Connecting data with student support actions in a course: A hands-on tutorial

Abelardo Pardo, Roberto Martinez-Maldonado, Simon Buckingham Shum, Jurgen Schulte, Simon McIntyre, Dragan Gasevic, Jing Gao, George Siemens

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

Abstract / Description of output

The amount of data extracted from learning experiences has grown at an astonishing pace both in depth due to the increasing variety of data sources, and in breath with courses now being offered to massive student cohorts. However, in this emerging scenario instructors are now facing the challenge of connecting the knowledge emerging from data analysis with the provision of meaningful support actions to students within the context of an instructional design.
The objective of this tutorial is to give attendees a set of hypothetical scenarios in which the knowledge extracted from a learning experience needs to be used to provide frequent personalized feedback to students.
Original languageEnglish
Title of host publicationProceedings of the 7th International Conference on Learning Analytics and Knowledge (LAK 2017)
PublisherACM Press
Pages522-523
Number of pages2
ISBN (Electronic)978-1-4503-4870-6
DOIs
Publication statusPublished - 13 Mar 2017

Publication series

NameACM International Conference Proceeding Series

Keywords / Materials (for Non-textual outputs)

  • learning analytics
  • feedback
  • predictive analytics
  • instructional design
  • student support

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