Download - Video research in education
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VIDEO RESEARCH IN EDUCATION
Arttu MykkänenUniversity of Oulu
Learning and Educational Technology Research Unit (LET)[email protected]
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Todays Content
• General notions about video research
• Approaches to data collection
• Approaches to analysis
• Presentation and transcription styles
• Pros & Cons
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Video research in general
• Catches the enactment of the person under
observation and the environmental factors.
– cf. paper-pencil observation.
• Video observations can be utilized as main
method or as a complementary method for other
methods (Surveys, Interviews).
– What occurs in the situation?
– Do people act like they claim they do.
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Video research in general
• It can be used in various situations and different kind of contexts.
• Allows many various analytic approaches.
• Gives an restricted view of the situation.
– You are always pointing something and leaving something out.
• Very usable when studying microlevelenactment.– Gestures
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DATA COLLECTION
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Data collection – theoretical starting points
• Data gathering should be planned carefully,
especially the fact how the data will be analysed in
future.
• Forming the theoretical framework
• Understanding the theoretical starting point helps to
understand the data when approaching the collected
data.
• Selection in the analysis
• Theory as a practical tool; directs the research and
analysis.
• Theory should be ”materialized” somehow in the
data.
• By some product or activity.
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Data Collection – Planning the set
• Tell to participants as thoroughly as possible the
different phases and aims of your study.
• The research permission should include
information as a much as possible about:
– Who owns the data and how long.
– How data is stored.
– Use in different contexts.
• Inform the participant about their rights and
flexibility.
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Data Collection – Planning the set
• Do you want to follow one or more participants?
• Classroom or some other more peaceful room?
• How many cameras are used for filming?
– What is the specific purpose of every camera.
• Do you use ”free” camera in addition to stable
cameras?
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Data Collection – Where to focus
• Teacher’s enactment
– Speech, teaching methods, tool used for
teaching, instruction
• Students’ enactment
– Participation to classroom activities, task
performance
• Interaction
– Teacher - student, student - student
• Content of the lecture
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Data collection – tips
– Vary your research ”traditions” as little as possible.
– Stay close to the object that your are filming.
– Use external mike if possible.
– Think about illumination.
– Use several cameras if possible.
– Piloting• Do not conduct the whole data gathering at one time. Try
different executions, for example, change the place of themike, different room.
– If you use more that one camera, make a distinguishable noise before you start
• Helps you to syncronize the films.
– Do not get ”friendly” with the participants.
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Data collection – sorting the data
• Don’t leave anything unsorted.
• Mark every event with some kind of a code
– Place, class, people…
• If you work in school or such place give an
overall feedback after data gathering. After
analysis personel and students might have
changed.
• Take backup copy from everything!
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ANALYSIS
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Analysis
• Starts by concretizing the situation and making
clear what happens in the event.
• Iterative interpretation of the data.
– Picking and selecting the ”essential” events
from the data.
• Scrutinizing these events as thoroughly as
possible.
– Try to find patterns or a behavior from the
data.
• If possible use data ”brainstorming” with your
collegues to check your interpretations.
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Analysis – meaningful parts
• Interaction, communication and behavior follows
usually somekind of pattern. (Mehan, 1979)
– What’s the time Denise?
– 2.30
– That´s good Denise!
• The structure of previous interaction is ”hidden”
behind the single frases.
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Example of a coding scheme
Whitebread et al. 2009
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Inter-coder reliabilities
• Is made in order to carantee the reliability of thecoding scheme and categories.
• Usually two independent coders.
– Cohen’s Kappa.
– Can be done in Nvivo for example.
– Usually only part of the data is coded due thelaborious nature of video data.
• Brainstorming the coding scheme / events with a research group or community.
– This is not a reliability check!
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Examples
• Marshmallow
• Luokkahuone
• Kiintymys
• Think what could be
studied for these
examples .
– What would be a
suitable grain size /
event for analysis?
– How to crop an event
from the data?
– How to describe your
results?
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PRESENTING THE RESULTS
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Transcripts
• Represents on what is happening in the situation
and interaction between participants.
• Transcripts also represents what researcher
wants to emphasize.
– What are you transcriping and what you are
leaving out.
• You must decide how much you are going to
include to the transcript.
– Gestures, expressions, speech sounds etc.
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Different options for transcription
• What’s the time Denise?
• 2.30
• That´s good Denise!
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Different options for transcription
23. (Teacher) What´s the time Denise
24. (2,3)
25. (Denise) ehmm
26. (0,6)
27. (Denise) Halfpast two
28. (0,5)
29. (Teacher) That´s good Denise
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”If you want to show
something from the
data, just do it”
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Melander, H, & Sahlström, F, 2009
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Different software for video research
• Different tools for different phases
– Rough editing: Movie Maker
– Transcriptions: Inqscribe ja Express scribe
– Analysis and categorisation: Nvivo tai Elan
– Final editing: Movie Maker
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Pros & Cons
Pros
• Amout of the data– Captures the situation
ubiquitously• In comparison to paper
and pencil
• Permanent– Can be analysed
countless times
– Allows different kindanalysing methods.
Cons
• Technical problems– Disruptive presence of
camera and theresearcher
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Pros & Cons
Pros
• Sustainability– Gives time for reflection
– Can be used as additionaltriangulation for othermethods
– Allows collaborationbetween peers
• In comparison to observation– Details are really hard to
capture ”on fly”• Details might be
unimportant in the moment
Cons
• Too easy to produce toomuch data.– Amount of data can be
ovewhelming.
– Laborious analysis.
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Interesting research environment
• Leaforum
• Lastu
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Few references to start with
• Derry, S. J., Pea, R. D., Barron, B., Engle, R. A.,
Erickson, F., Goldman, R., Hall, R., ....Sherin, M.
G. (2010). Conducting video research in the
learning sciences: Guidance on selection,
analysis, technology, and ethics. The Journal of
the Learning Sciences, 19(1),3–53
• Goldman, R.,Pea, R.,Barron, B., & Derry, S.
(eds.) (2007).Video research in the learning
sciences.Mahwah, NJ: Erlbau