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http://dx.doi.org/10.32431/kace.2020.23.3.006

A Study on Entrance Evaluation System for Data Scientist Postgraduate Program  

Kim, MiJeong (고려대학교 대학원 컴퓨터학과)
Kim, JaMee (고려대학교 교육대학원 컴퓨터교육전공)
Lee, WonGyu (고려대학교 대학원 컴퓨터학과)
Publication Information
The Journal of Korean Association of Computer Education / v.23, no.3, 2020 , pp. 49-58 More about this Journal
Abstract
Organizing entrance evaluation system for selecting students who can become expert in data science field according to need of the age and social demand is important. This study was conducted for the purpose of analyzing data science field graduate school entrance evaluation system and deriving implications after taking into account the importance of talents possessing convergence competency. For this aim, a total of 22 graduate schools in 7 countries have been selected targeting data scientist postgraduate program around the world. The selected graduate schools have been analyzed based on qualifications, necessary skills prior to entrance, entrance conditions, and selection methods. As a result of the analysis, 'graduate school which I can apply for regardless of possessing undergraduate degree or undergraduate major (63.6 percent)' in qualifications category, 'graduate school which mentioned skills required in completing master's degree prior to entrance (63.6 percent)' in skills required prior to entrance category, 'graduate school which does not mention separate entrance condition (81.8 percent)' in entrance conditions category, and 'graduate school selecting students merely based on document screening (68.2 percent)' in selection methods category took the highest portion. Based on the above, this study summarized the results of the data scientist process and suggested implications for objectifying admission evaluation.
Keywords
data science; data scientist; graduate school entrance; entrance evaluation system;
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