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 language | English (US) |
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Title of host publication | 12th International Conference of the Learning Sciences, ICLS 2016 |
Subtitle of host publication | Transforming Learning, Empowering Learners, Proceedings |
Editors | Chee-Kit Looi, Joseph L. Polman, Peter Reimann, Ulrike Cress |
Publisher | International Society of the Learning Sciences (ISLS) |
Pages | 1033-1040 |
Number of pages | 8 |
Volume | 2 |
ISBN (Electronic) | 9780990355083 |
State | Published - 2016 |
Event | 12th International Conference of the Learning Sciences: Transforming Learning, Empowering Learners, ICLS 2016 - Singapore, Singapore Duration: Jun 20 2016 → Jun 24 2016 |
Other
Other | 12th International Conference of the Learning Sciences: Transforming Learning, Empowering Learners, ICLS 2016 |
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Country/Territory | Singapore |
City | Singapore |
Period | 6/20/16 → 6/24/16 |
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