Instructional Computer Use in Turkey
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Using Rogers’ Theory to Interpret Instructional Computer Use by COE Faculty in Turkey
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Abstract
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The purpose of this research study was to explore instructional computer use by faculty members
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in the College of Education (COE) at an Anatolian university in Turkey. The faculty members in the
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study reported low levels of use and expertise in instructional computer technologies. Variables
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significantly correlated with faculty members’ level of computer use were computer expertise, computer
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access, barriers to computer access, attitude toward computer use, support for computer use, and adopter
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categories based on innovativeness. The importance of administrative support and the need for faculty
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development were two major findings from this study. Rogers’ (2003) Diffusion of Innovations theory
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was used as the theoretical framework both in the process of data collection and in the interpretation of
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the results. Findings interpreted through Roger’s theory suggest that an action plan should take advantage
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of faculty members’ positive computer attitudes and collegial communication to increase their low levels
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of use and expertise in instructional technologies. Results from this study indicate the similarities between
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patterns in Turkey and the US and suggest the value for sharing knowledge internationally.
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Keywords: Instruction, Computer, Diffusion of Innovations, College of Education
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Instructional Computer Use in Turkey
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Using Rogers’ Theory to Interpret Instructional Computer Use by COE Faculty in Turkey
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Now that technology is widely available on all campuses (The Campus Computing Project,
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2001), the integration of this technology in higher education teaching and learning has become more and
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more important. Technology serves as a foundation to universities to create the appropriate learning
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organizations and supports the four components of universities: organization, people, learning, and
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knowledge (Marquardt & Kearsley, 1999). Higher education institutions must deal with the major issues
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relating to educational technology, including instructional strategies, appropriate educational software,
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training, and support (Willis, 1993). McKenzie (2001) and Parisot (1995) criticized the standard approach
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of higher education institutions and schools – they buy the new and complex technologies and simply
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make them available to faculty members and teachers. In fact, “if higher education wants to survive in the
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expansion of technology, then it must be prepared and prepare its faculty to implement the new
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technologies within their classrooms” (Hagenson, 2001, p. 2). Educators in teacher education programs
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must prepare pre-service teachers for the integration of technology into instruction. Faculty should use
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instructional technology to help their students achieve curricular objectives (Cagle & Hornik, 2001).
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While technology is used more often in administration and research, its use is less frequent in instruction
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(Spotts, 1999; Zhao & Cziko, 2001), since the integration of computer technologies into teaching
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challenges the traditions and practices of faculty members and universities (Anderson, Varnhagen, &
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Campbell, 1998; Pope, Hare, & Howard, 2002). In research designed to understand the technology use by
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College of Education (COE) faculty in the US, Sahin and Thompson (in press) analyzed faculty
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technology adoption level in general and described the factors that were significant predictors of the
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technology adoption level. Using Rogers’ (2003) Diffusion of Innovations theory as the theoretical
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framework, the current quantitative study aimed to assess the adoption level of computers for
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instructional purposes by faculty members in the COE at an Anatolian university in Turkey and determine
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the variables that were significantly correlated with faculty members’ use of computers for instructional
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purposes. Hence, the goal of the current study is to better understand specific instructional computer use
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by COE faculty in Turkey following up on the results from the study in the US.
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Theoretical Framework
Since this study was aimed at identifying and interpreting computer adoption and diffusion for
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instructional purposes by COE faculty members, Everett Rogers’ (2003) Diffusion of Innovations theory
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was used as the theoretical framework. Specifically, Rogers’ theory was used in the process of data
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collection and as a frame to interpret of the findings from this study. The research instrument included
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items that measured faculty level with respect to the specific elements of this theory. Also, the results of
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this study were discussed and summarized using Rogers’ theory.
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For Rogers (2003), the innovation-decision process involves five steps: (1) knowledge, (2)
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persuasion, (3) decision, (4) implementation, and (5) confirmation. Also, attributes of innovations
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includes five characteristics of innovations: (1) relative advantage, (2) compatibility, (3) complexity, (4)
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trialability, and (5) observability. Rogers defined the following five adopter categories on the basis of
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innovativeness: innovators, early adopters, early majority, late majority, and laggards.
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In this survey study, COE faculty members’ current computer use and expertise in instructional
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computer technologies were evaluated to find out where they were in the innovation-decision process.
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Specifically, Rogers’ (2003) attributes of innovations and adopter categories were used in the construction
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of the research instrument. While the relative advantage, compatibility, and complexity attributes
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measured faculty attitudes toward instructional computer technologies, the research instrument included
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the trialability, and observability attributes as the social support variables. Moreover, specific survey
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items were used to classify the faculty members according to Rogers’ adopter categories based on
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innovativeness. For instance, the innovators’ category was determined by the following statement: “I was
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using computer technology for instructional purposes before most faculty members in my college knew
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what it was or before the college purchased equipment.” Results from the survey were interpreted using
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Roger’s categories as the frame for both describing the current level of faculty adoption and suggesting
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interventions for moving the faculty to higher levels.
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Instructional Computer Use in Turkey
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Methodology
Research Site and Participants
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The participants of this study consisted of COE faculty members of the Anatolian university. This
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university has an enrollment of 60,000 students. The COE is one of the 16 colleges in the university, with
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8,533 students. It has eight main departments: computer and instructional technologies education, social
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sciences, art education, primary education, science and mathematics education, educational leadership
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and policy studies, Turkish education, and foreign languages education.
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The research instrument was distributed to 157 full-time COE faculty members of whom 19 were
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full professors, 9 associate professors, 68 assistant professors, and 61 instructors (see Appendix A for the
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frequencies of faculty demographics). To include all faculty members, whether or not they used
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computers for instructional purposes, the research instrument was distributed to the faculty in a paper
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format. Of those who were asked to participate, 117 faculty members responded to the study, for a 74.5%
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response rate.
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Research Instrument
The data collection instrument for this study was a questionnaire originally developed by Isleem
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(2003). For this research, the survey was modified partially to measure the level of COE faculty computer
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use for instructional purposes and to include the elements of Rogers’ theory. The survey included the
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following sections: levels of instructional computer use and expertise, access to computers, barriers to
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computer access, attitudes toward computer use, and computer support. As an additional section added to
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the questionnaire developed originally by Less (2003), the fifth section included 6 items to classify the
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participants according to Rogers’ (2003) adopter categories. This section also includes an open-ended
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question asking for a reason for the adopter category that the participants selected. Finally, the last section
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consisted of faculty characteristics.
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Data Analysis
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Since each section of the survey had a list of several items, the current study used the canonical
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correlation analysis method to determine relationships between the level of computer use for instructional
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purposes and the selected factors. Canonical correlation (Rc) is a statistical method to measure the
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relationship between two multidimensional variables (Ashley, 1996). Wilks’ lambda (Λ) was used to test
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the significance of the relationship between the sets of variables. Wilks’ lambda is a multivariate statistic
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ranging between 0 and 1 (Mertler & Vannatta, 2002). Also, the Cronbach alpha value of the reliability test
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was used to check the survey sections for internal consistency that compares responses to different sets of
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survey items. The results of the reliability analyses showed that the value of the Cronbach standardized
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item alpha for each section of the survey was either moderate or high, confirming the reliability of the
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survey (see Table 1 and Appendix B for the reliability test results).
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Findings and Discussion
The findings from this study are organized and reported around instructional computer use. After
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the results related to COE faculty members’ use of computers for instructional purposes are presented, the
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relationship between instructional computer use and the following variables is analyzed: computer
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expertise, computer access, barriers to computer access, attitude toward computers, support for computer
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use, and adopter categories. After the findings are reported, the meaning of these results is discussed.
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Instructional Computer Use
As seen in Table 1, the findings of this study showed that COE faculty members had high levels
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of use of only three mainstream and personal computer applications: Internet, word processing, and email.
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There is a gap between the mean scores of these mainstream computer use applications (M>4.0) and other
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more specific computer use applications (M<2.9). Literature confirmed these results that the use of more
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mainstream and personal computer applications was common among faculty and teachers (Carter, 1998;
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Martin, 2001). However, the level of instructional computer use in general by COE faculty members was
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very low. These results are consistent with those of Odabasi (2000), who found that while Turkish faculty
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members use the traditional technologies more often, they lacked experience in the use of more computer-
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related technologies. Odabasi found that the word processor was the most frequently used computer
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application among the faculty members.
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[Insert Table 1 here]
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The open-ended items in the survey provided specifics for improving faculty use of computers for
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instructional purposes. COE faculty members defined the following main themes: support, training,
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change in teaching methods and strategies, improvement of school and classroom infrastructure, teaching
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workload, and attitudes toward computer use including relative advantage of computers for instructional
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purposes. These themes showed that COE faculty members need to be well-supported and trained in
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instructional computer use (Casmar, 2001) and higher education should encourage the integration of
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computer technologies into the curriculum (Parisot, 1995). Then, they will more likely have a positive
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attitude toward computers and use them for instructional purposes (Dexter, Anderson, & Ronnkvist,
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2002).
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Computer Expertise and Instructional Computer Use
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Similar to the findings reported on the levels of instructional computer use, faculty members had
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high levels of computer expertise in the three mainstream and personal computer applications and lacked
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computer expertise in instructional computer applications and the rest of the computer applications that
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were more specialized (see Table 1). Overall, these results showed that the COE faculty members’
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expertise in the computer applications was very low. As seen in Table 2, computer expertise is
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significantly correlated with the level of computer use. Cavanaugh (2002) confirmed these findings that
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COE faculty members do not have enough knowledge and skills to integrate and model the adoption of
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technology into instruction.
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[Insert Table 2 here]
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Literature and the results of this study revealed that computer expertise was the most important
factor influencing educators’ instructional computer use (Asan, 2002; Braak, 2001; Jenson, Lewis, &
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Smith, 2002; Zhao & Cziko, 2001). Knowledge is the first stage of the successful adoption of
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instructional computer technologies (Rogers, 2003). Thus, the knowledge stage is essential for other steps
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in the innovation-decision process. If COE faculty members do not have enough expertise in computer
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use, they cannot be expected to adopt computer technologies into their instruction. Without the
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knowledge of computer technology, COE faculty members might have a high level of uncertainty that
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influences their opinions and beliefs about the innovation. In addition, Rogers defined three types of
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knowledge: awareness-knowledge, how-to-knowledge, and principles-knowledge and these knowledge
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types refer to “what the innovation is and how and why it works” (p. 21). To construct new knowledge,
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COE faculty should be provided with both a how-to experience and a know-why experience (Seemann,
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2003).
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Computer Access and Instructional Computer Use
The COE faculty members reported high levels of computer access in more personalized spaces
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such as in their offices and at their homes (see Appendix B for the mean values of the independent
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variables). However, they stated that there was lack of computer access in most classrooms where they
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taught (M=2.3). In the responses to the open-ended questions, the participants mentioned the barrier that
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the school and classroom infrastructure need to be improved. Specifically, computer access in classrooms
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is essential for the successful adoption of computers for instructional purposes. Computer access in
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general is significantly correlated with the level of computer use (see Table 2).
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Trialability and observability are the two attributes of an innovation that might increase the rate
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of adoption of innovations (Rogers, 2003). Thus, computer technologies should be available and
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accessible to COE faculty members. Then, they will have the opportunity to observe each other’s
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instructional computer uses and to try computers for instructional purposes as needed. In summary, the
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contextually related literature and the results of this study showed that the accessibility and availability of
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computers was an important factor affecting the use of computers for instructional purposes (Blankenship,
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1998; Medlin, 2001; Surendra, 2001).
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Barriers to Computer Access and Instructional Computer Use
The most frequent barriers reported by the survey participants were lack of support for
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instructional computer use, training on existing computers and software, appropriate instructional
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software, and technical support. These findings also were supported by the participants’ responses to the
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open-ended questions. They mentioned (teaching, research, or advising) workload and lack of time as
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important barriers that limited their learning and using computer technologies for instructional purposes.
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In Odabasi’s (2003) study, the most important barrier for Turkish faculty members was the lack of easily
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accessible resources.
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The barriers to computer access were significantly correlated with the level of computer use.
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Therefore, barriers such as lack of support for instructional computer use and lack of training on existing
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computers and software limiting COE faculty members’ integration of computers for instructional
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purposes should be minimized as these barriers might result in inadequate or lack of use of instructional
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technologies by faculty members (Anderson et al, 1998; Zakaria, 2001).
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Attitude toward Computers and Instructional Computer Use
The faculty members had positive attitudes toward computer use for instructional purposes in
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general. For instance, they reported that they expect all faculty members in the College of Education to
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use computers for instruction (M=4.3), using computers improved the quality of teaching they do
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(M=4.1), and learning to use computers was easy for them (M=4.1). Workload and time required for
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computer use were a concern among the participants. Reducing the current teaching and advising
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workload of COE faculty members might positively change their attitudes toward workload increase with
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computer use. In the responses to the open-ended questions, disciplines not suitable for instructional
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computer use and unwillingness, especially by older faculty members, were among the negative attitudes
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toward computer use for instructional purposes.
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Rogers’ (2003) relative advantage, compatibility, and complexity attributes are related to attitudes
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of individuals. In this study, the participants reported positive attitudes toward the three attributes of
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innovations. Faculty members’ positive attitudes toward these attributes are very important because these
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attributes are significant predictors of the diffusion of instructional innovations (Parisot, 1997; Surendra,
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2001). It is crucial that faculty should perceive computer technologies as useful instructional tools and as
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being consistent with their beliefs (Jacobsen, 1998), and that they should not see computers as complex
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tools for instructional use.
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The results of this study showed that attitude was significantly correlated with the adoption of
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instructional computer applications (see Table 2). The literature confirmed this finding that attitude is an
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important factor for using or avoiding computer-based technology (Fisher, 2002; Yaghi & Ghaith, 2002;
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Yildirim, 2000). Moreover, these findings suggest that since faculty members have positive attitudes
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toward computer technologies at the persuasion stage, the second stage of the innovation-decision
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process, they will more likely end up adopting these technologies for instructional purposes.
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Support for Computer Use and Instructional Computer Use
Faculty members reported a great deal of collegial support in instructional computer use (see
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Appendix B). In fact, collegial interaction and support were a motivating factor for faculty to use
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technology (Casmar, 2001; Surendra, 2001). According to Rogers (2003), “diffusion is a very social
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process that involves interpersonal communication relationships” (p. 19). In fact, interpersonal channels
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are very influential in changing strong attitudes held by an individual, so they are effective through the
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persuasion, decision, and confirmation stages of the innovation-decision process. In particular, if
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interpersonal channels are localized, that is between individuals of the social system, they become more
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important at the persuasion stage of the innovation-decision process because close peers’ subjective
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evaluations of the innovation are more powerful in reducing uncertainty about the innovation outcomes.
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In the present study, Rogers’ (2003) trialability and observability attributes of innovations were
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included as part of the social support. Trialability and observability are the key motivational factors in the
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adoption and diffusion of technology (Parisot, 1997; Surendra, 2001). The participants reported that they
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had enough opportunity to try various computers for instructional purposes although they mentioned lack
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of observability in instructional computer use in the COE. It is the responsibility of administration to
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provide faculty with a social environment that includes these attributes of innovations. However, in this
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study, the participants stated lack of administration support in instructional computer use.
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The findings revealed the need for training in the integration of technology in curriculum. As
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mentioned by the participants in their responses to the open-ended questions, administration could play a
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significant role in the organization of training programs for COE faculty in instructional computer
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technologies. In the US, one of the most popular faculty technology training programs is the one-on-one
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mentoring program. Although the one-on-one faculty mentoring program is a successful approach and
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well-supported in the literature (Smith & O’Bannon, 1999; Beisser, 2000; Chaung, Thompson, &
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Schmidt, 2002), the majority of faculty members in the present study were not in favor of one-on-one
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mentoring with undergraduate students (M=2.5). This result shows that the hierarchical relationship
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between faculty and students is still an issue among the Turkish faculty members and needs to be
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considered in faculty development programs. Thus, one-on-one mentoring programs need to be modified
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to meet this particular culture and COE faculty needs in Turkey. Since the existence of collegial support is
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a crucial finding in this study, one-on-one one mentoring programs and administration might use collegial
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interaction and communication for faculty professional development in these technologies. Faculty
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development efforts should emphasize collegial support and slowly move toward one-on-one mentoring
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with undergraduate students.
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The results of this study showed that support was significantly correlated with the level of
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computer use by the faculty members in the COE (see Table 2). The findings of other research studies
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were consistent with these results that instructional technology support including collegial support,
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administrative support, and training is vital for the successful integration of technology (Gardner &
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Clarke, 2001; Quick & Davies, 1999; Rogers, Geoghehan, Marcus, & Johnson, 1996).
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Adopter Categories and Instructional Computer Use
In this study, the participants were asked about Rogers’ (2003) adopter categories based on
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innovativeness (see Appendix A for the frequencies of adopter categories). According to Rogers, the
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percentages of innovators, early adopters, early majority, late majority and laggards were 2.5%, 13.5%,
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34%, 34%, and 16%, respectively. In the present study, the percentages of innovators (19.7%) and
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laggards (23.1%) were higher and the percentages of early adopters (6.8%) and late majority (14.5%)
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were lower than those described by Rogers. In fact, only adopters of successful innovations generate the
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distribution defined by Rogers. However, the level of instructional computer use was very low in this
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study. When the level of successful instructional computer adoption by COE faculty members increases,
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the distribution of adopter categories might become closer to those described by Rogers.
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Of the participants, 44 faculty members responded to the open-ended question regarding reasons
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for the adopter category that they selected (see Appendix C for the themes and their frequencies for each
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category). The participants in the innovators category reported that they owned their personal computers
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without any support and funding from the administration or other sources before many faculty members
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in the COE had computers. Rogers (2003) confirmed this finding that innovators are the gatekeepers,
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introducing the innovation into the members of the social system, and they have to deal with difficulties
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such as unprofitable innovations and a certain level of uncertainty about the innovation. The participants
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in this category also described their self-motivation and willingness to try new things, which was a typical
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characteristic of innovators for Rogers. Finally, the participants in the innovators category stated that they
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had strong experience and background in instructional computer use. This finding was consistent Rogers’
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explanation that adventuresomeness of innovators requires them to have complex technical knowledge.
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Although the number of early adopters who participated in this study and their responses to the
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open ended question were low, one participant mentioned his initiative role in establishing computer labs.
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This finding was consistent with Rogers’ (2003) statement that early adopters are more likely to hold
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leadership roles in the social system. Thus, their attitudes toward and evaluations of an innovation are
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very critical. Compared to early adopters, early majority do not have a leadership role but they have good
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interactions with other members of the social system. In the responses to the open-ended questions, the
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participants in the early majority category reported positive attitudes toward instructional computer use,
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so they might eventually reach other faculty members through their interpersonal networks and encourage
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them to adopt instructional computer technologies. The participants in the late majority category reported
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that they used computer technologies for instructional purposes later than most of their colleagues. For
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Rogers, late majority individuals are skeptical about the innovation and its outcomes. Collegial interaction
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and support mentioned by one participant in this category might be used to persuade the late majority
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individual to adopt instructional computer technologies. Moreover, the faculty members in the laggards
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category had concerns similar to those of the late majority category. Laggards are very skeptical about
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innovations and tend to wait until an innovation works and is successfully adopted by other members of
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the social system. With the availability of Rogers’ five attributes of innovations (relative advantage,
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compatibility, simplicity, trialability, and observability), COE faculty members’ uncertainties about
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instructional computer technologies might be reduced.
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In summary, Rogers’ (2003) adopter categories based on innovativeness were significantly
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correlated with the level of computer use in this study (see Table 2). In general, the findings of this study
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were consistent with Rogers’ explanations regarding the adopter categories. This study and literature
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verified that innovativeness is a crucial factor in categorizing adopters of innovations (Braak, 2001;
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Hoerup, 2001; Less, 2003).
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Summary and Conclusions
In this study, instructional computer use by the faculty members in the COE at an Anatolian
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university in Turkey and the variables affecting their uses of computers for instructional purposes were
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analyzed. In the data analysis, the following variables were significantly correlated with the level of
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computer use by the faculty members in the COE: computer expertise, computer access, barriers to
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computer access, attitude toward computer use, support for computer use, and adopter categories based on
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innovativeness. The faculty members reported high levels of computer use and expertise in only three
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mainstream and personal applications (Internet, word processing, and email) and high levels of computer
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access in only personal spaces such as their offices and at their homes. However, the findings showed that
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COE faculty members had low levels of computer use and expertise in instructional computer
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applications in general. These results along with low level of computer access in public places indicate
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the need of instructional computer support for COE faculty members. In fact, lack of support and training
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also were mentioned as important barriers by the participants. Specifically, COE faculty members
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stressed two types of support: administrative and collegial. Although faculty members in the COE stated a
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great deal of collegial support in instructional computer use, they reported lack of administrative support
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in the use of computers for instructional purposes.
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In this study, Rogers’ theory was helpful in categorizing and understanding where faculty
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members were in terms of instructional computer technologies and in suggesting directions for faculty
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change in these technologies. Faculty members’ low levels of instructional computer use and expertise,
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the majority of the faculty members’ self-placement in the last three adopter categories, and their
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responses to the open-ended question regarding reasons for the adopter category that COE faculty
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members selected showed that they were in the first stage of the innovation-adoption process, the
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knowledge stage. To increase their instructional computer knowledge and use, administration should
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organize faculty training programs and minimize barriers to computer access, especially in public spaces
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such as classrooms that will also lead to the higher level of observability in the technology. Specifically,
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an action plan should take advantage of faculty members’ positive computer attitudes (including the
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relative advantage, compatibility, and simplicity attributes) and interpersonal communication channels
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(collegial communication). To diffuse instructional technology in the COE, faculty development efforts
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should involve early adopters who are more likely to hold leadership roles in the social system. Since the
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hierarchical relationship between faculty and students was still an issue among the Turkish faculty
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members, this needs to be considered in faculty development efforts.
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This study contributes to the sparse body of literature in the area of COE faculty development in
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the adoption of computer technologies for instructional purposes. Although this research study was not a
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comparative study, the findings from this study and related literature suggest the similarity of COE
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faculty members’ issues, concerns, and problems with instructional computer technology use in Turkey
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and the United States and the need to share knowledge in this area across cultures.
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431
Appendix A: Frequencies of Demographics and Adopter Categories
Figure 1: Frequency of Gender
Figure 2: Frequency of Academic Rank
Figure 3: Frequency of Department Affiliation
Figure 4: Frequency of Home Computer Ownership
Figure 5: Frequency of Office Computer Ownership
Figure 6: Frequency of Age Groups
Instructional Computer Use in Turkey 20
Figure 7: Frequency of Teaching Experience
Figure 8: Frequency of Computer Experience
Figure 9: Frequency of Average Number of
Students per Semester
Figure 10: Frequency of Number of Graduate
Students Supervised
Figure 11: Frequency of Adopter Categories
432
433
434
435
Instructional Computer Use in Turkey 21
436
437
Appendix B: Results for Descriptive Analysis and Reliability Test
Table 1: Means for Items of Computer Access
Item
Office
Home
Library/media Center
Most classrooms where they teach
Computer Lab
438
439
Mean
Std. Item Alpha
4.3
3.5
2.4
2.3
2
0.69
Table 2: Means for Items of Barriers to Computer Access
Item
Lack of Support for Computer Integration into Curriculum
Lack of Training on Existing Computers and Software
Lack of Appropriate Instructional Software
Lack of Technical Support
Lack of Time for Instructional Computer Use
Not enough computers
Outdated/incompatible Computers
Outdated/incompatible Software
Unreliable Computers/Software
Internet is not Easily Accessible
Not enough software licenses
440
441
Std. Item Alpha
3.1
3
2.9
2.9
2.8
2.7
2.6
2.6
2.5
2.5
2.4
0.92
Table 3: Means for Items of Attitudes toward Computer Use
Item
442
443
444
Mean
Email Usefulness
Attitude towards Colleagues’ Instructional Computer Use
Computer Anxietya
Relative Advantage of Instructional Computer Use
Simplicity of Computer Use
Computer Usefulness
Computer Use in Class
Compatibility of Instructional Computer Use
Confidence in Computer Use
Workload Increase with Computer Usea
a
Items were reverse-coded.
Mean
Std. Item Alpha
4.4
4.3
4.2
4.1
4.1
4
3.8
3.7
3.7
3.4
0.83
Table 4: Means for Items of Support for Computer Use
Item
445
Sharing Information and Ideas about Computer Use among Colleagues
Computers as Important Tools for Administration
Hardware and Software Updates, and Technical Support from Colleagues
Colleagues' Discouragement of Computer Usea
Trialability of Computers
Colleagues' Good Modeling of Computer Use
Support for Consistent Hardware and Software, and Updates from Administration a
Timely Technical Support and Maintenance of Computers from Administration
Observability of Computer Use
Workshops and Training on Computer Use from Administration
One-on-one Assistance from Undergraduate Students in Computer Use
a
Items were reverse-coded.
Mean
Std. Item Alpha
3.6
3.5
3.4
3.4
3.3
3.2
3.1
3.1
2.8
2.6
2.5
0.70
Instructional Computer Use in Turkey 22
Appendix C: Responses to Open-ended Question for Adopter Categories
Innovators
Themes
Personal effort and
interest
Computer experience
and background
Important role of
computers in
education
Using computers
early without support
Open to new ideas
and technologies
Self-motivation to
discover new things
(a)
Frequency (f).
f
(a)
Early Adopters
Themes
f
Early Majority
Themes
Research or
discipline-related
use
Owing personal
computer late
f
Late Majority
Themes
Laggards
f
Themes
f
4
Being involved late in
academic position
2
Lack of physical and
technological resources
4
2
Lack of computers
1
Discipline not suitable for
instructional computer use
3
Positive attitude
2
Poor physical
conditions for
computer use
1
Teaching and academic
workload
3
3
Faculty computer
lab founded late
1
Lack of knowledge
1
Personal use (not
instructional)
2
2
Workload
1
Lack of confidence
1
Lack of time
1
1
Involved late in
academic position
1
Lack of training
1
Lack of training
1
Foreign language
barrier
1
6
5
4
Leadership
Personal
interest
Computer
experience and
background
1
1
1
Using computers late
for instruction
Importance of
colleague support
Age
1
1
1
Lack of computer
knowledge
Lack of confidence in
computer use
Lack of computers and
software
Lack of support
Involved late in academic
position
1
1
1
1
1
Instructional Computer Use in Turkey 23
Table 1: Means for Items of Instructional Computer Use and Expertise
Instructional Computer Use in Turkey 24
Table 2: Canonical Correlation between Instructional Computer Use and Independent Variables