Faculty Development and the Diffusion of Innovations
Faculty are being asked to adopt, and adapt to, a number of information age
innovations in teaching. While some have adopted these technologies enthusiastically,
the majority of instructors have been much slower to integrate these new tools
in their teaching. Faculty developers remain frustrated with professors who
appear to resist technology integra- tion or those who clearly refuse to use
these innovations in their teaching.
What's needed is an examination of the source of the resistance. Why would
some faculty be so skeptical when others have achieved great success and discovered
new ways to increase learning outcomes? Why would faculty resist tools that
can help them simplify their work? The answer is that not all believe in the
inherent ability of technology to achieve these outcomes. They have to be convinced
before they will integrate technology into their teaching.
These teachers have to be convinced based on their own needs and values. Of
course, they likely share some of the values with those who are quick to adopt
and adapt. Both groups are interested in improving students' learning, for example.
However, there are important differences and these must be addressed if larger-scale
integration of information technologies for teaching is to occur.
Once differing needs are assessed, a faculty development and support system
sensitive to these differing needs should be established. Below, we outline
a model for such a system and detail the theory and related literature behind
|Favor revolutionary change
||Favor evolutionary change
| Risk takers
|Willing to experiment
||Want proven applications
||May need significant support
| Horizontally connected
Diffusion of Innovations
Institutions attempting to establish faculty development and support that is
sensitive to differentiated needs can benefit from work done 40 years ago by
Everett Rogers on the Diffusion of Innovations (1962). The relevance of Rogers'
ideas persists, and is perhaps more relevant now in the midst of the information
technology revolution. Diffusion of Innovations theory can provide an excellent
framework from which to design, promote, and deliver faculty development and
In our work with the University of Vermont, Marlboro College, and Tufts University,
in conversations with numerous other institutions, and through a survey of the
literature, we have confirmed the relevance of Rogers' Diffusion of Innovations
theory. In turn, we have developed a framework for faculty development based
on it. This framework provides guidance to institutions seeking to plan, develop,
and implement both online and face-to-face faculty development opportunities.
Rogers' theory has been cited frequently—even in the last 10 years—in literature
about instructional technology. Rogers' theory posits that a population can
be categorized based on its tendency to be innovative ("Individual Innovativeness").
It also states that those who are more inclined to innovate will adopt an innovation
before those who are less inclined. Rogers showed that the percentages of each
of five categories within the target group coincides with a bell-shaped curve
that illustrates Innovator (2.5 percent), Early Adopter (13.5 percent), Early
Majority (34 percent), Late Majority (34 percent), and Laggards (16 percent).
In 1991, Geoffrey Moore used Rogers' ideas as a basis for a book about marketing
high-tech products to a mass market. In the book, Moore (1991) talks about the
"chasm" between the second and third of Rogers' categories: Early Adopter and
Early Majority. He points out that consumers in these categories have very different
reasons for adopting a technological innovation and marketers must address these
differences in order to reach mainstream markets.
A number of authors in the field of education have picked up on this notion
and have written about adoption of technological innovations by educators. Geoghegan
(1994) confirms the existence of Moore's categories among college faculty and
asserts that mainstream faculty members go largely unrecognized in faculty development
and support for technology integration. Carr (1999) suggests that "needs-based
diffusion strategies" be used. Donovan (1999) confirms that it's critical to
"get to know faculty" to understand differentiated needs and expectations before
effective faculty support can be implemented. Hagner and Schneebeck (2001) suggest
an alternative set of categories, mirroring Rogers' five areas. They also emphasize
that assessing faculty based on these categories is an important first step.
The central theme of all of the noted literature is that there are significant
differences between people who fall into Rogers' Early Adopter and Early Majority
categories. These differences create gaps in motivation and expectations. Such
gaps should be recognized and bridged in order for large-scale technology integration
Diffusion-Based Faculty Development
The professional development framework described here includes strategies for
bridging the gap between early adopter and mainstream faculty groups. The framework
includes considerations of a variety of needs and expectations across the target
groups. By attending to these needs, the framework helps developers achieve
success in readying faculty for innovation and ensures that faculty will achieve
Our framework suggests the creation of a faculty development structure that
uses multiple "spaces," with each space providing a different point of entry
into the structure. The spaces can include both physical and online tools and
resources, but online tools would be used as a central starting point. The "Learning
Modules" space would include direct instruction in the form of self-paced tutorials
and guided practice activities. The second space—"Effective Practices"—would
provide access to a database containing success stories of technology integration.
In the "Communities of Practice" space, faculty would engage in conversations
with others with similar interests in order to plan technology integration.
Content in each of the spaces is driven by the content and activity in the
others. For example, a faculty member entering through the Effective Practices
space may decide that they would like to learn how to integrate the same technology
used in a particular story in the database. They would follow a link from the
story to a tutorial in the Learning Modules space, or perhaps find out about
a face-to-face workshop related to the technology described in the success story.
On the other hand, they may decide to join a discussion with faculty members
in their own discipline who have integrated technology in a way similar to the
success story. They would then follow a link to an online discussion in the
Communities of Practice space. In this way, the model provides encouragement
for faculty to participate in each of the spaces, but d'es not require it. The
model is also flexible and learner-centered, providing opportunities for faculty
to engage in project-based learning, collegial communities, and effective practices
research and demonstration at their own pace and by their own choice.
It is the flexibility of the framework that addresses the diffusion of innovations
cited earlier. Imagine an Early Adopter who tends to be project-oriented in
their implementation of technology. Their project orientation would support
the development of a good success story for the Effective Practices space. A
more pragmatic Early Majority faculty member would be able to study the success
story for proof of the application's efficacy. The Early Adopter might also
participate in a number of communities of practice, because of their horizontal
interest in the application of technology. At the same time, the Early Majority
faculty member, with their vertical connectedness, would be interested in a
specific community formed around the interests of a shared discipline. There
are a variety of ways that the open, flexible framework provides access to faculty
development that are differentiated based on the needs and interests of Early
Adopter and Early Majority faculty.
Testing the Framework
We have not yet overseen the implementation of such a comprehensive framework.
However, concepts central to the framework have been developed through work
with higher education practitioners, while components of the model have been
prototyped. Limited feedback thus far confirms the relevance of the model, though
it is clear that a careful process of assessing faculty and determining their
categories will be critical to the model's success.
The faculty development framework outlined here provides for differentiated
participation based on "Individual Innova-tions." Not all faculty members will
be interested in using tech-nology for the same reasons, nor will they have
the same expectations about the outcomes they might achieve through technology
integration. There are fundamental differences in the ways that people approach
the adoption of an innovation, and programs designed to encourage such adoption
must be sensitive to these differences.
Carr, V.H. (1999) "Technology Adoption and Diffusion," United
States Air Force Air War College Gateway to Internet Resources. Available
Accessed October 7, 2002.
Donovan, Mark (1999) "Rethinking Faculty Support." The Technology
Source, September/October 1999. Available online at http://ts.mivu.org/default.asp?show=article&id=612.
Accessed October 7, 2002.
Geoghegan, William H. (1994) "Whatever Happened to Instructional Technology,"
paper presented at the 22nd Annual Conference of the International Business
Schools Computing Association. Baltimore, MD.
Hagner, Paul and Schneebeck, Charles (2001) "Engaging the Faculty,"
in Educause Leadership Strategies, Volume 5, Technology-Enhanced Teaching
and Learning: Leading and Supporting the Transformation on Your Campus.
Moore, Geoffery. (1991) Crossing the Chasm: Marketing and Selling
Technology Products to Mainstream Customers, New York: Harper Business.
Rogers, Everett M. (1962) Diffusion of Innovations, New York:
Free Press of Glenc'e.