Large model-based one-stop primary school artificial intelligence teaching system

Abstract

The invention relates to the technical field of artificial intelligence teaching, in particular to a one-stop primary school artificial intelligence teaching system based on a large model, and the system comprises a user management module which is used for managing the identity verification, account registration and login operation of a system user, and tracking the learning record and course progress of the user at the same time; the database management module is used for storing and managing various data generated in the system so as to support learning records and account information of the user and other data operations of the system; the course content management module is used for providing a systematic course learning management function for the user; and the large model management module is used for providing A I technical support for the user in the course content management module so as to simulate and solve problems in reality. The artificial intelligence teaching platform which is suitable for the primary school stage, easy to operate and high in interactivity can be constructed, the defect that education resources are insufficient is overcome, and the learning effect of students is improved.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence teaching technology, and in particular to a one-stop primary school artificial intelligence teaching system based on a large model. Background Art

[0002] With the rapid development of artificial intelligence technology, its application prospects in the field of education have gradually received attention. At present, artificial intelligence has become an important driving force for the development of social science and technology. Many countries and regions have begun to introduce artificial intelligence education in primary schools to help students develop an interest in and understanding of AI from an early age. This not only helps to improve students' scientific and technological literacy, but also cultivates their ability to use AI to solve practical problems in the future society. However, the promotion of AI teaching in primary school education still faces many challenges, especially in terms of resource allocation and teaching implementation, which urgently need technical means to be effectively optimized.

[0003] Among the existing solutions, some schools provide students with learning resources such as electronic textbooks and video tutorials through online platforms to make up for the uneven distribution of educational resources. These platforms usually use universal interface design and standardized content.

[0004] However, most of the existing platforms have not been optimized according to the cognitive level of young children, lacking fun and interactivity, making it difficult for students to maintain long-term learning interest. In addition, teachers' understanding and mastery of artificial intelligence are generally limited. Although the existing teacher training courses can improve teachers' AI teaching level to a certain extent, they are time-consuming and have limited coverage, especially in remote areas, making it difficult to carry out AI teaching in an all-round way. The existing AI curriculum system often pays too much attention to the explanation of theoretical knowledge and ignores the need for students to cultivate problem-solving thinking through practical operations, making it difficult for students to apply theory to actual scenarios. In summary, how to build an artificial intelligence teaching platform suitable for primary school, easy to operate and highly interactive to make up for the lack of educational resources and improve students' learning outcomes has become a difficult problem that needs to be solved in the current field of primary school AI education. Summary of the invention

[0005] This application provides a one-stop primary school artificial intelligence teaching system based on a large model, which can build an artificial intelligence teaching platform suitable for primary school, easy to operate and highly interactive, so as to make up for the lack of educational resources and improve students' learning effects. This application provides the following technical solutions:

[0006] In the first aspect, the present application provides a one-stop primary school artificial intelligence teaching system based on a large model, including:

[0007] The user management module is used to manage system users’ identity authentication, account registration and login operations, and track users’ learning records and course progress;

[0008] Database management module, used to store and manage various data generated in the system to support user learning records, account information and other data operations of the system;

[0009] Course content management module is used to provide users with systematic course learning management functions;

[0010] The large model management module is used to provide users with AI technical support in the course content management module to simulate and solve real-world problems.

[0011] In a specific implementation scheme, the user management module includes a student login submodule, a registration submodule and a teacher login submodule;

[0012] The student login submodule is used for students to log in to the system through their account and password, access course resources and view personal learning records;

[0013] The registration submodule is used for new users to create accounts, set usernames and passwords, and store account information;

[0014] The teacher login submodule is used for teachers to log in to the system through their account and password, manage course content, track student progress and view teaching feedback.

[0015] In a specific implementation scheme, the database management module includes a password modification submodule and a historical learning record submodule;

[0016] The password modification submodule is used to allow users to manage and modify their account passwords;

[0017] The historical learning record submodule is used to provide users with a query function for their learning progress and learning records.

[0018] In a specific implementation scheme, the course content management module includes a course access permission control submodule, a PPT selection submodule, an after-class practice selection submodule, and a PPT animation submodule;

[0019] The course access permission control submodule is used to limit the courses that the user can currently learn according to the user's course unlocking information;

[0020] The PPT selection submodule is responsible for providing theoretical teaching content to users;

[0021] The after-class practice selection submodule is used to provide users with a learning environment for practical operations;

[0022] The PPT animation submodule is used to present course content through animation and situational simulation.

[0023] In a specific implementation scheme, the design architecture of the course content management module includes:

[0024] Design navigation interfaces to provide clear learning paths and guidance, and correct incorrect learning sequences. Help students learn in the correct order through intuitive layouts and clear instructions;

[0025] Design a resource integration interface to integrate courseware and other teaching resources. The resource integration interface displays all resources in a centralized manner for teachers and students to access the required resources.

[0026] In a specific possible implementation scheme, the PPT animation submodule combines the life situations of the self-created digital human to simulate the various difficulties and problems encountered in daily life and demonstrate the process of solving the problems.

[0027] In a specific possible implementation scheme, the large model management module includes an operation interface submodule, a function display interface submodule and an API call submodule;

[0028] The operation interface submodule is used to simulate the operation process of users solving problems;

[0029] The function display interface submodule is used to display the problem and various steps and tools in its solution process;

[0030] The API calling submodule is responsible for integrating AI technology into the system and providing users with intelligent problem analysis and solutions.

[0031] In a specific feasible implementation scheme, Python's Pygame library is used to construct the front-end display interface of the one-stop primary school artificial intelligence teaching system based on the large model;

[0032] Create a basic canvas through Pygame, set up an event listening loop to capture user operations, and design and implement an algorithm framework for the front-end display interface based on Pygame.

[0033] In a specific feasible implementation scheme, C#, Java Spring Boot, Python Django or other back-end development frameworks are used to develop the back-end of the one-stop primary school artificial intelligence teaching system based on the big model.

[0034] In a specific implementation scheme, the database management module uses MySQL, PostgreSQL, Oracle Database or other relational database management systems;

[0035] The API calling submodule supports large model interfaces of Google's TensorFlow, Microsoft's Azure AI, Alibaba Cloud's ModelScope, or other AI platforms.

[0036] In summary, the beneficial effects of this application include at least:

[0037] 1) Through animated learning PPT and life situation simulation, the course content can be vividly presented, and abstract concepts can be intuitive and easy to understand through dynamic demonstration. This method can effectively improve students' participation and understanding ability, enabling them to better apply what they have learned in real situations, thereby enhancing learning effects.

[0038] 2) The after-school practical operation interface designed is implemented using pygame, which provides a simple, easy-to-operate and interesting virtual environment. Students can simulate actual scenes in this environment, perform practical operations, enhance their hands-on ability and application ability, and make the learning process more vivid and interesting.

[0039] 3) The concise function display interface can clearly present various functions, allowing students to understand the power and application value of AI tools at a glance. This design not only improves students' understanding of AI functions, but also lowers the learning threshold for using AI tools, promoting students' interest in technology and active exploration.

[0040] Through the user management module, database management module, course content management module and large model management module, functions such as user identity management, data storage, course content management and AI technology support are realized. Through the carefully designed user interaction interface and dynamic feedback mechanism, the user's learning experience and operation accuracy are improved, while ensuring that the course content is in line with the cognitive characteristics of young children, and enhancing the fun and practicality of learning. The system supports the flexible application of different back-end development frameworks, ensures stability and scalability, and promotes the continuous improvement and optimization of future functions.

[0041] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application and implement it according to the contents of the specification, the following is a detailed description of the preferred embodiments of the present application in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is the software architecture diagram of the one-stop primary school artificial intelligence teaching system based on the big model in the embodiment of this application.

[0043] Figure 2 This is a demonstration interface diagram of the smart mask wearing monitoring class in the embodiment of the present application.

[0044] Figure 3It is a functional display interface diagram of the automatic math exercise corrector in the embodiment of the present application.

[0045] Figure 4 It is a diagram of the operation interface of the automatic math exercise corrector in the embodiment of the present application. DETAILED DESCRIPTION

[0046] The specific implementation methods of the present application are further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present application but are not intended to limit the scope of the present application.

[0047] Reference Figure 1 , is a software architecture diagram of a one-stop primary school artificial intelligence teaching system based on a large model provided by an embodiment of the present application, the system includes:

[0048] 1) User management module, which is used to manage the authentication, account registration and login operations of system users, and track the user's learning records and course progress.

[0049] Specifically, the user management module includes a student login submodule, a registration submodule, and a teacher login submodule. The student login submodule is used for students to log in to the system with their account and password, access course resources, and view personal learning records. The registration submodule is used for new users to create accounts, set usernames and passwords, and store account information. The teacher login submodule is used for teachers to log in to the system with their account and password, manage course content, track student progress, and view teaching feedback.

[0050] 2) Database management module, which is used to store and manage various data generated in the system to support user learning records, account information and other data operations of the system.

[0051] Specifically, the user data stored in this module includes account information, password, learning progress, unlocked course records, etc. Through the database management module, the system can provide users with historical learning record query, password modification and other services. The database management module includes a password modification submodule and a historical learning record submodule, wherein the password modification submodule is used to allow users to manage and change their account passwords. Specifically, when a user logs in to the system, the password modification operation can be performed through this submodule. The user first needs to enter the existing password for identity authentication, and then enter and confirm the new password. The system verifies the format and strength of the new password to ensure that it meets the preset security standards. After completing the password modification, the system will update the user password information stored in the database and feedback the user the information that the password modification is successful. The historical learning record submodule is used to provide users with the query function of their learning progress and learning records. This submodule retrieves the stored user learning information through the database, including completed courses, learning time, learning progress and related grades or evaluations. Users can view their personal learning history through this submodule, and the system automatically updates and saves relevant data according to the user's learning behavior, helping users track their learning progress and reasonably plan subsequent learning content.

[0052] In the implementation, the database management module mainly uses relational database management systems such as MySQL to ensure efficient data storage and query capabilities. In addition, the system can also choose to use other relational database management systems, such as PostgreSQL or Oracle Database, to meet different database requirements. These database systems have good scalability and performance, and can cope with large-scale data storage and query tasks. In addition, the system also supports the use of non-relational databases, such as MongoDB or Cassandra, which are suitable for processing large amounts of unstructured data and have good distributed storage and expansion capabilities, suitable for different types of application scenarios.

[0053] 3) Course content management module, used to provide users with systematic course learning management functions.

[0054] Specifically, this module controls the user's course access rights to ensure that the user unlocks the course in sequence according to the predetermined learning path, and provides two learning methods: theoretical teaching and practical operation, to help users effectively master the course content. This module not only standardizes the user's learning progress, but also provides users with a more flexible learning experience through diversified learning resources. The course content management module includes a course access rights control submodule, a PPT selection submodule, and an after-class practice selection submodule. Among them, the course access rights control submodule is used to limit the courses that the user can currently learn according to the user's course unlocking information, ensuring that the user completes the course content learning in a standardized order. By accessing the user's unlocking information in the database, the system dynamically controls the accessible course list to prevent users from skipping unlocked courses and realizing orderly learning progress management. The PPT selection submodule is responsible for providing theoretical teaching content for users. After unlocking the course, users can select the corresponding PPT courseware for learning through this module. The system supports page-by-page display of courseware, key marking, and zooming in and out, helping users to obtain efficient and clear guidance in the process of theoretical knowledge learning. The after-class practice selection submodule is used to provide users with a learning environment for practical operations. After completing the theoretical course, users can select after-class practical tasks through this module and enter a simulated operation scenario. In this scenario, users can use AI tools and the solutions provided by the system to simulate solving real-life problems, consolidate their theoretical learning content, and improve their practical operation capabilities.

[0055] In the implementation, a navigation interface is designed to provide clear learning paths and guidance to correct incorrect learning sequences. The navigation interface helps students learn in the correct order through intuitive layout and clear instructions. This design reduces students' confusion and frustration caused by improper learning sequence and improves learning efficiency. At the same time, the navigation interface also provides a feedback mechanism to promptly correct students' learning path deviations and ensure the consistency and effectiveness of the learning process. In addition, a resource integration interface is designed to integrate courseware and other teaching resources. Since the resource integration interface displays all resources in a centralized manner, teachers and students can easily access the required resources. This design not only improves the accessibility of resources, but also simplifies the search process, allowing users to quickly find and use the required materials. In addition, through unified resource management, the consistency and quality of resources are ensured, and the teaching effect is improved.

[0056] In addition, as a preferred embodiment, the course content management module also includes a PPT animation submodule, which is used to display the course content through animation and situational simulation. Specifically, this module makes abstract concepts more intuitive and easy to understand by dynamically demonstrating the course content. The PPT animation module combines the life situations of self-created digital people, simulates the various difficulties and problems encountered in daily life, and shows the process of solving problems. This situational simulation is close to the students' actual experience and can significantly improve their participation and understanding ability. In the design of teaching content, the PPT animation module adopts an animated teaching method and creates a virtual digital person as a guide. Through the life experience of the virtual digital person and the process of solving difficulties, the teaching content can be unfolded coherently and vividly. Students can not only perceive problems through the situation of the virtual digital person, but also use the knowledge they have learned to solve them in the situation. Animation teaching can more effectively attract the attention of primary school students and help them better understand and master the course content.

[0057] It should be noted that the course system design in the course content management module starts with the music smart player class, using voice recognition technology to allow students to understand how AI recognizes and understands the world through sound while enjoying music. Then, through the classical poetry audio library class, students can experience the integration of traditional culture and modern technology through voice synthesis technology.

[0058] Next, we will take the study of one of the courses as an example to illustrate:

[0059] Reference Figure 2 and Figure 3 In the four lessons of the instant image translator, students gradually learn how to use AI tools to solve problems, including extracting text from pictures, instant translation, converting text to speech, and finally integrating these skills to complete the whole process experience from image to speech output. Then, through the fast calculation automatic correction system lesson, students learn how to refine complex correction logic into rules and hand them over to AI for execution, so as to master the principle of automatic correction of four arithmetic problems. In the smart mask wearing monitoring lesson, students simulate the application of AI in the field of public health by participating in a simplified version of the model training activities, understand the basic principles of machine learning, and stimulate interest in technology.

[0060] Each class follows the principle of "learning first, then practicing". During the learning stage, students can use animated and interesting PPTs to delve into specific situations and understand the ideas of solving problems. In the after-class practice module, students use simple operations such as dragging, clicking, compositing, and puzzle programming through the operation interface to simulate and complete the practice of what they have learned, and further develop their thinking ability.

[0061] For example, the user first clicks to study the interesting PPT of the seventh lesson. After studying the interesting PPT of the seventh lesson, click to enter the after-class practical homework of the seventh lesson. The after-class practical module of the seventh lesson simulates the workflow of the automatic grader of math exercises, helping children to summarize the logic behind automatic graders and understand the essence of machine automation. In the operation interface, children can complete the flowchart with puzzles of various shapes by dragging and dropping. After completing the logic, they can get an automatic grader. The operation interface is as follows: Figure 4 shown.

[0062] 4) Large model management module, which is used to provide AI technical support to users in the after-class practice sub-module to simulate and solve real-life problems.

[0063] Specifically, the large model management module includes an operation interface submodule, a function display interface submodule, and an API call submodule, wherein the operation interface submodule is used to simulate the user's operation process of solving problems. Through the written interface program, users can select and use the tools provided by the system in the operation interface, and simulate the actual operation according to the predetermined steps. Based on the principle of interactive design, the interface provides an intuitive and convenient operation experience to ensure that users can effectively understand the problem-solving process during the operation. The function display interface submodule is used to display the various steps and tools in the problem and its solution process. Through this interface, users can view the specific content of the problem and the system's preset solution tools, and gradually complete the problem solving through interaction. The deep integration of the large model platform and this module ensures that users can call AI tools during the operation process to achieve intelligent problem solving. The API call submodule is responsible for integrating AI technology into the system to provide users with intelligent problem analysis and solutions. The system implements intelligent analysis of user input problems and generates corresponding solutions by calling the API of the large model platform. The return result of the API call is processed and displayed to the user. This submodule not only supports the existing large model interface, but also allows other mature and stable AI platforms such as Google's TensorFlow, Microsoft's Azure AI, or Alibaba Cloud's ModelScope to be replaced according to technological development to ensure the technological advancement and stability of the system.

[0064] In the interface design, the system takes blue as the core to create a harmonious and technological visual experience. Following the "four-color principle", each interface has no more than four colors to ensure visual purity and unity. In addition, the system focuses on natural color transitions, avoids high-intensity contrast, and improves visual comfort. The font is "Microsoft Yahei" to ensure clarity, readability and modernity. The icon design is intuitive and highly consistent with the function. Through subtle color changes and detail processing, it enhances the user's intuitive understanding.

[0065] At the same time, for primary school students, the interface layout focuses on intuitiveness and simplicity. Adopting the design concept of "simple but not simple", the layout design is refined, and only key elements are retained to avoid information overload. Large fonts and intuitive icons are used instead of lengthy text descriptions to ensure that information is clear at a glance. Through reasonable spatial layout and color distinction, the user's visual flow is guided to focus on the core functional area. Adhering to the principle of "less is more", blank space is used to enhance the breathing sense of the interface and improve the comfort of use.

[0066] In addition, as a preferred method, visual hints and shape matching logic are incorporated into the user interaction design. Soft shadows prompt the user's operation position, reduce cognitive barriers, and improve the accuracy of operation. Shape matching design ensures the correct embedding of puzzle pieces, exercises the user's spatial thinking ability, and provides positive feedback.

[0067] In the implementation, Python's Pygame library is used to build the front-end display interface of the system. Specifically, a basic canvas is created through Pygame, and an event listening loop is set to capture user operations, such as click and drag events. In this way, an algorithm framework is designed and implemented. This framework is based on Pygame, which can simplify the process of creating a highly interactive UI and efficiently implement interface logic. This framework ensures the seamless integration of icons and events, providing users with an intuitive operating environment. The back-end of the system is developed in C# to ensure the stability and scalability of the system and support future functional expansion and maintenance. In future development, the system can also consider using other back-end development frameworks, such as Java Spring Boot or PythonDjango, which also have efficient data processing capabilities and good system integration features, and can support more complex service requirements.

[0068] In addition, as preferably, since pygame does not directly provide rich interface controls, such as buttons, etc., this brings challenges to the design of the user interface. To this end, the present application abstracts and encapsulates common interface elements and develops a flexible and feature-rich Button class for building an interactive interface. Specifically, through a custom drawing method, the appearance style of the button can be flexibly set. The button can automatically switch the display effect according to the current state (such as activation, disabling, mouse hovering, etc.), making the interface more vivid and intuitive. The response logic of multiple states is implemented for the Button class, including mouse hovering, click events, etc. When the user operates the mouse, the button can make timely feedback according to different interactive states, improving the user's operating experience. The event handling mechanism is introduced in the Button class, which ensures the accuracy and sensitivity of the interface operation by monitoring and responding to the user's input events. By setting the callback function, the developer can associate the specific logical operation with the button click event to achieve flexible expansion in function. In order to adapt to different application scenarios, the Button class supports multiple attribute configurations, such as activation state, disabled state, and callback function, etc. When the user instantiates the Button object, the attribute can be flexibly configured according to specific needs, thereby simplifying the process of subsequent interface development. Through the above encapsulation work, this application significantly reduces the writing of repeated code in development. Developers only need to instantiate the Button class and make slight adjustments according to actual needs to quickly build a fully functional interface, which greatly improves development efficiency. Especially when developing after-class practical operation interfaces and function display interfaces related to course content, this encapsulated application makes interface interaction smoother, enhances the fun and interactivity of the system, and thus improves students' learning experience.

[0069] In implementation, the large model platform API call module written in Python can successfully acquire and process data, but when these data are passed to the function display interface developed in C#, garbled characters appear, resulting in data display errors. After testing, it was found that the root cause of the problem lies in the inconsistency of character encoding during data transmission. Python uses the character encoding related to the operating system environment by default, and in the C# environment, if the encoding method is not explicitly specified, different encoding formats may be used to process strings, resulting in encoding matching problems during transmission. Based on this, this application proposes the following solutions to the character encoding problem:

[0070] Specifically, the widely applicable UTF-8 encoding format was selected. UTF-8 is not only consistent with the default encoding of the large model platform API, but also can handle characters in multiple languages, which helps to avoid encoding conflicts. In the Python environment, all string operations involving data transmission are specified to use UTF-8 encoding. This includes reading, processing and transmitting the data returned by the API to ensure that the encoding of the data remains consistent before it is transmitted to the C# environment. In the development of the C# function display interface, it is clearly specified that all data receiving, reading and processing links use UTF-8 encoding. This ensures that the data transmitted from Python can be correctly parsed and displayed in the C# environment. After the encoding settings are completed on both ends, tests are performed to ensure that there will be no inconsistent encoding of the data in the transmission link. By simulating various data input scenarios and verifying the integrity of the data from the Python API module to the C# interface, the garbled problem was successfully solved. Through the above measures, this application significantly improves the compatibility in cross-language and cross-platform environments, ensures the uniformity of encoding during data transmission, and solves the garbled problem caused by inconsistent character encoding. This technical improvement not only restored the correct display of data, but also enhanced the system stability and user experience, and accumulated valuable experience for further optimizing cross-platform development.

[0071] In practice, in the operation interface of the present application, in order to enable users to have a better experience when interacting with the interface, the pygame library is used to develop the operation interface, allowing users to interact with icons in the interface by clicking or dragging. However, since pygame only provides basic event processing methods, it is necessary to distinguish between the user's drag operation and the click operation.

[0072] Specifically, in a drag operation, the mouse will move between clicking and releasing, while in a click operation, the mouse will not move during this process. During the event processing process, two state variables are set for each icon: the drag state and the click state. When a user clicks an icon, the system sets both the drag state and the click state of the icon to True, indicating that the user may be performing a drag or click operation. After the mouse is clicked, it is immediately determined whether the mouse has moved. If the mouse movement is detected between the mouse click and the release, it can be determined that the user is performing a drag operation. At this time, the click state of the icon is set to False, that is, the possibility of the click operation is excluded, and the dragging process is continued to be tracked. When the mouse is released, the present invention gives priority to judging the click state. If the click state is still True and is not set to False by the mouse movement detection, it means that the user has completed the click operation, and the system will respond to the click event; conversely, if the click state has been set to False, it means that the user has completed the drag operation, and the system will process the drag event. In order to implement the above judgment logic, the present application adjusts the if-elif-else structure in the event loop. First, it is prioritized to detect whether the mouse click occurs above the icon area, and then the click state and drag state are dynamically adjusted according to the mouse movement to ensure that the user's intention can be accurately identified when the mouse is released. Through this flexible processing method, the application can accurately distinguish the user's drag and click operations in the operation interface, thereby improving the interface's responsiveness to user input. This method significantly improves the accuracy of user interaction, ensures that the system can correctly execute the user's intention, and further improves the user experience.

[0073] In summary, the technical solution of this application relates to a one-stop primary school artificial intelligence teaching system based on a large model, which aims to build an AI education platform suitable for the primary school stage, easy to operate and highly interactive, so as to solve the current technical problems in primary school AI education, such as insufficient resources, lack of fun and interactivity in learning experience, and limited teacher training. The system realizes functions such as user identity management, data storage, course content management and AI technical support through components such as user management module, database management module, course content management module and large model management module. Through a carefully designed user interaction interface and dynamic feedback mechanism, the user's learning experience and operation accuracy are improved, while ensuring that the course content is in line with the cognitive characteristics of young children, and enhancing the fun and practicality of learning. The system supports the flexible application of different back-end development frameworks, ensures stability and scalability, and promotes the continuous improvement and optimization of future functions.

[0074] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0075] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A one-stop primary school artificial intelligence teaching system based on a large model, characterized by: include: The user management module is used to manage system users’ identity authentication, account registration and login operations, and track users’ learning records and course progress; Database management module, used to store and manage various data generated in the system to support user learning records, account information and other data operations of the system; Course content management module is used to provide users with systematic course learning management functions; The large model management module is used to provide users with AI technical support in the course content management module to simulate and solve real-world problems.

2. The one-stop primary school artificial intelligence teaching system based on a large model according to claim 1 is characterized in that: The user management module includes a student login submodule, a registration submodule and a teacher login submodule; The student login submodule is used for students to log in to the system through their account and password, access course resources and view personal learning records; The registration submodule is used for new users to create accounts, set usernames and passwords, and store account information; The teacher login submodule is used for teachers to log in to the system through their account and password, manage course content, track student progress and view teaching feedback.

3. The one-stop primary school artificial intelligence teaching system based on a large model according to claim 1 is characterized in that: The database management module includes a password modification submodule and a historical learning record submodule; The password modification submodule is used to allow users to manage and modify their account passwords; The historical learning record submodule is used to provide users with a query function for their learning progress and learning records.

4. The one-stop primary school artificial intelligence teaching system based on a large model according to claim 1 is characterized in that: The course content management module includes a course access permission control submodule, a PPT selection submodule, an after-class practice selection submodule and a PPT animation submodule; The course access permission control submodule is used to limit the courses that the user can currently learn according to the user's course unlocking information; The PPT selection submodule is responsible for providing theoretical teaching content to users; The after-class practice selection submodule is used to provide users with a learning environment for practical operations; The PPT animation submodule is used to present course content through animation and situational simulation.

5. The one-stop primary school artificial intelligence teaching system based on a large model according to claim 4 is characterized in that: The design architecture of the course content management module includes: Design navigation interfaces to provide clear learning paths and guidance, and correct incorrect learning sequences. Help students learn in the correct order through intuitive layouts and clear instructions; Design a resource integration interface to integrate courseware and other teaching resources. The resource integration interface displays all resources in a centralized manner for teachers and students to access the required resources.

6. The one-stop primary school artificial intelligence teaching system based on a large model according to claim 4 is characterized in that: The PPT animation submodule combines the life situations of the self-created digital human to simulate the various difficulties and problems encountered in daily life and demonstrate the process of solving the problems.

7. The one-stop primary school artificial intelligence teaching system based on a large model according to claim 1 is characterized in that: The large model management module includes an operation interface submodule, a function display interface submodule and an API calling submodule; The operation interface submodule is used to simulate the operation process of users solving problems; The function display interface submodule is used to display the problem and various steps and tools in its solution process; The API calling submodule is responsible for integrating AI technology into the system and providing users with intelligent problem analysis and solutions.

8. The one-stop primary school artificial intelligence teaching system based on a large model according to claim 1 is characterized in that: The Python Pygame library is used to construct the front-end display interface of the one-stop primary school artificial intelligence teaching system based on the large model; Create a basic canvas through Pygame, set up an event listening loop to capture user operations, and design and implement an algorithm framework for the front-end display interface based on Pygame.

9. The one-stop primary school artificial intelligence teaching system based on a large model according to claim 1 is characterized in that: Use C#, Java Spring Boot, Python Django or other back-end development frameworks to develop the back-end of the one-stop primary school artificial intelligence teaching system based on the big model.

10. The one-stop primary school artificial intelligence teaching system based on a large model according to claim 7 is characterized in that: The database management module adopts MySQL, PostgreSQL, Oracle Database or other relational database management systems; The API calling submodule supports large model interfaces of Google's TensorFlow, Microsoft's Azure AI, Alibaba Cloud's ModelScope, or other AI platforms.

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