메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색
질문

논문 기본 정보

자료유형
학술저널
저자정보
서영재 (연세대학교) 김지훈 (한성대학교)
저널정보
한국체육과학회 한국체육과학회지 한국체육과학회지 제30권 제3호 (인문사회과학 편)
발행연도
2021.6
수록면
861 - 874 (14page)
DOI
10.35159/kjss.2021.6.30.3.861

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색
질문

초록· 키워드

오류제보하기
The purpose of this study was to provide meaningful data on senior citizens" participation in dance during academic research in the field of physical education in Korea, the research was conducted using the paper search site of KISS, a Korean academic information service, to search for research with “old people” and “dance” in the title of the paper, and collected the year of publication, names of academic societies, and titles. Finally, 104 papers were selected and content analysis and network text analysis were conducted. The results are as follows. By year, research on elderly people"s participation in dance was the most active in 2017 and 2018, and the Korean Dance Science Association showed the most research results in academic journals. As a result of analyzing the frequency according to the research method, it was shown in order of quantitative research, literature study, mixed study, and qualitative study. As a result of frequency analysis of keywords in the title of the paper, “old people” and “women old people” were mentioned the most, followed by “Korean dance,” “living dance,” “participation,” “dance” and “program.” As a result of the network text analysis, the keywords “dance”, “elderly”, “program”, “participation”, “Korean dance”, and “leisure” play a central role, and it can be interpreted that studies related to these keywords have been actively conducted. In conclusion, senior citizen dance research was being conducted based on major academic journals, and cross-study between the two clusters will need to be actively conducted.

목차

Abstract
Ⅰ. 서론
Ⅱ. 연구방법
Ⅲ. 결과 및 논의
Ⅳ. 결론 및 제언
참고문헌

참고문헌 (36)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0

UCI(KEPA) : I410-ECN-0101-2021-692-001861905