TEXAS TECH UNIVERSITY, 1997
EDUCATION, TECHNOLOGY (0710); SOCIOLOGY, THEORY AND METHODS (0344); EDUCATION,
HIGHER (0745); EDUCATION, ADMINISTRATION (0514)
Identifying predictors of computer use such as attitude, anxiety, and receptivity
to change have been the
primary area of interest in instructional technology. Research relating to the
diffusion of innovations in
education has been based primarily on looking at these individual characteristics
as predictors of use.
This dissertation proposes to use social network analysis to study the diffusion
of two computer-based
administrative innovations within a university faculty network. Methodology
issues concerning time of
adoption and network nominations were examined as well as the relationship of
time of adoption and the
number of network nominations received, spatial proximity, and organizational
unit proximity. Finally, the
diffusion of the innovations was to be analyzed using the dual-classification
and T/CM models. Subjects
were 66 faculty members in a College in Education from a southwestern university
during the 1996-1997
academic year. At the beginning of the study subjects were introduced to the
innovations and asked to
provide demographic information and to identify communication partners in the
areas of advice,
friendship, and discussion. At the conclusion of the study subjects were asked
to provide feed back
related to the innovations and to once again identify their communication partners
in the areas of advice,
friendship, and discussion. Results indicated that there was no significant
difference between adopters
recall time of adoption and actual time of adoption. In addition, there was
no significant difference
between network nominations for advice, friendship, and discussion identified
at the beginning and at
the end of the study. The number of network nominations received was found to
be negatively
correlated with the time of adoption. No correlation was found between time
of adoption and spatial and
organizational unit proximity. The diffusion process could not be studied, because
the necessary
threshold and critical mass levels were not reached. The innovations did not
diffuse through the network.
The lack of diffusion could be explained by the negative correlation between
the number of network
nominations received and the time of adoption as well as by comments faculty
submitted related to the
innovations and a graphical representation of the social network with the nodes
of adopters shaded.
Social
Systems Simulation Group
P.O. Box 6904 San Diego, CA 92166-0904 Roland Werner, Principal Phone/FAX (619) 660-1603 |