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Trend Analysis of Individualized Learning -Using the Keyword Network-
김현하,서희,박창언 사단법인 미래융합기술연구학회 2022 아시아태평양융합연구교류논문지 Vol.8 No.9
Individualized learning is the education that is provided at a speed and method appropriate to each learner based on the learner’s knowledge, interests, and so on. This study aimed to analyze the trends in individualized learning for general education in the past ten years by dividing them into those from 2012–2016 (Period 1) and 2017–2021 (Period 2), and to obtain implications necessary to practice individualized learning in school education. After screening, a total of 277 studies were analyzed by conducting text mining and keyword network analysis, using Textom, Ucinet, and NetDraw. By conducting the process, term frequency, TF-IDF, the keyword network, degree centrality, closeness centrality, and betweenness centrality, which are the analysis indices, came up. Results of the study revealed that studies about individualized learning have been continuously conducted since 2012, and their number increased over time. Most keywords from both periods were the same based on the term-frequency and TF-IDF, but “SMART-Education” and “Under-achievement” appeared frequently only during Period 1, whereas “Artificial intelligence,” “COVID-19,” “Future,” and “Future education” appeared only during Period 2. Through keyword network analysis, it was found that the density of the network is higher during the second period, but the group degree centralization appeared to be higher during the first period. Furthermore, the degree centrality of “e-learning” during Period 1 and “Online,” “Artificial intelligence” appeared to be high. Based on the research results, there are implications for analyzing trends in individualized learning and practicing individualized learning in schools’ education in the future. Therefore, it is necessary to create an environment for individualized learning so that schooling does not become overly dependent on developing technology and neglects the curriculum and other elements of education like grades.
저온플라즈마 구동 촉매 반응기를 이용한 벤젠과 톨루엔의 처리
김현하,오가타 아쯔시,후타무라 시게루 한국대기환경학회 2006 한국대기환경학회지 Vol.22 No.1
Nonthermal plasma-driven catalysis (PDC) was investigated for the decomposition of benzene and toluene asof catalysts Ag/TiO2 and Pt/γ-Al2O3 were tested in this study. The amount of catalysts packed in the PDC reactordid not influence on the decomposition efficiency of benzene. The type of catalysts also had no influence on thedecomposition efficiency of toluene and carbon balance. The Ag/TiO2 catalyst showed constant CO2 selectivity of2 was greatly enhanced with thePt/γ-Al2O3 catalysts, and reached 97% at 205 J/L. Two test runs with 20 fold difference in the gas flow clearlyindicated that lab-scale data can be successfully applied for the scaling-up of PDC system.