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Analysis of Factors Affecting the Transfer of Educational Training of Science and Technology Personnel
  • Kim, Miri ;
  • Jeon, Sehyeok ;
  • Hwang, Joo Sung ;
  • Kim, Seoyong
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dc.contributor.authorKim, Miri-
dc.contributor.authorJeon, Sehyeok-
dc.contributor.authorHwang, Joo Sung-
dc.contributor.authorKim, Seoyong-
dc.date.issued2022-01-01-
dc.identifier.urihttps://aurora.ajou.ac.kr/handle/2018.oak/36795-
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85127567881&origin=inward-
dc.description.abstractThe purpose of this study is to analyze a number of factors affecting the transfer of educational training targeting science and technology personnel. This study utilized data collected from the 'Science and Technology Human Resources Development Panel Survey' of the Korea Institute of R & D Human Resource Development(KIRD). The research was conducted by dividing the main contents of this study are as follows. First, the Durbin Watson test was conducted to verify the independence of the residuals based on the research model. Second, multiple regression analysis was performed to check how each variable affects education and training transfer. Second, it is checked whether interpersonal and cultural factors act as modulating variables. As a result of the analysis, it was found that intrinsic learning motivation, instrumental learning motivation, learning competency, learning climate, education and training effect, organizational compensation, and intellectual utilization ability, which are variables of educational factors, were significant in the positive (+) direction for education and training transfer. Objective ambiguity, autonomy, and workload, which are job factors, were also found to be significant in education and training transfer. Goal ambiguity was significant in the positive (+) direction for education and training transfer, and autonomy and workload were significant in the negative (-) direction. It was confirmed that the interpersonal and cultural factors had an effect between the independent variable and the transfer of education and training as moderating variables.-
dc.language.isoeng-
dc.publisherInstitute of Electrical and Electronics Engineers Inc.-
dc.subject.meshCultural factors-
dc.subject.meshDeterminant-
dc.subject.meshEducation and training-
dc.subject.meshEducational training-
dc.subject.meshHuman resources development-
dc.subject.meshLearning motivation-
dc.subject.meshNumber of factors-
dc.subject.meshScience and Technology-
dc.subject.meshScience and technology personnel-
dc.subject.meshTransfer of educational training-
dc.titleAnalysis of Factors Affecting the Transfer of Educational Training of Science and Technology Personnel-
dc.typeConference-
dc.citation.conferenceDate2022.1.17. ~ 2022.1.20.-
dc.citation.conferenceName2022 IEEE International Conference on Big Data and Smart Computing, BigComp 2022-
dc.citation.editionProceedings - 2022 IEEE International Conference on Big Data and Smart Computing, BigComp 2022-
dc.citation.endPage351-
dc.citation.startPage345-
dc.citation.titleProceedings - 2022 IEEE International Conference on Big Data and Smart Computing, BigComp 2022-
dc.identifier.bibliographicCitationProceedings - 2022 IEEE International Conference on Big Data and Smart Computing, BigComp 2022, pp.345-351-
dc.identifier.doi10.1109/bigcomp54360.2022.00077-
dc.identifier.scopusid2-s2.0-85127567881-
dc.identifier.urlhttp://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=9736461-
dc.subject.keyworddeterminants-
dc.subject.keywordeducational training-
dc.subject.keywordscience and technology personnel-
dc.subject.keywordtransfer of educational training-
dc.type.otherConference Paper-
dc.description.isoafalse-
dc.subject.subareaArtificial Intelligence-
dc.subject.subareaComputer Science Applications-
dc.subject.subareaComputer Vision and Pattern Recognition-
dc.subject.subareaInformation Systems and Management-
dc.subject.subareaHealth Informatics-
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