landscape design schemes, commercial real-world project resources, and digital renderings. S12. Resource standardization processing: Perform unified format conversion on the collected multi-format resources and remove damaged and redundant resources; S13. Labeling: Label the standardized resources from six dimensions: professional direction, difficulty level, applicable scenarios, teaching purpose, entrepreneurial suitability, and copyright attributes. S14. Hierarchical rights confirmation: Classify all resources into free teaching and sharing resources, paid commercial resources, and authorized trial resources, generate resource copyright traceability codes, and realize full traceability of resource sharing.

3. The digital teaching resource sharing and guidance platform for environmental design as described in claim 1, characterized in that, The user segmentation and profiling modeling module also collects data on users' different resource usage frequencies, entrepreneurial intentions, and practical experiences, dividing users into ordinary learning users, aspiring entrepreneurs, and startup users. Ordinary learning users are students or industry newcomers with no clear entrepreneurial intentions and whose core needs are professional course learning, practical training, and skills improvement. Aspiring entrepreneurs are teachers, students, and industry practitioners with entrepreneurial planning intentions who are preparing entrepreneurial projects or learning entrepreneurial knowledge. Startup users are employees of startup entities who have registered studios and are conducting small-scale entrepreneurial operations.

4. The digital teaching resource sharing and guidance platform for environmental design as described in claim 1, characterized in that, The digital resource standardization module incorporates a resource entrepreneurship adaptation quantification model, which uses a resource entrepreneurship adaptation quantification formula to quantitatively distinguish between ordinary teaching resources and entrepreneurship empowerment resources; the resource entrepreneurship adaptation quantification formula is as follows: in, The environmental design resource suitability score for entrepreneurship is given, with a value range of 1-100. To match the resource with commercial application scenarios, To improve the practical reusability of resources industry practices, It provides auxiliary value for the implementation of resource projects. , , , is the resource obsolescence and decay coefficient, and is the weight correction coefficient obtained from big data training based on the sub-tracks of interior design, landscape design, and public space renovation. The sum of the four coefficients is 1.

5. The digital teaching resource sharing and guidance platform for environmental design as described in claim 3, characterized in that, The user profiling and modeling module incorporates a user entrepreneurial potential scoring model, which accurately classifies users into different levels using a user entrepreneurial potential scoring formula. The user entrepreneurial potential scoring formula is as follows: in, A comprehensive score is given to users' entrepreneurial potential, with a value range of 1-100; The platform quantifies and generates metrics to measure users’ mastery of professional skills through practical training assessments and resource learning. To increase user activity in entrepreneurial activities; User project practical experience points; The risk factor for entrepreneurship is the minimum threshold. , , , These are normalized weighting coefficients used for the automatic rigid partitioning of user levels.

6. The digital teaching resource sharing and guidance platform for environmental design as described in claim 1, characterized in that, The resource sharing and matching module adopts an improved collaborative filtering algorithm, equipped with an intelligent matching weight quantification calculation model, and combines users' historical browsing, downloading, collection and operation records to build a resource demand prediction model to achieve accurate push; The intelligent resource matching weight formula achieves a dynamic weight balance between learning needs and entrepreneurial needs, enabling differentiated and precise resource delivery. The intelligent resource matching weight formula is as follows: in, The matching weight value between users and resources is determined by the weight value; the higher the weight value, the higher the push priority. Matching the user's basic learning needs; This represents the entrepreneurial demand bias coefficient.

7. The digital teaching resource sharing and guidance platform for environmental design as described in claim 1, characterized in that, The startup project simulation incubation module includes a practical training and assessment unit. This unit is used to set up environment design for practical startup exam questions, project bidding simulation, and customer negotiation simulation scenarios. It records user training data, generates startup capability assessment reports, and provides data support for users to optimize their startup capabilities and improve their startup projects.

8. The digital teaching resource sharing and guidance platform for environmental design as described in claim 1, characterized in that, The university-enterprise collaboration service module can automatically filter the best entrepreneurial space resources based on the scale of the user's entrepreneurial project, the design track, the office equipment needs, and the geographical requirements. At the same time, it provides a one-stop online service for entrepreneurial space application, qualification review, venue reservation, and university-enterprise cooperation project matching.

9. The digital teaching resource sharing and guidance platform for environmental design as described in claim 1, characterized in that, It also includes an entrepreneurial community interaction module, which is used to build an environment design entrepreneurial exchange community, supporting users to share resources, exchange entrepreneurial experiences, and connect with project partners.

10. The digital teaching resource sharing and guidance platform for environmental design as described in claim 5, characterized in that, The user tiered profile modeling module is configured with a rigid tiered mechanism based on a score threshold, using the user's comprehensive entrepreneurial potential score P as the criterion: when P < 30, the user is judged as an ordinary learning user; when 30 ≤ P ≤ 70, the user is judged as a potential entrepreneurial user; and when P > 70, the user is judged as a startup user.

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