본 연구에서는 대한민국 난민법 제정과 시행에 따라 현 시점의 난민아동 생활실태를 짚 어보고 그 대안으로서 교육적인 방안을 모색하고자 하였다. 연구 목적의 효과적인 달성을 위하여 난민아동 교육관여자 12명과 면담을 실시하였고, 면담자료와 관련 문헌 연구를 바 탕으로 근거이론을 통해 접근하는 질적 연구를 수행하였다. 분석 결과 난민의 삶 시작, 상 실감, 순간을 살기, 심신의 스트레스, 인식부족, 정책미비, 불편한 주변세계에 대한 반응, 사 람에 대한 그리움, 교육적 접근, 사회적 지원, 회피, 긍정의 탐색, 심적 재정착, 현재와 미래 간 가교 설정, 적응과 공존, 부적응 시나리오의 16개 범주를 도출하였고 이를 토대로 인과 적 조건, 현상, 맥락, 중재적 조건, 전략, 결과로 이어지는 국내 난민아동의 생활실태와 교 육 방안에 관한 이론적 패러다임 모형을 구성하였다. 핵심범주는 ‘순간을 사는 삶에서 희망 적 존재감을 발견하고 공존의 삶으로 나아가기’로 설정하였으며 이와 관련하여 연구의 분 석 결과를 중심으로 국내 난민아동의 교육 방안에 대하여 개인, 학교, 기관, 사회 각 영역 의 실천 방안을 제안하였다.

Purpose - In this paper, we categorize and segment the 28 national universities in South Korea and measure the degree of dissimilarity (or similarity) between pairs of ones by using dissimilarity distance matrix and cluster analysis, respectively, based on the seven quantitative evaluation of educational conditions (percentage of small-scale courses, percentage of lecture by the faculty, collection of books per student, material purchase per student, percentage of building capacity, percentage of real estate capacity and rate of accommodation) in 2015. In addition, multidimensional scaling (MDS) techniques can obtain visual representation for exploring patterns of proximities among 28 national universities based on seven attributes of educational conditions. Research design, data, and methodology - This work is carried out by the 2015 Announcement of University Information, which is provided by Ministry of Education in South Korea and utilized by multivariate analyses with CLUSTER, PROXIMITIES and ALSCAL modules in IBM SPSS 23.0. Results - We make certain that 28 national universities can be categorized into five clusters which have similar traits by applying two-stage cluster analysis. MDS is utilized to perform positioning of grouped places of cluster and 28 national universities joining every cluster. Conclusions - Both types and traits of each national university can be relatively assessed and practically utilized for each university competitiveness based on underlying results.

dissimilarity (or similarity) between pairs of ones by using dissimilarity distance matrix and cluster analysis, respectively, based on the seven quantitative evaluation of educational conditions (percentage of small-scale courses, percentage of lecture by the faculty, collection of books per student, material purchase per student, percentage of building capacity, percentage of real estate capacity and rate of accommodation) in 2015. In addition, multidimensional scaling (MDS) techniques can obtain visual representation for exploring patterns of proximities among 28 national universities based on seven attributes of educational conditions. Research design, data, and methodology - This work is carried out by the 2015 Announcement of University Information, which is provided by Ministry of Education in South Korea and utilized by multivariate analyses with CLUSTER, PROXIMITIES and ALSCAL modules in IBM SPSS 23.0. Results - We make certain that 28 national universities can be categorized into five clusters which have similar traits by applying two-stage cluster analysis. MDS is utilized to perform positioning of grouped places of cluster and 28 national universities joining every cluster. Conclusions - Both types and traits of each national university can be relatively assessed and practically utilized for each university competitiveness based on underlying results.