KR102655119B1 - Method for matching study contents considering study tendency - Google Patents

Abstract

A learning content matching method that provides optimal learning content based on the learner's learning tendency is disclosed. The matching method inputs learning content and related information corresponding to the learning content from the user terminal, sets a group to which the learning content belongs, and the management server provides the learning content and information related to the learning content and learning. Storing and registering meta information of content; Inputting learner information and grade levels from the user terminal, and inputting the learner's learning propensity; And a step of the management server combining the grade and the learning propensity to extract and provide learning content groups matching the corresponding learner from the data server according to priority.

Description

Method for matching study contents considering study tendency}

The present invention relates to a method of matching learners and content, and particularly to technology that provides optimal learning content based on the learner's learning tendencies.

Recently, a form of learning is being conducted in which learners study online at their own expense and at their own expense, and the learning results are evaluated through a test recognized by the learning site or academy that provided the lecture or the government.

However, the above-mentioned online learning method is a provider-centered lecture, providing standardized, unit-specific lectures regardless of each learner's academic achievement, allowing learners to study overlapping areas of study they already know, saving time and money. Waste occurs.

For example, in Korea Registered Patent No. 0675438, the learning level of the learner is identified using a predetermined method, a course tailored to the learner's learning level is provided, and the understanding or achievement level of the course is tested. Based on the results of this test, the learner's weak learning areas are analyzed, and lectures, problems, and explanation videos corresponding to the analyzed weak learning areas are extracted and combined in real time from the combination database to provide customized courses and in-depth learning courses. , we are proposing an online customized learning method that combines lectures with an inverted pyramid-style infinite repetition of learning areas for the learner's weak areas.

This method does not take into account the fact that, from the learner's perspective, there are many differences in learning methods as well as inclinations, and that each learner has different concepts of weak areas and types of problems, so personalized content and methods are needed.

On the other hand, looking at Domestic Patent Publication No. 2019-0053983, a learning method of diagnosing the learner's disposition by selecting one of the disposition diagnosis means consisting of SSI, MBTI, and MLST tests is provided. It is starting.

However, these propensity diagnoses are mainly about psychological propensity and do not take into account the diagnosis of really important learning propensity, so they cannot provide a learning method that optimally matches the learner's learning propensity.

Moreover, there is no description of how the diagnosis results of the learner's tendencies are specifically applied and learning is achieved.

Therefore, the purpose of the present invention is to provide a learning content matching method based on a combination of the learner's grade level and learning propensity.

Another purpose of the present invention is to provide a learning content matching method that can enable self-directed learning to proceed reliably and efficiently.

According to the present invention, a user terminal including a computer device or a portable terminal is connected to a management server through the Internet, the management server is connected to a data server where learning content is stored, and a learning content matching application is installed to optimally match the learner. A learning content matching method applied to a learning content matching system that extracts learning content and provides it to the user terminal, inputting learning content and related information corresponding to the learning content from the user terminal, and selecting a group to which the learning content belongs. Setting a (group) and registering the management server by storing the learning content, information related to the learning content, and meta information of the learning content; Inputting learner information and grade levels from the user terminal, and inputting the learner's learning propensity; And a step of the management server combining the grade and the learning tendency to extract and provide learning content groups matching the corresponding learner from the data server according to priority. Learning content taking learning tendencies into account, comprising: A matching method is provided.

Preferably, the learning content group is provided as follows by the horizontal axis (column) representing the learner's grade level and the vertical axis (row) showing the degree of application, and the grade level is 8 or less, 6- or less along the horizontal axis. It is divided into the order 7, 5, 3-4, and 1-2, and the degree of application is divided into the order of concept, basics, utilization, application, and advanced description along the vertical axis.

Preferably, the relationship between the grade level and the learning content group may be as follows.

Preferably, the learning propensity consists of six questions: 1) ability to answer questions, 2) concentration, 3) concept organization, 4) application ability, 5) problem solving, and 6) problem solving at all levels, and each question has The answer stage can be composed of five stages in which the points are constantly increased.

Preferably, the learning tendency is concept organization, a) when the grade level is 1-2, the priority of recommended learning content for the answer to step 5 is 21, 2, 7, 12, 17, and b) When the grade level is 3-4, the priority of recommended learning content for answers to steps 4-5 is 16, 21, 2, 7, 12, c) When the grade level is 5, 3- The priorities of the recommended learning content for the answers to step 5 are 11, 16, 21, 2, and 7. d) When the above grade level is 6 to 7, the priority of the recommended learning content for the answers to steps 2 to 5 The rankings are 6, 11, 16, 21, and 2, and e) when the grade is lower than 8, the priority of recommended learning content may be 1, 6, 11, 16, and 21.

Preferably, the learning tendency is application ability, a) when the grade level is 1-2, the priority of recommended learning content is 25, 20, 15, 10, 5, and b) when the grade level is 3-4 When the grade is 5, the priority of recommended learning content for answers in steps 2-5 is 20, 15, 10, 5, 24, and c) when the above grade is 5, recommendations for answers in steps 3-5 The priorities of learning content are 15, 10, 5, 24, 19, and d) when the above grade level is 6-7, the priorities of recommended learning content for the answers to steps 4-5 are 10, 5, 24. , 19, and 14, and e) when the grade is 8 or lower, the priority of recommended learning content for the answer to step 5 may be 5, 24, 19, 14, or 9.

Preferably, the learning tendency is problem solving, and a) when the grade level is 1-2, the priorities of recommended learning content for answers to steps 1-2 and 4-5 are 20, 19, 18, and 20, respectively. 25, 24, 23, and b) when the above grade level is 3-4, the priority of recommended learning content for the answers to steps 1-2 and 4-5 is 15, 14, 13 and 20, 19, 18. and c) when the grade level is 5, the priorities of recommended learning content for the answers to steps 1-2 and 4-5 are 10, 9, 8 and 15, 14, 13, and d) the grade level When the grade is 6-7, the priority of recommended learning content for the answers to steps 1-2 and 4-5 is 5, 4, 3, and 10, 9, and 8, e) When the grade is 8 or lower , the priorities of recommended learning content for the answers to steps 1-2 and 4-5 may be 5, 4, and 3.

Preferably, the learning tendency is problem solving at all levels, and a) when the grade level is 1-2, the priorities of recommended learning content for answers to levels 4-5 are 21, 17, 13, and 9, respectively. 5, b) when the grade is 3-4, the priority of recommended learning content for answers to steps 4-5 is 16, 12, 8, 4, and c) when the grade is 5. , the priorities of the recommended learning content for the answers to steps 4-5 are 11, 7, and 3, d) When the above grade level is 6-7, the priorities of the recommended learning content for the answers to steps 4-5 is 6, 2, and e) when the grade is 8 or lower, the priority of recommended learning content for the answers to steps 4 and 5 may be 1.

Preferably, when the management server combines the grade level and the learning tendency to extract the learning content group by priority, the question takes priority over the grade level in the criteria for determining priority, and within the question, You can follow the priority order for each question above.

Preferably, the learning content registration step may further include inputting whether the corresponding learning content can answer questions.

According to the matching method of the present invention, the learner's learning efficiency can be maximized because recommended learning content is extracted by combining the learner's grade level and the learning tendencies of various learners.

Figure 1 shows a network configuration applied to the present invention.
Figure 2 is a flow chart showing the matching method of the present invention.
Figure 3 shows an input table for selecting a learning content group.
Figures 4(a) to 4(e) show the priority of recommended learning content according to the learner's grade level.
Figures 5(a) to 5(f) show a screen for entering the answer steps for each question.
Figures 6(a) to 6(e) show the priority of recommended learning content according to the level of the learner's answer to the concept summary questions.
Figures 7(a) to 7(e) show the priority of recommended learning content according to the level of the learner's answer to the application questions.
Figures 8(a) to 8(e) show the priority of recommended learning content according to the stage of the learner's answer to the problem-solving question.
Figures 9(a) to 9(e) show the priority of recommended learning content according to the level of the learner's answer to all level problem-solving questions.
Figure 10 shows an example of contents input for each question by a learner to explain the matching method of the present invention.

It should be noted that the technical terms used in the present invention are only used to describe specific embodiments and are not intended to limit the present invention. In addition, the technical terms used in the present invention, unless specifically defined in a different sense in the present invention, should be interpreted as meanings generally understood by those skilled in the art to which the present invention pertains, and should not be used excessively. It should not be interpreted in a comprehensive or excessively reduced sense.

Hereinafter, specific embodiments of the present invention will be described in detail with reference to the attached drawings. In the description below, 'learning content' includes not only lecture videos, but also equivalent animations and lecture audio.

Figure 1 shows a network configuration applied to the present invention.

A computer device 100 or a smartphone 110 can be used as a user terminal for applying the matching method of the present invention, and can be connected to the management server 200 through the Internet 150, for example.

The management server 200 is connected to the data server 300 where the learning content is stored, and a learning content matching application is installed to extract learning content optimally matched to the learner and provide it to the user terminals 100 and 110.

Learners can access the web page provided by the management server 200 using the computer device 100 or the smartphone 110 to search for learning content, and download and play the desired learning content when necessary. You can create your own web page.

Figure 2 is a flow chart showing the matching method of the present invention.

<Registration of learning content>

The learning content provider provides learning content, for example, a lecture video, to the management server 200 from a computer device via the Internet, and the management server 200 stores the learning content together with the items entered by the learning content provider on a data server ( 300) and save it.

Here, the learning content provider may be an instructor or teacher, or a professional content producer who produces content under their guidance.

When a learning content provider accesses the management server 200 through the user terminal 100 or 110 to register learning content, the management server 200 provides the input screen of FIG. 3 to receive information related to the learning content. .

First, the learning content provider inputs relevant information corresponding to the learning content, such as subjects, units, and subunits (step S21).

The subject can be one of Korean, Mathematics, English, Gwatam, and Sattam, and multiple subunits can be selected.

Next, set the group to which the learning content belongs (step S22).

An input table as shown in Figure 4 can be provided so that the learning content provider can easily select a learning content group.

Specifically, looking at Figure 4, the horizontal axis (column) represents the learner's grade level and the vertical axis (row) represents the degree of application.

Grade levels can be divided into 1-2, 3-4, 5, 6-7, and 8 or less to represent a uniform number of people in each grade zone based on the learner's normal grade distribution.

The application level is divided into five levels, starting with the lowest application level, concept, basic, utilization, application, and advanced description. Specifically, the concepts are at the level of middle school content, concept explanation and grammar organization, the basics are at the level of concept explanation and CSAT 2-point problems, the utilization is at the level of application problem solving and CSAT 3-point problems, the application is at the level of application problems and CSAT 4-point problems, and In-depth descriptions represent the highest level of difficulty and descriptive problems.

Therefore, once it is determined which level of grade and application level the learning content to be registered corresponds to, the learning content group (Group 1 to Group 25) is determined by their combination.

Figure 4 shows that the content of the learning content to be registered corresponds to a grade level of 3-4 and an application level of 'Application', so the learning content provider inputs the learning content into group 19.

Next, input whether an answer service is available when the learner asks a question about the registered learning content (step S23).

After going through the above steps, the management server 200 stores the learning content and related information input by the learning content provider in the data server 300 along with meta information of the learning content, such as playback time.

In this way, since the instructor or teacher who directly or indirectly produces the learning content directly classifies the grade level and degree of application related to the learning content, it is possible to lay the foundation for optimal matching between the learner and the learning content.

<Member registration>

The learner accesses the management server 200 and performs member registration.

First, register as a member by entering learner information including name, school, grade, gender, address, phone number, email, ID, and password on the web page provided by the management server 200 (step S24).

Next, the learner enters the grades for each subject, that is, Korean, English, mathematics, and Gwatam and Satam (step S25).

Here, the grade of performance may be divided into grades 1-2, 3-4, 5, 6-7, and 8 to maintain consistency with the input table of FIG. 3.

Learners, such as high school students, take mock exams at least twice a year and know their grade level for each subject, so they input their current grade status and manage it by refreshing it about four times a year. By doing this, you can proceed with true self-directed learning.

The grade entered by the learner is used as one of the criteria for the order of recommending learning content. Figures 4(a) to 4(e) show an example of the priority of recommended learning content according to the learner's grade. Priorities are indicated by dotted arrows.

Next, the learner enters each answer to a number of questions to provide his/her learning tendencies (step S26).

Figures 5(a) to 5(f) show a screen for entering the answer steps for each question.

The input screen lists a total of 6 questions, and each question is structured so that you can enter the answer in steps 1 to 5 according to your grade.

In this embodiment, the six questions are (1) concept organization, (2) application ability, (3) problem solving, (4) problem solving at all levels, (5) ability to answer questions, (6) concentration, and input stage. It is divided into five levels, for example, level 1 is ‘strongly not’, level 2 is ‘no’, level 3 is ‘average’, level 4 is ‘yes’, and level 5 is ‘very much’.

Each stage is assigned points, ranging from 1 to 5 points from stage 1 to stage 5, and the score for each stage is used as a standard when determining the order of each question.

Question (5) checks whether the learning content is 'possible to answer questions', which is determined based on the information entered in step S23 of registering the learning content, and gives priority to learning content that can answer questions.

The priority standard is, for example, when selecting steps 1-3, there is no priority, and when selecting steps 4-5, priority is given to learning content that allows questions.

Question (6) checks the learner's concentration, and the criteria for determining priority are, for example, when selecting level 1, priority is given to learning content with a playback time of less than 30 minutes, and when selecting level 2, priority is given to learning content with a playback time of less than 45 minutes. Priority is given to learning content, and when selecting steps 3-5, there is no priority regardless of playback time.

In this way, for questions (5) and (6) among the six questions, the priority of recommended learning content is determined regardless of the grade level, while the answer to each question except this is combined with the grade level to determine the priority of learning content recommendation. are different from each other.

Hereinafter, this will be described in detail with reference to FIGS. 6 to 9.

Figure 6 shows that recommendations are omitted (indicated by hatching) or priority is determined depending on the stage of the learner's answer to question (1) (concept summary). Figures 6(a) to 6(e) show Recommended content for learners' answers at each grade level for question (1) is displayed as a content group, and in particular, the priority of recommended content is indicated by a dotted arrow.

In this embodiment, the number of recommended contents is shown as 5, but is not limited to this number.

Specifically, if the answer of a learner with a grade of 1-2 is 2-5 levels, the recommendation is omitted, and if the answer of a learner with a grade of 3-4 is 3-5, the recommendation is omitted, and for a learner with a grade of 5 If the answer is level 4 or 5, the recommendation is omitted, and if the answer of a learner with a grade of 6 or 7 is level 5, the recommendation is omitted. On the other hand, answers from learners with a grade of 8 or lower are not recommended at any level.

In addition, Figure 6(a) shows the priority when the answer of a learner with grade 1-2 is level 1, and Figure 6(b) shows the priority when the answer of a learner with grade 3-4 is level 1-2. Shows the ranking, 6(c) shows the priority when the answer of a learner with grade 5 is steps 1-3, and 6(d) shows the priority when the answer of a learner with grade 6-7 is steps 1-4. 6(e) shows the priority of learners with grades 8 or lower.

Figure 7 shows that recommendations are omitted (indicated by hatching) or priority is determined depending on the level of the learner's answer to question (2) (applicability). Figures 7(a) to 7(e) show the question Recommended content for the learner's answer to each grade level for (2) is shown as a content group, and in particular, the priority of the recommended content is indicated by a dotted arrow.

Likewise, the number of recommended contents is shown as 5, but it is not limited to that number.

Specifically, responses from learners with grades 1-2 are not recommended for any level. In addition, if the answer of a learner with a grade of 3-4 is in level 1, the recommendation is omitted, if the answer of a learner with a grade of 5 is in level 1-2, the recommendation is omitted, and the answer of a learner with a grade of 6-7 is omitted. If the answer is level 1-3, the recommendation is omitted, and if the answer of a learner with a grade of 8 or lower is in level 1-4, the recommendation is omitted.

In addition, Figure 7(a) shows the priority for learners with grades 1-2, and Figure 7(b) shows the priorities for learners with grades 3-4 whose answers are grades 2-5. 7(c) shows the priority when the answer of a learner with grade 5 is level 3-5, and 7(d) shows the priority when the answer of a learner with grade 6-7 is level 4-5. 7(e) shows the priority when the answer of a learner with a grade of 8 or lower is level 5.

Figure 8 shows that recommendations are omitted (indicated by hatching) or priority is determined depending on the stage of the learner's answer to question (3) (problem solving). Figures 8(a) to 8(e) show Recommended content for the learner's answer at each grade level for question (3) is displayed as a content group, and in particular, the priority of the recommended content is indicated by a dotted arrow.

Likewise, the number of recommended contents is shown as 5, but it is not limited to that number.

Specifically, recommendations are omitted only if the learner's answer at each grade level is level 3.

In addition, Figures 8(a) to 8(e) show recommended learning content corresponding to each case where the learner's answer at each grade level is 1-2 and 4-5, and the priority is indicated by a dotted arrow.

Figure 9 shows that recommendations are omitted (indicated by hatching) or priority is determined depending on the level of the learner's answer to question (4) (all level problem solving), Figures 9(a) to 9(e) ) shows the recommended content for the learner's answer at each grade level to question (4) as a content group, and in particular, the priority of the recommended content is indicated by a dotted arrow.

Likewise, the number of recommended contents is shown as 5, but it is not limited to that number.

Specifically, recommendations are omitted only when the learner's answer for each grade level is 1-3 levels, and when the learner's answer for each grade level is 4-5 levels, the priority is shown.

<Matching of learning contents>

Figure 10 shows an example of input content for each question by a learner to explain the matching method of the present invention.

For convenience, in this embodiment, it is assumed that the learner's grade level is 5th grade.

Here, in determining priority, the question basically takes priority over the grade level, and within the question, the priority for each question, which will be described later, is followed.

There is no priority level for the question itself, but priority is given by points allocated according to the level of answer to the question.

Question (1) (the concept is not well organized) was rated as ‘yes’ with 4 points, question (2) (good applicability) was rated as ‘average’ with 3 points, and question (3) (I want to solve a lot of problems) was rated as ‘yes’. 4 points, and question (4) (I want to solve problems at all levels) is given 5 points as ‘strongly agree’.

Additionally, questions (5) and (6) are not assigned points because they only determine whether or not they are applied based on priority. Here, question (5) (possible to answer questions) is applied as a priority standard as 'yes', and question (6) (good concentration) is not applied as a priority as 'average'.

The priority for each question is question (4) - question (1) - question (3) - question (2) with the highest score, and learning content that can answer questions according to question (5) is given priority.

Recommended content groups for each question will be described with reference to FIGS. 6 to 9.

For question (4) (I want to solve all level problems), the recommended content groups are in the order of 11, 7, and 3, as shown in Figure 9(c).

For question (1) (concept summary), as shown in Figure 6(c), the recommended content groups are in the order of 11, 16, 21, 2, and 7.

For question (3) (I want to solve a lot of problems), the recommended content groups are in the order of 15, 14, and 13, as shown in Figure 8(c).

For question (2) (good applicability), as shown in Figure 7(c), the recommended content groups are in the order of 15, 10, 5, 24, and 19.

Additionally, as mentioned above, in this embodiment, the student's grade level is 5, so referring to FIG. 5(c), the recommended content groups are in the order of 15, 14, 13, 12, and 11.

If you organize this and count the number of appearances of each recommended content group, it appears 3 times (11, 15), 2 times (7, 14, 13, 10), and 1 time (3, 16, 21, 2, 7, 9, 8, 5, 24, 19, 12).

Here, the priority for the same number of occurrences follows the priority for each question.

Therefore, the final order of recommended content groups that optimally matches the learner's grade level and learning tendency is 11, 15, 7, 14, 13, 3, 16, 21, 2, 10, 5, 24, 19, 12. The order is:

Optionally, the level of the learning content provider may be further added to the criteria for determining the matching order to determine the order of the recommended content group. In other words, among learning contents belonging to the same group, learning contents from a higher level learning content provider may appear first.

As described above, according to the matching method of the present invention, the learner's learning efficiency can be maximized because recommended learning content is extracted by combining the learner's grade level and the learning tendencies of various learners.

Although the above description focuses on embodiments of the present invention, it goes without saying that various changes can be made at the level of those skilled in the art. Therefore, the scope of the present invention cannot be construed as limited to the above-described embodiments, and should be interpreted in accordance with the claims set forth below.

100: computer device
110: smartphone
150: Internet
200: Management server
300: data server

Claims (11)

A learning content matching method applied to a learning content matching system in which a wired or wireless user terminal is connected to a management server through the Internet, and the management server is connected to a data server storing learning content,
A learning content matching application is installed on the management server to extract learning content that optimally matches the learner and provide it to the user terminal,
The learning content matching method is,
The user terminal receives learning content, related information corresponding to the learning content, and a group to which the learning content belongs through manipulation by a learning content provider, and transmits the input to the management server;
Here, the relevant information corresponding to the learning content includes subjects, units, and subunits, and the learning content group is a combination of the learner's grade level and the degree of application divided into the order of concept, basic, utilization, application, and advanced description. decided,
The management server storing and registering the learning content, related information and groups of the learning content, and meta information of the learning content;
Entering learner information and the learner's grade from the user terminal, and entering answers to questions for determining the learner's learning propensity; and
Learning content matching considering learning tendencies, comprising the step of the management server combining the grade and the learning tendencies to extract and provide learning content groups matching the corresponding learner from the data server according to priority. method. In claim 1,
The learning content group is provided in the table below by the coordinates of the horizontal axis (column) representing the learner's grade level and the vertical axis (row) representing the degree of application,
The performance level is a learning content matching method considering learning tendency, characterized in that it is divided into grades 8 or lower, grades 6-7, grades 5, grades 3-4, and grades 1-2 along the horizontal axis.

In claim 2,
A learning content matching method considering learning propensity, characterized in that the relationship between the grade level and the learning content group is as follows.
In claim 2,
The learning tendency consists of six questions: 1) ability to answer questions, 2) concentration, 3) concept organization, 4) application ability, 5) problem solving, and 6) problem solving at all levels,
A learning content matching method that takes into account learning tendencies, characterized in that the answer to each question consists of 5 stages in which the points are constantly increased. In claim 4,
The learning tendency is concept organization,
a) When the above grade level is 1-2, the priority of recommended learning content for the answer to step 5 is 21, 2, 7, 12, 17,
b) When the above grade level is 3-4, the priorities of recommended learning content for answers to levels 4-5 are 16, 21, 2, 7, 12,
c) When the above grade level is 5, the priority of recommended learning content for the answers to steps 3 to 5 is 11, 16, 21, 2, and 7,
d) When the above grade level is 6-7, the priorities of recommended learning content for answers to steps 2-5 are 6, 11, 16, 21, 2,
e) When the grade level is 8 or lower, the priorities of recommended learning content are 1, 6, 11, 16, and 21. Learning content matching method considering learning tendency. In claim 4,
In claim 4,
The learning tendency is application ability,
a) When the above grade level is 1-2, the priority of recommended learning content is 25, 20, 15, 10, 5,
b) When the above grade level is 3-4, the priority of recommended learning content for the answers to steps 2-5 is 20, 15, 10, 5, 24,
c) When the above grade level is 5, the priority of recommended learning content for the answers to steps 3-5 is 15, 10, 5, 24, 19,
d) When the above grade level is 6-7, the priority of recommended learning content for the answers to steps 4-5 is 10, 5, 24, 19, 14,
e) When the grade is 8 or lower, the priority of recommended learning content for the answer to step 5 is 5, 24, 19, 14, and 9. Learning content matching method considering learning propensity. In claim 4,
The learning tendency is problem solving,
a) When the above grade level is 1-2, the priorities of recommended learning content for answers to steps 1-2 and 4-5 are 20, 19, 18 and 25, 24, and 23, respectively,
b) When the above grade level is 3-4, the priorities of recommended learning content for answers to steps 1-2 and 4-5 are 15, 14, 13 and 20, 19, 18,
c) When the above grade level is 5, the priorities of recommended learning content for answers to steps 1-2 and 4-5 are 10, 9, 8, and 15, 14, and 13,
d) When the above grade level is 6-7, the priorities of recommended learning content for answers to steps 1-2 and 4-5 are 5, 4, 3, and 10, 9, and 8,
e) When the grade is 8 or lower, the priorities of recommended learning content for the answers to steps 1-2 and 4-5 are 5, 4, and 3. A learning content matching method considering learning tendencies. In claim 4,
The learning tendency is problem solving at all levels,
a) When the above grade level is 1-2, the priorities of recommended learning content for the answers to steps 4-5 are 21, 17, 13, 9, and 5, respectively.
b) When the above grade level is 3-4, the priority of recommended learning content for answers to levels 4-5 is 16, 12, 8, 4,
c) When the above grade level is 5, the priority of recommended learning content for the answers to steps 4 and 5 is 11, 7, and 3,
d) When the above grade level is 6-7, the priority of recommended learning content for the answers to steps 4-5 is 6 and 2,
e) When the grade is 8 or lower, the priority of recommended learning content for the answers to steps 4 and 5 is 1. A learning content matching method considering learning propensity. delete delete A learning content matching method applied to a learning content matching system in which a wired or wireless user terminal is connected to a management server through the Internet, and the management server is connected to a data server storing learning content,
A learning content matching application is installed on the management server to extract learning content that optimally matches the learner and provide it to the user terminal,
The learning content matching method is,
The user terminal receives learning content, related information corresponding to the learning content, and a group to which the learning content belongs through manipulation by a learning content provider, and transmits the input to the management server;
Here, the relevant information corresponding to the learning content includes subjects, units, and subunits, and the learning content group is a combination of the learner's grade level and the degree of application divided into the order of concept, basic, utilization, application, and advanced description. decided,
The management server stores and registers the learning content, related information and groups of the learning content, and meta information of the learning content, and inputs whether the learning content is capable of answering questions;
Entering learner information and the learner's grade from the user terminal, and entering answers to questions for determining the learner's learning propensity; and
A step of the management server extracting and providing learning content groups matching the learner by priority from the data server by combining the grade level and the learning tendency,
When extracting the learning content group by priority, the question takes priority over the grade level in terms of priority judgment, and within the question, priority is given based on the points assigned to the answer to the question. Learning content matching method considering learning tendencies.

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