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Making Modeling Social: Introducing the Modeling Commons

Making Modeling Social: Introducing the Modeling Commons. Reuven M. Lerner, Sharona T. Levy, and Uri Wilensky Northwestern University & University of Haifa Meital Conference October 14 th , 2009. Models. Model: Reified theory about a system Often used in science and engineering

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Making Modeling Social: Introducing the Modeling Commons

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  1. Making Modeling Social:Introducing the Modeling Commons • Reuven M. Lerner, Sharona T. Levy, and Uri Wilensky • Northwestern University & University of Haifa • Meital Conference • October 14th, 2009

  2. Models • Model: Reified theory about a system • Often used in science and engineering • Anatomy, molecules, DNA • Also mathematical models • Economics, cognitive science

  3. Modeling and Constructionism • Purpose of modeling: Construction and revision of conceptual understanding (Jonassen, 2006) • Papert: Best way to construct knowledge is by creating sharing artifacts (1991) • Modeling has been shown to help learning (Goldstone & Wilensky, 2008; Blikstein & Wilensky, 2008)

  4. NetLogo

  5. NetLogo • Wilensky, 1999 • http://ccl.northwestern.edu/netlogo • 100,000 users worldwide • Includes 400+ models, code examples • Associated curricula (ProbLab, Connected Chemistry, MaterialSim, NIELS, BEAGLE)

  6. Building vs. sharing • NetLogo is successful for building... • ... but existing community structures are not promoting sharing. • Sharing in journals, Web — not community • netlogo-users: Only 5.7% of 9,696 messages included a model (over 7 years) • Limited community models (274 in 7 years)

  7. Interactions are vital • Vygotsky: Learning leads to development when “interacting with people in his environment and in collaboration with his peers.” (1978, p. 90) • Lave & Wenger (1991): Legitimate Peripheral Participation, CoP • Schön (1983): “Reflection in Action”

  8. Collaboration is vital • A skill and a perspective (Kolodner and Guzdial, 1996) • Much of our culture depends on collaboration and remixing (Lessig, 2008) • CSCL sees collaborative communities as a learning paradigm (Stahl, 2006; Koschmann, 1994)

  9. My research • Encourage sharing, collaboration, communities of practice • Encourage communication with models, not about them • Identify patterns that emerge from such interactions

  10. Modeling Commons

  11. Modeling Commons • Wikipedia of modeling • View, share, collaboratively build models • Run models in the browser • Create families of “branched” models • Discussion, requests for help • Social tagging

  12. Research to date • Round #1: Winter-spring 2008 • 12 people, 3 interviews, 4 written reports • Concentrated on design • Round #2: Fall 2008 • 24 people, 10 interviews • Combination of design and usage

  13. Research to date • Round #3: Spring 2009 • 36 participants in 3 classes at 2 universities • Total of 90 models uploaded

  14. Design Research • Clinical interviews (Ginsburg, 1997) and defined tasks (Nielsen, 2000) to improve design: • Improve system usability • Reduce threshold to sharing, collaboration, discussion

  15. Home pages • Users consistently reported a “lost” feeling • “It would be nice ... to find out what models were new, or what models there had been recent activity on. Both, actually... here’s a new model, and people are talking about this model.”

  16. Solution: Dynamic page Your models Most-viewed Your tags Most downloaded Requests for help

  17. Privacy • 8/10 subjects said “sharing my models with others” has importance of 4 or 5 (out of 5) • However, many expressed reservations for classwork or work-in-progress • “...I wouldn’t have been comfortable, and the people I work with wouldn’t have been comfortable — showing the models to the world in an unfinished form”

  18. Groups, permissions

  19. Groups, permissions

  20. Logfile analysis • Every action in the Commons is logged • Allows for analysis, understanding without looking over users’ shoulders

  21. Logfile analysis: LPP* • Predicted by Lave, Wenger (1991) • 3 neither viewed nor uploaded • 8 did view, but never uploaded • 15 viewed before uploading • 9 uploaded before viewing • Some LPP behavior is seen in 63% (n = 36) *Legitimate Peripheral Participation

  22. Networks • Explicit vs. implicit networks • Networks of people • via models, discussions, tags • Graphs are from one university class, where students were instructed to tag and discuss models, as well as upload them • Some measures from Krackhardt (1994)

  23. Explicit membership

  24. Models + creators Connectedness = 0.097 Hierarchy = 0.271

  25. Models + taggers Connectedness = 0.656 Hierarchy = 0.0426

  26. Models + commenters Connectedness = 0.862 Hierarchy = 0.085

  27. Models + all actions Connectedness = 0.731 Hierarchy = 0.030

  28. Social networking • Explicit group membership does not necessarily indicate actual ties • Connectedness is a useful comparison only when the number of nodes is the same • Multiple communication channels would appear to be the key to a truly connected graph (and thus community)

  29. Future work • 3 courses already used it; another soon • Refining and extending logfile, network analysis methods • Explore: http://modelingcommons.org/ • Soon will be announced to the world

  30. Acknowledgements • Prof. Uri Wilensky • Dr. Sharona T. Levy • Members of the CCL • Researchers, students, and TAs who participated

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