图书馆杂志

图书馆杂志 ›› 2020, Vol. 39 ›› Issue (9): 30-37.

• 阅读推广学坛 • 上一篇    下一篇

21世纪以来青少年阅读的国际研究主题演化分析

刘艳华 华薇娜 谭华军 刘 婧   

  • 出版日期:2020-09-17 发布日期:2020-09-17
  • 作者简介:刘艳华 女,南京中医药大学卫生经济管理学院信息 管理系,讲师。研究方向:科学计量学人文社会科学 研究评价。作者贡献:选题拟定、架构设计、初稿写 作与统稿改定。E-mail: zhengdalyh@126.com 江苏 南京 210023 华薇娜 女,南京大学信息管理学院,教授。研究 方向:信息检索、人文社会科学研究评价。作者贡 献:数据检索审核与确定、文章修改。 江苏南 京 210023 谭华军 女,南京大学信息管理学院,副教授。研究 方向:阅读文化学。作者贡献:数据、文献资料发掘 与文章修改。 江苏南京 210023 刘  婧 女,南京邮电大学管理学院,副教授。研究 方向:青少年阅读。作者贡献:选题讨论商定、文稿 校核。 江苏南京 210023

Theme Evolution of International Research Papers on Teenager’s Reading since the 21stCentury

Liu Yanhua, Hua WeinaTan Huajun, Liu Jing   

  • Online:2020-09-17 Published:2020-09-17

摘要: ? 基于WoS检索2000-2017青少年阅读文献1 578篇,以关键词为分析单元,共词分析和聚类分析为方法,SciMAT为图谱绘制工具,揭示主题的演化路径。研究发现:两条重要的演化路径阅读障碍和理解能力,经学习障碍、技能、教导、阅读理解、语音意识、个体差异等演化过程再生为阅读障碍、理解能力、阅读理解,持续成为热点方向;阅读动机经成绩、动机演化为内在动机的路径已趋于成熟;性别差异、个体、教学策略等专业主题在不同时期出现并很快消亡。

关键词: 青少年阅读 主题演化 共词分析 聚类分析 SciMAT

Abstract: Based on WoS, we collected a total of 1,578 papers related to adolescent reading from 2000 to 2017. By selecting keywords as the units of analysis, using co-word analysis and cluster analysis as methods, and adopting SciMAT as the knowledge mapping tool, this paper identified the theme evolution paths of teenager’s reading since the 21st century. Research demonstrated that the most important evolution paths were “reading-disabilities” and “comprehension”. The two themes went through the process of“learningdisabilities”, “skills”, “instruction”, “reading-comprehension”, “phonological-awareness”, “individualdifferences”, and finally changed into themes of “reading-disabilities”, “comprehension” and “readingcomprehension”, which continued to be hot topics. The evolution path from “reading-motivation” through “achievement” and “motivation” to “intrinsic-motivation” hasbecome mature, whereas the professional themes, such as “gender-differencfs”, “indivduals” and “instructionai-strategies”, emerged at different times and soon disappeared.

Key words: Teenager’s reading, Theme evolution, Co-word analysis, Cluster analysis, SciMAT