期刊文献+

思想政治教育运用大数据相关关系的哲学反思——基于思想与行为的因果关系 被引量:3

Philosophical Reflection on the Correlation of Big Data in Ideological and Political Education——Based on the Causality of Thought and Behavior
下载PDF
导出
摘要 大数据通过对人的行为之间存在的关系来预测人未来可能发生的行为,而思想政治教育通过分析人的思想动机来预测人未来可能发生的行为。大数据只追问"是什么"而不问"为什么"的思维方式,虽然可以预测人的行为取向,但要从行为趋向中来推导出人的思想动机,则仍然需要运用因果关系。因此,思想政治教育运用大数据可以预测人的行为趋向,但难以运用相关关系来准确预测人的思想动机。 Big data predicts the possible behaviors of people in the future through the correlation between human behaviors,while ideological and political education predicts people's possible behaviors in the future by analyzing people's ideological motivation.Big data only asks"what is"without asking"why",which means that although it can predict people's behavioral orientation,it is still necessary to use causality to derive human ideological motivation from behavioral tendency.Therefore,the use of big data in ideological and political education can predict people's behavioral trends,but it is difficult to use relevant relationships to accurately predict people's ideological motivation.
作者 管爱花 王升臻 GUAN Ai-hua;WANG Sheng-zhen(School of Marxism,Huaiyin Normal University,Huai'an 223300,China)
出处 《广西师范大学学报(哲学社会科学版)》 2019年第1期55-60,共6页 Journal of Guangxi Normal University(Philosophy and Social Sciences Edition)
基金 国家社科基金重点项目"城镇化进程中的农民工组织化研究"(17AZZ015) 河南省教育厅人文社科一般项目"新时代思想政治教育历史使命研究"(2019-ZZJH-379)
关键词 思想政治教育 思想与行为 相关关系 因果关系 the ideological and political education thought and behavior correlation causality
  • 相关文献

参考文献8

二级参考文献73

  • 1孙其昂.政治性:思想政治教育的内容本质[J].南京社会科学,2006(3):56-61. 被引量:57
  • 2康德..《纯粹理性批判》..北京:生活.读书.新知三联书店,,1957..第16,260-261,456页..
  • 3康德.《纯粹理性批判》,邓晓芒译,北京:人民出版社,2004年.
  • 4T. Cass, "A Handler for Big Data," Science, 282 (5389), 1998, p. 636.
  • 5Science. Special online collection: Dealing with data. http: //www. seiencemag, org/site/special/data/, 2011.
  • 6R. Weiss, L. Zgorski, "Obama Administration Unveils ' Big Data' Initiative : Announces MYM200 Million in New R&D Investments", Office of Scierwe and Technology Policy, Washington, DC, 2012.
  • 7S. Leonelli, '" Classificatory Theory in Data-intensive Science: The Case of Open Biomedical Ontologies," International Studies in the Philosophical of Science, 26 (1), 2012, pp. 47 -65.
  • 8W. Pietsch, "Big Data-The New Science of Complexity", 6t Munich-Sydney-Tilbarg Conference on models and Decision, 2013.
  • 9H. Barwick. , The " Four VS " of Big Data, Implementing Information Infrastructure Symposium, http: // www. computerworld, com. au/article/396198/iiis_ four vs big_ data/.
  • 10R. Sarah, "Is There an Astronomer in the House?", Science, 331, 2011, p. 696.

共引文献325

同被引文献44

引证文献3

二级引证文献18

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部