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Analysis of Agenda Prediction According to Big Data Based Creative Education Performance Factors

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Advances in Computer Science and Ubiquitous Computing (CUTE 2017, CSA 2017)

Abstract

In the present study, to derive future mid/long-term development directions and agendas according to the outcomes of South Korean creativity education policies that have been steadily implemented thus far, opinion mining analyses were conducted utilizing educational data. With regard to analysis methods, creativity education related unstructured data were collected, linkage analysis based higher education policy keywords were extracted, and opinion mining analyses were conducted through the extracted keywords. From the analyzed results, we derived educational systems that can be very important for future development of creativity education and performance factors through the positive and negative data on the educational policies that are currently being implemented. The outcomes of the present study will be a solution that can be utilized hereafter in preparing direction points according to domestic and foreign educational policies.

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Acknowledgments

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. 2017R1D1A1B03029292).

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Correspondence to Kil-Hong Joo .

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Seo, JH., Cho, E., Joo, KH. (2018). Analysis of Agenda Prediction According to Big Data Based Creative Education Performance Factors. In: Park, J., Loia, V., Yi, G., Sung, Y. (eds) Advances in Computer Science and Ubiquitous Computing. CUTE CSA 2017 2017. Lecture Notes in Electrical Engineering, vol 474. Springer, Singapore. https://doi.org/10.1007/978-981-10-7605-3_209

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  • DOI: https://doi.org/10.1007/978-981-10-7605-3_209

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7604-6

  • Online ISBN: 978-981-10-7605-3

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