MORPH: Supporting the integration of learning analytics at institutional level

Zoran Jeremic, Vive Kumar, Sabine Graf

Research output: Chapter in Book/Report/Conference proceedingPublished Conference contributionpeer-review

1 Citation (Scopus)

Abstract

While there is high potential in using learning analytics to provide educational institutions as well as teachers and learners with actionable information and improve learning experiences, currently only very few learning analytics tools are actually used in educational institutions. In this paper, we introduce MORPH, a platform that facilitates the integration of learning analytics modules and tools into institutional learning systems. MORPH provides a robust distributed architecture which combines batch, stream and real-time data processing using a parallel processing model to enable and support efficient processing of large amounts of data. Furthermore, it provides common management and administration features that enable the seamless integration of learning analytics research modules and tools into existing institutional learning systems.

Original languageEnglish
Title of host publicationLAK 2017 Conference Proceedings - 7th International Learning Analytics and Knowledge Conference
Subtitle of host publicationUnderstanding, Informing and Improving Learning with Data
Pages596-597
Number of pages2
ISBN (Electronic)9781450348706
DOIs
Publication statusPublished - 13 Mar. 2017
Event7th International Conference on Learning Analytics and Knowledge, LAK 2017 - Vancouver, Canada
Duration: 13 Mar. 201717 Mar. 2017

Publication series

NameACM International Conference Proceeding Series

Conference

Conference7th International Conference on Learning Analytics and Knowledge, LAK 2017
Country/TerritoryCanada
CityVancouver
Period13/03/1717/03/17

Keywords

  • Batch processing
  • Dashboards
  • Data streaming
  • Institutional learning environments
  • Learning analytics
  • Real-time processing

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