Learner differences in the online context: Introducing a new method

  • Arne Hendrik Schulz
  • , Debora Jeske

Research output: Chapter in Book/Report/Conference proceedingsChapterpeer-review

Abstract

The paper introduces an alternative method to analyze different learning styles among students. This method was developed as an alternative to more traditional methods such as hierarchical cluster analysis. The method was tested using a large data set (n = 868) which included participants completing a small e-module in addition to a small number of measures to assess learner characteristics. The resulting log files were analyzed using the new method. Results were similar to those observed using traditional methods. The method provides a new starting point for subsequent analysis and identification of learner differences using other information such as log files from e-learning and Massive Online Open Courses (MOOCs).

Original languageEnglish
Title of host publicationKey Competencies in ICT and Informatics
Subtitle of host publicationImplications and Issues for Educational Professionals and Management - IFIP WG 3.4/3.7 International Conferences KCICTP and ITEM 2014, Revised Selected Papers
EditorsDon Passey, Arthur Tatnall
PublisherSpringer New York LLC
Pages306-317
Number of pages12
ISBN (Electronic)9783662457696
DOIs
Publication statusPublished - 2014
Externally publishedYes
EventIFIP WG 3.4/3.7 International Conference on Key Competencies in Informatics and Information and Communication Technologies, KCICTP and ITEM 2014 - Potsdam, Germany
Duration: 1 Jul 20144 Jul 2014

Publication series

NameIFIP Advances in Information and Communication Technology
Volume444
ISSN (Print)1868-4238
ISSN (Electronic)1868-422X

Conference

ConferenceIFIP WG 3.4/3.7 International Conference on Key Competencies in Informatics and Information and Communication Technologies, KCICTP and ITEM 2014
Country/TerritoryGermany
CityPotsdam
Period1/07/144/07/14

Keywords

  • Cluster analysis
  • E-learning
  • Learner group differences
  • Learning strategies
  • Log file analysis

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