期刊文献+
任意字段
题名或关键词
题名
关键词
文摘
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息

教育领域中的脑-机接口应用:动向与挑战 被引量：1

Brain-computer interface applications in education:Trends and challenges
原文传递
导出
摘要 概述了脑-机接口技术与理念,总结了脑-机接口个体化、实时化和场景化3个重要技术特点;从学习状态识别、学习者个体特质测评和学习障碍干预3方面梳理了脑-机接口在教育领域的研究成果;探讨当前研究存在的问题,从理解、优化现有教育场景和开创新型教育场景等方面展望了脑-机接口未来的应用方向。 This paper reviews the technology and the concept of the brain-computer interface,from the three important technical features:the individualization,the real-time nature and the scenario-based property,as well as the research progresses in education from the three aspects:the learning state recognition,the individual learner trait assessment and the learning disability intervention.The problems of existing researches are then analyzed.Finally,the future application directions of the brain-computer interface are discussed in terms of understanding and optimizing the existing educational scenarios and creating new educational scenarios.
作者 陈菁菁 王非 高小榕 张羽 李卓然 张丹 CHEN Jingjing;WANG Fei;GAO Xiaorong;ZHANG Yu;LI Zhuoran;ZHANG Dan(Department of Psychology,School of Social Sciences,Tsinghua University,Beijing 100084,China;Tsinghua Laboratory of Brain and Intelligence,Tsinghua University,Beijing 100084,China;Department of Biomedical Engineering,School of Medicine,Tsinghua University,Beijing 100084,China;Institute of Education,Tsinghua University,Beijing 100084,China)
机构地区 清华大学社会科学学院心理学系 清华大学脑与智能实验室 清华大学医学院生物医学工程系 清华大学教育研究院
出处 《科技导报》 CAS CSCD 北大核心 2022年第12期90-101,共12页 Science & Technology Review
基金 国家自然科学基金项目(61977041,6210020370)。
关键词 脑-机接口 个性化教学 认知状态识别 个体测评 认知干预 brain-computer interface personalized instruction cognitive state detection individual trait assessment cognitive intervention
分类号 G434 [文化科学—教育技术学] TN911.7 [电子电信—通信与信息系统]
  • 相关文献

参考文献5

二级参考文献88

  • 1CULNAN M J, ARMSTRONG P K. Information privacy concerns, procedural fairness, and impersonal trust: an empirical investigation[J]. Organization Science, 1999, 10(1): 104-115.
  • 2DINEV T, HART P. Privacy concems and intemet use-a model of trade-off factors[C]//,~cademy of Management. c2003:1-6.
  • 3LI H, SARATHY R, XU H. Understanding situational online informa- tion disclosure as a privacy calculus[J]. Journal of Computer Informa- tion Systems, 2010, 51(1): 62-71.
  • 4KEHR F, KOWATSCH T, WENTZEL D, et al. Blissfully ignorant: the effects of general privacy concerns, general institutional trust, and af- fect in the privacy calculus[J]. Information Systems Journal, 2015, 25(6): 607-635.
  • 5MACHANAVAJJHALA A, KIFER D, GEHRKE J, ~t al. /-diversity: privacy beyond k-anonymity[J]. ACM Transactions on Knowledge Discovery from Data (TKDD), 2007, 1(1): 3.
  • 6AGRAWAL D, AGGARWAL C C. On the design and quantification of privacy preserving data mining algorithms[C]//The 20th ACM SIG- MOD-SIGACT-SIGART Symposium on Principles of Database Sys- tems. ACM, c2001 : 247-255.
  • 7LIU K, KARGUPTA H, RYAN J. Random projection-based multipli- eative data perturbation for privacy preserving distributed data min- ing[J]. IEEE Transactions on Knowledge and Data Engineering, 2006, 18(1): 92-106.
  • 8OLIVEIRA S R M, ZAIANE O R. Privacy preserving clustering by data transformation[C]//The 18th Brazilian Symposium on Databases. c2003:304-318.
  • 9OLIVEIRA S R M, ZAIANE O R. Privacy preserving clustering by object similarity-based representation and dimensionality reduction transformation[C]/Fl'he Workshop on Privacy and Security Aspects of Data Mining. e2004:21-30.
  • 10OLIVEIRA S R M, ZAIANE 0 R. Privacy preserving frequent itemsetmining[C]//The IEEE International Conference on Privacy, Security and Data Mining-Volume 14, Australian Computer Society. c2002: 43-54.

共引文献122

同被引文献16

引证文献1

二级引证文献6

科技导报
2022年 第12期

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