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Analysis of Massive E-learning Processes: An Approach Based on Big Association Rules Mining

  • Asma HassaniEmail author
  • Sonia Ayachi GhannouchiEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 931)

Abstract

In today’s learning environments (MOOCs), process learning in highly dynamic. This dynamicity generates a large volume of data describing the handling of such processes. Mining that data is a powerful discipline for getting valuable insights. Thus big data mining becomes more and more an integral part of handling a business process management (BPM) project. Furthermore, using data mining outputs to extend process model with additional knowledge allows to provide more details for future process improvement. In this paper we aim to apply data mining techniques (Association rules mining) to recorded data in the context of massive learning process.

Keywords

Learning process MOOCs Analytics BPM Association rules mining Big data 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.ISITCom Hammam Sousse, RIADI Laboratory, ENSI ManoubaManoubaTunisia
  2. 2.ISG Sousse, RIADI Laboratory, ENSI ManoubaManoubaTunisia

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