KR102343385B1 - 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

An apparatus for managing a competency-based training process according to an embodiment disclosed in this 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 job data from the plurality of external electronic devices through the communication circuit, and the national competency standard data; Configure an ontology model related to occupation, job, and subject based on the subject data and the occupation data, and the subject and the subject based on the ontology model, the national competency standard data, the subject data and the occupation data A degree of association between a job or the job may be calculated, and based on the calculated degree of relevance, the subject and the job or the subject and the job related to more than a specified value in the ontology model may be matched.

Description

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

Various embodiments disclosed in this document are related to machine learning technology for career exploration or training course management.

Recently, education is not limited to imparting simple knowledge, but aims to nurture talents desired by companies or society. Accordingly, educational institutions or professors are trying to analyze the human resources desired by companies or industries and apply education corresponding to them.

Korean Patent Publication No. 10-2018-0041478

However, due to the rapid change of jobs and jobs due to paradigms such as the 4th industrial revolution, it may be difficult for small individuals to analyze in real time the human resources desired by a company or industry based on national data. Therefore, there is a need for an automation system to analyze the requirements (talent image) desired by rapidly changing companies or industrial sites from various angles and apply them to the educational process.

Various embodiments disclosed in this document may provide an apparatus and method for managing a socially customized competency-based training process based on an ontology and deep learning that can identify and guide job competency required for a user based on machine learning.

An apparatus for managing a competency-based training process according to an embodiment disclosed in this 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 job data from the plurality of external electronic devices through the communication circuit, and the national competency standard data; Configure an ontology model related to occupation, job, and subject based on the subject data and the occupation data, and the subject and the subject based on the ontology model, the national competency standard data, the subject data and the occupation data A degree of association between a job or the job may be calculated, and based on the calculated degree of relevance, the subject and the job or the subject and the job related to more than a specified value in the ontology model may be matched.

In addition, the competency-based training process management method according to an embodiment disclosed in this document, the operation of 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 between the subject and the job or the subject and the job related to a numerical value or more specified in the ontology model based on the calculated degree of relevance.

According to various embodiments disclosed in this document, based on machine learning, it is possible to identify and guide the job competency required for the user. In addition, various effects directly or indirectly identified through this document may be provided.

1 illustrates an implementation environment of an apparatus for managing a competency-based educational process according to an embodiment.
2 is a diagram illustrating a configuration of an apparatus for managing a competency-based educational process according to an exemplary embodiment.
3 illustrates a competency-based training process management method according to an embodiment.
4 and 5 are diagrams in which a correspondence relationship between monitoring data based on a capability unit is defined according to an embodiment.
6 shows an example of a job description among national job competency standard data according to an embodiment.
7 is a diagram illustrating an associative reasoning function of an ontology instance by an apparatus for managing a competency-based curriculum according to an embodiment.
8 illustrates a correspondence relationship between company announcement data and jobs, occupations, and subjects according to an embodiment.
9, 10, and 11 show examples of career counseling services by the competency-based training course management apparatus 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 illustrates an implementation environment of an apparatus for managing a competency-based educational process according to an embodiment.

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

Competency-based curriculum management device 120 collects national job competency standard data (hereinafter referred to as “NCS data”), subject data and job data through websites 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 occupations, jobs, and subjects may 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 the ontology model, NCS data, subject data, and job data, and based on the calculated degree of association, the ontology model may relate the subject and the job or the subject and the job.

The competency-based educational process management apparatus 120 may provide a career counseling service to the user terminal 130 based on a correspondence between subjects and jobs or subjects and jobs in the ontology model. For example, the competency-based curriculum management device 120 receives a subject, job, or job-related query from the user terminal 130, and subject-related job information and subject-related information corresponding to the received query based on the ontology model. Determining at least one career-related information (eg, vocational information corresponding to a competency, curriculum information required for a target occupation) of vocational information, vocational-related subject information, or subject-related vocational information, and using the determined at least one career-related information It may 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 company announcement data. The NCS data may include, for example, at least one of classification system information defined in the national job competency standard, job description information, and capability description information. The subject data may include, for example, grade information related to each subject, textbook information (eg, textbook name), major information (eg, major name), textbook introduction information, textbook contents information, and syllabus information (eg, syllabus) ) and at least one of lecture goal information. The job data may include, for example, job summary information related to each job (eg, job summary of each job worker), job information to be performed (eg, job performed by each job worker), and similar name information (eg, each job). name information similar to ), related job information (eg job information related to each job), certification information (eg, certification information useful or required for each job), standard industry classification information, and standard job classification information (eg Korean standard job information) classification and Korea Employment Occupation Classification). For example, each of the external electronic devices 110 may be a web service server that provides at least one piece of monitoring data through a web site. Each of the external electronic devices 110 includes a website server that discloses national standard job competency data, a public job search website server (eg, Career Net), a private job search website server (eg, human) and a website server that discloses the classification information. It may include at least one of web site servers (eg, Statistics Office server, Ministry of Employment and Labor server, Ministry of Education server).

According to an embodiment, the user terminal 130 requests a career counseling service from the competency-based training course management device 120 through a website or an application program provided by the competency-based training course management device 120, and A user interface screen related to a career counseling service may be provided from the educational process management device 120 , and the interface screen may be displayed. The user terminal 130 is a computing device such as a PC, a notebook computer, a smart phone, a tablet, and a wearable computer, and a web/mobile site related to the competency-based training course management device 120 . It may refer to any terminal device capable of installing and executing a connection or service-only application. The user terminal 130 may be a computing device used by at least one of a learner and 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, in addition to NCS data, curriculum data, and job data, corporate announcement data Based on this, an ontology model related to occupations, jobs, and subjects can be constructed. In this case, the competency-based training process management device 120 checks the company required job information, job information, technical information and qualification information from the company announcement data, calculates the correlation between the company demand and job, job or education, and calculates Based on the calculated computational chart, it is possible to relate occupations, jobs, or subjects to respond to corporate demands in the ontology model.

According to the above-described embodiment, the competency-based training process management device 120 may diagnose the user's current competency (eg, certification information, completed subjects) and guide the user's more necessary competency information for the desired job or job. have.

Also, according to the above-described embodiment, the competency-based training course management apparatus 120 may provide a career counseling service according to actual demand by matching between occupations, jobs, or subjects to respond to corporate demand.

2 is a diagram illustrating a configuration of an apparatus for managing a competency-based educational process according to an exemplary embodiment.

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

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

The memory 220 may store various data used by at least one component (eg, the processor 230 ) of the apparatus 200 for managing the competency-based training process. Data may include, for example, input data or output data for software and related instructions. 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 non-volatile memory.

The processor 230 may control at least one other component (eg, a hardware or software component) of the competency-based training process management apparatus 200 as it executes at least one instruction, and performs various data processing or calculations. can be done The processor 230 may include, for example, a central processing unit (CPU), a graphic processing unit (GPU), a microprocessor, an application processor, an application specific integrated circuit (ASIC), or 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 results, it is possible to relate jobs and jobs, the subjects and jobs or subjects and jobs in the ontology model, and provide career counseling services based on the correspondence between subjects and jobs or jobs 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 the plurality of external electronic devices 110 through the communication circuit 210 (eg, : At least one of crawling or scraping can be performed). The NCS data may include, for example, at least one of classification system information defined in the national job competency standard, job description information, and capability description information. The subject data may include, for example, grade information related to each subject, major information (eg, major name, major university), textbook information (eg, textbook name), textbook introduction information, textbook table of contents information, syllabus information (eg, : syllabus) and syllabus goal information. The job data may include, for example, job summary information related to each job (eg, job summary of each job worker), job information to be performed (eg, job performed by each job worker), and similar name information (eg, each job). name information similar to ), related job information (eg job information related to each job), certification information (eg, certification information useful or required for each job), standard industry classification information, and standard job classification information (eg Korean standard job information) classification and Korea Employment Occupation 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 configure an ontology model related to a relationship between occupations, subjects, and jobs based on a capability unit according to the NCS data by using the monitoring data. As another example, the processor 230 may configure an ontology model for each job, subject, and job based on a capability unit according to the NCS data by using the monitoring data. The job may be a set of similar (or related more than a specified degree of similarity) jobs. The job may include a series of tasks and duties. The competency unit may be a sub-unit of a job according to the national competency standard classification. Each competency unit can be composed of competency unit elements (performance criteria, knowledge technology attitude) corresponding to each competency unit, application scope and work situation, evaluation guidelines, and basic vocational competency. In this regard, the processor 230 analyzes at least one of the characteristics of the classification system according to the national job competency standard, the job description, and the capability description to check the structure of job-related data, and a competency unit (or task) according to the national job competency standard. ), an ontology model that defines the relationship between ontology instances can be constructed.

According to an embodiment, the processor 230 calculates a degree of association (eg, similarity) between a subject and a job or a job based on the ontology model, NCS data, subject data, and job data, and generates an ontology based on the calculated degree of association. In the model, subjects and occupations or subjects and jobs can be related. For example, the processor 230 may calculate a degree of association between a subject and a profession or subject based on the capability unit, and may relate the subject and a profession or subject in the ontology model based on the calculated association degree. 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 a Word2Vec algorithm and a Late Semantic Analysis (LSA) 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 ( or grouped). As another example, the processor 230 calculates a degree of similarity (eg, cosine similarity) between a subject and a job or a subject and a job, and creates an ontology between a subject and a job or a subject and a job in which the calculated similarity is greater than or equal to a specified value (eg, 0.6) can be related in the model.

In this regard, the processor 230 generates a job or job list related to subject by department, and provides the generated job or job list to the user terminal 130 (eg, a professor terminal) through the communication circuit 210 . can The processor 230 may obtain the job or the job selected by the user terminal 130 , 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 correlation between departments and jobs for some departments among departments (eg, a department in which a job is selected), and for the other departments among departments (eg, a department in which a job is selected), subject by department The relationship between and occupation can be calculated. The processor 230 may use at least one of the Doc2Vec algorithm and the LSA algorithm to check the degree of association between some departments and the rest of the department, and check the degree of association between the job and the job based on the degree of association between some departments and the other departments. .

According to an embodiment, the processor 230 may provide a career counseling service to the user terminal 130 based on a correspondence between subjects and jobs or subjects and jobs in the ontology model. In one embodiment, the processor 230 checks the instance graph as it performs ontology inference based on subjects and jobs or subjects and jobs related to the capability unit in the ontology model, and includes queries and responses 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 ontology inference, At least one of the subject-related job information, the job-related subject information, and the 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 information on the subjects completed by the user through the user terminal 130 , and confirms job information or job information related to the subject information and the specified degree of relevance or more 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 of target job information or target job information of the user through the user terminal 130 , and is related to the at least one target information (or performs a target job or job) It is possible to determine at least one required competency information among subject information and certification information (required for ), and provide at least one required competency 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 competency information based on the obtained learner information. In this process, the processor 230 obtains account information from the user terminal 130, and obtains learner information corresponding to the account information from a database in which learner information is stored (eg, an educational institution DB where the learner is learning). . The learner information may include, for example, at least one of major information, grade information, completed subject information, and possessed certificate information. The learner information may include, for example, at least one of information on a student's writing/presentation thesis, information on a learner's training activity, volunteer activity information, and internship activity information.

According to various embodiments, the processor 230 periodically collects company announcement data from at least one external electronic device (eg, the external electronic devices 110 of FIG. 1 ), and in addition to NCS data, subject data, and job data, An ontology model related to occupations, jobs, and subjects can be constructed further based on company announcement data. In this case, the processor 230 checks the company required job information, job information, technical information and qualification information from the company announcement data, calculates a degree of association between the company demand and job, job or education, and based on the calculated degree of association to relate (or respond) between occupations, jobs, or subjects to respond to corporate needs. In various embodiments, the processor 230 may share the company announcement data with users with job competency according to the company announcement data based on the company announcement data. For example, the processor 230 may provide a job advertisement according to the company announcement data to the user (eg, learner) terminal 130 having all the requirements according to the corporate 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 Thus, compared to other educational institutions, it can support to guide the subjects (or curriculum) that the current educational institution lacks.

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

According to the above-described embodiment, the competency-based curriculum management device 200 general-purposes job, 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, ability unit) of NCS data used as

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

In addition, according to the above-described embodiment, the competency-based curriculum management device 200 can guide the required subjects or qualifications more required in order for the learner to have a target job or job, so that the learner can efficiently learn the curriculum can assist you in choosing

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

3 illustrates a competency-based training process management method 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 occupations, duties, and subjects based on NCS data, subject data, and occupation data. For example, the competency-based training process management apparatus 200 uses at least one monitoring data to create an ontology related to subjects, occupations and jobs, or each job, subject and job centering on a competency unit according to the national job competency standard data. model can be constructed.

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 job based on the ontology model, NCS data, subject data, and the job data. . For example, the competency-based curriculum management apparatus 200 may calculate the 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 relate (or match) subjects and jobs or subjects and jobs in the ontology model based on the calculated degree of association. For example, the competency-based curriculum management apparatus 200 may relate subjects and occupations or subjects and jobs having a degree of correlation greater than or equal to a specified value among subjects and occupations or subjects and duties.

In operation 350, the competency-based curriculum management apparatus 200 may provide a career counseling service based on a correspondence between subjects and occupations or between subjects and jobs in the ontology model. For example, the competency-based curriculum management device 200 checks the instance graph through ontology inference based on subjects and occupations or subjects and jobs related to competency units in the ontology model, and queries and responses that can be processed through the instance graph. You can create service scenarios that include The competency-based training course management apparatus 200 may provide a career counseling service according to the generated service scenario.

4 and 5 are diagrams in which a correspondence relationship between monitoring data based on a capability unit is defined according to an embodiment.

Referring to FIG. 4 , the competency-based curriculum management apparatus 200 includes the subject data 420 (or data belonging to the subject domain) and job data (or data belonging to the subject domain) centered on the competency unit 411 according to the NCS data 410 ( 430) (or data belonging to the job domain) may be matched.

Referring to FIG. 5 , the competency-based training process management device 200 is based on the national competency unit 510 according to the national competency standard, from the national job competency data, subject data, and job data related to each job job skill period, academic background, major , field, detailed work, knowledge, skills, qualifications, prior work experience, and at least one of the classifications to which each task belongs (large category, medium category, small category, and subcategory) can be matched. The competency-based training course management apparatus 200 may configure a career counseling service scenario based on the matched correspondence, and may 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.

Referring to FIG. 6 , the job description of the NCS data includes the job 610 to which each competency unit belongs, the name of each competency unit 620 , the qualification information 630 and knowledge technology information required to perform the job of each competency unit. (640). Accordingly, according to an embodiment, the competency-based educational process management apparatus 200 may efficiently match subjects, jobs, and occupations based on the national job competency standard.

7 is a diagram illustrating an associative reasoning function of an ontology instance by an apparatus for managing a competency-based curriculum according to an embodiment.

Referring to FIG. 7 , the competency-based training process management apparatus 200 includes tasks 710 , certifications 720 , subjects 730 , training periods 740 and similar occupations 750 related to each competency unit. It is possible to identify ontology instances and provide a career counseling service based on inferences related to the ontology instances. For example, the competency-based training process management apparatus 200 performs tasks 710 (eg, dynamic analysis model verification, interface design, software engineering utilization, application design) related to the competency unit of the job for the applied software engineer job. ), certification (720) (e.g. information processing engineer, information processing industry engineer, computer system application engineer, information management engineer), subject (730) (eg software engineering, computer science, IT service, IT technology), acquisition of related skills It is possible to perform associative inference based on an ontology instance such as the training period 740 (eg, 2 years) and similar occupations 750 (eg, programmer, software developer, developer) required for .

8 illustrates a correspondence relationship between company announcement data and jobs, occupations, and subjects according to an embodiment.

Referring to FIG. 8 , the competency-based training process management device 200 performs tasks related to each job included in the corporate announcement based on the correspondence between the corporate announcement data and the job, job, and education in the ontology model (blue in FIG. 8 ). See the intersection of the solid line and the solid red line) and the technique (refer to the intersection of the solid blue line and the solid green line in FIG. 8). According to various embodiments, the capability-based training process management apparatus 200 may share (or guide) corporate announcement data to users with capabilities according to the corporate announcement data based on the corporate announcement data.

9, 10, and 11 show examples of career counseling services by the competency-based curriculum management apparatus according to an embodiment.

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

Referring to FIG. 10 , the competency-based training process management apparatus 200 according to an embodiment receives a message from a user terminal (eg, the user terminal 130 of FIG. 1 ) "I want to become a web developer. The most important (necessary) subject What have you heard?" In this case, the competency-based curriculum management apparatus 200 detects the keyword "web developer" from the received query, and job information 1010 and job information 1010 related to the keyword "web developer" based on the ontology model. The related competency unit tasks 1020 may 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 a portion of the identified subject information 1030 to the user terminal 130 . have.

Referring to FIG. 11 , the competency-based educational process management apparatus 200 according to an embodiment receives a query from a user terminal (eg, the user terminal 130 of FIG. 1 ) "what jobs can I have in computer science?" can receive In this case, the competency-based curriculum management apparatus 200 detects the keyword "Computer Engineering Department" from the received query, searches the related keyword and related job information of the keyword "Computer Engineering Department" based on the ontology model, and confirms the related The job information 1010 may be searched and provided to the user terminal 130 .

The various embodiments of this document and terms used therein are not intended to limit the technical features described in this document to specific embodiments, but it should be understood to include various modifications, equivalents, or substitutions of the embodiments. In connection with the description of the drawings, like reference numerals may be used for similar or related components. The singular form of the noun corresponding to the item may include one or more of the item, unless the relevant context clearly dictates otherwise. As used herein, "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 the phrases such as "at least one of B, or C" may include any one of, or all possible combinations of, items listed together in the corresponding one of the phrases. Terms such as “first”, “second”, or “first” or “second” may simply be used to distinguish the component from other components in question, and may refer to components in other aspects (e.g., importance or order) is not limited. It is said that one (eg, first) component is "coupled" or "connected" to another (eg, second) component, with or without the terms "functionally" or "communicatively". When referenced, it means that one component can be connected to the other component directly (eg by wire), wirelessly, or through a third component.

As used herein, the term “module” may include a unit implemented in hardware, software, or firmware, and may be used interchangeably with terms such as, for example, logic, logic block, component, or circuit. A module may be an integrally formed part or a minimum unit or a part of the part 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) readable by a machine (eg, competency-based training process management apparatus 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, the competency-based curriculum management apparatus 200 ) may call at least one of the one or more instructions stored from the 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 a code generated by a compiler or a code executable by an interpreter. A device-readable storage medium may be provided in the form of a non-transitory storage medium, where 'non-transitory' is a device in which the storage medium is tangible, and a signal (eg electromagnetic waves) is not included, and this term does not distinguish between cases where data is stored semi-permanently on a storage medium and cases where it is temporarily stored.

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

According to various embodiments, each component (eg, a module or a program) of the above-described components may include a singular 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 a 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 identically or similarly to those 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 are executed sequentially, in parallel, repeatedly, or heuristically, or one or more of the operations are executed in a different order, or omitted. or one or more other operations may be added.

Claims (10)

In the competency-based training process management device,
a communication circuit capable of communicating with a plurality of external electronic devices;
Memory; and
A processor comprising:
Collecting National Competency Standards (NCS) data, subject data, job data and company announcement data from the plurality of external electronic devices through the communication circuit,
On the basis of the national job competency standard data, the subject data, the job data, and the company announcement data to construct an ontology model related to a job, a job, and a subject,
Calculating the degree of association between the subject and the job or job based on the ontology model, the national job competency standard data, the subject data, the job data, and the company announcement data,
The processor acquires the job or job selected by the user terminal, and calculates the degree of association between the subject for each department and the selected job or job, and the degree of correlation between the subject and the job for each department for some departments in which the job is selected among a plurality of departments After calculating the degree of correlation between subjects and occupations by department for the remaining departments in which occupations are selected among a plurality of departments, the degree of association between some departments and the remaining departments is calculated based on at least one of the Doc2Vec algorithm and the LSA algorithm and calculating the degree of relevance between occupation and job based on the degree of relevance between some departments and the rest of the departments,
Based on the calculated degree of relevance, matching the subject and the job or the subject and the job related to more than the specified number in the ontology model, but in the ontology model, the correlation between the company announcement data and the job, job, and subject Based on the intersection of the connecting line corresponding to each job included in the corporate announcement data and the connecting line corresponding to the job data and job data, the related work is provided, and the connecting line and job corresponding to each job included in the corporate announcement data provide the relevant technology through the intersection of the connecting line corresponding to the description of the data and job data;
The processor constructs a job ontology model, a job ontology model, and a subject ontology model related to the job, the job, and the subject based on each competency unit included in the national job competency standard data, wherein the capability unit is in each capability unit Consists of the corresponding competency unit element, scope of application and work situation, evaluation guidelines and basic vocational competency;
The processor analyzes the characteristics of the classification system according to the National Competency Standards data, job descriptions and capability descriptions to confirm the structure of job-related data, and focuses on competency units according to the National Competency Standards data, including qualifications, subjects, training periods, and Constructs an ontology model that defines the relationship between ontology instances defined by similar occupations,
In the ontology model, an instance graph is obtained by performing associative reasoning of ontology instances based on subjects and jobs or subjects and jobs related to competency units, and a service scenario including queries and responses that can be processed through the instance graph is generated. A competency-based curriculum management device. delete The method according to claim 1, The subject data,
A competency-based curriculum management device including at least one of grade information, major information, textbook information, textbook introduction information, textbook table of contents information, syllabus information, and syllabus information related to each subject. The method according to claim 1, The job data,
Competency-based curriculum management device including at least one of job summary information, performance job information, similar name information, related job information, certification information, standard industry classification information, and standard occupation classification information related to each job. delete The method according to claim 1, wherein the processor,
A competency-based educational process management apparatus for providing a career counseling service based on a correspondence between the subject and the job or the subject and the job in the ontology model to the user terminal through the communication circuit. The method according to 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,
determining at least one career-related information from among subject-related job information, subject-related job information, job-related subject information, or subject-related job information matched to the received query in the ontology model;
Competence-based training course management apparatus for providing the determined at least one career-related information to the user terminal. The method according to claim 6, wherein the processor,
Obtaining the user's completed course information through the user terminal,
Check the job information or job information related to the completed subject information and the specified degree of relevance or more from the memory,
Competence-based training course management device for providing the identified job information or the identified job information to the user terminal. The method according to claim 6, wherein the processor,
acquiring at least one of target job information or target job information of the user through the user terminal;
determining at least one required competency information among subject information and certification information related to the obtained at least one target information,
Competency-based training process management apparatus that provides the at least one required competency information to the user terminal. In the competency-based training process management method by the competency-based training process management device,
collecting national job competency standard data, subject data, job data, and company announcement 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, the job data, and the company announcement data;
calculating a degree of association between the subject and the job or job based on the ontology model, the national job competency standard data, the subject data, the job data, and the company announcement data; and
An operation of matching between the subject and the job or the subject and the job related to more than a specified value in the ontology model based on the calculated degree of relevance
including,
The operation of constructing the ontology model is,
A job ontology model, a job ontology model, and a subject ontology model related to the job, the job, and the subject are configured based on each competency unit included in the national job competency standard data, wherein the capability unit is a capability corresponding to each capability unit It is composed of unit elements, application scope and work situation, evaluation guidelines and basic vocational competency,
The structure of job-related data is confirmed by analyzing the characteristics of the classification system according to the national competency standard data, the job description and the capability description, and the competency unit according to the national competency standard data is centered on qualifications, subjects, training period, and similar occupations. Configure the ontology model that defines the relationship between the defined ontology instances,
In the ontology model, an operation of obtaining an instance graph by performing associative inference of ontology instances based on subjects and jobs or subjects and jobs related to the unit of competency; and
and generating a service scenario including queries and responses that can be processed through the instance graph,
The operation of calculating the degree of association is
Obtain the job or job selected by the user terminal, calculate the degree of association between the subject for each department and the selected job or job, and calculate the degree of correlation between the subject and the job for each department for some departments in which the job is selected among a plurality of departments, , after calculating the degree of association between subjects and occupations by department for the remaining departments in which the profession is selected among the plurality of departments, the degree of association between the some departments and the remaining departments is calculated based on at least one of the Doc2Vec algorithm and the LSA algorithm, Calculate the degree of association between occupations and jobs based on the degree of association between some departments and other departments;
The matching operation is
Based on the correlation between the corporate announcement data and jobs, occupations and subjects in the ontology model, related work through the intersection of the connecting line corresponding to each job included in the corporate announcement data and the connecting line corresponding to the job of the job data and job data A competency-based curriculum management method for providing and providing related skills through the intersection of a connecting line corresponding to each job included in the company announcement data and a connecting line corresponding to the description of job data and job data.

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