KR102281642B1 - System for providing question for english study through user equipment - Google Patents

Abstract

The present invention relates to a system for providing problems for learning English through a user device.
The present invention also relates to a method and system for problem extraction and analysis for learning English.

Description

A system that provides problems for learning English through a user device {SYSTEM FOR PROVIDING QUESTION FOR ENGLISH STUDY THROUGH USER EQUIPMENT}

The present invention relates to a system for providing problems for learning English through a user device.

The present invention also relates to a method and system for problem extraction and analysis for learning English.

In learning English for exams such as the TOEIC, it is very important to face many different problems. The types of questions asked in the TOEIC test are standardized to some extent. Therefore, by properly using the existing problems, effective test preparation and learning may be possible.

When there is data including previously made problems, learning materials may be generated by selecting an appropriate number of problems. In general, this process is done manually and requires a lot of effort and time. Due to the nature of manual work, it is difficult to trace the history of problem extraction, and it is also expensive to add new problems.

The technology underlying the present invention is disclosed in Korean Patent Registration No. 10-1493490 (February 24, 2015) and Korean Patent Application Laid-Open No. 10-2019-0028045 (March 18, 2019).

An object of the present invention is to provide a system for providing a problem for learning English through a user device.

The present invention is to provide a method and system for effectively extracting and providing problems for learning English from a database.

The present invention is to provide a method and system for effectively adding a new problem for learning English to a database.

An object of the present invention is to provide a method and system for selecting and extracting problems for learning English by reflecting the characteristics of the user.

According to an embodiment of the present invention, a method for providing a problem in a system for learning English includes determining a range for problem selection, selecting a plurality of problems within the determined range, and solving the selected plurality of problems. transmitting data including The range depends on at least one of a quantitative range, a tangible range, and a range for each grade, and the range is determined according to the service grade of the user who requested the provision of the problem.

The present invention can provide the user with a problem for learning English through the user device.

The system according to the present invention can provide effective learning materials by utilizing the problems accumulated in the database.

1 shows the structure of a system according to an embodiment of the present invention.
2 shows the structure of a device in a system according to an embodiment of the present invention.
3 illustrates an interaction between a server and a user device in a system according to an embodiment of the present invention.
4 shows an example of the structure of a database utilized in a system according to an embodiment of the present invention.
5 is an operation flowchart for problem extraction in a system according to an embodiment of the present invention.
6 is an operation flowchart for adding a problem in a system according to an embodiment of the present invention.
7 is a flowchart of an operation for collecting feedback information in a system according to an embodiment of the present invention.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. And, in describing the present invention, if it is determined that a detailed description of a related known function or configuration may unnecessarily obscure the gist of the present invention, the detailed description thereof will be omitted.

Hereinafter, the present invention relates to a system for extracting and analyzing an English problem, and various techniques for extracting a problem or adding a problem will be described.

1 shows a system according to an embodiment of the present invention.

Referring to FIG. 1 , a system includes a server 101 and a user device 102 .

The server 101 is a device that stores big data including problems for learning English, that is, a database. The server 101 may extract and provide issues according to the request of the user device 102 . Also, when a new problem is provided, the server 101 may add the new problem to the database. The server 101 stores and manages subscriber information for users.

User device 102 is a device used by a user. The user device 102 may transmit to the server 101 information for subscription, a request for problem extraction, and feedback information of the user. The user device 102 may receive information about the extracted problem from the server 101 . In order to use the English learning service proposed by the present invention, it may be required to install a dedicated application in the user device 102 . The user device 102 is an electronic device including a screen and input means such as a smart phone, tablet, computer, or the like.

2 shows the structure of a device in a system according to an embodiment of the present invention.

The structure shown in FIG. 2 may be applied to the server 101 and the user device 102 . Referring to FIG. 2 , the device includes a control unit 202 , a communication unit 204 , a storage unit 206 , and a display/input unit 208 . In the case of the webtoon server 120 or the payment server 130 , the display/input unit 208 may be omitted.

The controller 202 controls overall operations of the device. For example, the controller 202 executes an application using commands stored in the storage unit 206 and controls operations of other components. For example, the control unit 202 controls the communication unit 204 to transmit and receive signals, stores data in the storage unit 206, and reads data, commands, etc. stored in the storage unit 206, The control unit 202 displays a screen through the display/input unit 208 and processes the detected input. The control unit 202 may be implemented by a microprocessor, a processor, or the like.

The communication unit 204 performs a function for connecting to an external communication network and transmitting and receiving data/signal/information. For example, the communication unit 204 may perform a function of accessing an Internet network, a wireless communication network, a mobile communication network, and the like. To this end, the communication unit 204 performs functions such as modulation/demodulation, amplification, and filtering of the signal.

The storage unit 206 stores data, setting information, commands, microcodes, applications, and the like. The storage unit 206 may be implemented as a temporary or non-transitory storage medium. In addition, the storage unit 206 may be fixed to the device or implemented in a detachable form. For example, when the device of FIG. 2 is the server 101, the storage unit 206 may store an English problem database, subscriber information, and the like.

The display/input unit 208 includes means for displaying a screen and means for sensing an input from the outside. Here, the means for displaying the screen may be implemented as a monitor, a liquid crystal screen, or the like. The means for sensing an input includes a touch pad, a key button, a sensor, a camera, and the like. The display/input unit 208 may include a touch screen in which a liquid crystal screen and a touch pad are combined. In some cases, the display/input unit 208 may be interpreted as a set of physically separated two or more hardware modules.

3 illustrates an interaction between a server 101 and a user device 102 in a system according to an embodiment of the present invention. Referring to FIG. 3 , a subscription procedure 301 between the server 101 and the user device 102 , a problem request and provision procedure 302 , feedback and a database (database) update procedure 303 , and the like may be performed.

The subscription procedure 301 is a procedure in which the user of the user device 102 subscribes to the service of the server 101 in order to receive a problem provision service. To this end, the user device 102 transmits necessary information including an identifier (ID) of the user, and the server 101 generates and stores subscriber data of the user. At this time, the server 101 designates and records the user's service level or service level. A user's service level is designated based on a usage fee, a subscription period, a history of providing feedback, and the like. The service level affects problem extraction in the problem request and provision procedure 302 described below.

The problem request and provision procedure 302 is a procedure in which the user device 102 requests selection and provision of a problem, and the server 101 provides a list of problems and explanation information in response thereto. To this end, the user device 102 may indicate the desired part and number of problems. The server 101 may extract problems in consideration of the user's service level of the user device 102 , problems that have been provided to the user, feedback received from the user, and the like.

The feedback and DB update procedure 303 receives feedback from a user and stores the feedback in a database. The feedback may include whether the correct answer to the provided question is correct, the user's satisfaction evaluation of the provided questions or individual questions, and the like. In this case, the server 101 may correct the content of the problem based on the user's feedback. For example, the server 101 may change the views of the problem to lower the difficulty.

In order to perform the procedures shown in FIG. 3 , the user device 102 may be required to install and run a dedicated application. A dedicated application may be required for a subscription procedure 301 , a problem request and provision procedure 302 , and a feedback and DB update procedure 303 . In this case, the dedicated application may provide various convenient functions necessary for the user to receive the service. For example, by providing a voice recognition function (eg, a speech to text (STT) function), the dedicated application may improve user convenience in at least one of a problem request, problem solving, and feedback process.

4 shows an example of the structure of a database utilized in a system according to an embodiment of the present invention. 4 shows a specific example of a database including English problems. In Fig. 4, each row is a record storing one problem. Each record is made up of multiple columns, where the columns are serial number 401, problem 402, view A 403, view B 404, view C 405, and view D 406. , correct answer (407), correct vocabulary (408), year (409), number of times (410), part-of-speech classification (411), type classification (412), detail 1 (413), detail 2 (414), detail 3 (415) ), and a commentary 416 .

Here, the year 409 and the number of times 410 are columns for storing information on the year and number of questions submitted in the regular exam, and may not be used when the corresponding question is not a previous question. The part-of-speech classification 411 is index information for classifying the part-of-speech of the correct word, as any one of 'noun', 'pronoun', 'verb', 'adjective', 'adverb', 'conjunction', 'preposition', and 'other'. can be specified. The type classification 412 is a large classification of the problem type, and may be designated as any one of 'structure', 'grammar', and 'vocabulary'.

Details 1 (413), detail 2 (414), and detail 3 (415) include index information for classifying problems, and may not be used or only part of them may be used depending on the problem. Candidates for values that can be assigned to detail 1 413 may vary according to type classification 412 . That is, when the type classification 412 is 'structure', the values that can be assigned to the detail 1 (413) and when the type classification 412 is 'grammar', the values that can be assigned to the detail 1 413 are They may be different, at least in part. For example, when the type classification 412 is 'grammar', the detail 1 413 may be designated as one of 'number match', 'noun classification', and 'compound noun'.

As shown in FIG. 4 , a database including English problems may be built. In the case of FIG. 4 , explanations and the like are written in Korean. However, in order to support users in various countries, the database may be built in multiple languages, and thus the system may provide multiple language packs. For example, the system may be implemented to support various languages such as English, Vietnamese, Chinese, and Japanese.

Using the database as shown in FIG. 4 , the system according to an embodiment of the present invention, for example, the server 101 may extract problems and provide them to the user. Hereinafter, specific operations for extracting a problem and specific operations for adding a problem will be described.

5 is an operation flowchart for problem extraction in a system according to an embodiment of the present invention.

Referring to FIG. 5 , the server 101 determines a problem selection range ( S501 ). Here, the problem selection range may be defined as at least one of a quantitative range, a tangible range, and a grade-specific range. According to an embodiment, the problem selection range may vary according to the service level of the user who requested the problem provision. For example, as the user's rating is higher, the number of selectable problems that can be provided at one time may increase (eg, 30 questions for grade A, 10 questions for grade B). According to another embodiment, the problem selection range may vary according to the problem solving history of the user who requested the problem provision. For example, the problem selection range may be determined as a type to which problems of a type having a high user's incorrect answer rate belong.

Thereafter, the server 101 selects problems within the determined range ( S502 ). The server 101 selects a plurality of problems within the determined problem selection range. Specifically, the server 101 searches the database for problems belonging to the determined range, and extracts the number of problems specified by the problem selection range according to a given criterion. For example, a given criterion may be fixed or variable. Here, the fixed criterion may be random selection or sequential selection. The variable criterion may be defined based on the extraction frequency or based on user satisfaction.

Next, the server 101 configures the layout of the question paper and arranges the questions (S503). The layout of the question paper may vary according to the characteristics of the user device 102 of the user. For example, the server 101 may determine a layout optimized for a screen size of the user device 102 and a display type (eg, a general display, virtual reality (VR), etc.). For example, if the size or resolution of the screen is large enough, a layout can be constructed that arranges the problems in two or three columns. Then, the server 101 places the selected problems in the configured layout. In some cases, this step S503 may be omitted.

Thereafter, the server 101 transmits the problem data (S504). The server 101 generates a problem data packet including the content of the problems (eg, problems and examples), layout information, and placement information, and sends the problem data packet to the user device 102 . Information on correct answers and explanations may be transmitted together with the question data, or may be transmitted separately later. For example, information on correct answers and explanations may be sent subject to feedback on problems.

5 , the server 101 can extract and provide problems. Various criteria may be applied in determining the scope of selection of problems and in selecting problems. According to an embodiment, the server 101 may analyze a pattern of the user's problem solving result, search for similar cases in which excellent results are obtained through similar patterns, and then extract problems based on the retrieved cases. Such similar instances may be retrieved by simple comparison, or may be retrieved based on an artificial intelligence (AI) algorithm.

When using the AI algorithm, learning of the AI algorithm may be performed using statistical data for many existing users. The server 101 may perform learning after generating learning data from statistical data for learning. First, in order to select information to be used as learning data, the server 101 collects statistical data of users who have achieved scores above a certain level. Then, the server 101 classifies the collected statistical data for each question type and the corresponding correct rate for each period of the regular test or for each question provision time, and the user's characteristic information (eg, gender, age, learning frequency, etc.) After confirming, learning may be performed using the classified information and the user's characteristic information.

When extracting problems based on similar cases, in addition to extracting problems, the server 101 may further suggest a learning schedule. In other words, the server 101 may determine a learning schedule and transmit data indicating the learning schedule. The learning schedule may include recommendations on when to provide the next problem, the frequency of request for problem provision, and the like. When the learning schedule is provided, when the time specified by the schedule arrives, the server 101 may transmit a notification message (eg, text message, push message, etc.) to the user device 102 indicating that the problem provision is recommended. there is.

6 is an operation flowchart for adding a problem in a system according to an embodiment of the present invention.

Referring to FIG. 6 , the server 101 checks the input of the problem ( S601 ). The problem may be entered offline by the administrator of the server 101 . Alternatively, the problem may be entered online via a telecommunication network remotely.

Then, the server 101 analyzes and classifies the problem type (S602). The server 101 analyzes the content of the problem and the content of the example, and classifies the problem type according to the analysis result. For example, the server 101 may check the part-of-speech of the example or search the dictionary meaning of a word included in the example. For example, the server 101 may analyze the words before and after the correct answer column of the problem. As another example, the server 101 may identify the type of problem with a similar structure. By a combination of various analysis approaches, the type of final problem can be determined.

Thereafter, the server 101 adds a problem to the database (S603). The server 101 stores the information about the problem and the type determined together as a new record in the database.

As shown in FIG. 6 , the server 101 may classify and store the types of problems. In this case, in determining the type of problem according to the given algorithm, when the determination criterion has a probability below a certain level, a notification requesting review may be transmitted to the administrator. Accordingly, when the accuracy of the determination by the algorithm is low, a more clear type classification can be made by the intervention of the manager. Here, the notification may be displayed on a display means provided in the server 101 or may be delivered as an online message transmitted through a communication network.

7 is a flowchart of an operation for collecting feedback information in a system according to an embodiment of the present invention.

Referring to FIG. 7 , the server 101 determines whether a feedback request condition is satisfied ( S701 ). The feedback request condition may be defined in various ways. For example, the feedback condition may be a time when problem solving is completed, a time when a correct answer to a problem is provided, or a time when a regular test is finished. By requesting feedback at an appropriate time right after the end of the regular test, more accurate feedback can be obtained from the user. In this case, information on the end time of the regular test may be obtained from the site of the test organizer or may be input by the administrator.

If the feedback request condition is satisfied, the server 101 generates and transmits a feedback request message (S702). For example, the feedback request message may include a question inquiring about satisfaction with a provided problem, a question inquiring about satisfaction with a ratio of problem types, and a question inquiring about a direction of change in the ratio of provided problem types. As another example, the feedback request message includes questions about whether the provided questions were helpful in taking the regular exam, questions about whether the provided questions match the regular exam questions, etc., provided before the regular exam for your reference. It may further include summary information about the issues that have been raised.

The server 101 receives the feedback (S703). The feedback includes the user's answer to the question included in the feedback request message. The feedback information is stored by the server 101 and may be utilized for later problem extraction.

In the detailed description of the present invention, although specific embodiments have been described, various modifications are possible without departing from the scope of the present invention. Therefore, the scope of the present invention should not be limited to the described embodiments and should be defined by the claims described below as well as the claims and equivalents.

Claims (1)

In a system that provides a problem for learning English through a user device,
the user device used by the user; and
server; including,
The server is
determining a range for problem selection according to a request from the user device;
A plurality of problems are selected according to a criterion defined based on the extraction frequency or satisfaction of existing users within a determined range,
determining a layout for arranging the plurality of problems in consideration of a screen size and a display type of the user device;
placing the plurality of problems in the layout;
sending problem data including information about a selected plurality of problems, information about the layout, and arrangement of the plurality of problems to the user device;
sending schedule data including a recommendation on the timing of the next problem provision and a problem provision request period to the user device;
After the schedule data is transmitted, when a time point at which provision of the next problem designated by the schedule data is recommended arrives, a notification message indicating that the time point at which provision of the next problem is recommended arrives to the user device;
At the time when the regular test related to English learning is finished, a feedback request message inquiring about satisfaction with the plurality of problems included in the problem data is sent to the user device,
receiving a response message to the feedback request message from the user device;
The range depends on at least one of a quantitative range, a tangible range, and a graded range,
The range is characterized in that it is determined according to the service level of the user who requested the provision of the problem,
The server is
Classify the type of input problem,
Control to store the input problem and type information in a database,
The type is characterized in that it is classified based on at least one of parts-of-speech of examples, dictionary meanings of words included in examples, and front and back words of the correct answer column,
The server is
Analyze the pattern of the user's problem solving result,
Searching for cases with a pattern similar to the analyzed pattern,
Extracting problems based on the searched cases,
Learning about an artificial intelligence (AI) algorithm for searching for cases with the similar pattern is performed, i) collecting statistical data of users who have achieved a certain level or higher, ii) analyzing the collected statistical data by problem type It is characterized in that the ratio and the correct answer rate corresponding thereto are classified by the period of the regular test or the time of providing the problem, and iii) learning is performed using the classified information and the corresponding characteristic information of the user,
The server is
Create a learning schedule, wherein the learning schedule includes a recommendation for the next problem provision time and a problem provision request period,
sending data representing the learning schedule to the user device;
When the time specified by the learning schedule arrives, sending a notification message to the user device indicating that the problem provision is recommended time,
system.

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