Online change detection for monitoring individual student behavior via clickstream data on E-book system

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

Abstract

We propose a new change detection method using clickstream data collected through an e-Book system. Most of the prior work has focused on the batch processing of clickstream data. In contrast, the proposed method is designed for online processing, with the model parameters for change detection updated sequentially based on observations of new click events. More specifically, our method generates a model for an individual student and performs minute-by-minute change detection based on click events during a classroom lecture. We collected clickstream data from four face-to-face lectures, and conducted experiments to demonstrate how the proposed method discovered change points and how such change points correlated with the students’ performances.

Original languageEnglish
Title of host publicationProceedings of the 8th International Conference on Learning Analytics and Knowledge
Subtitle of host publicationTowards User-Centred Learning Analytics, LAK 2018
PublisherAssociation for Computing Machinery
Pages446-450
Number of pages5
ISBN (Electronic)9781450364003
DOIs
Publication statusPublished - Mar 7 2018
Event8th International Conference on Learning Analytics and Knowledge, LAK 2018 - Sydney, Australia
Duration: Mar 5 2018Mar 9 2018

Publication series

NameACM International Conference Proceeding Series

Conference

Conference8th International Conference on Learning Analytics and Knowledge, LAK 2018
Country/TerritoryAustralia
CitySydney
Period3/5/183/9/18

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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