WO2023234651A1

WO2023234651A1 - System and method for learning mathematics through artificial intelligence and online convergence

Info

Publication number: WO2023234651A1
Application number: PCT/KR2023/007261
Authority: WO
Inventors: 이승호
Original assignee: 이승호
Priority date: 2022-05-30
Filing date: 2023-05-26
Publication date: 2023-12-07
Also published as: KR102496227B1

Abstract

The present invention relates to a system and a method for learning mathematics through artificial intelligence and online convergence, in which data, such as a table of contents for mathematics, conceptual terms, problems according to types, calculation problems, comprehensive problems, and mathematical theories, may be systematically collected through a big data technology, and learner data, such as a learner's attitude and learning behavior, may be collected by monitoring through a camera, so that analytical use of the data is possible. Furthermore, the present invention comprehensively provides a learning modeling unit, a weak area enhancement unit, a 10-minute summary unit, and a learning planning unit system so as to enable maximum improvement in mathematical problem-solving abilities of learners.

Description

Mathematics learning system and method through artificial intelligence and online convergence

The present invention relates to a mathematics learning system and method through artificial intelligence and online convergence. More specifically, the characteristics of mathematics subjects and learner-specific data are collected and stored systematically and analytically, and an artificial intelligence learning method is applied based on this. An artificial intelligence and online convergence mathematics learning system and method that can best improve individual problem-solving skills by strengthening the learner's weak areas and utilizing a learning model system and learning management system consisting of a summary and learning plan, etc. It's about.

Mathematics has been considered very important as a study that develops logical thinking skills, but on the other hand, it is also known as a subject where many learners have learning difficulties. It is known that the learning deviation of mathematics learners increases as they progress to higher grades, and various mathematics learning methods that help mathematics learners' problem-solving skills have been discussed.

Meanwhile, there has been much discussion about ways to use artificial intelligence and online as learning tools. However, there have been limitations in deriving the best learning results by considering artificial intelligence methods in the learner's learning style, the academic characteristics of mathematics as a subject of learning, and combining these with technologies such as big data, online, and artificial intelligence learning.

Republic of Korea Patent Publication No. 10-2017-0096699 proposes an artificial intelligence-based personalized STEM learning service system and method, but does not reflect the characteristics of the learning subject and the learning method of artificial intelligence.

Republic of Korea Patent No. 10-2065746 provides an online learning service provision system and method through editing guidance, but this also has limitations in that it does not analyze and apply the artificial intelligence learning method itself.

Accordingly, the present invention provides a mathematics learning system that can optimize the learning results of mathematics learners by focusing on the fusion of systematicity, which is a characteristic of the discipline of mathematics, and the learning method of artificial intelligence and an online system. In other words, mathematical problems are a very good way to develop and evaluate data interpretation skills and application and application skills among the various problems that humans encounter. In particular, solving human problems through mathematics utilizes the way artificial intelligence solves mathematics. The goal is to maximize ability improvement and produce the best learning results.

The task of the present invention is 1) not to simply convert mathematical problems into data, but to improve the nature of mathematics subjects and problem-solving skills, with the ultimate goal of improving the order of mathematics, the expansion of concepts by systematicity, problems by type, calculation power, and mathematics. Theories, etc. are collected and stored systematically and analytically. In addition, for interactive learning with artificial intelligence, a database should be provided in which the learner's attitude and behavior are collected as data based on camera observation.

In addition, 2) a learning management system in which the learning process is not simply carried out sequentially, but the weak areas identified according to the individual learner's learning result records are generated as data and fed back to the learning process to complete the learning by supplementing them. shall be provided.

3) Provide a system in which the individual learner's summary book extracted according to the learner's learning process can be used during the entire course of the Bang University mathematics subject. 4) In addition, the learner sets a study plan with artificial intelligence, but supplements the weak areas above. The system, the summary system, the study plan, and the problem-solving system that interprets problems by underlining are linked together to ultimately enable learners to efficiently improve their math problem-solving skills and achieve the best learning results.

According to one embodiment of the present invention, a mathematics learning system through artificial intelligence and online convergence includes a data collection unit necessary for implementation of the present invention. The data collection department collects and acquires data from the entire mathematics process. In particular, the title, order, and subdivision of not only mathematics problems but also units such as the table of contents of mathematics textbooks are used to substantially help learners improve their mathematics problem-solving skills. Concepts related to the systematicity of mathematics, mathematical terms, problems by type, computational power data, comprehensive problems, and mathematical theory data are collected, stored, and used. In particular, through camera observation, notes, attitudes, and behaviors written by learners when solving problems are collected and used. History, past exam questions, etc. are collected and reflected and utilized in the future learning process.

In addition, the mathematics learning system through artificial intelligence and online convergence of the present invention is characterized by having a learning modeling unit that utilizes data from the data collection unit provided above and provides it to the learner.

The learning modeling unit is equipped with a curriculum that considers the learner's acquisition and improvement of problem-solving methods, so that when the learner solves a math problem, he underlines the problem and explains which part of the table of contents of mathematics it is, what concepts appear in the table of contents, and what type of problem it is. It is characterized by providing a unit preparation stage, a unit learning stage, a problem solving stage, a unit organization stage, and a comprehensive problem stage, which are structured so that one can naturally acquire the method of finding cognition sequentially.

In addition, each unit preparation stage, unit learning stage, and unit organizing stage above are provided in a way that trains the learner to master the learning content, memorize it, and then use it immediately in the problem-solving process later, for example, the math turn. In the case of contents related to mathematics, after the list contents of mathematics are provided, parentheses are placed on the contents of the mathematics table so that the learner can fill in the parentheses. Ultimately, the learner is asked to memorize and enter all the contents so that the learner fully acquires the learning contents. It is equipped with a memorization-enhancing modeling department and a problem-solving system department.

The present invention is equipped with a problem-solving system that helps the learner solve problems while interactively communicating between the learner and artificial intelligence using artificial intelligence technology, so that the learner can solve the problem on his own, but does not give up when the learner gets stuck or makes a mistake. Ultimately, it provides a support system to solve math problems.

Meanwhile, the present invention is not a uniform progress for each learning unit, but a periodic learning plan that communicates with artificial intelligence to create a learning plan according to the learner's skills and learning history, and the learning amount and content are automatically calculated by inputting a specific test date and test preparation period. Provide a study plan that can be used.

In addition, the present invention provides a weak area strengthening unit that identifies and supplements weak areas calculated according to the learner's learning history in order to effectively acquire the vast mathematics subject content and produce the best learning results.

In addition, the present invention provides a system in which a 10-minute summary is generated and provided to the learner by summarizing the learning content so that the learner can review during the learning process and efficiently repeat weak parts.

As above, the problem-solving system section, lesson plan section, weak area strengthening section, and 10-minute summary section are linked together to manage each learner's individual learning, so that the learner's math problem-solving ability can be maximized very efficiently.

According to the present invention, 1) the learner strengthens weaknesses according to his/her learning data, efficiently repeats learning through a summary book, and learns according to an individual learning plan, so that the learner learns problem-solving methods and efficiently completes weak areas. Through the system, you can reach the best learning results you aim for.

2) By providing an individual learning curriculum according to the learner's learning history and plan and providing a system to supplement each learner's individual weaknesses, upward equalization of mathematics education can be achieved by providing the best customized learning even to learners who have difficulty receiving private education.

Figures 1 and 2 are conceptual diagrams for schematically explaining the entire system according to an embodiment of the present invention.

Figure 3 is shown in the form of a flowchart to schematically explain the learning modeling unit 200 according to an embodiment of the present invention.

Figures 4 and 5 are shown in the form of a flow chart to schematically explain the memorization enhancement modeling unit 300 according to an embodiment of the present invention.

Figures 6 and 7 are shown in the form of a flow chart to schematically explain the problem solving system unit 400 according to an embodiment of the present invention.

Figure 8 is an explanatory diagram explaining the n-step problem solving method.

Figure 9 is a reference diagram to increase understanding of the problem-solving ability of learners who have learned according to an embodiment of the present invention.

Hereinafter, embodiments will be described in detail with reference to the attached drawings. However, various changes can be made to the embodiments, so the scope of the patent application is not limited or limited by these embodiments. It should be understood that all changes, equivalents, or substitutes for the embodiments are included in the scope of rights.

1 and 2 are conceptual diagrams for schematically explaining the entire system according to an embodiment of the present invention.

According to an embodiment of the present invention, the mathematics learning system and method through artificial intelligence and online convergence are stored in the data collection unit 100 and the data collection unit 100, where data necessary for execution of the present invention is collected and stored. A learning modeling unit 200 in which a learning model is formed so that the learner can learn more efficiently through data, and a learning process that is managed so that the learner can obtain the best learning effect and results when learning according to the present invention. It is comprised of a learning management department (300).

The present invention does not simply present the learning content by the learning modeling unit 200 and allows the learner to proceed with the learning, but artificial intelligence provides the learning period, learning scope, and what the learner has learned according to the learner through the learning management unit 300. A system to identify and supplement vulnerabilities in records is also provided.

Referring to Figure 1, the data collection unit 100 in the present invention carefully selects, classifies, and stores data that should be derived as a result of executing the present invention. Data on the entire process of mathematics can be classified, collected, and obtained, but in particular, the order of mathematics and the detailed order are collected separately, expansion elements of concepts related to the systematicity of mathematics, mathematical terms, basic concept organizing formulas for each word, It includes formal derivation, proof theorem problems, etc., and the problem title (pattern, conditions given in the problem) for each type is matched with the core method of solving the problem (how to use the given conditions). and are organized and collected by level, and mathematical theories such as analysis, geometry, algebra, number history, and sequence are also organized and collected, and camera observation elements are also collected and stored as data.

The data collected and stored in the data collection unit 100 are the actual contents of the present invention, and if we look at the contents and characteristics of these data one by one, first, in the present invention, not only the mathematics problem or solution process, but also the title of the unit such as the table of contents of a mathematics textbook and the table of contents (table of contents), and more specifically, the detailed table of contents, are collected, stored, and utilized separately. By learning the mathematics sequence and the detailed sequence separately, learners can accurately identify where the unit they are learning belongs to and learn concepts and problems. When actually solving a math problem later, they can determine which unit the problem is from and which unit. This will be of great help in figuring out whether you need to use .

The expansion element of concepts related to the systematicity of mathematics refers to the nature of mathematics in which the content to be learned is sequential and progressive, and each step is connected. When the concept of the unit to be learned is stored, the systematicity on which the learning unit is based is stored. In the sense that the units are linked and stored together and provided to learners later, data that is an expansion element of concepts related to the systematicity of mathematics is collected and stored. Formula derivation, memorization, and proof organization problems are classified into beginner, intermediate, and advanced levels, and data are collected and presented to learners later. In the case of beginner level, which will be presented later, all proof processes, etc. are presented to be written down as is, and for intermediate level, important parts are presented as is. Blank spaces are provided in parentheses so that the learner can fill in the parentheses later, and in the advanced version, the data is saved so that the entire proof process and parts can be memorized and presented so that the learner can fill in the parts. In addition, a type-specific problem in which the title of the problem by type (pattern, conditions given in the problem) and the core method of solving the problem (how to use the given conditions) are matched means that the problem by type and the core method are grouped together and understood at the same time, and the learner memorizes them at the same time. When the types and solutions are initially collected in a way that encourages them to do so, they are collected at the same time and presented to the learner as a set when the present invention is implemented.

For example, the types and core methods for solving problems are stored and presented together as follows. The aspects of using conditions and conditions given in these problems will be explained in detail later in the Problem Solving System Department.

Condition (type) of identity

equation

is an identity for x, what is the value of ab for the constants a and b?

① -12 ② -6 ③ -3 ④ 3 ⑤ 6

Key ways to solve problems

ax+b =cx + d (a,b,c,d are constants) is the identity for x. The coefficients of x are the same and the constant terms are the same.

Solve as a=c, b=d.

Meanwhile, calculation problems refer to the calculation skills of all grades, and comprehensive problems refer to problems that end each unit.

The camera observation element collects information about the learner, and the learning attitude, behavioral history when solving math problems, and newly generated past questions are recognized and collected through the camera to form the data collection unit 100. The camera observation element allows the camera to observe the learner's learning attitude, such as facial expressions and gestures, to accumulate and collect individual learner data, and has the function of filming and storing the learner's questions or learning materials that need to be saved. In addition, the camera observation element can be created by filming the learner's solving process on the exercise book through a camera, and can also be created by using a tablet PC, cell phone, recognition pen, etc. connected to the Internet of Things.

The learning modeling unit 200 of the present invention is a place where each data is sorted according to the learning order and stage and created as a learning model so that the data in the data collection unit 100 can be formed into a learning model and provided to the learner. Figure 3 is a flowchart to increase understanding of the learning modeling unit 200 according to an embodiment.

Referring to Figure 3, the learning modeling unit 200 in the present invention is executed by the following process. It largely goes through the unit preparation stage and the unit learning stage, and when this is passed, it passes the problem solving stage and then unit summary. Learning is completed when you pass the comprehensive problem stage.

In the entire process of the learning modeling unit 200, the data collected in the data collection unit 100 are presented according to the learning order. Specifically, in the unit preparation stage, as a preparation stage for learning according to the systematicity of mathematics, students learn the order of mathematics, and then again. It is designed to learn detailed sequences, concepts related to the systematicity of mathematics, and then learn the basic terms and formulas of the unit. Mastering math turns is a part of learning the turns up to the unit you want to learn, with the ultimate goal of memorizing them. It is structured so that the learner can memorize the turns of the previous level. For example, in the case of high school students, the middle school level is It is designed so that you can memorize the order.

The detailed order is the step of memorizing the detailed order of the units related to the unit you want to learn in the unit preparation stage, and it consists of a table of contents that is more detailed than the table of contents in a mathematics textbook. The step of learning concepts related to the systematicity of mathematics is to introduce units with systematicity related to the unit you want to learn, understand the concepts, and then memorize them. At this stage, problems in which the tree diagrams of previously learned mathematics units are traditionally connected are presented, but problems in which concepts are expanded and combined may also be presented. In other words, after encountering problems that come out in combination with the unit you want to learn, you can be presented to study and memorize the related units again. In the structure of learning basic terms and formulas, the basic terms and formulas of mathematics learned before learning the unit are introduced and presented so that the learner can memorize them. While the unit preparation stage is a part of improving learning effectiveness by identifying the location of learning content based on the sequence, the unit learning stage is a stage of accurately learning the concepts of the unit.

The unit learning stage consists of the formula itself, how to derive the formula, how to prove it, and then memorize it, and is divided into beginner, intermediate, and advanced courses. The specific execution of the unit preparation stage and the unit learning stage is carried out according to the memorization enhancement modeling unit 210 in Figure 4.

In other words, the unit preparation stage, unit learning stage, and unit organizing stage are specifically provided in a way that trains the learner to master the learning content, memorize it, and then immediately use it in the problem-solving process later. For example, in mathematics, In the case of content related to the math turn list, after the content of the math turn list is provided, some parentheses are placed on the math turn content so that the learner can fill in the parentheses. Ultimately, the learner is asked to memorize and enter all the content so that the learner can complete the learning content. It is provided in the form of a memorization enhancement modeling unit 210 that allows you to completely acquire. This structure, which consists of putting content in parentheses and memorizing the content, acts like a problem location tracker that allows you to figure out which unit of which grade the problem is and how it is related to other units just by looking at the problem, and helps learners solve math problems when solving them. It will help you when making a plan.

In addition, the memorization enhancement modeling unit 210 presents the learning content as shown in Figure 4, confirms the learned content by inserting parentheses, and provides a final memorization step. At this time, the final memorization The steps that can be done can be saved separately so that the learner can use them when reviewing and provided to the learner at a later date.

Figure 5 shows the memorization enhancement modeling unit 210 of another embodiment, which is a method that can be specifically implemented in the unit learning stage. In particular, it concerns the process of deriving and memorizing formulas and proofs, and as mentioned above, the formula itself. , the method of deriving a formula and the method of proving it are divided into beginner, intermediate, and advanced courses. Beginner, intermediate, and advanced are divided by level into the process of deriving and understanding a formula or proof. Beginner is a process of taking notes while understanding. , The intermediate level consists of memorizing and recording certain parts using parentheses, and the advanced level consists of memorizing and recording all parts.

Figures 6 and 7 are explanatory diagrams displayed as flowcharts to explain one embodiment of the problem solving system unit 220.

The main characteristics of the problem-solving system unit 220 are that it is structured so that conditions and their use are always presented as a set, that the learner is presented in a way to interpret the problem and find a method by underlining it through a smart fan, etc., and that the artificial It is composed of problem-solving progressing through communication between intelligence and the learner.

The problem solving system unit 220 is the entire process applied when a mathematical problem is presented in the implementation of the present invention, and ensures that the conditions of the problem, the method of using the conditions, the type problem and the key solution method are presented simultaneously, and the camera observation element is This provides support to solve problems through communication between learners and artificial intelligence, and provides a system to practice by underlining problems. When learners encounter problems while learning through the present invention, they continuously practice by underlining key conditions and methods in the problem.

In the present invention, when learning is carried out by the learning modeling unit 200, a concept problem is first presented as a problem solving step, and the learner goes through a process of learning and solving the concept problem. Next, problems by type and key problem solving methods are presented. The problem is presented and goes through a process of solving it.

The problem-solving system unit 220 is configured to allow learners to solve problems on their own with the support of the camera observation element of the data collection unit 100, but supports the learner to ultimately solve the problem without giving up in areas where he or she gets stuck or makes mistakes. Provides a learner interactive system.

In addition, what is particularly characteristic of the problem solving system unit 220 is that, as shown in FIG. 6, problems by type and key methods for solving the problem are presented together. The learner's learning training according to this presentation method is designed so that the learner can understand the type and the core method of solving the problem according to each type at a glance and memorize them together. Accordingly, when the learner looks at the problem, the type and the core method of solving the problem of that type are designed to be memorized. You are trained to think of methods as a group. This applies to all mathematical problems presented in the present invention by ensuring that the conditions of the problem and the use of the conditions are presented not only by type but also in general.

The unit organization stage consists of learning the math sequence of the learned unit again as if it were the first time, learning the detailed sequence (table of contents), then checking concepts, terms, formulas, formula derivation, and proof, and learning the core methods of solving problems and problems by type. After passing this, the learning stage is completed through step-by-step comprehensive problems. The n-step problem solving method is applied to unit-specific comprehensive problems, and the n-step problem solving method is an algorithm that presents problems by increasing the level of convergence and difficulty.

The n-step problem solving method is applied to all cases of mathematical problems provided in the present invention. In the present invention, step-by-step problem solving such as a total of N steps is applied to the problem. In one embodiment, n step is set to 5 steps. In this case, level 1 refers to a problem of understanding the concept, formula, and proof, level 2 is a low-level application problem with only the problem expression changed, and level 3 includes systematicity integrated with other units. It is a problem, and level 4 refers to all types of problems that may arise in the unit, and level 5 presents application problems with high difficulty.

Meanwhile, the present invention is characterized in that it is further provided with a learning management unit 300, which includes data on the data collection unit 100 of the present invention, a learning modeling unit 200, a memorization reinforcement modeling unit 210, and a problem solving unit. It is a system that is linked to the system unit 220, uses data to create greater value, and manages learning so that learners can completely complete mathematics learning. Referring to Figures 1 and 2, the learning management unit 300 uses camera observation elements as basic data for data utilization, and applies the mathematics learning system in a personalized manner according to the characteristics of the learner to achieve the best learning effect. It enables questions and answers between AI and artificial intelligence, allows learners to communicate and solve problems with artificial intelligence, provides a learning system that strengthens learners' weak areas, informs them of their weak areas, and summarizes what they have learned in a short form. It provides a 10-minute summary generated by the 10-minute summary unit 310 that can be repeated within time, provides a system where learners and artificial intelligence can make a study plan together, and underlining problem analysis and formulating are strengthened. A system can be provided to share learning evaluation results, and individual learner data can be stored and reflected in the system.

Looking at it in more detail below, the 10-minute summary unit 310, which is a component of the learning management unit 300, stores and provides the information to be memorized by the learner in a short time. The 10-minute summary unit 310 ) can be divided into two parts. First, it is composed by editing the explanation of mathematics (table of contents), concepts, formulas, types of problems and key methods to solve them into a summary book, and second, the learner The parts that the learner needs to review according to the content and history of what the learner has learned from the learning modeling unit (200), the memorization reinforcement modeling unit (210), and the problem solving system unit (220) are created and provided as learning is performed. It is automatically collected, created, and organized. In other words, the 10-minute summary 310 is accumulated, spread, and aggregated as the learner's learning progresses, and a program that completes the learner's skills can be provided through the accumulated 10-minute summary. The 10-minute summary section 310 is configured so that the learner can complete one 10-minute summary section within 1 to 2 minutes after studying it at least once. When reviewing, if 100 summaries are provided, it takes about 10 minutes. It takes about 100 minutes to learn 1,000 summaries, and it is structured so that learners can quickly review the entire thing by skipping what they know well and advancing the time further.

The weak part strengthening unit 320, which is another component of the learning management unit 300, is a function to supplement the weak part if the learner does not pass the learning outcome evaluation during learning, and is repeatedly damaged during learning. When a defect is revealed, it is composed of a system that allows the entire systematic process corresponding to the missing part to be organized regardless of the grade. In addition, for students who are new to learning, it is organized from the basics to attributes through a test, so that normal learning can be achieved. This is an element that helps achieve this. The weak portion strengthening unit 320 is equipped to execute the learning step again if the score set at each learning step is not obtained in the evaluation presented according to the embodiment of the present invention, and finally, a method of interpreting the problem with an underline is learned. The weak part strengthening unit 320 is set and applied step by step until it is possible. In other words, a specific score is set according to the level of difficulty at each stage, so that if the specific score falls short, the process of each stage is repeated, and if the score exceeds a certain score, the next stage learning process can be executed.

In addition, when solving a problem while progressing through a unit study, the weak part strengthening unit 320 is executed even if the learner recognizes the need for more intensive supplementation during the statistical analysis process of artificial intelligence. The weak portion strengthening unit 320 is configured to relearn the entire unit selected as the weak portion, but the portions connected systematically can be configured to display the entire course from middle school to high school. The Weak Spot Strengthening Department (320) is also a program prepared for learners who lack basic learning, which is a problem in the current domestic mathematics education reality, or for students who have given up on mathematics subjects. When learners who lack basic learning begin math, they either give up learning math or experience difficulties in learning math due to the step-by-step systematicity of math. In the subject of mathematics, if your grades drop, it is not easy to raise them again, and even if you try to study again, you often give up soon due to the systematic nature of mathematics. However, if you accurately know and understand your weak areas and supplement them, you can achieve great results in a short period of time. Therefore, the weak area strengthening unit 320 of the present invention can be of great help to learners who lack basic learning or students who have given up on mathematics subjects. The weak area reinforcement learning unit 320 is presented in conjunction with the 10-minute summary unit 310. If you learn concepts, formulas, terms, etc. according to a system that quickly organizes them through the 10-minute summary unit 310, you will be able to improve your skills if you lack the basics. Students also gain a foundation for studying mathematics, making continuous learning possible. In addition, the weak part strengthening unit 320 is provided with an element that informs the learner of the weak part. The element that notifies the weak part is the part that the learner wants to learn when the weak part is derived according to the input learner information. This is an element that allows learners to focus their attention on weak areas by displaying a caution sign in front of a unit or a warning sign in front of a problem. An active improvement program is provided so that insufficient learning can be repeated by informing learners of their weak areas before starting a unit or solving problems.

The learning plan unit 330, which is a component of the learning management unit 300, is a schedule derived by artificial intelligence based on data input by the learner, and a periodic learning schedule is created for consistently learning every day according to the learning period, etc. It can be distinguished as a test purpose plan prepared ahead of tests such as midterm exams, final exams, end-of-year exams, mock exams, and scholastic ability tests.

In addition, the learning planning department (330) allows artificial intelligence and learners to communicate with each other and create a schedule based on statistics and analysis of learning materials and learning evaluations, including a 1-day plan, a 10-day plan, and a month's plan for each period. , a 100-day plan, etc. can be created, and a plan for stable learning progress can be made through a periodic plan. The periodic schedule first determines the progress of unit learning and is provided so that a plan can be made with artificial intelligence after identifying the learner's capabilities. In addition, the study schedule can be modified. Progress is checked on a daily, 10-day, and monthly basis, and the study schedule is checked with artificial intelligence according to accumulated and stored statistical results so that the study schedule can be modified. In addition, as a plan to achieve the goal, a plan for strengthening learning of weak areas through the weak area strengthening unit 320, a study plan for exam preparation, etc. are provided. Meanwhile, the 10-minute summary unit 310 is executed in conjunction with the study plan unit 330, and the 10-minute summary unit 310 is important for both periodic study plans and purposeful study plans. The 10-minute summary section 310 is developed into a collection of 10-minute summaries according to the learner's learning progress. It is executed along with a periodic schedule, so the learning time is shortened when reviewing, and it is determined how many of the collection of 10-minute summaries will be studied per day. Goals are created through a periodic learning schedule. After one unit is completed, repeated learning for each unit can be provided, and a plan can be made based on artificial intelligence and evaluation of learning achievement. In addition, the learning schedule with a purpose is especially linked to the weak area strengthening unit 320. If you learn according to the flow chart in weak area reinforcement learning, you can learn according to the periodic learning plan, but if you are not a learner who has studied consistently, set a progress appropriate for the learner's level through a test and the purpose is when you start learning. The study plan provided is used. In addition, it is possible to set a period for learning the basic course and proceed with the study according to the period by using a study schedule with a purpose. When preparing for exams such as midterm exams, final exams, end-of-year exams, mock exams, and college entrance exams, artificial intelligence creates a purposeful study plan considering the learner's grades and learning ability and provides a system to achieve the best results in the exam. For example, a 10-minute summary to be read the day before the CSAT, a 10-day plan before the CSAT, a 100-day plan before the CSAT, a 1-year plan before the CSAT, etc., so that you can establish a plan by setting the necessary parts with a purpose.

The learning planning unit 330 is applied in the implementation of the present invention. For example, the learning modeling unit 200 forms one cycle for each unit, but when the test scope and test characteristics are specified and entered, the midterm exam, Like the final exam, year-end exam, mock test, and scholastic ability test, the test scope becomes one cycle, and the unit preparation stage, unit study stage, communication problem solving stage, unit organization stage, and step-by-step comprehensive problem stage are each configured to fit the test scope. When the test scope, type, and period are set, a new cycle is formed accordingly, and the result of the learning modeling unit 200 is newly created according to the test period, such as 100 days, 1 month, 10 days, and the last day, and the test range and type. This allows the learner to learn very effectively. In particular, in the case of tests such as the Scholastic Ability Test, which are broad and burdensome to learners, many courses can be effectively organized and studied in a short period of time through the customized cycle process of the learning modeling unit 200, enabling very effective learning. In this way, the 10-minute summary unit 310, the weak area strengthening unit 320, and the learning plan unit 330 operate in conjunction with each other, and as they are provided together and systemized, the effect of the present invention is optimally realized.

Meanwhile, the above-mentioned problem solving system unit 220 is applied in the entire problem solving process of the present invention, and provides underlining and interpretation, formulating, given conditions and methods of using the given conditions as a set, artificial intelligence and learner. It can be characterized as including components that communicate and solve problems. In particular, underlining and interpreting and formulating formulas allow learners to underline the problem, interpret it, and build formulas based on it when solving a problem. It refers to the components that require training. To solve a mathematical problem, you have to establish an equation, and to establish an equation, you have to interpret the conditions given in the problem. If the learner, the interpreter, does not systematize and learn how to interpret the problem, the solution may not be found, or even if it is found, it will take time. It takes a lot of time and you won't be able to get a high score on the test. In order to solve this problem, the present invention narrows the scope of mathematics to learners based on problem-solving methods trained through the 10-minute summary section and the weak area strengthening section of the lesson plan, utilizes data, and underlines the problem. As the method of interpretation is presented and provided to the learner so that the problem can be solved in that way, the problem-solving system section (220) also provides the 10-minute summary section (310) of the learning management section (300), strengthening weak areas. It is provided in conjunction with the study plan unit 320 and the study plan unit 330 to obtain the best learning effect.

Figure 9 is an explanatory diagram illustrating an example of the problem-solving ability formed in the learner's brain when learning is continuously performed according to the present invention.

My data unit 400 stores the total and partial statistical processing of the learner's learning contents. This is fed back to the data collection unit and used to identify the learner's current learning contents, study schedule, and progress. , it is used in connection with sexual situations, vulnerable areas, etc.

In addition, the reward system unit 500 is designed to increase students' motivation to learn. For example, when they pass the comprehensive problem solving stage and move to a higher category or when the goal of the study schedule is achieved or exceeded, rewards are awarded in cyber money according to cyber money. This compensation system unit 500 may be further provided to enable the purchase of products.

Below, the steps in which mathematics learning is performed through the artificial intelligence and online convergence mathematics learning and management system according to an embodiment of the present invention will be described.

Learning content is provided to the learner by the learning modeling unit 200, which is generated through machine learning using the data from the data collection unit 100.

As the learner progresses through learning by the learning modeling unit 200, the learning management unit 300 is formed by operating the learning contents recorded. The 10-minute summary unit 310 of the learning management unit 300 is formed within the scope completed by the learner. It is extracted and stored.

In addition, the learning management unit 300 operates together according to the learning contents recorded while learning by the learning modeling unit 200, and a weak area strengthening unit 320 is formed in the area where the learner entered an incorrect answer, and the learner learns. When progressing, learning management is carried out to eliminate weak areas by presenting them repeatedly. At this time, the process of reviewing the weak parts involves reinforcement learning so that the summary generated in the 10-minute summary unit 310 can be memorized.

Meanwhile, when the learner inputs the test date and test scope in connection with the study plan 330 of the learning management unit 300, the 10-minute summary section 310 and the weak area strengthening section within the test range during the period up to the set test date and time. (320) is formed, and the learning content within the test scope is repeated so that one's weaknesses can be strengthened very efficiently during the test period, resulting in the best learning management and effectiveness.

Meanwhile, in the present invention, the problem solving system unit 220, which can practice problem interpretation with underlining, is continuously provided when solving problems during the execution process of the present invention. It provides an explanation of how artificial intelligence interprets problems and helps the learner. The problem is interpreted by underlining, and the learner receives feedback as the artificial intelligence evaluates and guides the part underlined by the learner. In accordance with the implementation of the present invention, the learner repeats this process countless times to underline the problem. You learn how to interpret by drawing.

The method of inputting mathematical data into the learner's mind is that the 10-minute summary unit (310), the weak area strengthening unit (320), and the lesson plan unit (330) are linked together to proceed smoothly, and the learning materials are entered into the learner's mind at the same time. The effectiveness of learning mathematics is further maximized by practicing underlining and interpreting problems. In other words, the method by which mathematical data (data for interpreting problems) are input into the learner's head is the 10-minute summary unit (310), the weak area strengthening unit (320), the study plan (330), and the problem-solving system unit (220). ), the methods provided to practice text analysis are deeply connected to each other, and the effect of the invention is maximized.

The present invention can be used in the field of learning using artificial intelligence.

Claims

A data collection unit 100 where data is collected and stored;

A learning modeling unit 200 in which a learning model is formed through data stored in the data collection unit 100;

A mathematics learning system through artificial intelligence and online convergence, which includes a learning management unit 300 that manages the learning process when learning progresses through the learning modeling unit 200.
According to paragraph 1,

The learning modeling unit 200 includes a memorization reinforcement modeling unit 210 that allows the learner to completely acquire the learning content by having the learner memorize and input the content after the content is provided. When a math problem is presented, the type problem and the key solution are provided. The method is provided at the same time, and the data from the data collection unit 100 collected through camera observation supports communication between the learner and artificial intelligence to solve the problem, and provides a system that allows practice by underlining the problem. A mathematics learning system through artificial intelligence and online convergence, characterized in that it further includes a problem solving system unit 220.
According to paragraph 1,

The learning management unit 300 is configured to apply the mathematics learning system in a personalized manner according to the characteristics of the learner using the materials in the data collection unit 100, and is generated according to the content and history of the learner's learning and allows the learner to use the materials in a short period of time. A mathematics learning system through artificial intelligence and online convergence, characterized by including a 10-minute summary section 310 in which matters to be memorized are stored and provided to the learner.
According to paragraph 1,

The learning management unit 300 is created according to the learner's learning content and history, and is designed to supplement weak areas if the learner fails to pass the learning result evaluation that appears during learning, so that the learner can inform the learner of the weak areas and focus on them. A mathematics learning system through artificial intelligence and online convergence, characterized in that it includes a weak part strengthening unit 320 that allows the learner to repeatedly learn weak parts before starting unit study or before starting problem solving.
According to paragraph 1,

The learning management unit 300 is an artificial intelligence system that includes a learning planning unit 330 that allows the artificial intelligence and the learner to communicate with each other and create a schedule based on statistics and analysis of the learner's learning materials and learning evaluation. and a mathematics learning system through online convergence.
According to paragraph 1,

The learning management unit 300 is a mathematics learning system through artificial intelligence and online convergence, characterized in that the 10-minute summary unit 310, the weak area strengthening unit 320, and the learning planning unit 330 are linked and systemized together.
According to clause 1,

In the mathematics learning and management system through artificial intelligence and online convergence, it includes a data collection unit (100), a learning modeling unit (200), and a learning management unit (300),

A mathematics learning system characterized by further comprising a my data unit (400) that stores the total and partial statistical processing of the learner's learning contents and a reward system unit (500) provided to increase students' learning motivation.
A learning modeling unit 200 formed through machine learning is provided through the data collection unit 100;

As the learning modeling unit 200 is executed, the learner's learning history is recorded to form a 10-minute summary unit 310 and a weak portion strengthening unit 320; a math learning system through artificial intelligence and online convergence including How to learn mathematics through.
According to clause 8 above,

It further includes a step of forming a learning plan unit 330 that is created and operated according to the learning period and learning scope entered by the learner,

Mathematics learning through artificial intelligence and online convergence and mathematics learning and management system provided to learners by the 10-minute summary department (310) and the weak area strengthening department (320) according to the period and learning scope of the learning planning department (330). method