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文獻計量法可視化分析:探索博物館教育之發展現況

Visualizing Recent Development of Museum Education by Bibliometric Analysis

摘要


本研究採用HistCite和VOSviewer軟體為研究工具,以WOS資料庫文獻為主,探索博物館教育之歷年論文發表量及引用量、重要作者、論文發佈地區、關鍵詞、重要論文及論文間互引和為國際引用情況等,掌握文獻資料之內涵。發現文章發表量與年度之趨勢關係為指數函數關係,且發文量前兩名美國及英國則貢獻近60%;根據論文同領域引用量分析,最高者之主題為透過學校與博物館合作提升學生科學素養(Science literacy),因此博物館與校方之緊密合作有助於科學教育之推展,再透過產生文獻引用關係時序圖能辨別出論文引用的時序關係並可分群類,輕易聚焦出關鍵論文。運用VOSviewer分析共著作者之國家合作關係、文獻引用之作者分析及關鍵詞共現分析,產生社會網路密度圖,透過密度圖內親疏關係及自動分類分群,可以聚焦出貢獻度最高國家,並能表列出最具關注的論文作者,再根據關鍵詞共現分析列舉出博物館教育之研究熱點,最後透過心智圖整併熱門作者關鍵詞,鑑別出研究熱點與前沿發展。

並列摘要


Adopting two bibliometric tools: HistCite and vosviewer, the present study attempts to analyze the published articles pertaining to museum education retrieved from Web of Science (WOS) database to obtain the yearly output, geographic distribution, prolific authors, mostly cited keywords, and total local citation and construct the social network structures to visualize the bibliometric status, research hotspot and trend. The number of yearly publications increases in the exponential manner and the top two countries, USA and UK contributed to alomost 60 % of all. The frequently cited paper focused on the collaboration between university and museum to promote the students' science literacy, so it is n that the collaboration could facilitate science education. Moreover, the time-wise citation historiography by HistCite and bibliometric network visualizations by VOSviewer could aid to clarify the research hotspots and find out the key papers quickly. Finally, the mind mapping of the keyword co-occurrence analytical resuts is presented to elucidate the research hotspots and development fronts.

參考文獻


蔡欣倫。(2017)。引文編年可視化軟體HistCite 的功能、優缺點與改進之道,科學與人文研究,4(3): 57-76。
蔡欣倫。(2018)。文獻計量法可視化分析:以金屬增材製造(3D 打印)技術發展為例,科學與人文研究,5(3), 97-121。
Kosmopoulos, D. and Styliaras, G.(2018). A survey on developing personalized content services in museums, accepted published in Pervasive and Mobile Computing.
Van Eck, N. J., & Waltman, L. (2010).Software survey: VOSviewer, a computer program for bibliometric mapping, Scientometrics, 84:523–538.
Van Eck, N. J., & Waltman, L. (2009). How to normalize cooccurrence data? An analysis of some well known similarity measures. Journal of the American Society for Information Science and Technology, 60(8), 1635–1651.

被引用紀錄


蔡欣倫(2020)。運用CiteSpace繪製與探索台灣期刊資料庫之能源教育與素養知識圖譜科學與人文研究7(2),268-281。https://doi.org/10.6535/JSH.202002_7(2).0002
余義箴、程紹同、張惠萍(2021)。臺灣運動管理學研究趨勢之探討-2012-2020中華體育季刊35(3),137-144。https://doi.org/10.6223/qcpe.202109_35(3).0001

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