KR101652500B1 - Smart learning system based on the real-time knowledge sharing - Google Patents

Abstract

A real-time knowledge-based shared smart learning system and method for interactively teaching a plurality of users to share a mobile (e.g., smartphone) screen in real time to ask and answer a question, A learner terminal for presenting a problem, performing a query, and receiving a learning while interacting with an answerer terminal in real time through a query and a response, while sharing a screen through a screen sharing function with an answerer terminal; An answerer terminal for sharing a screen through the screen sharing function with the learner terminal and learning how to solve a problem while interacting with a voice about an answer; And registering, in a database, a solution recording image of a response provided from the answerer terminal, searching the database in response to a search request, To the search request terminal, and the smart learning system is implemented.

Description

[0001] The present invention relates to a smart learning system and a real-

The present invention relates to a real-time knowledge-based shared smart learning, and more particularly, to an interactive learning method capable of sharing a mobile (e.g., smartphone) screen among a plurality of users in real time, Based knowledge sharing system and a method thereof.

In general, online and offline education is a one-sided education system in which one educator (the teacher) teaches a small number of learners (educators) or a large number of learners. However, this general education system is a one-way education system, and education efficiency is not so high because it is a simple injection education.

To improve the problem of unidirectional infant education, educational methods such as K-math, Wisemeet, and Bapul have been conventionally proposed.

Here, K-math is a teaching method that provides a problem to the user, scoring based on the user's problem, and providing a short video solution for each problem.

In addition, WiseMit is an online meeting room concept, sharing the documents you see with your opponents, and writing your pen in the document.

In addition, unraveling is a learning SNS that allows you to ask and answer math questions. When you take a picture of a question and put it along with the explanation, another user puts up a picture that he or she has solved and responds with little explanation.

Meanwhile, another prior art proposed to improve the problem of unidirectional injection type education is disclosed in Korean Patent Laid-Open Publication No. 10-2009-0040800 (published on Apr. 27, 2009) and Non-Patent Document 1 > Jaejae, Duphwa, Kim Tae Suk, "Web-based learner-centered mathematical problem solving system", Korea Multimedia Society, Spring 2002 (pp. 786-791.

Patent Document 1 discloses a method of analyzing an answer to a problem in real time by moving away from a conventional unidirectional offline test form, and when a correct answer or an incorrect answer message is input at the same time, the correct answer rate, correct answer number, It provides a real-time response check program that shows the number of people and the number of checkers for each item by statistics using bar graphs and numerical values, displays correct answers, and also shows commentary on correct answers.

<Non-Patent Document 1> is a web-based question-and-answer learning method based on a multimedia-based instructional design model to develop a remote lecture program to solve problems by interacting with a teacher or other learner through learning- It provides a courseware design model and provides a remote learning system that solves real-time mathematical problems based on learner. In addition, after solving the problem, proceed with the remote lecture for annotation.

Korean Patent Publication No. 10-2009-0040800 (disclosed on Apr. 27, 2009)

Jaejae, Duplication, Kim Tae Suk "A Web-Based Learner-Centered Mathematical Problem-Solving System", Korea Multimedia Society, Spring 2002 (pp. 786-791

However, the K-math method is a one-way education method, and the learning effect is low because it does not interact with the educator and the learner. The WiseMeet method is a limited interactive training method, but also the interaction between the educator and the learner , The learning effect is low, and the method of solving the problem has the disadvantage that the learning effect is low because the interactive learning method or the limited interaction between the educator and the learner is performed.

Also, the conventional art disclosed in Patent Document 1 is a unidirectional real-time problem solving system that lacks interaction and low learning effect, and the prior art disclosed in Non-Patent Document 1 is a real- It is not an interaction, it is a way of teaching a remote lecture for annotation after solving problems.

It is an object of the present invention to provide a mobile communication terminal capable of sharing a mobile (e.g., a smartphone) screen among a plurality of users in real time to inquire and answer a problem in real time, A smart learning system and a method therefor are provided.

Another object of the present invention is to provide a real-time knowledge-sharing smart phone capable of enhancing learning efficiency by allowing users to inquire and answer questions while chatting with each other by adding a screen sharing function and a telephone function to a smartphone chat function A running system and a method thereof.

Another object of the present invention is to provide a method and system for real-time interactive and interactive learning, in which a learner can listen to a solving process and a description simultaneously by providing a voice while viewing the same screen, A knowledge-based shared smart learning system and a method thereof.

It is another object of the present invention to provide a real-time knowledge-based shared smart learning system and a method thereof, in which learning is performed through interaction among a plurality of users in real time without departing from spatial physical conditions.

Another object of the present invention is to provide a system and method for a learner to evaluate an educator and to provide a differential incentive to an educator based on the evaluation result, A real-time knowledge-based shared smart learning system and a method thereof.

In order to achieve the above object, a real-time knowledge-based shared smart learning system according to the present invention displays and queries a problem through a network, and real- A learner terminal that receives learning while interacting through inquiries and responses; An answerer terminal for accessing the learner terminal in real time via a network, sharing a screen through a screen sharing function, and interacting with a voice over an answer to learn a solution process for a problem; Registering a query process presented from the learner terminal in a database, registering a solution process recording video corresponding to a response provided from the answerer terminal in the database, searching the database in response to a search request, And an administrator terminal for transmitting the search request to the search request terminal.

In the above, the learner terminal and the answerer terminal are parallel to the learning function and the answer function, and the learner terminal and the answerer terminal are implemented as mobile devices capable of moving.

A learner terminal for generating a question to be queried; A tag selection unit for selecting a tag to be mapped to a problem generated for searching; A query problem registering unit for generating a query problem by mapping a problem to the tag and registering the query problem on a network of a problem query registration site; A control unit for controlling a query problem registration generated by the query problem registering unit and controlling a chat, a screen sharing, and a telephone function upon receiving a query response; A screen sharing unit for sharing a document sharing window in real time with an answer terminal upon receiving an answer according to the control of the control unit; And a chat window processing unit for chatting with the answer terminal through a chat window under the control of the control unit.

The learner terminal may further include an answer evaluation unit for generating assessment information on the answer presented by the answerer terminal in cooperation with the control unit.

The learner terminal may further include an image correcting unit for correcting an image of a query problem generated by the query problem registering unit under the control of the control unit.

In this case, the image correction unit distinguishes the query problem from the handwriting image and the general image, calculates the average brightness value in units of frames in the case of a general image, corrects the general image with interpolation on the basis of the calculated average brightness value, The brightness value is corrected based on the reference set value.

Wherein the answerer terminal comprises: an input unit for inputting search information for searching a query problem stored in the problem registration site or inputting a selection signal for selecting a query problem; A controller for controlling the generation and processing of a chat window and a screen sharing window for searching and selecting the query problem, an answer to a selected query problem, and the like; A chat window generating unit for generating a chat window for chatting on a query problem under control of the controller, listing chat information input through the input unit in the chat window, and displaying partner chat information in the chat window; And a screen sharing unit that shares a document sharing window with a learner terminal in real time when an answer is provided under the control of the controller.

The answer terminal may further include a recording unit for recording the record information of the document sharing window generated through the screen sharing unit and the problem solving voice inputted through the voice processing unit under the control of the control unit and generating the answer solving voice as an answer file do.

The answer terminal may further include an answer registration unit for registering an answer file generated by the recording unit on the problem registration site through a network under the control of the control unit.

The administrator terminal includes a tag providing unit for providing a tag for searching for a query problem to the learner terminal. A query problem register for registering a query problem; An answer registration unit for registering an answer file; A search processor for performing a search through a keyword search when a query for a query problem is requested by the terminal, and outputting a query problem and an answer file; A controller for controlling the tag provisioning, the query problem registration and the answer file registration, the search processing, and the evaluation information processing; And an evaluation information processing unit for registering the evaluation information transmitted from the learner terminal in a database, analyzing the evaluation information for each answerer to determine an incentive of the answerer, and guiding incentive information to the answerer.

In order to achieve the above object, a real-time knowledge-based shared smart learning method according to the present invention is a smart learning method for real-time knowledge sharing based on a real-time chat window, a document sharing window and a telephone function, A learner terminal and an answerer terminal; A method for performing knowledge-based shared smart learning in real time using a smart learning system including an administrator terminal for managing a query problem registration and an answer registration by interaction between the learner terminal and an answer terminal through a database,

The learner terminal includes: (a) generating a problem to be registered in a query problem registration site; (b) selecting a tag to search for the problem in association with the administrator terminal; (c) generating a query problem by mapping the problem to a tag; (d) storing the query problem and registering the query problem on the problem registration site; (e) creating a chat window and chatting when the answerer terminal is connected to the query problem; (f) receiving a document sharing window for solving a problem sent from the answer terminal during the chat and sharing a document sharing window; (g) querying the answer terminal in real time through the chat window and the telephone function, and listening to a description of the problem solving through the voice while viewing the problem solving information through the document sharing window do.

The learner terminal may further include a step of (h) correcting the image for the query problem when the image correction is requested before the step (d).

The learner terminal may further include (i) generating evaluation information on a question problem after the step (g), and registering evaluation information on the problem registration site.

The step (h) comprises the steps of: (h1) distinguishing the query problem as a letter image and a general image; (h2) calculating an average brightness value per frame in the case of the general image; (h3) correcting the general image with the calculated average brightness value, and correcting the handwritten image to a predetermined reference setting value for the handwritten image.

In order to achieve the above object, a real-time knowledge-based shared smart learning method according to the present invention is a smart learning method for real-time knowledge sharing based on a real-time chat window, a document sharing window and a telephone function, A learner terminal and an answerer terminal; A method for performing knowledge-based shared smart learning in real time using a smart learning system including an administrator terminal for managing a query problem registration and an answer registration by interaction between the learner terminal and an answer terminal through a database,

The answer terminal comprises: (a) selecting a query problem through a search of a query problem registration site; (b) creating a chat window by accessing the learner terminal registering the query question, and responding to the query problem through a chat; (c) creating a document sharing window when the creation of a document sharing window for solving a problem is requested during the chatting; (d) transmitting the generated document sharing window to the connected learner terminal and sharing the document sharing window with the learner terminal; (e) providing a response to the query problem with the learner terminal in real time through the chat window, the document sharing window, and the telephone function.

In the above, the answerer terminal records (f) a voice, a chat, and a document sharing window at the time of solving a problem through a chat and a document sharing window according to a request of a user, and registers a recorded answer file in the query question registration site Further comprising the steps of:

In order to achieve the above object, a real-time knowledge-based shared smart learning method according to the present invention is a smart learning method for real-time knowledge sharing based on a real-time chat window, a document sharing window and a telephone function, A learner terminal and an answerer terminal; A method for performing knowledge-based shared smart learning in real time using a smart learning system including an administrator terminal for managing a query problem registration and an answer registration by interaction between the learner terminal and an answer terminal through a database,

The administrator terminal comprises the steps of: (a) providing a tag for query problem search to the learner terminal; (b) registering a query problem transmitted from the learner terminal in a database; (c) registering an answer file transmitted from the answer terminal in the database; (d) searching the database based on the keyword inputted at the time of the search request and providing the search request terminal with the search query.

(E) registering an answer file in the database, receiving response evaluation information from the learner terminal and registering the response evaluation information in the database; (f) analyzing response evaluation information registered in the database to determine an incentive of the respondent, and the step (f) transmits the incentive information to the answer terminal in the incentive determination step.

According to the present invention, it is possible to implement an interactive training in which a plurality of users can share a mobile screen in real time to inquire and answer questions.

In addition, according to the present invention, there is an advantage that learning efficiency can be improved by adding a screen sharing function and a telephone function to a smartphone chat function, allowing a user to inquire and reply to each other in real time.

In addition, according to the present invention, it is possible to improve the meaning transfer by allowing the learner to simultaneously listen to the solving process and the explanation by providing questions and answers through interaction in real time, .

In addition, according to the present invention, there is an advantage that the learning can be realized through mutual action among a plurality of users in real time without departing from a spatial physical condition.

Further, according to the present invention, the learner evaluates the educator and provides the incentive to the educator based on the evaluation result, which has an advantage that the educator can induce heat and affection in the answer.

1 is a configuration diagram of a real-time knowledge-based shared smart learning system according to a preferred embodiment of the present invention;
FIG. 2 is a configuration diagram of an embodiment of the learner terminal of FIG. 1;
FIG. 3 is a block diagram of an embodiment of the educator terminal of FIG. 1;
FIG. 4 is a block diagram of an embodiment of the administrator terminal of FIG. 1;
FIG. 5 is a flowchart illustrating a smart learning process in a learner terminal among a real-time knowledge-based shared smart learning method according to the present invention;
Figure 6 is a flow chart of an embodiment of the image correction routine of Figure 5,
FIG. 7 is a flowchart illustrating a smart learning process in an educator terminal in a real-time knowledge-based shared smart learning method according to the present invention;
FIG. 8 is a flowchart illustrating a smart learning process in an administrator terminal among a real-time knowledge-based shared smart learning method according to the present invention.

Hereinafter, a real-time knowledge-based shared smart learning system and method according to a preferred embodiment of the present invention will be described in detail with reference to the accompanying drawings.

1 is a configuration diagram of a real-time knowledge-based shared smart learning system according to a preferred embodiment of the present invention.

A real-time knowledge-based shared smart learning system according to a preferred embodiment of the present invention includes a learner terminal 100, an answer terminal 200, a network 300, an administrator terminal 400, and a database 500.

In this case, the learner terminal 100 plays a role as a learner terminal in the case of querying the user's own problem, but plays the role of the answerer terminal in the case of answering another question. Similarly, the answerer terminal 200 plays the role of the answerer terminal in the case of answering, but acts as the learner terminal in the case of the question itself. Therefore, the learner terminal 100 and the answerer terminal 200 may perform two roles of learning and answer. However, in the present invention, the learner terminal and the answerer terminal are distinguished from each other for convenience of explanation.

The learner terminal 100 presents a question and queries through the network 300 and communicates with the answerer terminal 200 in real time via inquiry and response while sharing a screen through the screen sharing function with the answerer terminal 200 It plays a role of receiving learning while acting. The learner terminal 100 can be implemented in various mobile devices. In the present invention, it is assumed that the learner terminal 100 is a smart phone.

2 is a block diagram of an embodiment of the learner terminal 100, which includes a problem generation unit 106 for generating a question to be queried; A tag selecting unit 101 for selecting a tag to be mapped to a problem generated for searching; A query problem registering unit (108) for generating a query problem by mapping a problem to the tag and registering the query problem on a network at a registration site of the problem query; A control unit 105 for controlling registration of a query problem generated by the query problem registering unit 108 and controlling chatting, screen sharing and telephone function upon receiving a response to a query problem; A screen sharing unit 109 for sharing a document sharing window in real time with the answerer terminal 200 upon receipt of an answer according to the control of the controller 105; And a chat window processing unit 110 for chatting with the answerer terminal 200 through a chat window under the control of the controller 105.

The learner terminal 100 may include a communication unit 102 for communicating with the answerer terminal 200 or the administrator terminal 400 through the network 300; A display unit 103 for displaying information required when a query problem is generated or for solving a query problem on a screen and displaying a chat window and a shared document window on a screen individually or simultaneously when a problem is solved; A voice processing unit 104 for processing voice input by the learner or voice transmitted or recorded by the answerer; A storage unit 107 for storing a question or answer information; An answer evaluation unit (111) for generating evaluation information on the answer presented by the answerer terminal (100) in cooperation with the control unit (105); And an image correction unit 112 for correcting the image of the query problem generated by the query problem registering unit 108 under the control of the control unit 105. [

The answerer terminal 200 accesses the learner terminal 100 in real time through the network 300 and interacts with the answer through voice by sharing a screen through a screen sharing function, It plays a role of learning.

As shown in FIG. 3, the answerer terminal 200 includes an input unit 201 for inputting search information for searching for a query problem stored in the problem registration site, or for inputting a selection signal for selecting a query problem; A control unit 205 for controlling the search and selection of the query problem, the chat window for responding to the selected query problem and the screen sharing window creation and processing; The control unit 205 generates a chat window for chatting about a query problem, records the chat information input through the input unit 201 in the chat window, and displays the chat information of the partner in the chat window A chat window generation unit 206; And a screen sharing unit 207 for sharing a document sharing window in real time with the learner terminal 100 when an answer is provided under the control of the controller 206. [

The answerer terminal 200 records the record information of the document sharing window created through the screen sharing unit 207 and the problem solving voice inputted through the voice processing unit 204 according to the control of the controller 205 A recording unit 208 for generating an answer file; An answer registration unit 210 for registering an answer file generated by the recording unit 208 on the problem registration site through the network 200; A communication unit 202 for communicating with the learner terminal 100 and the administrator terminal 400 through the network 300; A display unit 203 for displaying a retrieved query problem and displaying a chat window and a document sharing window; And a storage unit 209 for storing the recorded answer file.

The manager terminal 400 registers the query problem presented from the learner terminal 100 in the database 500 and registers the solution process recording image corresponding to the answer provided from the answerer terminal 200 in the database 500 And searches for the database 500 in response to a search request and transmits the query and answer information requested to be searched to the search request terminal. The administrator terminal 400 also operates and controls the query problem registration site established on the web.

4, the administrator terminal 400 includes a communication unit 401 for communicating with the learner terminal 100 and the answerer terminal 200 through the network 300; An input unit 403 which is an input device for an administrator to input necessary information; A tag providing unit 402 for providing a tag for searching for a query problem to the learner terminal 100; A query problem registering unit 405 for registering a query problem; An answer registration unit 406 for registering an answer file; A search processing unit (407) for performing a search through a keyword search when a query for a query problem is requested by the terminal, and outputting a query problem and an answer file; A control unit 404 for controlling tag provision, query problem registration, answer file registration, search processing, and evaluation information processing; And an evaluation information processing unit (408) for registering evaluation information transmitted from the learner terminal (100) in the database (500), analyzing the evaluation information for each answerer to determine an incentive of the answerer, and guiding incentive information to the answerer.

The operation of the real-time knowledge-based shared smart learning system according to the present invention will now be described in detail.

First, the learner generates a problem through the problem generation unit 106 when a question problem requiring solving information occurs during learning. In this case, problems can be generated by photographing a problem using a camera, and problems can be generated in various ways in addition to generating such images. The tag selection unit 101 requests tag information to the administrator terminal 400 through the network 300 for later retrieval by posting the created problem on the query problem registration site operated by the administrator terminal 400 do. Here, the tag is identification information for identifying a problem, and may include a subject, a type, grade information, and the like.

The tag providing unit 402 of the administrator terminal 400 displays the tag information registered in the database 500 on the web browser of the learner terminal 100 and the tag selecting unit 101 of the learner terminal 100 transmits the tag information Select the tag according to the operation. Here, the tag selection unit 101 may be referred to as an input device. In this method, the administrator terminal 400 provides all the tag information. If the learner terminal 100 provides the classification information including the subject or the grade information in advance to the administrator terminal 400 in addition to this method, It is also possible to transmit only the registered tag information corresponding to the classification information to the learner terminal 100 in the terminal 400.

When a tag to be mapped to the generation problem is selected, the problem generation unit 106 generates a single file by mapping the generation problem and the tag according to the control of the control unit 105, and generates this as a query problem. Then, the learner can see the image condition of the generated query problem, and can correct the image if the image quality deteriorates. That is, the image correction unit 112 corrects the image of the query problem when the image correction is performed. For example, it distinguishes a question of quality from a letter image and a general image. Here, the handwriting image recognizes the handwriting image by recognizing the background color (usually white). Then, the image excluding the text image is judged as a general image in the whole image. Thereafter, image correction is performed. Here, the image correction can use various image correction methods known in the conventional image processing. For example, the entire image is divided into frames, and a Y value, which is the number of lines (the number of lines), is cumulatively calculated for each of the X-axis and the table, which is a horizontal image (number of pixels per line) for one frame. Similarly, the X value is cumulatively calculated for each of the Y-axis coordinates. Thereafter, an average of each cumulative value is obtained, and an interpolation method is used in which the brightness per pixel is compensated based on the calculated average value. If the brightness of the corresponding pixel is smaller than the average value, the brightness compensation is performed by applying a compensation value corresponding to the difference. If the brightness of the pixel is larger than the average value, the corresponding pixel is compensated for by not performing compensation. In addition, in case of a text image, a brightness reference compensation value according to resolution is set in advance, and the reference compensation value is compared with the brightness of the corresponding pixel, and compensation is performed by the difference.

When the correction of the image is completed using this interpolation method, the query problem is stored in the storage unit 107 and is also registered in the query problem registration site through the query problem registering unit 108. [

In a state where the question of question is registered in the question problem registration site, the answerer visits the question problem registration site using the answerer terminal 200 and searches for the question of the question. Here, the query problem retrieval method can search all the registered query problems one by one, and it is also possible to retrieve the query problems corresponding to the classification through classification information such as a subject or a grade in advance.

Then, if there is a query problem that can be answered, select the query problem. If the answerer selects the question problem, the question of the question including the information about the learner who registered the question by the control of the administrator terminal 400 (information for chatting, for example, a pre-registered telephone number, e-mail address, etc.) To the answerer terminal (200). At this time, it is desirable to register the information of the answerer in order to prevent the information from being used for any purpose other than solving the query problem later.

The control unit 205 of the answering terminal 200 attempts to chat with the learner terminal 100 through the communication unit 202 after receiving it. When the connection is established, the chat window generation unit 206 generates a chat window and displays the chat window on the display unit 203. [ When the chatting is performed, the respondent answers the query problem while chatting with the learner in real time through the chat window generating unit 206. The learner uses the chat window processing unit 110 to chat with the answerer in real time, Listen to questions or answer questions.

In the case of an answer which is inconvenient in the chat window (text communication method) during the answer to the question, the learner creates a whiteboard (document sharing window) through which to explain the question through the screen sharing unit 207 . The generated document sharing window is transmitted to the learner terminal 100 through the network 300 and the document sharing window is shared through the screen sharing unit 109 of the learner terminal 100 and displayed on the display unit 103.

That is, a chat window and a document sharing window are simultaneously displayed on the display unit 103 of the learner terminal 103 and the display unit 203 of the answerer terminal 200. [ At this time, the displayed document sharing window becomes the same document sharing window.

Thereafter, when the answerer gives a solution to the query problem in the document sharing window, the same document sharing window is displayed on the learner's display unit 103, and the query problem solving process is displayed. Here, inquiries and answers are possible through the phone functions provided in the smartphone of both the respondent and the learner. In particular, the respondent can create a document sharing window, explain the problem in the document sharing window, and simultaneously explain the problem solving by voice. This voice processing is processed through the voice processing unit 204 and transmitted to the learner terminal 100 through the telephone function.

Likewise, the learner terminal 100 uses the telephone function and sends the received voice to the speaker through the voice processing unit 104 so that the learner can check the problem solving process while listening to the voice described by the answerer.

For example, the present invention allows the respondent and the learner to learn through interaction such as a query and an answer to a question using a chat function, a document sharing function, and a telephone function in real time. Particularly, learning is performed in a dialogue manner in real time using a mobile device such as a smart phone, so that it becomes possible to move away from a specific learning space and learn regardless of a place.

It is also a further feature of the present invention that a problem solving process for a query problem can be recorded. That is, the respondent selects the recording function through the input unit 201 during learning as needed. When the recording function is selected, the recording unit 208 performs recording. For example, the pool information displayed in the document sharing window is matched with the voice input through the microphone, and then recorded. When the recording is finished, the answer information is stored in the storage unit 209 as an answer file. When an answer file is stored in the storage unit 209, the answer registration unit 210 transmits the answer file to the administrator terminal 400 through the network 300. [

The administrator terminal 400 registers the received answer file in the database 500 via the answer registration unit 406. [ At this time, the answer file includes tag information matched when registering the first query problem.

Meanwhile, as another feature of the present invention, an answer can be evaluated, and a variety of incentives (mileage, points, cache, etc.) are provided to the answerer based on the evaluation information. Therefore, the answerer will try to provide more accurate and accurate answers to the inquiry questions by these incentives. This effort is a way to help learners in the end, which can increase learning efficiency.

For example, when the answer of the answerer is completed and the chatting is completed, the answer evaluation unit 111 evaluates the answer according to the key input operation of the learner, and generates the evaluation information. Here, it is preferable that the answer evaluation method adopts various evaluation methods known in the art as it is.

The evaluation information is transmitted to the administrator terminal 400 through the communication unit 102 under the control of the control unit 105. [ The evaluation information processing unit 408 of the administrator terminal 400 stores the received evaluation information in the database 500. [ And the incentives are determined by analyzing the evaluation information. The incentive decision can determine the criteria by which the evaluation information can be analyzed in advance, and the incentive can be determined by evaluating the answer information based on the criteria. The criteria may vary, and may be of the form used in ordinary surveys, such as very satisfied, satisfied, moderate, dissatisfied, and highly dissatisfied. You can also use the same scoring method as a few points on a 100-point scale.

When the incentive for the answerer is determined, the controller 404 of the administrator terminal 400 extracts the contact information (telephone number) of the answerer stored at the time of registering the answer in the database 500, (Incentive information, incentive usage information, etc.).

On the other hand, as another feature of the present invention, the answer information can be retrieved. For example, the learner terminal 100 or the answerer terminal 200 accesses a query question registration site operated by the administrator terminal 400 and searches for a query problem (or answer file) through a query word input method. If an answer file exists in the query problem, the answer file is interlocked with the query problem. If there is no answer file, only the query problem is displayed. The search processing unit 407 of the administrator terminal 400 searches the database 500 using a general keyword search method to search for a query problem. After that, if a query problem corresponding to a search word requested by the user is searched, it is transmitted to the user terminal. At this time, the tag information can be used to perform the search easily and quickly.

As described above, the present invention can increase the educational effect by inquiring the problem through the interaction method such as the dialogue in real time, and by responding to the inquired question.

FIG. 5 is a flowchart illustrating a smart learning process in the learner terminal 100 among the real-time knowledge-based shared smart learning method according to the present invention. Where S represents the step.

As shown in FIG. 5, a real-time knowledge-based shared smart learning method according to the present invention includes the steps of: (a) generating a problem to be registered in a query problem registration site (S101); (b) selecting (S102) a tag to search for the problem in association with the administrator terminal (400); (c) generating a query problem by mapping the problem to a tag (S103); (d) storing the query problem and registering the query problem on the problem registration site (S106 to S107); (e) creating a chat window and chatting (S108 to S109) when the answerer terminal 200 is connected to the query problem; (f) receiving a document sharing window for solving the problem sent from the answerer terminal 200 during the chat and sharing a document sharing window (Sl 10); (g) inquiring the answerer terminal 200 in real time through the chat window and the telephone function, listening to the explanation of the problem solving through the voice while viewing the problem solving information through the document sharing window (S111) ; (h) correcting the image for the query problem (S104 to S105) when the image correction is requested before the step (d); (i) generating evaluation information on the question problem after the step (g), and registering the evaluation information on the problem registration site (S112).

In the real-time knowledge-based shared smart learning method according to the present invention configured as described above, if there is a question to be asked during learning of a problem in step S101, a problem to be registered in the question problem registration site is generated. The problem generation is preferably generated as an image.

Next, in step S102, a tag to search for the problem is selected in association with the administrator terminal 400. [ Here, the tag may include information such as subject, type, and grade. Thereafter, in step S103, the problem is mapped to the tag to generate a query problem.

Next, it is checked whether the image correction for the query problem generated in step S104 is necessary. If the image correction is not necessary, the process moves to step S106 and stores the generated query problem in the storage unit.

Otherwise, if image correction is required (image quality is low), the flow advances to step S105 to correct the image. Here, the image correction method is the same as that shown in FIG. For example, in step S201, the query problem is classified into a letter image and a general image. In step S202, the average brightness value per frame is calculated in step S202. In step S203, the general image is corrected to the calculated average brightness value. And corrects the text image with a predetermined reference setting value for the text image. It is preferable to use a normal interpolation method for image correction.

After storing the query problem, the process moves to step S107 and registers the query problem on the problem registration site. If the answerer terminal 200 is connected to the inquiry question in step S108, the flow advances to step S109 to create a chat window and confirm the answer to the inquiry problem while chatting. If a document sharing window for solving a problem transmitted from the answerer terminal 200 is received during a chat, the document sharing window is shared through the display unit in step S110.

Thereafter, in S111, the answer terminal 200 is inquired in real time through the chat window and the telephone function, and while listening to the problem solving information through the document sharing window, learning is performed while listening to the explanation of the problem solving through voice do.

When the learning ends, evaluation information on the answer is generated in step S112 and transmitted to the administrator terminal 400. [

FIG. 7 is a flowchart illustrating a smart learning process in the answerer terminal 200 among the real-time knowledge-based shared smart learning methods according to the present invention. Where S represents the step.

The smart learning method in the answer terminal of the real-time knowledge-based shared smart learning method according to the present invention comprises the steps of: (a) selecting a query problem through search of a query problem registration site (S301); (b) creating a chat window by accessing the learner terminal 100 registered with the query problem, and (S302 to S303) responding to the query problem through chatting; (c) creating a document sharing window when a document sharing window for solving a problem is requested during the chatting (S304); (d) transmitting the generated document sharing window to the connected learner terminal and sharing the document sharing window with the learner terminal (S304 to S306); (e) providing a response to the query problem with the learner terminal in real time through the chat window, the document sharing window, and the telephone function (S307); (f) recording a problem solving voice, a chat and a document sharing window by solving a problem through a chat and a document sharing window according to a user's request, registering a recorded answer file in the question inquiry registration site, and ending the chat (S308 to S309).

In the smart learning method of the real-time knowledge-based shared smart learning method according to the present invention configured as described above, the smart learning method in the answer terminal searches for a query problem through a search of a query problem registration site registered on the web in step S301, Select a questionable question. Here, it is preferable to use a general keyword retrieval method for the query problem retrieval method. Using a keyword search method that uses tags when searching for a keyword makes it easier and quicker to search for a query problem.

Next, a chat window is created by connecting to the learner terminal 100 that registered the question in step S302, and a question is answered through chat in step S303.

However, there is a limit to the answers through chat because they are responses through letters. Accordingly, the present invention uses a document sharing window such as a whiteboard to overcome such limitations. For example, if it is desired to solve the problem specifically in addition to the characters, the document sharing window is selected as in step S304. When the document sharing window is selected, a document sharing window is created in step S305, and the generated document sharing window is transmitted to the connected learner terminal in step S306, and the document sharing window is shared with the learner terminal.

Thereafter, in step S307, the learner terminal and the learner terminal are provided with answers to the query problem in real time through the chat window, the document sharing window, and the telephone function. When the user requests the recording (editing) in step S308, the user can record the voice, chat, and document sharing windows at the time of problem solving through the chat and document sharing windows, and registers the recorded answer file in the query question registration site Leave. Thereafter, the chat is ended in step S309.

FIG. 8 is a flowchart illustrating a smart learning process in a manager terminal among a real-time knowledge-based shared smart learning method according to the present invention. Where S represents the step.

A real-time knowledge-based shared smart learning method according to the present invention includes the steps of: (a) providing a tag for query problem search to the learner terminal 200 (S401); (b) registering the query problem transmitted from the learner terminal 200 in the database 500 (S402); (c) registering the answer file transmitted from the answerer terminal 200 in the database 500 (S403); (d) searching the database 500 based on the keyword inputted in the search request and providing the searched query problem to the search request terminal (S406 to S408); (e) registering an answer file in the database 500, receiving response evaluation information from the learner terminal 100, and registering the response evaluation information in the database 500 (S404); (f) analyzing answer evaluation information registered in the database 500 to determine an incentive of the answerer, and transmitting the incentive information to the answer terminal in the incentive determination step (S405).

In the smart learning process of the administrator's terminal among the real-time knowledge-based shared smart learning method according to the present invention configured as described above, a tag for query problem search is provided to the learner terminal 200 in step S401. Here, the tag may include the subject, type, grade information, and the like.

Next, a query problem transmitted from the learner terminal 200 is registered in the database 500 in step S401, and an answer file transmitted from the answerer terminal 200 is registered in the database 500 in step S403.

After the answer file is registered in the database 500, if the answer evaluation information is transmitted from the learner terminal 100 in step S404, the answer file is received and registered in the database 500. [ In step S405, the answer evaluation information registered in the database 500 is analyzed to determine the answerer's incentive. Herein, the incentive determination method is the same as the incentive determination method in the evaluation information processing unit 408 of FIG. 4, so a detailed description will be omitted in order to avoid redundant description. When incentives are determined, incentive information is sent to the answerer terminal. These incentives enable answerers to be more enthusiastic, responsive, and accurate in responding to questions, thereby enabling learners to obtain answer information accurately and efficiently.

Next, in step S407, the database 500 is searched based on the keyword inputted at the time of the search request, and a query problem (interworking when an answer file exists) is searched. If a query problem is searched in step S408, And provides a problem to the search request terminal.

Although the present invention has been described in detail with reference to the above embodiments, it is needless to say that the present invention is not limited to the above-described embodiments, and various modifications may be made without departing from the spirit of the present invention.

The present invention is effectively applied to a technique using a network and learning through interaction such as dialogue in real time.

100: the learner terminal
101: Tag selection unit
106:
108: Query problem register
109:
110: Chat window processor
200: Answer terminal
206: Chat window processor
207: Screen Sharing Unit
208:
210: Answers registry
400: administrator terminal
402: tag supply
405: query problem register
406: Answer register
407:
408: Evaluation information processor
500: Database

Claims (19)

A learner terminal for presenting a problem through a network, inquiring a question, sharing a screen through a screen sharing function with an answer terminal, and receiving a learning while interacting with an answerer terminal through a query and a response in real time; An answerer terminal connected to the learner terminal through a network in real time, sharing a screen through a screen sharing function, and interacting with a voice through an answer, thereby learning a problem solving process; Wherein the answer recording unit records the question and answer information presented from the learner terminal in the database and registers the answer recording process recording video provided from the answerer terminal in the database, And an administrator terminal for transmitting to the terminal,
The learner terminal controlling the registration of the query problem and controlling chatting, screen sharing, and telephone function upon receiving a response to a query problem; A screen sharing unit for sharing a document sharing window in real time with an answer terminal upon receiving an answer according to the control of the control unit; A chat window processing unit for chatting with the answer terminal through a chat window under the control of the controller; And an image correction unit for correcting the image of the query problem generated by the query problem registering unit under the control of the control unit,
The image correcting unit distinguishes the question of the query from the normal image and the normal image. In the case of a general image, the average brightness value is calculated in frame units. The average image brightness is corrected based on the calculated average brightness value. Wherein the brightness value is corrected based on the reference setting value.
The smart learning system according to claim 1, wherein the learner terminal and the answerer terminal are parallel to a learning function and an answer function, and the learner terminal and the answerer terminal are implemented as mobile devices capable of moving.
The learner terminal of claim 1, wherein the learner terminal generates a problem to be queried; A tag selection unit for selecting a tag to be mapped to a problem generated for searching; And a query problem registering unit for generating a query problem by mapping the problem with the tag and registering the query problem on the network at the registration site of the problem query.
4. The smart learning system of claim 3, wherein the learner terminal further comprises an answer evaluation unit for generating evaluation information on the answer presented by the answerer terminal in association with the control unit.
delete delete The method of claim 1, wherein the answer terminal comprises: an input unit for inputting search information for searching for a query problem or a selection signal for selecting a query problem; A controller for controlling the generation and processing of a chat window and a screen sharing window for searching and selecting the query problem, an answer to a selected query problem, and the like; A chat window generating unit for generating a chat window for chatting on a query problem under control of the controller, listing chat information input through an input unit in the chat window, and displaying partner chat information in the chat window; And a screen sharing unit that shares a document sharing window with a learner terminal in real time when an answer is provided under the control of the controller.
[7] The apparatus of claim 7, wherein the answer terminal further comprises a recording unit for recording the record information of the document sharing window generated through the screen sharing unit and the problem solving voice inputted through the voice processing unit under the control of the controller, Based knowledge-based smart learning system.
The system according to claim 8, wherein the answer terminal further comprises an answer registration unit that registers an answer file generated by the recording unit on a problem registration site through a network under the control of the controller. .
4. The learner terminal of claim 1, wherein the manager terminal comprises: a tag providing unit for providing a tag for searching for a query problem to the learner terminal; A query problem register for registering a query problem; An answer registration unit for registering an answer file; A search processor for performing a search through a keyword search when a query for a query problem is requested by the terminal, and outputting a query problem and an answer file; A controller for controlling the tag provisioning, the query problem registration and the answer file registration, the search processing, and the evaluation information processing; And an evaluation information processing unit for registering the evaluation information transmitted from the learner terminal in a database, analyzing the evaluation information for each answerer to determine an incentive of the answerer, and guiding incentive information to the answerer. system.
A learner terminal and an answerer terminal for inquiring about and responding to a problem solution through a chat window, a document sharing window, and a telephone function in real time in response to a query problem; A method for performing knowledge-based shared smart learning in real time using a smart learning system including an administrator terminal for managing a query problem registration and an answer registration by interaction between the learner terminal and an answer terminal through a database,
The learner terminal includes: (a) generating a problem to be registered in a query problem registration site; (b) selecting a tag to search for the problem in association with the administrator terminal; (c) generating a query problem by mapping the problem to a tag; (d) storing the query problem and registering the query problem on the problem registration site; (e) creating a chat window and chatting when the answerer terminal is connected to the query problem; (f) receiving a document sharing window for solving a problem sent from the answer terminal during the chat and sharing a document sharing window; (g) querying the answer terminal in real time through the chat window and the telephone function, and listening to a problem solving description through a voice while viewing the problem solving information through the document sharing window; (h) correcting the image for the query problem if image correction is requested prior to step (d)
The step (h) comprises the steps of: (h1) distinguishing the query problem as a letter image and a general image; (h2) calculating an average brightness value per frame in the case of the general image; (h3) correcting the general image with the calculated average brightness value, and correcting the handwritten image with a predetermined reference set value for the handwritten image.
delete The smart learning method according to claim 11, further comprising: (i) generating evaluation information on a question problem after step (g) and registering evaluation information on the problem registration site .
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