Personalized learning path planning system based on AI and big data analysis

Abstract

The invention discloses a personalized learning path planning system based on AI and big data analysis, and the system comprises a cloud server, the cloud server is provided with a planning system, the cloud server is also connected with a knowledge database and a dress-up database, the knowledge database stores learning materials and course content, and the course content is stored in the dress-up database. The planning system generates a personalized learning path according to the demands and levels of students, and the dress-up database stores dress-up accessories for the AI robot to simulate figures. According to the system, learning and personalized dress-up are combined, students are motivated to learn actively through a mechanism of point reward and exchange dress-up, the students learn step by step according to a personalized learning path, and corresponding points can be obtained through knowledge points of each stage for exchange dress-up, so that the learning efficiency is improved. Through the design, the interestingness and attraction of learning are enhanced, the learning motivation and participation degree of students are also improved, and therefore the learning effect is promoted to be improved.

Description

Technical Field

[0001] The present invention relates to the field of educational technology, and in particular to a personalized learning path planning system based on AI and big data analysis. Background Art

[0002] The learning path planning system is usually aimed at the needs of students or learners, aiming to develop a learning route for them based on their learning goals, interests and current levels. When primary school students are studying, it is difficult to improve their autonomous learning because their attention is not focused and sustained enough, and the learning content is too boring and tedious. In addition, the learning path planning in the existing learning path planning software is rigid and inflexible, and it is impossible to carry out personalized learning path planning according to the specific situation of each student. Therefore, a personalized learning path planning system based on AI and big data analysis is designed. Summary of the invention

[0003] The purpose of the present invention is to provide a personalized learning path planning system based on AI and big data analysis to solve the problems raised in the above background technology.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] A personalized learning path planning system based on AI and big data analysis, including

[0006] A cloud server, wherein the cloud server is deployed with a planning system, and the cloud server is also connected to a knowledge database and a dressing database, wherein the knowledge database stores learning materials and course content, the planning system generates a personalized learning path according to the needs and levels of students, and the dressing database stores dressing accessories that can be used by the AI ​​robot to simulate a character;

[0007] A learning terminal, wherein the learning terminal is interconnected with the planning system in the cloud server via a network, and the learning terminal is further provided with an AI simulation module, wherein the AI ​​simulation module simulates a character image;

[0008] The planning system consists of an integration module, an analysis module, a scoring module and a user information module.

[0009] Preferably, the points module includes a points management unit and an exchange function unit, the points management unit records the students' learning achievements and calculates the points, and the exchange function unit exchanges the students' points for costumes.

[0010] Preferably, the analysis module includes a data collection unit and a data analysis unit, the data collection unit collects students' learning behavior data and preference information, and the data analysis unit analyzes students' learning preferences and dressing preferences.

[0011] Preferably, the scoring module includes a learning evaluation unit, which scores and rewards students' learning performance.

[0012] Preferably, the user information module includes a user information database, a learning history database and an interest and hobby database. The user information database stores students' personal information, including name, age, gender and points data. The learning history database records students' learning history and learning behavior. The interest and hobby database records students' interests, hobbies and preferences.

[0013] Preferably, the knowledge database is composed of a learning material storage unit and a learning path generation unit, wherein the learning material storage unit stores learning materials and course content, and the learning path generation unit generates a personalized learning path according to the needs and levels of students.

[0014] Preferably, the dressing database consists of an accessories storage unit and a dressing selection unit, the accessories storage unit stores accessories that can be used by the AI ​​robot to simulate character dressing, and the dressing selection unit provides corresponding dressing options based on the interests, hobbies and preferences of students recorded in the interest database.

[0015] Preferably, the AI ​​simulation module consists of a simulated character image generation unit, a guided learning unit and a learning achievement display unit, the simulated character image generation unit generates a simulated character image, the guided learning unit guides students to learn according to path planning, and the learning achievement display unit displays students' learning achievements.

[0016] Compared with the prior art, the present invention has the following beneficial effects:

[0017] 1. The system of the present invention combines learning with personalized dressing, and motivates students to actively learn through the mechanism of point rewards and redemption of dressing. Students learn step by step according to the personalized learning path, and can obtain corresponding points for each stage of knowledge points passed, which can be used to redeem dressing. Such a design not only enhances the fun and attractiveness of learning, but also improves students' learning motivation and participation, thereby promoting the improvement of learning effect;

[0018] 2. The scoring system configured in the learning terminal of the present invention integrates the learning process and evaluation throughout, bringing multiple benefits to students. Through the scoring system, students can receive scores after each learning of a knowledge point, obtain corresponding badges and dress up as AI characters. This incentive mechanism not only increases the fun of learning, but also encourages students to continue to work hard to improve the quality of learning. The analysis function of the scoring system helps to evaluate students' learning level and knowledge mastery, identify problems in a timely manner and provide targeted feedback and guidance.

[0019] 3. The present invention combines personal information in the user information database, and the system can generate targeted learning paths based on the age and gender characteristics of students. By using the learning behavior recorded in the learning history database, the system can understand the students' learning habits and preferences, thereby adjusting the learning content and methods and improving learning efficiency. The data in the interest and hobby database can help the system better understand students' interests, recommend relevant learning materials and courses to them, and increase the fun and attractiveness of learning. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is a schematic diagram of the system structure of a personalized learning path planning system based on AI and big data analysis in the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] like Figure 1 As shown, the present invention provides a technical solution:

[0023] A personalized learning path planning system based on AI and big data analysis includes a cloud server, a planning system is deployed on the cloud server, and the cloud server is also connected to a knowledge database and a dressing database, the knowledge database stores learning materials and course content, the planning system generates personalized learning paths according to students' needs and levels, and the dressing database stores dressing accessories that can be used by AI robots to simulate characters; a learning terminal, the learning terminal is interconnected with the planning system in the cloud server through a network, and the learning terminal is also provided with an AI simulation module, and the AI ​​simulation module simulates the character image; the planning system is composed of a scoring module, an analysis module, a scoring module and a user information module; the AI ​​simulation module generates a single character by simulating the character image The AI ​​robot simulates the character image generation unit to generate a simulated character image, the guided learning unit guides students to learn according to the path planning, and the learning achievement display unit displays the students' learning achievements; the knowledge database is composed of a learning material storage unit and a learning path generation unit. The learning material storage unit stores learning materials and course content, and the learning path generation unit generates personalized learning paths according to the needs and levels of students; the dressing database is composed of an accessories storage unit and a dressing selection unit. The accessories storage unit stores accessories that can be used by the AI ​​robot to simulate the character dress, and the dressing selection unit provides corresponding dressing options based on the interests and preferences of students recorded in the interest database;

[0024] Specifically, the system configures an AI simulation module in the learning terminal, and the AI ​​simulation module can simulate an AI character, wherein the knowledge database stores learning materials, and the dressing database stores various accessories that can be used to dress up the AI ​​character, including various types of clothes, shoes, and headwear. For example, the types of toys that girls like and the types of mechas that boys like. Students learn step by step according to the path planned in the learning knowledge base. Every time they pass a stage of knowledge points, they can obtain corresponding points. By accumulating points, they can exchange for the costumes stored in the dressing database to change their own AI characters.

[0025] In this embodiment, the analysis module includes a data collection unit and a data analysis unit. The data collection unit collects students' learning behavior data and preference information, and the data analysis unit analyzes students' learning preferences and dressing preferences.

[0026] Specifically, the learning terminal is configured with an analysis module, which collects, organizes and analyzes the student's dressing preferences based on big data, and then links the knowledge points that must be mastered with the type of dressing the student likes, and sets up a separate exchange system. After the student masters the knowledge points, he can directly exchange them for the corresponding dressing.

[0027] In this embodiment, the points module includes a points management unit and a redemption function unit. The points management unit records the students' learning achievements and calculates the points. The redemption function unit redeems the students' points for costumes. The scoring module includes a learning evaluation unit. The learning evaluation unit scores and rewards the students' learning achievements.

[0028] Specifically, the learning terminal is equipped with a scoring system to facilitate scoring after each learning of the corresponding knowledge point. The score can be obtained with a corresponding badge, which can also be worn on the AI ​​character. At the same time, the scoring module can also analyze the student's learning quality and the mastery of the knowledge point. If the score is not up to standard, the corresponding points will not be obtained, and the knowledge point will be displayed as failed, which increases the difficulty for students to obtain points.

[0029] In this embodiment, the user information module includes a user information database, a learning history database and a hobby database. The user information database stores the student's personal information, including name, age, gender and score data. The learning history database records the student's learning history and learning behavior. The hobby database records the student's hobbies and preferences.

[0030] Specifically, combined with the personal information in the user information database, the system can generate targeted learning paths based on the students' age and gender characteristics. By using the learning behavior recorded in the learning history database, the system can understand the students' learning habits and preferences, thereby adjusting the learning content and methods and improving learning efficiency. The data in the interest and hobby database can help the system better understand students' interests, recommend relevant learning materials and courses to them, and increase the fun and attractiveness of learning.

[0031] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0032] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A personalized learning path planning system based on AI and big data analysis, characterized by: include A cloud server, wherein the cloud server is deployed with a planning system, and the cloud server is also connected to a knowledge database and a dressing database, wherein the knowledge database stores learning materials and course content, the planning system generates a personalized learning path according to the needs and levels of students, and the dressing database stores dressing accessories that can be used by the AI ​​robot to simulate a character; A learning terminal, wherein the learning terminal is interconnected with the planning system in the cloud server via a network, and the learning terminal is further provided with an AI simulation module, wherein the AI ​​simulation module simulates a character image; The planning system consists of an integration module, an analysis module, a scoring module and a user information module.

2. The personalized learning path planning system based on AI and big data analysis according to claim 1, characterized in that: The points module includes a points management unit and an exchange function unit. The points management unit records the students' learning achievements and calculates the points. The exchange function unit exchanges the students' points for costumes.

3. The personalized learning path planning system based on AI and big data analysis according to claim 1, characterized in that: The analysis module includes a data collection unit and a data analysis unit. The data collection unit collects students' learning behavior data and preference information, and the data analysis unit analyzes students' learning preferences and dressing preferences.

4. The personalized learning path planning system based on AI and big data analysis according to claim 1, characterized in that: The scoring module includes a learning evaluation unit, which scores and rewards students' learning performance.

5. The personalized learning path planning system based on AI and big data analysis according to claim 1, characterized in that: The user information module includes a user information database, a learning history database and an interest and hobby database. The user information database stores students' personal information, including name, age, gender and points data. The learning history database records students' learning history and learning behavior. The interest and hobby database records students' interests, hobbies and preferences.

6. The personalized learning path planning system based on AI and big data analysis according to claim 1, characterized in that: The knowledge database is composed of a learning material storage unit and a learning path generation unit. The learning material storage unit stores learning materials and course content, and the learning path generation unit generates a personalized learning path according to the needs and levels of students.

7. The personalized learning path planning system based on AI and big data analysis according to claim 1, characterized in that: The dressing database consists of an accessories storage unit and a dressing selection unit. The accessories storage unit stores accessories that can be used by the AI ​​robot to simulate character dressing. The dressing selection unit provides corresponding dressing options based on the interests, hobbies and preferences of students recorded in the interest database.

8. The personalized learning path planning system based on AI and big data analysis according to claim 1, characterized in that: The AI ​​simulation module consists of a simulated character image generation unit, a guided learning unit and a learning achievement display unit. The simulated character image generation unit generates a simulated character image, the guided learning unit guides students to learn according to path planning, and the learning achievement display unit displays students' learning achievements.

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