Home
About
us
Papers & Talks
Software
Data Sets & Examples
Workshops
|
|
Workshops
Intervention Effects on Social
Networks in Education Research
March 2014, Spring Meeting of the Society for Research on Educational Effectiveness (SREE)
Tracy
Sweet, University of Maryland
Andrew Thomas & Brian Junker, Carnegie Mellon University
Experimental
and observational studies in education are sometimes focused not on the
effects of changing curriculum, teaching and learning materials, or
classroom technique, but rather on changes in the way students -- or
teachers, teaching coaches and administrators -- interact with one
another (e.g., relationship between transformational leadership and
leaders' professional social connections, influence of peer group
structure on student behavior and aggression, diffusion of innovation
and reform initiatives in schools, advice giving/receiving and social
capital among teachers, etc.). Many whole school initiatives encourage
some type of social structural change, be it an increase in
collaboration, distribution of leadership or a push toward small
learning communities: in short, they encourage changes in the social
networks of students and of professionals in school systems.
Hierarchical
Network Models (HNMs) enable you to model and detect the effects of
interventions and other covariates on the structure of social networks,
by pooling information across ensembles of social networks (teachers’
professional networks across multiple school buildings, students’ peer
networks across multiple geographic areas, etc.).
We will
walk you through hands-on data analyses, using software we have
developed, to model and understand influences on social network
structure in education settings. A brief summary of the
technical
aspects of HNMs will be included but most of the workshop will focus on
substantive research questions and useful interpretations.
All
data
analyses will be conducted in the free statistical package R;
participants should bring a laptop with the current version of R
installed and functioning correctly. Other data and software
will
be provided in the workshop. There will be an optional "R
bootcamp" from 8am to 9am, and the main workshop will run from 9am to
noon.
For
more information about the workshop, or to find out what will be
covered in the R bootcamp, please see 2014-03
SREE WORKSHOP.
Participants
wishing to brush up on R in advance may consult the websites
and/or the books
- Teetor, P. (2011). R cookbook.
O'Reilly.
- Chang, W. (2012). R graphics
cookbook. O'Reilly.
SOME SUGGESTED READINGS:
- Ennett,
S. and Bauman, K. (1993). Peer group structure and adolescent
cigarette smoking: a social network analysis.
Journal of
Health and Social Behavior, 226--236.
- Frank,
K. A., Zhao, Y., & Borman, K. (2004). Social capital and the
diffusion of innovations within organizations: The case of
computer technology in schools. Sociology of Education, 77,
148--171.
- Low, S., Polanin, J.R., Espelage,
D.L.
(2013). The Role of Social Networks in Physical and
Relational
Aggression Among Young Adolescents. Journal of
Youth and
Adolescence, 42(7), 1078--1089.
- Penuel, W. R.,
Frank, K. A., & Krause, A. (2006). The distribution of
resources and expertise and the implementation of schoolwide
reform initiatives. In Proceedings of the 7th international
conference on Learning sciences, ICLS '06, (pp. 522--528).
International Society of the Learning Sciences.
- Spillane,
J., Kim, C., and Frank, K. (2011). Instructional Advice and
Information Providing and Receiving Behavior in Elementary
Schools: Exploring Tie Formation as a Building Block in
Social
Capital Development. Institute for Policy Research,
Northwester University, Working Paper Series.
- Sweet,
T. M., Thomas, A. C., and Junker, B. W. (2013) Hierarchical
network models for education research: hierarchical latent
space
models. Journal of Educational and Behavioral Research, 33,
295--318
- Thomas, A., Dabbs, B., Sadinle, M,
Sweet,
T., & Junker, B. (June 2013). Conditionally
independent dyad
network models; an integrative framework for modeling and
computing. Working paper.
- Thomas, A., Dabbs,
B., & Sweet, T. (August 2013). CIDnet: An R
software
package for inference with conditionally independent dyad
network
models. In preparation.
- Weinbaum, E., Cole, R.,
Weiss, M., & Supovitz, J. (2008). Going with the
flow:
Communication and reform in high schools. In J. Supovitz &
E.Weinbaum (Eds.), The implementation gap: understanding
reform
in high schools (pp. 68--102). Teachers College Press.
|
|