Multi-dimensional dynamic visual advanced mathematics teaching system
Through multi-dimensional dynamic visualization of advanced mathematics teaching system, combined with artificial intelligence and multimedia technology, the traditional teaching system ignores mathematical application ability and teaches according to its aptitude, realizes personalized learning paths and efficient teaching effects, and improves students' learning experience and system performance.
Patent Information
- Application Number
- CN202411193256.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-08-28
- Publication Date
- 2025-01-17
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
When pursuing theoretical rigor, the traditional higher mathematics teaching system ignores the cultivation of mathematical application ability, and it is difficult to achieve teaching according to students' individual differences, so the teaching effect is limited.
A multi-dimensional dynamic visual advanced mathematics teaching system was designed, including knowledge graph construction module, dynamic visual display module, personalized learning path recommendation module, exercise and testing module, teaching resource and management module, interaction and communication module and cloud storage backup module , utilizing artificial intelligence and multimedia technology, provide personalized learning paths and interactive platforms, integrate teaching resources, and improve learning efficiency and effectiveness.
Through personalized learning path recommendation and multimedia display, students' math application ability and learning efficiency are improved, teaching students in accordance with their aptitude, learning experience and sense of participation are enhanced, and the system's response speed and processing efficiency are improved through cloud storage backup.
Smart Images
Figure CN119323908A_ABST
Abstract
Description
Technical Field
[0001] The invention relates to the technical field of higher mathematics teaching systems, and in particular to a multi-dimensional dynamic visualization higher mathematics teaching system. Background Art
[0002] With the development of educational technology, teaching media plays an increasingly important role in the higher mathematics teaching system. Traditional teaching media such as blackboards and chalks have gradually been replaced by modern teaching media such as multimedia equipment and network platforms. The higher mathematics teaching system refers to a complex system composed of multiple elements, aiming to achieve the teaching goals of higher mathematics. This system includes teachers, students, teaching materials, teaching media, and teaching environment. However, when using the higher mathematics teaching system, the teaching content is systematic and comprehensive, and the pursuit of theoretical rigor often ignores the cultivation of mathematical application ability. It usually emphasizes the dominant position of teachers, teaches through blackboard writing and lectures, and pays attention to students' induction, derivation and calculation of mathematical concepts and methods. Therefore, the teaching effect often varies due to individual differences among students, and it is difficult to teach students in accordance with their aptitude. Summary of the invention
[0003] In order to overcome the problem that when using the higher mathematics teaching system, the teaching content is systematic and comprehensive, pursuing theoretical rigor, but often neglecting the cultivation of mathematical application ability, and usually emphasizing the dominant position of teachers, teaching through blackboard writing and lectures, focusing on students' induction, deduction and calculation of mathematical concepts and methods. Therefore, the teaching effect often varies due to individual differences among students, and it is difficult to achieve teaching students in accordance with their aptitude.
[0004] The technical solution of the present invention is: a multi-dimensional dynamic visualization higher mathematics teaching system, comprising: Knowledge graph building module: used to classify and divide knowledge points in the system; Dynamic visualization display module: used to display knowledge points in a visual way; Personalized learning path recommendation module: used to evaluate and recommend users based on their habits; Exercise and test module: used to intelligently create user exercise question bank; Teaching resources and management module: used to integrate and manage teaching resources; Interaction and communication module: used to provide users with an online discussion platform; Cloud storage backup module: used to store and back up data generated by system operation.
[0005] Preferably, the knowledge graph construction module is used to classify and hierarchically divide the knowledge points in higher mathematics to form a clear knowledge structure diagram, helping students to grasp the internal connections between various knowledge points from a macro perspective, and display the logical relationship between different concepts through nodes and lines, such as prerequisite knowledge, subsequent applications, etc., to help students establish a systematic knowledge framework.
[0006] Preferably, the dynamic visualization display module is used to use multimedia means such as graphics and animation to display abstract mathematical concepts, theorems, formulas, etc. in an intuitive and vivid way, reducing the difficulty of understanding. At the same time, it provides an interactive operation interface, allowing students to observe and understand mathematical objects from different angles through operations such as dragging, rotating, and zooming, thereby enhancing the sense of participation and experience in learning.
[0007] Preferably, the personalized learning path recommendation module is used to intelligently evaluate students' learning levels and ability characteristics through their learning behaviors, test scores and other data in the system. Based on the evaluation results, personalized learning paths are recommended to students, including the sequence of learning content, difficulty gradient, etc., to achieve teaching according to students' aptitude.
[0008] Preferably, the personalized learning path recommendation module includes the following steps when working: S11: First, collect students’ basic information, learning style, cognitive level and other characteristic data through various channels such as students’ learning behavior logs, test scores, questionnaires, etc.; S12: Use data analysis techniques, such as cluster analysis and association rule mining, to process and analyze the collected data to identify students’ personalized characteristics and learning needs; S13: Based on the learning paths of similar users, by calculating the similarity between students, the knowledge items commonly selected by similar users are recommended to the current student; S14: Using intelligent algorithms such as ant colony algorithm, find the probability optimization path according to the student's learning history and current learning status, that is, the learning path that is most likely to improve the student's learning effect; S15: The system monitors students’ learning progress and results in real time, and dynamically adjusts the recommended learning path based on changes in students’ learning behavior; S16: Evaluate the effectiveness of the learning path based on multiple indicators such as students’ academic performance, study time, and participation, to ensure that the recommended path can maximize the students’ learning needs.
[0009] Preferably, through the recommendation of personalized learning paths, students can avoid wasting time on irrelevant or already mastered content, and instead focus their energy on areas where they need to focus on learning and improving. Targeted learning methods can significantly improve learning efficiency, allowing students to achieve the greatest learning results in a limited time. The personalized learning path recommendation module can customize learning content according to students' interests, learning styles and learning progress, making the learning process more in line with students' personal needs.
[0010] As a preferred option, the exercises and tests module is used to build an exercise bank with various question types and difficulty levels, covering the main knowledge points and test points of advanced mathematics, providing a dynamic analysis process of exercises, helping students understand problem-solving ideas and methods, and improving their problem-solving ability. At the same time, regular tests are conducted to verify students' learning outcomes, and targeted feedback and suggestions are provided based on the test results.
[0011] As a preferred option, the teaching resource and management module is used to integrate various teaching resources such as textbooks, lesson plans, courseware, videos, etc., to provide teachers with rich teaching materials. At the same time, it supports teachers to publish teaching tasks, correct homework, manage student information online, etc., to improve the efficiency and convenience of teaching management.
[0012] Preferably, the interaction and communication module is used to provide an online discussion area or forum to encourage students and teachers to communicate and discuss problems encountered in learning, promote knowledge sharing and collision of ideas, and support students to form study groups to complete learning tasks and projects together, and cultivate teamwork and problem-solving abilities.
[0013] Preferably, the cloud storage backup module includes an information resource management submodule and a cloud storage terminal, which integrates the online data generated by the system operation, manages and stores the integrated data, and stores and backs up the online data generated by the system operation to the cloud.
[0014] Preferably, when the cloud storage backup module backs up and stores data, the following method is included: A21: Create a master document based on the corresponding date on the cloud platform; A22: Create classification sub-documents in the main document based on classification information; A23: Compress and encrypt the online data generated by the system operation for backup; A24: Put the online data generated by the system operation into a sub-document.
[0015] Preferably, the cloud storage backup module facilitates permanent storage of various data required by the system, and can effectively back up online data generated by system operation. The data storage module can effectively improve the response speed and processing efficiency of the system.
[0016] Beneficial effects of the present invention: 1. Compared with the traditional higher mathematics teaching system, the teaching content is systematic and comprehensive, and the pursuit of theoretical rigor, but the cultivation of mathematical application ability is often neglected. It usually emphasizes the dominant position of teachers, teaches through blackboard writing and lectures, and focuses on students' induction, derivation and calculation of mathematical concepts and methods. Therefore, the teaching effect often varies due to individual differences among students, and it is difficult to teach students in accordance with their aptitude. This higher mathematics teaching system introduces advanced artificial intelligence technology and educational theory to provide students with personalized learning path recommendations. Students can choose appropriate learning content and paths according to their own learning progress and ability level, and realize independent learning and personalized development; 2. Through the recommendation of personalized learning paths, students can avoid wasting time on irrelevant or already mastered content, and instead focus their energy on areas where they need to focus on learning and improving. Targeted learning methods can significantly improve learning efficiency, allowing students to achieve the greatest learning results within a limited time. The personalized learning path recommendation module can customize learning content based on students' interests, learning styles, and learning progress, making the learning process more in line with students' personal needs; 3. The cloud storage backup module facilitates the permanent preservation of various data required by the system, and can effectively back up the online data generated by the system operation. The data storage module can effectively improve the system's response speed and processing efficiency. BRIEF DESCRIPTION OF THE DRAWINGS
[0017] Figure 1 What is shown is a schematic diagram of the workflow of a personalized learning path recommendation module of a multi-dimensional dynamic visualization higher mathematics teaching system of the present invention. DETAILED DESCRIPTION
[0018] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.
[0019] See also Figure 1 The present invention provides an embodiment: a multi-dimensional dynamic visualization higher mathematics teaching system, comprising: Knowledge graph building module: used to classify and divide knowledge points in the system; Dynamic visualization display module: used to display knowledge points in a visual way; Personalized learning path recommendation module: used to evaluate and recommend users based on their habits; Exercise and test module: used to intelligently create user exercise question bank; Teaching resources and management module: used to integrate and manage teaching resources; Interaction and communication module: used to provide users with an online discussion platform; Cloud storage backup module: used to store and back up data generated by system operation.
[0020] Preferably, the knowledge graph construction module is used to classify and hierarchically divide the knowledge points in higher mathematics to form a clear knowledge structure diagram, helping students to grasp the internal connections between various knowledge points from a macro perspective, and display the logical relationship between different concepts through nodes and lines, such as prerequisite knowledge, subsequent applications, etc., to help students establish a systematic knowledge framework.
[0021] Preferably, the dynamic visualization display module is used to use multimedia means such as graphics and animation to display abstract mathematical concepts, theorems, formulas, etc. in an intuitive and vivid way, reducing the difficulty of understanding. At the same time, it provides an interactive operation interface, allowing students to observe and understand mathematical objects from different angles through operations such as dragging, rotating, and zooming, thereby enhancing the sense of participation and experience in learning.
[0022] Preferably, the personalized learning path recommendation module is used to intelligently evaluate students' learning levels and ability characteristics through their learning behaviors, test scores and other data in the system. Based on the evaluation results, personalized learning paths are recommended to students, including the sequence of learning content, difficulty gradient, etc., to achieve teaching according to students' aptitude.
[0023] Preferably, the personalized learning path recommendation module includes the following steps when working: S11: First, collect students’ basic information, learning style, cognitive level and other characteristic data through various channels such as students’ learning behavior logs, test scores, questionnaires, etc.; S12: Use data analysis techniques, such as cluster analysis and association rule mining, to process and analyze the collected data to identify students’ personalized characteristics and learning needs; S13: Based on the learning paths of similar users, by calculating the similarity between students, the knowledge items commonly selected by similar users are recommended to the current student; S14: Using intelligent algorithms such as ant colony algorithm, find the probability optimization path according to the student's learning history and current learning status, that is, the learning path that is most likely to improve the student's learning effect; S15: The system monitors students’ learning progress and results in real time, and dynamically adjusts the recommended learning path based on changes in students’ learning behavior; S16: Evaluate the effectiveness of the learning path based on multiple indicators such as students’ academic performance, study time, and participation, to ensure that the recommended path can maximize the students’ learning needs.
[0024] Preferably, through the recommendation of personalized learning paths, students can avoid wasting time on irrelevant or already mastered content, and instead focus their energy on areas where they need to focus on learning and improving. Targeted learning methods can significantly improve learning efficiency, allowing students to achieve the greatest learning results in a limited time. The personalized learning path recommendation module can customize learning content according to students' interests, learning styles and learning progress, making the learning process more in line with students' personal needs.
[0025] As a preferred option, the exercises and tests module is used to build an exercise bank with various question types and difficulty levels, covering the main knowledge points and test points of advanced mathematics, providing a dynamic analysis process of exercises, helping students understand problem-solving ideas and methods, and improving their problem-solving ability. At the same time, regular tests are conducted to verify students' learning outcomes, and targeted feedback and suggestions are provided based on the test results.
[0026] As a preferred option, the teaching resource and management module is used to integrate various teaching resources such as textbooks, lesson plans, courseware, videos, etc., to provide teachers with rich teaching materials. At the same time, it supports teachers to publish teaching tasks, correct homework, manage student information online, etc., to improve the efficiency and convenience of teaching management.
[0027] Preferably, the interaction and communication module is used to provide an online discussion area or forum to encourage students and teachers to communicate and discuss problems encountered in learning, promote knowledge sharing and collision of ideas, and support students to form study groups to complete learning tasks and projects together, and cultivate teamwork and problem-solving abilities.
[0028] Preferably, the cloud storage backup module includes an information resource management submodule and a cloud storage terminal, which integrates the online data generated by the system operation, manages and stores the integrated data, and stores and backs up the online data generated by the system operation to the cloud.
[0029] Preferably, when the cloud storage backup module backs up and stores data, the following method is included: A21: Create a master document based on the corresponding date on the cloud platform; A22: Create classification sub-documents in the main document based on classification information; A23: Compress and encrypt the online data generated by the system operation for backup; A24: Put the online data generated by the system operation into a sub-document.
[0030] Preferably, the cloud storage backup module facilitates permanent storage of various data required by the system, and can effectively back up online data generated by system operation. The data storage module can effectively improve the response speed and processing efficiency of the system.
[0031] The embodiments of the present invention are described in detail above with reference to the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge scope of those skilled in the art without departing from the spirit of the present invention.
Claims
1. A multi-dimensional dynamic visualization advanced mathematics teaching system; characterized by: Included are: Knowledge graph building module: used to classify and divide knowledge points in the system; Dynamic visualization display module: used to display knowledge points in a visual way; Personalized learning path recommendation module: used to evaluate and recommend users based on their habits; Exercise and test module: used to intelligently create user exercise question bank; Teaching resources and management module: used to integrate and manage teaching resources; Interaction and communication module: used to provide users with an online discussion platform; Cloud storage backup module: used to store and back up data generated by system operation.
2. A multi-dimensional dynamic visualization higher mathematics teaching system according to claim 1, characterized in that: The knowledge graph construction module is used to classify and hierarchically divide knowledge points in higher mathematics to form a clear knowledge structure diagram, helping students grasp the internal connections between various knowledge points from a macro perspective, and display the logical relationship between different concepts through nodes and lines, such as prerequisite knowledge, subsequent applications, etc., to help students establish a systematic knowledge framework.
3. A multi-dimensional dynamic visualization higher mathematics teaching system according to claim 2, characterized in that: The dynamic visualization display module is used to use multimedia means such as graphics and animation to display abstract mathematical concepts, theorems, formulas, etc. in an intuitive and vivid way, reducing the difficulty of understanding. At the same time, it provides an interactive operation interface, allowing students to observe and understand mathematical objects from different angles through operations such as dragging, rotating, and zooming, thereby enhancing their sense of participation and experience in learning.
4. A multi-dimensional dynamic visualization higher mathematics teaching system according to claim 3, characterized in that: The personalized learning path recommendation module is used to intelligently evaluate students' learning levels and ability characteristics through their learning behaviors, test scores and other data in the system. Based on the evaluation results, it recommends personalized learning paths for students, including the sequence of learning content, difficulty gradient, etc., to achieve teaching according to their aptitude.
5. A multi-dimensional dynamic visualization higher mathematics teaching system according to claim 4, characterized in that: The personalized learning path recommendation module includes the following steps when working: S11: First, collect students’ basic information, learning style, cognitive level and other characteristic data through various channels such as students’ learning behavior logs, test scores, questionnaires, etc.; S12: Use data analysis techniques, such as cluster analysis and association rule mining, to process and analyze the collected data to identify students’ personalized characteristics and learning needs; S13: Based on the learning paths of similar users, by calculating the similarity between students, the knowledge items commonly selected by similar users are recommended to the current student; S14: Using intelligent algorithms such as ant colony algorithm, find the probability optimization path according to the student's learning history and current learning status, that is, the learning path that is most likely to improve the student's learning effect; S15: The system monitors students’ learning progress and results in real time, and dynamically adjusts the recommended learning path based on changes in students’ learning behavior; S16: Evaluate the effectiveness of the learning path based on multiple indicators such as students’ academic performance, study time, and participation, to ensure that the recommended path can maximize the students’ learning needs.
6. A multi-dimensional dynamic visualization higher mathematics teaching system according to claim 5, characterized in that: The exercises and tests module is used to build an exercise bank with various question types and difficulty levels, covering the main knowledge points and test points of advanced mathematics, providing a dynamic analysis process for exercises, helping students understand problem-solving ideas and methods, and improving their problem-solving skills. At the same time, regular tests are conducted to verify students' learning outcomes, and targeted feedback and suggestions are provided based on the test results.
7. A multi-dimensional dynamic visualization higher mathematics teaching system according to claim 6, characterized in that: The teaching resource and management module is used to integrate various teaching resources such as textbooks, lesson plans, courseware, videos, etc., to provide teachers with rich teaching materials. It also supports teachers to publish teaching tasks, correct homework, manage student information, etc. online, thereby improving the efficiency and convenience of teaching management.
8. A multi-dimensional dynamic visualization higher mathematics teaching system according to claim 7, characterized in that: The interaction and communication module is used to provide an online discussion area or forum to encourage students and teachers to communicate and discuss problems encountered in learning, promote knowledge sharing and collision of ideas, and support students to form study groups to complete learning tasks and projects together, and cultivate teamwork and problem-solving skills.
9. A multi-dimensional dynamic visualization higher mathematics teaching system according to claim 8, characterized in that: The cloud storage backup module includes an information resource management submodule and a cloud storage terminal. It integrates the online data generated by the system operation, manages and stores the integrated data, and stores and backs up the online data generated by the system operation to the cloud.
10. A multi-dimensional dynamic visualization higher mathematics teaching system according to claim 9, characterized in that: When backing up and storing data in the cloud storage backup module, the following methods are included: A21: Create a master document based on the corresponding date on the cloud platform; A22: Create classification sub-documents in the main document based on classification information; A23: Compress and encrypt the online data generated by the system operation for backup; A24: Put the online data generated by the system operation into a sub-document.