Self-adaptive learning system

Abstract

The invention relates to the technical field of adaptive learning, in particular to an adaptive learning system, which comprises a user management module, a course management module, a progress tracking module and an evaluation and test module, and is characterized in that the user management module is configured with a login interface; the course management module is configured with a big data processing unit, and the big data processing unit is used for analyzing the learning content file and decomposing the learning content file into basic course information, advanced course information, intermediate course information and graduation course information; the progress tracking module is based on the personal account and is used for transmitting current course information to the personal account and recording the completion time of each course information; and the evaluation and test module is connected to the course management module, receives the course information average completion time counted by the user management module, compares the completion time with the average completion time, and sends a test instruction to the personal account information. The method aims at helping different users to quickly, stably and gradually master knowledge with different difficulties.

Description

Technical Field

[0001] The present invention relates to the field of adaptive learning technology, and in particular to an adaptive learning system. Background Art

[0002] The current educational goal is to teach well so that learners can learn efficiently and have less negative emotions. Under the premise of the same teaching goal, learners have different foundations or learning abilities. If the same learning content is provided to different students, it will not enable all students to achieve the ideal learning effect. Therefore, a learner-centered method is needed to provide targeted learning content or learning paths for different people.

[0003] At present, in online learning systems, the traditional method of judging students' mastery of knowledge points is to judge right or wrong only by doing questions. After an error occurs, the system will mark the wrong question and continuously release the wrong question to students so that students can master the solution to the question. However, this often only enables students to master the question when faced with this question, and cannot train students' ability to draw inferences from one example. In addition, simply releasing knowledge points of different difficulty levels to students in the form of questions will increase students' learning pressure and prevent them from learning efficiently. Summary of the invention

[0004] The main purpose of the present invention is to provide an adaptive learning system, which aims to help different users to gradually master knowledge of different difficulty levels quickly and stably.

[0005] To achieve the above objectives, the present invention proposes an adaptive learning system, including a user management module, a course management module, a progress tracking module, and an evaluation and testing module:

[0006] The user management module is configured with a login interface, through which one can enter a personal account to obtain personal account information, authority management, and personal files;

[0007] The course management module receives the learning content file and is configured with a big data processing unit, which is used to analyze the learning content file and decompose it into basic course information, advanced course information, intermediate course information, and graduation course information;

[0008] The progress tracking module is based on the personal account and connected to the course management module, and is used to transmit the current course information to the personal account and record and monitor the user's completion time at each course information;

[0009] The evaluation and testing module is connected to the course management module and receives the average completion time of the course information counted by the user management module. The evaluation and testing module compares the completion time with the average completion time and issues a test instruction to the personal account information;

[0010] When the test score is greater than 80 out of 100, the excellent score is output to the personal account, and the course management module enters the next stage;

[0011] When the test score is greater than 60 and less than 80, the completion time is compared with the average completion time. When the average completion time is greater than the completion time, the good score is output to the personal account, and the course management module enters the next stage;

[0012] When the test score is greater than 60 and less than 80, and the average completion time is less than the completion time, the pass score is output to the personal account, and the course management module enters the next stage and imports the current course content for hybrid learning;

[0013] When the test score is less than 60, the assessment failure is output to the personal account, and the course management module executes the review command.

[0014] In one embodiment of the present application, the personal account is provided with a feedback and suggestion module based on the evaluation and test results, and the feedback and suggestion module is used to analyze the test scores and wrong questions appearing in the test;

[0015] If the result is excellent, no more than 10% of the wrong questions in the previous stage will be included in the next stage of the exam;

[0016] When the result is good, the next stage of the exam will include no more than 30% of the wrong questions from the previous stage;

[0017] When the score is passing, the next stage of the exam will be mixed with no more than 50% of the wrong questions in the previous stage, and will be tested by the assessment and testing module. When the score is greater than or equal to good, you will enter the next stage of study. When the score is passing, a new test paper with no more than 10% of the wrong questions in the previous stage will be issued for re-verification.

[0018] In one embodiment of the present application, the course management module is configured with a learning resource library for receiving learning content files. The learning resource library is provided with a feature analysis unit, which decomposes the learning content files into multiple stages, including basic course information, advanced course information, intermediate course information, and graduation course information, by analyzing the knowledge points used in the process of answering relevant questions and the complexity of the application of the knowledge points.

[0019] In one embodiment of the present application, the learning material library is configured with a suggestion unit, which is connected to the evaluation and testing module, and is used to receive wrong questions that appear in the test, and call the learning material library to find the correct solution through the wrong questions, and thereby confirm the stage that the question is in. At the same time, according to the knowledge points and formulas referenced by the correct solution, find the same type of questions, and package the same type of questions into the next stage examination information, and the next stage examination information is received by the feedback and suggestion module.

[0020] In one embodiment of the present application, the progress tracking module is configured with an interactive module, which is connected to the learning database and is used to add questions corresponding to the knowledge points in the learning course. Only when the corresponding questions are completely correct will the progress tracking module display the completion of the current learning stage and activate the evaluation and testing module. The interactive module is configured to mark the knowledge points and formulas corresponding to the questions when errors occur in the questions, and while the completion time of the learning continues to increase, the current question is locked for one minute. The one-minute personal account hides the knowledge points and formulas, and at the same time the question re-enters the state of requiring an answer until the question is completely answered. The interactive module outputs the completion time corresponding to the current stage.

[0021] In one embodiment of the present application, the progress tracking module is also configured with a communication module, which is connected to the interaction module and is used to display the analysis of the question through the display module of the personal account when the number of errors in the same question exceeds 2 times. After the user confirms the analysis of the question, the subsequent learning task is carried out, and after a certain period of time, another question with the same knowledge point is proposed based on the suggestion unit until the user completes the learning task of the current stage.

[0022] In one embodiment of the present application, the evaluation and testing module is also configured with an analysis module, which is used to extract the final grades of different courses after the learning tasks corresponding to the graduation course information are completed, and to organize the wrong questions into a wrong question set, which is sent to the user management module in combination with the final grade analysis to facilitate the user's subsequent review and improvement.

[0023] To achieve the above object, the present invention proposes an adaptive learning method, including the above adaptive learning system, and the adaptive learning method includes:

[0024] In one embodiment of the present application, the adaptive learning method is applied to an adaptive learning system, and the method includes:

[0025] S100, collecting the user's learning goals, and collecting the learning content files required to complete the learning goals through the learning goals;

[0026] S200, splitting the learning content file into multiple course information based on the interactivity and complexity of the knowledge points in the learning content file, and organizing the multiple course information into multiple class hours according to the number of the multiple course information;

[0027] S300, the user logs in to the personal account and calls up the complete lesson information. Each lesson needs to be completed once before entering the next lesson;

[0028] S400, based on the completion speed of the class and the completion status of the coursework, analyzes the user's learning ability and learning habits, and is used to adjust the length of the class to avoid users' disgust;

[0029] S500, proposes a test task based on the completion status of the class, and summarizes the analysis of wrong questions according to the completion status of the test task. Only when the test task score is greater than good can you directly enter the next learning stage.

[0030] In one embodiment of the present application, after step S500, the following steps are further included:

[0031] S501, a same knowledge point search module is configured based on wrong question analysis to search for other questions that mainly include the knowledge point and to reference related questions during user testing;

[0032] S502, when errors continue to occur on the same type of questions, manual interaction will be connected. The customer service teacher will receive an analysis of the wrong questions and communicate directly with the user.

[0033] The technical solution of the present invention adopts the method of decomposing the adaptive learning system into multiple modules, including a user management module, a course management module, a progress tracking module, and an evaluation and detection module. The user management module is mainly used to enable each user to have an independent account, which is a personal account, including personal account information, authority management, and personal files. After logging into the independent account, the user can connect to the course management module separately, so that the course management module can, after initially decomposing the learning content file into multiple courses, plan the learning path based on the personal files in a personalized manner, and when the course is divided into multiple classes, adjust the duration to a duration that the user will not dislike, and raise questions corresponding to the knowledge points at different stages of the class according to the students' learning habits, so as to assist the students to better master the knowledge points and formulas, and will not cause the students to have excessive learning process. The boredom of students leads to a significant decrease in learning efficiency. The general course management module can import different learning content files according to possible learning objectives, which include knowledge points, questions, and formulas of different stages and complexities. The big data processing unit is used to split them into basic, advanced, intermediate, and graduation courses. There are exams between each course. Only after passing the exam of a course can you enter the next course. The personal account is used to split each course independently, and divide it into classes with different time intervals according to the students' learning ability and habits. The class is the class that students can normally complete. Only when the class is completely completed can they enter the next class. If a student suspends or terminates a group of classes due to personal problems, he or she will re-enter the class when he or she logs in next time. Only in this way can we avoid greatly reducing the learning efficiency due to self-procrastination.

[0034] Furthermore, the progress tracking module is also based on the personal account and is connected to the course management module. The current course stage and class stage are saved by the module and transmitted to the display module of the personal account for display, which is used to assist students in learning, so that students can watch the completion of the task step by step, so that students can have confidence in the learning process, can complete their studies more actively, and reduce their resistance to learning. At the same time, the progress tracking module can record and monitor the user's completion time of each course and class. Monitoring this time can make the system understand the student's learning ability more intuitively and facilitate the division of class hours. The user management module can call the time when all users who use the system complete the class. The time data with excessive difference at both ends can be taken to obtain the average time to complete the course. This average time can better reflect the student's learning efficiency and is used to assist in evaluating the student's completion status, so that students can complete their studies more firmly and avoid forgetting.

[0035] Furthermore, the evaluation and testing module is connected to the course management module, and can receive the time it takes for students to complete the course and the average time it takes for users to complete the course. These two time periods can be used as references to improve the degree of learning mastery, and a test instruction can be issued after the course is completed. When the output result is excellent, the student's knowledge points are very solid, no matter how long they have studied, and the course management module enters the next stage; when the test score is greater than 60 and less than 80, the completion time is compared with the average completion time. When the average completion time is greater than the completion time, a good result is output to the personal account, which means that the student has mastered the basic knowledge points and the efficiency is normal, and the course management module enters the next stage. The next stage: when the test score is greater than 60 and less than 80, and the average completion time is less than the completion time, a qualified score is output to the personal account, which means that the student has basically mastered the knowledge points, but the efficiency is extremely low and there is a risk of forgetting. The course management module enters the next stage and imports the current course content for mixed learning to prevent students from forgetting too quickly, resulting in wasted time but no learning efficiency; when the test score is less than 60, the assessment failure is output to the personal account, the course management module executes the review command, and the student repeats the learning of the content. The above results can effectively help different users quickly and steadily master knowledge of different difficulty levels. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying creative work.

[0037] Figure 1 It is a structural schematic diagram of the adaptive learning system of the present invention;

[0038] Figure 2 is a flow chart of the adaptive learning method of the present invention;

[0039] Figure 3 This is a summary and analysis flow chart of the adaptive learning method of the present invention.

[0040] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0042] To solve the problems in the background technology, such as Figure 1 As shown, an adaptive learning system proposed by the present invention includes a user management module, a course management module, a progress tracking module, and an evaluation and testing module. The user management module is configured with a login interface, through which a personal account can be entered to obtain personal account information, authority management and personal files; the course management module receives learning content files and is configured with a big data processing unit, which is used to analyze the learning content files and decompose them into basic course information, advanced course information, intermediate course information, and graduation course information; the progress tracking module is based on the personal account and is connected to the course management module, and is used to transmit the current course information to the personal account, and record and monitor the completion time of the user at each course information; the evaluation and testing module is connected to the course management module, and receives the course information counted by the user management module. The evaluation and testing module compares the completion time with the average completion time and sends a test instruction to the personal account information; when the test score is greater than 80 out of 100, the personal account is output with an excellent score, and the course management module enters the next stage; when the test score is greater than 60 and less than 80, the completion time is compared with the average completion time. When the average completion time is greater than the completion time, the personal account is output with a good score, and the course management module enters the next stage; when the test score is greater than 60 and less than 80, and the average completion time is less than the completion time, the personal account is output with a qualified score, the course management module enters the next stage, and the current course content is imported for hybrid learning; when the test score is less than 60, the personal account is output with an assessment failure, and the course management module executes a review command.

[0043] Understandably, the adaptive learning system is decomposed into multiple modules, including user management module, course management module, progress tracking module, and evaluation and testing module. The user management module is mainly used to enable each user to have an independent account. An independent account is a personal account, including personal account information, authority management, and personal files. After logging into an independent account, the user can connect to the course management module individually, so that the course management module can initially decompose the learning content files into multiple courses, and then personalize the learning path based on the personal files. When the course is divided into multiple classes, it can be adjusted to a length that the user will not be disgusted with, and questions corresponding to knowledge points are raised at different stages of the class according to the students' learning habits, so as to assist students in better mastering knowledge points and formulas, and will not make students too bored during the learning process. Emotions greatly reduce learning efficiency. General course management modules can import different learning content files according to possible learning objectives, which include knowledge points, questions, and formulas of different stages and complexities. The big data processing unit is used to split them into basic, advanced, intermediate, and graduation courses. There are exams between each course. Only after passing a course exam can you enter the next course. Personal accounts are used to independently split each course into classes with different time intervals according to students' learning abilities and habits. The class is the class that students can normally complete. Only when the class is completely completed can they enter the next class. If a student suspends or terminates a group of classes due to personal problems, he or she will re-enter the class at the next login. Only in this way can students avoid greatly reducing their learning efficiency due to self-procrastination.

[0044] Furthermore, the progress tracking module is also based on the personal account and is connected to the course management module. The current course stage and class stage are saved by the module and transmitted to the display module of the personal account for display, which is used to assist students in learning, so that students can watch the completion of the task step by step, so that students can have confidence in the learning process, can complete their studies more actively, and reduce their resistance to learning. At the same time, the progress tracking module can record and monitor the user's completion time of each course and class. Monitoring this time can make the system understand the student's learning ability more intuitively and facilitate the division of class hours. The user management module can call the time when all users who use the system complete the class. The time data with excessive difference at both ends can be taken to obtain the average time to complete the course. This average time can better reflect the student's learning efficiency and is used to assist in evaluating the student's completion status, so that students can complete their studies more firmly and avoid forgetting.

[0045] Furthermore, the evaluation and testing module is connected to the course management module, and can receive the time it takes for students to complete the course and the average time it takes for users to complete the course. These two time periods can be used as references to improve the degree of learning mastery, and a test instruction can be issued after the course is completed. When the output result is excellent, the student's knowledge points are very solid, no matter how long they have studied, and the course management module enters the next stage; when the test score is greater than 60 and less than 80, the completion time is compared with the average completion time. When the average completion time is greater than the completion time, a good result is output to the personal account, which means that the student has mastered the basic knowledge points and the efficiency is normal, and the course management module enters the next stage. The next stage: when the test score is greater than 60 and less than 80, and the average completion time is less than the completion time, a qualified score is output to the personal account, which means that the student has basically mastered the knowledge points, but the efficiency is extremely low and there is a risk of forgetting. The course management module enters the next stage and imports the current course content for mixed learning to prevent students from forgetting too quickly, resulting in wasted time but no learning efficiency; when the test score is less than 60, the assessment failure is output to the personal account, the course management module executes the review command, and the student repeats the learning of the content. The above results can effectively help different users quickly and steadily master knowledge of different difficulty levels.

[0046] In one embodiment of the present application, a personal account is provided with a feedback and suggestion module based on the evaluation and test results, and the feedback and suggestion module is used to analyze the test results and the wrong questions that appear in the test; when the result is excellent, no more than 10% of the wrong questions in the previous stage will be mixed in the next stage examination; when the result is good, no more than 30% of the wrong questions in the previous stage will be mixed in the next stage examination; when the result is qualified, no more than 50% of the wrong questions in the previous stage will be mixed in the next stage examination, and the evaluation and testing module will be used for detection. When the result is greater than or equal to good, the next learning stage will be entered, and when the result is qualified, a new test paper with no more than 10% of the wrong questions in the previous stage will be issued for re-verification.

[0047] Understandably, personal accounts are equipped with a feedback and suggestion module based on assessment and test results. This module is mainly used to analyze test scores and wrong questions in the test, so as to systematically provide students with suggestions for auxiliary learning and avoid major omissions in learning. It is mainly through collecting wrong questions and extracting the correct answers, formulas involved and knowledge points involved in the wrong questions in the learning content file through the features of the course management module, and retrieving other similar questions included in the file based on these knowledge points and formulas, and making a wrong question collection. When the score is excellent, the next stage of the exam will be mixed with no more than 10% of the wrong question collection content, which can be used to assist students in reviewing. The same is true for good. In order to consolidate the knowledge points, 30% of the wrong question collection needs to be mixed. If the score is only qualified, it is necessary to review almost all over again. In order to avoid loose knowledge learning, 50% of the questions in each stage are needed. Only when the test is good can you enter the next stage. When it is qualified, you need to take an additional test paper of the current stage to avoid incomplete knowledge.

[0048] In one embodiment of the present application, the course management module is configured with a learning resource library for receiving learning content files. The learning resource library is provided with a feature analysis unit, which decomposes the learning content files into multiple stages, including basic course information, advanced course information, intermediate course information, and graduation course information, by analyzing the knowledge points used in the process of answering relevant questions and the complexity of the application of the knowledge points.

[0049] It can be understood that the course management module is configured with a learning resource library for receiving learning content files. It is provided with a feature analysis unit, which is mainly used to perform feature analysis on the knowledge points and application complexity contained in the questions in the learning content files, so as to divide the learning content files into multiple course stages including basic course information, advanced course information, intermediate course information, and graduation course information, helping students to grasp the knowledge points step by step and improve their learning efficiency.

[0050] In one embodiment of the present application, the learning material library is configured with a suggestion unit, which is connected to the evaluation and testing module, and is used to receive wrong questions that appear in the test, and call the learning material library to find the correct solution through the wrong questions, and thereby confirm the stage that the question is in. At the same time, according to the knowledge points and formulas referenced by the correct solution, find the same type of questions, and package the same type of questions into the next stage of examination information, and the next stage of examination information is received by the feedback and suggestion module.

[0051] It can be understood that the learning resource library is equipped with a suggestion unit, which is connected to the evaluation and testing module and is used to receive wrong questions that appear in the test. The suggestion unit itself can call the feature analysis unit in the learning resource library to find the same type of questions as the wrong questions through the feature analysis unit, so as to avoid students only mastering the solution to a question instead of mastering the knowledge point. In this way, different users can be helped to quickly and steadily master knowledge of different difficulty levels.

[0052] In one embodiment of the present application, the progress tracking module is configured with an interactive module, which is connected to the learning database and is used to add questions corresponding to the knowledge points in the learning course. Only when the corresponding questions are completely correct will the progress tracking module display the completion of the current learning stage and activate the evaluation and testing module. The interactive module is configured to mark the knowledge points and formulas corresponding to the questions when errors occur in the questions, and while the completion time for learning continues to increase, the current question is locked for one minute. The one-minute personal account hides the knowledge points and formulas, and at the same time the question re-enters the state of requiring an answer until the question is completely answered. The interactive module outputs the completion time corresponding to the current stage.

[0053] Understandably, the progress tracking module is configured with an interactive module, which is connected to the learning database. It can set questions corresponding to the knowledge points in each class according to the knowledge points learned by students. Only when the questions are completely correct can the knowledge points be considered completed. The interactive module is configured to mark the knowledge points and formulas corresponding to the questions when there are errors in the questions, so that students can have a deeper understanding of the knowledge points. After the question is wrong, the question will be locked for at least one minute, and other questions cannot be viewed within this minute, and the class completion time will continue to accumulate. When the countdown ends, you need to answer the questions again. The completion time of the class will not be settled until the questions are completed, which is used to facilitate the system to evaluate the students' learning status and learning efficiency.

[0054] In one embodiment of the present application, the progress tracking module is also configured with a communication module, which is connected to the interaction module and is used to display the analysis of the question through the display module of the personal account when the number of errors in the same question exceeds 2 times. After the user confirms the analysis of the question, the subsequent learning task is carried out, and after a certain period of time, another question with the same knowledge point is proposed based on the suggestion unit until the user completes the learning task of the current stage.

[0055] It can be understood that the progress tracking module is also configured with a communication module, which is connected to the interaction module. During the students' learning process in each lesson, students with particularly poor foundations may make multiple mistakes in the questions. When the same question appears more than twice, it means that the students are completely unable to understand the knowledge point. The system will display a complete analysis until the students confirm that they have completed the learning to avoid students being unable to understand the knowledge points.

[0056] In one embodiment of the present application, the evaluation and testing module is also configured with an analysis module, which is used to extract the final grades of different courses after the learning tasks corresponding to the graduation course information are completed, and the wrong questions are sorted into a wrong question set, which is sent to the user management module in combination with the final grade analysis to facilitate the user's subsequent review and improvement.

[0057] It can be understood that the evaluation and testing module is also configured with an analysis module, which is used to extract the final grades of different courses based on the course management module and the evaluation and testing module, and output the wrong question collection and send it to the user. After the students complete all the courses, the wrong question collection can be sent to the students in the form of a file. The wrong question collection can be saved or printed to improve the review efficiency. This structure can assist different students to master knowledge efficiently.

[0058] refer to Figures 2 to 3 The present invention also proposes an adaptive learning method, which includes the above-mentioned adaptive learning system. The specific structure of the adaptive learning system refers to the above-mentioned embodiment. Since the adaptive learning method adopts all the technical solutions of all the above-mentioned embodiments, it has at least all the beneficial effects brought by the technical solutions of the above-mentioned embodiments, which will not be repeated here one by one.

[0059] An adaptive learning method proposed by the present invention comprises the following steps:

[0060] S100, collecting the user's learning goals, and collecting the learning content files required to complete the learning goals through the learning goals;

[0061] S200, splitting the learning content file into multiple course information based on the interactivity and complexity of the knowledge points in the learning content file, and organizing the multiple course information into multiple class hours according to the number of the multiple course information;

[0062] S300, the user logs in to the personal account and calls up the complete lesson information. Each lesson needs to be completed once before entering the next lesson;

[0063] S400, based on the completion speed of the class and the completion status of the coursework, analyzes the user's learning ability and learning habits, and is used to adjust the length of the class to avoid users' disgust;

[0064] S500, proposes a test task based on the completion status of the class, and summarizes the analysis of wrong questions according to the completion status of the test task. Only when the test task score is greater than good can you directly enter the next learning stage.

[0065] Understandably, the method of adaptive learning mainly includes collecting learning content files necessary to complete some learning goals. These files can be used as basic courses. Through the complexity and interactivity of the knowledge points involved in these files, these files can be divided into multiple courses from simple to difficult, and multiple courses can be divided into multiple classes. Only in-class exercises are needed between classes, and tests must be passed between courses before entering the next course. The setting of personal accounts allows the division of classes to be different for different users, avoiding students from feeling strenuous due to insufficient learning ability. Based on the completion speed of classes and the completion status of course assignments, the user's learning ability and learning habits are analyzed, and they can also be used to adjust the length of classes. When all the classes of a group of courses are completed, test tasks are carried out, and wrong questions are summarized after the tasks are completed. When the results are good, they can directly enter the next learning stage, otherwise it is necessary to strengthen the review of this stage to prevent poor learning efficiency of users.

[0066] S501, a same knowledge point search module is configured based on wrong question analysis to search for other questions that mainly include the knowledge point and to reference related questions during user testing.

[0067] Understandably, based on the wrong question analysis, a same knowledge point search module is configured to find the knowledge points used in the wrong questions, as well as other related questions that mainly use the knowledge points. The wrong question collection compiled in this way can be referenced when students are tested, allowing students to better master the knowledge points.

[0068] S502, when errors continue to occur on the same type of questions, manual interaction will be connected. The customer service teacher will receive an analysis of the wrong questions and communicate directly with the user.

[0069] Understandably, when errors continue to occur on the same type of questions, manual interaction is initiated. When the customer service teacher accesses the system, he or she will directly check the cause of the error and then communicate directly with the student, which can better tutor the student's schoolwork. The above structure and method are intended to help different users quickly and steadily master knowledge of different difficulty levels.

[0070] The same or similar numbers in the drawings of this embodiment correspond to the same or similar parts; in the description of this application, it should be understood that if the terms "upper", "lower", "left", "right", etc. indicate an orientation or position relationship based on the orientation or position relationship shown in the drawings, it is only for the convenience of describing this application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, the terms describing the position relationship in the drawings are only used for illustrative purposes and cannot be understood as a limitation on this patent. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0071] The above are only preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. An adaptive learning system, characterized in that: include: A user management module, wherein the user management module is configured with a login interface, through which a person can enter a personal account to obtain personal account information, authority management, and personal files; A course management module, which receives learning content files and is configured with a big data processing unit, which is used to analyze the learning content files and decompose them into basic course information, advanced course information, intermediate course information, and graduation course information; A progress tracking module, which is based on a personal account and connected to the course management module, is used to transmit current course information to the personal account and record and monitor the user's completion time for each course information; An evaluation and testing module, which is connected to the course management module and receives the average completion time of the course information counted by the user management module. The evaluation and testing module compares the completion time with the average completion time and issues a test instruction to the personal account information; When the test score is greater than 80 out of 100, the excellent score is output to the personal account, and the course management module enters the next stage; When the test score is greater than 60 and less than 80, the completion time is compared with the average completion time. When the average completion time is greater than the completion time, the good score is output to the personal account, and the course management module enters the next stage; When the test score is greater than 60 and less than 80, and the average completion time is less than the completion time, the pass score is output to the personal account, and the course management module enters the next stage and imports the current course content for hybrid learning; When the test score is less than 60, the assessment failure is output to the personal account, and the course management module executes the review command.

2. An adaptive learning system according to claim 1, characterized in that: The personal account is provided with a feedback and suggestion module based on the evaluation and test results, and the feedback and suggestion module is used to analyze the test scores and wrong questions in the test; If the result is excellent, no more than 10% of the wrong questions in the previous stage will be included in the next stage of the exam; When the result is good, the next stage of the exam will include no more than 30% of the wrong questions from the previous stage; When the score is passing, the next stage of the exam will be mixed with no more than 50% of the wrong questions in the previous stage, and will be tested by the assessment and testing module. When the score is greater than or equal to good, you will enter the next stage of study. When the score is passing, a new test paper with no more than 10% of the wrong questions in the previous stage will be issued for re-verification.

3. An adaptive learning system according to claim 2, characterized in that: The course management module is configured with a learning resource library for receiving learning content files. The learning resource library is provided with a feature analysis unit, which decomposes the learning content files into multiple stages, including basic course information, advanced course information, intermediate course information, and graduation course information, by analyzing the knowledge points used in the process of answering relevant questions and the complexity of the application of the knowledge points.

4. An adaptive learning system according to claim 3, characterized in that: The learning material library is configured with a suggestion unit, which is connected to the evaluation and testing module, and is used to receive wrong questions that appear in the test, and call the learning material library to find the correct solution through the wrong questions, and thereby confirm the stage that the question is in. At the same time, according to the knowledge points and formulas referenced by the correct solution, find the same type of questions, and package the same type of questions into the next stage examination information, which is received by the feedback and suggestion module.

5. An adaptive learning system according to claim 4, characterized in that: The progress tracking module is configured with an interactive module, which is connected to the learning database and is used to add questions corresponding to the knowledge points in the learning course. When the corresponding questions are completely correct, the progress tracking module will display the completion of the current learning stage and activate the evaluation and testing module. The interactive module is configured to mark the knowledge points and formulas corresponding to the questions when errors occur in the questions, and lock the current question for one minute while the completion time of the learning continues to increase. The one-minute personal account hides the knowledge points and formulas, and at the same time the question re-enters the state of requiring answers until the question is completely answered. The interactive module outputs the completion time corresponding to the current stage.

6. An adaptive learning system according to claim 5, characterized in that: The progress tracking module is also configured with a communication module, which is connected to the interaction module and is used to display the analysis of the question through the display module of the personal account when the number of errors in the same question exceeds 2 times. When the user confirms the analysis of the question, the subsequent learning task is carried out, and after a certain period of time, another question with the same knowledge point is proposed based on the suggestion unit until the user completes the learning task of the current stage.

7. An adaptive learning system according to claim 6, characterized in that: The evaluation and testing module is also configured with an analysis module, which is used to extract the final scores of different courses after the learning tasks corresponding to the graduation course information are completed, and to organize the wrong questions into a wrong question set. The wrong question set is sent to the user management module in combination with the final score analysis to facilitate the user's subsequent review and improvement.

8. An adaptive learning method, comprising an adaptive learning system as claimed in any one of claims 1 to 7, characterized in that: The adaptive learning method comprises the following steps: S100, collecting the user's learning goals, and collecting the learning content files required to complete the learning goals through the learning goals; S200, splitting the learning content file into multiple course information based on the interactivity and complexity of the knowledge points in the learning content file, and organizing the multiple course information into multiple class hours according to the number of the multiple course information; S300, the user logs in to the personal account and calls up the complete lesson information. Each lesson needs to be completed once before entering the next lesson; S400, based on the completion speed of the class and the completion status of the coursework, analyzes the user's learning ability and learning habits, and is used to adjust the length of the class to avoid users' disgust; S500, proposes a test task based on the completion status of the class, and summarizes the analysis of wrong questions according to the completion status of the test task. Only when the test task score is greater than good can you directly enter the next learning stage.

9. An adaptive learning method according to claim 8, characterized in that: After step S500, the following steps are further included: S501, a same knowledge point search module is configured based on wrong question analysis to search for other questions that mainly include the knowledge point and to reference related questions during user testing; S502, when errors continue to occur on the same type of questions, manual interaction will be connected. The customer service teacher will receive an analysis of the wrong questions and communicate directly with the user.

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