This document discusses diffusion theories and the adoption of innovations. It describes Rogers' innovation-decision process model involving knowledge, persuasion, decision, implementation, and confirmation stages. It also outlines Rogers' adopter categories of innovators, early adopters, early majority, late majority, and laggards. The document applies these concepts to instructional design and technology, discussing determinist and instrumentalist perspectives and models like CBAM and UTAUT. It analyzes factors influencing adoption and provides examples applying the theories to objectives and problem-based learning.

1. Diffusion Theories
INTC 5110
Fall 2010

2. Diffusion and Adoption
 Technology and Instructional Design can be seen as
innovations
 New inventions/practices
 The success of innovations lies in how widely they
are distributed (diffused) and accepted (adopted).
 Diffusion and adoption has to do with studying the
extent to which an innovation is used or not used,
and why.
 Looks at how people adapt to innovations, and the
complexity of social and other structures that impact an
innovation’s acceptance.
 http://rer.sagepub.com/content/79/2/625.full

3. Process
 Everett Rogers’ book, Diffusion of
Innovations, first set out this idea of a
diffusion and adoption process.
 Innovation-Decision Process Model:
Knowledge Persuasion Decision Implementation Confirmation

4. Adopter Categories
 In each community, organization, or group there are
different types of people:
 Innovators are the 2.5% who readily adopt. These are the
people who will try any new technology that comes along.
 Early Adopters are the 13.5% who are persuaded quickly
and try the innovation and find it useful.
 Early Majority are the 34% who wait for Early Adopters to
have success then adopt.
 Late Majority are 34% who adopt once an innovation has
become commonplace.
 Laggards are the 16% who either never adopt or fight
adoption after it has become common.

5. Adoption Curve

6. FIGURE 1. How individual adoptions compose diffusion.
Straub E T REVIEW OF EDUCATIONAL RESEARCH
2009;79:625-649
Copyright © by American Educational Research Association

7. Time to Adoption
 Usually adoption
follows a pattern of a
slow start (only the
Innovators and Early
Majority), followed by a
rapid adoption (the
Early Majority and Late
Majority) then slowing
down.
Source: http://www.sfu.ca/~anethert/cns-491-lecs/cns-491-5/id53.htm

8. Theory of Perceived Attributes (Rogers)
 Increased adoption if perceived by adopters
in certain ways:
 Trialability - Can be tried on a limited basis before
adoption
 Observability- Offers observable results
 Relative Advantage - Has an advantage relative
to other innovations
 Complexity - Is not overly complex
 Compatibility - Is compatible with existing
practices and values.

9. How it Applies
 When looking to infuse technology into a
community (an organization or a school
district, for example), the diffusion and
adoption process helps you:
 Plan for best chance of success
 Identify important persons (users)
 Measure potential concerns/ problems
 Identify obstacles and plan to overcome

10. How it Applies
 Used for:
 Planning systemic change and reforms
 Increasing utilization of specific instructional
products and processes
 Useful as a tool for evaluating progress

11. Determinist versus Instrumentalist
 Determinist – technology is a force that takes
over the process, and we are knowing or
unknowing slaves to it
 Instrumentalist – we control technology, using
it as a tool for our own aims and goals
http://www2.gsu.edu/~wwwitr/docs/diffusion/

12. Determinist versus Instrumentalist
http://www2.gsu.edu/~wwwitr/docs/diffusion/

13. Determinist versus Instrumentalist
 Determinist ID models
 Deterministic in belief that superior technological
products and systems will, by virtue of their
superiority alone, replace inferior products and
systems
 Potential adopters are viewed as being
predisposed to adopt innovations that are
quantifiably superior (top-down?)
 Diffusion through technological superiority is the
implicit goal of the process
http://www2.gsu.edu/~wwwitr/docs/diffusion/

14. Determinist versus Instrumentalist
 Instrumentalist ID models
 Focus on the human and interpersonal aspects of
innovation diffusion
 View the individual who will ultimately implement
the innovation in a practical setting, as the primary
force for change
 A variety of factors, most unrelated to technical
superiority, influence the decision to adopt or
reject an innovation
http://www2.gsu.edu/~wwwitr/docs/diffusion/

15. Determinist versus Instrumentalist
http://www2.gsu.edu/~wwwitr/docs/diffusion/

16. User Oriented Instructional Development
 Burkman (1987)
 Identify the potential adopter
 Measure relevant potential adopter perceptions
 Design and develop a user-friendly product
 Inform the potential adopter (of the product's
user-friendliness)
 Provide Post Adoption Support

17. CBAM (Concerns Based Adoption Model)
 Hall and Hord (1987)
 Change facilitators understand change from the
point of view of the people who will be affected by
change
 Bring about systemic restructuring by
understanding the social, political, and
interpersonal aspects
 http://www.nas.edu/rise/backg4a.htm

18. CBAM Assumptions
 CBAM was developed based on six explicit
assumptions:
 “Change is a process, not an event.”
 “Change is accomplished by individuals.”
 “Change is a highly personal experience.”
 “Change involves developmental growth.”
 “Change is best understood in operational terms.”
 “The focus of facilitation should be on individuals,
innovations, and context.”
 (Hord, Rutherford, Huling-Austin, & Hall, 1987)

19. CBAM Components
 Stages of concern (SoC)
 Levels of use (LoU)
 Innovation configuration (IC).

22. TAP and UTAUT
Technology Acceptance Model
Unified Theory of Acceptance and Use of Technology

23. Facilitative Conditions
 Ely (1999) identified eight common conditions
for implementation:
 Dissatisfaction with present process
 Knowledge and skills exist
 Availability of resources
 Availability of time
 Rewards and incentives
 Participation by all parties
 Commitment
 Leadership

24. Other Factors
 A host of other factors can also impact
whether an innovation is adopted, including:
 Organizational climate
 Demographics
 Relative advantage
 Complexity vs. Simplicity
 “Trialability” before wholesale adoption

25. Applied to Organizations
 So how does technology and instructional
design become diffused and adopted?
 What make some innovations more likely to
be adopted?
 What innovations have been successfully
implemented already?

26. Some Background
 Instructional Design and Technology (IDT)
 “ID” Came out of systems thinking and military/corporate
practice
 “T” developed from visual communications and instructional
media
 Where the two meet they have been prone to
misunderstandings
 See IDT people as strictly technologists
 See value as technology integration specialists
 Merely an add-on to existing practice, not as redefining
practice

27. Goal of IDT
 Understanding the potential for technology to
be used in conjunction with instructional
design to enhance learning and performance.
 Understand how people utilize technology,
and support the development of new
practices that foster learning and
achievement.
 Provide alternative methods and strategies
for adoption.

28. Example: Objectives
 Objectives
 In IDT field, started in 1960s with Mager, and also via
Programmed Instruction (Skinner).
 In K-12, started in 1970s with administrative push for
teacher planning.
 Expectations of their value have been high, but research
mixed.
 Many times seen as trivial by teachers and trainers.
 Best when used to make sound decisions about
instructional strategies
 Low impact for this innovation.

29. Example: Problem-Based Learning
 Idea that using authentic problems and cases
when teaching helps students achieve
higher-order outcomes such as critical
thinking.
 Often works when done correctly.
 However, it takes a great deal of work, and often
appears misaligned to curriculum standards (does
not teach to the test).
 Some adoption, but not on large scale.

30. Implications
 Obviously, IDT has not had wide adoption in K-12 schools.
 Expectations often not met.
 Not part of K-12 culture.
 Standards and other initiatives take precedence.
 Still seen as technologists.
 Yet we persist in trying to match the two, and we get many
students in Masters programs in IDT.
 Value seen at the small scale level (one teacher, one school)
 Inherent belief that we can do things better
 Technology is a tool, and ID is a process, with great potential; we
just need to figure out better ways of using them in K-12