Few ideas on how to use video as a method

1. VIDEO RESEARCH IN EDUCATION
Arttu Mykkänen
University of Oulu
Learning and Educational Technology Research Unit (LET)
arttu.mykkanen@oulu.fi

2. Todays Content
• General notions about video research
• Approaches to data collection
• Approaches to analysis
• Presentation and transcription styles
• Pros & Cons

3. 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.

4. 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 microlevel
enactment.
– Gestures

5. DATA COLLECTION

6. 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.

7. 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.

8. 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?

9. 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

10. 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 the
mike, 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.

11. 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!

12. ANALYSIS

13. 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.

14. 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.

15. Example of a coding scheme
Whitebread et al. 2009

16. Inter-coder reliabilities
• Is made in order to carantee the reliability of the
coding 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 the
laborious nature of video data.
• Brainstorming the coding scheme / events with a
research group or community.
– This is not a reliability check!

17. 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?

18. PRESENTING THE RESULTS

19. 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.

20. Different options for transcription
• What’s the time Denise?
• 2.30
• That´s good Denise!

21. 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

22. ”If you want to show
something from the
data, just do it”

24. Melander, H, & Sahlström, F, 2009

25. 25

26. 26

27. 27

28. 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

29. 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 kind
analysing methods.
Cons
• Technical problems
– Disruptive presence of
camera and the
researcher

30. Pros & Cons
Pros
• Sustainability
– Gives time for reflection
– Can be used as additional
triangulation for other
methods
– Allows collaboration
between 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 too
much data.
– Amount of data can be
ovewhelming.
– Laborious analysis.

31. Interesting research environment
• Leaforum
• Lastu

32. 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