What can we learn from Facebook activity? Using social learning analytics to observe new media literacy skills

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

Abstract

Social media platforms such as Facebook are now a ubiquitous part of everyday life for many people. New media scholars posit that the participatory culture encouraged by social media gives rise to new forms of literacy skills that are vital to learning. However, there have been few attempts to use analytics to understand the new media literacy skills that may be embedded in an individual's participation in social media. In this paper, I collect raw activity data that was shared by an exploratory sample of Facebook users. I then utilize factor analysis and regression models to show how (a) Facebook members' online activity coalesce into distinct categories of social media behavior and (b) how these participatory behaviors correlate with and predict measures of new media literacy skills. The study demonstrates the use of analytics to understand the literacies embedded in people's social media activity. The implications speak to the potential of social learning analytics to identify and predict new media literacy skills from data streams in social media platforms.

Original languageEnglish (US)
Title of host publicationLAK 2013
Subtitle of host publication3rd International Conference on Learning Analytics and Knowledge
Pages135-144
Number of pages10
DOIs
StatePublished - 2013
Event3rd International Conference on Learning Analytics and Knowledge, LAK 2013 - Leuven, Belgium
Duration: Apr 8 2013Apr 12 2013

Publication series

NameACM International Conference Proceeding Series

Other

Other3rd International Conference on Learning Analytics and Knowledge, LAK 2013
CountryBelgium
CityLeuven
Period4/8/134/12/13

Keywords

  • learning analytics
  • literacy
  • new media literacy
  • social learning analytics
  • social media

ASJC Scopus subject areas

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

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