Dynamic digital textbook generation system and method with separated structure and content

Abstract

The invention discloses a structure and content separated dynamic digital textbook generation system and method.In the using process, a situation awareness module firstly obtains situation information, individual feature information and teaching and learning historical information of a user, and the specific requirement of the current digital textbook user is recognized; and the automatic generation module sequentially confirms a structural framework of the digital textbook from the data storage module according to the demand feature combination, extracts an element set which is highly matched with the current teaching situation, and carries out structured assembly on the extracted element set according to the structural framework. The assembled digital textbook is subjected to polymorphic display and personalized presentation through the polymorphic output module, and the dynamic supervision module ensures supervision strictness and quality compliance of the digital textbook generation, use and update processes. According to the invention, more accurate and efficient resource supply can be realized, and personalized demands of teaching and learning are supported.

Description

Technical Field

[0001] The present invention belongs to the technical field of online education, and in particular relates to a dynamic digital teaching material generation system and method with separated structure and content. Background Art

[0002] The accelerated innovation of digital technology is driving the rapid development of various fields, and it has also played a huge supporting and promoting role in the development and reform of education. In teaching, digital teaching materials have become an important tool for enriching the teaching material system and teaching design, and are very important digital teaching resources.

[0003] At present, the development of digital textbooks presents certain pattern characteristics, such as the e-book model, interactive textbook model, adaptive textbook model, hybrid textbook model, socialized textbook model and news publishing industry standard model. The e-book model converts paper textbooks into e-book format, allowing students to access digital textbook content through electronic devices such as tablets, e-readers or smartphones. The interactive textbook model adds rich interactive functions to the e-book to improve learning participation and effectiveness. This model can include multimedia elements, and students and teachers can interact directly with the textbooks. Compared with the digital textbooks of the e-book model, it brings users a better interactive experience. The adaptive textbook model dynamically adjusts the learning order and knowledge difficulty of the textbooks based on learning analysis and algorithms, and provides personalized teaching and learning suggestions and recommends relevant resources. The hybrid textbook model combines digital textbooks with traditional textbooks to create a teaching experience that combines online and offline learning elements. Users can use digital textbooks in the classroom to interact and discuss with teachers and classmates. The socialized textbook model emphasizes social interaction and collaborative learning among students. Through online platforms or applications, students can share notes, discuss problems, solve problems together, and participate in online learning communities. The socialized textbook model improves learning effectiveness through collaborative learning and cooperative projects, and increases students' participation, motivation and learning interest. Teachers play the role of instructors and facilitators in the socialized textbook model, encouraging and guiding interactions between students. The standard model of the news publishing industry can be simply expressed as A→A'+a, where A represents paper textbooks, A' represents the digital version of paper textbooks, and a represents the multimedia resource set that matches A or A'. Based on A→A'+a, A→A'+a+b+c can also be derived. Among them, b and c represent tool sets and service sets that can match A. However, the teaching strategies and teaching activities in A or A' are designed for non-informationized environments. The teaching strategies in a and A or A' usually do not match, resulting in the content of digital textbooks and the logic of teaching strategies being inconsistent, making it difficult to support conventional digital teaching activities.

[0004] These typical digital teaching material technology models provide a wealth of choices and innovations for education. Technology models can be used alone or in combination, and appropriate models can be selected according to different teaching needs and student characteristics. However, the current technology models have the characteristics of rigid structure and single teaching strategy, which leads to the lack of ability of digital teaching materials to adaptively support dynamic teaching and learning. Summary of the invention

[0005] To solve the above technical problems, the present invention provides a dynamic digital teaching material generation system and method with separated structure and content, which enables users to dynamically generate adaptive digital teaching materials according to situational characteristics and user roles during the teaching and learning process.

[0006] To achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0007] A dynamic digital teaching material generation system with separated structure and content, the system comprises a data storage module, a context awareness module, an automatic generation module, a polymorphic output module and a dynamic supervision module, wherein:

[0008] A data storage module is responsible for storing and managing various element libraries of the dynamic digital teaching material generation system, wherein the various element libraries all use the triple form of <entity, relationship, attribute> to semantically represent the elements;

[0009] A context perception module is used to perceive the context when generating and using digital teaching materials, including the user's time and space context, physical environment context, medium context, teaching context and individual characteristic context;

[0010] An automatic generation module is used to determine an adapted teaching material structure framework according to the perception results of the situation perception module, and to extract a plurality of teaching material element sets adapted to the perception results from the data storage module to automatically construct a digital teaching material;

[0011] A polymorphic output module, used for polymorphic display and personalized presentation of the automatically constructed digital teaching materials;

[0012] The dynamic supervision module is used to dynamically supervise the automatic generation process, usage process, and update process of digital teaching materials.

[0013] Furthermore, in the dynamic digital teaching material generation system with separated structure and content, the various element libraries of the data storage module include a knowledge base, a context library, a target library, an individual library, a template library, a strategy library, a resource library, an activity library, a tool library, and a material library.

[0014] Furthermore, in the dynamic digital teaching material generation system with separated structure and content, the individual characteristic context includes knowledge mastery level, learning style preference and role identity.

[0015] Furthermore, in the dynamic digital teaching material generation system with separated structure and content, the spatiotemporal context information includes the learner's time and geographical location, which is determined by the global positioning system and the device's built-in clock; the physical environment context information includes light, temperature, humidity and noise, which is determined by monitoring the integrated environmental sensors; the medium context information includes the device brand, model, operating system, screen size and resolution, which is obtained through the system's built-in tools; the teaching context and individual characteristic context information rely on historical usage data and user information input.

[0016] Furthermore, in the dynamic digital teaching material generation system with separated structure and content, the automatic generation module realizes the automatic construction of digital teaching materials through three sub-modules of confirming the structural framework, extracting the element set and structured assembly; the confirming structural framework sub-module uses the detailed contextual information provided by the contextual awareness module to determine the teaching material structure framework suitable for specific teaching needs and individual characteristics; the extracting element set sub-module extracts the teaching material element set that matches the detailed contextual information from the data storage module; and the structured assembly sub-module performs orderly structured assembly of the extracted teaching material element set according to the confirmed teaching material structure framework.

[0017] Furthermore, in the dynamic digital teaching material generation system with separated structure and content, when the structured assembly submodule performs structured assembly, a loop filling algorithm is used to orderly assemble the extracted teaching material element set according to the confirmed teaching material structure framework to form a digital teaching material aggregation package.

[0018] Furthermore, in the dynamic digital teaching material generation system with separated structure and content, the polymorphic output module reads the digital teaching material aggregation package generated by the automatic generation module, and designs a variety of presentation forms and interaction methods according to the user's time and space context, physical environment context, medium context, teaching context and individual characteristic context.

[0019] Furthermore, in the dynamic digital textbook generation system with separated structure and content, the dynamic supervision module includes a pre-publication review of the digital textbook and generative supervision during use, and the review and supervision both include a human-machine combined review form of machine screening and manual review.

[0020] Under the support of the dynamic digital teaching material generation system with separated structure and content, the present invention also provides a dynamic digital teaching material generation method with separated structure and content, which mainly includes the following steps:

[0021] Step 1: The context awareness module uses the built-in sensors and information processing technology of the device to fully perceive the characteristics of the user and his environment, including the spatiotemporal context, physical environment context, medium context, teaching context, and individual characteristic context;

[0022] Step 2: The automatic generation module receives the perception results of the situation perception module, analyzes various situation feature combinations according to the set rules, identifies the teaching material structure framework that meets specific needs, and extracts a teaching material element set that matches the situation features from the data storage module;

[0023] Step 3: The automatic generation module generates digital teaching materials by using a loop filling algorithm to perform structured assembly based on the determined teaching material structure framework and the extracted teaching material set;

[0024] Step 4: The polymorphic output module selects an adaptive display layout and interaction mode for the generated digital teaching materials based on modularization and componentization;

[0025] Step 5: The dynamic supervision module uses cloud services to achieve centralized supervision of digital teaching materials, including pre-publication approval and productive supervision during use.

[0026] The beneficial effects of the present invention are:

[0027] Firstly, the dynamic digital teaching material generation system with separated structure and content of the present invention greatly improves the personalization and adaptability of teaching material generation. Through the sophisticated semantic representation of resources and contexts, such as RDF triple annotation, the system can accurately customize and combine the content of the textbooks, dynamically aggregate and generate the most suitable combination of elements according to the specific needs of users and the context of teaching and learning; secondly, a dynamic digital textbook generation model is proposed, which separates the structure and content of the resources, defines the elements separately, and forms a complete digital textbook composition system, highlighting the teaching, adaptability, publishing, polymorphism and controllability of digital textbooks. Based on this model, users can dynamically generate adaptive digital textbooks according to context characteristics and user roles in the teaching and learning process; in addition, the present invention realizes the transformation of the supply of dynamic digital textbook resources from focusing on external tools to focusing on internal needs, and realizes the design of learning scenarios and cognitive processes of digital textbooks in different display forms, which can promote learners' in-depth learning, break the limitations of material solidification, and fully consider the needs of different teaching modes and user roles; finally, based on the dynamic digital textbook generation model and mechanism, the present invention designs a supervision mode for digital textbook content. This dynamic supervision mode further improves the quality and teaching effect of the textbooks, making the textbook generation process more accurate and effective. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1It is a logic flow chart of a dynamic digital teaching material generation system with separated structure and content of the present invention;

[0029] Figure 2 A schematic diagram of a semantic representation method for digital teaching material elements supporting semantic query implemented by the present invention;

[0030] Figure 3 A schematic diagram of the composition of a digital teaching material model supporting separation of structure and content implemented by the present invention;

[0031] Figure 4 This is an implementation effect diagram of the digital teaching material generation system in a teaching scenario implemented by the present invention. DETAILED DESCRIPTION

[0032] In order to make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0033] The technical problem to be solved by the present invention is: how to improve the diversity of digital teaching materials and dynamically generate rich and diverse teaching materials that adapt to various learning situations and teaching strategies while ensuring the strict supervision of digital teaching materials. Existing digital teaching material generation systems usually rely on fixed templates and preset content, which is difficult to meet the rapidly changing teaching needs and specific requirements of personalized learning. The present invention designs a highly flexible mechanism for separating structure and content through context-aware technology, semantic ontology technology and dynamic recommendation technology, and carefully designs and semantically annotates the representation elements of teaching materials such as strategies, templates, and knowledge. According to the perceived teaching situation requirements, such as specific roles, situations, media, goals and other information, the structure and content elements of digital teaching materials are intelligently and dynamically combined, thereby generating polymorphic digital teaching materials that adapt to diverse needs. At the same time, the quality compliance of dynamically generated digital teaching materials is guaranteed by centralized management of digital teaching material content.

[0034] In order to solve the above technical problems, the present invention provides a logic flow chart of a dynamic digital teaching material generation system with separated structure and content as shown in FIG. Figure 1 As shown, it mainly includes five modules: data storage module, context awareness module, automatic generation module, polymorphic output module and dynamic supervision module, so as to dynamically generate high-quality personalized digital teaching materials. Among them:

[0035] The data storage module is responsible for storing and managing various element libraries of the dynamic digital textbook generation system, including knowledge base, context library, target library, individual library, template library, strategy library, resource library, activity library, tool library, material library, etc. To ensure the efficiency and accuracy of the automatic generation process of digital textbooks, all elements are semantically represented in the form of <entity, relationship, attribute> triples. The semantic representation of digital textbook elements that support semantic query is as follows: Figure 2As shown in the figure, owl:Thing represents all entities in the knowledge graph and points to all entities in the data storage module, including knowledge, context, objective, individual feature, template, strategy, resource, activity, tool and material, and the arrows between different entities represent the relationship between entities; the knowledge base stores the basic knowledge units, concepts and their relationships necessary for learning resources, providing accurate knowledge calls and references for the generation of teaching materials; the context library records in detail the specific environment and status of the learners, such as the time and space background, physical conditions, equipment usage status, etc., to ensure that the teaching materials can accurately adapt to the specific needs of each user; the target library clearly records the teaching objectives and expected results, providing a basis for the customization of teaching materials; the individual library collects and analyzes the user's learning style, cognitive ability and role identity, and supports the personalized adjustment and optimization of teaching materials; the template library provides a series of adaptive teaching methods. The strategy library contains a variety of teaching strategies and methods, specifies the core teaching links of digital teaching materials and their implementation forms, and ensures the efficient matching of teaching content and teaching methods. The resource library stores various teaching resources, such as videos, texts, images and multimedia files, to enrich the teaching materials and enhance the learning experience. The activity library designs detailed teaching activity plans to improve learners' participation and learning motivation through various interactive and participatory activities. The tool library provides various tools and auxiliary facilities to support the teaching and learning process, such as online calculators and communication platforms, to help learners complete learning tasks more effectively. The material library includes rich teaching materials, such as texts, images, audio, video, knowledge maps, 3D models, animations and various interactive materials, to support the specific assembly of resources and activities. This module uses OWL (Ontology Web Language) to provide strict semantic descriptions for all elements, and defines operation rules and constraints through SWRL (Semantic Web Rule Language) to ensure effective reasoning and filtering based on rich semantic information during the teaching material generation process. This comprehensive and in-depth data management and intelligent processing mechanism significantly improves the adaptability and teaching effectiveness of digital teaching materials, creating a more personalized and dynamic learning environment for education providers and learners.

[0036] The context perception module is used to realize the perception of the context when generating and using digital teaching materials, ensuring that digital teaching materials can accurately adapt to the specific needs of users and optimize the teaching and learning experience; the context includes the user's time and space context, physical environment context, medium context, teaching context and individual characteristic context; the time and space context involves the learner's time and geographical location, which is determined by GPS positioning and system timestamp; the physical environment context detects physical parameters such as light, temperature, humidity and noise in the environment through environmental sensors; the medium context covers device type, screen size, resolution, etc. to adapt to the teaching material display of different terminal devices; the teaching context includes information directly related to teaching, such as teaching objectives, strategies and knowledge points involved, which are used to guide the structure and organization of digital teaching material content; the individual characteristic context includes personalized characteristic context information such as the user's knowledge mastery level, learning style preference and role identity; when the user enters a specific context to generate and use digital teaching materials, its context information is collected and packaged through the sensor of the terminal medium, and finally passed to the automatic generation module in the form of a Json array. The form of the context information represented by the Json array is:

[0037] {

[0038] "contextId": "CTX123",

[0039] "spatialTemporalContext": {

[0040] "time": "2023-04-27T15:30:00Z",

[0041] "location": "Beijing",

[0042] "latitude": 39.9042,

[0043] "longitude": 116.4074,

[0044] "altitude": 44

[0045] },

[0046] "physicalContext": {

[0047] "illumination": "Bright",

[0048] "temperature": "22C",

[0049] "humidity": "40%",

[0050] "noiseLevel": "Low"

[0051] },

[0052] "deviceContext": {

[0053] "deviceModel": "Notebook Pro 15",

[0054] "operatingSystem": "Windows 10",

[0055] "screenSize": "15 inches",

[0056] "resolution": "1920x1080",

[0057] "processor": "Intel Core i7"

[0058] },

[0059] "educatingContext": {

[0060] "objective": "A1",

[0061] "strategy": "Inquiry",

[0062] "knowledge": "K0101"

[0063] },

[0064] "individualFeature": {

[0065] "knowledgeMastery": {

[0066] "knowledge": "K0101",

[0067] "cognitiveLevel": "B3"

[0068] },

[0069] "learningStylePreference": "Visual",

[0070] "userRole": "Student"

[0071] }

[0072] }

[0073] On the one hand, this information is encapsulated as a Json array to describe the personalized context of teachers or learners, and then transmitted to the client, which provides an adaptive interface for users. On the other hand, the transmitted data is stored in the form of xAPI, forming a clue collection that can be used by the data storage module and the automatic generation module to match the target template and material.

[0074] The automatic generation module is used to determine the adapted teaching material structure framework according to the perception results of the situation perception module, and extract a plurality of teaching material element sets adapted to the perception results from the data storage module to automatically construct the digital teaching material. The process is as follows: Figure 3 As shown in the figure, the confirmation structure framework submodule determines the teaching material structure framework suitable for specific teaching needs and individual characteristics based on the Json array of detailed context information provided by the context awareness module; the structure framework is based on specific goals and strategies, and organizes activities, resources, services and formats in a structured manner through semantic description information; the goals represent the individual characteristics of using digital teaching materials and the knowledge points that need to be mastered; the strategies clarify the teaching and learning strategies and their module divisions under specific individual characteristics and teaching situations; the activities, resources, services and formats are matched with goals and strategies to ensure the support and practicality of the teaching material content; the extraction element set submodule accurately extracts knowledge, strategies, goals, individuals, and other information that have a high degree of matching with the context information combination transmitted by the context awareness module from the data storage module. The structured assembly submodule is responsible for orderly assembling the extracted element set according to the structural framework, and using the loop filling algorithm to ensure that the activities, resources, tools, materials and other elements of each digital textbook structural framework submodule accurately correspond to the predetermined goals and strategies, and at the same time adjust the teaching service according to the individual characteristic elements, and use the knowledge elements to set the publication information of the textbook, so as to ensure that the generated digital textbook is reasonable in structure, complete in content, and can adapt to different teaching situations and individual specific needs; the automatic production module supports the supervisor to conduct quality review of various elements of the digital textbook content library, and updates the digital textbook content library according to the review results; the detailed calculation process is as follows:

[0075] 1) Situational information analysis: Receive and parse the Json array of detailed situational information provided by the situational awareness module.

[0076] 2) Structural framework setting: Analyze current teaching needs and individual characteristics to determine the most suitable teaching material structure framework. After the structural framework, the module will set specific teaching goals and strategies, and further use semantic descriptions to accurately organize the activities, resources, services and layout in the teaching materials to ensure the organization and logic of the teaching material content.

[0077] 3) Matching element extraction: Extract elements from the data storage module that are highly matched with the situational information transmitted from the situational awareness module, including knowledge, strategies, goals, individual characteristics, templates, situations, resources, activities, tools, materials, etc.

[0078] 4) Ordered assembly: Use the loop filling algorithm to assemble the elements extracted in the previous step in an orderly manner to ensure that the activities, resources, tools, materials and other elements of each sub-module can accurately correspond to the predetermined goals and strategies.

[0079] 5) Personalized adjustment: Adjust teaching services according to the input individual characteristics, and use the extracted knowledge elements to set the publishing information of the teaching materials, ensuring that the generated digital teaching materials are not only reasonable in structure and complete in content, but also can flexibly adapt to different teaching situations and meet the specific needs of individuals.

[0080] The polymorphic output module is used to support the polymorphic presentation of the generated digital teaching materials, ensuring that the teaching materials are adaptively displayed in different time and space situations, physical environment situations, media situations, teaching situations and individual characteristic situations. According to the specific environment and individual needs of the user, the output form of the teaching materials is dynamically adjusted. For different types of materials in the teaching materials content, such as text, images, videos, animations, etc., as well as various teaching and learning activities and resources, this module can provide adaptive layout and interactive design, support the effective use of teaching materials in a variety of teaching situations, and ensure that high-quality teaching and learning experiences can be provided in various time and space, physical, and media environments; the generated polymorphic digital teaching materials such as Figure 4 As shown, Figure 4 (Left) is the digital teaching material for the student role in the self-learning mode. Figure 4 (Middle) is the digital teaching material for the student role in the flipped classroom model. Figure 4 (Top right) is the digital teaching material of the student role in the knowledge review mode. Figure 4 (Bottom right) Digital teaching materials for student roles in the inquiry-based learning teaching model.

[0081] The dynamic supervision module is used for dynamic supervision of the entire life cycle of digital textbooks, ensuring the quality and compliance of textbooks from generation to use and then to updating. It uses cloud service technology to widely distribute digital textbooks, ensuring that users at all levels such as the national education cloud platform, schools, teachers, and students can easily obtain and use textbooks. All textbook content is stored in the cloud to enhance data security and access flexibility; publishing institutions manage textbook content through this platform, including controlling the use rights authorized to other institutions, maintaining the copyright of content and the standardization of distribution; regulatory agencies can centrally review and approve textbook content and its structural templates, and track and manage the updates and changes of each textbook content through the system. Based on the combination of manual review and machine screening, pre-publication approval review and generative supervision during use are carried out to ensure that all published textbooks meet education standards and regulatory requirements. For the dynamic digital textbook generation system, this module uses cloud service technology to centrally store and manage data, and based on the combination of manual review and machine screening, it realizes pre-publication approval review and generative supervision during use. It has the characteristics of "two links" and "two forms". The "two links" include the pre-publication pass review and the generative supervision during use, and the "two forms" refer to the human-machine combined review form of machine screening and manual review. The present invention intends to use J2EE technology to develop the functions of the supervision and review module of the dynamic digital textbook generation system, and the underlying database uses MySQL and Neo4j for storage. MySQL stores relatively simple entity relationships, and the Neo4j graph database stores complex knowledge relationships. Based on Spring MVC, data transmission between the background storage module and the front-end user end is realized.

[0082] Furthermore, in the dynamic digital teaching material generation system with separated structure and content, the representations of entities in the knowledge base, situation library, target library, individual library, template library, strategy library, resource library, activity library, tool library, and material library in the data storage module are all represented by ontology triples, in the form of <entity, relationship, attribute>.

[0083] Furthermore, in the dynamic digital teaching material generation system with separated structure and content, the construction of the contextual elements of the contextual awareness module includes not only external space-time context, physical environment context, medium context and teaching context, but also internal individual characteristic contexts such as knowledge mastery level, learning style preference and role identity.

[0084] Furthermore, in the dynamic digital teaching material generation system with separated structure and content, the context elements of the context perception module are obtained by comprehensively capturing and analyzing the user's environment and personalized characteristics through multiple sensors and logical sensors; the spatiotemporal context information is mainly determined by the global positioning system and the built-in clock of the device, accurately capturing time and geographic location data, including longitude and latitude and altitude; the physical context information monitors light, temperature, humidity and noise through integrated environmental sensors to evaluate environmental suitability; the medium context information obtains the device brand, model, operating system, screen size and resolution through the system's built-in tools to ensure the best display effect of the teaching material content on various devices; the teaching context and individual characteristic context information rely on historical usage data and user information input, analyzes learners' interaction data, test scores, homework submissions and questionnaire feedback, and collects comprehensive information about learning behavior patterns, knowledge mastery levels, learning style preferences and learning motivations.

[0085] Furthermore, in the dynamic digital teaching material generation system with separated structure and content, the automatic generation module realizes the automatic construction of digital teaching materials through three sub-modules of confirming the structural framework, extracting the element set and structured assembly; the confirming the structural framework sub-module uses the detailed situational information provided by the situational awareness module to determine the teaching material structure framework suitable for specific teaching needs and individual characteristics; the extracting the element set sub-module accurately extracts the teaching material elements that match the situational information from the data storage module, including knowledge, strategies, goals, individual characteristics, templates, etc.; the structured assembly sub-module assembles the extracted elements in an orderly manner according to the confirmed structural framework.

[0086] Furthermore, in the dynamic digital teaching material generation system with separated structure and content, when performing structured assembly in the automatic generation module, a loop filling algorithm is used to assemble the extracted element set in order according to the confirmed structural framework, so as to ensure that the activities, resources, tools, materials and other elements of each sub-module are accurately matched with the predetermined goals and strategies; the teaching service is adjusted according to the individual characteristic elements, and the knowledge elements are used to determine the publishing information of the teaching material, such as the cover design and the teaching material title, so as to ensure that the generated digital teaching material has a reasonable structure and complete content.

[0087] Furthermore, in the dynamic digital teaching material generation system with separated structure and content, the polymorphic output module reads the digital teaching material aggregation package generated by the automatic generation module, and designs a variety of presentation forms and interaction methods according to the user's time and space context, physical environment context, medium context, teaching context and individual learning style and cognitive style characteristics, so as to ensure that the presentation of teaching materials adapts to the context and the user's specific needs to the greatest extent possible.

[0088] Furthermore, in the dynamic digital textbook generation system with separated structure and content, the supervision model design of the dynamic supervision module has the characteristics of "two links" and "two forms"; the "two links" include the pre-publication pass review and the generative supervision in use, and the "two forms" refer to the human-machine combined review form of machine screening and manual review; the human-machine collaborative review process before publication includes the beginning of the review of material resources, machine screening, expert review, and ending or injecting resources into the digital textbook content library according to the review results; after the digital textbook generated by the collection of material resources is completed, the crowdsourcing supervision mechanism in use is started. This supervision mechanism includes three parts: machine screening, crowdsourcing supervision and expert judgment.

[0089] Under the support of the dynamic digital teaching material generation system with separated structure and content, the present invention also provides a dynamic digital teaching material generation method with separated structure and content, which mainly includes the following steps:

[0090] Step (1) When learners start using digital teaching materials, the context awareness module uses the built-in sensors and information processing technology of the device to fully perceive the characteristics of the user and his environment, including spatiotemporal context, physical environment context, medium context, teaching context, and individual characteristic context. The spatiotemporal context captures the user's specific time and geographic location through GPS and system timestamp; the physical environment context monitors conditions such as light, temperature, and humidity through environmental sensors; the medium context analyzes the user's device type and operating system to determine whether a computer, tablet, or mobile phone is used; the teaching context determines the teaching mode based on user input, such as lecture-based, inquiry-based, or personalized learning, and captures teaching goals and strategies; the individual characteristic context combines machine learning technology and user behavior data (such as learning progress, answer rate, and learning time) to evaluate the user's learning style and cognitive state, and identifies whether the user is a teacher or a student through role selection. These context information are integrated and packaged in Json format to provide data support for the next step of semantic processing.

[0091] Step (2) receives and processes the context features in the Json format collected in step (1). The automatic generation module analyzes various combinations of context features according to the set rules, identifies the structural framework features that are suitable for specific needs, and extracts the element set that matches the context from the data storage module. First, the individual characteristics and teaching context are analyzed to determine the goals and strategies of the structural framework. Then, by parsing the semantic description related to the context features, the specific activity or resource type and the required teaching and learning services and the layout design of the teaching materials are further determined to confirm the structural framework of the digital teaching materials. Based on the context features and the structural framework requirements, the element set is extracted, including knowledge, templates, strategies, resources, activities, tools, materials, etc. The extraction of each type of element is based on the preset quality evaluation standards and type matching rules to ensure that the selected content can best meet the context and individual needs. The digital teaching material structural framework and material set generated in this step will be passed to step (3).

[0092] Step (3) performs structured assembly on the structural framework determined in step (2) and the extracted material set. The automatic generation module automatically initializes and configures the strategy submodules based on pre-set rules by adopting a loop filling algorithm. First, the order of each submodule in the strategy and the corresponding resource or activity type are determined, and then the introduction, specific content and summary of each module are filled in turn, the teaching and learning services are adjusted according to individual characteristics, and the cover image, name and other publishing information of the digital textbook are generated using knowledge elements. The digital textbook generated in this step will be output to the polymorphic output module.

[0093] Step (4) realizes the polymorphic display of the digital teaching materials generated in step (3). The polymorphic output module selects adaptive display layouts and interactive methods based on the design concept of modularization and componentization. For different content element types, such as text, images, audio, video, knowledge maps, 3D files, various topics, animations, etc., a special display method is designed for each material and interactive tools are provided. Combined with individual characteristics, teaching situations and device situations, a variety of display layouts are applied to adapt to various cognitive styles, teaching modes and terminal devices. The polymorphic digital teaching materials generated in this step are presented to users.

[0094] Step (5) The dynamic supervision module uses cloud services to achieve centralized supervision of digital textbooks and conduct content supervision on the data storage module, including pre-publication approval review and in-use generative supervision. The human-machine collaborative review process before publication is to start reviewing the material resources, machine screening, expert review, and end or inject the material into the data storage module based on the review results. After the digital textbooks generated by the collection of material resources are digitally published, the crowdsourcing supervision mechanism is started, including machine screening, crowdsourcing supervision and expert judgment. According to the results of the supervision review, valuable content will be re-injected into the data storage module to achieve continuous updating and iteration of the element library.

[0095] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A dynamic digital teaching material generation system with structure and content separated. It is characterized in that The system includes a data storage module, a context awareness module, an automatic generation module, a polymorphic output module and a dynamic supervision module, wherein: The data storage module is responsible for storing and managing various element libraries of the dynamic digital teaching material generation system, and the various element libraries all use the triple form of <entity, relationship, attribute> to semantically represent the elements; The context perception module is used to perceive the context when generating and using digital teaching materials, and the context includes the user's time and space context, physical environment context, medium context, teaching context and individual characteristic context; The automatic generation module is used to determine the adapted teaching material structure framework according to the perception results of the situation perception module, and extract a plurality of teaching material element sets adapted to the perception results from the data storage module to automatically construct the digital teaching material; The polymorphic output module is used to display the automatically constructed digital teaching materials in polymorphic and personalized ways; The dynamic supervision module is used to dynamically supervise the automatic generation process, usage process, and update process of digital teaching materials.

2. A dynamic digital teaching material generation system with separated structure and content according to claim 1, It is characterized in that The various element libraries of the data storage module include a knowledge library, a context library, a target library, an individual library, a template library, a strategy library, a resource library, an activity library, a tool library, and a material library.

3. A dynamic digital teaching material generation system with separated structure and content according to claim 1, It is characterized in that The individual characteristic context includes knowledge mastery level, learning style preference and role identity.

4. A dynamic digital teaching material generation system with separated structure and content according to claim 1, It is characterized in that The spatiotemporal context information includes the learner's time and geographic location, which is determined by the global positioning system and the device's built-in clock; the physical environment context information includes light, temperature, humidity and noise, which are monitored and determined by integrated environmental sensors; the media context information includes device brand, model, operating system, screen size and resolution, which is obtained through the system's built-in tools; the teaching context and individual characteristic context information rely on historical usage data and user information input.

5. A dynamic digital teaching material generation system with separated structure and content according to claim 1, It is characterized in that The automatic generation module realizes the automatic construction of digital teaching materials through three sub-modules: confirming the structural framework, extracting the element set and structured assembly; the confirming the structural framework sub-module uses the detailed context information provided by the context perception module to determine the teaching material structural framework suitable for specific teaching needs and individual characteristics; the extracting the element set sub-module extracts the teaching material element set that matches the detailed context information from the data storage module; the structured assembly sub-module performs orderly structured assembly of the extracted teaching material element set according to the confirmed teaching material structural framework.

6. A dynamic digital teaching material generation system with separated structure and content according to claim 1, It is characterized in that When the structured assembly submodule performs structured assembly, a cyclic filling algorithm is used to orderly assemble the extracted teaching material element set according to the confirmed teaching material structure framework to form a digital teaching material aggregation package.

7. A dynamic digital teaching material generation system with separated structure and content according to claim 1, It is characterized in that The polymorphic output module reads the digital teaching material aggregation package generated by the automatic generation module, and designs a variety of presentation forms and interaction methods according to the user's time and space context, physical environment context, medium context, teaching context and individual characteristic context.

8. A dynamic digital teaching material generation system with separated structure and content according to claim 1, It is characterized in that The dynamic supervision module includes the pre-publication approval review of digital teaching materials and the generative supervision during use. The review and supervision both include a human-machine combination review mode of machine screening and manual review.

9. A method for generating dynamic digital teaching materials with separation of structure and content. It is characterized in that The method is implemented in the following steps: Step 1: The context awareness module uses the built-in sensors and information processing technology of the device to fully perceive the characteristics of the user and his environment, including the spatiotemporal context, physical environment context, medium context, teaching context, and individual characteristic context; Step 2: The automatic generation module receives the perception results of the situation perception module, analyzes various situation feature combinations according to the set rules, identifies the teaching material structure framework that meets specific needs, and extracts a teaching material element set that matches the situation features from the data storage module; Step 3: The automatic generation module generates digital teaching materials by using a loop filling algorithm to perform structured assembly based on the determined teaching material structure framework and the extracted teaching material set; Step 4: The polymorphic output module selects an adaptive display layout and interaction mode for the generated digital teaching materials based on modularization and componentization; Step 5: The dynamic supervision module uses cloud services to achieve centralized supervision of digital teaching materials, including pre-publication approval and productive supervision during use.

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