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

논문 기본 정보

자료유형
학술저널
저자정보
엄지영 (삼육대학교) 황혜미 (삼육대학교)
저널정보
한국무역연구원 무역연구 무역연구 제19권 제2호
발행연도
2023.4
수록면
131 - 146 (16page)

이용수

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

초록· 키워드

오류제보하기
Purpose – The purpose of this study is to examine the effectiveness of industry-university linked capstone design classes within the humanities and social sciences. Also, sharing the result of the study further encourages capstone design classes within the humanities and social sciences. Design/Methodology/Approach – An importance-satisfaction survey was conducted in the two classes of 2022. After explaining the purpose of the survey and data utilization plan to a total of 27 students, the questionnaire was distributed, and 24 responses were used for analysis. In addition, at the end of each semester, focus group interviews were conducted for participating students. Findings – As a result of the IPA analysis, areas of maintaining superiority, maintaining the status quo, areas of major improvement, and areas of low priority were identified. In the area of ​​maintaining superiority, many items corresponding to the unique characteristics of capstone design classes, such as problem-based approach and creative exploration, were included. In the areas of focus improvement, there were many items related to companies, such as meetings with business executives, and advice and guidance from corporate executives. Research Implications – This study is meaningful in that it was used as basic data by analyzing the effectiveness of industry-university linked capstone design classes in humanities and social sciences, in a situation where there are not many studies. In addition, it is meaningful that all student thoughts and opinions on the capstone design class were synthesized through IPA analysis and FGI analysis for students that participated in the class.

목차

등록된 정보가 없습니다.

참고문헌 (0)

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