Structured intelligent question bank generation system based on knowledge points

Abstract

The invention discloses a structured intelligent question bank generation system based on knowledge points, and relates to the technical field of computer analysis processing. The system comprises an online self-learning tutorial platform which is used for providing learning contents covering all subjects of a course outline; the question bank generation module is used for generating a personalized question bank according to the learning progress and the ability level of the student; and the diagnosis module is used for providing accurate learning diagnosis and helping the students to identify learning weaknesses. According to the method, firstly, the user is guided to register and perform learning diagnosis, the knowledge point mastering condition is evaluated through a preset problem, then the system analyzes learning data of the user by using a data mining technology, mastered and weak knowledge points are identified, future learning requirements of the user are predicted in combination with a machine learning algorithm, and the learning requirement of the user is predicted according to the analysis results. The system dynamically generates a personalized question bank, and progressively presents learning contents according to knowledge points, so that students are ensured to progressively learn and grasp knowledge.

Description

Technical Field

[0001] The present invention relates to the technical field of computer analysis and processing, and in particular to a structured intelligent question bank generation system based on knowledge points. Background Art

[0002] In traditional online education, learning platforms typically provide a wealth of learning materials and exercises for students to study independently. However, these resources often lack specificity and personalization, making it difficult for students to find the right content amidst the vast amount of information, resulting in low learning efficiency. Furthermore, traditional learning platforms often neglect interaction between students and between students and teachers, limiting the potential for the development of learning communities.

[0003] Traditional online learning platforms have significant limitations. Their resources are generalized: the exercises and learning materials provided lack specificity and cannot be personalized according to students' specific circumstances; there is insufficient interactivity: communication between students and teachers, and between students, is limited, and there is a lack of an effective communication platform; information updates lag: information related to university entrance exams is not updated in a timely manner, making it difficult for students to obtain the latest exam information.

[0004] For this purpose, a structured intelligent question bank generation system based on knowledge points is proposed. Summary of the Invention

[0005] The purpose of the present invention is to solve the problems raised in the above background technology, and to provide a structured intelligent question bank generation system based on knowledge points.

[0006] In order to achieve the above-mentioned purpose, the present invention specifically adopts the following technical solutions: A structured intelligent question bank generation system based on knowledge points, including: An online self-learning tutorial platform that provides learning content covering all subjects in the syllabus; Question bank generation module, used to generate personalized question banks based on students' learning progress and ability levels; Diagnostic module, used to provide accurate learning diagnosis and help students identify learning weaknesses; Full subject support module, used to ensure that the system covers knowledge points of all subjects; Infinite holographic learning scenario module, used to provide multiple learning scenarios to meet the learning needs of different students; Communication platform module to enable students to prepare for the exams without any hassle.

[0007] Furthermore, the question bank generation module includes: Data mining is used to analyze students’ learning data and identify their mastery of knowledge points; Machine learning algorithms are used to predict students' learning needs and generate personalized question banks.

[0008] Furthermore, the diagnosis module can conduct a preliminary diagnosis of students through a series of preset questions, evaluate students' mastery of knowledge points, and provide feedback.

[0009] Furthermore, the full subject support module includes: Database, which stores knowledge points and related questions of all subjects; The retrieval system is used to retrieve and provide relevant topics based on students' learning progress.

[0010] Furthermore, the infinite holographic learning scenario module can provide a variety of learning scenarios, including but not limited to simulated exams, interactive learning, video tutorials, etc., and can adjust the learning scenarios according to students' learning habits and preferences.

[0011] Furthermore, the communication platform module includes: Communication forums for communication between students and between students and teachers; Information publishing system, used to publish information related to college entrance examinations.

[0012] The method for generating a structured intelligent question bank system based on knowledge points is characterized by comprising the following specific steps: Step S1: User registration and login; Step S2: Learning diagnosis, assessing students’ mastery of knowledge points through pre-set questions; Step S3: Generate a personalized question bank based on the diagnosis results; Step S4: Learning and practicing, students learn and practice through the question bank provided by the system; Step S5: Feedback and adjustment, the system provides feedback based on students' learning performance and adjusts the question bank.

[0013] The step S3 comprises the following steps: Step S31: Analyze students' learning data using data mining technology; Step S32: Use machine learning algorithms to predict students' learning needs.

[0014] The step S5 comprises: Step S51: providing real-time records of students’ learning progress and grades; Step S52: Adjust the question bank content based on the student's learning performance The beneficial effects of the present invention are as follows: The system uses structured knowledge points and artificial intelligence technology to provide students with a personalized and efficient learning experience. It combines user learning diagnostic information and behavioral data to dynamically generate a question bank tailored to students' learning needs and adjusts content in real time based on student performance. The system first guides users to register and conduct a learning diagnosis, using pre-set questions to assess their knowledge mastery. The system then uses data mining technology to analyze the user's learning data, identifying key knowledge points they have mastered and those they are weak at. It also uses machine learning algorithms to predict the user's future learning needs. Based on these analysis results, the system dynamically generates a personalized question bank and presents learning content in a progressive manner by key knowledge point, ensuring that students learn and master knowledge step by step. Students learn and practice content in the system. After completing a question, the system provides detailed feedback and explanations based on the student's answers, helping them understand the reasons for their mistakes and deepen their learning. The system also records students' learning progress and grades, and dynamically adjusts the question bank content based on the user's learning performance, ensuring that the learning materials remain relevant and effective. The system provides a communication forum and information release system to promote communication between students and between students and teachers, and form a positive learning community atmosphere. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic diagram of the three-dimensional structure of the present invention; Figure 2 Schematic diagram of the composition of the question bank generation module of the present invention; Figure 3 It is a schematic diagram of the composition of the full subject support module of the present invention; Figure 4 It is a schematic diagram of the composition of the communication platform module of the present invention; Figure 5 It is a flow chart of the system of the present invention. DETAILED DESCRIPTION

[0016] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of 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. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0017] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but rather merely represents selected embodiments of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort are intended to fall within the scope of protection of the present invention.

[0018] It should be noted that similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings. In addition, the terms "first," "second," etc. are used only to distinguish the descriptions and are not to be understood as indicating or implying relative importance.

[0019] In the description of the embodiments of the present invention, it should be noted that the terms "inside", "outside", "upper", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, or are the orientations or positional relationships in which the inventive product is usually placed when in use. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, they cannot be understood as limitations on the present invention.

[0020] like Figures 1 to 5 As shown in the figure, the structured intelligent question bank generation system based on knowledge points includes: An online self-learning tutorial platform that provides learning content covering all subjects in the syllabus; The platform is a web-based interactive learning environment that provides learning content covering all subjects from P1 to F6 of the Hong Kong Curriculum. It allows students to access a variety of learning materials such as video tutorials, text materials, interactive exercises, etc., and supports online assessment and feedback.

[0021] Question bank generation module, used to generate personalized question banks based on students' learning progress and ability levels; This module uses data mining technology and machine learning algorithms to analyze students' learning data, identify students' mastery of knowledge points, and generate personalized question banks based on students' learning progress and ability levels.

[0022] Diagnostic module, used to provide accurate learning diagnosis and help students identify learning weaknesses; The diagnostic module uses a series of pre-set questions to conduct a preliminary diagnosis of students, assess their knowledge of key points, and provide feedback. These diagnostic results are used to adjust the study plan and question bank content.

[0023] Full subject support module, used to ensure that the system covers knowledge points of all subjects; This module includes a database that stores knowledge points and related questions for all subjects, and a retrieval system that is used to retrieve and provide relevant questions based on students' learning progress.

[0024] Infinite holographic learning scenario module, used to provide multiple learning scenarios to meet the learning needs of different students; The module provides a variety of learning scenarios, including mock exams, interactive learning, video tutorials, etc., to adapt to the learning habits and preferences of different students.

[0025] Communication platform module to enable students to prepare for the exam without any hassle; The communication platform module includes a forum and an information publishing system for communication between students and between students and teachers, as well as publishing information related to university entrance examinations.

[0026] More specifically, the online self-study tutorial platform, as the core module, is tightly integrated with the question bank generation module, diagnosis module, full subject support module, infinite holographic learning scenario module and communication platform module to provide a comprehensive learning experience. The question bank generation module is connected to the online self-study tutorial platform to generate personalized learning materials and exercises based on the data collected by the platform. At the same time, it is also connected to the diagnosis module to ensure that the generated question bank can provide intensive training for students' weaknesses. The diagnosis module is connected to the online self-study tutorial platform and the question bank generation module to provide feedback on students' learning status in order to generate more targeted learning materials and exercises. The full subject support module provides content support for the online self-study tutorial platform and the question bank generation module to ensure the comprehensiveness and accuracy of learning materials and exercises. The infinite holographic learning scenario module is connected to the online self-study tutorial platform to adjust the learning scenario according to students' learning habits and preferences to enhance the learning experience. The infinite holographic learning scenario module is connected to the online self-study tutorial platform to adjust the learning scenario according to students' learning habits and preferences to enhance the learning experience.

[0027] The question bank generation module includes: Data mining is used to analyze students’ learning data and identify their mastery of knowledge points; Machine learning algorithms are used to predict students' learning needs and generate personalized question banks.

[0028] More specifically, the question bank generation module comprehensively uses data mining and machine learning algorithms to identify students' mastery of knowledge points and predict their learning needs by analyzing their learning data. The module first extracts students' learning behavior patterns and knowledge point mastery through data mining technology, and then uses machine learning algorithms to predict students' future learning needs based on this information. Finally, based on the prediction results, questions suitable for students' current learning stage are screened or generated from the huge question bank to form a personalized question bank to improve learning efficiency and effectiveness. This process is dynamic. As students' learning progress is updated, the question bank will also be adjusted accordingly to ensure that the learning materials that best meet students' current needs are always provided.

[0029] The diagnostic module can conduct preliminary diagnosis of students through a series of preset questions, evaluate students' mastery of knowledge points, and provide feedback.

[0030] Full subject support modules include: Database, which stores knowledge points and related questions of all subjects; The retrieval system is used to retrieve and provide relevant topics based on students' learning progress.

[0031] More specifically, the Full Subject Support Module provides comprehensive learning support for students through the collaborative work of a database and retrieval system. The database, as a knowledge base, stores a rich collection of knowledge points and related questions, while the retrieval system retrieves appropriate questions from the database based on the student's learning progress and needs. This design ensures that students receive learning materials tailored to their learning stage while also ensuring comprehensive and up-to-date learning content. Through this mechanism, the Full Subject Support Module provides personalized learning resources for students across different subjects and at different learning stages, helping them to more effectively master knowledge points and improve learning efficiency.

[0032] The infinite holographic learning scenario module can provide a variety of learning scenarios, including but not limited to mock exams, interactive learning, video tutorials, etc., and can adjust the learning scenarios according to students' learning habits and preferences.

[0033] The communication platform modules include: Communication forums for communication between students and between students and teachers; Information publishing system, used to publish information related to college entrance examinations.

[0034] More specifically, the communication platform module promotes communication and information sharing among students, teachers and other users through the combination of communication forums and information release systems. The communication forum allows users to have open discussions on learning-related topics, while the information release system provides an official information dissemination channel to ensure that students can obtain accurate and timely exam-related information. This design not only enhances the interactivity of the learning community, but also improves the efficiency and accuracy of information transmission. Students can ask questions and share experiences on the forum. At the same time, teachers and administrators can convey important educational information in a timely manner through the information release system to help students better prepare for college entrance examinations. In this way, the communication platform module becomes an important bridge connecting students, teachers and educational institutions.

[0035] The method for generating a structured intelligent question bank system based on knowledge points is characterized by comprising the following specific steps: Step S1: User registration and login; Step S2: Learning diagnosis, assessing students’ mastery of knowledge points through pre-set questions; Step S3: Generate a personalized question bank based on the diagnosis results; Step S4: Learning and practicing, students learn and practice through the question bank provided by the system; Step S5: Feedback and adjustment, the system provides feedback based on students' learning performance and adjusts the question bank.

[0036] Step S3 includes the following steps: Step S31: Analyze students' learning data using data mining technology; Step S32: Use machine learning algorithms to predict students' learning needs.

[0037] Step S5 includes: Step S51: providing real-time records of students’ learning progress and grades; Step S52: Adjust the question bank content according to the student's learning performance.

[0038] In summary, the system leverages structured knowledge points and artificial intelligence technology to provide students with a personalized and efficient learning experience. Combining user learning diagnostic information and behavioral data, it dynamically generates a question bank tailored to students' learning needs and adjusts content in real time based on their learning performance. The system first guides users through registration and a learning diagnostic, assessing their knowledge mastery through pre-set questions. The system then uses data mining techniques to analyze the user's learning data, identifying key areas of mastery and weaknesses. It then incorporates machine learning algorithms to predict the user's future learning needs. Based on these analysis results, the system dynamically generates a personalized question bank and presents learning content in a progressive manner, organized by key areas, ensuring students progressively learn and master knowledge. Students learn and practice content within the system. After completing a question, the system provides detailed feedback and explanations based on their responses, helping them understand the reasons for any errors and deepen their learning. The system also records students' learning progress and grades and dynamically adjusts the question bank content based on their learning performance, ensuring that learning materials remain relevant and effective. The system also provides a forum and information dissemination system to foster communication between students and between students and teachers, fostering a positive learning community.

[0039] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions merely illustrate the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A structured intelligent question bank generation system based on knowledge points, characterized by: include, An online self-learning tutorial platform that provides learning content covering all subjects in the syllabus; Question bank generation module, used to generate personalized question banks based on students' learning progress and ability levels; Diagnostic module, used to provide accurate learning diagnosis and help students identify learning weaknesses; Full subject support module, used to ensure that the system covers knowledge points of all subjects; Infinite holographic learning scenario module, used to provide multiple learning scenarios to meet the learning needs of different students; Communication platform module to enable students to prepare for the exams without any hassle.

2. The structured intelligent question bank generation system based on knowledge points according to claim 1 is characterized in that: The question bank generation module includes: Data mining is used to analyze students’ learning data and identify their mastery of knowledge points; Machine learning algorithms are used to predict students' learning needs and generate personalized question banks.

3. The structured intelligent question bank generation system based on knowledge points according to claim 1 is characterized in that: The diagnostic module can conduct a preliminary diagnosis of students through a series of preset questions, evaluate students' mastery of knowledge points, and provide feedback.

4. The structured intelligent question bank generation system based on knowledge points according to claim 1 is characterized in that: The full subject support modules include: Database, which stores knowledge points and related questions of all subjects; The retrieval system is used to retrieve and provide relevant topics based on students' learning progress.

5. The structured intelligent question bank generation system based on knowledge points according to claim 1 is characterized in that: The infinite holographic learning scenario module can provide a variety of learning scenarios, including but not limited to simulated exams, interactive learning, video tutorials, etc., and can adjust the learning scenarios according to students' learning habits and preferences.

6. The structured intelligent question bank generation system based on knowledge points according to claim 1 is characterized in that: The communication platform module includes: Communication forums for communication between students and between students and teachers; Information publishing system, used to publish information related to college entrance examinations.

7. A method for using the knowledge point-based structured intelligent question bank generation system according to any one of claims 1 to 6, characterized in that: The specific steps include: Step S1: User registration and login; Step S2: Learning diagnosis, assessing students’ mastery of knowledge points through pre-set questions; Step S3: Generate a personalized question bank based on the diagnosis results; Step S4: Learning and practicing, students learn and practice through the question bank provided by the system; Step S5: Feedback and adjustment, the system provides feedback based on students' learning performance and adjusts the question bank.

8. The structured intelligent question bank generation system based on knowledge points according to claim 7 is characterized in that: The step S3 comprises the following steps: Step S31: Analyze students' learning data using data mining technology; Step S32: Use machine learning algorithms to predict students' learning needs.

9. The structured intelligent question bank generation system based on knowledge points according to claim 7 is characterized in that: The step S5 comprises: Step S51: providing real-time records of students’ learning progress and grades; Step S52: Adjust the question bank content according to the student's learning performance.

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