AAT - A tool for accessing and analysing students' behaviour data in learning systems

Sabine Graf, Cindy Ives, Nazim Rahman, Arnold Ferri

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

47 Citations (Scopus)

Abstract

In online learning environments, teachers and course designers often get little feedback about how students actually interact with and learn in online courses. Most of the learning systems used by educational institutions store comprehensive log data associated with students' behaviours and actions. However, these systems typically reveal or report on very general and limited information based on this data. In order to provide teachers and course designers with more detailed and meaningful information about students' behaviour and their use of learning resources within online courses, an analytics tool has been developed. The tool incorporates functionality to access and analyse data related to students' behaviours in learning systems. This tool can provide valuable information about students' learning processes allowing the identification of difficult or inappropriate learning material, and can therefore significantly contribute to the design of improved student support activities and resources.

Original languageEnglish
Title of host publicationLAK'11 - Proceedings of the 1st International Conference on Learning Analytics and Knowledge
Pages174-179
Number of pages6
DOIs
Publication statusPublished - 2011
Event1st International Conference on Learning Analytics and Knowledge, LAK'11 - Banff, AB, Canada
Duration: 27 Feb. 20111 Mar. 2011

Publication series

NameACM International Conference Proceeding Series

Conference

Conference1st International Conference on Learning Analytics and Knowledge, LAK'11
Country/TerritoryCanada
CityBanff, AB
Period27/02/111/03/11

Keywords

  • Academic analytics
  • Data extraction and analysis
  • Learning systems

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