Transcript Who's in your school learning community network

Who’s in Your School
Learning Community
Network?
Barbara Schultz-Jones, PhD
Department of Library and Information Sciences
College of Information
University of North Texas
Denton, TX
ESC Region XI
Virtual Technology Conference
November 10, 2009
Agenda
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Show me your network
Background
Social network theory
Social network analysis
Texas schools
Constructing a social network
Applications of this approach
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Social Networking
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Background
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The application of social network theory to
the study of groups and group dynamics has
its roots in the 1930s and the formulation of
sociometry (Moreno, 1934).
Textile metaphors of fabric and web were
used to describe interweaving relations of
social action (1950 – 1970)
Diverse traditions culminated in the current
use of social network analysis: anthropology,
psychology, sociology and mathematics.
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Social network theory
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Seeks to explain the workings of networks
Small-world method (Milgram, 1967)
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6 degrees of separation (the Kevin Bacon Game)
Two prominent network properties provide a
framework for viewing network behavior:
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the strength of weak ties (Granovetter, 1973,
1983)
structural holes (Burt, 1992)
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Social network example
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Social network analysis
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The methodology used to research network
behavior
The network diagram, or sociogram, is a crucial
means to demonstrate and illustrate the concepts,
despite the limitations to its use by the difficulties of
illustrating networks of high density.
In order to apply the concepts regarding the
behavior of networks it is essential to identify the
roles and positions of the members of the network.
The members of a network may be people, things or
concepts depending on the focus of the analysis.
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Who uses this approach?
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Seven disciplines:
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business and management
computer science
humanities
information science
medicine and health
sciences
social sciences
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Network approaches
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Citation analysis
Diffusion of information
Information flow
Degree of contact/interaction
Role and position analysis
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How does this apply to the
school learning environment?
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Demonstrated levels of connectivity:
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Between individuals
Within and between departments
Assessment tool for group interaction
Analysis tool for students
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Frequency of Interaction
SLMS 1
Blue – Language Arts
Green – Math/Science
Purple – History/Foreign Lang.
Yellow – Administration
Red - SLMS
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Level of Interaction
SLMS 1
Blue – Language Arts
Green – Math/Science
Purple – History/Foreign Lang.
Yellow – Administration
Red - SLMS
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Frequency of Interaction
SLMS 2
Blue – Language Arts
Green – Math/Science
Purple – History/Foreign Lang.
Yellow – Administration
Red - SLMS
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Level of Interaction
SLMS 2
Blue – Language Arts
Green – Math/Science
Purple – History/Foreign Lang.
Yellow – Administration
Red - SLMS
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Frequency of Interaction
SLMS 3
Blue – Language Arts
Green – Math/Science
Purple – History/Foreign Lang.
Yellow – Administration
Red - SLMS
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Level of Interaction
SLMS 3
Blue – Language Arts
Green – Math/Science
Purple – History/Foreign Lang.
Yellow – Administration
Red - SLMS
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Frequency of Interaction
SLMS 4
Blue – Language Arts
Green – Math/Science
Purple – History/Foreign Lang.
Yellow – Administration
Red - SLMS
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Level of Interaction
SLMS 4
Blue – Language Arts
Green – Math/Science
Purple – History/Foreign Lang.
Yellow – Administration
Red - SLMS
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Frequency of Interaction
SLMS 5
Blue – Language Arts
Green – Math/Science
Purple – History/Foreign Lang.
Yellow – Administration
Red - SLMS
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Level of Interaction
SLMS 5
Blue – Language Arts
Green – Math/Science
Purple – History/Foreign Lang.
Yellow – Administration
Red - SLMS
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Frequency of Interaction
2 Schools - Science
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Terminology
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Network: an interconnected system
Node/actor/social entity: “discrete individual, corporate or collective
social units” (Wasserman & Faust, 1999, p.17)
Level of analysis/discussion:
 Egocentric: single node as the focus of attention
 Whole: consideration of all nodes in the environment
Ties: the relationship connection between pairs of
nodes/actors/entities:
 Content: the resource shared, delivered or exchanged
 Directed/Asymmetrical: content flows in one direction
 Reciprocal/Symmetrical: content flows in both directions
 Undirected: physically proximate but no exchange, or the
exchange is not considered relevant to the research question
 Strong: close association, based on the research context
 Weak: distant association, based on the research context
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How is data gathered?
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Social network map – an instrument developed by
Todd (cited in Curtis, 1979)
Surveys and interviews – personal or group network
surveys that identify information exchange
connections (Cross & Parker, 2003)
Agent-based technology to capture email and
document flow across servers
Metrics of journals, authors, citations, co-citations,
websites, online community positions
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How is the data analyzed?
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Construct a matrix identifying connections between
nodes/actors/individuals
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How is the data analyzed?
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Employ software programs:
 GraphPlot: a spreadsheet and a drawing tool for sociometric data
 KrackPlot: a network graphics computer program.
 Social Network Analysis Functional Utility (SNAFU): MacOS
network analysis and algorithm development software
 Social Network Visualizer for Linux (SocNetV): a GNU program
for Linux OS to visualize graphically and play with social
networks
 UCINET: a general program designed to facilitate the analysis of
social network data (Borgatti & Freeman, 2002)
 http://www.analytictech.com/networks/
 Pajek: a network drawing package; large density networks
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Practical Demonstration
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Sign-up sheet of attendees
Distribute list and ask each attendee to
identify if they have met any other attendees
Compile results in a matrix
Input matrix to UCINET software program
Produce sociogram of attending network
Discuss results
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Classroom applications
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Math
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Science
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Calculate distances between contacts
Map the connections between countries and
animal species
English
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Map the connections between authors
(Shakespeare, for example), and derivative works
(the movie Shakespeare in Love, for example).
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Future applications
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Within a subject area
Within a school
Within a district
Within a state
Within a region
Anywhere the degree or frequency of
connectivity is important
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Thank You!
If you have any interest in exploring future
applications of social network analysis
Please contact me:
[email protected]
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References
Borgatti, S.P., Everett, M.G. & Freeman, L.C. (2002).
Ucinet for Windows: Software for social network
analysis. Harvard, MA: Analytic Technologies.
Burt, R.S. (1992). Structural holes: The social structure of
competition. Cambridge, MA: Harvard University Press.
Cross, R. & Parker, A. (2003). The hidden power of social
networks: Understanding how work really gets done in
organizations. Boston, MA: Harvard Business School
Press.
Granovetter, M.S. (1973). The strength of weak ties.
American Journal of Sociology, 78, 1360-1380.
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References (cont.)
Granovetter, M.S. (1983). The strength of weak ties: A
network theory revisited. Sociological Theory, 1, 201-233.
Moreno, J.L. (1934). Who shall survive? New York: Beacon
Press.
Schultz-Jones, B. (2009). Collaboration in the school social
network: School library media specialists connect.
Knowledge Quest, 37(4), 20-25.
Wasserman, S. & Faust, K. (1999). Social network analysis:
Methods and applications. New York: Cambridge
University Press.
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