Course construction system and method based on knowledge graph

Abstract

The invention relates to the technical field of teaching systems, in particular to a course construction system and method based on a knowledge graph, and the system comprises a user information management module, a course knowledge graph construction module and a course recommendation module, and also comprises a multi-source data collection module, a learning data analysis module and a student portrait establishment module. The multi-source data acquisition module is connected with the user information management module, the learning data analysis module is connected with the multi-source data acquisition module, the student portrait establishment module is connected with the learning data analysis module and the user information management module, and the course knowledge graph construction module is connected with the course recommendation module. The course recommendation module is connected with the learning data analysis module and is connected with the user information management module, learning information of students can be monitored and evaluated by comprehensively collecting and analyzing learning data of the students, and then the learning quality of the corresponding students is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of teaching systems, and in particular to a course construction system and method based on knowledge graphs. Background Art

[0002] A knowledge graph is usually a large, semi-structured, subject-oriented, multimodal knowledge base that contains various entities, relationships, attributes and other information. This information is processed and reasoned through a series of algorithms and models, so that computers can automatically acquire, reason and generate new knowledge from it.

[0003] With the rapid development of artificial intelligence technology, knowledge graphs, as an important technical tool, have been widely used in many fields. In the field of education, knowledge graphs can realize the organization, management and reasoning of knowledge, so that the course content forms an interconnected and logically clear knowledge system. The traditional education model often adopts a "one-size-fits-all" teaching method, which is difficult to meet the diverse learning needs of students. The course construction system based on knowledge graphs can intelligently recommend personalized learning paths and course content according to students' interests, abilities and learning progress, thereby improving learning efficiency and stimulating students' interest and initiative in learning.

[0004] The course construction system mainly makes judgments based on the collected student information, and then evaluates the student's learning progress and quality of the corresponding subjects and content. However, since some students have relatively weak self-control during the learning process, and the existing course construction system is unable to judge the authenticity of the information when collecting student learning information, students may enter corresponding information that is beyond their ability in an inappropriate manner during independent learning, which will cause the system to misjudge and misestimate the student's ability, ultimately affecting the student's learning quality. Summary of the invention

[0005] The purpose of the present invention is to provide a course construction system and method based on knowledge graph, which can monitor and evaluate students' learning information through comprehensive collection and analysis of students' learning data, thereby ensuring the learning quality of the corresponding students.

[0006] To achieve the above-mentioned purpose, the present invention provides a course construction system and method based on knowledge graph, including a user information management module, a course knowledge graph construction module and a course recommendation module, and also includes a multi-source data collection module, a learning data analysis module and a student portrait establishment module;

[0007] The multi-source data acquisition module is connected to the user information management module, the learning data analysis module is connected to the multi-source data acquisition module and to the user information management module, the student portrait establishment module is connected to the learning data analysis module and to the user information management module, the course knowledge graph construction module is connected to the course recommendation module, and the course recommendation module is connected to the learning data analysis module and to the user information management module.

[0008] The user information management module is used to collect, input and manage information of a specified type;

[0009] The learning data analysis module: analyzes the collected learning data through a corresponding algorithm;

[0010] The course knowledge graph construction module: sorts out the course content, extracts course knowledge points, establishes a relationship network structure between knowledge points, and forms a course knowledge graph;

[0011] The course recommendation module: intelligently recommends personalized learning paths and course content based on the knowledge graph and the students' evaluation results;

[0012] The student portrait building module builds a student portrait of the corresponding student based on the student's own learning data and the corresponding course evaluation.

[0013] Wherein, the user information management module includes an information collection and storage submodule, an autonomous management submodule and a background management submodule; the information collection and storage submodule is connected to the autonomous management submodule; the background management submodule is connected to the information collection and storage submodule;

[0014] The information collection and storage submodule: collects the basic information of the students and classifies and stores the input learning information data;

[0015] The self-management submodule is used for trainees to view and manage the corresponding information in their own system;

[0016] The backend management submodule is used by management personnel to extract, view and manage the information of designated students.

[0017] Wherein, the multi-source data acquisition module includes a function selection submodule and an information entry submodule, the function selection submodule is connected to the information entry submodule; the information entry submodule is connected to the user information management module;

[0018] The function selection submodule is used for students to select and edit the subjects they need to study;

[0019] The information input submodule is used to collect the learning data of the students.

[0020] Wherein, the learning data analysis module includes a designated information analysis submodule and a comprehensive judgment submodule, the designated information analysis submodule is connected to the multi-source data acquisition module; the comprehensive judgment submodule is connected to the designated information analysis submodule;

[0021] The designated information analysis submodule: classifies and processes the collected student learning data, and then performs corresponding analysis according to a preset algorithm;

[0022] The comprehensive judgment submodule is used to evaluate the learning quality and progress of a designated student in a designated subject based on the analysis results of the collected student learning data.

[0023] Among them, the student portrait establishment module includes a learning information summary submodule, an interesting chart establishment submodule and an interaction submodule, the learning information summary submodule is connected to the learning data analysis module; the interesting chart establishment submodule is connected to the learning information summary submodule; the interaction submodule is connected to the interesting chart establishment submodule, and is also connected to the learning information summary submodule;

[0024] The learning information summary submodule summarizes the learning evaluation results of all subjects of the students;

[0025] The interesting chart creation submodule generates corresponding interesting charts according to the basic information of the students and the summarized learning evaluation results;

[0026] The interactive submodule generates preset interactive images and videos according to the basic information of the students and the learning results of the corresponding stage.

[0027] Wherein, the function selection submodule includes a classification unit and a selection unit, the classification unit is connected to the information entry submodule; the selection unit is connected to the classification unit;

[0028] The classification unit is used to classify and sort out the learning subjects of students at a specified stage;

[0029] The selection unit is used to select subjects that need to be edited and studied from the subjects after classification.

[0030] Wherein, the information entry submodule includes a video data collection unit, a voice data collection unit and a picture data collection unit, the video data collection unit is connected to the function selection submodule and connected to the user information management module; the voice data collection unit is connected to the function selection submodule and connected to the user information management module; the picture data collection unit is connected to the function selection submodule and connected to the user information management module;

[0031] The video data collection unit is used to collect the learning video data of the trainees;

[0032] The voice data collection unit is used to collect the students' voice data related to learning;

[0033] The picture data collection unit collects picture data related to learning of students.

[0034] Wherein, the designated information analysis submodule includes a video information analysis unit, a voice information analysis unit and a picture information analysis unit, the video information analysis unit is connected to the information entry submodule; the voice information analysis unit is connected to the information entry submodule; the picture information analysis unit is connected to the information entry submodule;

[0035] The video information analysis unit is used to analyze the collected video data using a set algorithm;

[0036] The voice information analysis unit: analyzes the collected voice data through a set algorithm;

[0037] The picture information analysis unit analyzes the collected picture data using a set algorithm.

[0038] Wherein, the comprehensive judgment submodule includes a learning behavior judgment unit and a learning content judgment unit, the learning behavior judgment unit is connected to the specified information analysis submodule; the learning content judgment unit is connected to the specified information analysis submodule;

[0039] The learning behavior judgment unit is used to judge the learning behavior of the students according to the collected analysis results of the learning videos of the students;

[0040] The learning content judgment unit judges the learning content of the students according to the analysis results of the collected student learning data.

[0041] In the course construction system and method based on knowledge graph of the present invention, the information collection and storage submodule in the user information management module can input the basic information of the students and register to generate the corresponding system. At the same time, the information collection and storage submodule can also classify and store the learning data generated in the designated system, so that the students can modify, edit and view the information in the designated system through the autonomous management submodule, and the management personnel can view the learning materials in the designated student system through the background management submodule, which is convenient for the management personnel to manage;

[0042] The course knowledge graph construction module mainly uses AI technology and subject experts to manually or automatically sort out course content, extract course knowledge points, establish a relationship network structure between knowledge points, and form a course knowledge graph. Then, the course recommendation module is used to intelligently recommend personalized learning paths and course content based on the knowledge graph and the students' evaluation results. At the same time, the entire learning channel can track industry trends and the latest research results in real time, dynamically update course content, and ensure that students learn the latest and most cutting-edge knowledge.

[0043] The multi-source data acquisition module can complete the learning information collection of designated students according to the corresponding contents set by different disciplines, and then analyze and judge the collected learning information through the learning data analysis module, and generate a designated student portrait through the student portrait template according to the judgment structure, so that students and managers can directly evaluate and understand the students' learning ability by viewing the generated student portrait. At the same time, when the learning information collected by the multi-source data acquisition module is judged by the learning data analysis module, the learning behavior of the students can be monitored and evaluated to supervise the students to develop good learning behavior and learning attitude, so as to better improve the overall learning quality of the students. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below.

[0045] Figure 1 It is a structural diagram of the course construction system based on knowledge graph of the present invention.

[0046] Figure 2 It is a structural schematic diagram of the user information management module and the multi-source data acquisition module of the present invention.

[0047] Figure 3 It is a structural diagram of the learning data analysis module and the student portrait establishment module of the present invention.

[0048] Figure 4It is a structural schematic diagram of the function selection submodule of the present invention.

[0049] Figure 5 It is a structural diagram of the information entry submodule of the present invention.

[0050] Figure 6 It is a structural diagram of the designated information analysis submodule of the present invention.

[0051] Figure 7 It is a structural schematic diagram of the comprehensive judgment submodule of the present invention.

[0052] Figure 8 It is a flow chart of the knowledge graph-based course construction method of the present invention.

[0053] In the figure: 1-user information management module, 2-course knowledge graph construction module, 3-course recommendation module, 4-multi-source data acquisition module, 5-learning data analysis module, 6-student portrait establishment module, 11-information acquisition and storage sub-module, 12-autonomy management sub-module, 13-background management sub-module, 41-function selection sub-module, 42-information entry sub-module, 51-specified information analysis sub-module, 52-comprehensive judgment sub-module, 61-learning information summary sub-module, 62-interesting chart establishment sub-module, 63-interaction sub-module, 411-classification unit, 412-selection unit, 421-video data collection unit, 422-voice data collection unit, 423-picture data collection unit, 511-video information analysis unit, 512-voice information analysis unit, 513-picture information analysis unit, 521-learning behavior judgment unit, 522-learning content judgment unit. DETAILED DESCRIPTION

[0054] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0055] In the description of the present invention, it should be understood that “plurality” means two or more than two, unless otherwise clearly and specifically defined.

[0056] See also Figures 1 to 7The present invention provides a course construction system based on knowledge graph: including user information management module 1, course knowledge graph construction module 2, course recommendation module 3, multi-source data collection module 4, learning data analysis module 5 and student portrait establishment module 6. The above scheme solves the problem that the course construction system mainly makes judgments based on the collected student information, and then evaluates the learning progress and quality of the students' corresponding subjects and corresponding contents. However, since some students have relatively weak self-control in the learning process, and the existing course construction system cannot judge the authenticity of the information when collecting the student learning information, it will cause the students to enter the corresponding information that is not within their ability in an inappropriate way during self-study, which will cause the system to misjudge and misestimate the students' abilities, and ultimately affect the students' learning quality.

[0057] For further information, see Figure 1 The multi-source data acquisition module 4 is connected to the user information management module 1, the learning data analysis module 5 is connected to the multi-source data acquisition module 4 and is connected to the user information management module 1, the student portrait establishment module 6 is connected to the learning data analysis module 5 and is connected to the user information management module 1, the course knowledge graph construction module 2 is connected to the course recommendation module 3, and the course recommendation module 3 is connected to the learning data analysis module 5 and is connected to the user information management module 1.

[0058] The user information management module 1 is used to collect, input and manage information of a specified type;

[0059] The learning data analysis module 5: analyzes the collected learning data through a corresponding algorithm;

[0060] The course knowledge graph construction module 2: sorting out the course content, extracting course knowledge points, establishing a relationship network structure between knowledge points, and forming a course knowledge graph;

[0061] The course recommendation module 3: intelligently recommends personalized learning paths and course contents based on the knowledge graph and the evaluation results of the students;

[0062] The student portrait building module 6 builds a student portrait of the corresponding student based on the student's own learning data and the corresponding course evaluation.

[0063] For further information, see Figure 2 , the user information management module 1 includes an information collection and storage submodule 11, an autonomous management submodule 12 and a background management submodule 13; the information collection and storage submodule 11 is connected to the autonomous management submodule 12; the background management submodule 13 is connected to the information collection and storage submodule 11;

[0064] The information collection and storage submodule 11: collects the basic information of the students and classifies and stores the input learning information data;

[0065] The autonomous management submodule 12 is used for trainees to view and manage corresponding information in their own system;

[0066] The backend management submodule 13 is used by management personnel to extract, view and manage the information of designated students.

[0067] When this embodiment is used, the information collection and storage submodule 11 in the user information management module 1 can input the basic information of the trainees and register and generate the corresponding system. At the same time, the information collection and storage submodule 11 can also classify and store the learning data generated in the designated system, so that the trainees can modify, edit and view the information in the designated system through the provided self-management submodule 12, and the management personnel can view the learning materials in the designated trainee system through the background management submodule 13, which is convenient for the management personnel to manage;

[0068] The course knowledge graph construction module 2 mainly uses AI technology and subject experts to manually or automatically sort out course content, extract course knowledge points, establish a relationship network structure between knowledge points, and form a course knowledge graph. Then, the course recommendation module 3 is provided to intelligently recommend personalized learning paths and course content based on the knowledge graph and the evaluation results of the students. At the same time, the entire learning channel can track industry trends and the latest research results in real time, dynamically update course content, and ensure that students learn the latest and most cutting-edge knowledge;

[0069] The multi-source data acquisition module 4 can complete the learning information collection of designated students according to the corresponding contents set by different subjects, and then analyze and judge the collected learning information through the learning data analysis module 5, and generate a designated student portrait through the student portrait template according to the judgment structure, so that students and managers can directly evaluate and understand the students' learning ability by viewing the generated student portrait. At the same time, when the learning information collected by the multi-source data acquisition module 4 is judged by the learning data analysis module 5, the learning behavior of the students can be monitored and evaluated, so as to supervise the students to develop good learning behavior and learning attitude, so as to better improve the overall learning quality of the students.

[0070] For further information, see Figure 2, the multi-source data acquisition module 4 includes a function selection submodule 41 and an information entry submodule 42, the function selection submodule 41 is connected to the information entry submodule 42; the information entry submodule 42 is connected to the user information management module 1;

[0071] The function selection submodule 41 is used for students to select and edit the subjects they need to study;

[0072] The information input submodule 42 is used to collect the learning data of the students.

[0073] For further information, see Figure 4 The function selection submodule 41 includes a classification unit 411 and a selection unit 412, wherein the classification unit 411 is connected to the information entry submodule 42; the selection unit 412 is connected to the classification unit 411;

[0074] The classification unit 411 is used to classify and sort out the learning subjects of the students at a specified stage;

[0075] The selection unit 412 is used to select subjects that need to be edited and studied from the subjects after classification.

[0076] For further information, see Figure 5 The information entry submodule 42 includes a video data collection unit 421, a voice data collection unit 422 and a picture data collection unit 423. The video data collection unit 421 is connected to the function selection submodule 41 and is connected to the user information management module 1; the voice data collection unit 422 is connected to the function selection submodule 41 and is connected to the user information management module 1; the picture data collection unit 423 is connected to the function selection submodule 41 and is connected to the user information management module 1;

[0077] The video data collection unit 421 collects the learning video data of the trainees;

[0078] The voice data collection unit 422 collects the student's voice data related to learning;

[0079] The picture data collection unit 423 collects picture data related to learning of the students.

[0080] When this embodiment is used, the function selection submodule 41 can allow students to select corresponding subjects according to the specified tasks and their own learning needs through the classification unit 411 and the selection unit 412, and then set different learning contents according to different subjects, and then determine the different types of learning data to be collected. The information input submodule 42 can collect different learning contents through the video data collection unit 421, the voice data collection unit 422 and the picture data collection unit 423.

[0081] It should be noted that in order to be able to make better subsequent judgments on the students' learning behavior, the video data collection unit 421 can use face recognition technology in conjunction with the shooting equipment to collect video data when the students are studying, and then record the overall learning situation of the students. Moreover, the video data collection unit 421 and the voice data collection unit 422 can realize the comprehensive collection of the students' learning data. The image data collection unit 423 is mainly used to identify the students' written homework and homework that requires handwriting operations and collect corresponding data. For example, in the study of literary subjects such as English and Chinese, it is necessary not only to collect the data of test answers, but also to collect the students' reading data and writing data, so as to facilitate the subsequent analysis and judgment of the students' comprehensive learning ability and learning situation.

[0082] For further information, see Figure 3 , the learning data analysis module 5 includes a designated information analysis submodule 51 and a comprehensive judgment submodule 52, the designated information analysis submodule 51 is connected to the multi-source data acquisition module 4; the comprehensive judgment submodule 52 is connected to the designated information analysis submodule 51;

[0083] The designated information analysis submodule 51: classifies the collected student learning data, and then performs corresponding analysis according to a preset algorithm;

[0084] The comprehensive judgment submodule 52 evaluates the learning quality and learning progress of a designated student in a designated subject according to the analysis results of the collected student learning data.

[0085] For further information, see Figure 6 The designated information analysis submodule 51 includes a video information analysis unit 511, a voice information analysis unit 512 and a picture information analysis unit 513. The video information analysis unit 511 is connected to the information entry submodule 42; the voice information analysis unit 512 is connected to the information entry submodule 42; the picture information analysis unit 513 is connected to the information entry submodule 42;

[0086] The video information analysis unit 511 analyzes the collected video data using a set algorithm;

[0087] The voice information analysis unit 512 analyzes the collected voice data using a set algorithm;

[0088] The picture information analysis unit 513 analyzes the collected picture data using a set algorithm.

[0089] For further information, see Figure 7 The comprehensive judgment submodule 52 includes a learning behavior judgment unit 521 and a learning content judgment unit 522, wherein the learning behavior judgment unit 521 is connected to the specified information analysis submodule 51; and the learning content judgment unit 522 is connected to the specified information analysis submodule 51;

[0090] The learning behavior judgment unit 521 judges the learning behavior of the students according to the collected analysis results of the student learning videos;

[0091] The learning content judgment unit 522 judges the learning content of the students according to the analysis results of the collected student learning data.

[0092] When this embodiment is used, the corresponding data is collected through the information input submodule 42 according to the subject content selected by the student, and then the video information analysis unit 511, the voice information analysis unit 512 and the picture information analysis unit 513 provided in the designated information analysis submodule 51 are used to process and analyze the collected various information. When performing the analysis, the video information analysis unit 511 can combine computer vision and image processing technology to track the movement of the eyeball, so as to estimate the direction and position of the student's line of sight during the learning process by taking a video image of the eye and processing and analyzing the image using an algorithm, and then the learning behavior judgment unit 521 is used to judge the student's learning behavior according to the preset The standard situation is used to continuously analyze and monitor the sight state of the students during the learning process. When the students' sight is offset, the video node with the problem can be marked and recorded and displayed in the final judgment result, so that the management personnel can correct the learning behavior problems of the corresponding students in time when checking the learning data of the students' background. Most of the learning behavior judgment units 521 make judgments based on the analysis results of the video content. When making judgments, computer vision algorithms can be used to detect and track key points of the human body, and then analyze the posture and movement of the human body to ensure that the students' sitting posture is continuously maintained during the learning process and the learning status is continuously monitored, so as to better assist the management personnel in improving the learning quality of the students;

[0093] The voice information analysis unit 512 mainly analyzes and judges the voice learning data collected by the voice data collection unit 422. A voice recognition system is set in the voice information analysis unit 512. The information collection and storage submodule 11 of the user information management module 1 needs to collect the voice data of the designated student when collecting user information, so as to assist the voice information analysis unit 512 to judge the subsequently collected voice learning data, so that after the voice data collection unit 422 collects the learning data such as recitation and spelling, the voice information analysis unit 512 can judge whether it is the student himself who is learning through the voice recognition system, so as to avoid the situation where the student is read by others;

[0094] The image information analysis unit 513 scans and inputs the learning information such as the writing data uploaded by the students. The image information analysis unit 513 can set different algorithms for analysis and judgment according to different subject contents. For example, for some literary subjects, the writing quality of the students can be mechanically evaluated by setting corresponding writing evaluation algorithms. The writing evaluation algorithm is mainly a judgment method based on image processing. First, the text in the writing sample is converted into recognizable digital characters using OCR technology, and then key features such as stroke order, stroke length, font size, tilt angle, etc. are extracted from the recognized characters. At the same time, the texture features of the writing sample, such as paper background, ink penetration, etc., can be analyzed to evaluate the neatness and clarity of the writing. The edge of the character can also be detected using an image processing algorithm to evaluate the fineness and stability of the writing.

[0095] After the corresponding analysis unit completes the analysis and judgment of the designated data, the corresponding learning evaluation can be performed through the learning content judgment unit 522. At the same time, based on the monitoring and analysis of the learning status, the evaluation can also be performed through the learning behavior judgment unit 521. The evaluation results are then converted into numbers for output, so as to provide a basis for the subsequent establishment and update of student portraits. At the same time, the generated evaluation results will also be stored in the information collection and storage submodule 11 in the user information management module 1, so that students and managers can view them.

[0096] For further information, see Figure 3 The student portrait building module 6 includes a learning information summary submodule 61, an interesting chart building submodule 62 and an interaction submodule 63. The learning information summary submodule 61 is connected to the learning data analysis module 5; the interesting chart building submodule 62 is connected to the learning information summary submodule 61; the interaction submodule 63 is connected to the interesting chart building submodule 62 and to the learning information summary submodule 61;

[0097] The learning information summary submodule 61 is used to summarize the learning evaluation results of all subjects of the students;

[0098] The interesting chart creation submodule 62 generates a corresponding interesting chart according to the basic information of the students and the summarized learning evaluation results;

[0099] The interaction submodule 63 generates preset interaction images and videos according to the basic information of the students and the learning results of the corresponding stage.

[0100] When the present embodiment is in use, the learning information summary submodule 61 can summarize and collect the learning assessment data generated for the designated subject, and then generate the corresponding student portrait through the interesting chart creation submodule 62. The interesting chart creation submodule 62 can classify the generated student portrait according to the collected gender information, roughly into two categories: female and male. Different types of student portraits can be generated according to the different aesthetics of females and males, and then the corresponding student portraits can be updated in real time according to the set subject combined with the learning assessment data of the corresponding subject. For example, male students can design the overall portrait interface as an ability table in the game, set the corresponding subject and the corresponding value in the ability table, and then continuously update the ability table in the portrait according to the periodic learning assessment data. This not only allows students and managers to intuitively observe the students' learning ability but also greatly prompts the students' learning interest.

[0101] The student portrait established by the learning information aggregation submodule 61 and the interesting chart establishment submodule 62 can produce different interesting interactive effects through the set interactive submodule 63. For example, when a designated student has a phased breakthrough in a certain subject, a corresponding image interaction effect can be generated, thereby giving the corresponding student a certain encouragement, and at the same time cultivating the student's interest in active learning. Different image interactions can be set according to different types of subjects, so that students can more intuitively feel the improvement of their own learning ability, thereby stimulating the corresponding students' interest in learning.

[0102] See also Figure 8 A method for course construction based on knowledge graph, using the course construction system based on knowledge graph, comprises the following steps:

[0103] S1: The basic information of the trainees is collected and inputted through the user information management module 1, thereby generating a corresponding learning system, so that the users and managers can subsequently view and edit the learning content in the generated system through the user information management module 1;

[0104] S2: Collect various types of learning data of designated students through the multi-source data collection module 4 and store them in the system generated by the user information management module 1;

[0105] S3: Analyze and evaluate the learning data collected by the multi-source data collection module 4 according to the selected subject through the learning data analysis module 5, and store the final analysis and evaluation data in the system generated by the user information management module 1;

[0106] S4: The student portrait establishing module 6 generates a student portrait of the corresponding student according to the learning assessment data generated by the learning data analyzing module 5, so as to understand the learning status and learning ability of the corresponding student more specifically through the generated student portrait.

[0107] What is disclosed above is only one or more preferred embodiments of the present application, and cannot be used to limit the scope of rights of the present application. Ordinary technicians in this field can understand that all or part of the processes of implementing the above embodiments and equivalent changes made according to the claims of the present application are still within the scope covered by the present application.

Claims

1. A course construction system based on knowledge graph, including a user information management module, a course knowledge graph construction module and a course recommendation module, characterized in that: It also includes a multi-source data collection module, a learning data analysis module, and a student portrait building module; The multi-source data acquisition module is connected to the user information management module, the learning data analysis module is connected to the multi-source data acquisition module and to the user information management module, the student portrait establishment module is connected to the learning data analysis module and to the user information management module, the course knowledge graph construction module is connected to the course recommendation module, and the course recommendation module is connected to the learning data analysis module and to the user information management module. The user information management module is used to collect, input and manage information of a specified type; The learning data analysis module: analyzes the collected learning data through a corresponding algorithm; The course knowledge graph construction module: sorts out the course content, extracts course knowledge points, establishes a relationship network structure between knowledge points, and forms a course knowledge graph; The course recommendation module: intelligently recommends personalized learning paths and course content based on the knowledge graph and the students' evaluation results; The student portrait building module builds a student portrait of the corresponding student based on the student's own learning data and the corresponding course evaluation.

2. The course construction system based on knowledge graph as claimed in claim 1, characterized in that: The user information management module includes an information collection and storage submodule, an autonomous management submodule and a background management submodule; The information collection and storage submodule is connected to the autonomous management submodule; the background management submodule is connected to the information collection and storage submodule; The information collection and storage submodule: collects the basic information of the students and classifies and stores the input learning information data; The self-management submodule is used for trainees to view and manage the corresponding information in their own system; The backend management submodule is used by management personnel to extract, view and manage the information of designated students.

3. The course construction system based on knowledge graph as claimed in claim 1, characterized in that: The multi-source data acquisition module includes a function selection submodule and an information entry submodule, wherein the function selection submodule is connected to the information entry submodule; the information entry submodule is connected to the user information management module; The function selection submodule is used for students to select and edit the subjects they need to study; The information input submodule is used to collect the learning data of the students.

4. The course construction system based on knowledge graph as claimed in claim 1, characterized in that: The learning data analysis module includes a designated information analysis submodule and a comprehensive judgment submodule, wherein the designated information analysis submodule is connected to the multi-source data acquisition module; the comprehensive judgment submodule is connected to the designated information analysis submodule; The designated information analysis submodule: classifies and processes the collected student learning data, and then performs corresponding analysis according to a preset algorithm; The comprehensive judgment submodule is used to evaluate the learning quality and progress of a designated student in a designated subject based on the analysis results of the collected student learning data.

5. The course construction system based on knowledge graph according to claim 1, characterized in that: The student portrait building module includes a learning information summary submodule, an interesting chart building submodule and an interaction submodule. The learning information summary submodule is connected to the learning data analysis module; the interesting chart building submodule is connected to the learning information summary submodule; the interaction submodule is connected to the interesting chart building submodule and to the learning information summary submodule; The learning information summary submodule summarizes the learning evaluation results of all subjects of the students; The interesting chart creation submodule generates corresponding interesting charts according to the basic information of the students and the summarized learning evaluation results; The interactive submodule generates preset interactive images and videos according to the basic information of the students and the learning results of the corresponding stage.

6. The course construction system based on knowledge graph as claimed in claim 3, characterized in that: The function selection submodule includes a classification unit and a selection unit, the classification unit is connected to the information entry submodule; the selection unit is connected to the classification unit; The classification unit is used to classify and sort out the learning subjects of students at a specified stage; The selection unit is used to select subjects that need to be edited and studied from the subjects after classification.

7. The course construction system based on knowledge graph according to claim 6, characterized in that: The information entry submodule includes a video data collection unit, a voice data collection unit and a picture data collection unit. The video data collection unit is connected to the function selection submodule and to the user information management module; the voice data collection unit is connected to the function selection submodule and to the user information management module; the picture data collection unit is connected to the function selection submodule and to the user information management module; The video data collection unit is used to collect the learning video data of the trainees; The voice data collection unit collects the student's voice data related to learning; The picture data collection unit collects picture data related to learning of students.

8. The course construction system based on knowledge graph as claimed in claim 4, characterized in that: The designated information analysis submodule includes a video information analysis unit, a voice information analysis unit and a picture information analysis unit, wherein the video information analysis unit is connected to the information entry submodule; the voice information analysis unit is connected to the information entry submodule; and the picture information analysis unit is connected to the information entry submodule; The video information analysis unit is used to analyze the collected video data using a set algorithm; The voice information analysis unit: analyzes the collected voice data through a set algorithm; The picture information analysis unit analyzes the collected picture data using a set algorithm.

9. The course construction system based on knowledge graph as claimed in claim 8, characterized in that: The comprehensive judgment submodule includes a learning behavior judgment unit and a learning content judgment unit, the learning behavior judgment unit is connected to the specified information analysis submodule; the learning content judgment unit is connected to the specified information analysis submodule; The learning behavior judgment unit is used to judge the learning behavior of the students according to the collected analysis results of the learning videos of the students; The learning content judgment unit judges the learning content of the students according to the analysis results of the collected student learning data.

10. A method for course construction based on knowledge graph, using the course construction system based on knowledge graph as claimed in claim 1, characterized in that: The following steps are included: The basic information of the students is collected and input through the user information management module, thereby generating a corresponding learning system, so that users and managers can subsequently view and edit the learning content in the generated system through the user information management module; Collect various types of learning data of designated students through the multi-source data collection module and store them in the system generated by the user information management module; Analyze and evaluate the learning data collected by the multi-source data collection module according to the selected subject through the learning data analysis module, and store the final analysis and evaluation data in the system generated by the user information management module; The student portrait establishment module generates a student portrait of the corresponding student based on the learning assessment data generated by the learning data analysis module, so as to understand the learning status and learning ability of the corresponding student more specifically through the generated student portrait.

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