Learning competency characteristic diagnosis system through observation of shared activity records

Abstract

A learning competency characteristic diagnosis system according to one embodiment of the technical concept of the present invention, wherein the learning competency characteristic diagnosis system connects an online data server containing a URL containing a shared activity record and a user terminal via a network, the system comprises: a shared activity record collection unit capable of receiving one or more URLs containing a shared activity record from a user terminal to extract text data and processing and storing the extracted text data; a shared activity record information analysis unit that analyzes a user's shared activity record using the text data extracted and processed by the shared activity record collection unit; and a user diagnosis unit that diagnoses a user's learning competency characteristic using the analysis result of the shared activity record information analysis unit.

Description

Technology Field

[0001] The present invention relates to a system for extracting and diagnosing learning competency characteristics through the observation of shared activity records, and more specifically, to a system that enables the extraction and diagnosis of a user's learning competency characteristics by extracting and observing shared activity records, which are learning history that was previously performed online, without the need to build a separate learning history anew on a specific platform or learning site. Background Technology

[0002] With the advent of the knowledge society, people's educational attainment and knowledge levels are steadily rising. Furthermore, while fields of knowledge are becoming more diverse, the amount of specialized knowledge required to be learned within those same fields is simultaneously increasing.

[0003] Consequently, while the level of knowledge and expertise acquired by individuals varies, it is currently difficult to evaluate such knowledge and to specifically diagnose their learning capabilities.

[0004] Furthermore, since most learning competency extraction systems or diagnostic devices require vast amounts of learners' learning history or data, existing systems and devices could only provide diagnostic services regarding individual learning competencies to users who had already accumulated learning history or data.

[0005] In an effort to solve these problems, many inventors have attempted to find a solution, but satisfactory results have not yet been obtained. Prior art literature

[65535] Published Patent Application No. 10-2020-0078947 (July 2, 2020) Registered Patent Application No. 10-2007987 (August 6, 2019) Published Patent Application No. 10-2019-0139079 (December 17, 2019) The problem to be solved

[0006] The objective of the learning competency characteristic diagnosis system according to the technical concept of the present invention is to provide a system that allows an individual user to have their learning competencies specifically diagnosed without the need to build new learning history or data on any platform or learning site.

[0007] Another objective of the learning competency characteristic diagnosis system according to the technical concept of the present invention is to provide a system that allows an individual user to be diagnosed in areas where they may demonstrate strengths, even though those areas are fields they have not yet studied.

[0008] Another objective of the learning competency characteristic diagnosis system according to the technical concept of the present invention is to provide a system that can quantify the knowledge fields and level of expertise an individual has acquired by observing records of shared online activities, and thereby compare the individual user's learning competency with that of other third-party users. means of solving the problem

[0009] A learning competency characteristic diagnosis system according to one embodiment of the technical concept of the present invention, in a learning competency characteristic diagnosis system that connects an online data server containing a URL containing a shared activity record and a user terminal via a network, may include: a shared activity record collection unit capable of receiving one or more URLs containing a shared activity record from a user terminal to extract text data and processing and storing the extracted text data; a shared activity record information analysis unit that analyzes a user's shared activity record using the text data extracted and processed by the shared activity record collection unit; and a user diagnosis unit that diagnoses a user's learning competency characteristic using the analysis result of the shared activity record information analysis unit.

[0010] In addition, the sharing activity record collection unit can selectively perform data crawling or API calls according to URL predefined rules regarding the method of collecting sharing activity records via URL or the collection area, and process and store text data extracted by performing data crawling or API calls.

[0011] In addition, the shared activity record information analysis unit may include a learning amount extraction unit that extracts a learning amount by counting the number of behaviors serving as the basis for analysis for each webpage of a URL containing a shared activity record, using a predefined URL dictionary rule for behaviors serving as the basis for analysis for each webpage of a URL.

[0012] In addition, the shared activity record information analysis unit may include a learning duration extraction unit that extracts the learning duration by counting the maximum number of consecutive days the behavior serving as the basis for analysis occurred on each webpage of the URL containing the shared activity record, using a predefined URL dictionary rule for the behavior serving as the basis for analysis on each webpage of the URL.

[0013] In addition, the shared activity record information analysis unit may include a field extraction unit that uses text data extracted and processed by the shared activity record collection unit, selects only nouns from the text data through morphological analysis, and extracts the fields of the selected nouns using a predefined field classification model.

[0014] Additionally, the shared activity record information analysis unit may include a learning proficiency extraction unit that uses nouns selected by the field extraction unit (123) and fields extracted by the field extraction unit (123), maps the nouns to a predefined field-specific word difficulty weight mapping table, and calculates field-specific proficiency or learning proficiency by counting the difficulty weights defined in the mapping table.

[0015] In addition, the user diagnosis unit visualizes learning competency characteristics in the form of a polygonal graph using the analysis results of the shared activity record information analysis unit, and the polygonal graph may include at least one of the learning amount extracted by the learning amount extraction unit, the learning duration extracted by the learning duration extraction unit, and the learning proficiency extracted by the learning proficiency extraction unit.

[0016] In addition, the User Diagnosis Department can diagnose the user's strengths or weaknesses based on pre-set criteria using the analysis results of the Shared Activity Record Information Analysis Department.

[0017] In addition, the user diagnosis unit utilizes a knowledge graph with predefined relationships by field, and based on the field diagnosed as the user's strength field, it can diagnose the field with the highest correlation in the knowledge graph as the field with the user's potential for development.

[0018] In addition, the learning capability characteristic diagnosis system may further include a diagnosis result output unit that transmits the diagnosis result diagnosed by the user diagnosis unit to the user terminal.

[0019] Additionally, the user terminal receives check information and transmits it to the user diagnostic unit, and the user diagnostic unit transmits the received check information to the administrator terminal; the user terminal includes a display unit in the form of a display device located on one side of the user terminal and capable of displaying an input area capable of inputting check items for check information and response values ​​corresponding to the check items; and a detector unit in the form of a camera or sensor located on one side of the user terminal, spaced apart from the display unit, and located at a first end portion of the user terminal; and the learning capability feature diagnostic system includes an input housing having a housing space formed therein with both end surfaces open and having a shape corresponding to the user terminal, into which the user terminal can be inserted, a display opening connected to the housing space formed on the upper surface, a concave placement space formed on the bottom surface of the housing space corresponding to the user terminal, and a plurality of moving guides positioned on each of the two sides so as to be spaced apart from each other along one direction. The device further includes an input plate formed in a plate shape, having a check opening and an input opening formed therein, and comprising a pair of moving auxiliary members positioned along one direction on both sides, formed in the shape of a rack gear, and capable of engaging with a moving guide; the moving guide comprises a moving power body in the form of a motor located on the side of the input housing; and a moving transmission body in the form of a pinion gear positioned to correspond to the moving power body in the housing space, connected to the moving power body, capable of being rotated by the moving power body, and capable of engaging with a moving auxiliary member; the input plate is inserted and positioned in the housing space so that the moving auxiliary member and the moving transmission body of the moving guide are engaged; a user terminal is positioned in the housing space and inserted into the placement space, a display unit and a detector unit are positioned to correspond to the display opening and are located on the lower side of the input plate, and when the moving power body of the moving guide rotates the moving transmission body, the moving auxiliary member moves so that the input plate can move in the housing space.

[0020] Additionally, a detector mark is formed on a first end portion of the lower surface of the input plate, and the input plate is positioned to correspond to a display opening and is located on the upper side of a user terminal located in a housing space, such that when the detector mark is positioned to correspond to a detector part and detected by the detector part, the display part displays a plurality of check items corresponding to the detector mark and an input area corresponding to each of the check items, and the check opening and the input opening of the input plate are positioned to correspond to one check item and an input area corresponding to one check item displayed on the first end portion of the display part, respectively, and when a user touches an input area displayed on the display part through the input opening, the display part displays a touch mark corresponding to the touched input area, the user terminal generates an operation signal and transmits it to the input housing, the moving power body rotates the moving transmission body, and the moving auxiliary body moves toward the second end portion opposite the first end portion of the display part, and the check opening and the input opening correspond to another check item and another check item displayed on the display part It is positioned to correspond to the input area, and a part of the input plate can be positioned to protrude from the housing space.

[0021] Additionally, the input housing further includes a rectangular plate-shaped substopper positioned near a moving guide and a first end surface of the housing space and hinged to the inner surface of the housing space, wherein the first end portion of the substopper is hinged to the inner surface of the housing space so as to be adjacent to a moving conveyor positioned to face the first end surface of the housing space, and the second end portion opposite the first end portion of the substopper contacts or is spaced apart from the placement space, and a stopper projection made of rubber is formed on the lower surface of the first end portion of the substopper, and when the input plate is positioned in the housing space and the user terminal is not positioned in the housing space, the second end portion of the substopper contacts the placement space and is positioned lower than the first end portion of the substopper, and when the user terminal is gradually inserted into the housing space through the second end surface of the housing space, the substopper contacts the user terminal and rotates, and the second of the substopper When the end is gradually spaced apart from the placement space and the display portion of the user terminal is positioned to correspond to the display opening of the input housing, the stopper projection of the substopper is positioned on one side of the first end portion of the user terminal, and the second end of the substopper is positioned above the first end of the substopper so that the substopper can be tilted to face the first end surface of the input plate. Effects of the invention

[0022] A learning competency characteristic diagnosis system according to the technical concept of the present invention can provide a system that allows an individual user to receive a specific diagnosis of their learning competency without the need for the user to build new learning history or data on any platform or learning site.

[0023] A learning competency characteristic diagnosis system according to the technical concept of the present invention can provide a system that allows an individual user to receive a diagnosis of a field in which the user may demonstrate strengths, even though that user has not yet studied that field.

[0024] A learning competency characteristic diagnosis system according to the technical concept of the present invention can quantify the knowledge fields and level of expertise that an individual has learned by observing records of shared activities online, and thereby provide a system that can compare an individual user's learning competency with that of other third users.

[0025] However, the effects achievable by the learning capability characteristic diagnosis system according to one embodiment of the present invention are not limited to those mentioned above, and other unmentioned effects will be clearly understood by a person skilled in the art from the description below. Brief explanation of the drawing

[0026] A brief description of each drawing is provided to help to better understand the drawings cited in this specification. FIG. 1 is a schematic diagram of a learning competency characteristic diagnosis system according to one embodiment of the present invention. FIG. 2 is an implementation flowchart of a learning competency characteristic diagnosis system according to one embodiment of the present invention. Figure 3 is an example of a sharing activity record collection unit processing and storing text data according to predefined URL dictionary rules. Figure 4 is an example of a URL dictionary rule in which the behavior serving as the basis for analysis is predefined for each webpage of a URL. Figure 5 is an example illustrating the process of the shared activity record information analysis unit extracting nouns and fields from text data and extracting learning fields. Figure 6 is an example illustrating the process by which the shared activity record information analysis department extracts proficiency by field. Figure 7 is an example of a user diagnostic unit visualizing learning capability characteristics in the form of a polygonal graph. Figure 8 is an example illustrating the process of the user diagnostic unit extracting areas with potential for user development. Figure 9 is an example in which the diagnostic result output unit transmits the diagnostic result to a user terminal. FIG. 10 is a perspective view showing an input housing and an input plate separated and applied to a user terminal connected to a learning capability feature diagnosis system according to one embodiment of the present invention. FIG. 11 is a drawing illustrating the application of an input housing and an input plate to a user terminal connected to a learning capability feature diagnosis system according to one embodiment of the present invention. FIG. 12 is a diagram illustrating the operation of an input housing and an input plate applied to a user terminal connected to a learning capability feature diagnosis system according to one embodiment of the present invention. Specific details for implementing the invention

[0027] The present invention is capable of various modifications and may have various embodiments, and specific embodiments are illustrated in the drawings and described in detail in the detailed description. However, this is not intended to limit the present invention to specific embodiments, and it should be understood that the present invention includes all modifications, equivalents, and substitutions that fall within the spirit and scope of the invention.

[0028] In describing the present invention, if it is determined that a detailed description of related prior art may unnecessarily obscure the essence of the present invention, such detailed description is omitted. Additionally, numbers used in the description of this specification (e.g., 1st, 2nd, etc.) are merely identification symbols to distinguish one component from another.

[0029] In addition, when a component is described in this specification as being "connected" or "connected" to another component, it should be understood that the component may be directly connected to or directly connected to the other component, but unless otherwise specifically stated, it may also be connected or connected through another component in between.

[0030] In addition, components expressed as '~part' in this specification may consist of two or more components combined into a single component, or a single component may be divided into two or more components according to more detailed functions. Furthermore, each component described below may additionally perform some or all of the functions performed by other components in addition to the primary function it is responsible for, and it goes without saying that some of the primary functions performed by each component may be exclusively performed by other components.

[0031] Hereinafter, embodiments based on the technical concept of the present invention will be described in detail in turn.

[0032] FIG. 1 is a schematic diagram of a learning competency characteristic diagnosis system according to one embodiment of the present invention.

[0033] As illustrated in FIG. 1, a learning competency characteristic diagnosis system (100) according to one embodiment of the present invention may be connected via a network to an online data server (30) including a user terminal (10), an administrator terminal (20), and a URL (31) containing a shared activity record, and may include a shared activity record collection unit (110), a shared activity record information analysis unit (120), a user diagnosis unit (130), and a diagnosis result output unit (140). Here, the user refers to a person who wishes to have their learning competency characteristics diagnosed through the learning competency characteristic diagnosis system (100), and the administrator refers to a person who manages the learning competency characteristic diagnosis system (100) and checks the diagnosis results of the user based on the use of the learning competency characteristic diagnosis system (100).

[0034] The learning capability characteristic diagnosis system (100) can communicate with the terminal and the data server (30) via a network. The learning capability characteristic diagnosis system (100) may be a computing device that provides services, such as a server.

[0035] According to one embodiment, a network refers to a connection structure capable of exchanging information among respective nodes, such as a plurality of terminals and servers. Examples of such a network include, but are not limited to, a 3GPP (3rd Generation Partnership Project) network, an LTE (Long Term Evolution) network, a 5G network, a WIMAX (World Interoperability for Microwave Access) network, the Internet, a LAN (Local Area Network), a Wireless LAN (Wireless Local Area Network), a WAN (Wide Area Network), a PAN (Personal Area Network), a Bluetooth network, a satellite broadcasting network, an analog broadcasting network, and a DMB (Digital Multimedia Broadcasting) network.

[0036] According to one embodiment, the terminal may be a user terminal (10) or a manager terminal (20), and the user terminal (10) and the manager terminal (20) may include, for example, a wireless communication device that ensures portability and mobility, or a computing device that includes or is connected to a camera, such as a PCS (Personal Communication System), GSM (Global System for Mobile communications), PDC (Personal Digital Cellular), PHS (Personal Handyphone System), PDA (Personal Digital Assistant), IMT (International Mobile Telecommunication)-2000, CDMA (Code Division Multiple Access)-2000, W-CDMA (W-Code Division Multiple Access), Wibro (Wireless Broadband Internet) terminal, a smartphone, a smartpad, a tablet PC, etc., all kinds of handheld-based wireless communication devices.

[0037] According to one embodiment, an online data server (30) includes a URL (31) containing a shared activity record, and the shared activity record refers to information contained in the webpage of the said URL. The online data server (30) may be an administrator server or may be a server other than an administrator server. Accordingly, the shared activity record refers to all information contained in all URL webpages accessible to users or administrators.

[0038] FIG. 2 is a flowchart of an implementation of a learning competency characteristic diagnosis system according to an embodiment of the present invention. As shown in FIG. 2, the learning competency characteristic diagnosis system according to an embodiment may receive a URL containing a user's shared activity record from a user terminal to a shared activity record collection unit (110) (S101). Subsequently, the shared activity record collection unit (110) may collect the shared activity record according to a predefined URL prior rule (S102). The collected shared activity records may be analyzed by a shared activity record information analysis unit (120) (S102), and more specifically, may be analyzed by a learning amount extraction unit (121), a learning duration extraction unit (122), a field extraction unit (123), and a learning proficiency extraction unit (124) (S103). New data is generated from the analysis of these shared activity records (S104). The new data can be used to diagnose the user's learning ability characteristics (S105). The diagnosis of the user's learning ability characteristics using the new data is performed in the user diagnosis unit (130), and the diagnosis result can be displayed on the user terminal through the diagnosis result output unit (140) (S106).

[0039] A shared activity record collection unit (110) according to one embodiment of the present invention may receive one or more URLs (31) containing shared activity records from a user terminal (10) to extract text data, and may process and store the extracted text data. A more detailed shared activity record collection unit (110) according to one embodiment of the present invention may selectively perform data crawling or API calls according to a URL dictionary rule in which a shared activity record collection method or collection area is predefined via a URL, and may process and store the text data extracted by performing data crawling or API calls.

[0040] According to one embodiment, a predefined URL dictionary rule may be a rule provided by an administrator from an administrator terminal. That is, the administrator can predict in advance what kind of URL the user will provide, generate a URL dictionary rule based on the characteristics of the website in the URL, and provide it to a learning capability characteristic diagnosis system. For example, the administrator may define a rule to perform data crawling in the case of a URL belonging to "SNS".

[0041] In this regard, FIG. 3 illustrates an embodiment in which a shared activity record collection unit (110) processes and stores text data according to a predefined URL dictionary rule.

[0042] As illustrated in FIG. 3, when a URL named "aaa.com" is provided from a user terminal, the sharing activity record collection unit (110) can check a URL dictionary in which the administrator has predefined rules. In this case, for example, the URL dictionary may define the URL "aaa.com" as " / share / ", " / like / ", or " / hate / ". Based on the content defined in the URL dictionary, the sharing activity record collection unit (110) can identify links that require data crawling or API calls, perform data crawling or API calls according to the content defined in the URL dictionary, and extract sharing activity records as text data within the website named "aaa.com".

[0043] According to one embodiment of the present invention, a URL dictionary, which is a dataset that defines the collection method and collection area of ​​a sharing activity record for each URL in advance, may define the collection method as two types: data crawling or a provided API.

[0044] According to one embodiment of the present invention, a URL dictionary, which is a dataset that defines the collection method and collection area of ​​sharing activity records by URL in advance, can designate URLs and tags related to sharing activity records as collection areas in the case of data crawling, and in the case of provided APIs, can define the URL, Method, request, and response information of the API related to sharing activity records so that only necessary information can be extracted.

[0045] According to one embodiment of the present invention, the shared activity record collection unit (110) can process and store the extracted information. For example, the shared activity record collection unit (110) can process and store text data by going through the steps of removing emoticons, stop words, etc. from the extracted information and encoding.

[0046] According to one embodiment of the present invention, the sharing activity record information analysis unit (120) may include a learning amount extraction unit (121) that extracts a learning amount by counting the number of actions that serve as the basis for analysis for each webpage of a URL containing a sharing activity record, using a predefined URL dictionary rule for actions that serve as the basis for analysis for each webpage of a URL. The predefined URL dictionary rule may be an example illustrated in FIG. 4. For example, in the case of a URL "aaa.com" corresponding to "SNS", the administrator may predefine 'the action of sharing another person's post to one's own SNS account' as the action that serves as the basis for analysis. As another example, in the case of a URL "ddd.com" corresponding to "developer community", the administrator may predefine 'commit' as the action that serves as the basis for analysis. According to one embodiment, the learning amount extracted by counting may be a natural number such as 0, 1, 2, or 3.

[0047] According to one embodiment of the present invention, the shared activity record information analysis unit (120) may include a learning duration extraction unit (122) that extracts the learning duration by counting how many consecutive days the behavior serving as the basis for analysis occurred for each webpage of the URL containing the shared activity record using a predefined URL dictionary rule for each webpage of the URL containing the shared activity record. The predefined URL dictionary rule may be an example illustrated in FIG. 4, and according to one embodiment, the learning duration may be calculated using the following formula.

[0049]

[0051] According to one embodiment of the present invention, the shared activity record information analysis unit (120) may include a field extraction unit (123) that uses text data extracted and processed by the shared activity record collection unit (110), selects only nouns from the text data through morphological analysis, and extracts the field of the selected nouns using a predefined field classification model. According to one embodiment, morphological analysis can be processed through a morphological analyzer using Python, and the 'nouns' selected can be selected to include 'proper nouns'. According to one embodiment, the predefined field classification model may be a classification model provided by an administrator from an administrator terminal. For example, as shown in FIG. 5, the administrator may have predefined the noun "Python" to be classified into the "programming language" field through the administrator terminal, the noun "Java" to be predefined to be classified into the "programming language" field, and the noun "gradient descent" to be predefined to be classified into the "deep learning" field. According to one embodiment, as shown in FIG. 5, the fields of nouns selected through morphological analysis can be extracted through a field classification model, and then the number of fields and the number of words per field are counted, and the ratio of the number of fields and the number of words per field is calculated to determine the learning frequency per field, and the fields outputted thereafter can be defined as learning fields. That is, as shown in FIG. 5, when the nouns outputted through the field classification model are five, namely "Python," "Java," "Gradient Descent," "Backpropagation," and "Data Cleaning," and there are two nouns in the "Deep Learning" field, two nouns in the "Programming Language" field, and one noun in the "Data Analysis" field, the output frequency of the "Deep Learning" field can be extracted as 40%, the output frequency of the "Programming Language" field as 40%, and the output frequency of the "Data Analysis" field as 20%.In addition, the extracted fields of "deep learning," "programming languages," and "data analysis" can be defined as "learning fields."

[0052] According to one embodiment of the present invention, the shared activity record information analysis unit (120) may include a learning proficiency extraction unit (124) that uses a noun selected by the field extraction unit (123) and a field extracted by the field extraction unit (123), maps the noun to a predefined field-specific word difficulty weight mapping table, and calculates field-specific proficiency or learning proficiency by counting the difficulty weights defined in the mapping table. According to one embodiment, the predefined field-specific word difficulty weight mapping table may be a table provided by an administrator from an administrator terminal. For example, as illustrated in FIG. 6, an administrator may have predefined the noun "artificial neural network" as having a difficulty value of "2" in the "machine learning" field through an administrator terminal, the noun "clustering" as having a difficulty value of "3" in the "machine learning" field, the noun "layer" as having a difficulty value of "1" in the "machine learning" field, and the noun "network" as having a difficulty value of "1" in the "machine learning" field. According to one embodiment, the proficiency level by field can be calculated as shown in FIG. 6 by counting the difficulty weights defined in the mapping table. That is, as shown in FIG. 6, since the "nouns" "artificial neural network," "clustering," "layer," and "network" are all extracted into the "machine learning" field, the user's proficiency level in the "machine learning" field in FIG. 6 is extracted as 7. In addition, "learning proficiency," which is distinct from "proficiency by field," can be extracted as the value obtained by summing the proficiency levels extracted for each field as described above and dividing by the number of extracted fields (i.e., the average of all proficiency levels by field).

[0053] According to one embodiment of the present invention, the user diagnosis unit (130) visualizes learning competency characteristics in the form of a polygonal graph using the analysis results of the shared activity record information analysis unit (120), and the polygonal graph may include at least one of the learning amount extracted by the learning amount extraction unit (121), the learning duration extracted by the learning duration extraction unit (122), and the learning proficiency extracted by the learning proficiency extraction unit (124). According to one embodiment, as shown in FIG. 7, the user diagnosis unit (130) can visualize learning competency characteristics in the form of a triangle graph including "number of learning sessions," "learning duration," and "learning proficiency" information using the analysis results of the shared activity record information analysis unit (120). Additionally, according to one embodiment, the number of learning sessions, the learning duration, and the learning proficiency may be calculated using the following formulas.

[0055]

[0057]

[0059]

[0061] According to one embodiment of the present invention, the user diagnosis unit (130) can diagnose a user's strengths or weaknesses based on a pre-set standard using the analysis results of the shared activity record information analysis unit (120). The pre-set standard may be a standard provided by the administrator from the administrator terminal. For example, the administrator may pre-define a standard to extract a field with a high number of learning sessions and high learning proficiency as a strength field, and conversely, pre-define a standard to extract a field with a high number of learning sessions and low learning proficiency as a weakness field. Additionally, the administrator may pre-define a standard so that a user with one or fewer learning fields does not have a strength or weakness field extracted.

[0062] According to an embodiment of the present invention, the user diagnosis unit (130) uses a knowledge graph in which field-specific relationships are predefined, and based on the field diagnosed as the user's strength field, the field with the highest correlation in the knowledge graph can be diagnosed as the field with potential for development of the user. A knowledge graph is a type of knowledge graph that lists search results closest to the user's search intent by displaying information related to the word when a search term is entered, and a knowledge graph in which field-specific relationships are predefined may be a knowledge graph provided by the administrator from the administrator terminal. More specifically, for example, as shown in FIG. 8, the administrator may have predefined the field-specific correlation between the "machine learning" field and the "deep learning" field as having the highest correlation of 0.8, the correlation between the "machine learning" field and the "data mining" field as having 0.2, and the correlation between the "machine learning" field and the "calculus" field as having 0.2. In this case, if the user's strength field is extracted and diagnosed as "machine learning," the field with potential for development can be extracted and diagnosed as "deep learning." According to one embodiment, a model that outputs predefined related fields or a predefined TF-IDF method may be used to replace a knowledge graph with predefined field relationships, but using a knowledge graph with predefined field relationships may be more suitable for "diagnosing the user's field with potential for development."

[0063] According to an embodiment of the present invention, the learning capability characteristic diagnosis system (100) may further include a diagnosis result output unit (140) that transmits the diagnosis result diagnosed by the user diagnosis unit (130) to a user terminal or an administrator terminal.

[0064] According to an embodiment of the present invention, the diagnostic result output unit (140) can transmit a graph to a user terminal or an administrator terminal that can compare basic indicators of learning ability characteristics, such as "number of learning sessions," "learning duration," "maximum value of learning proficiency," "minimum value of learning proficiency," "average value of learning proficiency," and "user's current overall score value," and can provide an interface to the user terminal or an administrator terminal that includes visualizations to allow verification of a comparison graph of "learning proficiency by field." For example, as shown in FIG. 9, information can be transmitted to the user terminal or an administrator terminal regarding how much the user's "learning amount" corresponds to compared with an average person and a person in the top tier, how much the user's "learning duration" corresponds to compared with an average person and a person in the top tier, and how much the user's "learning proficiency" corresponds to compared with an average person and a person in the top tier.

[0065] FIG. 10 is a perspective view showing an input housing (201) and an input plate (202) applied to a user terminal (10) connected to a learning competency feature diagnosis system (100) according to an embodiment of the present invention, FIG. 11 is a drawing showing the application of the input housing (201) and the input plate (202) to a user terminal (10) connected to a learning competency feature diagnosis system (100) according to an embodiment of the present invention, and FIG. 12 is a drawing showing the operation of the input housing (201) and the input plate (202) applied to a user terminal (10) connected to a learning competency feature diagnosis system (100) according to an embodiment of the present invention.

[0066] As illustrated in FIGS. 10 to 12, a user terminal (10) is combined with an input housing (201) and an input plate (202), and using the input housing (201) and the input plate (202), check information can be received and transmitted to a user diagnostic unit (130), and the user diagnostic unit (130) can transmit the check information to an administrator terminal (20). Here, the check information is information used to verify the user's satisfaction, etc., regarding the use of the learning competency characteristic diagnostic system (100), and can be verified by an administrator managing the learning competency characteristic diagnostic system (100).

[0067] The user terminal (10) is formed in the form of a smartphone and may include a display unit (11) in the form of a display device that is located on one side of the user terminal (10) and can display a check item (a) for check information and an input area (b) for inputting a score corresponding to the check item (a), and a detector unit (12) in the form of a camera or sensor that is spaced apart from the display unit (11) on one side of the user terminal (10) and located at a first end portion of the user terminal (10). Here, the check item may be in the form of "Is the system convenient to use?", "Do you want to continue using the system?", "Do you want to recommend the system to others?", etc., and the input area is shown as being composed of three, but is not limited thereto and may be composed of three or more, such as five, seven, nine, etc.

[0068] The input housing (201) is formed in a shape corresponding to the user terminal (10) and can accommodate the user terminal (10) in a detachable manner. A housing space (210), a display opening (201a), and a placement space (201b) may be formed in the input housing (201).

[0069] The housing space (210) is formed in a shape corresponding to the user terminal (10) inside the input housing (201), and both end faces can be open.

[0070] A display opening (201a) may be formed on the upper surface of an input housing (201) and connected to a housing space (210). When a user terminal (10) is positioned in the housing space (210), the display portion (11) and detector portion (12) of the user terminal (10) may be positioned to correspond to the display opening (201a).

[0071] The placement space (201b) can be formed concavely on the bottom surface of the housing space (210) to correspond to the user terminal (10) and can be positioned to correspond to the display opening (201a). The user terminal (10) can be positioned in the housing space (210) and inserted into the placement space (201b), and the display unit (11) and detector unit (12) can be positioned to correspond to the display opening (201a) and can be viewed through the display opening (201a).

[0072] Additionally, the input housing (201) may include a moving guide (211) and a sub-stopper (213).

[0073] The moving guide (211) may be composed of multiple guides and positioned on each side of the input housing (201) so as to be spaced apart from one another along one direction (A). When the user terminal (10) is positioned in the housing space (210), the moving guide (211) may be positioned above the user terminal (10) and spaced apart from the upper surface of the housing space (210).

[0074] Additionally, the moving guide (211) may include a moving power body (211a) and a moving transmission body (211b).

[0075] The moving power body (211a) is formed in the form of a motor and can be located on the outer side of the input housing (201).

[0076] The moving transmission body (211b) is formed in the form of a pinion gear and is positioned to correspond to the moving power body (211a) on the inner side of the housing space (210) and can be connected to the moving power body (211a). Here, the moving transmission body (211b) can be rotated by the moving power body (211a).

[0077] The sub-stopper (213) is formed in the shape of a rectangular plate and is located near the first end surface of the housing space (210) and the moving guide (211) in the housing space (210), and can be hinged to the inner surface of the housing space (210). Here, the first end portion of the sub-stopper (213) can be hinged to the inner surface of the housing space (210) so as to be adjacent to a moving conveyor (211b) positioned to face the first end surface of the housing space (210), and the second end portion opposite the first end portion of the sub-stopper (213) can be in contact with the placement space (201b) or spaced apart from the placement space (201b).

[0078] Meanwhile, the user terminal (10) can be inserted into or separated from the housing space (210) through the second end face opposite the first end face of the housing space (210) due to the sub-stopper (213).

[0079] Additionally, a stopper projection (213a) may be formed on the lower surface of the first end portion of the sub-stopper (213), and the stopper projection (213a) may be made of a material such as rubber.

[0080] When the user terminal (10) is not positioned in the housing space (210), the substopper (213) is tilted so that the second end of the substopper (213) contacts the placement space (201b) and can be positioned lower than the first end portion of the substopper (213) (see FIG. 11(a)).

[0081] Meanwhile, when the user terminal (10) is gradually inserted into the housing space (210) through the second end surface of the housing space (210) (the left portion of the housing space (210) in FIG. 11), the sub-stopper (213) is rotated in contact with the user terminal (10), and the second end of the sub-stopper (213) can be gradually separated from the placement space (201b). Additionally, when the display portion (11) of the user terminal (10) is positioned to correspond to the display opening (201a) of the input housing (201), the stopper projection (213a) of the sub-stopper (213) can be positioned on one surface of the first end portion of the user terminal (10). Here, the sub-stopper (213) is tilted so that the second end of the sub-stopper (213) is positioned above the first end of the sub-stopper (213) by means of the stopper projection (213a) (see FIG. 11(b)). Additionally, the sub-stopper (213) may be positioned to face the first end surface of the input plate (202).

[0082] The input plate (202) may be formed in a plate shape corresponding to the display opening (201a). Here, the input plate (202) may be inserted into the housing space (210) and engaged with the moving guide (211), and may be movable by the moving guide (211). A check opening (202a) and an input opening (202b) may be formed in the input plate (202).

[0083] A check opening (202a) can be formed on an input plate (202) with a size corresponding to one check item (a) displayed on the display unit (11) of a user terminal (10) for check information.

[0084] The input opening (202b) may be formed on the input plate (202) with a size corresponding to the input area (b) displayed on the display unit (11) of the user terminal (10) for inputting check information. Here, the input opening (202b) may be positioned on the input plate (202) in combination with the check opening (202a) to form the same straight line along a direction orthogonal to one direction (A), and may be formed in multiple numbers corresponding to the input area (b).

[0085] Additionally, a detector mark (220) may be formed on the first end portion of the lower surface of the input plate (202) (refer to the upper portion of the input plate (202) in FIG. 10). Here, the detector mark (220) may be in the form of a QR code, a bar code, etc.

[0086] With the input plate (202) accommodated in the housing space (210), the detector mark (220) may be positioned to correspond to the detector section (12) of the user terminal (10) accommodated in the housing space (210). Here, the detector section (12) detects the detector mark (220), and the display section (11) may display a plurality of check items (a) for inputting check information corresponding to the detector mark (220) and an input area (b) corresponding to each of the check items (a). Additionally, one check item (a) and an input area (b) corresponding to one check item (a) displayed at the first end portion of the display section (11) may be confirmed through the check opening (202a) and the input opening (202b).

[0087] Additionally, the input plate (202) may include a moving aid (221).

[0088] The moving aid (221) is formed as a pair and can be positioned along one direction (A) on both sides of the input plate (202). Here, the moving aid (221) can be formed in the form of a rack gear. When the input plate (202) is inserted into the housing space (210), the moving aid (221) is positioned above the moving transmission body (211b) of the moving guide (211) and can be engaged with the moving transmission body (211b). Here, the moving aid (221) and the moving transmission body (211b) can be engaged in a combination of a rack gear and a pinion gear. When the moving power body (211a) rotates the moving transmission body (211b), the moving transmission body (211b) can move the moving aid (221) to move the input plate (202).

[0089] Meanwhile, as previously mentioned, the display portion (11) of the user terminal (10) is positioned to correspond to the display opening (201a) of the input housing (201), and the substopper (213) can be tilted so that the second end of the substopper (213) is positioned above the first end of the substopper (213) by the stopper projection (213a). Here, the input plate (202) is positioned in the housing space (210) and is positioned above the user terminal (10), and its movement toward the first end surface of the housing space (210) can be restricted by the substopper (213). That is, when the user terminal (10) is accommodated in the housing space (210) of the input housing (201), the input plate (202) cannot pass through the first end surface of the housing space (210) and can pass through the second end surface of the housing space (210).

[0090] The above-described input housing (201) and input plate (202) can be applied to a user terminal (10) and operated as follows.

[0091] First, an input plate (202) can be inserted into and accommodated in a housing space (210). Here, the input plate (202) can be positioned to correspond to a display opening (201a), and the moving aid (221) of the input plate (202) can be engaged with the moving conveyor (211b) of the moving guide (211) (see FIG. 11(a) and FIG. 11(b)).

[0092] Next, the user terminal (10) can be inserted into and accommodated in the housing space (210) of the input housing (201) (see FIG. 11(b)). Here, the user terminal (10) is inserted into the placement space (201b) and positioned below the input plate (202), and the sub-stopper (213) is tilted so that the second end of the sub-stopper (213) is positioned above the first end of the sub-stopper (213). Additionally, the display unit (11) and detector unit (12) of the user terminal (10) can be positioned to correspond to the display opening (201a).

[0093] In the above state, the detector mark (220) of the input plate (202) may be positioned to correspond to the detector unit (12) of the user terminal (10). Here, the detector unit (12) detects the detector mark (220), and the display unit (11) may display a plurality of check items (a) for inputting check information corresponding to the detector mark (220) and an input area (b) corresponding to each of the check items (a). Additionally, the check opening (202a) and the input opening (202b) of the input plate (202) may be positioned to correspond to one check item (a) and an input area (b) corresponding to one check item (a) displayed on the first end portion (upper portion of FIG. 5) of the display unit (11), respectively (see FIG. 6(a)). Here, the user terminal (10) can generate a check item (a) corresponding to the check opening (202a) as voice. That is, the user can easily recognize the check item (a) and input area (b) to be entered through the check opening (202a) and input opening (202b).

[0094] Additionally, the user can touch the input area (b) displayed on the display unit (11) through the input opening (202b). Here, the display unit (11) can display a touch mark (c) corresponding to the touched input area (b), and a response value corresponding to the input area (b) where the touch mark (c) is displayed can be input to the user terminal (10) for the check item (a). The user terminal (10) can generate an operation signal and transmit it to the input housing (201). Additionally, the operation of the moving guide (211) can be performed in the input housing (201). The moving power body (211a) of the moving guide (211) rotates the moving transmission body (211b), so that the moving transmission body (211b) can move the moving auxiliary body (221) toward the second end portion (lower portion of FIG. 12) opposite the first end portion of the display unit (11). That is, the detector mark (220) can be moved away from the detector unit (12). As a result, the check opening (202a) and the input opening (202b) of the input plate (202) can be positioned to correspond to another check item (a) and an input area (b) corresponding to another check item (a) displayed on the display unit (11), and a part of the input plate (202) can be positioned to protrude from the housing space (210) (see FIG. 12(b)).

[0095] As described above, the user can input check information by selectively touching the input area (b) for each check item (a) displayed on the display unit (11) through the input opening (202b).

[0096] As illustrated in FIG. 12(b), the input plate (202) is continuously moved by the moving guide (211) so that the user can touch the input area (b) for the last check item (a) among the check items (a) displayed on the display unit (11). When the user touches the display unit (11) to select the input area (b) for the last check item (a), the user terminal (10) can generate check information including check items (a) and response values ​​corresponding to the check items (a) and the selected input area (b). Additionally, the display unit (11) can display multiple check items (a) of different content and input areas (b) corresponding to each of the check items (a) for inputting check information.

[0097] In the above state, the user terminal (10) can generate a restoration signal and transmit it to the input housing (201). Additionally, the operation of the moving guide (211) can be performed in the input housing (201). The moving power body (211a) of the moving guide (211) rotates the moving transmission body (211b), so that the moving transmission body (211b) can move the moving auxiliary body (221) toward the first end portion (upper portion of FIG. 12) of the display unit (11). Here, the detector mark (220) can be moved to be close to the detector unit (12). A detector mark (220) is positioned to correspond to the detector unit (12), and when the detector unit (12) detects the detector mark (220), the user terminal (10) generates a stop signal and transmits it to the input housing (201), and the moving guide (211) can be stopped. Additionally, the input plate (202) may not be moved to pass through the first end surface of the housing space (210) by means of a sub-stopper (213). Here, the check opening (202a) and the input opening (202b) of the input plate (202) may again be positioned to correspond to one check item (a) displayed on the first end portion of the display unit (11) and an input area (b) corresponding to one check item (a) (see FIG. 12(a)). That is, the input housing (201) and the input plate (202) can be used to input check information while checking multiple check items (a) of different content and an input area (b) corresponding to each of the check items (a).

[0098] The learning competency characteristic diagnosis system (100) of the present embodiment can receive check information through the user terminal (10) while the input housing (201) and the input plate (202) are applied to the user terminal (10). Check items (a) for inputting check information displayed on the display unit (11) of the user terminal (10) and the input area (b) corresponding to the check items (a) can be physically identified by the input plate (202) for each check item (a). As a result, the response value corresponding to the input area (b) for the check item (a) displayed on the display unit (11) of the user terminal (10) can be input more accurately, so that the user can input check information to the user terminal (10) more easily and accurately.

[0099] The functional operations and embodiments relating to the subject matter described above in this specification may be implemented in digital electronic circuits, computer software, firmware, or hardware, or in a combination of one or more of these, including the structures disclosed in this specification and their structural equivalents.

[0100] Embodiments of the subject matter described herein may be implemented as one or more computer program products, that is, as one or more modules relating to computer program instructions encoded on a tangible program medium for execution by a data processing device or for controlling the operation thereof. The tangible program medium may be a radio signal or a computer-readable medium. A radio signal is an artificially generated signal, such as an electrical, optical, or electromagnetic signal generated by a machine, for example, to encode information to be transmitted to a suitable receiver device for execution by a computer. A computer-readable medium may be a machine-readable storage device, a machine-readable storage substrate, a memory device, a combination of materials affecting a machine-readable radio signal, or a combination of one or more of these.

[0101] A computer program (also known as a program, software, software application, script, or code) may be written in any form of a programming language, including compiled or interpreted languages, or a priori or procedural languages, and may be developed in any form, including a standalone program, modules, components, subroutines, or other units suitable for use in a computer environment.

[0102] A computer program does not necessarily correspond to a file in a file system. A program may be stored within a single file provided to the requested program, within multiple interacting files (e.g., a file storing one or more modules, subprograms, or parts of code), or within a part of a file containing other programs or data (e.g., one or more scripts stored within a markup language document).

[0103] Computer programs can be deployed to be executed on multiple computers or a single computer that are located at one site or distributed across multiple sites and interconnected by a communication network.

[0104] Additionally, the logical flow and structural block diagrams described herein describe corresponding actions and / or specific methods supported by corresponding functions and steps supported by the disclosed structural means, and can also be used to construct corresponding software structures and algorithms and their equivalents.

[0105] The processes and logic flows described in this specification can be performed by one or more programmable processors that execute one or more computer programs to perform functions by operating on input data and generating outputs.

[0106] Processors suitable for the execution of computer programs include, for example, both general-purpose and special-purpose microprocessors and any one or more processors of any type of digital computer. Generally, the processor will receive instructions and data from read-only memory or random access memory or both.

[0107] The core elements of a computer are one or more memory devices for storing instructions and data, and a processor for executing instructions. Additionally, a computer will generally be combined with or include one or more mass storage devices for storing data, such as magnetic, magneto-optical, or optical discs, to be operable to receive data from, transmit data to, or perform both of these operations. However, a computer does not need to have such devices.

[0108] The description provided herein presents the best mode of the invention and offers examples to explain the invention and to enable those skilled in the art to manufacture and use the invention. The specification thus written is not intended to limit the invention to the specific terms presented.

[0109] Accordingly, although the present invention has been described in detail with reference to the examples above, those skilled in the art may make modifications, changes, and variations to these examples without departing from the scope of the present invention. In short, it is stated that in order to achieve the intended effect of the present invention, it is not necessary to separately include all functional blocks shown in the drawings or to follow all sequences shown in the drawings exactly as shown; such matters may fall within the technical scope of the present invention as described in the claims even if they are not. Explanation of the symbols

[0110] 10: User terminal 20: Administrator Terminal 30: Online data server 31: Shared Activity URL 100: Learning Competency Characteristics Diagnostic System 110: Shared Activity Record Collection Department 120: Shared Activity Record Information Analysis Department 130: User Diagnostics Unit 140: Diagnosis Result Output Section

Claims

Claim 1 A learning competency characteristic diagnosis system that connects an online data server containing a URL containing a shared activity record and a user terminal via a network, comprising: a shared activity record collection unit (110) capable of receiving one or more URLs containing a shared activity record from a user terminal to extract text data and processing and storing the extracted text data; a shared activity record information analysis unit (120) that analyzes the user's shared activity record using the text data extracted and processed by the shared activity record collection unit; and a user diagnosis unit (130) that diagnoses the user's learning competency characteristics using the analysis results of the shared activity record information analysis unit (120), wherein the user terminal receives check information and transmits it to the user diagnosis unit, and the user diagnosis unit transmits the received check information to an administrator terminal, and the user terminal includes a display unit in the form of a display device located on one side of the user terminal and capable of displaying an input area in which a check item for the check information and a response value corresponding to the check item can be entered. The learning capability feature diagnosis system includes a detector unit in the form of a camera or sensor spaced apart from a display unit on one side of the user terminal and located at a first end portion of the user terminal, and the input housing includes a plurality of moving guides positioned spaced apart from each other along one direction on each of the two sides, wherein a housing space is formed internally with both end surfaces open and having a shape corresponding to the user terminal and into which the user terminal can be inserted, a display opening connected to the housing space is formed on the upper surface, and a concave placement space corresponding to the user terminal is formed on the bottom surface of the housing space; and the input plate further includes a pair of moving auxiliary bodies formed in a plate shape, having a check opening and an input opening formed therein, positioned along one direction on both sides, formed in the form of a rack gear, and capable of engaging with the moving guides, wherein the moving guidesA motor-shaped moving power element located on the side of the input housing; It includes a moving transmission body in the form of a pinion gear that is positioned to correspond to a moving power body in the housing space, connected to the moving power body, can be rotated by the moving power body, and can mesh with a moving auxiliary body; an input plate is inserted and positioned in the housing space, so that the moving auxiliary body and the moving transmission body of the moving guide mesh with each other; a user terminal is positioned in the housing space and inserted into the placement space, a display unit and a detector unit are positioned to correspond to the display opening and are located below the input plate; when the moving power body of the moving guide rotates the moving transmission body, the moving auxiliary body moves and the input plate moves in the housing space; a detector mark is formed on a first end portion of the lower surface of the input plate; the input plate is positioned to correspond to the display opening and is located above the user terminal located in the housing space, so that the detector mark is positioned to correspond to the detector unit and when detected by the detector unit, the display unit displays a plurality of check items corresponding to the detector mark and an input area corresponding to each of the check items. The check opening and the input opening of the input plate are positioned to correspond to one check item displayed on the first end portion of the display unit and an input area corresponding to one check item, respectively; when a user touches the input area displayed on the display unit through the input opening, the display unit displays a touch mark corresponding to the touched input area; the user terminal generates an operation signal and transmits it to the input housing; the moving power body rotates the moving transmission body; the moving auxiliary body moves toward the second end portion opposite the first end portion of the display unit; the check opening and the input opening are positioned to correspond to another check item displayed on the display unit and an input area corresponding to another check item; a part of the input plate is positioned to protrude from the housing space; and the input housing is,It further includes a rectangular plate-shaped substopper located near a moving guide and a first end surface of the housing space and hinged to the inner surface of the housing space; the first end portion of the substopper is hinged to the inner surface of the housing space so as to be adjacent to a moving conveyor positioned to face the first end surface of the housing space; the second end portion opposite the first end portion of the substopper contacts or is spaced apart from the placement space; a stopper projection made of rubber is formed on the lower surface of the first end portion of the substopper; when an input plate is located in the housing space and a user terminal is not located in the housing space, the second end portion of the substopper contacts the placement space and is located lower than the first end portion of the substopper; when the user terminal is gradually inserted into the housing space through the second end surface of the housing space, the substopper contacts the user terminal and rotates, and the second end portion of the substopper is gradually separated from the placement space A learning capability feature diagnosis system characterized by being spaced apart, and when the display portion of the user terminal is positioned to correspond to the display opening of the input housing, the stopper projection of the substopper is positioned on one surface of the first end portion of the user terminal, and the second end of the substopper is positioned above the first end of the substopper so that the substopper is tilted to face the first end surface of the input plate. Claim 2 A learning capability characteristic diagnosis system according to claim 1, wherein the shared activity record collection unit (110) selectively performs data crawling or API calls according to a predefined URL rule for a shared activity record collection method or collection area via URL, and can process and store text data extracted by performing data crawling or API calls. Claim 3 A learning competency characteristic diagnosis system according to claim 1, wherein the shared activity record information analysis unit (120) includes a learning amount extraction unit (121) that extracts the learning amount by counting the number of actions that serve as the basis for analysis for each webpage of the URL containing the shared activity record using a predefined URL dictionary rule for actions that serve as the basis for analysis for each webpage of the URL. Claim 4 A learning competency characteristic diagnosis system according to claim 1, wherein the shared activity record information analysis unit (120) includes a learning duration extraction unit (122) that extracts the learning duration by counting how many consecutive days the behavior serving as the basis for analysis occurred for each webpage of the URL containing the shared activity record, using a predefined URL dictionary rule for the behavior serving as the basis for analysis for each webpage of the URL. Claim 5 A learning competency feature diagnosis system according to claim 1, wherein the shared activity record information analysis unit (120) utilizes text data extracted and processed by the shared activity record collection unit, and includes a field extraction unit (123) that selects only nouns from the text data through morphological analysis and extracts the field of the selected nouns using a predefined field classification model. Claim 6 A learning competency feature diagnosis system according to claim 5, wherein the shared activity record information analysis unit (120) utilizes nouns selected by the field extraction unit (123) and fields extracted by the field extraction unit (123), maps the nouns to a predefined field-specific word difficulty weight mapping table, and includes a learning proficiency extraction unit (124) that calculates field-specific proficiency or learning proficiency by counting the difficulty weights defined in the mapping table. Claim 7 A learning competency characteristic diagnosis system according to claim 1, wherein the user diagnosis unit (130) visualizes learning competency characteristics in the form of a polygonal graph using the analysis results of the shared activity record information analysis unit (120), and the polygonal graph includes at least one of the learning amount extracted by the learning amount extraction unit (121), the learning duration extracted by the learning duration extraction unit (122), and the learning proficiency extracted by the learning proficiency extraction unit (124). Claim 8 A learning competency characteristic diagnosis system according to claim 1, wherein the user diagnosis unit (130) diagnoses the user's strengths or weaknesses according to pre-set criteria using the analysis results of the shared activity record information analysis unit (120). Claim 9 In claim 8, the user diagnosis unit (130) uses a knowledge graph in which the relationship between fields is predefined, and is characterized by diagnosing the field with the highest correlation of the knowledge graph as the field with potential for development of the user based on the field diagnosed as the user's strength field. Claim 10 In claim 1, the learning competency feature diagnosis system (100) further comprises a diagnosis result output unit (140) that transmits a diagnosis result diagnosed by a user diagnosis unit (130) to a user terminal.

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