• Journal of Engineering Education Research
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• v.10 no.4
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• pp.17-28
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• 2007

This paper aims to present the ways to maximize educational effects and facilitate a curriculum renovation through the Specified Track Curriculum Development, a joint lecture system among local universities which is implemented by Busan Educational Alliance of Mechanical Engineering (BEAM) as part of New University for Regional Innovation(NURI), a government-sponsored project to facilitate a balanced regional development of Korea. The Specified Track Curriculum is a unified governing body joined by 4 universities of mechanical engineering departments with an emphasis on their specified academic fields(advanced hightech, environmental, marine and foundational machinery sectors), And the universities mutually recognize academic credits. The track (Specified-Track Curriculum) was carried out three times from winter semester in 2005 to the present and 486 students took the track course for two years. As a result, the track laid out a foundation for the first local joint lecture system in korea with the performance-oriented and students-tailored education, meeting needs of the new era and training efficiency. The graduates' employment rose to 8.5%, compared with that of 2005. According to recent survey conducted on companies employing the graduates, the satisfaction with the graduates' performance marked 9.4% improvement. The track also contributed to expanding human networks, facilitating the educational exchange of local universities.

• Journal of The Korean Association of Information Education
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• v.23 no.6
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• pp.675-687
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• 2019

As interest in artificial intelligence increases, each university has been establishing a special graduate school with artificial intelligence major, and recently, the Korea government has established various support policies for artificial intelligence education. However, each university has a lot of difficulties because it has little experience in operating graduate education with the latest field of artificial intelligence and it is not easy to find experts. In this study, the response of graduate school students majoring in artificial intelligence was analyzed using IPA technique, and the direction of education of graduate school artificial intelligence major was searched. Among the 40 items surveyed by IPA, 12 items such as systematization of artificial intelligence curriculum, progress of class considering learning level, improvement of academic relations with guidance professors were extracted as items to be improved first. On the other hand, 8 items such as assistant capacity, and relationship with colleagues were overloaded, and twelve items such as instructor's lecture competency, appropriateness of educational contents, learner's artificial intelligence skills and knowledge, and attitude acquisition were to be maintained. In addition, eight items such as convergence education curriculum and diversity of education methods were all low in importance and performance. It is suggested that AI graduate school should be divided into two tracks(technical specialization, convergence expansion) by educational goal, and each track should be conducted by level-specific educational contents and methods suitable for student level. The curriculum should be elaborate and systematic to acquire AI knowledge, skills, and attitudes, and should have an individualized guidance system centered on excellent faculty members.

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