KR102284502B1 - Method for operating learner guiding service, system and computer-readable medium recording the method - Google Patents

Abstract

The present invention relates to a method of operating a learner orientation correction service using at least one learner terminal and a computer system having a server computer connected through a network, and provides information on passing student propensity related to propensity of past pass model and past rejection model. receiving disqualification information related to disposition; receiving learner propensity information related to learner propensity of the learner from the learner terminal; generating matching information that matches disposition information of a past passed student model or a failed student model similar to the learner disposition information among the passed student disposition information or the failed student disposition information; and the learner's learning propensity is similar to the learning propensity of the past pass student model as compared with the pass student propensity information of the matched past pass student model, or the learner learns by comparing it with the failing propensity information of the matched past pass student model transmitting learning propensity correction information capable of correcting the learner's learning propensity to the learner terminal so that the propensity is similar to the learning propensity of the past failure model.

Description

Method for operating learner guiding service, system and computer-readable medium recording the method}

The present invention relates to a method and system for operating a learner disposition correction service, and a computer-readable recording medium recording the method, and more particularly, referring to both passed and failed students according to the pass result, the learner's behavioral propensity It relates to a method and system for operating a learner disposition correction service that analyzes and corrects the learner's learning disposition and behavioral disposition, and a computer-readable recording medium in which the method is recorded.

In general, information analysis-based education systems may generate various information meaningful for learning from academic information.

These information analysis-based education systems have been maintained since the days when computerization was insignificant in the past, and various devices have been developed at present, and various information other than studies are naturally generated and accumulated.

For example, with a wearable device (smartwatch, etc.), heart rate, sleep pattern, daily step count, location information, etc. can be obtained in real time, and students who can obtain through personality type questionnaire and current self-emotion report Psychological information of students and emotional state detection through real-time facial expression analysis, etc., which are not directly related to education, but are complexly more meaningful than academic information when accumulated, can be extracted.

However, there was a problem in that various information other than the study was discarded as it was because there were no proper methods to analyze it.

On the other hand, recently, various services are provided using various smart devices including smart phones, communication networks, or the Internet, and using computer networks that interconnect a huge number of computers and these computers not only in a short distance through communication links but also worldwide. can be

Interconnected computers in association with various smart devices can exchange information with each other using various services, such as e-mail, gopher, and the World Wide Web (WWW). The World Wide Web may allow a server computer system (eg a web server or website) to send graphical web pages of information to a remote client computer system.

Such a remote client computer system may display various screens received from the server computer in the form of a work screen or a web page.

Meanwhile, recently 2G, 3G, 4G, 5G, LTE, etc. mobile communication networks, WIFI communication networks, Bluetooth communication networks, cellular networks, CDMA networks, LTE networks, Ethernet networks, WiMAX networks, local area networks (LANs), wide area networks (WANs), RF As wireless communication networks, such as communication networks, infrared communication networks, and optical communication networks, have developed rapidly, various services are being developed using such wireless communication networks.

Laid-open Patent Publication No. 10-2013-0040373 (2013.04.24.) Registered Patent Publication No. 10-1318562 (2013.10.16.)

The present invention is intended to solve various problems including the above problems, and it is possible to comprehensively analyze a wide variety of disposition information such as the learner's learning propensity and learning content, as well as behavioral propensity other than learning, and the learner's disposition and By matching the most similar pass and fail models, it is possible to provide the best customized learning propensity and behavioral propensity correction information that can be helpful to learners in real time. A method and system for operating a learner propensity correction service that can perform high value-added education and learning services that cannot be provided by educational institutions, and greatly enhance security using distributed ledger technology, and this method An object of the present invention is to provide a computer-readable recording medium. However, these problems are exemplary, and the scope of the present invention is not limited thereto.

A method of operating a learner orientation correction service according to an idea of the present invention for solving the above problem is a method of operating a learner orientation correction service using a computer system having at least one learner terminal and a server computer connected through a network In the method, the method comprising: receiving information on the tendency of accepted students related to the tendency of the past passed model and the disposition information of the rejected students related to the tendency of the past model of the unsuccessful students; receiving learner propensity information related to learner propensity of the learner from the learner terminal; generating matching information that matches disposition information of a past passed student model or a failed student model similar to the learner disposition information among the passed student disposition information or the failed student disposition information; and the learner's learning propensity is similar to the learning propensity of the past pass student model as compared with the pass student propensity information of the matched past pass student model, or the learner learns by comparing it with the failing propensity information of the matched past pass student model transmitting learning propensity correction information capable of correcting the learner's learning propensity to the learner terminal so that the propensity is similar to the learning propensity of the past failure model.

On the other hand, in the method of operating a learner orientation correction service according to the spirit of the present invention for solving the above problem, the learner orientation correction service is operated using a computer system having at least one learner terminal and a server computer connected through a network. In this method, the server computer comprises: a pass/fail student propensity information input program for receiving pass student propensity information related to propensity of the past pass model and failing propensity information related to propensity of the past failing model, learner from the learner terminal A learner propensity information input program that receives learner propensity information related to the learner propensity of A matching program that generates information, compared with the passed student propensity information of the matched past pass student model, the learner's learning propensity is similar to the learning propensity of the past pass student model, or the failed student propensity information of the past failed model matched A learning propensity correction information transmission program that transmits learning propensity correction information capable of correcting the learner's learning propensity to the learner terminal so that the learner's learning propensity is similar to the learning propensity of the past unsuccessful model by comparison, the pass student propensity A passing student propensity information database storing information, a failing student propensity information database storing the failing student propensity information, a learner propensity information database storing the learner propensity information, a matching information database storing the matching information, and the learning propensity correction information includes a learning propensity correction information database to be stored; receiving input; (b) receiving, by the learner propensity information input program, learner propensity information related to the learner propensity of the learner from the learner terminal; (c) generating, by the matching program, matching information that matches disposition information of a past passed student model or a failed student model similar to the learner disposition information among the passed student disposition information or the failed student disposition information; and (d) a past rejected student model in which the learner's learning propensity is similar to or matched with the learning propensity of the past pass student model by comparing with the pass student propensity information of the matched past pass student model by the learning propensity correction information transmission program Transmitting learning propensity correction information capable of correcting the learner's learning propensity to the learner terminal so that the learner's learning propensity is similar to the learning propensity of the past failed student model compared with the failing student propensity information of may include

In addition, according to the present invention, the matching information includes at least past pass student information with similar or identical initial learning achievement by comparing statistics, past failed student information with similar or identical initial learning achievement information, past passed student information with similar or identical learning method, Information on past rejected students with similar or identical learning methods, information on past accepted students with similar or identical integrity, information on past failed students with similar or identical integrity, information on past accepted students with similar or identical willpower, information on past failed students with similar or identical willpower, planning By selecting any one or more of this similar or identical past passed student information, past rejected student information with similar or identical planning, past passed student information with similar or identical goal consciousness, past failed student information with similar or identical goal consciousness, and combinations thereof, can be done

In addition, according to the present invention, the server computer transmits pass and fail propensity information for transmitting the pass student propensity information of the matched past pass student model or the fail pass propensity information of the matched past pass student model to the learner terminal The program further comprises, before the step (d), (e) by the passing and failing student tendency information transmission program, the passed student tendency information of a matched past passed student model or the failure of the matched past failed student model It may further include; transmitting the biopropensity information to the learner terminal.

Also, according to the present invention, the passed student propensity information includes any one or more of learning propensity information related to learning of the passed student model based on average statistics, learning content information related to learning content, and combinations thereof, and the failing The life propensity information may include any one or more of learning propensity information related to learning of the failing model based on average statistics, learning content information related to learning content, and combinations thereof.

In addition, according to the present invention, the learning propensity information includes at least learning period information for a specific test, content understanding method information, content memorization method information, learning time zone information such as morning/am/pm/evening/dawn, learning time/learning It can be made by selecting any one or more of conscientiousness information, such as whether concentration time / scrap time is used / break time / plan practice / repeated learning, etc., learning location information, study group information, and combinations thereof.

In addition, according to the present invention, the learning content information includes at least initial learning achievement information such as level test results, mock test information, problem solving information, note test information, video viewing information, detailed learning topic information, difficulty information for each question, problem It may be made by selecting any one or more of type information, score information for each subject, incorrect answer note information, and combinations thereof.

Also, according to the present invention, the passed student propensity information includes behavioral propensity information related to behavioral information other than learning of the passed student model based on average statistics, and the failing student propensity information includes the failed student model based on average statistics. includes behavioral tendency information related to behavioral information other than the learning of Willpower information such as the number of beginning of the year/number of close friends meeting, planning information such as meal times/snacks/bedtime/percentage of planning execution/number of weekly exercise, integrity information such as percentage adherence to appointment time/percentage absent/percent tardy, disease status/type of disease, etc. Select any one or more of health status information, occupational consciousness information such as occupational awareness/vocational sense of duty value, goal awareness information such as goal setting/goal achievement percentage, personality information such as calm/hurried/hot-tempered/question-solving values, and combinations thereof can be done by

In addition, according to the present invention, the learning disposition correction information includes at least learning difference information indicating a learning difference between the learner and the passed student model or the failing model with a numerical value or degree, and a learner learning disposition change indicating a change in the learner's learning disposition. Information, pass and failed students learning disposition change information indicating a change in the learning propensity of the passed student model or the failing model, learning proposal or learning recommendation information for the learner, and combinations thereof may be selected. .

In addition, according to the present invention, the server computer compares the pass student propensity information of the matched past pass student model, and the learner's behavioral propensity is similar to the behavioral propensity of the past pass student model or the failure of the matched past failed student model Behavioral tendency correction information transmission program for transmitting behavioral orientation correction information capable of correcting the learner's behavioral orientation to the learner terminal so that the learner's behavioral orientation is similar to that of the past failed student model compared with the lively orientation information , a behavioral tendency correction information database in which the behavioral tendency correction information is stored, and before or after the step (d), (f) by the behavioral tendency correction information transmission program, the passed student tendency of the past passed student model matched by the program Compared with the information, the learner's behavioral propensity is similar to or matched with the behavioral propensity of the past passed student model. It may further include; transmitting behavioral tendency correction information capable of correcting the behavioral tendency of the learner to the learner terminal so as to be dead.

In addition, according to the present invention, the behavioral tendency information includes at least sleep time / waking time / cell phone use time / internet use time / game time / drinking / dating the opposite sex / smoking / smoking seconds / number of close friends, etc. willpower information, planning information such as meal time/snacks/bedtime/percent of planned practice/number of weekly exercise, conscientiousness information such as appointment time adherence percentage/absence percentage/percent tardy, health status information such as disease status/type of disease, occupational consciousness/occupation Job consciousness information such as sense of duty value, goal awareness information such as goal setting/goal achievement percentage, personality information such as calm/urgent/hot-tempered/question-solving values, and combinations thereof are selected and the behavioral tendency is corrected The information includes, at least, behavioral difference information indicating a numerical or degree difference in behavior between the learner and the passed student model, learner behavioral tendency change information indicating a change in the learner's behavioral tendency, and passed student behavioral change information indicating a behavioral change of the passed student model , it may be made by selecting any one or more of action suggestion or action recommendation information for the learner, and combinations thereof.

In addition, according to the present invention, the pass/fail student tendency information input program includes a learner tendency information input program that receives learner tendency information related to a learner's learner tendency from the learner terminal, and the learner's information from the learner terminal or the operator terminal. A pass result information input program that receives pass result information for a pass result, a correlation analysis program that calculates analysis information by analyzing the correlation between the learner propensity information of the learner and the pass result information, the learner propensity information a learner propensity information database to be stored, a pass result information database to store the pass result information, and an analysis information database to store the analysis information, wherein the step (a) includes: (a-1) the learner propensity information input program receiving learner tendency information related to the learner's learner's orientation from the learner's terminal; (a-2) receiving pass result information on the pass result of the learner from the learner terminal or the operator terminal by the pass result information input program; (a-3) analyzing the correlation between the learner propensity information of the learner and the pass result information of the learner by the correlation analysis program to calculate analysis information;

In addition, according to the present invention, the learner tendency information is at least one of learning tendency information related to learning, behavioral tendency information related to behavior other than learning, learning content information related to learning content, and combinations thereof. The learning tendency information is, at least, learning period information for a specific test, content understanding method information, content memorization method information, learning time zone information such as morning / morning / afternoon / evening / dawn, learning time / study concentration time / scraps It is made by selecting any one or more of sincerity information such as whether time is used / rest time / plan practice / repeated learning, learning place information, study group information, and combinations thereof, and the behavioral tendency information is at least sleep time / Wake-up time/cell phone use time/internet use time/game time/drinking/experience of the opposite sex/smoking status/smoking the number of seconds of smoking/number of close friends meeting etc. Planning information such as number of times, conscientiousness information such as appointment time compliance percentage/absence percentage/percent tardy, health status information such as disease status/type of disease, occupational consciousness information such as occupational awareness/vocational sense of duty, goal setting/goal achievement percentage, etc. Information, personality information such as calm/urgent/hot-tempered/curious questions, etc., and any one or more of combinations thereof is selected, and the learning content information includes at least initial learning achievement information such as level test results, mock test information, problems It may be made by selecting any one or more of solution information, note test information, video viewing information, detailed learning topic information, difficulty information for each question, question type information, score information for each subject, incorrect answer note information, and combinations thereof.

In addition, according to the present invention, the pass result information includes at least information on passed students who can be given a benefit according to passing, information about students who have failed to receive a retake opportunity or discount benefits due to failure, and longevity students who have not passed for more than N years. It can be made by selecting any one or more of information, information about students who have not been learning for more than M years, and combinations thereof.

In addition, according to the present invention, the correlation analysis program of the server computer, a quantification program for scoring or quantifying the learner tendency information of the learner; a change factor determination program for determining a change factor by analyzing the learner's score or quantitative numerical change; and a pass probability prediction program for predicting the passability of the learner according to the variation factors based on the pass result information for each type of learner in the past, wherein the step (a-3) includes, (a-3-1) ) scoring or quantifying the learner tendency information of the learner by the quantification program; (a-3-2) determining the change factor by analyzing the change in the learner's score or quantitative numerical value by the change factor determination program; and (a-3-3) estimating the passability of the learner according to the variation factor based on the pass result information for each type of learner in the past by the pass probability predicting program.

On the other hand, a system for operating a learner orientation correction service according to the spirit of the present invention for solving the above problem operates a learner orientation correction service using a computer system having at least one learner terminal and a server computer connected through a network In the following system, the server computer comprises: a pass/fail student propensity information input program for receiving pass student propensity information related to the propensity of the past pass model and failing propensity information related to the propensity of the past failing model, and a learner from the learner terminal A learner propensity information input program that receives learner propensity information related to the learner propensity of A matching program that generates information, compared with the passed student propensity information of the matched past pass student model, the learner's learning propensity is similar to the learning propensity of the past pass student model, or the failed student propensity information of the past failed model matched A learning propensity correction information transmission program that transmits learning propensity correction information capable of correcting the learner's learning propensity to the learner terminal so that the learner's learning propensity is similar to the learning propensity of the past unsuccessful model by comparison, the pass student propensity A passing student propensity information database storing information, a failing student propensity information database storing the failing student propensity information, a learner propensity information database storing the learner propensity information, a matching information database storing the matching information, and the learning propensity correction information includes a learning propensity correction information database to be stored, and by the pass and fail propensity information input program, pass student propensity information related to the propensity of the past pass model and reject student propensity information related to the propensity of the past failing model is inputted , by the learner propensity information input program, the learner propensity and the learner propensity from the learner terminal Receives related learner disposition information, and generates matching information that matches disposition information of a past passed student model or a failed student model similar to the learner disposition information among the passed student disposition information or the failed student disposition information by the matching program and, by the learning propensity correction information transmission program, the learning propensity of the learner is similar to or matched with the learning propensity of the past pass student model in comparison with the pass student propensity information of the matched past pass student model. Comprising a control unit programmed to transmit learning propensity correction information capable of correcting the learner's learning propensity to the learner terminal so that the learner's learning propensity is similar to the learning propensity of the past failed student model compared with the failing propensity information can do.

On the other hand, a computer readable recording medium recording a method of operating a learner disposition correction service according to the spirit of the present invention for solving the above problem is a computer system having at least one learner terminal and a server computer connected through a network In a computer-readable recording medium recording a method of operating a learner disposition correction service using Passing and failing propensity information input program for receiving information, a learner propensity information input program for receiving learner propensity information related to learner propensity from the learner terminal, the learner from among the pass student propensity information or the failing propensity information A matching program that generates matching information that matches the disposition information of the past passed student model or the disqualified model similar to the disposition information The learner's learning propensity can be corrected with the learner terminal so that the learner's learning propensity is dissimilar to the learning propensity of the past failing model by comparing it with the failing student propensity information of the past failed student model that is similar to or matched with A learning propensity correction information transmission program that transmits learning propensity correction information, a pass student propensity information database in which the passed student propensity information is stored, a failing student propensity information database in which the failing student propensity information is stored, and a learner propensity in which the learner propensity information is stored an information database, a matching information database in which the matching information is stored, and a learning tendency correction information database in which the learning tendency correction information is stored; receiving information on the disposition of accepted students and disqualification information related to the disposition of the past failed model; (b) receiving, by the learner propensity information input program, learner propensity information related to the learner propensity of the learner from the learner terminal; (c) generating, by the matching program, matching information that matches disposition information of a past passed student model or a failed student model similar to the learner disposition information among the passed student disposition information or the failed student disposition information; and (d) a past rejected student model in which the learner's learning propensity is similar to or matched with the learning propensity of the past pass student model by comparing with the pass student propensity information of the matched past pass student model by the learning propensity correction information transmission program Transmitting learning propensity correction information capable of correcting the learner's learning propensity to the learner terminal so that the learner's learning propensity is similar to the learning propensity of the past failed student model compared with the failing student propensity information of may include

According to various embodiments of the present invention made as described above, it is possible to comprehensively analyze a wide variety of disposition information, such as a learner's learning tendency or learning content, as well as a behavioral tendency other than learning, and is most similar to the learner's disposition. By matching the passing model and the non-passing model, it is possible to provide the optimal customized learning propensity and behavioral propensity correction information that can be helpful to learners in real time. It is possible to perform high value-added education and learning services that cannot be provided by , and has the effect of greatly enhancing security by using distributed ledger technology. Of course, the scope of the present invention is not limited by these effects.

1 is a conceptual diagram illustrating a system for operating a learner disposition correction service according to some embodiments of the present invention.
FIG. 2 is a block diagram showing in more detail a program for inputting information about passing student propensity in a system for operating the learner propensity correction service of FIG. 1 .
FIG. 3 is a block diagram illustrating in more detail a correlation analysis program of the program for inputting information about passing student propensity of FIG. 2 .
4 is a schematic diagram illustrating a relationship between an operator who operates a learner disposition correction service of the present invention and a learner.
5 is a flowchart illustrating a method of operating a learner disposition correction service according to some embodiments of the present invention.
6 is a flowchart illustrating in more detail step (a) of the method of operating the learner disposition correction service of FIG. 5 .
7 is a flowchart illustrating a method of operating a learner disposition correction service according to some other embodiments of the present invention.
8 is a conceptual diagram illustrating a system for operating a learner disposition correction service according to some other embodiments of the present invention.
9 and 10 are diagrams illustrating an example of a screen provided by a learner disposition correction service according to some embodiments of the present invention.

Hereinafter, several preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

Examples of the present invention are provided to more completely explain the present invention to those of ordinary skill in the art, and the following examples may be modified in various other forms, and the scope of the present invention is as follows It is not limited to an Example. Rather, these embodiments are provided so as to more fully and complete the present disclosure, and to fully convey the spirit of the present invention to those skilled in the art. In addition, in the drawings, the thickness or size of each layer is exaggerated for convenience and clarity of description.

The terminology used herein is used to describe specific embodiments, not to limit the present invention. As used herein, the singular forms may include the plural forms unless the context clearly dictates otherwise. Also, as used herein, “comprise” and/or “comprising” refers to the presence of the recited shapes, numbers, steps, actions, members, elements, and/or groups of which are specified. and does not exclude the presence or addition of one or more other shapes, numbers, movements, members, elements and/or groups.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described with reference to the drawings schematically illustrating ideal embodiments of the present invention. In the drawings, variations of the illustrated shape can be expected, for example depending on manufacturing technology and/or tolerances. Accordingly, embodiments of the spirit of the present invention should not be construed as limited to the specific shape of the region shown in the present specification, but should include, for example, changes in shape caused by manufacturing.

Hereinafter, a method and system for operating a learner disposition correction service according to some embodiments of the present invention, and a computer-readable recording medium recording the method will be described in detail with reference to the drawings.

1 is a conceptual diagram illustrating a system for operating a learner disposition correction service according to some embodiments of the present invention.

First, as shown in FIG. 1 , a system for operating a learner disposition correction service according to some embodiments of the present invention is largely a learner terminal 10 , a learning content provider terminal 20 , and an operator terminal 90 . and a server computer 60 connected through the network 50 .

Here, the server computer 60 receives the pass student propensity information related to the propensity of the past passed student model and the failed student propensity information related to the propensity of the past failing model, and receives the pass student propensity information related to the learner propensity of the learner from the learner terminal 10 receiving learner disposition information, generating matching information that matches disposition information of a past passed student model or a failed student model similar to the learner disposition information among the passed student disposition information or the disqualified student disposition information, and matching the past passed student model Compared with the passed student propensity information of It is programmed to transmit learning propensity correction information that can correct the learner's learning propensity to the learner terminal 10 so as to be similar to the learning propensity of the learner propensity correction service can be operated through the network 50 It may be a computer provided in an institute, a company, a factory, a business entity, a head office, a branch office, a sales office, an agency, a data center, or the like.

In addition, for example, the learner terminal 10 is, through the system of the present invention, a student, academy student, trainee, trainee, public examination student, examinee, test preparation student, etc. It may be a terminal.

Here, the learner terminal 10 is not necessarily limited to a computer, and all information terminal devices capable of processing various types of information may be applied. For example, not only various smart phones, but also various wearable devices, smart sensors, smart pads, smart watches, mobile terminals, PDAs, laptops, laptop computers, smart cameras, smart camcorders, e-books, smart scanners, etc. are all can be applied.

In particular, when using a wearable device, the heart rate and sleep pattern of the learner wearing the wearable device, the number of steps taken per day, location information, etc. are available in real time Although it is not directly related to education, such as psychological information and emotional state detection through real-time facial expression analysis, it is possible to extract and use student information that is more meaningful than academic information in a complex way when it is accumulated.

In addition, for example, the learning content provider terminal 20 is, through the system of the present invention, lectures, video lectures, questions, exam papers, etc., lecturers, professors, private institutes, companies, etc. who want to provide various learning contents, etc. It may be a terminal or computer provided in a factory, a business entity, a head office, a branch office, a sales office, an agency, a data center, or the like.

Here, the learning content provider terminal 20 is not necessarily limited to a computer, and all information terminal devices capable of processing various types of information may be applied. For example, not only various smart phones, but also various wearable devices, smart sensors, smart pads, smart watches, mobile terminals, PDAs, laptops, laptop computers, smart cameras, smart camcorders, e-books, smart scanners, etc. are all can be applied.

Also, for example, the operator terminal 90 is a terminal of an individual or company, factory, business, central office, headquarters, branch, sales office, or computerized person who manages and operates the server computer 60 . As a computer, it is not necessarily limited to a computer or a smartphone, and various information terminals, PDAs, smart watches, smart pads, cameras, Camcorders, notebook computers, laptop computers, e-books, personal computers, other server computers, and the like can all be applied.

Meanwhile, as shown in FIG. 1 , the learning content provider terminal 20 and the operator terminal 90 are not necessarily independently provided, for example, the learning content provider terminal 20 and the operator terminal 90 . ) is also possible.

In addition, for example, the learner terminal 10 of FIG. 1 , the learning content provider terminal 20 , the operator terminal 90 and the server computer 60 are installed with various applications, apps, hybrid apps, programs, etc. Thus, the terminals are connected to each other through the network 50, and the terminals connected by the network 50 are conventional 2G, 3G, 4G, 5G, LTE, etc. mobile communication networks, WIFI communication networks, Bluetooth communication networks, cellular networks, CDMA Communication networks such as communication network, LTE communication network, Ethernet communication network, WiMAX communication network, local area network (LAN), wide area network (WAN), RF communication network, infrared communication network, and optical communication network can be used as well as HTML, XML, HTML5, etc. It may have an Internet browser (Netscape, Internet Explorer, etc.) that can display web contents with the Internet browser, or a protocol device for internal or external or local/long-distance wired/wireless network access.

Meanwhile, as shown in FIG. 1 , the server computer 60 may include a program control unit PG for controlling a program and a database DB for storing various types of information.

In particular, the program control unit PG inputs registration application information from the main program 61 operating the entire program, the learner terminal 10 or the learning content provider terminal 20 as shown in FIG. 1 . A member registration program 62 that receives and registers as a member, a login program 63 that receives login information from the learner terminal 10 or the learning content provider terminal 20, passed student propensity information related to the propensity of the past passed student model, and Passing and failing student propensity information input program 64 that receives disqualification propensity information related to the propensity of the past failing model, and learner propensity information input that receives learner propensity information related to the learner propensity from the learner terminal 10 Program 65, a matching program 66 for generating matching information that matches disposition information of a past passed student model or a failed student model similar to the learner propensity information among the passed student disposition information or the failed student disposition information; Compared with the passed student propensity information of the past passed student model, the learner's learning propensity is similar to the learning propensity of the past passed student model, or the learner's learning propensity is in the past compared with the failed pass propensity information of the past failed model matched A learning propensity correction information transmission program 67 that transmits learning propensity correction information capable of correcting the learner's learning propensity to the learner terminal 10 so as to be similar to the learning propensity of the failed model, the matched past pass model Passing and failing propensity information transmission program 68 that transmits the pass student propensity information or the failed pass propensity information of the matched past failing model to the learner terminal, compared with the pass student propensity information of the matched past pass student model so that the learner's behavioral tendency is similar to or matched with the behavioral tendency of the past passed student model, and the learner's behavioral tendency is similar to the behavioral tendency of the past failed student model A behavioral tendency correction information transmission program 69 for transmitting behavioral tendency correction information capable of correcting the learner's behavioral tendency to the learner terminal, and other programs 69 for performing functions such as various graphics or payment or bulletin boards, etc. may include.

Here, for example, the main program 61 operates the entire program, and may be expressed in the form of a learner management homepage or a main screen of an application or program online, and the learner terminal 10 or the learning content provider terminal It may be a program capable of controlling all the programs by receiving various information and command signals from ( 20 ) or the operator terminal 90 .

Also, for example, the member registration program 62 is a program for receiving registration application information from the learner terminal 10 and registering as a member, and can authenticate the learner terminal 10 to store learner registration information. It may be a program with

In addition, the member registration program 62 receives unique information from the learner terminal 10 or the learning content provider terminal 20 or the operator terminal 90 to receive standard terms and conditions or terms and conditions for information collection and use, etc. It is a program that can give consent and can be registered with real name verification, public IPIN, ID, password, e-mail, mobile phone, address, personal information, patient information, social security number information, unique number, or phone number stored in the SIM card. can

Also, for example, the log-in program 63 is a program that can perform a log-in process by receiving log-in information from the learner terminal 10. After the learner accesses the server computer 60, the user ID or It may be a program that can receive login information from the learner terminal 10 to log in by automatically or manually inputting a password or a phone number.

Also, for example, the passed student propensity input program 64 is a program that can receive passed student propensity information related to the propensity of the past passed student model, and can receive a large amount of big data so that the propensity of past pass students can be identified. can be

FIG. 2 is a block diagram showing in more detail the pass/fail student propensity information input program 64 of the system for operating the learner propensity correction service of FIG. 1 .

More specifically, for example, the pass/fail student disposition information input program 64 includes a learner disposition information input program 641 that receives learner disposition information related to the learner disposition from the learner terminal, and the learner terminal Alternatively, the pass result information input program 642 that receives pass result information on the pass result of the learner from the operator terminal, and the learner's learner propensity information and the pass result information are analyzed to analyze the correlation to calculate analysis information a correlation analysis program 643, an artificial intelligence program 644 that analyzes various data in real time using a deep learning technique through feedback, and at least the learner tendency information, the pass result information, the analysis information and Distributed ledger program 645, which distributes and stores information made by selecting any one or more of these combinations in a plurality of storage locations using distributed ledger technology, and allows information to be viewed using a distributed ledger key, etc. may include.

In addition, for example, as shown in FIG. 2 , the learner propensity information input program 641 is a program that can receive learner propensity information related to the learner propensity of the learner from the learner terminal 10, and various surveys Of course, it may be a program capable of collecting various learner tendency information by various smart devices such as smart phones or various wearable devices such as smart locations and smart sensors.

For example, the learner propensity information can be divided into three types of information: first, learning propensity information related to learning, second, behavioral propensity information related to behavior other than learning, and third, learning content and It may consist of related learning content information.

More specifically, for example, the learning tendency information may include at least learning period information for a specific test, content understanding method information, content memorization method information, learning time zone information such as morning/am/pm/evening/dawn, learning time/learning It can be made by selecting any one or more of conscientiousness information, such as whether concentration time / scrap time is used / break time / plan practice / repeated learning, etc., learning location information, study group information, and combinations thereof.

In addition, more specifically, for example, the behavioral tendency information may include at least sleep time/waking time/cell phone use time/internet use time/game time/intoxication/whether dating the opposite sex/smoking/smoking seconds/number of close friends meeting Willpower information, such as meal time/number of snacks/bedtime/percentage of planning execution/number of weekly workouts, etc. planning information, conscientiousness information such as appointment time adherence percentage/absence percentage/percent tardy, health status information such as disease status/type of disease, occupational consciousness / It can be done by selecting any one or more of professional awareness information such as /vocational sense of duty, goal setting information such as goal setting/goal achievement percentage, personality information such as calmness/urgent/hot-tempered/question resolution values, and combinations thereof.

In addition, more specifically, for example, the learning content information may include all learning content information such as viewing, listening, viewing, and reading, and at least initial learning achievement information such as level test results, mock test information, and problem solving Information, note test information, video viewing information, detailed learning topic information, difficulty information for each question, question type information, score information for each subject, incorrect answer note information, and combinations thereof may be selected.

As an example, the learning video is divided into small pieces based on detailed learning topics and keywords and divided into one lesson based on a running time of about 30 to 60 minutes, and each lesson is divided into detailed learning topics, difficulty levels, and question types. can

Here, detailed learning topics and keywords are divided into core keywords by dividing the total amount of learning into units that can generate problems according to the progress, and the difficulty is divided into high/middle/low, and the question type is English , (1) Vocabulary A1. Choose the same meaning as the underscore, (2) Expression B1. Choose the same meaning as the underscore B2. Fill in the blanks, (3) Living English C1. Pick a blank C2. Other types, (4) Grammar D1. Fill in the blanks, D2. Picking the wrong underline, D3. Choosing Wrong/Right Sentences, D4. English writing, (5) reading comprehension sentence completion, E1 vocabulary-centered, E2 logic-centered, (6) overall reading comprehension E3 gist and argument, E4 topic, D5 title, etc.

This learning content information can be provided through a question bank using the learning content provider terminal 20 or the operator terminal 90, and the detailed learning topic, difficulty, question type, and 100% divided in the learning video. Similarly, you can build a problem DB for each subject.

Accordingly, according to the present invention, it is possible to collect not only the learner's learning content, but also various learning tendency information indicating the learning tendency and various behavioral tendency information indicating the behavioral tendency in addition to the learning content.

Various disposition correction information that can be helpful to a learner in the future may be generated based on the learner disposition information.

Meanwhile, as shown in FIG. 2 , the pass result information input program 642 is a program capable of receiving pass result information on the pass result of the learner from the learner terminal 10 or the operator terminal 90 . As such, the pass result information is the result of passing or failing through the learner terminal 10 so that the learner terminal 10 can receive various benefits or benefits after all tests such as public officials exams are completed. This can be done by allowing the user to input or the operator through the operator terminal 90 to input a list of passed students.

More specifically, for example, the pass result information includes, at least, pass student information that can be given a benefit according to pass, failed student information that can be given a retake opportunity or discount according to failing, and longevity students who have not passed for more than N years. It can be made by selecting any one or more of information, information about students who have not been learning for more than M years, and combinations thereof.

Therefore, it is possible to know whether the result of a learner with a certain learning disposition, behavioral disposition, or learning content is pass or fail. It is possible to obtain valid data such as Korean values.

In order to analyze this correlation, as shown in FIG. 2 , the correlation analysis program 643 analyzes the correlation between the learner propensity information of the learner and the pass result information to calculate analysis information. As a program that can do this, the relationship between each factor can be analyzed in a wide variety of statistical methods.

3 is a block diagram illustrating in more detail the correlation analysis program 643 of the system for operating the learner disposition correction service of FIG. 1 .

More specifically, for example, as shown in FIGS. 2 and 3 , the correlation analysis program 643 includes a quantification program 643-1 for scoring or quantifying the learner propensity information of the learner, and the A variable factor determination program (643-2) that analyzes a learner's score or quantitative numerical value change to determine a variable factor, and predicts the learner's passability according to the variable factor based on the pass result information for each type of learner in the past A propensity correction program (643-4) for generating behavior correction information capable of correcting the learner's learning propensity or behavioral propensity excluding the learning content to increase the passability prediction program (643-3) of the learner and the learner's passability may include.

More specifically, for example, the quantification program 643-1 is a program that can score or quantify the learner's propensity information of the learner, for example, when a survey or other measurement value is "No" or 1 to 20 1 point for “strongly no” or 21-40, 3 points for “strongly agree” or 41-60, 4 points for “agree” or 61-80, “strongly agree” In the case of 81~100, it is scored with 5 points, a total of 5 grades are divided, each is scored, and each factor can be summed and quantified.

In addition, for example, the variable factor determination program 643-2 is a program capable of determining the variable factor by analyzing the learner's score or quantitative numerical value change, and the effect of the tendency information A on the above-mentioned score value or quantitative value A variation value is measured, and as the variation value is relatively large, it can be determined as an important variation factor.

For example, in the passed student model, the amount of study time may be determined as a very important variable factor leading to acceptance.

Also, for example, the pass probability prediction program 643-3 is a program capable of predicting the passability of the learner according to the variable factors based on the pass result information for each type of learner in the past. If it is determined, the current learner can determine how much the current learner is consistent with the passing student in terms of his or her disposition, and score or quantify this judgment to indicate the probability of passing or failing, for example, as a percentage or other numerical value.

In addition, for example, the disposition correction program 643-4 is a program capable of generating disposition correction information capable of correcting the learner's learning propensity or behavioral propensity excluding the learning content in order to increase the learner's passability. , it is possible to generate disposition correction information to be corrected in a direction to increase the passability of the learner.

Here, the disposition correction information may include various types of learning disposition information to be corrected, behavioral disposition information, and learning content information of the learner.

For example, as a kind of the disposition correction information, the learner may be provided with his or her own curriculum through a precise pre-diagnosis test result.

More specifically, for example, the diagnostic test that can be performed in advance consists of 20 questions for each subject and is tested twice. can be entered.

Through these diagnostic tests, analysis results such as the overall average, scores for each subject, difficulty and type of each item can be shown, and a learning curriculum suitable for each student's level can be presented.

For example, the customized curriculum presentation can be presented by using an artificial intelligence system (AI), and a more sophisticated curriculum presentation can be implemented in a familiar form by artificial intelligence or a curriculum can be presented in detail through a professional curator by an operator. .

This curator type of information on correction of propensity not only presents an online-only curriculum, but also recommends the curriculum of an offline academy in detail in consideration of the student's residence, recommends textbooks, makes a study plan, and can proceed with 1:1 online tutoring. there is.

Online tutoring here can be conducted by using wired/wireless telephones, video systems, and bulletin boards to meet the needs and level of students.

Each learning curriculum can be divided into theoretical lectures/in-depth lectures/problem solving for each subject according to the level of students, and each presented lecture is thoroughly divided into the students' weak topic parts and question type parts. It can be customized.

Therefore, learners receive customized learning according to their individual level, and each detailed lecture is matched with a detailed question bank that matches the detailed topic/question type/difficulty level. can be saved as an incorrect answer note and recommended to learn by linking other video learning and related theories and problems that match the problem.

In addition, for example, this tendency correction information can be made in stages, and more specifically, for example, after completing the first stage theory learning, a check test (mock test) is automatically given, and according to the result, the details of the same lecture The system can suggest whether to do topic repetition learning or 2nd step learning, and 2nd step deep learning also includes in-depth video learning of specific topics, and each detailed lecture is a detailed question bank that matches the specific topic/question type/difficulty level. Matching, you can learn by linking video learning with a question bank, and save incorrect questions as incorrect answer notes, and receive recommendations for learning by linking other video learning and related theories and problems that match the problem .

After going through the 3rd stage, the 4th stage learning analyzes the trend of the student's learning data, and automatically extracts the high-level problems and the frequently wrong problems by detailed topic and type, just like the actual test, 5 subjects 20 questions for a total of 100 Depending on the individual situation, the problem can be solved over 5 times in total. After learning for the mock test, important or frequently wrong questions are again saved in the incorrect answer notes for each detailed topic and type, and supplementary learning can be done through matching video lectures on the relevant detailed topic.

Therefore, through this process, you can repeat 1:1 customized video learning and problem-solving learning, learn faster through repeated learning according to your weaknesses and level, and pass through selective customized learning It can shorten the period of operation and achieve economic cost savings.

In addition, this data analysis function is fed back in real time and uses artificial intelligence to greatly increase the chances of passing various learners, so that high value-added education and learning services that cannot be provided by other educational institutions can be performed.

In addition, since it is possible to comprehensively analyze the learner's learning propensity and learning content, as well as a wide variety of propensity information such as behavioral propensities other than learning, it is helpful to the learner by matching the pass or fail model that is most similar to the learner's propensity. It is possible to provide the optimal customized propensity correction information in real time.

On the other hand, as shown in Figure 2, the distributed ledger program 645, at least the learner propensity information, the pass result information, the analysis information, and information formed by selecting any one or more of combinations thereof. It is a program that distributes and stores information in multiple storage locations using distributed ledger technology and allows information to be viewed using distributed ledger keys, and prevents information leakage or illegal copying, such as virtual currency or block chain technology. Thus, it is possible to protect not only goodwill but also personal privacy, that is, security as much as possible.

On the other hand, for example, as shown in FIG. 1 , the learner propensity information input program 65 is a program capable of receiving learner propensity information related to the learner propensity of the learner from the learner terminal 10, and various surveys Of course, it may be a program capable of collecting various learner tendency information by various smart devices such as smart phones or various wearable devices such as smart locations or smart sensors.

Also, for example, the matching program 66 may generate matching information that matches disposition information of a past passed student model or a failed student model similar to the learner disposition information among the passed student disposition information or the failed student disposition information. More specifically, for example, a past model of passed or failed students with similar initial mock test scores to the learner is matched, or a past model of passed or failed students with similar learning tendencies, behavioral tendencies, and learning contents. It may be a program that can match .

For example, the matching information may include information on past passed students who have at least similar or identical initial learning achievements by comparing statistics, information about past passed students with similar or identical learning methods, information about past passed students with similar or identical sincerity, and past students with similar or identical willpower. This may be accomplished by selecting any one or more of information on passed students, information on past students with similar or identical plans, information on past students with similar or identical goals, and combinations thereof.

Also, for example, as shown in FIG. 1 , the learning propensity correction information transmission program 67 compares the learner's learning propensity with the learning propensity of the past pass student model and the passed student propensity information of the matched past pass student model. The learner's learning propensity is corrected with the learner terminal 10 so that the learner's learning propensity is dissimilar to the learning propensity of the past failing model by comparing it with the failing propensity information of the similar or matched past failing model. As a program that can transmit learning propensity correction information that can It may be a program that can transmit learning propensity correction information about how many intervals have been studied, what is the order of study, and what is the curriculum.

Also, for example, the passing student propensity information transmission program 68 may transmit the passed student propensity information of the matched past passed student model or the failed student propensity information of the matched past unsuccessful student model to the learner terminal 10 . In this program, learners can study on their own by predicting their passing period in the pass prediction system and being presented with a specific method and curriculum to pass in the shortest period of time. Through this, you can continuously check the acceptance period, etc. In other words, you practice through the behaviors and change factors and curriculum for the proposed reduction of the acceptance period, measure the results every month, and receive information about the past passed students according to the changed results. can pass the exam.

Therefore, learners can achieve a high pass rate by figuring out what they lack in order to pass, in particular, various behavioral tendencies other than learning by themselves and correcting them. It can be boosted to the benefit of everyone.

In addition, for example, as shown in FIG. 1 , the behavioral disposition correction information transmission program 69 compares the learner’s behavioral disposition with the past passed student model’s behavioral disposition and the past passed student model’s behavioral disposition by comparing it with the passed student disposition information of the matched past passed student model. The learner's behavioral tendency is corrected with the learner terminal 10 so that the learner's behavioral tendency is similar to that of the past failed student model by comparing it with the failing student's tendency information of a similar or matched past failed student model. As a program that can transmit behavioral tendency correction information that can It may be a program capable of transmitting behavioral tendency correction information.

For example, it analyzes the causal relationship between the grades and behavioral orientation of passed students and the causal relationship between the grades and behavioral orientation of the failed students through the grades, behaviors, and orientation information of boarding school students accumulated over 10 years and can be observed 24 hours a day. In addition, grades are affected by disposition and behavioral factors, and the grades can be a criterion for determining pass/fail or pass period.

The behavioral tendency information of students can be analyzed and corrected from the time when they first start studying at the academy, and the time when they pass or fail or when they leave the school. For example, when a student enters a private academy for the first time, the student's grades are recorded through a diagnostic test for each subject, and the progress and change of grades can be analyzed through monthly mock tests. You can self-diagnose or measure factors such as study pattern, sincerity, willpower, planning, conscientiousness, health status, occupational consciousness, goal consciousness, and personality. It can guide learners' behavioral tendencies.

In addition, based on statistics, each causal relationship can be statistically processed by analyzing the pattern of whether grades rise when certain behaviors and tendencies are shown, and grades go down when certain behaviors and tendencies are shown, and these results can be used to correct the behavioral tendencies The information may be transmitted to the learner terminal 10 .

According to these changes in behavior and disposition, grades change, and as a result, the pattern of students passing within 5 months, patterns of students passing within 10 months, patterns of students passing within 12 months, and students passing within 1 year and 6 months It is also possible to perform statistical processing by analyzing the pattern of students who pass within 2 years, the pattern of students who pass after 2 years, the pattern of students who give up studying, and the pattern of students who fail.

Therefore, based on the correlation statistics between academic and non-academic information of accepted and failed students accumulated over decades, it is possible to predict an individual's acceptance period and to predict what kind of change in disposition and behavior must be made to pass faster. there is.

As part of the behavioral disposition correction information, the acceptance prediction system may be presented with a change factor for my expected acceptance period and the shortest period of time. First, self-diagnosis of test scores and study experience, study method, study pattern, sincerity, willpower, planning, conscientiousness, health status, occupational consciousness, goal awareness, personality, etc. Through this, you can predict the pass period by presenting the results of past pass student statistical information that are most similar to you, and you can be presented with specific factors for change in tendencies and behaviors that can shorten the pass period. You can receive an optimized and customized learning curriculum by your level and weak detailed study topics.

Here, the above-described programs are in the form of interlocking with the learner terminal 10, the learning content provider terminal 20, or an execution program downloaded or installed in the operator terminal 90, a screen control program, or a user application. can be operated

However, the above-described programs are not necessarily limited to interworking with an execution program or a smart phone application, and may interwork with all various types of terminals.

Meanwhile, as shown in FIG. 1 , the database DB includes a member registration information database 71 in which the member registration information is stored, a login information database 72 in which the login information is stored, and the passed student propensity information. The passed student propensity information database 73 is stored, the failed student propensity information database 74 is stored in the disqualified student disposition information, the learner disposition information database 75 is stored in the learner disposition information, and the matching information is stored in the matching information. A database 76, a learning propensity correction information database 77 in which the learning propensity correction information is stored, a behavior propensity correction information database 78 in which the behavioral propensity correction information is stored, and a pass result information database in which the pass result information is stored (79), an analysis information database 80 in which the analysis information is stored, and other information databases 81 in which information such as other learner management homepages, various advertisements, publicity, payment, bulletin boards, etc. are stored.

Accordingly, the server computer 60 uses the pass student propensity information input program 64 and the pass/fail student propensity information input program 64 to transmit pass student propensity information and past failings related to propensity of the past pass student model. Receive disqualification information related to the propensity of the raw model, receive learner propensity information related to the learner propensity of the learner from the learner terminal 10 by the learner propensity information input program 65, and the matching program ( 66), from among the passed student disposition information or the unsuccessful student disposition information, generates matching information that matches disposition information of a past passed student model or a failed student model similar to the learner disposition information, and the learning propensity correction information transmission program By (67), the learner's learning propensity is similar to the learning propensity of the past passed student model as compared with the passed student propensity information of the matched past passed student model, or compared with the failed student propensity information of the matched past unsuccessful student model To perform a learner tendency correction data analysis service that transmits learning tendency correction information that can correct the learner's learning tendency to the learner terminal 10 so that the learner's learning tendency is similar to the learning tendency of the past failed student model can do.

4 is a schematic diagram illustrating a relationship between an operator who operates a learner disposition correction service of the present invention and a learner.

As shown in Figure 4, therefore, learners can improve their pass rate by correcting their propensity by receiving propensity correction information as well as various learning contents, and determine their current location by receiving passability information Various services can be provided, such as viewing, and the operator who operates the server computer 60 can receive and utilize various learner tendency information through this, and can receive various membership fees or content usage fees in return for the service. It can provide a useful computational management model or business model that can benefit everyone.

5 is a flowchart illustrating a method of operating a learner disposition correction service according to some embodiments of the present invention.

On the other hand, as shown in FIGS. 1 to 5 , if the method of operating the learner orientation correction service according to some embodiments of the present invention is sequentially shown, the learner orientation correction service according to some embodiments of the present invention is shown in order. The operation method is first to configure the server computer 60 that can provide the learner disposition correction service, (a) related to the disposition of the past passed student model by the pass and failed student propensity information input program 64 Receiving the pass student propensity information and the failing student propensity information related to the propensity of the past failing model, (b) by the learner propensity information input program 65, from the learner terminal 10 related to the learner propensity receiving learner propensity information; (c) by the matching program 66, propensity information of a past pass student model or a failed student model similar to the learner propensity information among the pass student propensity information or the failed student propensity information generating matching information that matches the The learner's learning propensity with the learner terminal 10 so that the learner's learning propensity is dissimilar to the learning propensity of the past failing model by comparing it with the failing student propensity information of the past failed student model that is similar to or matched with the propensity It may include the step of transmitting the learning tendency correction information that can correct the.

6 is a flowchart illustrating in more detail step (a) of the method of operating the learner disposition correction service of FIG. 5 .

As shown in FIG. 6 , (a) through the pass and failed student propensity information input program 64, pass student propensity information related to the propensity of the past passed student model and disqualified student propensity information related to the propensity of the past failed student model The step of receiving the input includes: (a-1) receiving, by the learner propensity information input program 65, learner propensity information related to the learner propensity of the learner from the learner terminal 10; (a-2) the receiving pass result information on the pass result of the learner from the learner terminal 10 or the operator terminal 90 by the pass result information input program 642; (a-3) the correlation analysis program The method may include calculating analysis information by analyzing a correlation between the learner propensity information and the pass result information of the learner by step 643 .

Here, the step (a-3) includes: (a-3-1) scoring or quantifying the learner tendency information of the learner by the quantification program 643-1; (a-3-2) ) by the variable factor determination program (643-2), analyzing the learner's score or quantitative numerical value change to determine the variable factor, and (a-3-3) to the pass probability prediction program (643-3) estimating the passability of the learner according to the variation factor based on the pass result information for each type of learner in the past.

Here, in the step (a-3-2), the correlation between the learner's score or quantitative numerical value fluctuation and the fluctuation factor is information with high correlation using a statistical processing process such as Bayesian Theory. can be made by selecting as the main variation factor.

In addition, in step (a-3-3), the accuracy of the passability of the learner may be improved through machine learning of the artificial intelligence program 644 of FIG. 2 .

Here, the Bayesian theory or artificial intelligence technology, etc. are widely known technologies such as statistics and deep learning, and detailed descriptions thereof will be omitted.

However, the present invention is not necessarily limited to the drawings, and various steps may be additionally included.

7 is a flowchart illustrating a method of operating a learner disposition correction service according to some other embodiments of the present invention.

On the other hand, as shown in FIGS. 1 to 7 , when a method of operating a learner disposition correction service according to some other embodiments of the present invention is sequentially shown, learner disposition correction according to some other embodiments of the present invention In the method of operating the service, first, the server computer 60 that can provide the learner disposition correction service is configured, (a) the disposition of the past passed student model by the pass and failed student propensity information input program 64 . A step of receiving the pass student propensity information related to and failing student propensity information related to the propensity of the past failing model, and (b) the learner propensity of the learner from the learner terminal 10 by the learner propensity information input program 65 receiving learner propensity information related to the above; generating matching information that matches the disposition information; (e) using the passed and failed student disposition information transmission program 68, the passed student disposition information of the matched past passed student model or the matched past unsuccessful student model transmitting the disqualified student disposition information to the learner terminal 10; The learner terminal ( 10) transmitting learning propensity correction information capable of correcting the learner's learning propensity, and (f) comparing it with the pass student propensity information of the matched past pass student model by the behavioral propensity correction information transmission program 69 Therefore, the behavioral tendency of the learner is the behavioral tendency of the past passed student model. The learner's behavioral tendency is corrected with the learner terminal 10 so that the learner's behavioral tendency is dissimilar to that of the past failed student model by comparing it with the failing student's tendency information of the past failed student model that is similar to or matched with It may include the step of transmitting the behavioral tendency correction information that can be done.

8 is a conceptual diagram illustrating a system for operating a learner disposition correction service according to some other embodiments of the present invention.

As shown in Fig. 8, the system for operating the learner disposition correction service according to some other embodiments of the present invention can be largely composed of two subjects, <System> representing the program, and <DB representing the database. > can be done.

Therefore, using the above-described various programs, it is possible to match the learner with the past model of passed students or models of unsuccessful students with the [Learner Matching Similarity] program based on information obtained through the [Learner Propensity Analysis] program. In this case, "learning state data" and "learning type statistics" data may be used.

Next, by comparing the propensity of past pass or unsuccessful learners, the [propensity change history inquiry] program provides learners with the [propensity correction] Suggestion of measures] Depending on the program, information on propensity correction can be provided.

9 and 10 are diagrams illustrating an example of a screen provided by a learner disposition correction service according to some embodiments of the present invention.

As shown in Figure 9, the screen provided by the learner tendency correction service according to some embodiments of the present invention, for example, the total study time required to pass the examination, the average daily study time of the students who passed the examination, the average preparation period for the examination, etc. General behavioral propensity information, learning propensity information, etc. may be displayed, and the average study time for passing students, the average working time of the passed students, and the average preparation period for passing students of the passed student model matched with the learner for comparison with this may be displayed. In addition, various behavioral propensity correction information, such as the learner's own total study time to pass the current diagnostic standard, the current diagnostic standard work time, and the estimation of the current diagnostic standard preparation period, may be provided in the form of a screen.

In addition, as shown in FIG. 10, factors such as sincerity, willpower, goal consciousness, learning method, and planning are divided into quintiles, and the current diagnostic index and the average diagnostic index of the passed students are displayed in three dimensions in the form of a screen. It can also be provided. In addition, various types of information that can be helpful for learners' learning may be provided by using a wide variety of graphic effects.

Meanwhile, the present invention can also be implemented as computer-readable codes on a computer-readable recording medium.

The computer-readable recording medium may include any type of recording device in which data readable by a computer system is stored.

Examples of the computer-readable recording medium include ROM, RAM, CD-ROM, magnetic tape, floppy disk, magneto-optical disk, optical data storage device, flash memory, USB memory, etc. as well as the server computer 60 described above. may include.

In addition, the computer-readable recording medium is distributed in a computer system connected through a network, so that the computer-readable code can be stored and executed in a distributed manner.

Although the present invention has been described with reference to the embodiment shown in the drawings, which is merely exemplary, those skilled in the art will understand that various modifications and equivalent other embodiments are possible therefrom. Therefore, the true technical protection scope of the present invention should be determined by the technical spirit of the appended claims.

10: learner terminal
20: learning content provider terminal
90: operator terminal
50: network
60: server computer
PG: Program Control
DB: database

Claims (17)

In the method of operating a learner tendency correction service using a computer system having at least one learner terminal and a server computer connected through a network,
receiving information on the tendency of accepted students related to the tendency of the past passed student model and the information on the disposition of failing students related to the tendency of the past rejected model;
receiving learner propensity information related to learner propensity of the learner from the learner terminal;
generating matching information that matches disposition information of a past passed student model or a failed student model similar to the learner disposition information among the passed student disposition information or the failed student disposition information; and
The learning propensity of the learner becomes similar to the learning propensity of the past pass student model as compared with the pass student propensity information of the matched past pass student model, or the learner's learning propensity compared with the failed student propensity information of the matched past pass student model transmitting learning propensity correction information capable of correcting the learner's learning propensity to the learner terminal so as to be similar to the learning propensity of the past failed student model;
including,
Before transmitting the learning tendency correction information,
transmitting the passed student propensity information of the matched past passed student model or the failed student propensity information of the matched past unsuccessful student model to the learner terminal;
further comprising,
The learner propensity information includes at least learning propensity information related to learning, behavior propensity information related to behavior other than learning, and learning content information related to learning content,
The passed student propensity information includes learning propensity information related to learning of the passed student model based on average statistics, learning content information related to learning content, and behavioral propensity information related to behavioral information other than learning of the passed student model,
The failing student disposition information includes learning propensity information related to learning of the failed student model based on average statistics, learning content information related to learning content, and behavioral propensity information related to behavioral information other than learning of the failing model,
The learning propensity information is, at least, learning period information for a specific test, content understanding method information, content memorization method information, morning / morning / afternoon / evening / dawn learning time information, learning time / study intensive time / whether or not use of spare time It is made by selecting any one or more of / break time / plan practice / sincerity information of whether repeated learning, learning place information, study group information, and combinations thereof,
The learning content information includes at least initial learning achievement information through level test results, mock test information, problem solving information, note test information, video viewing information, detailed learning topic information, difficulty information for each question, problem type information, and score for each subject. It is made by selecting any one or more of information, incorrect note information, and combinations thereof,
The behavioral tendency information includes at least any one or more of sleep time / waking time / cell phone use time / Internet use time / game time / drinking / dating / smoking / number of seconds of smoking / number of close friends meeting , planning information including any one or more of meal time/snack times/bedtime/percent of planned practice/weekly exercise, conscientiousness information including any one or more of percentage adherence to appointment/percentage absent/percent tardy, disease status/ Health status information including any one or more of disease types, occupational consciousness information including any one or more of occupational consciousness/vocational sense of duty, goal setting information including any one or more of goal setting/goal achievement percentage, calmness/ A method of operating a learner disposition correction service, which is made by selecting any one or more of personality information and combinations thereof including any one or more of urgent/hot-tempered/curious resolution values. In the method of operating a learner tendency correction service using a computer system having at least one learner terminal and a server computer connected through a network,
The server computer includes a pass and failed student propensity information input program that receives pass student propensity information related to the propensity of the past pass model and reject propensity information related to the propensity of the past failing model, and related to the learner propensity of the learner from the learner terminal A learner disposition information input program that receives learner disposition information, and matching information that matches disposition information of a past passed student model or a failed student model similar to the learner disposition information among the passed student disposition information or the disqualified student disposition information The learner's learning propensity is similar to the learning propensity of the past pass model model compared to the pass student propensity information of the program, the matched past pass student model, or the learner's learning propensity is compared with the failed student propensity information of the past failed pass model matched A learning propensity correction information transmission program that transmits learning propensity correction information capable of correcting the learner's learning propensity to the learner terminal so that the learning propensity is similar to the learning propensity of the past unsuccessful student model, and the passed student propensity information is stored A disposition information database, a disqualified student disposition information database in which the failing student disposition information is stored, a learner disposition information database in which the learner disposition information is stored, a matching information database in which the matching information is stored, and a learning disposition in which the learning disposition correction information is stored. a database of calibration information;
The server computer further includes a pass/fail student propensity information transmission program that transmits the passed student propensity information of the matched past pass student model or the failed student propensity information of the matched past unsuccessful student model to the learner terminal,
The learner propensity information includes at least learning propensity information related to learning, behavior propensity information related to behavior other than learning, and learning content information related to learning content,
The passed student propensity information includes learning propensity information related to learning of the passed student model based on average statistics, learning content information related to learning content, and behavioral propensity information related to behavioral information other than learning of the passed student model,
The failing student disposition information includes learning propensity information related to learning of the failed student model based on average statistics, learning content information related to learning content, and behavioral propensity information related to behavioral information other than learning of the failing model,
(a) receiving, through the pass/fail student propensity information input program, pass student propensity information related to the propensity of the past pass model and reject student propensity information related to the propensity of the past failed model;
(b) receiving, by the learner propensity information input program, learner propensity information related to the learner propensity of the learner from the learner terminal;
(c) generating, by the matching program, matching information that matches disposition information of a past passed student model or a failed student model similar to the learner disposition information among the passed student disposition information or the failed student disposition information; and
(d) the learning propensity of the learner is similar to or matched with the learning propensity of the past pass student model in comparison with the pass student propensity information of the matched past pass student model by the learning propensity correction information transmission program; transmitting learning propensity correction information capable of correcting the learner's learning propensity to the learner terminal so that the learner's learning propensity is similar to the learning propensity of the past failed student model compared with the failing student propensity information;
including,
Before step (d),
(e) transmitting, by the pass and fail propensity information transmission program, the pass student propensity information of the matched past pass student model or the failed student propensity information of the matched past pass student model to the learner terminal;
further comprising,
The learning propensity information is, at least, learning period information for a specific test, content understanding method information, content memorization method information, morning / morning / afternoon / evening / dawn learning time information, learning time / study intensive time / whether or not use of spare time It is made by selecting any one or more of / break time / plan practice / sincerity information of whether repeated learning, learning place information, study group information, and combinations thereof,
The learning content information includes at least initial learning achievement information through level test results, mock test information, problem solving information, note test information, video viewing information, detailed learning topic information, difficulty information for each question, problem type information, and score for each subject. It is made by selecting any one or more of information, incorrect note information, and combinations thereof,
The behavioral tendency information includes at least any one or more of sleep time / waking time / cell phone use time / Internet use time / game time / drinking / dating / smoking / number of seconds of smoking / number of close friends meeting , planning information including any one or more of meal time/snack times/bedtime/percent of planned practice/weekly exercise, conscientiousness information including any one or more of percentage adherence to appointment/percentage absent/percent tardy, disease status/ Health status information including any one or more of disease types, occupational consciousness information including any one or more of occupational consciousness/vocational sense of duty, goal setting information including any one or more of goal setting/goal achievement percentage, calmness/ A method of operating a learner disposition correction service, which is made by selecting any one or more of personality information and combinations thereof including any one or more of urgent/hot-tempered/curious resolution values. 3. The method of claim 2,
The matching information includes at least past pass student information with similar or identical initial learning achievement by comparing statistics, past failed student information with similar or identical initial learning achievement information, past passed student information with similar or identical learning method, and past passed student information with similar or identical learning method. Information on rejected students, information on past accepted students with similar or identical integrity, information on past failed students with similar or identical integrity, information on past accepted students with similar or identical willpower, information on past failed students with similar or identical willpower, information on past accepted students with similar or identical planning , information on past failed students with similar or identical planning, information on past passed students with similar or identical goal consciousness, information on past failed students with similar or identical goal consciousness, and combinations thereof How to operate. delete delete delete delete delete 3. The method of claim 2,
The learning disposition correction information may include at least learning difference information indicating a learning difference between the learner and the passed student model or the failing model model to a numerical value or degree, learner learning disposition change information indicating a change in the learner's learning disposition, the passed student model, or the Method of operating a learner disposition correction service, which is made by selecting any one or more of pass and failed student learning disposition change information indicating the learning disposition change of the failing model, learning suggestion or learning recommendation information for the learner, and combinations thereof . 3. The method of claim 2,
The server computer compares the learner's behavioral propensity to the behavioral propensity of the past passed student model by comparison with the passed student propensity information of the matched past pass student model, or compares it with the failing student propensity information of the past failed pass model matched A behavioral orientation correction information transmission program for transmitting behavioral orientation correction information capable of correcting the learner's behavioral orientation to the learner terminal so that the learner's behavioral orientation is similar to the behavioral orientation of the past failure model, the behavioral orientation correction information Including a behavioral propensity correction information database to be stored,
Before or after step (d),
(f) the behavioral tendency of the learner is similar to or matched with the behavioral tendency of the past passed student model in comparison with the passed student tendency information of the matched past passed student model by the behavioral tendency correction information transmission program; transmitting behavioral tendency correction information capable of correcting the learner's behavioral tendency to the learner terminal so that the learner's behavioral tendency is similar to that of the past failed student model by comparing it with the failing student's tendency information;
A method of operating a learner orientation correction service, further comprising a. 11. The method of claim 10,
The behavioral disposition correction information may include at least behavioral difference information indicating a numerical or degree difference in behavior between the learner and the passed student model, learner behavioral disposition change information indicating a change in the learner's behavioral disposition, and a passed student indicating a behavioral disposition change of the passed student model. A method of operating a learner disposition correction service, which is made by selecting any one or more of behavioral disposition change information, action suggestion or action recommendation information for the learner, and combinations thereof. 3. The method of claim 2,
The pass and failed student propensity information input program includes a learner propensity information input program that receives learner propensity information related to the learner propensity from the learner terminal, and pass result information on the pass result of the learner from the learner terminal or the operator terminal A pass result information input program that receives an input, a correlation analysis program that calculates analysis information by analyzing the correlation between the learner propensity information of the learner and the pass result information, a learner propensity information database in which the learner propensity information is stored; a pass result information database in which the pass result information is stored, and an analysis information database in which the analysis information is stored;
The step (a) is,
(a-1) receiving learner tendency information related to the learner's learner's orientation from the learner terminal by the learner's orientation information input program;
(a-2) receiving pass result information on the pass result of the learner from the learner terminal or the operator terminal by the pass result information input program;
(a-3) calculating the analysis information by analyzing the correlation between the learner propensity information of the learner and the pass result information by the correlation analysis program;
A method of operating a learner disposition correction service, including. delete 13. The method of claim 12,
The pass result information includes, at least, information on passed students who can be given benefits according to passing, information about failed students who can be given a retake opportunity or discount benefits according to failure, information about longevity students who have not passed for more than N years, information input for more than M years A method of operating a learner disposition correction service that is made by selecting any one or more of information about students who have not been learning and combinations thereof. 13. The method of claim 12,
The correlation analysis program of the server computer may include: a quantification program for scoring or quantifying the learner tendency information of the learner; a change factor determination program for determining a change factor by analyzing the learner's score or quantitative numerical change; and a pass probability prediction program for predicting the passability of the learner according to the variation factor based on the pass result information for each type of learner in the past;
The step (a-3) is,
(a-3-1) scoring or quantifying the learner tendency information of the learner by the quantification program;
(a-3-2) determining the change factor by analyzing the change in the learner's score or quantitative numerical value by the change factor determination program; and
(a-3-3) predicting the passability of the learner based on the pass result information for each type of learner in the past by the pass probability predicting program according to the variation factor;
A method of operating a learner disposition correction service, including. A system for operating a learner disposition correction service using a computer system having at least one learner terminal and a server computer connected through a network,
The server computer includes a pass and failed student propensity information input program that receives pass student propensity information related to the propensity of the past pass model and reject propensity information related to the propensity of the past failing model, and related to the learner propensity of the learner from the learner terminal A learner disposition information input program that receives learner disposition information, and matching information that matches disposition information of a past passed student model or a failed student model similar to the learner disposition information among the passed student disposition information or the disqualified student disposition information The learner's learning propensity is similar to the learning propensity of the past pass model model compared to the pass student propensity information of the program, the matched past pass student model, or the learner's learning propensity is compared with the failed student propensity information of the past failed pass model matched A learning propensity correction information transmission program that transmits learning propensity correction information capable of correcting the learner's learning propensity to the learner terminal so that the learning propensity is similar to the learning propensity of the past unsuccessful student model, and the passed student propensity information is stored A disposition information database, a disqualified student disposition information database in which the failing student disposition information is stored, a learner disposition information database in which the learner disposition information is stored, a matching information database in which the matching information is stored, and a learning disposition in which the learning disposition correction information is stored. a database of calibration information;
The server computer further includes a pass/fail student propensity information transmission program that transmits the passed student propensity information of the matched past pass student model or the failed student propensity information of the matched past unsuccessful student model to the learner terminal,
The learner propensity information includes at least learning propensity information related to learning, behavior propensity information related to behavior other than learning, and learning content information related to learning content,
The passed student propensity information includes learning propensity information related to learning of the passed student model based on average statistics, learning content information related to learning content, and behavioral propensity information related to behavioral information other than learning of the passed student model,
The failing student disposition information includes learning propensity information related to learning of the failed student model based on average statistics, learning content information related to learning content, and behavioral propensity information related to behavioral information other than learning of the failing model,
Through the pass and failed student propensity information input program, pass student propensity information related to the propensity of the past passed student model and failing student propensity information related to the propensity of the past failing model are received, and the learner propensity information input program allows the learner Receive learner propensity information related to the learner propensity of the learner from the terminal, and by the matching program, propensity information of a past pass student model or a failed student model similar to the learner propensity information among the pass student propensity information or the failed student propensity information generating matching information that matches , and comparing with the passed student propensity information of the matched past passed student model by the learning propensity correction information transmission program, the learner's learning propensity is similar to or matched with the learning propensity of the past passed student model Learning propensity correction information capable of correcting the learner's learning propensity with the learner terminal so that the learner's learning propensity is similar to the learning propensity of the past failing model by comparing it with the failing student propensity information of the past failed model a control program programmed to transmit;
The learning propensity information is, at least, learning period information for a specific test, content understanding method information, content memorization method information, morning / morning / afternoon / evening / dawn learning time information, learning time / study intensive time / whether or not use of spare time It is made by selecting any one or more of / break time / plan practice / sincerity information of whether repeated learning, learning place information, study group information, and combinations thereof,
The learning content information includes at least initial learning achievement information through level test results, mock test information, problem solving information, note test information, video viewing information, detailed learning topic information, difficulty information for each question, problem type information, and score for each subject. It is made by selecting any one or more of information, incorrect note information, and combinations thereof,
The behavioral tendency information includes at least any one or more of sleep time / waking time / cell phone use time / Internet use time / game time / drinking / dating / smoking / number of seconds of smoking / number of close friends meeting , planning information including any one or more of meal time/snack times/bedtime/percent of planned practice/weekly exercise, conscientiousness information including any one or more of percentage adherence to appointment/percentage absent/percent tardy, disease status/ Health status information including any one or more of disease types, occupational consciousness information including any one or more of occupational consciousness/vocational sense of duty, goal setting information including any one or more of goal setting/goal achievement percentage, calmness/ A system for operating a learner disposition correction service, which is made by selecting any one or more of personality information including any one or more of urgent / hot-tempered / curious resolution values and combinations thereof. A computer-readable recording medium recording a method of operating a learner disposition correction service using at least one learner terminal and a computer system having a server computer connected through a network,
The server computer includes a pass and failed student propensity information input program that receives pass student propensity information related to the propensity of the past pass model and reject propensity information related to the propensity of the past failing model, and related to the learner propensity of the learner from the learner terminal A learner disposition information input program that receives learner disposition information, and matching information that matches disposition information of a past passed student model or a failed student model similar to the learner disposition information among the passed student disposition information or the disqualified student disposition information The learner's learning propensity is similar to the learning propensity of the past pass model model compared to the pass student propensity information of the program, the matched past pass student model, or the learner's learning propensity is compared with the failed student propensity information of the past failed pass model matched A learning propensity correction information transmission program that transmits learning propensity correction information capable of correcting the learner's learning propensity to the learner terminal so that the learning propensity is similar to the learning propensity of the past unsuccessful student model, and the passed student propensity information is stored A disposition information database, a disqualified student disposition information database in which the failing student disposition information is stored, a learner disposition information database in which the learner disposition information is stored, a matching information database in which the matching information is stored, and a learning disposition in which the learning disposition correction information is stored. a database of calibration information;
The server computer further includes a pass/fail student propensity information transmission program that transmits the passed student propensity information of the matched past pass student model or the failed student propensity information of the matched past unsuccessful student model to the learner terminal,
The learner propensity information includes at least learning propensity information related to learning, behavior propensity information related to behavior other than learning, and learning content information related to learning content,
The passed student propensity information includes learning propensity information related to learning of the passed student model based on average statistics, learning content information related to learning content, and behavioral propensity information related to behavioral information other than learning of the passed student model,
The failing student disposition information includes learning propensity information related to learning of the failed student model based on average statistics, learning content information related to learning content, and behavioral propensity information related to behavioral information other than learning of the failing model,
(a) receiving, through the pass/fail student propensity information input program, pass student propensity information related to the propensity of the past pass model and reject student propensity information related to the propensity of the past failed model;
(b) receiving, by the learner propensity information input program, learner propensity information related to the learner propensity of the learner from the learner terminal;
(c) generating, by the matching program, matching information that matches disposition information of a past passed student model or a failed student model similar to the learner disposition information among the passed student disposition information or the failed student disposition information; and
(d) the learning propensity of the learner is similar to or matched with the learning propensity of the past pass student model in comparison with the pass student propensity information of the matched past pass student model by the learning propensity correction information transmission program; transmitting learning propensity correction information capable of correcting the learner's learning propensity to the learner terminal so that the learner's learning propensity is similar to the learning propensity of the past failed student model compared with the failing student propensity information;
including,
Before step (d),
(e) transmitting, by the pass and fail propensity information transmission program, the pass student propensity information of the matched past pass student model or the failed student propensity information of the matched past pass student model to the learner terminal;
further comprising,
The learning propensity information is, at least, learning period information for a specific test, content understanding method information, content memorization method information, morning / morning / afternoon / evening / dawn learning time information, learning time / study intensive time / whether or not use of spare time It is made by selecting any one or more of / break time / plan practice / sincerity information of whether repeated learning, learning place information, study group information, and combinations thereof,
The learning content information includes at least initial learning achievement information through level test results, mock test information, problem solving information, note test information, video viewing information, detailed learning topic information, difficulty information for each question, problem type information, and score for each subject. It is made by selecting any one or more of information, incorrect note information, and combinations thereof,
The behavioral tendency information includes at least any one or more of sleep time / waking time / cell phone use time / Internet use time / game time / drinking / dating / smoking / number of seconds of smoking / number of close friends meeting , planning information including any one or more of meal time/snack times/bedtime/percent of planned practice/weekly exercise, conscientiousness information including any one or more of percentage adherence to appointment/percentage absent/percent tardy, disease status/ Health status information including any one or more of disease types, occupational consciousness information including any one or more of occupational consciousness/vocational sense of duty, goal setting information including any one or more of goal setting/goal achievement percentage, calmness/ A computer-readable recording medium recording a method of operating a learner disposition correction service, which is made by selecting any one or more of personality information including any one or more of urgency/hot-tempered/curious resolution values and combinations thereof.

Images