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A Study on Student Satisfaction according to Likert Scale in Big Data Training (빅데이터 양성 교육에서 리커트 척도에 따른 만족도 분석에 관한 연구)

Choi, Hyun
- Journal of the Korean Society of Industry Convergence
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- v.22 no.6
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- pp.775-783
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- 2019
The big data industry market continues to grow and is expected to grow further. In this paper, based on the five-point Likert scale of college students in the process of developing big data young people, the satisfaction of instructors in big data training and improvement of job (education) ability based on AI convergence The survey was conducted on the expectations of the participants and their intention to participate in the training process for the young talents. Male students were more satisfied than students. In terms of students, students who are less than 6th semester have the highest satisfaction, but students who are less than 7th and 8th semesters are less satisfied. By department, the satisfaction level of science and statistics students was the highest, while the satisfaction level of other students was low. According to the average of college credits, the satisfaction of students under 3.5~4.0 was the highest, and the satisfaction of students below 3.0 was the lowest.
https://doi.org/10.21289/KSIC.2019.22.6.775 인용 PDF KSCI

Nationally-Funded R&D Projects Data Based Dynamic Convergence Index Development: Focused On Life Science & Public Health Area (국가 연구개발(R&D) 과제 데이터 기반 동적 융합지표에 관한 연구: 생명·보건의료 분야를 중심으로)

Lee, Doyeon;Kim, Keunhwan
- Journal of the Korean Society of Industry Convergence
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- v.25 no.2_2
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- pp.219-232
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- 2022
The aim of this study is to provide the dynamic convergence index that reflected the inherent characteristics of the convergence phenomenon and utilized the nationally-funded R&D projects data, thereby suggesting useful information about the direction of the national convergence R&D strategy. The dynamic convergence index that we suggested was made of two indicators: persistency and diversity. From a time-series perspective, the persistency index, which measures the degree of continuous convergence of multidisciplinary nationally-funded R&D projects, and the diversity index, which measures the degree of binding with heterogeneous research areas. We conducted the empirical experiment with 151,248 convergence R&D projects during the 2015~2021 time period. The results showed that convergence R&D projects in both public health and life sciences appeared the highest degree of persistency. It was presumed that the degree of persistency has increased again due to the COVID-19 pandemic. Meanwhile, the degree of diversity has risen with combining with disciplinary such as materials, chemical engineering, and brain science areas to solve social problems including mental health, depression, and aging. This study not only provides implications for improving the concept and definition of dynamic convergence in terms of persistency and diversity for national convergence R&D strategy but also presented dynamic convergence index and analysis methods that can be practically applied for directing public R&D programs.
https://doi.org/10.21289/KSIC.2022.25.2.219 인용 PDF KSCI HTML

Empirical analysis of strategy selection for the technology leading and technology catch-up in the IT industry

Byung-Sun Cho;Sang-Sup Cho;Sung-Sik Shin;Gang-hoon Kim
- ETRI Journal
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- v.45 no.2
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- pp.267-276
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- 2023
R&D strategies of companies with low and high technological levels are discussed based on the concept of technology convergence and divergence. However, empirically detecting enterprise technology convergence in the distribution of enterprise technology (total productivity increase) over time and identifying key change factors are challenging. This study used a novel statistical indicator that captures the internal technology distribution change with a single number to clearly measure the technology distribution peak as a change in critical bandwidth for enterprise technology convergence and presented it as evidence of each technology convergence or divergence. Furthermore, this study applied the quantitative technology convergence identification method. Technology convergence appeared from the separation of total corporate productivity distribution of 69 IT companies in Korea in 2019-2020 rather than in 2015-2016. Results indicated that when the total technological level was separated from the technology leading and technology catch-up, IT companies were found to be pursuing R&D strategies for technology catch-up.
https://doi.org/10.4218/etrij.2021-0454 인용 PDF