• 대학교육
• /
• s.137
• /
• pp.7-11
• /
• 2005

산학협력에 있어 중앙정부와 지방정부의 정책적 지원은 더욱 강화되어야 하며, 대학은 경쟁력있고 특성화된 산학협력 모델을 다양하게 개발하여야 하고, 대학과 기업 간의 신뢰 구축과 상호 이해의 폭을 획기적으로 넓혀 나가야 대학의 산학협력단은 소기의 목적을 달성할 수 있다.

• Journal of Convergence for Information Technology
• /
• v.7 no.3
• /
• pp.47-53
• /
• 2017

The university must open the "School Development Plan and Specialization Plan" at the university allimi. The reason for this is the Special Act on the Disclosure of Information by Educational Institutions, enacted on May 25, 2007, and the Plan for Reform of University Reform announced by the Ministry of Education on Mar 28, 2014. Therefore, we examined the similarity and standardized model of the "School Development Plan and Specialization Plan" published by a total of 137 colleges. As a result of the study, only 17(12.4%) of the college produced information in two ways(school development and specialization), and the rest were not. The school development plan presented quantitative indicators such as world number one, The characterization plan presented qualitative indicators such as human. Based on this, standardized research procedures and conception are presented.

• 대학교육
• /
• s.147
• /
• pp.56-60
• /
• 2007

부산대학교의 통합은 대학구조개혁과 캠퍼스별 특성화를 동시에 이룩한 국립대 구조개혁의 표본적 성공 사례라 할 수 있다. 통합으로 인해 입학정원 감축, 단과대학 및 산업대학원 통폐합, 유사·중복학과 통폐합, 행정조직 감축, 신입생 충원율 개선 등의 성과가 있었으며, 캠퍼스 특화 전략에 따라 부산캠퍼스는 연구중심대학으로, 양산캠퍼스는 세계적 의료 허브로, 밀양캠퍼스는 나노·바이오 분야로 특화하였다. 향후 부산대학교는 지속적 개혁을 통하여 혁신을 도모함으로써 단발성, 일회성이 아닌 일상적, 상시적 혁신을 추진하여 혁신의 시스템화를 정착시키고자 한다. 그리고 진정한 혁신을 위해 교육 분야 혁신, 산학연구 혁신, 행정 혁신에 더욱 박차를 가할 것이다.

• 대학교육
• /
• s.91
• /
• pp.62-75
• /
• 1998

• 대학교육
• /
• s.137
• /
• pp.49-53
• /
• 2005

• 대학교육
• /
• s.108
• /
• pp.124-127
• /
• 2000

• 대학교육
• /
• s.136
• /
• pp.57-62
• /
• 2005

• 대학교육
• /
• s.56
• /
• pp.83-89
• /
• 1992

• 대학교육
• /
• s.115
• /
• pp.94-97
• /
• 2002

• Journal of Service Research and Studies
• /
• v.9 no.3
• /
• pp.87-99
• /
• 2019

Healthcare and data science are often linked through finances as the industry attempts to reduce its expenses with the help of large amounts of data. Data science and medicine are rapidly developing, and it is important that they advance together. Data science is a driving force in transition of healthcare systems from treatment-oriented to preventive care in healthcare 3.0 era. It enables customized precision-based medicine that current healthcare systems cannot facilitate, and discovers more cost-effective treatment. Currently, healthcare big data is in the reality of medical institution, public health, medical academia, pharmaceutical sector as well as insurance agency. With this motivation, the medical college of Soonchunhyang university has performed a 'healthcare data science initiative(HDSI)' since 2014. Most of domestic HDSI programs focus on short-term contents such as mentoring and sharing cases for data science. Therefore, it is difficult to provide education tailored to the level of skills and job competency required at the practical site. Soonchunhyang HDSI implemented specialized strategies for improving resilience and response to changes in the IT education of current healthcare with the emphasis on the need for systematic activation of the practical HDSI. The HDSI has been performed as a part of on industry-academic link program in CK-1. Through quantitative and qualitative analysis, this paper discussed the HDSI process, performance, achievement, and implications.