• Title/Summary/Keyword: Grant Proposals

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Facilitating Interdisciplinary Research: An Analysis of Grant Proposal Acceptance Rates in South Korea (학제 간 융합연구 활성화 방안 연구)

  • Cho, Sung Kyum;Lee, Kwang Hee
    • The Journal of the Korea Contents Association
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    • v.18 no.5
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    • pp.539-544
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    • 2018
  • Interdisciplinary, or convergence, research has been a priority for the National Research Foundation of Korea (NRF) and many scholars in Korea have proposed interdisciplinary projects. Of the 4,930 proposals for the submitted in 2017, 2,575 (52.2%) of these proposals could be considered interdisciplinary projects. However, interdisciplinary projects had an acceptance rate of 35.0%, compared to an acceptance rate of 42.1% for single-discipline proposals. According to the study, despite the large share of research projects that appear to be interdisciplinary research, the characteristics of interdisciplinary studies was not reflected properly in the evaluation. I would suggest that it is required to prepare the criteria for classification of interdisciplinary studies in the classification system of research fields so that the characteristics of interdisciplinary research projects may be duly considered.

Developing a Quantitative Evaluation Model for Screening the Research Grant Applications (연구지원 대상자 선정을 위한 정량평가 모형개발)

  • Yoo, Jin-Man;Han, In-Soo;Oh, Keun-Yeob
    • The Journal of the Korea Contents Association
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    • v.17 no.4
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    • pp.541-549
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    • 2017
  • This research investigates the quantitative screening methods for the Grant Funding system and seeks for the efficient evaluation of a number of proposals. We search foreign cases of Grand Funding, but we found no appropriate model for using in Korea. Thus, we had to develope our own model for better screening. First, we analyse the existing evaluation system and find some problems and challenges. Second, we suggest a quantitative screening system for Grant Funding with a numeric model, and operates a tedious simulation by using the previous data and our suggested model. Third, we test the suggested model and find the optimal model by using simulation method The number of data analysed for simulation is larger than 200 thousands. Last, we suggest some brief policy implications based on the results in the paper.