Teaching system, teaching resource processing method, computer device, readable storage medium, and program product

Abstract

The invention relates to a teaching system, a teaching resource processing method, computer equipment, a computer readable storage medium and a computer program product. The teaching system comprises an access layer used for providing a portal entrance to log in the teaching system; the application aggregation layer comprises a learning module used for collecting activity information of learning of a learner and constructing a user portrait of the learner based on the activity information; determining a learning scheme based on the user portrait and the course knowledge graph; the teaching module is used for acquiring teaching resource information and constructing a course knowledge graph based on the teaching resource information; determining target learning resource information from the teaching resource information according to the learning scheme; the teaching and research module is used for constructing a virtual teaching and research room and sending the information to the virtual teaching and research room; and the background service layer is used for providing an interface service and a graph engine service and distributing system permissions to learners, teaching and research persons and system managers. The system realizes the integration of learning, teaching and teaching research in a digital environment.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of information technology, and in particular, to a teaching system, a teaching resource processing method, a computer device, a computer readable storage medium, and a computer program product. BACKGROUND

[0002] With the development of digital technology, the traditional education mode gradually develops into a digital teaching mode. Digital teaching can collect a large amount of digital teaching resources to provide convenience for learners. However, at present, the teaching system for digital teaching mainly focuses on the learning needs of learners, and lacks system function support related to teaching and research. SUMMARY

[0003] Therefore, it is necessary to provide a teaching system, a teaching resource processing method, a computer device, a computer readable storage medium, and a computer program product to realize the integration of learning, teaching, and teaching and research in a digital environment.

[0004] In a first aspect, the present application provides a teaching system, comprising:

[0005] An access layer is configured to provide a unified portal for learners, researchers, and system managers to log in to the teaching system.

[0006] An application aggregation layer includes a teaching module, a learning module, and a teaching and research module, wherein:

[0007] The teaching module is configured to obtain teaching resource information and construct a course knowledge graph based on the teaching resource information.

[0008] The learning module is configured to collect activity information of learners learning in the teaching system and construct a user portrait of the learners based on the activity information. Based on the user portrait and the course knowledge graph in the teaching module, a learning scheme corresponding to the learners is determined. The learning scheme includes target knowledge points in the course knowledge graph that the learners need to learn and the learning order between the target knowledge points.

[0009] The teaching module is further configured to determine target learning resource information from the teaching resource information according to the learning scheme and recommend the target learning resource information to the learners for learning.

[0010] The teaching and research module is configured to construct a virtual teaching and research room and display the teaching resource information, the course knowledge graph, the user portrait, and the learning scheme in the virtual teaching and research room for researchers to log in to the teaching system and use in the virtual teaching and research room for teaching and research.

[0011] A background service layer is configured to provide interface services for the access layer, provide graph engine services for the application aggregation layer, store data corresponding to the application aggregation layer, and assign corresponding system permissions to the learners, researchers, and system managers.

[0012] In one of the embodiments, the teaching module is further configured to:

[0013] determine learning information of the learner in the teaching system for learning the target learning resource information;

[0014] determine the mastery information of the target knowledge point of the learner based on the learning information;

[0015] generate learning suggestion information according to the mastery information and recommend it to the learner.

[0016] In one of the embodiments, the teaching module is further configured to: send the learning information and the mastery information to the virtual research office for the researchers to log in the teaching system and use in the virtual research office for teaching research.

[0017] In one of the embodiments, the teaching module is further configured to:

[0018] obtain question information raised by the learner for the target knowledge point corresponding to the target learning resource information;

[0019] determine answer information corresponding to the question information according to the course knowledge graph and the target learning resource information, to answer the questions in the question information;

[0020] statistically determine the click and reading information of the learner in the teaching system for the target learning resource information;

[0021] determine the learning information of the learner for the target learning resource information according to the click and reading information, the question information and the answer information.

[0022] In one of the embodiments, the teaching module is further configured to:

[0023] determine the target knowledge point that has been learned by the learner based on the click and reading information, and generate test question information;

[0024] send the test question information to the learning terminal corresponding to the learner, and receive the answer information fed back by the learning terminal;

[0025] determine the learning information of the learner for the target learning resource information according to the click and reading information, the question information, the answer information, the test question information and the answer information.

[0026] In one of the embodiments, the teaching module is further configured to:

[0027] generate a question graph according to the question information;

[0028] The research module is further configured to send the question graph to the virtual research office for the researchers to log in the teaching system and use in the virtual research office for teaching research.

[0029] In one of the embodiments, the teaching module is further configured to:

[0030] determine experiment project information corresponding to the learning scheme;

[0031] determine experiment teaching information corresponding to the experiment project information from the teaching resource information;

[0032] The application aggregation layer further comprises:

[0033] The experiment module is configured to generate an online virtual simulation laboratory according to the experiment project information and the experiment teaching information, so as to enable the learner to perform experiments.

[0034] In a second aspect, the present application further provides a teaching resource processing method applied to the teaching system in the first aspect, and the method comprises:

[0035] collecting activity information of the learner logging in the teaching system to learn, and constructing a user portrait of the learner based on the activity information; determining a learning scheme corresponding to the learner based on the user portrait and the course knowledge graph in the teaching module; the learning scheme comprises each target knowledge point in the course knowledge graph required to be learned by the learner and a learning order between the target knowledge points;

[0036] determining target learning resource information from the teaching resource information according to the learning scheme, so as to enable the learner to learn;

[0037] constructing a virtual teaching and research office, and sending the teaching resource information, the course knowledge graph, the user portrait and the learning scheme to the virtual teaching and research office, so as to enable a teaching and research staff to log in the teaching system and perform teaching and research in the virtual teaching and research office.

[0038] In a third aspect, the present application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method in the second aspect when executing the computer program.

[0039] In a fourth aspect, the present application further provides a computer readable storage medium, which stores a computer program, and the computer program implements the steps of the method in the second aspect when executed by a processor.

[0040] In a fifth aspect, the present application further provides a computer program product comprising a computer program, and the computer program implements the steps of the method in the second aspect when executed by a processor.

[0041] The aforementioned teaching system, methods, computer equipment, computer-readable storage media, and computer program products enable online learning and teaching. Through the learning module, personalized learning plans are determined for each learner. The teaching module accesses the target learning resources corresponding to these plans to facilitate instruction. Through the teaching research module, a virtual teaching research room is constructed, aggregating teaching-related information to support researchers' work. An access layer provides a unified portal for logging into the system, while a backend service layer provides services to the access layer and application aggregation layer, storing data from the application aggregation layer and assigning appropriate system permissions to learners, researchers, and system administrators. This teaching system enables online learning and teaching, and researchers can conduct research through the virtual teaching research room. It provides a unified platform for learning, teaching, research, and management, achieving integration of these activities in a digital environment. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is a diagram illustrating the application environment of a teaching system in one embodiment.

[0044] Figure 2 This is a block diagram of the teaching system in one embodiment;

[0045] Figure 3 This is a flowchart illustrating a teaching resource processing method in one embodiment;

[0046] Figure 4 This is a schematic diagram of the teaching system in one embodiment;

[0047] Figure 5 This is a diagram illustrating the permissions of a teaching system in one embodiment;

[0048] Figure 6 This is a schematic diagram of the teaching system in one embodiment;

[0049] Figure 7 A flowchart illustrating the generation of personalized learning paths in a teaching system according to one embodiment;

[0050] Figure 8 This is a closed-loop diagram of intelligent interactive teaching and feedback in a teaching system of one embodiment;

[0051] Figure 9Figure 1 is a system-level data flow overview diagram of a teaching system in one embodiment;

[0052] Figure 10 Figure 2 is an internal structure diagram of a computer device in one embodiment. DETAILED DESCRIPTION

[0053] In order to make the purposes, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and should not be used to limit the present application.

[0054] It should be noted that the terms "comprising" and "having" and any variations thereof used herein are intended to cover non-exclusive inclusion. The term "multiple" used herein refers to two or more. The term "and / or" used herein refers to one of the options or any combination of multiple options.

[0055] Education digitalization has become a core trend driving global education reform, not only revolutionizing traditional teaching models, but also providing new opportunities and ideas for personalized and lifelong learning. By effectively integrating online and offline resources, education digitalization eliminates the time and space limitations of knowledge dissemination, improving the flexibility and inclusiveness of education. Many online courses built in the past are pure resource directory structure construction, mainly for resource display, and do not have a complete subject knowledge system (considering supplementing relevant patents after novelty search). The pain points of the prior art are summarized as follows: Defects of traditional online education: linear course structure cannot adapt to individual differences, lack of dynamic adjustment ability; Knowledge graph application limitations: existing systems mostly stay in the knowledge visualization stage, without deep integration with teaching interaction; Insufficient interaction mechanism: the existing platform question and answer interaction mode is single, lacking intelligent guidance mechanism; Evaluation system lags behind: learning effect evaluation relies on manual correction, real-time feedback capability is weak; System section design defects: system functions are single, cannot meet the needs of teaching, learning, management, evaluation and research at the same time.

[0056] Based on the above analysis, the present application provides a teaching system, which will be described below by way of embodiments:

[0057] The teaching system provided by the embodiments of the present application can be applied to, for example Figure 1The application environment is shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data required by the server 104 to process. The data storage system can be integrated on the server 104, or placed on the cloud or other network servers. Among them, the terminal 102 can be but not limited to various personal computers, notebook computers, smart phones, tablet computers and the like. The server 104 can be a stand-alone physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0058] In an exemplary embodiment, as shown, a teaching system 200 is provided, which can be applied to the aforementioned server 104, and the teaching system 200 comprises: Figure 2

[0059] The access layer 201 is used to provide a unified portal for learners, teachers and researchers, and system managers to log in to the teaching system;

[0060] The application aggregation layer 202 comprises a learning module 204, a teaching module 205 and a teaching and research module 206; wherein,

[0061] The teaching module 205 is used to obtain teaching resource information, and construct a course knowledge graph based on the teaching resource information;

[0062] The learning module 204 is used to collect activity information of the learners logging in to the teaching system for learning, and construct a user portrait of the learners based on the activity information; based on the user portrait and the course knowledge graph in the teaching module, determine a learning scheme corresponding to the learners; the learning scheme comprises each target knowledge point in the course knowledge graph required by the learners to learn and the learning order between the target knowledge points;

[0063] The teaching module 205 is also used to determine target learning resource information from the teaching resource information according to the learning scheme, and recommend it to the learners;

[0064] The teaching and research module 206 is used to construct a virtual teaching and research room, and display the teaching resource information, the course knowledge graph, the user portrait, the learning scheme, the learning information and the mastery degree information in the virtual teaching and research room for the teachers and researchers to log in to the teaching system and use in the virtual teaching and research room for teaching research;

[0065] The background service layer 203 is used to provide interface services for the access layer, provide graph engine services for the application aggregation layer, store the data corresponding to the application aggregation layer, and allocate corresponding system permissions for the learners, the teachers and researchers, and the system managers.

[0066] ​The learner can refer to an object that uses the teaching system to learn. For example, the learner can include on-campus students, social learners, and visitors.

[0067] The user role permissions in the system mainly include a system administrator, a system operator, a teacher, and a student. The system administrator has a high permission, and supports the system administrator to create a new role permission in the permission management module, and configure the function permission, data viewing permission, and data operation permission of the role. In some embodiments, the system permissions corresponding to different learners can be the same or different.

[0068] The teacher can be a person responsible for teaching research, teaching improvement, course design, and education evaluation. For example, the teacher can include a course research and development team teacher.

[0069] The activity information can refer to information related to the learning activities of the learner in the teaching system. For example, the activity information can include information related to the learning duration of the learner for different courses, the learned subject professional content, the frequency of logging into the teaching system to learn, and the like.

[0070] The user portrait (User Persona or User Profile) refers to a virtualized and tagged description of a user's learning, which is constructed by collecting and analyzing the user's learning behavior data, preferences, and the like. It is an abstraction and summary of the user's learning characteristics. In the embodiments of the present application, the user portrait is used for virtualized and tagged description of the learning account without identifying the corresponding natural person.

[0071] In some embodiments, the learning module 204 can collect activity information of the learner logging into the teaching system to learn, and statistically analyze the activity information, thereby generating a user portrait that is exclusive to the learner.

[0072] The knowledge graph is a model for representing knowledge. It structures entities (Entities) and their relationships (Relationships) in the real world to form a large-scale semantic network. The course knowledge graph can be a knowledge graph corresponding to the course of the teaching resource information.

[0073] In some embodiments, the teaching resource information can include information related to the course syllabus, teaching materials, and teaching resources. The teaching module can extract knowledge points from the teaching resource information to form a knowledge point set, thereby constructing a course knowledge graph. For example, the teaching module can establish an association relationship between knowledge points according to the semantic association and logical relationship between the knowledge points, thereby forming the structure of the knowledge graph.

[0074] The virtual teaching and research office can be a virtual teaching and research office constructed in the teaching system.

[0075] In some embodiments, the virtual teaching and research office can serve the teaching and research work of the teachers and implement the following functions: teaching research: conducting research on course design, teaching resource processing methods, evaluation system, etc., aiming to improve teaching quality; teacher training and development: organizing various forms of teaching seminars, workshops, lectures, etc.; course development and improvement: participating in the design, development and updating of courses to ensure that the course content keeps pace with the times and meets the educational goals and social needs; teaching resource construction: collecting, sorting and developing teaching resources such as textbooks, courseware and case libraries for teachers to use; teaching evaluation and feedback: implementing teaching evaluation mechanisms, collecting feedback from students and peers on the teaching process, analyzing teaching effectiveness and providing suggestions for improvement; academic exchange: promoting academic exchange and cooperation between teachers inside and outside the school, and building a platform for teachers to share teaching experience and research results.

[0076] The graph engine service is a service based on knowledge graph technology, which provides powerful tools and interfaces to create, query, analyze and visualize complex entity relationship networks.

[0077] In some embodiments, the background service layer 203 can provide a graph engine service for the application aggregation layer, thereby serving the construction, query and display of course knowledge graphs.

[0078] The above teaching system determines a personalized learning plan for the learner through the learning module, calls the target learning resource information corresponding to the learning plan through the teaching module, and realizes teaching; through the teaching and research module, a virtual teaching and research office is constructed, and teaching-related information is gathered in the virtual teaching and research office, thereby serving the teaching and research work of the teachers; a unified portal is provided through the access layer to log in to the teaching system, and the background service layer provides services for the access layer and the application aggregation layer, stores the data corresponding to the application aggregation layer, and allocates corresponding system permissions to the learners, teachers and system managers. Through the above teaching system, online learning and teaching can be realized, and at the same time, teachers can perform teaching and research through the virtual teaching and research office. The above teaching system provides a unified learning, teaching, teaching and research and management platform, and realizes the integration of learning, teaching and teaching and research in a digital environment.

[0079] In one embodiment, the teaching module is further configured to: determine learning information of the learner learning the target learning resource information in the teaching system; determine mastery information of the target knowledge point of the learner based on the learning information; and generate learning suggestion information according to the mastery information, to provide learning suggestions for the learner learning the target learning resource information.

[0080] The learning information can be information representing learning of the learner in the teaching system with respect to the target learning resource information. For example, the learning information can include a browsing time, a number of times of checking, a frequency of checking, and the like of the learner in the teaching system with respect to the target learning resource information.

[0081] In some embodiments, the teaching module can determine the mastering degree of the learner with respect to the target knowledge point based on the analysis of the learning information, thereby obtaining the mastering degree information.

[0082] In some embodiments, the learning information can include a browsing time of the learner in the teaching system with respect to the target learning resource information: A, and the teaching module can determine different mastering degree information according to different A. For example, the teaching module can divide the browsing time into 1-3 levels, such as 0-1 hour belongs to level 3, 1-2 hours belongs to level 2, and more than 2 hours belongs to level 1. Different mastering degree information can be determined through different levels.

[0083] In some embodiments, the teaching module can generate personalized learning suggestion information for the learner based on the mastering degree information, thereby better helping the learner to learn the target learning resource information.

[0084] The above technical solution determines the mastering degree of the learner with respect to the target knowledge point based on the learning information of the learner in the teaching system with respect to the target learning resource information, thereby generating personalized learning suggestion information for the learner and helping the learner to learn the target learning resource information.

[0085] In one of the embodiments, the teaching module is further configured to: collect question information raised by the learner with respect to the target knowledge point corresponding to the target learning resource information; determine answer information corresponding to the question information according to the course knowledge graph and the target learning resource information, to answer the questions in the question information; count click and reading information of the learner in the teaching system with respect to the target learning resource information; and determine learning information of the learner with respect to the target learning resource information according to the click and reading information, the question information, and the answer information.

[0086] The question information can be information related to the questions raised by the learner with respect to the target knowledge point corresponding to the target learning resource information. The format of the question information can be at least one of text, picture, voice, and video.

[0087] In some embodiments, the teaching module is provided with a specific question window, through which various question information raised by the learner can be collected. For example, the question window can receive at least one of text, picture, voice, and video uploaded by the learner.

[0088] In some embodiments, the teaching module can feed back the answering information to the learner through the question window.

[0089] The click and reading information can be information representing the click, reading, and other related conditions of the learner with respect to the target learning resource information in the teaching system.

[0090] In some embodiments, the teaching module can comprehensively determine the learning information of the learner with respect to the target learning resource information based on the click and reading information, the question information, and the answering information.

[0091] The above technical solution collects the questions of the learner with respect to the target learning resource information in the teaching system, and determines the corresponding answering information to answer the questions. The learning information of the learner with respect to the target learning resource information is determined based on the click and reading information, the question information, and the answering information, which makes the learning information more comprehensively reflect the real learning situation of the learner in the teaching system, thereby providing a more accurate basis for determining the subsequent steps such as the mastery information.

[0092] In one of the embodiments, the teaching module is further configured to determine the target knowledge points learned by the learner based on the click and reading information, and generate test question information; send the test question information to the learning terminal corresponding to the learner, and receive the answer information fed back by the learning terminal; and determine the learning information of the learner with respect to the target learning resource information based on the click and reading information, the question information, the answering information, the test question information, and the answer information.

[0093] The target knowledge points learned by the learner are tested through the test question information, and the mastery of the target knowledge points learned by the learner is determined based on the answer information. Based on this, the learning information of the learner with respect to the target learning resource information can be more accurately determined based on the click and reading information, the question information, the answering information, the test question information, and the answer information.

[0094] In one of the embodiments, the teaching module is further configured to generate a question graph based on the question information; and the teaching and research module is further configured to send the question graph to the virtual teaching and research room, so that the teaching and research staff can log in to the teaching system and use the question graph for teaching and research in the virtual teaching and research room.

[0095] The question graph is a knowledge graph corresponding to the question information, which can reflect the questions of the learner in the process of learning the target knowledge points.

[0096] The question graph is generated according to the doubt information, and the question graph is sent to a virtual research office, so that a researcher logs in the teaching system and uses the virtual research office for teaching research. This helps the researcher to more quickly and accurately determine the teaching situation of the teaching system for the learner, provides support for the research work in the teaching system, and thus realizes the integration of learning and research.

[0097] In one of the embodiments, the teaching module is further configured to determine experiment item information corresponding to the learning scheme, and determine experiment teaching information corresponding to the experiment item information from the teaching resource information. The aggregation layer further includes an experiment module configured to generate an online virtual simulation laboratory according to the experiment item information and the experiment teaching information, so that the learner performs experiments.

[0098] The experiment item information can be information related to the project with the experiment in the learning scheme.

[0099] The experiment teaching information can be information related to the experiment teaching in the teaching resource information. For example, the experiment teaching information can include experiment description text, experiment demonstration video, etc.

[0100] In some embodiments, the teaching system can be a teaching system of a chemistry discipline. Considering the demand for chemical experiments in the chemistry discipline, the teaching module can determine experiment item information corresponding to the learning scheme, and determine experiment teaching information corresponding to the experiment item information from the teaching resource information.

[0101] In some embodiments, the teaching system can set up an online virtual simulation laboratory to provide experimental services for learners. Specifically, the aggregation layer can include an experiment module, which generates an online virtual simulation laboratory according to the experiment item information and the experiment teaching information, so that the learner performs experiments.

[0102] In some embodiments, the experiment module can load the experiment item information and the experiment teaching information into the online virtual simulation laboratory, analyze the experiment item information and the experiment teaching information to determine specific experiment content, and thus adjust or configure the online virtual simulation laboratory according to the specific experiment content.

[0103] In some embodiments, the experiment module can also collect experiment information of the learner performing experiments in the online virtual simulation laboratory, and send the experiment information to the virtual research office, so that the researcher logs in the teaching system and uses the virtual research office for teaching research. This can provide more abundant and comprehensive information data support for teaching research, and thus helps to realize the integration of learning, teaching and research in a digital environment.

[0104] In this embodiment, the experiment requirements corresponding to the learning scheme, i.e., the experiment item information and the experiment teaching information, are determined through the teaching module; the online virtual simulation laboratory is generated through the experiment module, which enables the teaching system to provide experiment services for learners, thereby better performing digital teaching.

[0105] In one exemplary embodiment, as shown in Figure 3 a teaching resource processing method applied to the aforementioned teaching system is provided, which includes steps S301 to S303:

[0106] Step S301: Collecting activity information of a learner logging into the teaching system for learning, and constructing a user portrait of the learner based on the activity information; determining a learning scheme corresponding to the learner based on the user portrait and a course knowledge graph in the teaching module; the learning scheme includes each target knowledge point in the course knowledge graph required to be learned by the learner and the learning order between the target knowledge points.

[0107] Step S302: Determining target learning resource information from the teaching resource information according to the learning scheme for the learner to learn.

[0108] Step S303: Constructing a virtual teaching and research office, and sending the teaching resource information, the course knowledge graph, the user portrait, the learning scheme, the learning information, and the mastery degree information to the virtual teaching and research office for a teaching researcher logging into the teaching system and using in the virtual teaching and research office for teaching research.

[0109] In some embodiments, for understanding of the teaching resource processing method, reference can be made to the aforementioned description of the teaching system, and repeated parts will not be described herein.

[0110] In one exemplary embodiment, a teaching system is provided, and the corresponding construction logic is as follows: on the basis of existing courses and teaching material construction results, integrating digital teaching resources such as electronic teaching plans, videos, and virtual simulations, forming a shared resource library for training of top-notch innovative talents in a specific discipline, and taking the chemical discipline as an example, through construction of a digital teaching system for core courses of the chemical discipline, a network platform with integrated functions of teaching, research, learning, and management is constructed, on one hand, the construction results of the “101 Plan” (the “101 Plan” refers to a foundation-building project for training of top-notch innovative talents) are gathered, and the application of digital resources in teaching practice is promoted; on the other hand, the resource barriers are broken, and the application scenarios of teachers' teaching and research, teaching, and students' learning based on knowledge graphs and ability graphs are constructed, and the ecological application of teaching resources in education and teaching practice is promoted, thereby promoting the transformation of teaching and research methods, and thus promoting the improvement of teaching quality.

[0111] In some embodiments, the teaching system can publish news, core courses, textbook recommendations, expert reviews, textbook trials, teacher training, classroom improvement, teaching papers, experimental projects, and practice platforms based on the "101 Plan" for Chemistry. News: Mainly used to publish news related to the "101 Plan" for Chemistry, with online viewing and sharing functions. Core Courses: Mainly used to display teaching resources for 12 chemistry-related professional disciplines, and to conduct course teaching activities. For example Figure 4 As shown in FIG. 1, a schematic diagram of a possible teaching system is provided;

[0112] Among them:

[0113] 1. Knowledge graph construction

[0114] Define knowledge representation: Use RDF (Resource Description Framework) triples (Subject-Predicate-Object) to represent knowledge points, where Subject and Object are entities, and Predicate is the relationship between entities.

[0115] Data collection: Collect data in related fields, which can come from databases, web pages, documents, etc.

[0116] Entity recognition: Identify entities and relationships from collected data, which usually involves natural language processing techniques.

[0117] Knowledge fusion: Solve entity disambiguation problems and ensure the consistency of the same entity.

[0118] 2. Knowledge graph storage

[0119] Choose storage method: Knowledge graph can be stored in a table-based database (such as a relational database) or a graph-based database (such as Neo4j, Amazon Neptune, etc.).

[0120] Data modeling: Design data models according to the characteristics of knowledge points, including entity types, attributes, and relationship types.

[0121] 3. Knowledge graph retrieval

[0122] Build index: Build an index on entities and relationships in the knowledge graph to improve retrieval efficiency.

[0123] Query language: Use a query language such as SPARQL to retrieve the knowledge graph, which supports basic CRUD operations and complex graph queries.

[0124] 4. Knowledge graph update and maintenance

[0125] Data Updates: Over time, knowledge graphs need to be updated regularly to reflect the latest state of knowledge.

[0126] Quality control: Ensure the accuracy and consistency of data in the knowledge graph.

[0127] 5. Knowledge Graph Applications

[0128] Visualization: Use tools to display knowledge graphs graphically, helping users to intuitively understand the knowledge structure.

[0129] Intelligent question answering: An automatic question answering system based on knowledge graphs, which answers questions related to knowledge points.

[0130] Recommendation systems: They use entity relationships in knowledge graphs to provide personalized recommendations to users.

[0131] 6. Technology Selection and Tools

[0132] Ontology modeling tools, such as Protégé, are used to build and manage ontology.

[0133] Graph databases, such as Neo4j, are specifically designed for storing and querying graph-structured data.

[0134] Natural language processing tools, such as SpaCy or NLTK, are used for entity recognition and relation extraction.

[0135] Search engines, such as Elasticsearch, are used for full-text search and complex queries.

[0136] 7. Security and Privacy

[0137] Data security: Ensure the secure storage of knowledge graph data and prevent data leakage.

[0138] Privacy protection: Comply with privacy protection regulations during data collection and processing.

[0139] 8. Performance optimization

[0140] Query optimization: Optimize query statements to reduce unnecessary data scanning.

[0141] Hardware resources: Allocate hardware resources reasonably according to the scale of the knowledge graph.

[0142] By following the steps above, an efficient and scalable knowledge graph system can be built for resource retrieval of a specific knowledge point across the entire network.

[0143] Core Textbooks: Textbook Recommendations - primarily used to showcase textbooks created based on the Chemistry "101 Plan"; Expert Review - primarily used to showcase experts who review textbooks published by the Chemistry "101 Plan"; Textbook Trials - primarily used to showcase textbook content and allow for textbook trials and feedback.

[0144] Core Faculty: Faculty Training - primarily used to showcase chemistry-related faculty training activities and allow for participation; Classroom Enhancement - primarily used to showcase chemistry classroom teaching enhancement activities and allow for participation; Teaching Papers - primarily used to showcase new chemistry-related papers and allow for online viewing.

[0145] Core Practice: Experimental Projects - primarily used to showcase chemistry-related online virtual simulation experiments and allow for participation; Practice Platforms - primarily used to showcase chemistry-related online virtual simulation experiment platforms and allow for jumping.

[0146] User Permission System: User roles in the system are primarily divided into system administrators, system operators, teachers, and students, and system administrators can create new role permissions in the permission management module, configure role function permissions, data viewing permissions, and data operation permissions.

[0147] In some embodiments, as shown in Figure 5 , a possible platform permission diagram of the teaching system (platform) is provided; as shown in Figure 6 , a possible structure diagram of the teaching system is provided, which includes an access layer, an application aggregation layer, and a background service layer.

[0148] In some embodiments, the permission allocation of the teaching system can be determined based on the following table:

[0149]

[0150]

[0151]

[0152]

[0153] (B) Core Architecture

[0154] The core architecture of the entire teaching platform is based on a multi-layer modular design, mainly including a data collection layer, a data processing layer, a knowledge graph construction layer, an analysis and prediction layer, and an application layer. Each layer interacts with data through standardized interfaces to ensure efficient operation and scalability of the system.

[0155] Data Acquisition Layer: Responsible for acquiring multimodal interactive data from various data sources (such as online teaching platforms, student terminals, etc.), including text, voice, images, and video.

[0156] Data processing layer: Preprocesses the collected multimodal data, including data cleaning, format conversion, and feature extraction, to ensure data quality and consistency.

[0157] Knowledge Graph Construction Layer: Utilizing natural language processing and machine learning techniques, this layer extracts entities, relationships, and attributes from the processed data to construct a knowledge graph. This layer supports dynamic updates, enabling it to reflect changes in teaching content and student behavior in real time.

[0158] Analysis and Prediction Layer: Through graph neural networks and deep learning algorithms, the data in the knowledge graph is analyzed, processed, deduced, and predicted to generate specific data reflecting students' learning status and effectiveness.

[0159] Application layer: Applying the analysis and prediction results to practical scenarios such as teaching management, personalized learning recommendations, and teaching effectiveness evaluation, providing an intuitive visualization interface and decision support tools.

[0160] (III) Data Processing and Analysis

[0161] The system employs advanced data processing technology, significantly improving data processing efficiency and the accuracy and efficiency of evaluation results.

[0162] Multimodal data fusion: Through multimodal data fusion technology, various data types such as text, voice, image and video are processed in a unified manner to extract rich learning behavior features.

[0163] High-efficiency data processing algorithms: Employing optimized algorithms and data structures, such as graph neural networks and deep learning frameworks, the system significantly improves data processing speed and accuracy. It can process large-scale data in real time, ensuring the timeliness and reliability of analysis results.

[0164] Intelligent Analysis and Prediction: Utilizing machine learning and deep learning algorithms to perform in-depth analysis and prediction of data in knowledge graphs.

[0165] like Figure 7 As shown, a flowchart for generating personalized learning paths in a possible teaching system is presented; Figure 8 As shown, a possible intelligent interactive teaching and feedback closed-loop diagram of a teaching system is presented; such as Figure 9 As shown, a system-level data flow overview diagram of a possible teaching system is presented.

[0166] The above teaching (platform) system has the following technical effects: data processing efficiency is improved: through the optimized data processing process and efficient algorithm, the system can quickly process large-scale multi-modal data, significantly improving the data processing efficiency; the accuracy / efficiency of the evaluation effect is improved: using advanced analysis and prediction algorithms, the system can more accurately evaluate the learning state and effect of students, and provide more accurate personalized learning suggestions; the adaptability of the system is enhanced: the system adopts modular design, supports multiple data sources and application scenarios, and has strong adaptability and scalability. It can be flexibly configured and extended according to different teaching needs.

[0167] At the same time, the above technical scheme realizes the construction of a digital teaching system for core courses of the chemical discipline. The platform has integrated functions of teaching, research, learning and management, breaks through resource barriers, builds teacher teaching and research, teaching and student learning application scenarios based on knowledge graph and ability graph, provides personalized learning paths and content recommendations, meets the learning needs of different students, and improves learning effectiveness; Real-time interaction between teaching content and students enhances learning initiative and participation; using the relevance and semantic information of the knowledge graph, the teaching process is optimized, and the teaching quality and efficiency are improved; through the learning effect evaluation and optimization mechanism, the dynamic adjustment of the teaching process is realized, and the achievement of the teaching goal is ensured; Mounting digital resources is open to teachers and students, thereby promoting the application of teaching resource ecology to education and teaching practice, promoting the transformation of teaching and research methods, and promoting the improvement of teaching quality.

[0168] It should be understood that although each step in the flowchart involved in each embodiment as described above is displayed in sequence according to the direction of the arrow, these steps are not necessarily executed in the order indicated by the arrow. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other orders. Moreover, at least part of the steps in the flowchart involved in each embodiment as described above can include multiple steps or stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least part of other steps or steps or stages in other steps. It can be understood that the steps in different embodiments can be freely combined as needed, and various non-contradictory schemes formed by the combination are within the scope of protection of the present application.

[0169] In some embodiments, each module in the above teaching system can be implemented wholly or partially by software, hardware, and combinations thereof. Each module described above can be embedded in or independent of the processor in the computer device in hardware form, or stored in the memory in the computer device in software form, so as to be called and executed by the processor to perform the operations corresponding to each module.

[0170] In an exemplary embodiment, a computer device, which can be a server, is provided, and an internal structure diagram of the computer device can be as shown in Figure 10 The computer device includes a processor, a memory, an input / output interface (I / O), and a communication interface. The processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for running the operating system and the computer program in the non-volatile storage medium. The database of the computer device is configured to store data such as teaching resource information. The input / output interface of the computer device is configured to exchange information between the processor and external devices. The communication interface of the computer device is configured to communicate with terminals outside through a network connection. The computer program is executed by the processor to implement a teaching resource processing method.

[0171] Those skilled in the art can understand that Figure 10 The structure shown in the above embodiment is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. Specifically, the computer device can include more or fewer components than those shown in the diagram, or combine certain components, or have a different arrangement of components.

[0172] In an embodiment, a computer device is also provided, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0173] In an embodiment, a computer readable storage medium is provided, which stores a computer program. The computer program is executed by a processor to implement the steps in the above method embodiments.

[0174] In an embodiment, a computer program product is provided, which includes a computer program. The computer program is executed by a processor to implement the steps in the above method embodiments.

[0175] It should be noted that the user information (including but not limited to user device information, user personal information, learner activity information, and user portrait, etc.) and data (including but not limited to data for analysis, stored data, and displayed data, etc.) involved in the present application are all information and data authorized by users or authorized by all parties, and the collection, use, and processing of related data need to comply with relevant regulations.

[0176] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when executed, can include the processes of the above-mentioned embodiment methods. Any reference to memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. The non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. The volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration but not limitation, the RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The database involved in the embodiments provided in the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a block chain, etc., without being limited thereto. The processor involved in the embodiments provided in the present application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., without being limited thereto.

[0177] The technical features of the above embodiments can be combined arbitrarily. In order to make the description simple, all possible combinations of the technical features in the above embodiments are not described, however, as long as the combinations of the technical features do not exist contradictory, they should be considered as the scope of the present application.

[0178] The above-described embodiments are merely illustrative of several embodiments of the present application, and the description is relatively specific and detailed, but should not be understood as a limitation on the scope of the patent. It should be noted that for those skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are all within the scope of the present application. Therefore, the scope of protection of the present application should be subject to the appended claims.

Claims

1. A teaching system, characterized in that, The system includes: The access layer provides a unified portal for learners, educators, and system administrators to log in to the teaching system. The application aggregation layer includes teaching modules, learning modules, and teaching research modules; among them, The teaching module is used to acquire teaching resource information and construct a course knowledge graph based on the teaching resource information; The learning module is used to acquire activity information of the learner logging into the teaching system to learn, and to construct a user profile of the learner based on the activity information; based on the user profile and the course knowledge graph in the teaching module, to determine the learning plan corresponding to the learner; the learning plan includes each target knowledge point in the course knowledge graph that the learner needs to learn and the learning order between each target knowledge point; The teaching module is also used to determine target learning resource information from the teaching resource information according to the learning plan, and recommend it to the learner for learning; The teaching and research module is used to construct a virtual teaching and research room, and to display the teaching resource information, the course knowledge graph, the user profile and the learning plan in the virtual teaching and research room, so that teaching and research personnel can log in to the teaching system and conduct teaching research in the virtual teaching and research room; The backend service layer is used to provide interface services for the access layer, provide graph engine services for the application aggregation layer, store the data corresponding to the application aggregation layer, and assign corresponding system permissions to the learners, the educators and researchers and the system administrators.

2. The system according to claim 1, characterized in that, The teaching module is also used for: The learning information obtained by the learner in the teaching system in response to the target learning resource information; Based on the learning information, determine the learner's mastery of the target knowledge point; Based on the mastery information, learning suggestions are generated and recommended to the learner.

3. The system according to claim 2, characterized in that, The teaching module is also used for: Obtain the questions raised by the learner regarding the target knowledge points corresponding to the target learning resource information; Based on the course knowledge graph and the target learning resource information, determine the answer information corresponding to the question information; The system collects click and view information of the target learning resources by the learners in the teaching system. Based on the click-through information, the question information, and the answer information, the learner's learning information regarding the target learning resource information is determined.

4. The system according to claim 3, characterized in that, The teaching module is also used for: Based on the click-through information, the target knowledge points that the learner has already learned are determined, and test question information is generated; The test question information is sent to the learning terminal corresponding to the learner, and the answer information fed back by the learning terminal is received; Based on the click-through information, the question information, the answer information, the test question information, and the answer information, the learner's learning information for the target learning resource information is determined.

5. The system according to claim 3, characterized in that, The teaching module is also used for: Based on the question information, a question map is generated; The teaching and research module is also used to send the problem map to the virtual teaching and research room, so that teachers and researchers can log in to the teaching system and conduct teaching research in the virtual teaching and research room.

6. The system according to any one of claims 1 to 5, characterized in that, The teaching module is also used for: Determine the experimental project information corresponding to the learning scheme; Determine the experimental teaching information corresponding to the experimental project information from the teaching resource information; The application aggregation layer also includes: The experiment module is used to generate an online virtual simulation laboratory based on the experiment project information and the experiment teaching information, so that the learners can conduct experiments.

7. A method for processing teaching resources, characterized in that, Applied to the teaching system as described in any one of claims 1 to 6, the method comprises: The system obtains activity information of learners logging into the teaching system and constructs a user profile of the learners based on the activity information; based on the user profile and the course knowledge graph in the teaching module, it determines the learning plan corresponding to the learners; the learning plan includes each target knowledge point in the course knowledge graph that the learners need to learn and the learning order between each target knowledge point. According to the learning plan, target learning resource information is determined from the teaching resource information for the learner to study; The teaching resource information, the course knowledge graph, the user profile, and the learning plan are sent to the virtual teaching and research room so that teachers and researchers can log in to the teaching system and conduct teaching research in the virtual teaching and research room.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method of claim 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method of claim 7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method of claim 7.

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