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Journal of Educational Innovation Research 2019, Vol. 29, No. 1, pp.91-116 DOI: http://dx.doi.org/10.21024/pnuedi.29.1.201903.91 : * Research Subject Trend Analysis on Educational Innovation with Network Text Analysis Purpose: The objective of this study was to analyze the research trends on the educational innovation gathered from Korean academic journals and master s and doctoral degree dissertations published from 2004 to 2018. Method: In order to achieve the objectives, 312 articles and dissertations were collected from RISS utilizing the key word "educational innovation". A total of 1,560 key words were selected from the articles to perform the network text analysis, especially to acquire each node's frequency, co-occurrence and centrality degree. Results: The four most frequently appeared key words were 'educational innovation', 'teacher', 'curriculum', and 'instruction'. The key word which appeared with the most frequency across all government administrations that were installed from 2004 to 2018 was 'educational innovation ; and the most frequent key words by coinciding with each administration are as follows: 1) Rho Moo-Hyun: 'teacher' and 'university' 2) Lee Myoung-Bak: 'university' and 'curriculum', 3) Park Geun-Hye: 'curriculum' and 'teachers', 4) Moon Jae-In: '4th Industrial Revolution' and 'teacher'. Extracted key words were categorized into six groups: group one - 'educational innovation' and 'curriculum', group two - 'university education', group three - 'teachers' and 'learners', group four - '4th industrial revolution', group five 'HRD' and 'regional innovation' and group six - 'educational innovation'. Conclusion: While the number of researches on educational innovation increased gradually from 2004, more research trend analyses should be conducted in order to provide better conceptualizations of 'educational innovation', 'educational reform' and 'innovation schools'. Key words : educational innovation, key word analysis, network text analysis, governmental analysis, research trend analysis * (2 ). Corresponding Author: Shon, Mi. Busan National University of Education, Dept. of Education, 24, Gyodae-ro, Yeonje-gu, Busan, South Korea, e-mail: shonm@bnue.ac.kr

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3) 정부별주요주제어빈도수분석결과.,,. 1. 2004~2008, 2009~2013, 2014~2017 2018. < -3>. (2004~2008) (2009~2013) (2014~2017) (2018) 77 79 116 40 312 4.,,,.,,.,,. 40, 4. < -4> 10.

(34), (12), (11), (11), (8), (5), (5), (4), (4), (4), (4), (4), (4), (4), (4) (29), (14), (10), (10), (5), (4), (4), (4), (4), (3), (3), (3), (3), (3), (3), (3) (45), (14), (13), (13), (11), (9), (8), 4 (7), ()(7), (7) (17), 4 (6), (6), (6), (5), (4), (4), (4), ()(3), (3), (3) < -5> < -4> ICT,.,. ICT, 10. ICT 4. (2004~2008) (2009~2013) (2014~2017) (2018) ICT (34), (8), (4), (4), (4), (4) (12), (11), (11), (5), (4), (4) (5), (4) 58 (50.8%) 47 (41.3%) 9 (7.9%) 100% (14), (10), (29), (4), (5), (10), (4), (4), (3), (4), 105 (3), (3), (3) (3) (3), (3), 43 (41%) 50 (47.6%) 12 (11.4%) 100% (45),(9), (8), (7) (14), (13), (13), (11), 4 (7), ()(7), 69 (51.5%) 51 (38%) 14 (10.5) 100% (6), (6), 4 (6), (17), (4) (5), (4), 61 (4), (3), (3) ()(3), 21 (34.4%) 31(50.8%) 9 (14.8%) 100% 191 (46.1%) 179 (43.2%) 44 (10.7%) 414 114 134

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,,,,,, (2005). 50 :. (2), 181-198.,, (2016). : 20,. (1), 31-53. http://dx.doi.org/10.15833/kafeiam.22.1.031 (1994).. (1), 85-102.,, (2018).. (2), 211-240. http://dx.doi.org/:10.24211/tjkte.2018.35.2.211 (2003). [ ]. 35-78. (2012).. (4), 349-378.,,, (2016).. (3). 81-105.,, (2016). -. (2), 153-185. (2005).. 1-30. (2005). : 10. (1), 1-16. (2010).. (2), 175-203., (2012).. (2), 53-66. (2007).. 140-177. OECD (2005). Oslo Manual, OECD & Statistical Office of the European Communities. Paris: OECD Publishing. Popping, R. (2000). Computer-assisted text analysis. London: SAGE. Roberts, C. W. (1997). "Introduction" In C. W. Roberts, ed. Text Analysis for the Social Sciences: Methods for Drawing Statistical Inferences from Texts and Transcripts, 1-8. Mahwah, NJ: Saur. : 2019.01.31. / : 2019.02.07. / : 2019.03.20.

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