Knowledge graph course teaching method and system

Abstract

The invention discloses a knowledge graph course teaching method and system, and the method comprises the steps: obtaining a query condition of a user side, constructing a knowledge graph based on the query condition, and uploading a teaching resource file through a teacher side based on the knowledge graph; constructing a course outline according to the teaching resource file and the knowledge graph, and arranging a teaching plan according to the course outline; generating an exclusive personalized learning path of each student by combining the learning basic information and the learning target information of the students through the teaching plan; and performing course teaching, intelligent question answering and score testing on each student according to the exclusive personalized learning path, and generating a comprehensive learning report of each student. By generating the exclusive personalized learning path of each student, the learning plan and the learning rhythm meeting the learning requirements of different students can be generated based on different learning levels of the different students, so that the learning efficiency of each student is ensured, and the practicability and the experience feeling of the students are improved.

Description

Technical Field

[0001] The present invention relates to the field of course teaching technology, and in particular to a knowledge graph course teaching method and system. Background Art

[0002] At present, with the rapid development of artificial intelligence technology, especially the emergence of large language models, new opportunities have been brought to the field of education. Traditional teaching models are often difficult to meet the needs of personalized learning, while knowledge graph technology can improve teaching efficiency and learning effects through automation and intelligence. Most existing knowledge graph teaching systems are based on preset learning plans and fixed teaching models or rely on linear outlines or fixed knowledge structures. This model has the following problems: (1) Static knowledge system: Traditional teaching outlines are updated slowly and are difficult to adapt to the rapid development of disciplines, such as the emergence of new technologies and new theories. (2) Lack of personalized adaptation: A unified teaching schedule is difficult to meet the learning needs of different students, resulting in some students falling behind due to weak foundations or differences in learning pace, reducing teaching efficiency and student experience. Summary of the Invention

[0003] In response to the problems shown above, the present invention provides a knowledge graph course teaching method and system to solve the problems mentioned in the background technology, such as the slow update of traditional teaching syllabus and the difficulty of unified teaching progress in meeting the learning needs of different students, which causes some students to fall behind due to weak foundation or different learning pace, reducing teaching efficiency and students' experience.

[0004] A knowledge graph course teaching method includes the following steps:

[0005] Obtain the query conditions from the user side and build a knowledge graph based on the query conditions. Upload teaching resource files through the teacher side based on the knowledge graph.

[0006] Build a course outline based on teaching resource files and knowledge graphs, and arrange teaching plans based on the course outline;

[0007] Generate a personalized learning path for each student by combining the student's basic learning information and learning goal information through the teaching plan;

[0008] Each student is provided with course instruction, intelligent Q&A, and performance testing based on their exclusive personalized learning path, and a comprehensive learning report is generated for each student.

[0009] Preferably, before obtaining the query conditions of the user end and constructing a knowledge graph based on the query conditions, and before uploading the teaching resource file through the teacher end based on the knowledge graph, the method further includes:

[0010] Detect the login status of the user and teacher terminals on the knowledge graph teaching platform, and determine whether the login status is logged in. If not, activate the login pop-up interface;

[0011] Obtain the login account, login password and login verification code entered by the user and teacher in the login pop-up window;

[0012] Proofread the login account, login password and login verification code, determine the account validity based on the proofreading results, and authorize the user and teacher terminals based on the account validity;

[0013] Obtain the preset account attributes of the user and teacher's respective login accounts, determine the identity tags of the user and teacher based on the preset account attributes, and perform deep operation permission binding based on the identity tags.

[0014] Preferably, the obtaining of query conditions from the user side and constructing a knowledge graph based on the query conditions, and uploading teaching resource files through the teacher side based on the knowledge graph, include:

[0015] Detect the user's knowledge graph construction requirements and obtain the user's query conditions based on the knowledge graph construction requirements;

[0016] Set the knowledge graph number and status according to the query conditions and obtain the number of knowledge points, the number of graph association types, the graph update frequency, the knowledge graph visualization method, and the information richness of the graph nodes;

[0017] Construct a knowledge graph based on the knowledge graph number and status, the number of knowledge points, the number of graph association types, the frequency of graph updates, the knowledge graph visualization method, and the information richness of graph nodes;

[0018] Determine the teaching resource requirements based on the knowledge graph, and obtain the teaching resource files uploaded from the teacher side based on the teaching resource requirements.

[0019] Preferably, determining the teaching resource requirements according to the knowledge graph and obtaining the teaching resource files uploaded from the teacher's end based on the teaching resource requirements include:

[0020] Determine the teaching resource adaptation requirements based on the knowledge graph, and based on the teaching resource adaptation requirements, determine the supported teaching resource types, resource upload size limits, resource review methods, the accuracy of resource and knowledge point association, and resource storage capacity;

[0021] Determine the resource formats of each type of supported teaching resources, and generate teaching resource review conditions based on resource formats and resource upload size limits, resource review methods, accuracy of resource-knowledge point associations, and resource storage capacity;

[0022] Determine teaching resource requirements based on teaching resource review conditions, and review and screen teaching resource files uploaded by teachers according to teaching resource requirements;

[0023] Determine the adapted teaching resource files based on the screening results and integrate the adapted teaching resource files.

[0024] Preferably, the process of constructing a course outline based on the teaching resource files and the knowledge graph, and arranging a teaching plan based on the course outline, includes:

[0025] Determine multiple teaching objectives and the teaching content corresponding to each teaching objective based on teaching resource files and knowledge graphs;

[0026] Construct a course outline based on multiple teaching objectives and the teaching content corresponding to each teaching objective, and determine multiple course projects based on the course outline;

[0027] Obtain the course volume of each course project, and set the total course credits, total course hours, and course stage hours for each course project based on the course volume;

[0028] Arrange the teaching plan for each course project based on the total course credits, total course hours and course phase hours.

[0029] Preferably, after arranging the teaching plan for each course project based on the total course credits, total course hours, and course phase hours, it also includes:

[0030] Determine the teaching methods and mastery objectives for each course item based on the teaching plan, and determine the standard learning parameters for each course item based on the teaching methods and mastery objectives;

[0031] Determine the qualified assessment indicators for each course project based on the standard learning parameters, and set the teaching method arrangement parameters for each course project based on the qualified assessment indicators;

[0032] Arrange parameters according to the teaching form to arrange the teaching progress statistics status information of each teaching project.

[0033] Preferably, the method of generating a unique personalized learning path for each student by combining the student's basic learning information and learning goal information through the teaching plan includes:

[0034] Obtaining each student's entrance test score information, and determining each student's multidimensional learning ability assessment parameters based on the entrance test score information;

[0035] Determine each student's basic learning information based on multi-dimensional learning ability assessment parameters, and determine the teaching resource allocation parameters for each student based on each student's basic information and learning goal information;

[0036] Generate each student's initial learning path through a personalized path generation algorithm based on the teaching resource allocation parameters for each student;

[0037] Obtain each student's teaching plan information, and adjust the initial learning path based on the teaching plan information through the learning path dynamic adjustment mechanism to generate each student's exclusive personalized learning path.

[0038] Preferably, the process of providing course teaching, intelligent question answering, and performance testing to each student based on the exclusive personalized learning path and generating a comprehensive learning report for each student includes:

[0039] Determine the teaching focus for each student based on their exclusive personalized learning path, and adjust the teaching content weight for each student based on the teaching focus;

[0040] Provide course instruction to each student based on the adjusted teaching content, detect student questions during the learning process, and provide intelligent answers using AI models;

[0041] Generate periodic test questions based on each student's teaching progress to test each student's periodic learning outcomes and obtain test scores;

[0042] Determine each student's knowledge mastery based on test scores, analyze each student's learning behavior, and generate personalized follow-up teaching suggestions and comprehensive learning reports for each student based on the analysis results and knowledge mastery.

[0043] Preferably, the method further comprises:

[0044] Collect the teaching feedback of each student and determine the teaching evaluation vector and vector value based on the teaching feedback;

[0045] Determine the teaching optimization direction based on the teaching evaluation vector and its value, and determine the specific optimization indicators based on the teaching optimization direction;

[0046] Deeply optimize specific optimization indicators to meet the subsequent teaching needs of students.

[0047] A knowledge graph course teaching system, the system comprising:

[0048] The acquisition module is used to obtain the query conditions of the user side and build a knowledge graph based on the query conditions, and upload teaching resource files through the teacher side based on the knowledge graph;

[0049] The arrangement module is used to build a course outline based on teaching resource files and knowledge graphs, and arrange teaching plans based on the course outline;

[0050] The first generation module is used to generate a unique personalized learning path for each student by combining the student's basic learning information and learning goal information through the teaching plan;

[0051] The second generation module is used to provide course teaching, intelligent question answering, and performance testing for each student based on an exclusive personalized learning path and generate a comprehensive learning report for each student.

[0052] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0053] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0055] Figure 1 A workflow diagram of the knowledge graph course teaching method provided by the present invention;

[0056] Figure 2 Another workflow diagram of the knowledge graph course teaching method provided by the present invention;

[0057] Figure 3 Another workflow diagram of the knowledge graph course teaching method provided by the present invention;

[0058] Figure 4 This is a structural diagram of a knowledge graph course teaching system provided by the present invention. DETAILED DESCRIPTION

[0059] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible embodiments consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.

[0060] At present, with the rapid development of artificial intelligence technology, especially the emergence of large language models, new opportunities have been brought to the field of education. Traditional teaching models are often difficult to meet the needs of personalized learning, while knowledge graph technology can improve teaching efficiency and learning effects through automation and intelligence. Most existing knowledge graph teaching systems are based on preset learning plans and fixed teaching models or rely on linear outlines or fixed knowledge structures. This model has the following problems: (1) Static knowledge system: Traditional teaching outlines are updated slowly and are difficult to adapt to the rapid development of disciplines, such as the emergence of new technologies and new theories. (2) Lack of personalized adaptation: A unified teaching schedule is difficult to meet the learning needs of different students, resulting in some students falling behind due to weak foundations or differences in learning rhythms, reducing teaching efficiency and student experience. In order to solve the above problems, this embodiment discloses a knowledge graph course teaching method.

[0061] A knowledge graph course teaching method, such as Figure 1 As shown, the following steps are included:

[0062] Step S101: Obtain the query conditions of the user end and build a knowledge graph based on the query conditions, and upload teaching resource files through the teacher end based on the knowledge graph;

[0063] Step S102: construct a course outline based on the teaching resource file and the knowledge graph, and arrange a teaching plan based on the course outline;

[0064] Step S103: Generate a unique personalized learning path for each student by combining the student's basic learning information and learning goal information through the teaching plan;

[0065] Step S104: Provide course instruction, intelligent question answering, and performance testing for each student based on the exclusive personalized learning path, and generate a comprehensive learning report for each student.

[0066] The working principle of the above technical solution is: obtain the query conditions of the user side and build a knowledge graph based on the query conditions, upload the teaching resource files through the teacher side based on the knowledge graph; build a course outline according to the teaching resource files and the knowledge graph, and arrange the teaching plan according to the course outline; generate a unique personalized learning path for each student through the teaching plan combined with the student's basic learning information and learning goal information; conduct course teaching, intelligent question answering, and performance testing for each student based on the unique personalized learning path and generate a comprehensive learning report for each student.

[0067] The beneficial effects of the above technical solution are: by uploading the corresponding teaching resource files through the teacher side according to the teaching resource condition requirements input by the student user side to generate a dynamic teaching syllabus, the real-time variability of the teaching syllabus can be guaranteed to adapt to teaching needs, thereby improving adaptability. Furthermore, by generating an exclusive personalized learning path for each student, a learning plan and learning rhythm that meets their learning needs can be generated based on the different learning levels of different students, thereby ensuring the learning efficiency of each student, improving practicality and student experience, and solving the problems mentioned in the prior art that the traditional teaching syllabus is slow to update and the unified teaching progress is difficult to meet the learning needs of different students, resulting in some students falling behind due to weak foundation or differences in learning rhythm, reducing teaching efficiency and student experience.

[0068] In this embodiment, after arranging the teaching plan according to the course syllabus, the following steps are also included:

[0069] Determine multiple learning indicators and statistical parameters of each learning indicator according to the teaching plan, and determine the knowledge statistical elements of each learning indicator according to the statistical parameters of each learning indicator;

[0070] Determine a historical learning state parameter of the knowledge statistical element of each learning indicator, and determine a learning emotion corresponding to the knowledge statistical element of each learning indicator based on the historical learning state parameter;

[0071] Determine the interactive emotion characteristics of each learning indicator according to the learning emotion, and determine the learning frequency for each learning indicator based on the interactive emotion characteristics;

[0072] Generate a learning unit sequence for each learning indicator based on the learning frequency, and generate a learning task for each learning indicator based on the learning unit sequence;

[0073] Conduct data analysis on the learning tasks of each learning indicator, and determine the student's recitation operation data weight and exercise operation data weight for each learning indicator based on the analysis results;

[0074] According to the weight of recitation operation data and exercise operation data, the error feedback of students' mastery degree of each learning indicator is determined through the recursive hierarchical analysis model;

[0075] Determine an operation adjustment parameter for each learning indicator based on the grasping degree error feedback, and determine an adjustment ratio between the recitation operation data and the exercise operation data of each learning indicator based on the operation adjustment parameter;

[0076] Adaptively adjust the semantic understanding feature vector and exercise vector of each learning indicator according to the adjustment ratio;

[0077] A knowledge-exam correlation feature vector is constructed for each learning indicator according to the adjustment result, and the teaching plan is optimized according to the knowledge-exam correlation feature vector to obtain an optimized teaching plan.

[0078] The beneficial effect of the above technical solution is: by evaluating and adjusting the knowledge recitation and exercise weights of each learning indicator in the teaching plan, the teaching plan can be adjusted based on the learning attributes of each learning indicator, that is, the knowledge point recitation points or exercise priority, thereby ensuring students' learning efficiency and reliability for each learning indicator and improving practicality.

[0079] In one embodiment, before obtaining the query conditions of the user terminal and constructing a knowledge graph based on the query conditions, and uploading the teaching resource file through the teacher terminal based on the knowledge graph, the method further includes:

[0080] Detect the login status of the user and teacher terminals on the knowledge graph teaching platform, and determine whether the login status is logged in. If not, activate the login pop-up interface;

[0081] Obtain the login account, login password and login verification code entered by the user and teacher in the login pop-up window;

[0082] Proofread the login account, login password and login verification code, determine the account validity based on the proofreading results, and authorize the user and teacher terminals based on the account validity;

[0083] Obtain the preset account attributes of the user and teacher's respective login accounts, determine the identity tags of the user and teacher based on the preset account attributes, and perform deep operation permission binding based on the identity tags.

[0084] The beneficial effects of the above technical solution are: by authenticating the accounts of students and teachers, the stability of platform use and the integrity of identity authentication can be guaranteed, thereby providing better teaching services and further improving practicality. Furthermore, by determining the account attributes to bind deep operation permissions, different platform operation permissions can be configured for different identities based on different identities, thereby further optimizing the richness of teaching.

[0085] In one embodiment, Figure 2 As shown, the method of obtaining the query conditions of the user end and constructing a knowledge graph based on the query conditions, and uploading the teaching resource file through the teacher end based on the knowledge graph includes:

[0086] Step S201: Detect the knowledge graph construction requirements of the user terminal, and obtain the query conditions of the user terminal based on the knowledge graph construction requirements;

[0087] Step S202: Set the knowledge graph number and status according to the query conditions and obtain the number of knowledge points, the number of graph association types, the graph update frequency, the knowledge graph visualization method, and the richness of graph node information;

[0088] Step S203: construct a knowledge graph based on the knowledge graph number and status, the number of knowledge points, the number of graph association types, the graph update frequency, the knowledge graph visualization method, and the information richness of the graph nodes;

[0089] Step S204: Determine the teaching resource requirements according to the knowledge graph, and obtain the teaching resource files uploaded from the teacher side based on the teaching resource requirements.

[0090] The beneficial effect of the above technical solution is: by obtaining knowledge point parameters and various required parameters of the knowledge graph from the student user end, it can not only ensure the richness of the constructed knowledge graph but also ensure its adaptability to user needs, thereby meeting the learning needs of student users and improving practicality.

[0091] In one embodiment, determining the teaching resource requirements according to the knowledge graph and obtaining the teaching resource files uploaded from the teacher's end based on the teaching resource requirements include:

[0092] Determine the teaching resource adaptation requirements based on the knowledge graph, and based on the teaching resource adaptation requirements, determine the supported teaching resource types, resource upload size limits, resource review methods, the accuracy of resource and knowledge point association, and resource storage capacity;

[0093] Determine the resource formats of each type of supported teaching resources, and generate teaching resource review conditions based on resource formats and resource upload size limits, resource review methods, accuracy of resource-knowledge point associations, and resource storage capacity;

[0094] Determine teaching resource requirements based on teaching resource review conditions, and review and screen teaching resource files uploaded by teachers according to teaching resource requirements;

[0095] Determine the adapted teaching resource files based on the screening results and integrate the adapted teaching resource files.

[0096] The beneficial effects of the above technical solution are: by determining the teaching resource requirements and then reviewing and screening the teaching resource files uploaded by the teacher, it is possible to ensure the high quality of the teaching resource files while also ensuring the adaptability of the teaching resource files to the students' learning needs, thereby improving teaching efficiency while achieving targeted and in-depth teaching, and further improving practicality.

[0097] In one embodiment, Figure 3 As shown, the course outline is constructed based on the teaching resource file and the knowledge graph, and the teaching plan is arranged according to the course outline, including:

[0098] Step S301: Determine multiple teaching objectives and the teaching content corresponding to each teaching objective based on the teaching resource file and the knowledge graph;

[0099] Step S302: constructing a course outline based on multiple teaching objectives and the teaching content corresponding to each teaching objective, and determining multiple course items according to the course outline;

[0100] Step S303: Obtain the course volume of each course project, and set the total course credits, total course hours, and course stage hours of each course project according to the course volume;

[0101] Step S304: Arrange a teaching plan for each course project based on the total course credits, total course hours, and course phase hours.

[0102] The beneficial effects of the above technical solution are: by determining multiple course projects based on the dynamic course outline and then arranging the learning plan according to the stage hours and credits set according to the course volume, an objective and reasonable teaching plan can be intelligently generated based on the teaching difficulty and teaching content throughput capacity of each course project, thereby ensuring the adaptability of teaching to students and further improving practicality.

[0103] In one embodiment, after arranging the teaching plan for each course project based on the total course credits, total course hours, and course phase hours, the following is further included:

[0104] Determine the teaching methods and mastery objectives for each course item based on the teaching plan, and determine the standard learning parameters for each course item based on the teaching methods and mastery objectives;

[0105] Determine the qualified assessment indicators for each course project based on the standard learning parameters, and set the teaching method arrangement parameters for each course project based on the qualified assessment indicators;

[0106] Arrange parameters according to the teaching form to arrange the teaching progress statistics status information of each teaching project.

[0107] The beneficial effects of the above technical solution are: by determining the standard learning parameters, the standardization and consistency of the teaching process can be ensured, and human experience bias can be reduced. Furthermore, by setting the teaching method arrangement parameters of each course project according to the qualified assessment indicators, the teaching method can be automatically optimized, the knowledge absorption rate can be improved, and the test content can be ensured to match the current teaching stage, avoiding "out-of-scope" or "delayed" assessments.

[0108] In one embodiment, the generation of a unique personalized learning path for each student by combining the student's basic learning information and learning goal information with the teaching plan includes:

[0109] Obtaining each student's entrance test score information, and determining each student's multidimensional learning ability assessment parameters based on the entrance test score information;

[0110] Determine each student's basic learning information based on multi-dimensional learning ability assessment parameters, and determine the teaching resource allocation parameters for each student based on each student's basic information and learning goal information;

[0111] Generate each student's initial learning path through a personalized path generation algorithm based on the teaching resource allocation parameters for each student;

[0112] Obtain each student's teaching plan information, and adjust the initial learning path based on the teaching plan information through the learning path dynamic adjustment mechanism to generate each student's exclusive personalized learning path.

[0113] The beneficial effects of the above technical solution are: by determining the learning ability of each student and then determining the teaching resource allocation parameters for each student, dynamic teaching resource allocation can be carried out by building a comprehensive student portrait, avoiding "one-size-fits-all" teaching and improving practicality. Furthermore, by intelligently adjusting the learning path of each student, the most suitable learning path that meets their learning needs can be formulated based on the teaching planning goals of each student, thereby improving learning efficiency and students' experience.

[0114] In one embodiment, the process of providing course instruction, intelligent question answering, and performance testing for each student based on a dedicated personalized learning path and generating a comprehensive learning report for each student includes:

[0115] Determine the teaching focus for each student based on their exclusive personalized learning path, and adjust the teaching content weight for each student based on the teaching focus;

[0116] Provide course instruction to each student based on the adjusted teaching content, detect student questions during the learning process, and provide intelligent answers using AI models;

[0117] Generate periodic test questions based on each student's teaching progress to test each student's periodic learning outcomes and obtain test scores;

[0118] Determine each student's knowledge mastery based on test scores, analyze each student's learning behavior, and generate personalized follow-up teaching suggestions and comprehensive learning reports for each student based on the analysis results and knowledge mastery.

[0119] The beneficial effects of the above technical solution are: by determining the teaching focus for each student to adjust the teaching content weight, the content attributes of the teaching can be intelligently adjusted based on the actual mastery goals of each student to achieve precise matching teaching, further improving the practicality and student experience. Furthermore, by conducting periodic performance tests, the students' periodic learning outcomes can be evaluated to achieve a complete teaching effect evaluation, thereby improving the objectivity and reliability of the evaluation.

[0120] In one embodiment, the method further comprises:

[0121] Collect the teaching feedback of each student and determine the teaching evaluation vector and vector value based on the teaching feedback;

[0122] Determine the teaching optimization direction based on the teaching evaluation vector and its value, and determine the specific optimization indicators based on the teaching optimization direction;

[0123] Deeply optimize specific optimization indicators to meet the subsequent teaching needs of students.

[0124] The beneficial effects of the above technical solution are: by optimizing teaching according to teaching feedback, it is possible to maximize the satisfaction of students' learning needs at all levels, thereby achieving high-quality teaching, and further improving practicality and students' learning efficiency.

[0125] In one embodiment, this embodiment also discloses a knowledge graph course teaching system, such as Figure 4 As shown, the system includes:

[0126] Acquisition module 401, used to obtain the query conditions of the user end and build a knowledge graph based on the query conditions, and upload teaching resource files through the teacher end based on the knowledge graph;

[0127] Arrangement module 402, used to construct a course outline based on the teaching resource files and the knowledge graph, and arrange the teaching plan according to the course outline;

[0128] The first generation module 403 is used to generate a unique personalized learning path for each student by combining the student's basic learning information and learning goal information with the teaching plan;

[0129] The second generating module 404 is used to provide course teaching, intelligent question answering, and performance testing for each student according to the exclusive personalized learning path and generate a comprehensive learning report for each student.

[0130] The working principle and beneficial effects of the above technical solution have been explained in the method embodiment and will not be repeated here.

[0131] Those skilled in the art should understand that the first and second in the present invention simply refer to different application stages.

[0132] Other embodiments of the present disclosure will readily occur to those skilled in the art after considering the specification and practicing the disclosure herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow from the general principles of the present disclosure and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the present disclosure being indicated by the following claims.

[0133] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes can be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A knowledge graph course teaching method, characterized by: The following steps are involved: Obtain the query conditions from the user side and build a knowledge graph based on the query conditions. Upload teaching resource files through the teacher side based on the knowledge graph. Build a course outline based on teaching resource files and knowledge graphs, and arrange teaching plans based on the course outline; Generate a personalized learning path for each student by combining the student's basic learning information and learning goal information through the teaching plan; Each student is provided with course instruction, intelligent Q&A, and performance testing based on their exclusive personalized learning path, and a comprehensive learning report is generated for each student.

2. The knowledge graph course teaching method according to claim 1 is characterized in that: Before obtaining the query conditions of the user end and constructing a knowledge graph based on the query conditions, and uploading the teaching resource file through the teacher end based on the knowledge graph, the method further includes: Detect the login status of the user and teacher terminals on the knowledge graph teaching platform, and determine whether the login status is logged in. If not, activate the login pop-up interface; Obtain the login account, login password and login verification code entered by the user and teacher in the login pop-up window; Proofread the login account, login password and login verification code, determine the account validity based on the proofreading results, and authorize the user and teacher terminals based on the account validity; Obtain the preset account attributes of the user and teacher's respective login accounts, determine the identity tags of the user and teacher based on the preset account attributes, and perform deep operation permission binding based on the identity tags.

3. The knowledge graph course teaching method according to claim 1 is characterized in that: The method of obtaining query conditions on the user side and constructing a knowledge graph based on the query conditions, and uploading teaching resource files through the teacher side based on the knowledge graph, includes: Detect the user's knowledge graph construction requirements and obtain the user's query conditions based on the knowledge graph construction requirements; Set the knowledge graph number and status according to the query conditions and obtain the number of knowledge points, the number of graph association types, the graph update frequency, the knowledge graph visualization method, and the information richness of the graph nodes; Construct a knowledge graph based on the knowledge graph number and status, the number of knowledge points, the number of graph association types, the frequency of graph updates, the knowledge graph visualization method, and the information richness of graph nodes; Determine the teaching resource requirements based on the knowledge graph, and obtain the teaching resource files uploaded from the teacher side based on the teaching resource requirements.

4. The knowledge graph course teaching method according to claim 3 is characterized in that: Determining teaching resource requirements based on the knowledge graph and obtaining teaching resource files uploaded from the teacher's end based on the teaching resource requirements includes: Determine the teaching resource adaptation requirements based on the knowledge graph, and based on the teaching resource adaptation requirements, determine the supported teaching resource types, resource upload size limits, resource review methods, the accuracy of resource and knowledge point association, and resource storage capacity; Determine the resource formats of each type of supported teaching resources, and generate teaching resource review conditions based on resource formats and resource upload size limits, resource review methods, accuracy of resource-knowledge point associations, and resource storage capacity; Determine teaching resource requirements based on teaching resource review conditions, and review and screen teaching resource files uploaded by teachers according to teaching resource requirements; Determine the adapted teaching resource files based on the screening results and integrate the adapted teaching resource files.

5. The knowledge graph course teaching method according to claim 1 is characterized in that: The course outline is constructed based on the teaching resource files and the knowledge graph, and the teaching plan is arranged based on the course outline, including: Determine multiple teaching objectives and the teaching content corresponding to each teaching objective based on teaching resource files and knowledge graphs; Construct a course outline based on multiple teaching objectives and the teaching content corresponding to each teaching objective, and determine multiple course projects based on the course outline; Obtain the course volume of each course project, and set the total course credits, total course hours, and course stage hours for each course project based on the course volume; Arrange the teaching plan for each course project based on the total course credits, total course hours and course phase hours.

6. The knowledge graph course teaching method according to claim 5 is characterized in that: After arranging the teaching plan for each course project based on the total course credits, total course hours, and course phase hours, it also includes: Determine the teaching methods and mastery objectives for each course item based on the teaching plan, and determine the standard learning parameters for each course item based on the teaching methods and mastery objectives; Determine the qualified assessment indicators for each course project based on the standard learning parameters, and set the teaching method arrangement parameters for each course project based on the qualified assessment indicators; Arrange parameters according to the teaching form to arrange the teaching progress statistics status information of each teaching project.

7. The knowledge graph course teaching method according to claim 1 is characterized in that: The teaching plan combines the student's basic learning information and learning goal information to generate a unique personalized learning path for each student, including: Obtaining each student's entrance test score information, and determining each student's multidimensional learning ability assessment parameters based on the entrance test score information; Determine each student's basic learning information based on multi-dimensional learning ability assessment parameters, and determine the teaching resource allocation parameters for each student based on each student's basic information and learning goal information; Generate each student's initial learning path through a personalized path generation algorithm based on the teaching resource allocation parameters for each student; Obtain each student's teaching plan information, and adjust the initial learning path based on the teaching plan information through the learning path dynamic adjustment mechanism to generate each student's exclusive personalized learning path.

8. The knowledge graph course teaching method according to claim 1, characterized in that: The system provides each student with course instruction, intelligent question answering, and performance testing based on their own personalized learning path, and generates a comprehensive learning report for each student, including: Determine the teaching focus for each student based on their exclusive personalized learning path, and adjust the teaching content weight for each student based on the teaching focus; Provide course instruction to each student based on the adjusted teaching content, detect student questions during the learning process, and provide intelligent answers using AI models; Generate periodic test questions based on each student's teaching progress to test each student's periodic learning outcomes and obtain test scores; Determine each student's knowledge mastery based on test scores, analyze each student's learning behavior, and generate personalized follow-up teaching suggestions and comprehensive learning reports for each student based on the analysis results and knowledge mastery.

9. The knowledge graph course teaching method according to claim 1, characterized in that: The method further comprises: Collect the teaching feedback of each student and determine the teaching evaluation vector and vector value based on the teaching feedback; Determine the teaching optimization direction based on the teaching evaluation vector and its value, and determine the specific optimization indicators based on the teaching optimization direction; Deeply optimize specific optimization indicators to meet the subsequent teaching needs of students.

10. A knowledge graph course teaching system, characterized by: The system includes: The acquisition module is used to obtain the query conditions of the user side and build a knowledge graph based on the query conditions, and upload teaching resource files through the teacher side based on the knowledge graph; The arrangement module is used to build a course outline based on teaching resource files and knowledge graphs, and arrange teaching plans based on the course outline; The first generation module is used to generate a unique personalized learning path for each student by combining the student's basic learning information and learning goal information through the teaching plan; The second generation module is used to provide course teaching, intelligent question answering, and performance testing for each student based on an exclusive personalized learning path and generate a comprehensive learning report for each student.

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