Video Research in Education
Questions and Guidelines for Researchers and Reviewers
In December 2005 the Data Research and Development Center (DRDC) organized and co-hosted with NSF the second in a series of workshops to enhance capacity to conduct scientific educational and scale-up research: the Video Research in Education Meeting. Chaired by Sharon Derry, the meeting brought together over 40 researchers from a wide range of disciplines to share insights and expertise regarding the use of video research in peer, informal and naturalistic settings; theories and methods for conducting video research on classroom and teacher learning; the use of advanced technologies for video collection, analysis, and archiving; and standards for video coding and analysis. Together these experts considered both the most fundamental and the newly emergent issues facing investigators considering the use of video to develop or to study the impacts of interventions designed to improve educational outcomes:
 When and how can video collection be used to produce data for basic research on teaching and learning processes in classroom settings?
When and how can video collection be used to produce data for basic research on learning in informal settings (including museums, and homes)?
How do people learn with and from video?
What factors need to be taken into account in deciding how to produce and index video recordings?
What factors influence designs for selecting segments of video recordings for analyses?
What considerations shape analysis plans and the selection of analytic tools?
How can studies plan for – and what are the constraints and limitations on – sharing and reporting video work?
An explicit goal of the meeting was to move the field towards identifying best practices and establishing guidelines for video research in education—especially in regards to coding, analyzing, and sharing video data—to be documented in a "white paper" on video research in education. The white paper Guidelines for Video Research in Education: Recommendations from an Expert Panel is now available online as a PDF file. Authored by twelve experts in the use of video for research purposes and enriched by comments and contributions from many others, the Guidelines address important practical, conceptual, and ethical issues investigators face in planning studies that incorporate the use of video (and audio) recordings to capture and transmit data (see Figure 1).
Figure 1. Guidelines for Video Research in Education – contents and contributors
Guidelines for Video Research in Education:
Recommendations from an Expert Panel
Introduction to the Guidelines
Sharon J. Derry
Strategies for Video Recording: Fast, Cheap, and (Mostly) in Control
Rogers Hall
Selection in Video
Ricki Goldman, Frederick Erickson, Jay Lemke, Sharon J. Derry
Analyzing Data Derived from Video Records
Brigid Barron, Randi A. Engle
Sharing and Reporting Video Work
Roy Pea, Jay Lemke
Research on How People Learn with and from Video
Miriam Gamoran Sherin, Bruce L. Sherin
Ethical Concerns in Video Data Collection
Sharon J. Derry, Dan Hickey, Timothy Koschmann |
Following is a list of major topics these experts address which are likely to be of particular interest to those planning and reviewing proposals for educational studies that incorporate video technologies. Included are references to sections of the Guidelines where the panel's recommendations are detailed. Designed as a roadmap—hyperlinked to assist online viewers in navigating the PDF version of the report—we hope investigators, reviewers, and funders will find this overview and the Guidelines helpful in stimulating thinking about the requirements and opportunities for using video to develop educational interventions and study their impact.
TOPICS TO CONSIDER
in designing, conducting, and reviewing proposals for educational studies that employ video technology
Planning to capture video data
It is important to "think carefully about how to allocate funds to technical infrastructure, to recording equipment, and to time for analysis on research projects."
(See Hall) |
 Planning—and adapting—field work strategies
See pages 4-6 of the Guidelines
Recording observations
See pages 6-12 of the Guidelines
 Equipment for capturing video and audio recordings
Camera configurations & the use of multiple recording devices
Field notes
Indexing recordings for subsequent analyses
See pages 12-14 of the Guidelines
Selecting elements for analyses
". . . [D]ata selection — a process of focusing on particular information in accordance with the theoretical frameworks, research questions, and instruments a researcher chooses" is critically important in "depicting or telling a narrative account of some phenomenon; and creating a source for information storage and retrieval that will support the identification and analysis of data."
(See Goldman, Erickson, Lemke, Derry ) |
Selecting video clips—deciding how to decompose complex events
See pages 16-18 of the Guidelines
Selecting for narrative power
See pages 19-20 of the Guidelines
Combining purposes
See pages 20-21 of the Guidelines
Selection strategies – inductive, deductive, and narrative-evolving
See pages 22-23 of the Guidelines
Analyzing data
"Potential criticisms . . . about generalizability of findings from video research can be countered by paying explicit attention to the logic of one's inquiry, including one's approach to selecting or collecting records, and by articulating the processes used to create explanations and generate claims."
". . . [V]ideo analysis can range from discovery-oriented approaches, in which the hope is to reveal unanticipated phenomena, to top down approaches, in which the records are used to identify and code events that have been mostly conceptualized before the data was collected. . . . An explicit multi-stage analytic approach can strengthen the likelihood of generating strong findings that are both reliable and valid."
(See Barron & Engle) |
A checklist for beginning researchers
See pages 24-26 of the Guidelines
Guiding questions
Expecting the unanticipated
Social practices for viewing
Representations for data selection & pattern finding
See pages 26-29 of the Guidelines
Indexing
Macro level coding
Narrative summaries
Diagrams
Transcription
See Appendix A: Common Transcription Choices
Making a case with video data
See pages 29-32 of the Guidelines
Reporting analyses ‘play-by-play'
Coding, counting, and statistical analyses
Refining hypotheses
Re-representing video records
Sharing and reporting video work
"... [T]hose who conduct educational research based on video records are more likely to advance cumulative knowledge building if a major part of their research activity includes sharing and vetting the boundary objects that are integral to the socio-technical practices of video research." Examples of these boundary objects include "technical practices, tool selection, data selection, coding schemes and practices, video data banks, metadata schemes for video, theories and conceptual frameworks for guiding video research practices, institutional review board (IRB) forms and practices, and video reporting practices and genres."
(See
Pea & Lemke) |
Boundary objects for video research
See pages 36-42 of the Guidelines
Video software tools—analysis tools; tools for developing & sharing video cases
Formats for sharing video research
Sharing video as data sources for research
See pages 42-45 of the Guidelines
Metadata schemas
Virtual repositories and collaboratories
Norms and practices for attribution and reuse
See page 45-46 of the Guidelines
How people learn with and from video
Issues in the design of video learning environments
See pages 48-49 of the Guidelines
The attention biases "that cause viewers to notice some aspects of classroom interactions and not others, the attributional stances that affect how viewers interpret what they see, and the epistemological beliefs that temper what they learn from viewing are not unique to videotaped representations of classroom processes. In fact, recent research suggests that video representations may provide a means of overcoming such biases."
(See
Sherin & Sherin) |
Technological infrastructure
Video content
Task structure
Social structure
Learning outcomes
See pages 50-52 of the Guidelines
Video assessment
See page 54 of the Guidelines
Paradigms for video-based professional development
See pages 54-58 of the Guidelines
Video clubs
Problem solving cycle
Lesson study
Problem-based learning models
Video case applications of cognitive flexibility theory
Ethical concerns in video data collection
General issues regarding use of human subjects in video research
See pages 59-62 of the Guidelines
Issues regarding broad sharing of video data sources
See pages 62-64 of the Guidelines
Protocols and informed consent
See pages 65-66 of the Guidelines, and Appendix B: Sample informed consent forms
The Data Research and Development Center (DRDC) is a research and technical center funded by the National Science Foundation (NSF) as part of the Interagency Education Research Initiative (IERI), a collaborative effort of NSF, the U.S. Department of Education, and the National Institute of Child Health and Human Development (NICHD) in the National Institutes of Health. Since 1999 these three agencies have funded over 100 IERI scientific research studies designed to develop and/or investigate the effectiveness of educational interventions in classrooms across the United States. DRDC conducts research to understand the factors that are essential for scaling up promising educational models, programs, and strategies. DRDC also works to identify and address the methodological and other challenges that arise when conducting scale-up research, and to support IERI investigators in the conduct of their research.
To learn more about the work of the Data Research and Development Center and the IERI projects it supports, please explore this website or contact: Sarah-Kathryn McDonald (773 256 6199 ) or Kevin Brown (773 256 6024).
Data Research and Development Center
NORC at the University of Chicago
1155 East 60 th Street
Chicago , Illinois 60637 |
This material is based upon work supported by the National Science Foundation under Grant No. 0129365. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
|
