KR20210041427A - Apparatus and Method for Managing Curriculum based on Job Competence which is corresponded to Society Demand based on ontology and deep-learning - Google Patents

Abstract

A competency-based education process management device according to one embodiment disclosed herein comprises: a communication circuit which can communicate with a plurality of external electronic devices; a memory; and a processor. The process is configured to: collect National Competency Standards (NCS) data, subject data, and job data from the plurality of external electronic devices through the communication circuit; configure an ontology model related to a job, a task, and a subject based on the NCS data, the subject data, and the job data; calculate the degree of association between the subject and the job or between the subject and the task based on the ontology model, the NCS data, the subject data, and the job data; and match the subject and the job or the subject and the task associated with a numerical value or more specified in the ontology model based on the calculated degree of association. According to the present invention, the competency-based education process management device can guide a user to check required task competency based on machine learning.

Description

Apparatus and Method for Managing Curriculum based on Job Competence which is corresponded to Society Demand based on ontology and deep-learning}

Various embodiments disclosed in this document relate to machine learning technology for career search or training course management.

In recent years, education is not limited to delivering simple knowledge, but aims to cultivate talents that companies or society want. Accordingly, educational institutions or professors are trying to analyze the human resources desired by companies or industries and apply education accordingly.

Korean Patent Publication No. 10-2018-0041478

However, since the speed of change in jobs and jobs has accelerated due to a paradigm such as the Fourth Industrial Revolution, it may be difficult for small-scale individuals to analyze in real time the talent image desired by a company or industry based on national data. Therefore, there is a need for an automated system to analyze the requirements (personnel) desired by rapidly changing companies or industrial sites from various angles and apply them to the education process.

Various embodiments disclosed in this document may provide an ontology capable of confirming and guiding a user's job competency based on machine learning, and an apparatus and method for managing a socially tailored competency-based training course based on deep learning.

An apparatus for managing a competency-based curriculum according to an embodiment disclosed in the present document includes: a communication circuit capable of communicating with a plurality of external electronic devices; Memory; And a processor, wherein the processor collects National Competency Standards (NCS) data, subject data, and occupation data from the plurality of external electronic devices through the communication circuit, and the national competency standard data, Based on the subject data and the job data, an ontology model related to a job, job, and subject is constructed, and the subject and the subject based on the ontology model, the national job competency standard data, the subject data and the job data A degree of association between a job or the job may be calculated, and the subject may be matched between the job or the subject and the job, which are associated with a number or more specified in the ontology model based on the calculated association.

In addition, a competency-based curriculum management method according to an embodiment disclosed in this document includes: collecting national competency standard data, subject data, and job data from a plurality of external electronic devices; Constructing an ontology model related to a job, a job, and a subject based on the national job competency standard data, the subject data, and the job data; Calculating a degree of association between the subject and the job or the job based on the ontology model, the national job competency standard data, the subject data, and the job data; And matching the subject and the job, or between the subject and the job, which are associated with a number or more specified in the ontology model based on the calculated degree of association.

According to various embodiments disclosed in this document, it is possible to check and guide a user's job competency required for a user based on machine learning. In addition to this, various effects that are directly or indirectly identified through this document can be provided.

1 shows an implementation environment of an apparatus for managing a competency-based curriculum according to an embodiment.
2 is a block diagram of an apparatus for managing a competency-based curriculum according to an embodiment.
3 shows a method for managing a competency-based curriculum according to an embodiment.
4 and 5 illustrate diagrams defining a correspondence relationship between monitoring data based on a capability unit, according to an exemplary embodiment.
6 shows an example of a job description among national job competency standard data according to an embodiment.
7 illustrates a function of inferring association of an ontology instance by the apparatus for managing a competency-based curriculum according to an exemplary embodiment.
8 shows a correspondence relationship between corporate announcement data and job, job, and subject according to an embodiment.
9, 10, and 11 illustrate examples of career counseling services by the apparatus for managing a competency-based curriculum according to an embodiment.
In connection with the description of the drawings, the same or similar reference numerals may be used for the same or similar components.

1 shows an implementation environment of an apparatus for managing a competency-based curriculum according to an embodiment.

Referring to FIG. 1, according to an embodiment, the competency-based curriculum management apparatus 120 collects monitoring data from a plurality of external electronic devices 110 and machine learns the collected data, and then based on the learning result. A career counseling service may be provided to the user terminal 130.

The competency-based curriculum management device 120 collects national competency standard data (hereinafter referred to as “NCS data”), subject data, and job data through web sites provided by a plurality of external electronic devices 110, Based on the collected NCS data, subject data, and occupation data, an ontology model related to occupation, job and subject can be constructed. The competency-based curriculum management device 120 calculates a degree of association (eg, similarity) between a subject and a job or job based on an ontology model, NCS data, subject data, and job data, and an ontology model based on the calculated degree of association. In, the subject and the job or the subject and the job can be related.

The competency-based curriculum management apparatus 120 may provide a career counseling service to the user terminal 130 based on a correspondence relationship between a subject and a job or a subject and a job in the ontology model. For example, the competency-based curriculum management device 120 receives a query related to a subject, job, or job from the user terminal 130, and subject to subject related job information corresponding to the received query based on the ontology model, subject related Determines at least one career-related information (e.g., job information that matches competency, subject information required for a target job) among job information, job-related subject information, or subject-related job information, and uses the determined at least one career-related information It can be provided to the terminal 130.

According to an embodiment, the external electronic devices 110 may be computing devices that store monitoring data of at least one of National Competency Standards (NCS) data, subject data, job data, and corporate announcement data. The NCS data may include, for example, at least one of classification system information, job description information, and competency description information defined in the national job competency standard. The subject data includes, for example, grade information related to each subject, textbook information (e.g., textbook name), major information (e.g., major name), textbook introduction information, textbook table of contents information, lecture plan information (e.g., lecture plan) ) And lecture goal information. The job data includes, for example, job overview information related to each job (eg, job summary of each job worker), job performance information (eg, job job performed by each job worker), and similar name information (eg, job summary of each job worker). Name information similar to), related job information (e.g. job information associated with each job), certification information (e.g., certification information useful or necessary for each job), standard industry classification information, and standard job classification information (e.g. Korean standard job information) It may include at least one of classification and Korean employment classification). For example, each of the external electronic devices 110 may be a web service server that provides at least one monitoring data through a web site. Each of the external electronic devices 110 includes a web site server that discloses national standard job competency data, a public job search web site server (eg, Career Net), a private job search web site server (eg, a person), and the classification information. It may include at least one of a web site server (eg, Statistics Korea server, Ministry of Employment and Labor server, and Ministry of Education server).

According to an embodiment, the user terminal 130 requests a career counseling service from the competency-based curriculum management device 120 through a website or an application program provided by the competency-based curriculum management device 120, and A user interface screen related to a career counseling service may be provided from the apparatus 120 for managing a curriculum, and the interface may be displayed. The user terminal 130 is a computing device such as a PC, a laptop computer, a smart phone, a tablet, and a wearable computer. It may refer to all terminal devices capable of installing and executing an access or service-only application. The user terminal 130 may be a computing device used by at least one user of a learner or a professor.

According to various embodiments, the competency-based curriculum management device 120 periodically collects corporate announcement data from at least one external electronic device (eg, 110), and provides corporate announcement data in addition to NCS data, subject data, and job data. Based on this, an ontology model related to occupations, jobs, and subjects can be constructed. In this case, the competency-based training course management device 120 checks the job information, job information, technical information, and qualification information requested by the company from the corporate announcement data, calculates the degree of association between the company demand and the job, job, or education, and calculates it. Jobs, jobs, or subjects can be related to respond to corporate demand in the ontology model based on the calculated calculation diagram.

According to the above-described embodiment, the competency-based curriculum management device 120 diagnoses the user's current competency (eg, certification information, completion subject), and guides the user's desired job or competency information more necessary for the job. have.

In addition, according to the above-described embodiment, the competency-based curriculum management apparatus 120 may provide a career counseling service according to actual demand by responding to a job, a job, or a subject so as to respond to corporate demand.

2 is a block diagram of an apparatus for managing a competency-based curriculum according to an embodiment.

Referring to FIG. 2, a competency-based curriculum management apparatus 200 (eg, competency-based curriculum management apparatus 120 of FIG. 1) according to an embodiment includes a communication circuit 210, a memory 220, and a processor ( 230). In an embodiment, the competency-based curriculum management apparatus 200 may omit some components or further include additional components. In addition, some of the components of the competency-based curriculum management apparatus 200 are combined to form a single entity, and functions of the corresponding components prior to the combination may be performed in the same manner.

The communication circuit 210 establishes a communication channel or a wireless communication channel between the competency-based training course management device 200 and other devices (eg, external electronic devices 110, user terminal 130), and the established communication channel It is possible to support communication through communication. The communication channel may be, for example, a communication channel of a communication method such as a local area network (LAN), FTTH (Fiber　to　the　home), xDSL (x-Digital　Subscriber　Line), WiFi, Wibro, 3G or 4G.

The memory 220 may store various data used by at least one component (eg, the processor 230) of the competency-based training course management apparatus 200. The data may include, for example, input data or output data for software and instructions related thereto. For example, the memory 220 may store at least one instruction for providing a competency-based curriculum management service. The memory 220 may include a volatile memory or a nonvolatile memory.

The processor 230 may control at least one other component (eg, hardware or software component) of the competency-based curriculum management apparatus 200 by executing at least one instruction, and perform various data processing or operations. You can do it. The processor 230 is, for example, a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor, an application processor, an application specific integrated circuit (ASIC), field programmable gate arrays (FPGA). )), and may have a plurality of cores. According to an embodiment, the processor 230 collects monitoring data such as NCS data, subject data, and job data from a plurality of external electronic devices 110 through the communication circuit 210, and learns the collected monitoring data. And, based on the learning result, the job and job, the subject and the job or the subject and the job are related in the ontology model, and a career counseling service can be provided based on the correspondence relationship between the subject and the job or job in the ontology model. .

According to an embodiment, the processor 230 collects monitoring data such as NCS data, subject data, and job data from web sites provided by a plurality of external electronic devices 110 through the communication circuit 210 (eg : Can perform at least one of crawling or scraping). The NCS data may include, for example, at least one of classification system information, job description information, and competency description information defined in the national job competency standard. The subject data includes, for example, grade information related to each subject, major information (e.g., major name, major university), textbook information (e.g. textbook name), textbook introduction information, textbook table of contents information, lecture plan information (e.g. : Lecture plan) and lecture goal information. The job data includes, for example, job overview information related to each job (eg, job summary of each job worker), job performance information (eg, job job performed by each job worker), and similar name information (eg, job summary of each job worker). Name information similar to), related job information (e.g. job information associated with each job), certification information (e.g., certification information useful or necessary for each job), standard industry classification information, and standard job classification information (e.g. Korean standard job information) It may include at least one of classification and Korean employment classification).

According to an embodiment, the processor 230 may configure an ontology model related to at least one of a job, a job, and a subject based on the collected monitoring data. For example, the processor 230 may construct an ontology model related to a relationship between a job, a subject, and a job centering on the competency unit according to the NCS data by using the monitoring data. For another example, the processor 230 may configure an ontology model for each job, subject, and job centering on the competency unit according to the NCS data by using the monitoring data. The job may be a set of jobs that are similar (or related to a specified degree of similarity or higher). The job may include a series of tasks and duties. The competency unit may be a sub-unit of the job according to the national job competency standard classification. Each competency unit can be composed of competency unit elements (performance standards, knowledge and skills attitude) corresponding to each competency unit, scope of application and work situation, evaluation guidelines, and basic job competency. In this regard, the processor 230 checks the structure of job-related data by analyzing at least one of the characteristics of the classification system according to the national job competency standard, job description, and competency description, and ) You can configure an ontology model that defines the relationship between ontology instances in the center.

According to an embodiment, the processor 230 calculates a degree of association (eg, similarity) between a subject and a job or job based on an ontology model, NCS data, subject data, and job data, and based on the calculated association, the ontology In the model, you can relate subjects and jobs or subjects and jobs. For example, the processor 230 may calculate a degree of association between a subject and a job or a subject based on the competency unit, and may associate a subject with a job or subject in the ontology model based on the calculated degree of association. For another example, the processor 230 extracts at least one of a job keyword, a job keyword, or a subject keyword from NCS data, subject data, and job data, and at least one of the Word2Vec algorithm and the LSA (Latent Semantic Analysis) algorithm. Feature vectors of at least one keyword may be calculated based on the algorithm. The processor 230 calculates the degree of association between the subject for each department and the job or the job based on the similarity of the calculated feature vectors, and relates the subject and the job or job in the ontology model based on the calculated association ( Or grouping). As another example, the processor 230 calculates the degree of similarity (e.g., cosine similarity) between a subject and a job or a subject and a job, and an ontology between a subject and a job or a subject and a job with a calculated similarity equal to or greater than a specified value (e.g. 0.6). You can relate it in the model.

In this regard, the processor 230 generates a job or job list related to a subject for each department, and provides the generated job or job list to the user terminal 130 (for example, a professor terminal) through the communication circuit 210. I can. The processor 230 may acquire a job selected by the user terminal 130 or a selected job, and calculate a degree of association between the subject for each department and the selected job or the selected job. The processor 230 calculates the degree of association between departmental subjects and jobs for some of the departments (e.g., departments for which job is selected), and for the rest of the departments (e.g., departments for which job is selected), subjects for each department It is possible to calculate the degree of association between the job and the job. The processor 230 may check the degree of association between some departments and the rest of the departments using at least one of the Doc2Vec algorithm and the LSA algorithm, and may check the degree of association between a job and a job based on the degree of association between some departments and the rest of the departments. .

According to an embodiment, the processor 230 may provide a career counseling service to the user terminal 130 based on a correspondence relationship between a subject and a job or a subject and a job in the ontology model. In one embodiment, the processor 230 checks the instance graph by performing the ontology inference based on the subject and job related to the competency unit or the subject and job in the ontology model, and includes a query and response that can be processed through the instance graph. Service scenarios can be created. The processor 230 may provide a career counseling service according to the generated service scenario.

For example, the processor 230 receives a query related to a subject, job, or job from the user terminal 130 through the communication circuit 210, and subject related job information corresponding to the received query based on the ontology inference, At least one career-related information among subject-related job information, job-related subject information, or subject-related job information may be determined, and the determined at least one career-related information may be provided to the user terminal 130. For another example, the processor 230 obtains the user's course information through the user terminal 130, and checks the job information or job information related to the course information and the specified degree of association or higher from the memory 220. And, the confirmed job information or the confirmed job information may be provided to the user terminal 130. As another example, the processor 230 acquires at least one target information of the user's target job information or target job information through the user terminal 130, and is related to at least one target information (or target job or job performance). It is possible to determine at least one required capability information among subject information and certification information (required for), and provide at least one required capability information to the user terminal 130. In this regard, the processor 230 may obtain learner information from the user terminal 130 (eg, a learner terminal), and provide the career-related information or the required capability information based on the obtained learner information. In this process, the processor 230 may acquire account information from the user terminal 130 and acquire learner information corresponding to the account information from a database in which the learner information is stored (eg, an educational institution DB in which the learner is studying). . The learner information may include at least one of, for example, major information, grade information, course completion information, and possession certificate information. In another example, the learner information may include at least one of information on a learner's writing/presentation thesis, information on a learner's training activity, information on volunteer activities, and information on internship activities.

According to various embodiments, the processor 230 periodically collects corporate announcement data from at least one external electronic device (for example, the external electronic devices 110 of FIG. 1 ), and in addition to NCS data, subject data, and job data. Ontology models related to occupations, jobs, and subjects can be constructed further based on corporate announcement data. In this case, the processor 230 checks the job information, job information, technical information, and qualification information requested by the company from the company announcement data, calculates the degree of association between the company demand and job, job, or education, and based on the calculated degree of association. Thus, you can relate (or respond) between jobs, jobs, or subjects to respond to corporate needs. In various embodiments, the processor 230 may share the corporate announcement data to a user with job competency based on the corporate announcement data based on the corporate announcement data. For example, the processor 230 may provide a job posting according to the company announcement data to a user (eg, a learner) terminal 130 that satisfies all requirements according to the company announcement based on the corporate announcement data.

According to various embodiments, the processor 230 learns corporate announcement data and subject data of other educational institutions from at least one external electronic device (eg, the external electronic devices 110 of FIG. 1 ), and based on the learning result. Therefore, compared to other educational institutions, it can be supported to guide the current educational institutions to the insufficient subjects (or curriculums).

According to various embodiments, the processor 230 may configure an ontology model related to a subject, a job, and a job based on other classification criteria (eg, job, job) according to the NCS data, or match a subject and a job or job. have.

According to the above-described embodiment, the competency-based curriculum management apparatus 200 provides general purpose, job, or subject-related data provided or managed by various web site servers (external electronic devices 110 of FIG. 1). Based on the classification unit (eg, competency unit) of the NCS data used as a basis, it is possible to provide a highly accurate career counseling service based on the correspondence between subject and job or occupation based on this.

In addition, according to the above-described embodiment, the competency-based curriculum management apparatus 200 may check the learner's competency, such as the learner's completed subject and possessed certificates, and provide job or job information related to the learner's competency. Accordingly, the competency-based curriculum management apparatus 200 may support a learner to search for a career path corresponding to a potential competency (or talent) other than the learner's major.

In addition, according to the above-described embodiment, the competency-based curriculum management apparatus 200 can guide the required courses or qualifications further required for the learner to have a target job or job, so that the learner can effectively perform the curriculum. Can support you to choose.

Furthermore, according to the above-described embodiment, the competency-based training course management apparatus 200 may become a human resource that meets the needs of a company or industrial site based on the company announcement data, or guide a training process for nurturing human resources. have.

3 shows a method for managing a competency-based curriculum according to an embodiment.

Referring to FIG. 3, in operation 310, the competency-based curriculum management apparatus 200 may collect NCS data, subject data, and job data.

In operation 320, the competency-based curriculum management apparatus 200 may configure an ontology model related to a job, a job, and a subject based on NCS data, subject data, and job data. For example, the competency-based curriculum management apparatus 200 uses at least one monitoring data to focus on a competency unit according to the national competency standard data, a relationship between a subject, a job and a job, or an ontology related to each job, subject, and job. You can build your model.

In operation 330, the competency-based curriculum management apparatus 200 may calculate a degree of association (eg, similarity) between the subject and the job or the job based on the ontology model, NCS data, subject data, and job data. . For example, the competency-based curriculum management apparatus 200 may calculate a degree of association between the subject for each department and the job or the job based on at least one of a Word2Vec algorithm and a Latent Semantic Analysis (LSA) algorithm. .

In operation 340, the competency-based curriculum management apparatus 200 may associate (or match) a subject and a job or a subject and a job in the ontology model based on the calculated degree of association. For example, the competency-based curriculum management apparatus 200 may associate a subject with a job or a subject having a degree of association of a specified number or higher among subjects and jobs, or between a subject and a job.

In operation 350, the competency-based curriculum management apparatus 200 may provide a career counseling service based on a correspondence relationship between a subject and a job or a subject and the job in the ontology model. For example, the competency-based curriculum management device 200 checks the instance graph through ontology inference based on the subject and job related to the competency unit in the ontology model, or the subject and job, and provides a query and response that can be processed through the instance graph. It is possible to create a service scenario that includes. The competency-based training course management apparatus 200 may provide a career counseling service according to the generated service scenario.

4 and 5 illustrate diagrams defining a correspondence relationship between monitoring data based on a capability unit, according to an exemplary embodiment.

Referring to FIG. 4, the competency-based curriculum management apparatus 200 includes subject data 420 (or data belonging to a subject domain) and occupation data ( 430) (or data belonging to the job domain) may be matched.

Referring to FIG. 5, the competency-based curriculum management apparatus 200 is based on the competency unit 510 according to the national competency standard, based on national competencies data, subject data, and job data, the job proficiency period, academic background, and major related to each job. , Field, sub-task, knowledge, skill, certification, prior job experience, and at least one of the categories to which each job belongs (large category, sub-category, sub-category, sub-category) can be matched. The competency-based training course management apparatus 200 may configure a career counseling service scenario based on the matched correspondence relationship, and provide a career counseling service based on the configured scenario.

6 shows an example of a job description among NCS data according to an embodiment according to an embodiment.

6, among NCS data, the job description is the job 610 to which each competency unit belongs, the name of each competency unit 620, certification information 630 required to perform the job of each competency unit, and knowledge technology information. Including 640. Accordingly, according to an embodiment, the competency-based curriculum management apparatus 200 may efficiently match a subject, a job, and a job based on the national job competency standard.

7 illustrates a function of inferring association of an ontology instance by the apparatus for managing a competency-based curriculum according to an embodiment.

Referring to FIG. 7, the competency-based curriculum management apparatus 200 includes tasks related to each competency unit 710, certification 720, subject 730, training period 740, and similar occupations 750. Ontology instances can be checked and career counseling services can be provided based on association inference of ontology instances. For example, the competency-based curriculum management device 200 includes tasks 710 related to the competency unit of the corresponding job for an applied software engineer job (eg, dynamic analysis model verification, interface design, software engineering application, application design). ), certification (720) (e.g. information processing engineer, information processing industry engineer, computer system application engineer, information management engineer), subject 730 (e.g. software engineering, computer science, IT service, IT technology), acquisition of related skills Associative reasoning based on ontology instances such as the training period 740 (eg, 2 years) and similar jobs 750 (eg, programmers, software developers, and developers) required for may be performed.

8 shows a correspondence relationship between corporate announcement data and job, job, and subject according to an embodiment.

Referring to FIG. 8, the competency-based training course management apparatus 200 includes tasks related to each job included in the corporate announcement based on the correspondence relationship between corporate announcement data and job, job, and education in the ontology model (blue color in FIG. 8 ). See the intersection of the solid line and the solid red line) and technology (refer to the intersection of the solid blue line and the solid green line in FIG. 8). According to various embodiments, the apparatus 200 for managing a competency-based training course may share (or guide) corporate announcement data to a user having a competency according to the corporate announcement data based on the corporate announcement data.

9, 10, and 11 illustrate examples of career counseling services by the apparatus for managing a competency-based curriculum according to an embodiment.

Referring to FIG. 9, the apparatus 200 for managing a competency-based training course according to an embodiment receives a query “what are the security-related occupations” from a user terminal (eg, the user terminal 130 of FIG. 1 ). can do. In this case, the competency-based curriculum management apparatus 200 detects the keyword "security" from the received query, and associates the job information 910 related to the keyword "security" and the keyword "complementary" based on the ontology model. The job information 920 related to the keyword “computer security” may be searched, and at least some of the searched job information 910 and 920 may be provided to the user terminal 130.

Referring to FIG. 10, the apparatus 200 for managing a competency-based curriculum according to an embodiment "I want to be a web developer. I want to be a web developer. The most important (necessary) subject" You can receive a query asking "What are they?" In this case, the competency-based curriculum management apparatus 200 detects the keyword "web developer" from the received query, and based on the ontology model, the job information 1010 and job information 1010 related to the keyword "web developer" Related competency unit tasks (1020) can be checked. The competency-based curriculum management apparatus 200 may check subject information 1030 related to the identified competency unit tasks 1020 and provide at least some of the identified subject information 1030 to the user terminal 130. have.

Referring to FIG. 11, the apparatus 200 for managing a competency-based curriculum according to an embodiment requests a query from a user terminal (for example, the user terminal 130 of FIG. 1) to "what occupations can I have in computer engineering?" You can receive it. In this case, the competency-based curriculum management apparatus 200 detects the keyword "Department of Computer Engineering" from the received query, searches for the keyword associated with the keyword "Department of Computer Engineering" and related job information based on the ontology model, The job information 1010 may be searched and provided to the user terminal 130.

Various embodiments of the present document and terms used therein are not intended to limit the technical features described in this document to specific embodiments, and should be understood to include various modifications, equivalents, or substitutes of the corresponding embodiment. In connection with the description of the drawings, similar reference numerals may be used for similar or related components. The singular form of a noun corresponding to an item may include one or more of the above items unless clearly indicated otherwise in a related context. In this document, "A or B", "at least one of A and B", "at least one of A or B", "A, B or C", "at least one of A, B and C" and "A, Each of phrases such as "at least one of B or C" may include any one of the items listed together in the corresponding one of the phrases, or all possible combinations thereof. Terms such as "first", "second", or "first" or "second" may be used simply to distinguish the component from other Order) is not limited. Some (eg, a first) component is referred to as “coupled” or “connected” to another (eg, a second) component, with or without the terms “functionally” or “communicatively”. When mentioned, it means that any of the above components may be connected to the other components directly (eg by wire), wirelessly, or via a third component.

The term "module" used in this document may include a unit implemented in hardware, software, or firmware, and may be used interchangeably with terms such as logic, logic blocks, parts, or circuits. The module may be an integrally configured component or a minimum unit of the component or a part thereof that performs one or more functions. For example, according to an embodiment, the module may be implemented in the form of an application-specific integrated circuit (ASIC).

Various embodiments of the present document are stored in a storage medium (eg, internal memory or external memory) (memory 220) that can be read by a machine (eg, capability-based training course management device 200). It may be implemented as software (eg, a program) including one or more stored instructions. For example, the processor (eg, the processor 230) of the device (eg, competency-based curriculum management apparatus 200) may call at least one command among one or more commands stored from a storage medium and execute it. This enables the device to be operated to perform at least one function according to the at least one instruction called, the one or more instructions may include code generated by a compiler or code executable by an interpreter. A storage medium that can be read by a device may be provided in the form of a non-transitory storage medium, where'non-transitory' refers to a device in which the storage medium is tangible and is a signal. It only means that it does not include (e.g., electromagnetic waves), and this term does not distinguish between a case where data is stored semi-permanently in a storage medium and a case that is temporarily stored.

According to an embodiment, a method according to various embodiments disclosed in the present document may be provided by being included in a computer program product. Computer program products can be traded between sellers and buyers as commodities. The computer program product is distributed in the form of a device-readable storage medium (e.g. compact disc read only memory (CD-ROM)), or through an application store (e.g. Play Store ^TM ) or two user devices (e.g., compact disc read only memory (CD-ROM)). It can be distributed (e.g., downloaded or uploaded) directly between, e.g. smartphones), online. In the case of online distribution, at least some of the computer program products may be temporarily stored or temporarily generated in a storage medium that can be read by a device such as a server of a manufacturer, a server of an application store, or a memory of a relay server.

According to various embodiments, each component (eg, module or program) of the above-described components may include a singular number or a plurality of entities. According to various embodiments, one or more components or operations among the above-described corresponding components may be omitted, or one or more other components or operations may be added. Alternatively or additionally, a plurality of components (eg, a module or program) may be integrated into one component. In this case, the integrated component may perform one or more functions of each component of the plurality of components in the same or similar to that performed by the corresponding component among the plurality of components prior to the integration. . According to various embodiments, operations performed by a module, program, or other component may be sequentially, parallel, repeatedly, or heuristically executed, or one or more of the operations may be executed in a different order or omitted. Or one or more other actions may be added.

Claims (10)

In the competency-based curriculum management device,
A communication circuit capable of communicating with a plurality of external electronic devices;
Memory; And
Including a processor, the processor,
Collecting National Competency Standards (NCS) data, subject data, and job data from the plurality of external electronic devices through the communication circuit,
Construct an ontology model related to occupations, jobs, and subjects based on the national job competency standard data, the subject data, and the job data,
Calculating a degree of association between the subject and the job or the job based on the ontology model, the national job competency standard data, the subject data, and the job data,
A competency-based curriculum management apparatus for matching the subject and the job or the subject and the job, which are associated with a number or more specified in the ontology model, based on the calculated correlation. The method of claim 1, wherein the processor,
Competency-based curriculum management apparatus for configuring an ontology model related to the job, the job, and the subject based on the competency unit included in the national job competency standard data. The method of claim 1, wherein the subject data,
Competency-based curriculum management device including at least one of grade information, major information, textbook information, textbook introduction information, textbook table of contents information, lecture plan information, and lecture goal information related to each subject. The method of claim 1, wherein the occupation data,
Competency-based curriculum management apparatus including at least one of job overview information, performance job information, similar name information, related job information, certification information, standard industry classification information, and standard job classification information related to each job. The method of claim 1, wherein the processor,
Obtaining company announcement data from another external electronic device through the communication circuit,
A competency-based curriculum management apparatus for configuring an ontology model related to a job, a job, and a subject based on the corporate announcement data, the national job competency standard data, the subject data, and the job data. The method of claim 1, wherein the processor,
In the ontology model, a competency-based curriculum management apparatus for providing a career counseling service based on a correspondence relationship between the subject and the job or the subject and the job to a user terminal through the communication circuit. The method of claim 6, wherein the processor,
Receiving a query related to the subject, the job, or the job from the user terminal through the communication circuit,
In the ontology model, at least one career-related information is determined among subject-related job information, subject-related job information, job-related subject information, or subject-related job information matched with the received query,
Competency-based training course management apparatus for providing the determined at least one career-related information to the user terminal. The method of claim 6, wherein the processor,
Obtaining the information of the user's courses through the user terminal,
Check the job information or job information related to the course information and the specified degree of association or higher from the memory,
Competency-based training course management apparatus for providing the verified job information or the verified job information to the user terminal. The method of claim 6, wherein the processor,
Obtaining at least one target information of the user's target job information or target job information through the user terminal,
Determine at least one required competency information among subject information and certification information related to the acquired at least one target information,
A capability-based training course management apparatus that provides the at least one requested capability information to the user terminal. In the competency-based curriculum management method using the competency-based curriculum management device,
Collecting national job competency standard data, subject data, and job data from a plurality of external electronic devices;
Constructing an ontology model related to a job, a job, and a subject based on the national job competency standard data, the subject data, and the job data;
Calculating a degree of association between the subject and the job or the job based on the ontology model, the national job competency standard data, the subject data, and the job data; And
Matching the subject and the job, or the subject and the job, which are associated with a number or more specified in the ontology model based on the calculated degree of association
Competency-based curriculum management method, including.

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