Adoption, Diffusion, Implementation, and Institutionalization of Educational Technology

Daniel W. Surry

University of South Alabama

Donald P. Ely

Syracuse University

Adoption, Diffusion, Implementation, and Institutionalization of Educational Technology

Educational technology is a field of innovation and change. Many of the most important products and practices developed by educational technologists require dramatic shifts in the way we think about, deliver, administer, and assess instruction and training. Studying the adoption, diffusion, implementation, and institutionalization of innovations is essential to the field of educational technology because the field has suffered from a lack of widespread acceptance of technology (Burkman, 1987). While it’s possible to point to some notable exceptions, such as the common use of electronic mail or word processors in higher education (Green,1996) or the growing use of performance technology in industry (Desrosiers & Harmon, 1996), the way that education and training are conducted has changed very little during the past few decades.

One major reason for this lack of utilization is that educational technologists have concentrated their efforts on developing instructionally sound and technically superior products while giving less consideration to other issues. Technical superiority, while important, is not the only factor that determines whether or not an innovation is widely adopted--it might not even be the most important factor (Pool, 1997). A complex web of social, economic, technical, organizational, and individual factors interact to influence which technologies are adopted and to alter the effect of a technology after it has been adopted (Segal, 1994). In order to fully understand the field, practitioners have to understand more than just hardware, software, design models, and learning theory. Understanding why people use educational technology and, perhaps more importantly, why they don’t is at the core of the process. That’s where adoption, diffusion, implementation, and institutionalization come in.

In this chapter, we will discuss the adoption, diffusion, implementation, and institutionalization of educational technology. We will begin by looking at some of the best known theories about adoption and diffusion. Following this we will discuss some examples of how adoption and diffusion theory has been incorporated into the field of educational technology. Then, we will discuss a very important trend--the gradual shift in focus from thinking about adoption (the initial decision to use an innovation) to thinking about implementation and institutionalization. We will define implementation and institutionalization and discuss why this shift is happening. We will also provide a list of conditions that contribute to implementation (Ely, 1999) and include a summary and conclusions.

Overview of the Adoption and Diffusion Process

There has been a long and impressive history of research related to the adoption and diffusion of innovations (Surry & Brennan, 1998). Many of the most important and earliest studies in this area were conducted by researchers working in the field of rural sociology (Rogers, 1995). In fact, a study that investigated the diffusion of hybrid-seed corn (Ryan & Gross, 1943) is considered to be the first major, influential diffusion study of the modern era (Rogers, 1995). Other researchers have investigated the diffusion of innovations in such diverse fields as solar power (Keeler, 1976), farm innovations in India (Sekon, 1968), and weather forecasting (Surry, 1993).

The most widely cited and most influential researcher in the area of adoption and diffusion is Everett Rogers. Rogers’ Diffusion of Innovations is perhaps the single most important book related to this topic and provides a comprehensive overview of adoption and diffusion theory. It was first published in 1962 and now in its 4th edition (Rogers, 1995).

One of the most important theories discussed by Rogers is the Innovation-Decision Process Model. As shown in Figure 1, this model suggests that the adoption of an innovation is not a single act, but a process that occurs over time. Potential adopters go through five stages when interacting with an innovation. The first stage is “Knowledge” in which potential adopters find out about an innovation and gain a basic understanding of what it is and how it works. The second stage is “Persuasion” in which potential adopters form a positive or negative impression of the innovation. It is only in the third stage, “Decision”, that the innovation is actually adopted or rejected. The fourth stage, “Implementation”, occurs when the innovation is actually used. In the fifth stage, “Confirmation”, the adopter seeks information about the innovation and either continues or discontinues use of the innovation. The Confirmation Stage might also describe the

adoption of an innovation that was previously rejected.

Figure 1. Five stages of Rogers’ (1995) Innovation-Decision Process Model.

Another important and influential idea discussed by Rogers is the concept of adopter categories. This concept states that, for any given innovation, a certain percentage of the population will readily adopt the innovation, while others will be less likely to adopt. According to Rogers, there is usually a normal distribution of the various adopter categories that forms the shape of a bell curve (see Figure 2). “Innovators”, those who readily adopt an innovation, make up about 2.5% of any population. “Early Adopters” make up approximatley 13.5% of the population. Most people will fall into either the Early Majority (34%) or the Late Majority (34%) categories. “Laggards”, those who will resist an innovation until the bitter end, comprise about 16% of the population. The concept of adopter categories is important because it shows that all innovations go through a natural, predictable, and sometimes lengthy process before becoming widely adopted within a population.

Figure 2. Hypothesized distribution of adopter categories within a typical population.

The concept of perceived attributes (Rogers, 1995) has served as the basis for a number of diffusion studies (e.g., Fliegel & Kivlin, 1966; Wyner, 1974). Perceived attributes refers to the opinions of potential adopters who base their feelings about of an innovation on how they perceive that innovation in regard to five key attributes: Relative Advantage; Compatibility; Complexity; Trialability, and; Observability. In short, this construct states that people are more likely to adopt an innovation if the innovation offers them a better way to do something, is compatible with their values, beliefs and needs, is not too complex, can be tried out before adoption, and has observable benefits. Perceived attributes are important because they show that potential adopters base their opinions of an innovation on a variety of attributes, not just relative advantage. Educational technologists, therefore, should try to think about how potential adopters will perceive their innovations in terms of all of the five attributes, and not focus exclusively on technical superiority.

The S-shaped adoption curve is another important idea that Rogers (1995) has described. This curve shows that a successful innovation will go through a period of slow adoption before experiencing a sudden period of rapid adoption and then a gradual leveling off . When depicted on a graph , this slow growth, rapid expansion and leveling off form an S-shaped curve (see Figure 3). The period of rapid expansion, for most successful innovations, occurs when social and technical factors combine to permit the innovation to experience dramatic growth. For example, one can think of the many factors that combined to lead to the widespread acceptance of the World Wide Web between the years 1993 and 1995.

Figure 3. Example of an S-curve showing initial slow growth, a period of rapid adoption, and a gradual leveling off.

Diffusion Theory Applied to Educational Technology

The theories and concepts discussed by Rogers in Diffusion of Innovations are applicable to the study of innovations in almost any field. A number of researchers have used these theories and concepts to study the adoption and diffusion of educational technology innovations. In the field of educational technology, diffusion theory has most often been applied to the study of either artifacts, such as computers, or knowledge, such as innovative teaching techniques (Holloway, 1996). Ernest Burkman (1987) is one of the authors who specifically links diffusion theory with educational technology. Burkman realized that educational technology had been suffering from little utilization and turned to diffusion theory for a possible solution. He used perceived attributes to develop a method for developing instructional products that would be more appealing to potential adopters. Burkman called his new approach “ user-oriented instructional development (UOID)”. The five steps in Burkman’s UOID are:

1) Identify the potential adopter

2) Measure relevant potential adopter perceptions

3) Design and develop a user-friendly product

4) Inform the potential adopter (of the product's user-friendliness)

5) Provide Post Adoption Support

In addition to Burkman, other researchers have incorporated diffuison theory into educational technology applications. For example, Stockdill and Morehouse (1992) used diffusion concepts in a checklist of factors to consider when attempting to increase the adoption of distance learning and other educational technologies. Farquhar and Surry (1994) used diffusion theory to identify and analyze factors that might impede or assist the adoption of instructional innovations within organizations. Sherry, Lawyer-Brook, and Black (1997) used diffusion concepts as the basis for an evaluation of a program intended to introduce teachers to the Internet. A growing amount of dissertation research is being conducted in the area of diffusion theory as it is related to educational technology.

From Diffusion and Adoption to Implementation

There appears to be a growing trend in innovation research away from adoption and diffusion towards implementation and institutionalization. As the adoption and diffusion process moves along, the actual use or implementation of an innovation in a specific setting becomes more and more important. Of course, implementation should be an integral part of a comprehensive and systematic change plan from the beginning. Michael Fullan, prominent researcher in this area, defines implementation as "...the actual use of an innovation in practice." Further, he calls the implementation perspective, "...both the content and process of dealing with ideas, programs, activities, structures, and policies that are new to the people involved" (Fullan, 1996). Until Fullan and Pomfret (1977) spelled out the process and issues in their review of implementation research, not much was said about the steps after diffusion and adoption.

From Replication to Mutual Adaptation

In the process of implementation, innovations that require replication for successful outcomes often follow an approach that is analogous to behavioral learning. That is, each product, procedure, and practice has to maintain a high fidelity to the original or else success cannot be guaranteed. Fullan and Pomfret (p. 360) introduced the concept of "mutual adaptation" whereby local conditions should be considered and modification of original materials and procedures should be altered accordingly. It was felt that the local professionals could make better assessments of the needs and potential reception of the innovation than the original developer or researcher. Purists, however, felt that if replication was not identical to the original specifications, implementation might fail.

Once professional educators realized that they could modify programs, products and practices, it was a short step to an approach that was less “lock step” and more analogous to constructivism. Local participation in the modifications created a greater sense of ownership.

Other Models

One of the tools often used to guide implementation efforts in schools is Hall's Concerns Based Adoption Model (CBAM) (Hall & Hord, 1987). In the implementation phase of this model, the Levels of Use (LoU) scale is introduced (Hall & Loucks, 1975). The basic levels are: Nonuse; Orientation (initial information); Preparation (to use); Mechanical use; Routine; Refinement; Integration; and Renewal. The last four levels actually move into the area of institutionalization discussed later in this chapter. A modification of the LoU, Levels of Technological Implementation (LoTi), based on measurement of classroom use of computers, has been proposed by Moersch (1995). Moersch modifies Hall's levels to provide guidance for determining the extent of implementation using seven levels: Nonuse; Awareness; Exploration; Infusion; Integration; Expansion; and Refinement.

What About Resistance to Innovations?

Over the years there have been studies and explorations of the resistance factors that thwart diffusion and implementation efforts. Prominent among those who have journeyed into this puzzling morass are Zaltman and Duncan (1977). These authors define resistance as "...any conduct that serves to maintain the status quo in the face of pressure to alter the status quo." The basic argument has been that if we knew what types of resistance exist, perhaps we could design strategies to combat them. There are many different types of resistance. They can be classified as cultural, social, organizational and psychological. This approach to implementation has been successful only when strategies for overcoming specific points of resistance have been developed.

Looking for Facilitative Conditions

A less common approach to understanding the process of implementation has been to tease out reasons for successful programs rather than to identify the barriers. Where innovations have been adopted and implemented, what are the conditions that appear to facilitate the process? Are there consistencies among the facilitating conditions from innovation to innovation and from place to place? This logic reverses a concern for resistance to a more positive one of facilitating factors thus providing an avenue for further exploration. Rather than to come up with ways to get around resistance, a series of studies looked at successful implementation of innovations and asked, "Why were these innovations successful?" The findings of these studies uncovered eight conditions that contribute to implementation (Ely, 1999).

1. Dissatisfaction with the status quo. Things could be better. Others seem to be moving ahead while we are standing still. Dissatisfaction is based on an innate feeling or is induced by a "marketing." campaign.

2. Knowledge and skills exist. Knowledge and skills are those required by the ultimate user of the innovation. Without them, people become frustrated and immobilized. Training is usually a vital part of most successful innovations.

3. Availability of resources. Resources are the things that are required to make implementation work--the hardware, software, audiovisual media and the like. Without them, implementation is reduced.

4. Availability of time. Time is necessary to acquire and practice knowledge and skills. This means good time, "company" time, not just personal time at home.

5. Rewards and/or incentives exist. An incentive is something that serves as an expectation of a reward--a stimulus to act. A reward is something given for meeting an acceptable standard of performance.

6. Participation. This is shared decision-making; communication among all parties involved in the process or their representatives.

7. Commitment. This condition demonstrates firm and visible evidence that there is endorsement and continuing support for the innovation. This factor is seen most frequently in those who advocate the innovation and their supervisors.

8. Leadership. This factor includes (1) leadership of the executive officer of the organization and, sometimes, by a board and (2) leadership within the institution or project related to the day-to-day activities of the innovation being implemented.

Variables in the Setting and the Innovation Itself

It is clear that the eight conditions are present in varying degrees whenever examples of successful implementation are studied. What is not so clear is the role of the setting in which the innovation is implemented. The setting and the nature of the innovation are major factors influencing the degree to which each condition is present. Some of the variables in the setting include organizational climate, political complexity and certain demographic factors. Some of the most important variables regarding the innovation are the attributes of the innovation discussed earlier--its relative advantage (when compared with the current status), compatibility with the values of the organization or institution, its complexity (or simplicity), trialability before wholesale adoption and observability by other professionals or the public. But...is implementation the final stage?

Implementation should lead naturally into institutionalization. Some writers call it "routinization" or "continuation.” The ultimate criterion for a successful innovation is that it is routinely used in settings for which it was designed. It has become integral to the organization or the social system and is no longer considered to be an innovation. A classic work on the topic defines institutionalization as "...an assimilation of change elements into a structured organization modifying the organization in a stable manner....a process through which an organization assimilates an innovation into its structure" (Miles, Eckholm, & Vandenburghe, 1987).

Indicators of Institutionalization

According to the Regional Laboratory for Educational Improvement of the Northeast and Islands (Eiseman, Fleming & Roody, 1990), there are six commonly accepted indicators of institutionalization:

1. Acceptance by relevant participants--a perception that the innovation legitimately belongs;

2. The innovation is stable and routinized;

3. Widespread use of the innovation throughout the institution or organization;

4. Firm expectation that use of the practice and/or product will continue within the institution or organization;

5. Continuation does not depend upon the actions of specific individuals but upon the organizational culture, structure or procedures; and

6. Routine allocations of time and money.

Once implementation has been achieved, one more decision must be made: "Is this innovation something we want to continue for the immediate future?" If it is, the above criteria could be used to assess the extent to which the innovation is institutionalized. Several other indicators of routine use, called "passages and cycles" are listed by Yin and Quick (1978): support by local funds; new personnel classification; changes in governance; internalization of training; and turnover of key personnel.

Summary and Conclusions

Case studies of diffusion, adoption, implementation and institutionalization have been conducted in many organizations and settings. One important conclusion is that there is no formula for this process. There are many elements that should be considered in the process, most of them outlined in this chapter. However, simple transfer of these principles to specific environments would likely be futile. Just as most instructional development requires a systemic approach so does the change process. There is no substitute for a "front-end analysis" or

needs assessment that yields the goals and objectives to be attained. Communication among all participants throughout the process is essential. A strategy or plan for achieving the goals is the best way to proceed when considering the many variables that are likely to affect the outcomes.

Evaluation should be a constant partner during the process.

All of this activity should be coordinated by a change agent--a person who is sensitive to the variables that will impinge on the process. The change agent could be an internal person or an external specialist. Awareness and experience with the change process is essential for a

successful outcome.

References

Burkman, E. (1987). Factors affecting utilization. In R. M. Gagne (Ed.) Instructional Technology: Foundations. Hillsdale, NJ: Lawrence Erlbaum.

Desrosiers, S.M. & Harmon, S.W. (1996). Performance support systems for education and training: Could this be the next generation? In M.L. Bailey and M.J. Jones (Eds.) Selected Papers from the Fifth Annual LEPS Research Symposium: Technology, Education, and Work. Dekalb, IL: Northern Illinois University.

Eiseman, J.W., D.S. Fleming and D.S. Roody. (1990) Making sure it sticks: The school improvement leader's role in institutionalizing change. Andover, MA: The Regional Laboratory.

Ely, D.P. (1999) New perspectives on the implementation of educational technology innovations. Paper delivered at the Association for Educational Communications and Technology Annual Conference, Houston, TX, Feb., 1999.

Farquhar, J.D., & Surry, D.W. (1994). Adoption analysis: An additional tool for instructional developers. Education and Training Technology International, 31(1), 19-25.

Fliegel, F.C. & Kivlin, J.E. (1966). Attributes of innovations as factors in diffusion. American Journal of Sociology 72(3), 235-248.

Fullan, M. (1996). Curriculum implementation. In D. P. Ely and T. Plomp (Eds.) International encyclopedia of educational technology. Oxford: Elsevier Science.

Fullan, M. and Pomfret, A. (1977) Research on curriculum and instruction implementation. Review of Educational Research, 47(1), 335-397

Green, K.C. (1996). The coming ubiquity of information technology. Change. March/April. 259-263.

Hall, G. and Hord, S. (1987) Change in schools: Facilitating the process. Albany, NY: SUNY Press.

Hall, G. and Loucks, S. (1975) Levels of use of the innovation: A framework for analyzing innovation adoption. Journal of Teacher Education, 26(1), 52-56.

Holloway, R.E. (1996). Diffusion and adoption of educational technology: A critique of research design. In David H. Jonassen (Ed.) Handbook of Research for Educational Communications and Technology. New York: Simon & Schuster Macmillan.

Keeler, J.D. (1976). Application of innovation attributes dimension to a new solar energy product: Implications for advertising and public relations. Dissertation Abstracts International, 37, 7386A. (University Microfilms No. 77-11, 540).

Miles, M.B., Eckholm, M. & Vandenburghe, R. (Eds.) (1987). School improvement: Exploring the process of institutionalization. Leuven, Belgium: ACCO

Moersch, C. (1995) Level of technology implementation (LoTi): Framework for measuring classroom technology use. Educational Technology, Nov.,40-42.

Pool, R. (1997). Beyond engineering: How society shapes technology. New York: Oxford University Press.

Rogers, E.M. (1995). Diffusion of innovations, 4th ed.. New York: Free Press.

Ryan, B. & Gross, C. (1943). The diffusion of hybrid seed corn in two Iowa communities. Rural Sociology, 8, 15-24.

Segal, H. P. (1994). Future imperfect: the mixed blessings of technology in America. Amherst: The University of Massachusetts Press.

Sekon, G.S. (1968). Differential perceptions of attributes of innovations by professional advocates and their clientele. Dissertation Abstracts, 30, 1245A. University Microfilms No. 69-14, 567).

Sherry, L., Lawyer-Brook, D., & Black, L. (1997). Evaluation of the Boulder Valley Internet Project: A Theory-Based Approach to Evaluation Design. Journal of Interactive Learning Research, 8(2), 199-234.

Surry, D. W. (1993). The role of perceptions in the development and adoption of three

computer-based learning modules. (Doctoral Dissertation, The University of Georgia, 1993).

Dissertation Abstracts International, 54 (9), 3409A - 3410A.

Stockdill, S.H., & Morehouse, D.L. (1992). Critical factors in the successful adoption of technology: A checklist based on TDC findings. Educational Technology, 32 (1), 57-58.

Surry, D. W. & Brennan, J. P. (1998). Diffusion of instructional innovations: Five important, unexplored questions. (ED 422 892).

Wyner, N. B. (1974). A study of diffusion of innovation: Measuring perceived attributes of an innovation that determine the rate of adoption. Dissertation Abstracts International, 35, 3583A. (University Microfilms No. 74-26, 628).

Yin, R. K. & Quick, S. K. (1978). Changing urban bureaucracies: How new practices become routinized. Lexington, MA D.C. Heath.

Zaltman, G. & Duncan, R. (1977). Strategies for planned change. New York: John Wiley and Sons.