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AI를 활용한 대학생 진로 조언 시스템 모델 및 데이터 수집과 융합에 대한 연구

A Study on the Data Collection and Convergence of Career Advisor System Using AI

  • 김종율 (한성대학교 스마트융합컨설팅) ;
  • 노광현 (한성대학교 IT융합공학부)
  • Kim, Jong-yul (Division of Smart Convergence Consulting, Hansung University) ;
  • Ro, Kwang-hyun (Division of IT Convergence Engineering, Hansung University)
  • 투고 : 2018.12.24
  • 심사 : 2019.02.20
  • 발행 : 2019.02.28

초록

본 연구는 국내 대학생들의 가장 큰 고민인 진로 문제에 대한 원인과 이를 해결하기 위한 국내 외 대학의 정보기술을 활용한 문제해결 사례 연구와 진로 조언을 위한 데이터 수집 유형 및 수집방법 연구를 통해 AI를 활용한 대학생 진로조언 시스템 모델을 제안하고자 한다. 데이터 분석 및 AI와 같은 정보기술을 활용하여 대학생들의 진로 문제 해결을 위해서는 조언과 학습을 위한 데이터의 수집이 가장 중요하다. 그러나 대학들 역시 학생들에게 진로 문제에 대해 조언할 수 있는 내부 데이터의 부족으로 정보기술을 활용한 진로 문제 해결방법에 대한 연구가 활발히 진행되지 못하고 있다. 본 논문에서는 대학생들의 진로 조언을 위해 공공 데이터와 대학 내부 민간기관 지자체에서 수집 가능한 진로 조언 데이터의 유형과 수집 방법 및 활용 방안에 대한 연구와 이를 활용하여 대학생 진로조언 시스템 모델을 제안하고자 한다.

The purpose of this study is to investigate the causes of career problems, which are the biggest problems of Korean university students, and to solve them by using case studies of domestic and global universities, I would like to suggest a career advisor system model for college students. It is most important to collect advice and learning data to solve the career problems of college students by utilizing information technology such as data analysis and AI. Research has not been actively pursued because the university has very limited internal data to advise on career problems. In this paper, we study the data types and methods of college students' career advice, and propose a career advisor counseling system for college students.

키워드

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Fig. 1. ASU’s online advising system

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Fig. 2. SKKU’s kingobot

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Fig. 3. AI use career advice and data processing model

Table 1. Worknet OpenAPI provided list

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Table 2. Search job information (worknet.go.kr)

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Table 3. Data collection for developing student job competency

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Table 4. Collect university internal data

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Table 5. Advice system Q&A data example

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Table 6. Career Advisor System Layer

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Table 7. career Advisor System simulation process

DJTJBT_2019_v17n2_177_t0007.png 이미지

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