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  • 标题:Machine Learning Based On Big Data Extraction of Massive Educational Knowledge
  • 本地全文:下载
  • 作者:Abdelladim Hadioui ; Nour-eddine El Faddouli ; Yassine Benjelloun Touimi
  • 期刊名称:International Journal of Emerging Technologies in Learning (iJET)
  • 印刷版ISSN:1863-0383
  • 出版年度:2017
  • 卷号:12
  • 期号:11
  • 页码:151-167
  • 语种:English
  • 出版社:Kassel University Press
  • 摘要:A learning environment generates massive knowledge by means of the services provided in MOOCs. Such knowledge is produced via learning actor interactions. This result is a motivation for researchers to put forward solutions for big data usage, depending on learning analytics techniques as well as the big data techniques relating to the educational field. In this context, the present article unfolds a uniform model to facilitate the exploitation of the experiences produced by the interactions of the pedagogical actors. The aim of proposing the said model is to make a unified analysis of the massive data generated by learning actors. This model suggests making an initial pre-processing of the massive data produced in an e-learning system, and it’s subsequently intends to produce machine learning, defined by rules of measures of actors knowledge relevance. All the processing stages of this model will be introduced in an algorithm that results in the production of learning actor knowledge tree.
  • 其他摘要:A learning environment generates massive knowledge by means of the services provided in MOOCs. Such knowledge is produced via learning actor interactions. This result is a motivation for researchers to put forward solutions for big data usage, depending on learning analytics techniques as well as the big data techniques relating to the educational field. In this context, the present article unfolds a uniform model to facilitate the exploitation of the experiences produced by the interactions of the pedagogical actors. The aim of proposing the said model is to make a unified analysis of the massive data generated by learning actors. This model suggests making an initial pre-processing of the massive data produced in an e-learning system, and it’s subsequently intends to produce machine learning, defined by rules of measures of actors knowledge relevance. All the processing stages of this model will be introduced in an algorithm that results in the production of learning actor knowledge tree.
  • 关键词:learning analytics;operational data;machine learning;big data analysis;knowledge management
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