Qualitative analysis of video data: Standards and heuristics

Kay E. Ramey, Dionne N. Champion, Elizabeth B. Dyer, Danielle T. Keifert, Christina Krist, Peter Meyerhoff, Krystal Villanosa, Jaakko Hilppö

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

16 Scopus citations

Abstract

Video research is an increasingly important method in the learning sciences. Video provides unique analytical affordances to researchers but also presents unique tensions, many of which have not yet been adequately addressed in the literature. The authors of this symposium draw on their diverse experiences, analyzing a variety of video corpuses, to provide theoretical and methodological standards and heuristics for the process of video analysis. We focus on three themes central to the process of video analysis that would benefit from increased theoretical and methodological attention: transcription tensions, defining the unit of analysis, and representing context. We discuss how our approaches to video analysis are framed by theory and how we have applied them to specific datasets, to answer a variety of research questions. In doing so, we make explicit some crosscutting methodological norms and invite continued discussion about these norms from multiple analytic traditions.

Original languageEnglish (US)
Title of host publication12th International Conference of the Learning Sciences, ICLS 2016
Subtitle of host publicationTransforming Learning, Empowering Learners, Proceedings
EditorsChee-Kit Looi, Joseph L. Polman, Peter Reimann, Ulrike Cress
PublisherInternational Society of the Learning Sciences (ISLS)
Pages1033-1040
Number of pages8
Volume2
ISBN (Electronic)9780990355083
StatePublished - 2016
Event12th International Conference of the Learning Sciences: Transforming Learning, Empowering Learners, ICLS 2016 - Singapore, Singapore
Duration: Jun 20 2016Jun 24 2016

Other

Other12th International Conference of the Learning Sciences: Transforming Learning, Empowering Learners, ICLS 2016
Country/TerritorySingapore
CitySingapore
Period6/20/166/24/16

Funding

This material is based upon work supported by the Institute of Education Sciences (U.S. Department of Education R205B080027); the National Science Foundation (grants DRL-1348800, DRL-1433724, SBE-0541957, SMA-0835854, ESI-1020316, and IIS-1123574); the National Science Foundation Graduate Research Fellowship Program (grant DGE-0824162); the AERA-MET Dissertation Fellowship Program; the NAEd/Spencer Dissertation Fellowship Program; and the Institute for Sustainability and Energy at Northwestern University. Contents are solely the responsibility of the authors and do not necessarily represent the official views of the organizations above.

Keywords

  • Analysis
  • Data representation
  • Methods
  • Qualitative
  • Video

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Education

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