Workshop:%20Utilizing%20concept%20maps%20and%20other%20approaches%20for%20acquiring,%20eliciting,%20representing,%20and%20comparing%20structural%20knowledge

1
Workshop Utilizing concept maps and other
approaches for acquiring, eliciting,
representing, and comparing structural knowledge

• By Roy Clariana
• http//www.personal.psu.edu/rbc4
• University of Oulu, Finland
• EDTECH Team seminar
• 14 and 15 of March, 2005
• (9am till 1pm)

Tuesday March 15th
2
Mindmaps for qualitative data collection, a
working seminar

• The goal today is to determine if mindmapping of
  interview data is useful (ECOL)
• Identify themes by extracting and sorting concept
  terms
• Capture meaning by extracting and representing
  propositions
• Products for today
• Activity 1 One (or possibly more) holistic
  map(s) that represents the themes across the 6
  interviews
• Activity 2 One representational map of each
  interview

Activity 1
Activity 2
3
The connection

• The purpose of most qualitative research is to
  explore the relationships between the data and
  ideas in the project (p.27, NVivo Getting Started
  Guide, 2002)
• Concept maps are particularly effective for
  representing the organization that students see
  among concepts (p.64, Turns, Atman, Adams,
  2000)

4
Using a group drawn mindmapduring an interview
Interview 1
In future, experiment with this approach,
contrast one group using yellow stickies on big
pieces of paper to respond to the interview
questions compared to regular (no map) interview.
See if there is a difference in the data
text
text
text
text
Qs
The capability and experience of the person
coding the text is critical
examples
interviewer
See William M. K. Trochim
5
Using a researcher drawn mindmap after an
interview
i.e., attribute theory note issue
Interview 1
Interview 1 Transcript text text text text text
text text text text text
memo
text
text
text
text
The capability and experience of the person
coding the text is critical
examples
coders
6
The connection
Daley, 2004

• Concept maps can provide one strategy to deal
  with the methodologic challenges of qualitative
  research. A mindmap can be used to
• frame a research project (develop the model)
• reduce qualitative data (20 page interview to one
  page map, visual identification of theme, one
  page maps facilitate comparison between groups
  and sites)
• analyze themes and interconnections (e.g., our
  cluster analysis activity), and
• present findings (similar to using participant
  comments, maps provide peremptory example).

Mindmaps and qualitative research are
philosophically consistent
Daley, 2004
7
You must determine the unit of analysis for each
pass through the interview

• Concept (one or two words, usually nouns)
• Phrase (several words, nouns and verbs)
• Proposition (noun-verb-noun combination)

8
The connection
Daley, 2004

• Concept maps can provide one strategy to deal
  with the methodologic challenges of qualitative
  research. A mindmap can be used to
• frame a research project (develop the model)
• reduce qualitative data (4 page interview to one
  page map, visual identification of theme, one
  page maps facilitate comparison between groups
  and sites)
• analyze themes and interconnections (e.g., our
  cluster analysis activity), and
• present findings (similar to using participant
  comments, maps provide peremptory example).

Mindmaps and qualitative research are
philosophically consistent
Daley, 2004
9
Activity 2 reduce qualitative data

• An example of a 20 page interview to one page
  map,
• visual identification of theme,
• one page maps facilitate comparison between
  groups and sites

phrases
10
ECOL data

• Activity 1 Lets look at the semi-structured
  interview audio tape from 2 groups over 3
  sessions
• The first activity is to derive themes (from
  terms)
• The second activity is to represent the
  interview (with phrases)

11
Activity 1 - Identifying broad themes

• text abstraction An alternative to brainstorming
  for generating a set of statements for concept
  mapping. A text abstraction method involves
  identifying text statements that are imbedded in
  some larger text and extracting them for use as
  separate statements in concept mapping. For
  instance, one could review the transcripts of a
  focus group discussion and identify key
  conclusion statements that were made. These could
  each be extracted and entered as a concept map
  statement set so that the results of the focus
  group discussion could be mapped and used in
  subsequent work (e.g., decision making or pattern
  matching).

http//www.conceptsystems.com/kb/00000376.cfm
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Activity 1 Cluster analysis, as 2 groups
Using all 6 interviews, if possible
Use yellow posit notes on large paper
Brainstorming (corpus list)
Sorting (move like terms closer)
Naming Clusters (name the categories/themes)
Merging Pruning (combine like terms, delete or
move unlike terms, synthesize terms)
and if necessary
Sorting Clusters (move like clusters closer)
Naming broad themes (name the cluster of clusters)
Finally, links may be added
Then document (save/print)
13
thoughts

• Keep note of the evolution of the process for
  later discussion, especially what works and what
  did not
• Each team presents their map
• Discussion of Activity 1 process

14
Activity 2a Lets try converting ECOL interview
data directly into a map

• Method 1
• Read a sentence, add a phrase or proposition to
  the map, repeat
• when done, play with structure and links
• Compare our maps
• Debrief

Activity 2a
15
How to copy from interview, double click paste
on CMAP
Interview
CMAP
Activity 2a
16
Activity 2b Converting ECOL interview data into
a map using propositions

• Method 2
• Write propositions into a text file
• Open text file with cmap tools
• Play with structure and links
• Compare our maps
• Debrief

Activity 2b
17
How to convert propositions ? a map

• Write propositions into a text file
• Open text file with cmap tools
• Play with structure and links
• Compare our maps
• Debrief

Activity 2b
18
How to convert propositions ? a map

• Makes a likes text file
• Import into CMAP Tools
• Select Format ? Auto layout
• View hierarchical
• View force directed

Activity 2b
19
Summary

• Additional approaches I will use your corpus
  terms and see what ALA-Reader can determine from
  the interviews
• Other comments?

20
readings

• Monday
• Turns, J., Atman, C.J., Adams, R. (2000).
  Concept maps for engineering education A
  cognitively motivated tool supporting varied
  assessment functions. IEEE Transactions on
  Education, 43 (2), 164-173
• Cicognani, A. (2000). Concept mapping as a
  collaborative tool for enhanced online learning.
  Educational Technology and Society, 3 (3),
  150-158.
• van Boxtel, C., van der Linden, J., Roelofs, E.,
  Erkens, G. (2002). Collaborative concept
  mapping provoking and supporting meaningful
  discourse. Theory Into Practice, 44 (1), 40-46.
• Chiu, C.H., Huang, C.C., Chang, W.T. (2000).
  The evaluation an influence of interaction in
  network supported collaborative concept mapping.
  Computers and Education, 34, 17-25.
• Kinchin, I.M. (2001). If concept mapping is so
  helpful to learning biology, why arent we all
  doing it? International Journal of Science
  Education, 23 (12), 1257-1269.
• Tuesday
• Daley, B.J. (2004). Using concept maps in
  qualitative research. In A.J.Canas, J.D.Novak,
  and F.M.Gonzales, Eds., Concept maps theory,
  methodology, technology, vol. 2, in the
  Proceedings of the First International Conference
  on Concept Mapping, Pamplona, Spain, Sep 14-17.
  http//cmc.ihmc.us/papers/cmc2004-060.pdf
• Daley, B.J. (2004). Using concept maps with adult
  students in higher education. In A.J.Canas,
  J.D.Novak, and F.M.Gonzales, Eds., Concept maps
  theory, methodology, technology, vol. 2, in the
  Proceedings of the First International Conference
  on Concept Mapping, Pamplona, Spain, Sep 14-17.
  http//cmc.ihmc.us/papers/cmc2004-059.pdf
• Basque, J., Pudelko, B., Leonard, M. (2004),
  Collaborative knowledge modeling between experts
  and novices a strategy to support transfer of
  expertise in an organization. In A.J.Canas,
  J.D.Novak, and F.M.Gonzales, Eds., Concept maps
  theory, methodology, technology, vol. 2, in the
  Proceedings of the First International Conference
  on Concept Mapping, Pamplona, Spain, Sep 14-17.
  http//cmc.ihmc.us/papers/cmc2004-215.pdf

21
Tuesday post workshop Lessons learned

• Only able to complete Activity 1 for 1 interview
  (5 page transcript), allow more time or fewer
  activities next time
• Lessons learned for Activity 1
• There are unsaid ideas that will not be
  captured solution, add memos
• Underlining key terms is quick, about the same as
  just reading the transcript
• Individuals underline, compare for inter-rater
  reliability
• We noted that the corpus terms depended on the
  perspective of the reader, and concluded that the
  corpus term list may be under represented and
  decided to do it again taking separate roles when
  underlining
• Have individuals read with different hats in
  order to capture different
• Themes began to emerge just simply during
  underlining
• Write a has in the margin when you think of it
• To prepare the interview, reduce names (i.e.,
  James becomes J ), number each exchange
• Note episodes while reading by drawing a line
  across the page
• On the yellow postit note, include line number
  and person (i.e., 12, J ) as well as the phrase
• It takes a lot of time to go from the underlined
  text to the postit notes solution, prepare
  postit notes ahead of time but dont tell the
  group until they are ready to write the postit
  notes, then add their phrases as additional
  postit notes
• Need a really big white board to stick the
  postits on and to be able to move them around and
  write on it
• 5 pages of interview produced about 50 stickies
• We first used a matrix to sort the stickies,
  students down the left column and time going from
  left to right. We noticed that certain students
  tended to start discussions and take certain
  roles, like leading or group regulation (this
  specific matrix can be done ahead of time, but is
  fairly quick to complete) need a way to capture
  this matrix because the next step moves all the
  stickies
• The next sort was open-ended, moving like terms
  together etc. we needed to do this as a big
  group, though several people were at the board at
  the same time moving things, we all discussed the
  names of clusters, moved more stickies, and then
  reached consensus on the THEMES, the themes that
  emerged were goals, group dynamics, external
  factors, regulation, positive feelings and
  negative feelings
• Looking at these clusters, we asked Who was the
  first to mention a theme and Who occurred the
  most within a theme cluster
• We drew a new matrix with these themes down the
  first column and time going across the top, we
  observed a pattern of group dynamic-external
  factor-regulation that repeated several times. A
  group dynamic issue seems to demand a regulation
  response to resolve it.

See Monday powerpoint at http//www.personal.psu.e
du/rbc4/edtech_monday.ppt