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http://dx.doi.org/10.14352/jkaie.2019.23.6.607

Analysis on Trend of Study Related to Computational Thinking Using Topic Modeling  

Moon, Seong-Yun (Dept. of Computer Education, Korea National University of Education)
Song, Ki-Sang (Dept. of Computer Education, Korea National University of Education)
Publication Information
Journal of The Korean Association of Information Education / v.23, no.6, 2019 , pp. 607-619 More about this Journal
Abstract
As software education was introduced through the 2015 revised curriculum, various research activities have been carried out to improve the computational thinking of learners beyond the existing ICT literacy and software utilization education. With this change, the purpose of this study is to examine the research trends of various research activities related to computational thinking which is emphasized in software education. To this end, we extracted the key words from 190 papers related to computational thinking subject published from January 2014 to September 2019, and conducted frequency analysis, word cloud, connection centrality, and topic modeling analysis on the words. As a result of the topical modeling analysis, we found that the main studies so far have included studies on 'computational thinking education program', 'computational thinking education for pre-service teacher education', 'robot utilization education for computational thinking', 'assessment of computational thinking', and 'computational thinking connected education'. Through this research method, it was possible to grasp the research trend related to computational thinking that has been conducted mainly up to now, and it is possible to know which part of computational thinking education is more important to researchers.
Keywords
Software Education; Computational Thinking; LDA; Topic Modeling; Research Trend;
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Times Cited By KSCI : 12  (Citation Analysis)
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1 EunJi Seong (2014). A Study on Computer Programming Education for Elementary, Master's Thesis, Seoul National University of Education.
2 DongMan Kim, TaeWuk Lee (2018). A Meta-Analysis on the Effects of Software Education on Computational Thinking. Journal of The Korea Society of Computer and Information, 23(11), 239-246.   DOI
3 Marwa Naili, Anja Chaibi, Henda Ghezala. (2017). Arabic topic identification based on empirical studies of topic models. Revue Africaine de la Recherche en Informatique et Mathematiques Appliquees, 27. 45-49.
4 Kyrola, Aapo. 10-702 Project Report: Parallel LDA, Truth or Dare?.
5 SeungKi Shin, YoungKwon Bae (2014). Analysis and Implication about Elementary Computer Education in India. Journal of The Korean Association of Information Education, 18(4), 585-594.   DOI
6 SangTae Na, JaHee Kim, MinHo Jung, JooEon Ahn (2016). Trend Analysis using Topic Modeling for Simulation Studies. Journal of the Korea Society for Simulation, 25(32), 107-116.   DOI
7 Meng-Leong How, Wei Loong David Hung (2019). Educing AI-Thinking in Science, Technology, Engineering, Arts, and Mathematics (STEAM) Education. Education Sciences, 9(3), 184-225.   DOI
8 Rad, Paul, Mehdi Roopaei, Nicole Beebe, Mehdi Shadaram, Yoris Au (2018). AI Thinking for Cloud Education Platform with Personalized Learning. In Proceedings of the 51st Hawaii International Conference on System Sciences.
9 Neller, Todd W. (2017). AI education: Machine learning resources. AI Matters, 3(2), 12-15.   DOI
10 Hyun Joo, DongSik Kim, JinJu Lee, ChungSoo Na (2018). Inducing Computational Thinking in Korean SW Education: Synthesizing Standardized Mean Changes through Meta-analysis. Journal of Educational Technology, 34(3), 775-815.   DOI
11 JunSeok Oh (2015). Identifying Research Opportunities in the Convergence of Transportation and ICT Using Text Mining Techniques. Journal of Transport Research, 22(4), 93-110.   DOI
12 Wing, J. M. (2008). Computational thinking and thinking about computing. Philosophical transactions of the royal society of London A: mathematical, physical and engineering sciences. 366(1881), 3717-3725.   DOI
13 MOE (2015). Software Education operating instructions.
14 ISTE & CSTA (2011). Operational Definition of Computational Thinking for K-12 Education. https://id.iste.org/docs/ct-documents/computational-thinking-operational-definition-flyer.pdf.
15 SungHoon Seo, HakYeon Lee (2015). Fintech trend analysis using topic modeling of BM patents. The Korean Institute of Industrial Engineers fall conference, 471-480.
16 David M. Blei (2012). Probabilistic Topic Models, Communications of the ACM, 55(4), 77-84.   DOI
17 David M. Blei, Andrew Y. Ng, Michael I. Jordan (2003). Latent Dirichlet Allocation. Journal of Machine Learning Research, 3(JAN), 993-1022.
18 JuSeop Park, SoonGoo Hong, JongWeon Kim (2017). A Study on Science Technology Trend and Prediction Using Topic Modeling. Journal of the Korea Industrial Information Systems Research, 22(4), 19-28.   DOI
19 SunJu Park (2015). A Topic Analysis of SW Education Textdata Using R. Journal of The Korean Assocaition of Information Education, 19(4), 517-524.   DOI
20 HyeYoung Han (2019). A study of research trends in nurses turnover using Topic modeling and Keyword Network Analysis. Master's Thesis, Korea University.
21 JaeWon Choi, Ho Lee, JungMin Kim, JuHo Song (2017). A Comparative Analysis of Curriculums for Software-related Departments based on Topic Modeling. Journal of Society for e-Business Studies, 22(4), 193-214.   DOI
22 MinChae Kim, YoungHwan Kim (2018). Analysis of Research Trends on Digital Textbook: Based on Text Network Analysis. Journal of Educational Information and Media, 24(2), 387-413.
23 DooBong Kang (2019). Comparison of Unplugged Activities at Home and Abroad using Semantic Network Analysis. Journal of Korean association of computer education, 22(4), 21-34.   DOI
24 JaeHwi Kim, DongHo Kim (2016). Development of Physical Computing Curriculum in Elementary Schools for Computational Thinking. Journal of The Korean Association of Information Education, 20(1), 69-82.   DOI
25 JiWon Lee, JeongBeom Kim, JungBog Kim (2018). Effects of the Experience in Developing Physics Teaching Materials Based on Computational Thinking for Improvement of Science Teachers' and Pre-service Teachers' Technological Pedagogical and Content Knowledge(TPACK). New Physics: Sae Mulli, 68(2), 1-15.   DOI
26 HyungWook Kim, SeongYun Mun, SoRi Jeong, SoJean Jeong (2018). The Effect of Making My Own Game using ‘Entry and Arduino' on Elementary Students Creative Problem Solving Ability and Interpersonal Relationship Ability. Journal of Learner-Centered Curriculum and Instruction, 18(1), 487-507.   DOI
27 JungSook Sung, HyeonCheol Kim (2015). Analysis on the International Comparison of Computer Education in Schools. Journal of The Korean Association of Information Education, 20(6), 543-552.
28 JaeChang Kho, KuenTae Cho, YoonHo Cho (2013). A Study on Recent Research Trend in Management of Technology Using Keywords Network Analysis. Journal of intelligence and information systems, 19(2), 101-123.   DOI
29 Gyun Heo (2016). A Study on the Research Trends to Flipped Learning through Keyword Network Analysis. Journal of fisheries and marine sciences education, 28(3), 872-880.   DOI
30 YoungChoo Choi, SuJung Park (2011). Analyzing Trends in the Study of Public Administration: Application of the Network Text Analysis Method. KOREAN REPUBLIC ADMINISTRATION REVIEW, 45(1), 123-139.
31 JuYeon Lee, YooHyun Park (2016). Social Network Analysis of author's interest area in Journals about Computer. Journal of the Korea Institute of Information and Communication Engineering, 20(1), 193-199.   DOI
32 SooSang Lee (2016). A Study on the Application of Topic Modeling for the Book Report Text. Journal of Korean Library and Information Science Society, 47(4), 1-18.   DOI