图书情报工作

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2023 , Vol. 67 >Issue 13: 142 - 151

DOI: https://doi.org/10.13266/j.issn.0252-3116.2023.13.015

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“数字中国”建设背景下高校学生计算思维培养研究：热点、趋势与建议

  • 马晓飞 ,
  • 张尔赫
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  • 北京邮电大学经济管理学院 北京 100876
马晓飞，副教授，博士，博士生导师，E-mail：maxiaofei@bupt.edu.cn；张尔赫，本科生。

收稿日期: 2023-03-22

  修回日期: 2023-04-26

  网络出版日期: 2023-07-11

基金资助

本文系教育部人文社会科学研究青年基金项目“多重异质条件下政府科技经费投入对产业网络创新绩效的影响机制与优化路径研究”（项目编号：19YJC630120）和中国工程院战略咨询项目“人工智能应用技术自主可控与产业生态发展战略研究”（项目编号：2019GCYGUO）研究成果之一。

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Research on the Cultivation of Computational Thinking among College Students under the background of “Digital China”: Hot Spots, Trends and Suggestions

  • Ma Xiaofei Zhang Erhe
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  • School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100876

Received date: 2023-03-22

  Revised date: 2023-04-26

  Online published: 2023-07-11

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摘要

[目的/意义] 我国高校学生计算思维能力培养途径不清晰，培养效果不显著的问题仍普遍存在。探索符合“数字中国”建设要求的高校学生计算思维培养途径至关重要。[方法/过程] 借助 CiteSpace 知识图谱工具，对2006 年 3 月至 2022 年 12 月发表于 SSCI 和 CSSCI 来源期刊的 940 篇计算思维领域的文献进行计量分析，挖掘适合高校学生的计算思维培养途径。[结果/结论] 研究发现：①计算思维培养研究方向主要聚焦于解决现实问题；②计算思维培养研究内容更关注跨学科交叉融合培养；③非计算机专业的计算思维培养课程教学形式和授课领域单一，缺乏体系化的课程设计；④计算思维培养研究力度国内总体低于国外。基于上述发现，从培养导向、学科交叉、课程设计、国际合作 4 个方面提出培养高校学生计算思维的具体建议。

关键词： 数字中国; 人才培养; 计算思维; 文献计量

本文引用格式

马晓飞 , 张尔赫 . “数字中国”建设背景下高校学生计算思维培养研究：热点、趋势与建议[J]. 图书情报工作, 2023 , 67(13) : 142 -151 . DOI: 10.13266/j.issn.0252-3116.2023.13.015

Abstract

[Purpose/Significance] The training of computational thinking ability of Chinese college students is not clear, and problems that the training effect is not obvious, still exist. It is very important to explore ways to cultivate computational thinking of college students that meet the requirements of “Digital China” construction. [Method/Process] By means of CiteSpace knowledge graph tool, this paper made a quantitative analysis of 940 literatures in the field of computational thinking published in SSCI and CSSCI source journals from March 2006 to December 2022, so as to find out suitable ways to cultivate computational thinking for college students. [Result/Conclusion] The research findings are as follows: ① The research direction of computational thinking training mainly focuses on solving practical problems. ② The research content of computational thinking training is more concerned with interdisciplinary fusion training. ③ The teaching form and teaching area of the training course of computational thinking for non-computer majors are single, and the lack of systematic course design. ④ The research intensity of computational thinking training in China is generally lower than that in foreign countries. Based on the above findings, this paper puts forward some suggestions on training college students’ computational thinking from four aspects: training orientation, interdisciplinary, curriculum design and international cooperation.

Key words： digital China; personnel training; computational thinking; bibliometric

参考文献

[1] HSU T C, CHANG S C, HUNG Y T. How to learn and how to teach computational thinking: suggestions based on a review of the literature[J]. Computers & education, 2018, 126: 296-310.
[2] WING J M. Computational thinking: what and why? [EB/OL]. [2023-04-17]. https://www.cs.cmu.edu/~CompThink/resources/TheLinkWing.pdf.
[3] SHUTE V J, SUN C, ASBELL-CLARKE J. Demystifying computational thinking[J]. Educational research review, 2017, 22(1): 142-158.
[4] 张立国, 王国华. 计算思维: 信息技术学科核心素养培养的核心议题[J]. 电化教育研究, 2018, 39(5): 115-121.
[5] WING J M. Computational thinking[J]. Communications of the ACM, 2006, 49(3): 33-35.
[6] KITE V, PARK S, WIEBE E. The code-centric nature of computational thinking education: a review of trends and issues in computational thinking education research[J]. SAGE open, 2021, 11(2): 1501-1514.
[7] 于颖, 周东岱, 于伟. 计算思维的意蕴解析与结构建构[J]. 现代教育技术, 2017, 27(5): 60-66.
[8] 邓磊, 战德臣, 姜学锋. 新工科教育中计算思维能力培养的价值探索与实践[J]. 高等工程教育研究, 2020(2): 49-53.
[9] WEINTROP D, BEHESHTI E, HORN M, et al. Defining computational thinking for mathematics and science classrooms[J]. Journal of science education and technology, 2016, 25(1): 127- 147.
[10] 王佑镁, 南希烜, 李宁宇, 等. 编程韧性：数字时代计算思维培养的新议题[J]. 现代教育技术, 2023, 33(2): 14-23.
[11] 任友群. 为数字中国培养“ 计算思维+” 新一代[J]. 中国信息技术教育, 2018(5): 7.
[12] 数字中国建设整体布局规划[EB/OL]. [2023-04-27]. http://www.gov.cn/zhengce/2023-02/27/content_5743484.htm.
[13] 关于构建数据基础制度更好发挥数据要素作用的意见[EB/ OL]. [2023-04-28]. http://www.gov.cn/zhengce/2022-12/19/content_5732695.htm.
[14] 马费成, 吴逸姝, 卢慧质. 数据要素价值实现路径研究[J]. 信息资源管理学报, 2023, 13(2): 4-11.
[15] 吕洁, 李瑛, 杜晶. 以计算思维为导向的大学计算机基础课程改革的实践与探索[J]. 计算机工程与科学, 2019, 41(S1): 1-5.
[16] 房敏, 孙颖, 陈伟, 等. 师范生计算思维发展现状与影响因素 —— 基于津冀鲁三地高校的调查[J]. 开放教育研究, 2021, 27(4): 98-110.
[17] 范文翔, 张一春, 李艺. 国内外计算思维研究与发展综述[J]. 远程教育杂志, 2018, 36(2): 3-17.
[18] 孙立会, 王晓倩. 计算思维培养阶段划分与教授策略探讨 —— 基于皮亚杰认知发展阶段论[J]. 中国电化教育, 2020(3): 32-41.
[19] 杨文正. 学习情境链创设视域下的计算思维培养模式[J]. 现代远程教育研究, 2021, 33(5): 72-81.
[20] 陈赞安, 李宁宇, 尹以晴, 等. 从算法到参与构建计算模型: 人机协同视域下计算思维的内涵演进与能力结构[J]. 远程教育杂志, 2021,39(4): 34-41.
[21] 冯友梅, 王珊, 王昕怡, 等. 支持我国信息技术课程评价体系构建的计算思维描述框架设计[J]. 电化教育研究, 2022, 43(6): 115-121.
[22] LEE I, MALYN-SMITTH J. Computational thinking integration patterns along the framework defining computational thinking from a disciplinary perspective[J]. Journal of science education and technology, 2020, 29(1): 9-18.
[23] 郁晓华, 王美玲. 流程图支持下的计算思维培养实践研究[J]. 中国远程教育, 2019(9): 83-91.
[24] 郁晓华, 王美玲. 计算思维培养之路还有多远?—— 基于计算思维测评视角[J]. 开放教育研究, 2020, 26(1): 60-71.
[25] COBAN E, KORKMAZ O. An alternative approach for measuring computational thinking: performance-based platform[J]. Thinking skills and creativity, 2021, 42(7): 100929.
[26] 丁世强, 王平升, 赵可云, 等. 面向计算思维能力发展的项目式教学研究[J]. 现代教育技术, 2020, 30(9): 49-55.
[27] 杨刚, 张银荣, 徐佳艳, 等. 图形化编程环境下建模方式对学生计算思维与编程行为的影响研究[J]. 电化教育研究, 2022, 43(4): 107-115.
[28] CHEN K Z, CHI H H. Novice young board-game players’ experience about computational thinking[J]. Interactive learning environments, 2022, 30(8): 1375-1387.
[29] 李杰, 陈超美. CiteSpace：科技文本挖掘及可视化[M]. 北京： 首都经济贸易大学出版社， 2016.
[30] 肖海林, 董慈慈. 突破性技术创新研究: 现状与展望—— 基于 SSCI和CSSCI期刊的文献计量分析[J]. 经济管理, 2020, 42(2): 192-208.
[31] 盛宇平, 王树贵, 盛春蕾. 作者机构指标纳入学术期刊评价重要指标的探讨[J]. 现代情报, 2018, 38(5): 117-119, 139.
[32] ROMAN-GONZALEZR M, PEREZ-GONZALEZ J C, JIMENEZ-FERNANDEZ C. Which cognitive abilities underlie computational thinking? criterion validity of the computational thinking test[J]. Computers in human behavior, 2017, 72(7): 678- 691.
[33] KORKMAZ O, CAKIR R, OZDEN M Y. A validity and reliability study of the computational thinking scales (CTS)[J]. Computers in human behavior, 2017, 72(7): 558-569.
[34] DURAK H Y, SARITEPECI M. Analysis of the relation between computational thinking skills and various variables with the structural equation model[J]. Computers & education, 2018, 116(1): 191-202.
[35] TANG X D, YIN Y, LIN Q, et al. Assessing computational thinking: a systematic review of empirical studies[J]. Computers & education, 2020, 148(5): 103798.
[36] ANGELI C, GIANNAKOS M. Computational thinking education: issues and challenges[J]. Computers in human behavior, 2020, 105(4): 106185.
[37] FLOREZ F B, CASALLAS R, HERNANDEZ M, et al. Changing a generation’s way of thinking: teaching computational thinking through programming[J]. Review of educational research, 2017, 87(4): 834-860.
[38] ATMATZIDOU S, DEMETRIADIS S. Advancing students’ computational thinking skills through educational robotics: a study on age and gender relevant differences[J]. Robotics and autonomous systems, 2016, 75(1): 661-670.
[39] 谢卫红, 李忠顺, 李秀敏, 等. 数字化创新研究的知识结构与拓展方向[J]. 经济管理, 2020, 42(12): 184-202.
[40] CHEN C. CiteSpace II: detecting and visualizing emerging trends and transient patterns in scientific literature[J]. Journal of the American Society for Information Science and Technology, 2006, 57(3): 359-377.
[41] 陈鹏, 黄荣怀, 梁跃, 等. 如何培养计算思维—— 基于2006- 2016年研究文献及最新国际会议论文[J]. 现代远程教育研究, 2018(1): 98-112.
[42] MOUZA C, YANG H, PAN Y C, et al. Resetting educational technology coursework for pre-service teachers: a computational thinking approach to the development of technological pedagogical content knowledge (TPACK)[J]. Australasian journal of educational technology, 2017, 33(3): 61-76.
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