who’s in your school learning community network?

Who’s in Your School

Learning CommunityNetwork?Barbara Schultz-Jones, PhD

Department of Library and Information Sciences

College of InformationUniversity of North Texas

Denton, TX

ESC Region XIVirtual Technology Conference

November 10, 2009

11/10/09 Schultz-Jones / ESC XI 2

Agenda Show me your network Background Social network theory Social network analysis Texas schools Constructing a social network Applications of this approach

11/10/09 Schultz-Jones / ESC XI 3

Social Networking

11/10/09 Schultz-Jones / ESC XI 4

Background 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.

11/10/09 Schultz-Jones / ESC XI 5

Social network theory Seeks to explain the workings of networks Small-world method (Milgram, 1967)

6 degrees of separation (the Kevin Bacon Game) Two prominent network properties provide a

framework for viewing network behavior: the strength of weak ties (Granovetter, 1973,

1983) structural holes (Burt, 1992)

11/10/09 Schultz-Jones / ESC XI 6

Social network example

11/10/09 Schultz-Jones / ESC XI 7

Social network analysis 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.

11/10/09 Schultz-Jones / ESC XI 8

Who uses this approach? Seven disciplines:

business and management computer science humanities information science medicine and health sciences social sciences

11/10/09 Schultz-Jones / ESC XI 9

Network approaches

Citation analysis Diffusion of information Information flow Degree of contact/interaction Role and position analysis

11/10/09 Schultz-Jones / ESC XI 10

How does this apply to the school learning environment?

Demonstrated levels of connectivity: Between individuals Within and between departments

Assessment tool for group interaction Analysis tool for students

11/10/09 Schultz-Jones / ESC XI 11

Frequency of Interaction SLMS 1

Blue – Language ArtsGreen – Math/SciencePurple – History/Foreign Lang.Yellow – AdministrationRed - SLMS

11/10/09 Schultz-Jones / ESC XI 12

Level of Interaction SLMS 1

Blue – Language ArtsGreen – Math/SciencePurple – History/Foreign Lang.Yellow – AdministrationRed - SLMS

11/10/09 Schultz-Jones / ESC XI 13

Frequency of InteractionSLMS 2

Blue – Language ArtsGreen – Math/SciencePurple – History/Foreign Lang.Yellow – AdministrationRed - SLMS

11/10/09 Schultz-Jones / ESC XI 14

Level of InteractionSLMS 2

Blue – Language ArtsGreen – Math/SciencePurple – History/Foreign Lang.Yellow – AdministrationRed - SLMS

11/10/09 Schultz-Jones / ESC XI 15

Frequency of InteractionSLMS 3

Blue – Language ArtsGreen – Math/SciencePurple – History/Foreign Lang.Yellow – AdministrationRed - SLMS

11/10/09 Schultz-Jones / ESC XI 16

Level of InteractionSLMS 3

Blue – Language ArtsGreen – Math/SciencePurple – History/Foreign Lang.Yellow – AdministrationRed - SLMS

11/10/09 Schultz-Jones / ESC XI 17

Frequency of InteractionSLMS 4

Blue – Language ArtsGreen – Math/SciencePurple – History/Foreign Lang.Yellow – AdministrationRed - SLMS

11/10/09 Schultz-Jones / ESC XI 18

Level of InteractionSLMS 4

Blue – Language ArtsGreen – Math/SciencePurple – History/Foreign Lang.Yellow – AdministrationRed - SLMS

11/10/09 Schultz-Jones / ESC XI 19

Frequency of InteractionSLMS 5

Blue – Language ArtsGreen – Math/SciencePurple – History/Foreign Lang.Yellow – AdministrationRed - SLMS

11/10/09 Schultz-Jones / ESC XI 20

Level of InteractionSLMS 5

Blue – Language ArtsGreen – Math/SciencePurple – History/Foreign Lang.Yellow – AdministrationRed - SLMS

11/10/09 Schultz-Jones / ESC XI 21

Frequency of Interaction2 Schools - Science

11/10/09 Schultz-Jones / ESC XI 22

Terminology 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

11/10/09 Schultz-Jones / ESC XI 23

How is data gathered? 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

11/10/09 Schultz-Jones / ESC XI 24

How is the data analyzed? Construct a matrix identifying connections between

nodes/actors/individuals

11/10/09 Schultz-Jones / ESC XI 25

How is the data analyzed? 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

11/10/09 Schultz-Jones / ESC XI 26

Practical Demonstration 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

11/10/09 Schultz-Jones / ESC XI 27

Classroom applications Math

Calculate distances between contacts Science

Map the connections between countries and animal species

English Map the connections between authors

(Shakespeare, for example), and derivative works (the movie Shakespeare in Love, for example).

11/10/09 Schultz-Jones / ESC XI 28

Future applications 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

11/10/09 Schultz-Jones / ESC XI 29

Thank You!

If you have any interest in exploring future applications of social network analysis

Please contact me:Barbara.Schultz-Jones@unt.edu

11/10/09 Schultz-Jones / ESC XI 30

ReferencesBorgatti, 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.

11/10/09 Schultz-Jones / ESC XI 31

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.