Journal of Educational Innovation Research 2018, Vol. 28, No. 3, pp.1-25 DOI: * An Analysis on Content

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1 Journal of Educational Innovation Research 2018, Vol. 28, No. 3, pp.1-25 DOI: * An Analysis on Contents of the Pedagogy Examination for Secondary-School Teacher s Employment using Text Mining & Semantic Network Analysis Purpose: The purpose of this study is to identify the central contents and tendency of the pedagogy examination for secondary-school teacher s employment(2014~2018), to confirm the degree of agreement with preliminary teacher education standard and teacher education institution curriculum. Method: The main research methodologies used in this study are 'text mining' and 'semantic network analysis' methodology. The text mining methodology was used for morpheme analysis, key word extraction, frequency search, and 1 mode matrix generation. Semantic network analysis methodology was used to analyze the structural characteristics in language network(density, degree, centrality, etc.). Results: First, in this study, the key words (top 20 most frequently) in the annual pedagogy examination for secondary-school teachers' employment from year 2014 to 2018 are curriculum, education evaluation, educational methodology and educational technology, educational psychology, guidance and counseling. Especially, many key words seem to be core competencies that teachers should perform at school, such as class, evaluation, curriculum, motivation, and subject. Second, from the 2014 to the 2018 academic year, the semantic network characteristics of the top 30 frequency words in the entire pedagogy examination showed that the activity among the key words is high and the convergence between various key words is being performed. The most central, closest, and highly mediating key words in the pedagogy examination for secondary-school teachers' employment were students, classes, teachers, and interests. Conclusion & Suggestions: In this study, the content analysis of the national pedagogy examination for secondary-school teacher s employment was conducted objectively and profoundly. The results of this study are expected to be used as meaningful and positive data for the educational curriculum and education methods of the secondary-school teachers training. Key words : pedagogy examination for secondary-school teacher s employment, text mining, semantic network analysis, contents analysis * 2018 (KWUI ). Corresponding Author: Kwon, Choong-Hoon. Kwangju Women s University, Dept. of Secondary Special Education, Yeodae-gil 201, Gwangsan-gu, Gwangju, Korea, kwonch@kwu.ac.kr

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24 Gottron, T. (2009). Document word clouds: Visualizing web documents as tag cloud to aid users in relevance decisions. Research and Advanced Technology for Digital Libraries-Lecture Notes in Computer Science, 5714, Leskovec, J., Rajaraman, A., & Ullman, J. D. (2016). Mining of Massive Datasets(2nd ed.). Cambridge University Press. McKinsey Global Institution (2011). Big data: The next frontier for innovation, competition, and productivity. McKinsey & Company. Nicholls, A., & Nicholls, H. (1981). Developing a curriculum: A practical approach. George Allen & Unwin Ltd. OECD (2011). Teachers Matter: Attracting, Developing and Retaining Effective Teachers. Paris: OECD. Scott, J. (2000). Social Network Analysis. London: SAGE Publication. Turney, P. D., & Pantel, P. (2010). From frequency to meaning: Vector space models of semantics. Journal of artificial intelligence research, 37, Tyler, R. W. (1949). Basic principles of curriculum and instruction. Chicago: The University of Chicago Press. Wheeler, D. K. (1967). Curriculum Process. London: University of London Press. : / : / :

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Journal of Educational Innovation Research 2019, Vol. 29, No. 1, pp DOI: : * Research Subject

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