KR20160116789A

KR20160116789A - A method for learning record management and a system using the same

Info

Publication number: KR20160116789A
Application number: KR1020150045036A
Authority: KR
Inventors: 정대욱
Original assignee: 정대욱
Priority date: 2015-03-31
Filing date: 2015-03-31
Publication date: 2016-10-10

Abstract

The learning history management system according to the present invention includes a learning paper generation unit for generating a first learning paper based on learning paper generation information input from a learner, a grading unit for grading a second learning paper in which the learning process of the learner is completed, A map generator for generating a mathematics instruction map showing the strong area and the week area of the learner based on the scoring result of the second learning material, a week list for creating a week list for the wek area of the learner based on the mathematics instruction map And a learning history database for storing at least one of a first learning material and a second learning material, a mathematical knowledge map or a week list, and managing a learning history of the learner.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a learning history management method,

The present invention relates to a learning history management method and system.

Students are exposed to a number of problems indiscreetly, constantly adjusting only to the problems they are familiar with, and repeatedly failing in areas that are unfamiliar or weak. In order to solve these problems, a system has been devised which distinguishes strong and weak areas from the various types of problems, and enables repeated learning on weak areas.

The present invention provides a method of generating a study paper from a problem database classified by type of problem and degree of difficulty.

The present invention provides a method of performing automatic grading on a learning paper in which learning has been completed by a learner.

The present invention provides a method of repeatedly performing learning on a learner's week area based on a scored workbook.

The learning history management system according to the present invention includes a learning paper generation unit for specifying a problem of learner designation based on learning paper generation information input from a learner and generating a first learning paper using the specified at least one problem, A scoring unit for scoring a second learning material for which the learning process of the learner is completed for the first learning material, a strong part and a weak part of the learner based on the scoring result of the second learning material, A map generator for generating a mathematics instruction map, a week list generator for generating a weak list for the learner's week area based on the generated mathematics instruction map, A mathematical knowledge map or a week list, and manages the learning history of the learner And a learning history database.

The learning history management system may further include a server for storing a code-based mathematical knowledge list.

In the learning history management system according to the present invention, the mathematical knowledge list includes the at least one problem for each type of problem and the degree of difficulty of the problem, and an identification code for identifying the type of the problem.

In the learning history management system according to the present invention, the learning paper creation information is data related to at least one of the identification code, the type, and the degree of difficulty.

In the learning history management system according to the present invention, the learning paper generation unit may generate the first learning paper using only a problem in which the frequency of use is smaller than a predetermined first threshold value among the problems used in the previously generated learning paper .

In the learning history management system according to the present invention, the frequency of use is allocated to each of the problems stored in the server, and the frequency of use is updated each time a learning paper is generated.

The learning history management system according to the present invention is characterized in that the predetermined first threshold value is a variable value adaptively determined according to a pre-determined value or a level of the learner.

In the learning history management system according to the present invention, the scoring unit may perform scoring through mapping between the question of the second learning material and the scoring data based on the keyword from the problem of the second learning material and the position of the keyword .

In the learning history management system according to the present invention, the keyword is determined as a character at a position set on a line-by-line basis in the problem of the second learning material, and the score data means data composed of a problem and an answer .

In the learning history management system according to the present invention, the mathematical knowledge map may include at least one of a learning range, an identification code, and data on a strong / weak area of a learner.

In the learning history management system according to the present invention, the data on the strong / weak area means information indicating whether the specific problem belongs to the strong area or the weak area to the learner.

In the learning history management system according to the present invention, the map generation unit is characterized in that it is determined whether it belongs to the strong area or the wek area based on the mapping relation between the correct rate of the problems concerning the specific type and the strong / weak area type .

In the learning history management system according to the present invention, the map generator may calculate the achievement of the learner based on the score of the second learning material, compare the calculated achievement with a predetermined second threshold, Is determined.

In the learning history management system according to the present invention, the achievement is calculated by applying different weights to the problem that the correct answer is matched with the problem that the correct answer is not matched with the previously learned problem.

According to the present invention, it is possible to provide a study paper composed of problems of each type and difficulty according to the ability or level of the learner.

According to the present invention, it is possible to easily identify a learner's week area on the basis of the completed learner's work and to enable iterative learning on a week area.

According to the present invention, learning history of a learner can be efficiently managed through creation of a learning paper suitable for a learner, a scoring result of the learning paper, and a week list of the learner.

FIG. 1 illustrates a learning system 100 for learning history management according to an embodiment of the present invention.
FIG. 2 illustrates a code-based Math Knowledge List according to an embodiment of the present invention.
FIG. 3 illustrates a Math Knowledge Map generated by the map generator 140 according to an embodiment of the present invention. Referring to FIG.
FIG. 4 illustrates a week list for a weak part created by the week list creating unit 150 according to an embodiment of the present invention. Referring to FIG.
FIG. 5 illustrates a method of managing a learning history of a learner in the learning system 100 according to an embodiment of the present invention.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. Prior to this, terms and words used in the present specification and claims are not to be construed as limited to ordinary or dictionary terms, and the inventor appropriately defines the concept of the term to describe its invention in the best way possible It should be construed as meaning and concept consistent with the technical idea of the present invention. Therefore, the embodiments described in this specification and the configurations shown in the drawings are merely the most preferred embodiments of the present invention and do not represent all the technical ideas of the present invention. Therefore, It is to be understood that equivalents and modifications are possible.

When an element is referred to herein as being "connected" or "connected" to another element, it may mean directly connected or connected to the other element, Element may be present. In addition, the content of " including " a specific configuration in this specification does not exclude a configuration other than the configuration, and means that additional configurations can be included in the scope of the present invention or the scope of the present invention.

The terms first, second, etc. may be used to describe various configurations, but the configurations are not limited by the term. The terms are used for the purpose of distinguishing one configuration from another. For example, without departing from the scope of the present invention, the first configuration may be referred to as the second configuration, and similarly, the second configuration may be named as the first configuration.

In addition, the components shown in the embodiments of the present invention are shown independently to represent different characteristic functions, and do not mean that the components are composed of separate hardware or software constituent units. That is, each constituent unit is included in each constituent unit for convenience of explanation, and at least two constituent units of each constituent unit may form one constituent unit or one constituent unit may be divided into a plurality of constituent units to perform a function. The integrated embodiments and the separate embodiments of each component are also included in the scope of the present invention unless they depart from the essence of the present invention.

In addition, some of the components are not essential components to perform essential functions in the present invention, but may be optional components only to improve performance. The present invention can be implemented only with components essential for realizing the essence of the present invention except for the components used for performance improvement, Are also included in the scope of the present invention.

FIG. 1 illustrates a learning system 100 for learning history management according to an embodiment of the present invention.

The learning system 100 of the present invention can be provided in a terminal in which a learning / management program is stored. Here, the terminal may mean a multimedia device based on wired / wireless communication such as a PC, a smart phone, a tablet PC, and the like.

1, a learning system 100 according to the present invention includes a server 110, a learning paper generating unit 120, a scoring unit 130, a map generating unit 140, a weak list generating unit 150 And a learning history database 160. [0050]

The server 110 may refer to a data base for storing a plurality of problems for learning. For example, the server 110 may store a code-based Math Knowledge List. Here, the mathematical knowledge list can be composed of problems sorted by type. For one particular type, at least one problem can be mapped for each degree of difficulty. An identification code may be assigned to each type to identify the problem types defined in the mathematical knowledge list. Since one problem can be mapped to a plurality of problem types, one problem can have a plurality of associated identification codes. If a plurality of identification codes are assigned to one problem, one representative similar group code representing a plurality of identification codes may be additionally allocated. The code-based mathematical knowledge list will be described in detail with reference to FIG. Hereinafter, the code can be flexibly interpreted to mean one identification code or representative similarity code assigned to one problem.

1, the server 110 is included in the learning system 100. However, the server 110 may be located outside the learning system 100 and may be connected to the learning system 100 by wire / wireless communication Of course.

The learning paper generation unit 120 can generate a learning paper using at least one problem stored in the server. To this end, the learning paper generator 120 may include software for generating a learning paper according to the level or capability of the learner. For example, when the learning paper generation information about at least one of the code, the learning range, the learning type, and the learning difficulty is input from the learner, the learning paper generating unit 120 generates the learning paper A problem of the learner designation among the problems can be identified and called to generate a learning paper (hereinafter, referred to as a first learning paper). In addition, the work sheet generating unit 120 may have an output function for the generated first work sheet, and may output the sheet in the form of a paper document or an electronic document.

In addition, the study paper generation unit 120 may generate the first study paper by considering the learning history for each learner. For example, it is possible to generate the current first learning work in consideration of whether the problem is the same as the problem already used in the previously generated first learning work for a specific learner. Alternatively, among the problems used in the at least one first learning paper previously generated, it may be possible to restrict the generation of the current first learning paper by using the problem that the frequency of use is smaller than the predetermined threshold value. For this purpose, a frequency of use may be assigned to each question used in the previous first learning work, and the frequency of use may be updated each time the first learning work is generated. Here, a pre-determined value may be used as a predetermined threshold, and a variable value adaptively determined according to the level or ability of the learner at the request of the learner or manager may be used .

The scoring unit 130 may score a learning paper (hereinafter, referred to as a second learning paper) in which the learning process of the learner is completed with respect to the first learning paper created by the learning paper generation unit 120. [

The scoring unit 130 may convert the second tutorial to a form of a picture or convert it into a form of an electronic file through a scan, and perform scoring on the converted second learning work. The scoring unit 130 may use a scoring program to perform the conversion process and scoring.

Specifically, the scoring unit 130 may perform scoring on the converted second learning material through mapping analysis between the second learning material and the scoring data. Here, the scoring data may mean data composed of a problem and a corresponding answer. A problem to be mapped to the problem of the second learning material can be determined from the scoring data and a scoring can be performed on the problem of the second learning material based on the answer corresponding to the determined question. A problem keyword mapping scheme may be used to determine the problem that is mapped from the scoring data to the problem of the second tutorial. The keyword mapping method of the present invention may mean a method of extracting a keyword from the problem of the second learning material and searching for a problem having the keyword in the scoring data. Here, the keyword can be determined as a character at a position set in line-by-line in the problem of the second learning material. In this manner, the same problem as that of the second learning material can be determined from the scoring data by mapping between the question of the second learning material and the scoring data based on the position of the keyword and the keyword.

The map generating unit 140 may generate a Math Knowledge Map showing a strong part and a weak part of the learner based on the scoring result of the second learning material. The generated Math Knowledge Map will be described in detail with reference to FIG.

Also, the map generator 140 may calculate the achievement of the learner based on the scoring result of the second learning material, and determine whether to re-learn by comparing the calculated achievement with the threshold.

Here, the achievement can be expressed as a percentage of correct answer to the problem. In addition, the correct answer rate can be calculated by applying different weights to the problem that the correct answer is matched with the problem that does not match the correct answer in consideration of whether the problem is a previously learned problem. For example, if the problem is a previously learned problem, the correct answer rate can be calculated by applying a weight that is larger than the problem that is the correct answer to the problem that did not meet the correct answer. However, if the problem is a problem that has not been learned previously, the correct answer rate can be calculated by applying the same weighting to the problem that the correct answer is matched to the problem that does not match the correct answer.

The threshold may be a pre-determined value in the map generator 140, or may be a value determined adaptively by the administrator in consideration of the level or capability of the learner.

The week list creator 150 may create a weak list for the weak part of the learner based on the math knowledge map generated by the map generator 140 . Here, the week list may include at least one of a code related to a learner's week area, a learning range, a learning type, or a learning difficulty, which will be described in detail with reference to FIG.

The learning history data base 160 stores the first and second learning materials from the learning material generating unit 120, the scoring unit 130, the map generating unit 140 and the week list generating unit 150, A Math Knowledge Map, and a weak list, so that the learning history of the learner can be managed.

FIG. 2 illustrates a code-based Math Knowledge List according to an embodiment of the present invention.

Referring to FIG. 2, the mathematical knowledge list of the present invention may be composed of at least one of a code, a type, and a degree of difficulty of a problem. Here, the code is for identifying each of a plurality of types belonging to the learning range, and may be assigned to each of the types defined in the mathematical knowledge list. There may be at least one problem with respect to one type, and if there are a plurality of problems, it is necessary to classify each problem by difficulty level. To this end, the mathematical knowledge list may use an identifier (for example, BOB-1, BOB-2, SA-1, SA-2) indicating the difficulty level of the problem.

FIG. 3 illustrates a Math Knowledge Map generated by the map generator 140 according to an embodiment of the present invention. Referring to FIG.

Referring to FIG. 3, the Math Knowledge Map of the present invention may include at least one of a learning range, a code, and data on a strong / wek area of a learner.

Specifically, the mathematical knowledge map may show codes (or types) corresponding to the learning ranges.

Data on the strong / wek area of the learner can be allocated for each specific code. Here, the data on the strong / wek area of the learner may mean information indicating whether the specific problem belongs to the strong area or the wek area.

For example, the data for the strong / weak region includes four types of data such as a first strong region (very strong), a second strong region (strong), a first weak region (weak) and a second weak region (very weak) . &Lt; / RTI > However, the present invention is not limited thereto, and the number of types can be variably determined within a range that is obvious to a person skilled in the art. At this time, as a criterion for distinguishing each region, the percentage of correctness of a problem with respect to a specific code or a specific type can be used. The mapping relationship between the learner's correct answer rate and the strong / weak area for a particular code can be defined as shown in Table 1 below.

type Percent correct (%) Strong / Week Area One 100-80 The first strong region 2 80-50 The second strong zone 3 50-25 First Week Area 4 25-0 Second Week Area

Also, the data about the Strong / Weak area may be assigned to the code in the form of a number or letter, or may be assigned to the code in the form of a color for visual implementation. Referring to FIG. 3, blue represents the first strong region, green represents the second strong region, yellow represents the first week region, and red represents the second week region. In this case, the blue assigned codes (eg, IR-12, IR-26, EA1-45, etc.) indicate that the learner is very strong for the type of problem, , IR-9, IR-30, EA1-10, etc.) indicate that the learner is very weak about the type of problem.

FIG. 4 illustrates a week list for a weak part created by the week list creating unit 150 according to an embodiment of the present invention. Referring to FIG.

Referring to FIG. 4, the week list of the present invention may include a code corresponding to a learner's week area and a type of a problem. In addition, the current week list can be updated based on the re-learning result for the week area. To this end, the week list may further include data on the number of re-learning and / or re-learning, and may further include a clinic result value indicating whether the learner's week area is changed to the strong area.

FIG. 5 illustrates a method of managing a learning history of a learner in the learning system 100 according to an embodiment of the present invention.

Referring to FIG. 5, the server 110 may transmit a problem to the work paper generation unit 120 (S500). The server 110 may transmit a problem when there is a problem transmission request from the work paper generation unit 120. [ Here, the problem to be transmitted may be one specified by the learning paper generation information input from the learner. As shown in FIG. 1, the learning paper generation information relates to at least one of a code, a learning range, a learning type, or a learning difficulty.

The learning paper generation unit 120 may generate the first learning paper using at least one of the transmitted problems (S510).

The learning paper generation unit 120 may generate a learning paper, that is, a second learning paper, on which the learning process is completed based on the input signal of the learner (S515).

The generated second tutoring can be transmitted to the scoring unit 130 and transmitted to the learning history database 160 for learning history management of the learner (S520).

The scoring unit 130 may perform scoring on the second learning material transmitted using the scoring program (S525). For example, the second learning material can be scored through the mapping analysis between the second learning material and the scoring data, and the mapping analysis of the present invention has been described in detail with reference to FIG. 1, .

The scoring unit 130 may transmit the scored second learning material to the map generating unit 140 and may transmit it to the learning history database 160 for learning management of the learner (S530).

The map generating unit 140 may generate a Math Knowledge Map showing the strong part and the weak part of the learner based on the scoring result of the second learning material (S535) .

In addition, the map generator 140 may determine whether the learner is to re-learn based on the scoring result of the second learning material and / or the generated mathematical knowledge map (S540).

Specifically, it is possible to calculate the achievement of the learner based on the result of scoring of the second learning material, and determine whether to re-learn by comparing the calculated achievement with the threshold, which has been described in detail with reference to FIG. .

If it is determined in step S540 that re-learning is required for the learner, steps S510 to S535 may be performed again to update the currently generated Math Knowledge Map. The update to the mathematical knowledge map may be repeatedly performed until it is determined in step S540 that the re-learning is not required for the learner.

If it is determined in step S540 that the re-learning is not required for the learner, the map generator 140 may transmit the last updated mathematical knowledge map to the week list creator 150, Similarly, it may be transmitted to the learning history database 160 for the learning history management of the learner (S545).

The week list creator 150 may generate a weak list indicating a weak part of the learner based on the transmitted Math Knowledge Map at operation S550. On the other hand, steps S510 to S545 may be repeatedly performed on the week area on the week list, and the week list may be updated based on a mathematical knowledge map according to the execution result .

Claims

A learning paper creation unit for specifying a problem of designation of a learner based on the learning paper creation information input from a learner and generating a first learning paper using the specified at least one problem;
A scoring unit for scoring a second learning paper on which the learning process of the learner is completed with respect to the generated first learning paper;
A map generator for generating a mathematical instruction map showing a strong part and a weak part of the learner based on a scoring result of the second learning material;
A week list creating unit for creating a weak list for the learner's week area based on the generated mathematics instruction map; And
And a learning history database that stores at least one of the first learning material and the second learning material, the mathematical knowledge map or the week list, and manages the learning history of the learner. Management system.

The learning history management system according to claim 1,
And a server for storing a code-based mathematical knowledge list (Math Knowledge List).

3. The learning history management system according to claim 2, wherein the mathematical knowledge list includes the at least one problem for each type of problem and the degree of difficulty of the problem, and an identification code for identifying the type of the problem.

4. The learning history management system according to claim 3, wherein the learning paper generation information is data relating to at least one of the identification code, the type, and the degree of difficulty.

5. The apparatus according to claim 4,
Wherein the learning history management system limits the generation of the first learning material using only a problem that the frequency of use is less than a predetermined first threshold value among the problems used in the learning material previously generated.

The learning history management system according to claim 5, wherein the frequency of use is allocated to each of the problems stored in the server, and the frequency of use is updated each time a tutoring is generated.

6. The learning history management system according to claim 5, wherein the predetermined first threshold value is a variable value that is adaptively determined according to a pre-determined value or a level of the learner.

The apparatus according to claim 2,
Wherein the grading is performed by mapping between the problem from the second learning material and the grading data based on the keyword from the problem of the second learning material and the position of the keyword.

9. The method of claim 8,
Wherein the keyword is determined as a character at a position set in line-by-line in the problem of the second learning material, and the score data means data composed of a problem and an answer.

The learning history management system according to claim 2, wherein the mathematical knowledge map includes at least one of a learning range, an identification code, and data on a strong / weak area of a learner.

11. The learning history management system according to claim 10, wherein the data related to the strong / wake area means information indicating whether the specific problem belongs to the strong area or the wek area to the learner.

12. The apparatus according to claim 11,
Based on a mapping relationship between a correct rate of problems of a specific type and a strong / weak area type, whether a strong or weak area belongs to a strong area or a weak area.

13. The map generating apparatus according to claim 12,
Wherein the learning history management system calculates the achievement level of the learner based on the evaluation result of the second learning material, and determines whether to re-learn by comparing the calculated achievement with a predetermined second threshold value.

14. The learning history management system according to claim 13, wherein the achievement degree is calculated by applying different weights to a problem in which a correct answer is matched with a problem in which a correct answer is not matched with a previously learned problem.