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Comparative Study of Discipline Evaluation Based on Bibliometrics and Topic Detection Considering the Education Disciplines of China, the U.S., the U.K., and Australia |
Wang Nan, Ma Qianchun |
College of Education, Capital Normal University, Beijing 100048 |
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Abstract Since the introduction of the “double first-class”, the academic community have been following the concept that the foundation obtained from a first-class university inculcates discipline. Further, research on discipline evaluation, particularly the evaluation methods and tools employed, has attracted considerable attention. This study compares the productivity and impact of research outcomes and topics in the discipline of education of China (excluding Hong Kong, Macau, and Taiwan), the U.S., the U.K., and Australia from 2013 to 2018, using bibliometrics indicators and research topic detection analyses. The research findings are as follows. A gap still exists between China and the U.S., the U.K, and Australia regarding research competitiveness in the discipline of education. First, compared with the U.S., the U.K., and Australia, the productivity and impact of research outcomes are dissatisfactory in China. Second, the research field is narrow; however, China monitors the global hot spots. Third, China has published the highest number of papers in the topics of engineering talent training and migrant and left-behind children in China. The paper suggests that the bibliometrics indicators of scientific research output and research topic detection methods could be further combined based on the characteristics of different disciplines. In this manner, we can better analyze the advantages and disadvantages of disciplines, evaluate the competitiveness of disciplines, and then serve help develop these disciplines.
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Received: 12 December 2019
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1 国务院关于印发统筹推进世界一流大学和一流学科建设总体方案的通知[EB/OL]. (2015-11-05) [2019-03-10]. http://www.gov.cn/zhengce/content/2015-11/05/content_10269.htm. 2 教育部、财政部、国家发展改革委关于公布世界一流大学和一流学科建设高校及建设学科名单的通知[EB/OL]. (2017-09-21) [2019-03-10].http://www.moe.gov.cn/srcsite/A22/moe_843/201709/ t20170921_314942.html. 3 谢维和. “双一流”建设与教育学的责任[J]. 探索与争鸣, 2016(7): 23-25. 4 周光礼, 武建鑫. 什么是世界一流学科[J]. 中国高教研究, 2016(1): 65-73. 5 董琳. 使用文献计量方法开展学科评价[J]. 情报杂志, 2009, 28(9): 65-68. 6 邱均平, 马瑞敏. 基于CSSCI的图书馆、情报与档案管理一级学科文献计量评价研究[J]. 中国图书馆学报, 2006, 32(1): 24-29. 7 夏玉华, 曹南灵, 亓靖涛. 基于SciVal的交叉学科竞争力评价指标研究[J]. 科技情报开发与经济, 2014(18): 99-101. 8 马春晖, 张南, 周晓丽, 等. 基于Scopus和SciVal的国内外高校食品科学研究现状分析[J]. 食品科学技术学报, 2016, 34(4): 54-60. 9 Pauna V H, Buonocore E, Renzi M, et al. The issue of microplastics in marine ecosystems: A bibliometric network analysis[J]. Marine Pollution Bulletin, 2019, 149: 110612. 10 Brimblecombe P, Grossi C M. The bibliometrics of atmospheric environment[J]. Atmospheric Environment, 2009, 43(1): 9-12. 11 郑文晖. 文献计量法与内容分析法的比较研究[J]. 情报杂志, 2006, 25(5): 31-33. 12 宋丽萍. REF与科研评价趋向[J]. 图书情报工作, 2011, 55(22): 60-63, 100. 13 安源, 张玲. 文献计量学在我国图书情报领域的应用研究进展综述[J]. 图书馆, 2014(5): 63-68. 14 李秀霞, 程结晶, 韩霞. 发文趋势与引文趋势融合的学科研究主题优先级排序——以我国情报学学科主题为例[J]. 图书情报工作, 2019, 63(11): 88-95. 15 李秀霞, 宋凯. STCF值: 基于研究主题的学术文献影响力评价新指标[J]. 图书情报工作, 2018, 62(20): 88-94. 16 刘自强, 王效岳, 白如江. 多维度视角下学科主题演化可视化分析方法研究——以我国图书情报领域大数据研究为例[J]. 中国图书馆学报, 2016, 42(6): 67-84. 17 崔宇红, 王飒, 高晓巍, 等. 基于全域微观模型的研究前沿主题探测和特征分析[J]. 图书情报工作, 2018, 62(15): 75-82. 18 颜端武, 苏琼, 张馨月. 基于时序主题关联演化的科学领域前沿探测研究[J]. 情报理论与实践, 2019, 42(7): 144-150. 19 周利琴, 徐健, 巴志超, 等. 基于SNA和DMR方法的高血压主题探测与演化趋势比较研究[J]. 图书情报工作, 2018, 62(13): 82-91. 20 严承希, 王军, 李晓杰. 基于优化随机游走模型的文本热点主题探测研究[J]. 情报科学, 2018, 36(1): 118-123. 21 Marshall E A. Defining population problems: Using topic models for cross-national comparison of disciplinary development[J]. Poetics, 2013, 41(6): 701-724. 22 Song M, Heo G E, Lee D. Identifying the landscape of Alzheimer’s disease research with network and content analysis[J]. Scientometrics, 2015, 102(1): 905-927. 23 最好大学网. 软科世界一流学科排名2018-教育学[EB/OL]. [2019-04-01]. http://www.zuihaodaxue.com/subject-ranking-2018/ education.html. 24 QS Top Universities. QS world university rankings by subject 2018: Education[EB/OL]. [2019-04-01]. https://www.topuniversi ties.com/university-rankings/university-subject-rankings/2018/ed ucation-training. 25 Times Higher Education. The 2019 times higher education world university rankings by subject: Education[EB/OL]. [2019-04-02]. https://www.timeshighereducation.com/.world-university-rankin gs/2019/subject-ranking/education# !/page/0/length/25/sort_by/rank/ sort_order/asc/cols/stats. 26 PreviewScopus. Scopus检索平台[EB/OL]. [2019-02-15]. https://www.scopus.com/. 27 Scival. SciVal检索平台[EB/OL]. [2019-03-05]. https://scival.com/. 28 Colledge L, Verlinde R. Elsevier research intelligence: SciVal version 1.02[R]. Amsterdam: Elsevier B.V., 2018: 49-50. 29 Elsevier. CiteScore Metrics[EB/OL]. [2019-03-05]. https://www.elsevier.com/__data/.assets/pdf_file/0010/276949/Citescore-metrics- Brochure.pdf. 30 Elsevier. Topic prominence in science [EB/OL]. [2019-03-05]. https://www.elsevier.com/solutions/scival/releases/topic-prominence- in-science#methodology. 31 Klavans R, Boyack K W. Research portfolio analysis and topic prominence[J]. Journal of Informetrics, 2017, 11(4): 1158-1174. 32 王淑妹. 面向卓越性的百分位数指标应用研究[D]. 北京: 北京理工大学, 2015. 33 栾春娟. 基于SciVal中外同类型高校评价指标选择与应用——实证分析大连理工大学与麻省理工学院[J]. 科技与管理, 2016, 36(3): 3-9. 34 秦奋, 高健. 基于Scopus数据库的Altmetrics指标与引文计量对比分析[J]. 情报学报, 2019, 38(4): 377-383. 35 邱均平, 叶晓峰, 熊尊妍. 国外索引工具发展趋势研究——以Scopus为例[J]. 情报科学, 2009, 27(6): 801-807. 36 田稷, 何晓薇, 余敏杰, 等. C9联盟与世界一流大学联盟信息计量学特征研究[J]. 情报学报, 2018, 37(1): 31-42. 37 Katz J S, Hicks D. How much is a collaboration worth? A calibrated bibliometric model[J]. Scientometrics, 1997, 40(3): 541-554. 38 Altbach P G. The costs and benefits of world-class universities [J]. Academe, 2004, 90(1): 20-23. |
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