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An analysis of online course enrollments for students and faculty members in a College of Professional Studies. The research project includes frequency data of students and faculty members who have taken or not taken online courses, summaries of findings, and figures illustrating the attributes of online learning and teaching, such as relative advantage, compatibility, complexity, trialability, and observability. The study aims to investigate the relationship between these attributes and students' and faculty members' adoption of online education.
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Running Head: Roger’s Five Attributes of Innovation Diffusion and Online Education.
Rogers’ Five Main Attributes of Innovation on the Adoption Rate of Online Learning
Truman Do
PSOC Master of Arts Organizational Change Hawaii Pacific University
Publication Date: 8/15/
Certification Page
The Professional Paper submitted by this student has been reviewed and is deemed to have met the Professional Paper (PSOC 7100/PSOC 7200) requirement for HawaiiPacific University's, College of Professional Studies Graduate Program.
Student Name: Truman Do Title of Professional Paper: Roger’s Five Attributes of Innovation Diffusion and Online Education 8/15/ Gerald Glover, PhD Date Professor of Organizational Change
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List of Figures
Figure Page 1 The research process 13 2 Students who have taken online courses 104 3 Students who have not taken online courses 113 4 Faculty members who have taught online courses 122 5 Faculty members who have not taught online courses 131 6 Student and faculty members samples 140
Acknowledgements I thank the faculty members in the College of Professional Studies and particularly in the Master of Arts in Organizational Change program. Dr. Gerald Glover, Dr. Richard Ward, Dr. Larry Zimmerman, and Dr. Gordon Jones were instrumental for their assistance and mentorship in the completion of this research project that began in fall 2005 and ended summer 2006. Dr. Gerald Glover was the primary source of help that I relied on to complete my research project. He guided me from the initial process of formulating the problem statement to the completion the paper. I did not think I would be able to complete this mammoth project without his guidance. Dr. Richard Ward was another important source of assistance for me. I was impressed with his extraordinary ability with paying attention to details. He caught many mistakes that I seemingly missed. In addition, a major part of the paper was influenced by his feedback. Dr. Larry Zimmerman was the person responsible for me in coming up with the problem statement. In the beginning, I was struggling with coming up with a workable problem statement, for weeks. He suggested that I should use Rogers’ innovation diffusion model. The last but not least was the contribution of Dr. Gordon Jones. Despite his demanding schedule, he made time on several occasions to share his extensive knowledge and expertise on the subject of online education. I gained a greater
Chapter One – Introduction Importance of Research Area Introduction. Every since 1995, Hawaii Pacific University (HPU), like many other post-secondary educational institutions across the country, has been integrating the online education component to its degree programs. A few years ago, HPU began to offer the Master of Arts in Organizational Change entirely online. Recently, it has offered prospective students the opportunity to pursue the business degree at the undergraduate level entirely online. There are various reasons for the increased offering of online education at this school. Three groups of stakeholder who have been creating the growth in online education are: school administrators, faculty members, and students. School administrators have been pushing for more online courses to reduce overhead costs that associated with rent, utility, insurance and janitorial services, etc. The national average instructor to student ratio was 20-to-1 per class, and this ratio was enforced by the limitation of a classroom size, faculty resistance to grading larger numbers of tests and papers, and the desire for smaller classes and individual attention (Housel & Bell, 2001). Likewise, faculty members have desired to teach online courses due to perceived advantages. One advantage cited was the ability to measure and monitor student accountability and participation in ways that were not feasible with traditional campus- based courses (Glover, 2006). And others, they like the flexibility of conducting classes while in other localities.
Students’ interest in online learning is quite similar to the faculty members. They want the flexibility to take classes online without leaving their home or terminating their present employment. In addition, the cost associated traditional education, such as travel would be reduced or eliminated (Glover, 2006). It is critical to measure the attributes that contribute to the adoption rate of online education by students and faculty members. The innovation diffusion model conceptualized by Dr. Everett Rogers has been applied by researchers to study the diffusion of new educational programs (Rogers, 2003). The advantages of online education perceived by faculty members may not be true as perceived by students. School administrators must carefully and intelligently craft an online education strategy that will benefit both stakeholders. In order for online education to be sustainable, two things must happen. Faculty members must want to teach in an online environment. Likewise, students must want to learn in an online environment. It is imperative that both stakeholders perceive the attributes of online education to be better than traditional campus-based education. Identification of Problem Statement of the Research Problem. The objective of this research project is to investigate the influence of Rogers’ five attributes of innovation diffusion on the adoption rates of online education by faculty members and graduate students in the College of Professional Studies at Hawaii Pacific University. First hypothesis : the attributes of relative advantage, compatibility, complexity (simplicity), trialability and observability of online learning are positively related to students who have taken online courses, in the College of Professional Studies.
research project. Instead of measuring the perceived complexity of online education, the researcher measured the perceived simplicity of online education. Trialability is the degree to which an innovation may be experimented with on a limited basis (Rogers, 2003). The subdimensions are the ability of adopters to try an innovation on installment basis, re-invention, and the ease of trying. Observability is the degree to which the results of an innovation are visible to others (Rogers, 2003). The subdimensions of this attribute are the difficulty in observing and in describing to others. Brief Overview of the Research Design A research chart of figure 1.0 is illustrated below to display the research process.
Recognition ofChapter 1: a problem
Statement of aChapter 1: problem
Chapter 1:Identify hypotheses inthe research
Chapters 2 & 3:Collection of secondary &primary data
Analysis ofChapter 4: data
Chapter 5:Accept or reject H. /Advice
Methods of inquiry. This chart illustrates a year and half of cyclical and methodical research process between the chapters in this project that began in the fall 2005 and ended in the summer 2006. The step or steps in each chapter affected the strategy and content of the next chapter. This research required the constant movement of back and forth to revise the chapters. The entire research project consisted of five chapters. Chapter one in the research process consisted of three principal steps. The first step was to identify a problem in the field of organizational change and development. The second step was to articulate a clear problem statement. Finally, the third step was to state one or more hypotheses to be tested. The first step in the research process was to identify a question that needs to be answered or a problem that needs to be solved. To identify a problem, the Innovation Diffusion book was extensively consulted. In addition, several research articles were searched and reviewed. The second step in the research process was to articulate a clear statement of problem. In addition, it had to be grammatically accurate. One problem statement was articulated to investigate the influence of innovation diffusion on the adoption rate of online education. Due to the limitation of time, the researcher only articulated one problem statement. The division of sub-problems was not feasible for this research project. The third step in the research process was to express one or several hypotheses. The objective was not to accept or reject the hypotheses, but it was to support or not support it. Four hypotheses were constructed from the problem statement. The first two
to administer the surveys in that month. In June, students were not occupied with their final exams. The primary data came from student and faculty member responses to the survey. They were asked to answer 21 questions regarding the five attributes of online education. The data was collected in two ways. First, the researcher approached all the faculty members whose courses were taught on campus in the College of Professional Studies. After all the respondents who completed the surveys on campus, the researcher contacted the faculty members who were teaching online classes to distribute the survey link to their students. Chapter Four involved the actual analysis of the primary data collect through the survey collection tool. The statistical analysis utilized was descriptive statistics and frequency distribution. The fifth step in the research process was to analyze results of the data and to form conclusions. As for the analysis, the findings were subjected to a descriptive analysis. The objective was to ascertain the strength of the relationship between the independent and dependent variables. Chapter Five and the final chapter in this research project involved the summary of the findings. In addition, recommendations were required to complete this chapter. The final step in the research process was to offer recommendations and solutions to the problem statement and hypotheses. An experimental project would be ideal, but time and resources were important considerations to the research design. Results from an experiment would show direct causations between the variables. Every aspect of the
research design for this research paper was influenced by work of “Diffusion of Innovations.” The first assumption. The first assumption was that online education has become an integral part of higher education at HPU. The second assumption. The second assumption was that HPU would continue to increase the offering of online courses and degree programs. The third assumption. The third assumption was that the demand from students and faculty members at HPU for online education would continue to grow. Criteria for testing H/PS. Each independent variable was measured with Likert- type numerical values. First, the number “5” was designated as “strongly agree.” Second, the number “4” was designated as “agree.” Third, the number “3” was designated as “No opinion.” Fourth, the number “2” was designated as “disagree.” Fifth, the number “1” was designated as “strongly disagree.” The dependent variable is the rate of adoption, and it is defined by the relative speed with which an innovation is adopted by members of a social system (Roger, 2003). First, the number “1” was designated for people who have taken or taught an online course. Second, the number “2” was designated for people who have not taken or taught an online course. Faculty members and students received the same survey. Of courses, there were one to two questions that were slightly different between the two surveys. Limitations to the Research Biases in research. All researches contain biases. It is critical for a researcher to recognize and state them clearly (Roger, 2003; Leady & Ormrod, 2005). With this recognition, the credibility of the research project and the researcher would be enhanced.
innovation diffuses in wider context. The fifth strategy is for innovation diffusion researchers or change agents to investigate and understand the motivation to the adoption of an innovation. At times, adopters may be unable to communicate the reasons why they have adopted or may be unwilling to communicate the reasons why they have adopted an innovation. Many times, researchers would use questionnaires to probe the motivation, but this method is not adequate. Another bias is the inclination for diffusion researchers to side with the change agencies that support innovations rather than with individuals who are possible adopters (Rogers, 2003). Consequently, there is a tendency to blame the individuals rather the system for a problem. In some cases, it is suitable to focus on the individuals to solve problems. For the most, an individual problem is part of a larger problem within a larger social context. Later adopters and laggards are often individually held responsible for not adopting an innovation and/or for being much later in adopting than other adopters of their social systems. Three reasons explain why an individual-blame bias exists in diffusion research (Rogers, 2003). The blame-orientation of sponsoring change agencies affects the perception of diffusion researchers. Many of these agencies tend to focus on the individuals as the source of the problem. Another reason could be that fact that it is much easier for diffusion researchers to change individuals than the entire social system. Finally, it is easy to have access to individuals than the whole system to conduct diffusion research. Many of the research tools have been created measure single units or individuals. Diffusion researchers rely heavily on surveys, and this methodology tends to reinforce this bias.
Innovation diffusion researchers can overcome the individual-blame bias by applying at least one out of the three identified strategies (Rogers, 2003). One strategy is for diffusion researchers to seek other substitutes to individuals as a unit of measurement and analysis. Another strategy is to have an open mind regarding issues and not to take the positions of agencies at their face value. To go one step further, all stakeholders in the innovation diffusion process should be involved in defining the innovation problem. The agencies and their change agents should not have exclusive power in this process. A general bias that diffusion researchers may encounter is the results may not by representative of the actual population. This bias occurs when the sample is not randomly selected. The only time when random sampling is possible is when researchers have control of the population. To overcome this problem, the only way is to collect a large sample. Hopefully, the sample results would reflect the results of the population. Constraint in research. Time is the great constraint for researchers (Leady & Ormrod, 2005). Often, a researcher wants to conduct a research project that is comprehensive and significant for publishing purpose. The size of the research may take years. When time is not in the control of the researcher, he or she needs to reduce the scope of the research. The five attributes of innovation diffusion explain the adoption rate of innovations from 49 to 87 percent, but it does not explain everything (Rogers, 2003). In addition to main five, other variables such as (1) the type of innovation-decision, (2) the nature of communication channels diffusing the innovation at various stages in the innovation- decision process, (3) the nature of the social system in which the innovation is diffusing, and (4) the extent of change agents’ promotion efforts in diffusing the innovation, affect
