Beyond traditional metrics: Using automated log coding to understand 21st century learning online

Denise Nacu, Caitlin K. Martin, Michael Schutzenhofer, Nichole Pinkard

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

5 Scopus citations

Abstract

While log analysis in massively open online courses and other online learning environments has mainly focused on traditional measures, such as completion rates and views of course content, research is responding to calls for analytic frameworks that are more reflective of social learning models. We introduce a generalizable approach to automatically code log data that highlights educator support roles and student actions that are consistent with recent conceptualizations of 21st century learning, such as creative production, self-directed learning, and social learning. Here, we describe details of a log-coding framework that builds from prior mixed method studies of the use of iRemix, an online social learning network, by middle school youth and adult educators in blended learning contexts.

Original languageEnglish (US)
Title of host publicationL@S 2016 - Proceedings of the 3rd 2016 ACM Conference on Learning at Scale
PublisherAssociation for Computing Machinery, Inc
Pages197-200
Number of pages4
ISBN (Electronic)9781450337267
DOIs
StatePublished - Apr 25 2016
Event3rd Annual ACM Conference on Learning at Scale, L@S 2016 - Edinburgh, United Kingdom
Duration: Apr 25 2016Apr 26 2016

Publication series

NameL@S 2016 - Proceedings of the 3rd 2016 ACM Conference on Learning at Scale

Other

Other3rd Annual ACM Conference on Learning at Scale, L@S 2016
CountryUnited Kingdom
CityEdinburgh
Period4/25/164/26/16

    Fingerprint

Keywords

  • 21st century learning
  • Educational data mining
  • Log analysis
  • Online learning
  • Teaching roles

ASJC Scopus subject areas

  • Education
  • Software
  • Computer Science Applications
  • Computer Networks and Communications

Cite this

Nacu, D., Martin, C. K., Schutzenhofer, M., & Pinkard, N. (2016). Beyond traditional metrics: Using automated log coding to understand 21st century learning online. In L@S 2016 - Proceedings of the 3rd 2016 ACM Conference on Learning at Scale (pp. 197-200). (L@S 2016 - Proceedings of the 3rd 2016 ACM Conference on Learning at Scale). Association for Computing Machinery, Inc. https://doi.org/10.1145/2876034.2893413