• Title/Summary/Keyword: 진로산업

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Influencing Factors on Intention of Career Choice toward Mental Health Nurses among Senior Nursing Students (졸업을 앞둔 간호대학생의 정신간호사에 대한 진로선택 의도 영향요인)

  • Jinyoung, Lee;Moonhee, Gang
    • Journal of Industrial Convergence
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    • v.21 no.2
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    • pp.53-59
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    • 2023
  • The purpose of this study was to identify the influencing factors on the intention of career choice toward psychiatric nurses among nursing students. The participants were 261 senior nursing students from five schools in D and W metropolitan cities. Data were collected from August 1 to 20, 2019, and analyzed by descriptive statistics, t-test, Pearson Correlation Coefficient, and multiple regression using SPSS 26.0 program. In the multiple regression analysis, age (𝛽=.13, p=.048), satisfaction of mental health nursing practicum (𝛽=.16, p=.035) were significant factors on intention of career choice toward mental nurses with 10.3% of total explanatory power. Therefore, it is necessary to improve the practice satisfaction of nursing students by improving the practice environment and clinical nursing instructors' teaching competence. In addition, an further study was proposed that can identify various variables that affect the career choice of mental health nurses by expanding the subjects.

The Effects of Civic Consciousness and Sense of Community on Happiness in Adolescent: Mediating Effects of Career Desision (중학생의 시민의식과 공동체의식이 행복감에 미치는 영향: 진로결정의 매개효과)

  • Myung-Ha Lee;Ouk-Sun Cho
    • Journal of Industrial Convergence
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    • v.21 no.5
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    • pp.97-107
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    • 2023
  • The purpose of this study was to provide basic data to improve happiness by verifying the mediating effect of career decision in the relationship between civic consciousness, community consciousness, career decision, and happiness of middle school students. As for the analysis data, the "2020 Gen Z Teenage Values Survey" data surveyed by the Korea Youth Policy Institute was used. Among the survey subjects, 2,703 middle school students who met the purpose of this study were sampled and analyzed using the SPSS WIN 25.0 program. For the analysis method, frequency analysis, descriptive statistical analysis, correlation analysis, and PROCESS MACRO Model Number 4 were used to verify the mediating effect, and indirect effects and significance were analyzed by applying the Bootstrap technique. The results of the study showed, first, that middle school students' sense of citizenship and community had a positive effect on happiness. Second, in the relationship between civic consciousness and happiness, career decision had a partial mediating effect. Third, in the relationship between community consciousness and happiness, career decision had a partial mediating effect. In other words, it is meaningful in that it presented policy alternatives and practical programs to improve the happiness of middle school students.

Artificial Intelligence-Based High School Course and University Major Recommendation System for Course-Related Career Exploration (교과 연계 진로 탐색을 위한 인공지능 기반 고교 선택교과 및 대학 학과 추천 시스템)

  • Baek, Jinheon;Kim, Hayeon;Kwon, Kiwon
    • KIPS Transactions on Software and Data Engineering
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    • v.10 no.1
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    • pp.35-44
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    • 2021
  • Recent advances in the 4th Industrial Revolution have accelerated the change of the working environment, such that the paradigm of education has been shifted in accordance with career education including the free semester system and the high school credit system. While the purpose of those systems is students' self-motivated career exploration, educational limitations for teachers and students exist due to the rapid change of the information on education. Also, education technology research to tackle these limitations is relatively insufficient. To this end, this study first defines three requirements that education technologies for the career education system should consider. Then, through data-driven artificial intelligence technology, this study proposes a data system and an artificial intelligence recommendation model that incorporates the topics for career exploration, courses, and majors in one scheme. Finally, this study demonstrates that the set-based artificial intelligence model shows satisfactory performances on recommending career education contents such as courses and majors, and further confirms that the actual application of this system in the educational field is acceptable.