首页> 外文期刊>International Journal of Electrical and Computer Engineering >Data science for digital culture improvement in higher education using K-means clustering and text analytics
【24h】

Data science for digital culture improvement in higher education using K-means clustering and text analytics

机译:使用K-Means聚类和文本分析的高等教育数字文化的数据科学

获取原文
获取外文期刊封面目录资料

摘要

This study aims to investigate the meaningful pattern that can be used to improve digital culture in higher education based on parameters of the technology acceptance model (TAM). The methodology used is the data mining technique with K-means algorithm and text analytics. The experiment using questionnaire data with 2887 respondents in Universitas Islam Negeri (UIN) Sunan Gunung Djati Bandung. The data analysis and clustering result show that the perceived usefulness and behavioral intention to use information systems are above the normal value, while the perceived ease of use and actual system use is quite low. Strengthened with text analytics, this research found that the EDA and K-means result in harmony with the hope or desire of academic society the information system implementation. This research also found how important the socialization and guidance of information systems, especially the new one information system, in order to improve digital culture in higher education.
机译:本研究旨在调查可用于改善高等教育数字文化的有意义的模式,基于技术验收模型(TAM)的参数。使用的方法是具有K-Means算法和文本分析的数据挖掘技术。实验在Universitas Islam Negeri(UIN)Sunan Gunung Djati Bandung中有关2887名受访者的研究。数据分析和聚类结果表明,使用信息系统的感知有用性和行为意图高于正常值,而感知的易用性和实际系统使用相当低。随着文本分析加强,这项研究发现,EDA和K-Meather与学术社会的希望或愿望和谐导致信息系统实施。本研究还发现,信息系统,特别是新的一个信息系统的社会化和指导,以改善高等教育的数字文化。

著录项

获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号