Instructional Technology. Investments in Higher Education: Are Faculty Using the Technology? Abstract. In times of budget constraints, colleges and universities ...
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Instructional Technology Investments in Higher Education: Are Faculty Using the Technology? Abstract In times of budget constraints, colleges and universities strive to make strategic investments in instructional technology and determine if those investments are being adopted and utilized by the faculty. The Information Technology Services (ITS) at a major southeastern university had invested in 49 technology classrooms and wanted to determine if the technology in these classrooms was being adopted and utilized by those faculty teaching in them and, if so, what hardware were they using and what prompted their adoption. This article describes the steps ITS took to determine this information, what they found, and future directions they plan to pursue after reflecting on what they learned from the process and the information gathered.
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he integration of technology into teaching provides faculty pedagogical opportunities to renovate the classroom learning environment (Jonassen, 1996; Resta & Laferriere, 2007). Colleges and universities have geared up to meet the learning needs of students by infusing technology into classrooms and purchasing enterprise level applications to accommodate online and hybrid courses. As huge investments are made to equip classrooms with hardware, software, and specialized equipment, the assumption is that the faculty assigned to teach in these electronic classrooms are, to some degree, utilizing the technology in their instruction. Recently there has been an increased focus on faculty use of technology (Keengwe & Anyanwu, 2007). While the implementation of technology into administrative tasks and research has been widely adopted, it is used less frequently for instructional purposes (Cuban, 2001; Spotts, 1999;
Amy Berryhill Mississippi State University Vance A. Durrington, University of North Carolina Wilmington
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Zhao & Cziko, 2001). Others would go as far as stating that there is resistance among faculty to the integration of technological tools into their teaching (Keengwe, Kidd, & Kyei-Blankson, 2009). As more technology is made available in the form of wireless networks, portals, and more technology-driven courses (Oblinger & Oblinger, 2005), faculty are expected to keep pace with the technology placed in the classrooms. In these economic times, it is necessary to determine how faculty are using these technology classrooms. Many institutions have invested in and installed technology classrooms, which are sometimes referred to as technology enhanced traditional classrooms. The movement toward installation of these classrooms has been slower than the implementation of online distance education courses and programs. The slow implementation pace appears to have resulted in a wide-spread low level use of these classrooms and an unpredictable high-level use (Ertmer, 2005). Many institutions do not have a process in place to monitor or track the extent of instructional technology use by the faculty who teach in the electronic classrooms. In this article we describe the process an Information Technology Services (ITS) division of a southeastern university went through to determine if their faculty were using the provided instructional technology, how they were using it, to what extent they were using it, and how the knowledge/training for using it was obtained.
Background Large sums of money have been invested into higher education technology infrastructures. These funds have predominantly been invested in administrative hardware systems, which many institutions are now trying to use to connect classrooms. The drive to invest and build information technology infrastructures overshadowed the usability of this technology by faculty for instructional purposes. While the task of these technology infrastructures is to support teaching and learning, the technology alone is not enough to enable pedagogy that integrates technology (Georgina & Hosford, 2009).
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In 2002, a southeastern university formed an ad hoc committee on classroom technology to determine what type of hardware would be needed to retrofit existing classrooms to create a Technology Classroom (Pearson & Brook, 2002). Recommendations were presented and two Technology Classrooms were built on campus by ITS and used as a pilot for the Fall 2003 semester. Every semester more classrooms were added and assigned to faculty. When the number of classrooms reached 49, the ITS group decided that they needed to step back from the implementation of these rooms and determine the purpose for these rooms and the extent that they were being utilized.
Student Expectations Students have been a contributing factor to the emphasis colleges and universities have placed on faculty to integrate technology into their instruction. As members of the Net Generation (Oblinger & Oblinger, 2005), college and university students expect technology to be used in the classroom and they expect faculty to be proficient in using the technology. Over 10 years ago, The Campus Computing Report (Green, 1996) stated that “Growing numbers of college students expect a technology component in their courses; across all disciplines, growing numbers of faculty are utilizing technology resources to enhance the curriculum” (p. 2). Having some “digital curriculum” in the classroom enhances student learning (Green, 1996). Green stated that “colleges confront growing expectations from students across all disciplines that technology will be part of the learning and instructional experience” (p. 3). McNeely (2005) further suggested that “traditional lectures are not fulfilling the learning potential of typical students today. “As technology in the classroom progresses, more and more students are going to demand it be included” (p. 4.7). Students have indicated that their learning was significantly enhanced when faculty demonstrated acceptance and adoption of instructional technology (Draude & Brace, 1999). Net Generation college students have grown up with technology (Oblinger & Oblinger, 2005). They were born around
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the time computers began entering homes and schools, and an estimated 20 percent were using computers between the ages of 5 and 8. In addition, by the age of 16 to 18 years old, virtually all of the Net Generation were using computers (Oblinger & Oblinger, 2005). Reports indicate (Kaiser Family Foundation, 2003; Grunwald, 2004; Grunwald, 2003) that through age groups beginning at 4 and going up to 17 years old, home digital media use has approached the amount of time spent watching television. Expectations and demand are the driving forces for higher education’s investment in Technology Classrooms. Access to the latest technology is important to the Net Generation (McNeely, 2005; Oblinger & Oblinger, 2005). Home computers and the Internet have become almost as prevalent as the telephone (Oblinger & Oblinger, 2005). With this prevalence, the use of instant messaging has emerged as a common form of communication as well as a social mechanism (Oblinger & Oblinger, 2005). According to the research by the Pew Internet and American Life Project (Lenhart, Simon, & Graziano, 2001), 70 percent of teenagers use instant messaging to keep in contact with friends and family. This is slightly less than the 81 percent who use e-mail for the same purpose. In a separate study conducted by NetDay (2004), 74 percent of the teenagers surveyed indicated that they used instant messaging as a major communication tool. Once in college, many students use instant messaging to stay in touch with people back home, often on a daily basis. Of these students, 41 percent indicated they planned to use e-mail and instant messaging to contact professors and classmates regarding assignments (Lenhart, Simon, & Graziano, 2001). The NetDay (2004) study found that students knew more screen names than home phone numbers, indicating the importance of instant access to this generation. Howe and Strauss (2000) characterized traditional college students as individuals who gravitate toward group activity, identify with parents’ values and feel close to their parents believe it’s cool to be smart, like new technologies, focus their attention on grades while participating in extracurricular activities, and are racially and ethnically diverse.
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Prensky (2001) believes, “Our students have changed radically. Today’s students are no longer the people our educational system was designed to teach” (p. 1). The students of today, kindergarten through college, are the first generation to be born into and grow up completely surrounded by technology. Prensky (2001) wrote that this group has spent their lives surrounded by computers, video games, digital music, video cameras and cell phones, along with whatever is the latest toy of the digital age. The average college graduate has spent less than 5,000 hours of their lives reading, but over 10,000 hours playing video games with the computer, using e-mail, the Internet, cell phones, and instant messaging. All of this has been interwoven into their everyday lives (Prensky, 2001). Because of the constant interaction, Prensky (2001) indicated that the students of today think and process information fundamentally different than the previous generation. Prensky (2001) identifies these students as Digital Natives because they are native speakers of the digital language, which includes computers, video games, and the Internet. In contrast to digital natives are the Digital Immigrants. Digital immigrants are those not born into the digital world but have, at some point in their lives, become interested in and adopted new technologies. The distinction between digital immigrants and digital natives is compared to immigrants adapting to a new country. Digital immigrants adapt to the new technologies, however, their “accent” is their foot in the past. Prensky (2001) illustrated how the accent of the digital immigrants could be seen in such ways as printing out e-mails (or having the secretary do it), bringing people physically into the office to see a Web site rather than sending them the URL, and making a phone call to ask someone if they received an e-mail. This accent of digital immigrant faculty is obvious to the digital natives in the educational setting because digital natives view current faculty as heavily accented, unintelligible foreigners lecturing to them. Often, the digital natives cannot understand what the digital immigrants are saying and ask questions
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such as “What does ‘dial’ a number mean?” (Prensky, 2001, p. 2). The characteristics of digital natives offered by Prensky (2001) are similar to the description offered by Howe and Strauss (2000) pertaining to the current traditional college student. In his description, Prensky (2001) described digital natives as being accustomed to obtaining information extremely fast, preferring to parallel process and multi-task, and preferring to see graphics than read the text. In addition, digital natives function better when networked, thrive on instant gratification/rewards, and prefer games to any type of serious work. Oblinger and Oblinger (2005) and Prensky (2001) both contend that students of today are different types of learners than in the past. Teaching this type of learner is challenging, but not impossible when one considers that “there is no reason that a generation that can memorize over 100 Pokemon characters with all their characteristics, history, and evolution can’t learn the names, populations, capitals and relationships of all 101 nations in the world. It just depends on how it is presented” (Prensky, 2001, p. 5). It has been established that students currently enrolled in colleges and universities like gadgets, and the newest, fastest, and most interesting technology devices are popular. This type of instant connectivity and communication translates into classroom learning. The Project Tomorrow (2009) report, indicated that the students of today are early adopters and adapters of new technologies and are creating new uses for a multitude of technology products to meet their complicated needs. These students serve as technology trendsetters for not only their peers, but also for their parents and educators. The technologies they use in their personal lives penetrate their schoolwork and have found a place in their school day.
Faculty Use of Instructional Technology Many educators understand that the integration of technology into teaching has the ability to enhance students’ education. As long as formal education has existed in the United
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States, there has been some controversy regarding the use of technology in the classroom (Baker & Baker, 2005). Classrooms in colleges and universities today contain sophisticated technology that is innately different from what was available in the past. The difference in the classroom technology of today is that it challenges the role of teachers and enhances student learning simultaneously (Baker & Baker, 2005). In recent years there has been additional focus on faculty use of technology and its impact on the learning of students in higher education (Keengwe & Anyanwu, 2007; Waxman, Lin, & Michko, 2003). Spotts (1999) interviewed faculty members at a U.S. Midwestern university about their use of instructional technology in their teaching. Fewer than 40% of the faculty population self reported that they had good to expert knowledge of or experiences with instructional technologies. While faculty members had become more comfortable with using computers, the instructional use of computers remained minimal. Even with attempts to introduce instructional technology into the higher education infrastructure, little change in the basic acts of classroom teaching had occurred. With technology and computers an integral part of everyday life, higher education classrooms do not appear to reflect this occurrence (Spotts, 1999). Wentworth, Earl, and Connell (2004) identified two elements that they believe stand out as major challenges to increasing the rate at which technology is applied towards the improvement of teaching and learning: (a) finding the time necessary to take full advantage of the opportunities that are presented; and (b) working with brains that came of age with typewriters and ditto machines rather than PowerPoint and Photoshop. Although there have been occasional glimpses of the transforming power of technology, today’s faculty find that they must repeatedly orient—and reorient—their thinking to focus on the potential that the technology has in helping accomplish their teaching goals. Wentworth, Earl, and Connell (2004) believe that this time in a faculty member’s career could be truly exciting, one in which continuing to negotiate the steep learning curve
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offers the promise of enabling faculty to become more effective teachers and learners through the integration of technology. Reinhardt (1999) reported that faculty willing to experiment with technology in the classroom determined that using the instructional technology alone was not enough. The importance in using instructional technology as a tool for delivering instruction was to add value to the teaching and learning process. Emphasis should be placed on understanding how using instructional technology results in improved learning (Baker & Baker, 2004). A study by Draude and Brace (1999) of college faculty at a middle southern university assessed the impact of instructional technology on teaching and learning. At the same university the following year, students were assessed to measure perceptions about instructional technology and its impact on learning (Draude & Brace, 1999). The results indicated that the use of instructional technology positively affected student learning as well as increased student interest and satisfaction. Further results indicated that the role of faculty and their ability to use instructional technology were major factors in student learning. The ability of faculty to use more advanced instructional technology techniques better facilitated learning activities. Students agreed that instructional technology was an integral part of the learning environment (Draude & Brace, 1999). Use of what may be considered “basic” for this day and age, technology is e-mail. This type of technology is also beneficial with teaching and learning. According to Project Tomorrow (2009), in 2006, 64% of teachers reported using e-mail on a regular basis for communications. Many did not see the educational benefit of using e-mail. Two years later, more than 94% of teachers reported using e-mail communications regularly and had embraced e-mail as a tool to improve student learning. It is important to find out what the students are using and leverage it in a way that promotes meaningful learning. Providing technology for faculty that can be used for instructional purposes has become a priority in higher education. Every year since 1996, The Campus Computing Report (Green,
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2005) has shown that the single most important technology issue of all institutions (public and private universities, public and private 4–year colleges, and community colleges) has been integrating technology into instruction. Having the facilities and resources available for use was reported as an important issue, as well. Eighty-five percent of the respondents at 600 colleges and universities believed technology had improved instruction on their campus (Green, 2005). Even though the use of instructional technology has been reported as important and improving (Green, 2005), a shortage of equipment, facilities, and institutional support has had a role in hindering the use of instructional technology; Geoghegan (1994) argued that the most important reason for limited use was in the human realm. “Objectively, it is not the effectiveness of technology, but the teacher’s perception of the effectiveness of technology that determines whether technology will be used” (Zhoa & Cziko, 2001, p. 21).
Diffusion of Innovations: Instructional Technology Use by Faculty Brace and Roberts (1996) wrote that a campus-wide approach to instructional technology integration based on Rogers’ (1995) stages of adoption targeted mainstream faculty’s perceived needs. Innovations were more likely to gain acceptance if users believed it had a somewhat high relative advantage or that it was better than the idea that came before (Rogers, 1995). Innovations that had a higher compatibility with existing values, past experiences, and the needs of the adopters also had a higher likelihood of being adopted. Individuals proceed from (1) knowledge of an innovation, (2) to persuasion, (3) to a decision to adopt or reject, (4) to implementation, and finally (5) to confirmation of the decision (Rogers 1995). Jacobsen (1997) examined the characteristics of early adopters and faculty use of instructional technology using Rogers’ (1995) diffusion of innovations theory. He focused on what differentiated early adopters of instructional technology from mainstream faculty. The results indicated that early adopt-
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ers self-reported good to excellent computer skills while the later adopting mainstream faculty self-reported poor to fair computer skills. Jacobsen’s research pointed to early adopters being more self-sufficient and more willing to experiment with technology than mainstream faculty. In addition, it was speculated that early adopters would continue to flourish in a status quo model because of their interpersonal networks. The field is constantly evolving because of technological advancements and developments that present challenges. Studies focusing on early adopters would assist institutions in moving forward in supporting classroom technology (Jacobsen, 1997). When approaching the integration of technology into instruction, Kearsley (1996) proposed that excellent teaching should be the first priority, citing that the adoption of technology would not improve poor teaching skills. He further stated that if cases were found where faculty were documented as both early adopters of instructional technology and demonstrated excellent teaching skills, profiling this expertise would prove beneficial to other higher education faculty who aspire to develop both their instructional technology and teaching skills (Kearsley, 1996). Surry and Farquhar (1997) explained that disciplines ranging from agriculture to marketing to medicine have used the diffusion of innovations theory to aid in the increase of adoption of innovative products and ideas. The research focused on how instructional technologists were using diffusion of innovations theory to increase implementation and utilization of innovative instructional practices and products. Diffusion of innovations theory was also useful for examining how media literacy proponents could apply the theory to determine if there was an increase in adoption (Surry & Farquhar, 1997). Jacobsen’s (1998) survey of faculty found that adoption patterns varied across disciplines. Despite findings that technology was being used by more faculty, the diffusion of technological innovations for teaching and learning was not widespread, and instructional technology had not become integrated into the curriculum. Faseyitan and Hirshbuhl (1992) described how the effects of
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personal attributes, organizational factors, and attitudinal factors were examined in regard to the adoption of computers for instruction by university faculty. The results indicated that the technological orientation of the faculty’s discipline, computer self-efficacy, computer utility beliefs, and attitudes toward computer were predictors of adoption. Geoghegan (1994) wrote about the technology adoption life cycle in relationship with Everett Rogers Diffusion of Innovations Theory (1995). Geoghegan (1994) focused on the innovation of incorporating informational technology into the instructional process. The diffusion process took place in a social context with variables being the knowledge and beliefs of the academic culture, the structure of the social networks, and communication patterns. The diffusion took place over a period of time, following the same distribution of adopters as the normal adopters distribution (Rogers, 1995). In the adoption process, individuals who adopt an innovation at different points in the diffusion process differ in terms of social and psychological characteristics. These characteristics brought about their willingness to accept and adapt to changes influenced by the innovation. Such characteristics also determined attitudes towards earlier adopters and factored into their ability to influence any followers (Geoghegan, 1994). Geoghegan (1994) illustrated how the Diffusion of Innovations theory may apply to faculty use of instructional technology. In his illustration, one or more faculty in the department were innovators. They became aware of new technology, such as multimedia, and experimented with it and perhaps used it in the classroom or in a lab setting. These trials may or may not have been considered successful, but by trying something new, it might have caught the attention of the early adopters. If the early adopters viewed this new technology as having the potential to make improvements in their instruction, they might have experimented with the technology as well. If these early adopters deemed the application successful and displayed a noticeable improvement in an important area of teaching or student
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learning, and if the improvement was highly visible and seemed attractive to the early adopter’s mainstream peers, then the instructional technology innovation would have a chance of being adopted into the mainstream population. This, according to Geoghegan (1994), would occur within the mainstream when the costs of adoption, such as time, money, and routine disruption were deemed less significant than the potential positive benefits of adoption. Geoghegan pointed out that as instructional technology use continued, it matured, became simpler, and was worked into the teaching routine. This use by the early majority would influence adoption by the late majority to possibly adopt its use (Geoghegan, 1994). The differences between the two groups (early adopters versus early majority) are key to the diffusion process and the potential changes that could alter the teaching and learning process. Geoghegan (1994) characterizes early adopters as favoring revolutionary change, are visionaries, project oriented, risk takers, are willing to experiment, generally self sufficient and horizontally connected. He characterized the early majority as favoring evolutionary change, pragmatic, process oriented, averse to risk, wanting proven applications, needing significant support, and vertically connected. The appeal of instructional technology to the early adopter will be very different from its appeal to a member of the early majority, despite the fact that both may recognize its potential benefits to teaching and learning; and the two are likely to have very different criteria for deciding whether or not to adopt a technology based innovation when it becomes feasible to do so. (p. 6) From a marketing standpoint, the two groups require completely different approaches in order to transition through the Chasm. According to Geoghegan (1994), the Chasm is so significant in regards to instructional technology that it has hindered practically all efforts to bridge it. This situation, in which early
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adopters have approached saturation in relationship to instructional technology as an innovation and that early majority adopters have not fully embraced it, has dramatically affected the perpetuation of the Chasm. Geoghegan (1994) identified four reasons behind the adoption process stalling and consequently preventing diffusion beyond the Chasm and into the early majority: (a) ignorance of the existence of the Chasm, (b) too hard of a push to induce change, (c) alienation of the mainstream, and (d) lack of compelling reasoning for the mainstream to adopt instructional technology. The recognition of these reasons and making efforts to correct the situation can get the adoption process moving forward again (Geoghegan 1994). In research by Moser (2007), the Faculty Educational Technology Adoption Cycle indicates faculty support as the critical factor in the success of instructional technology integration because the complexities are deemed too complex for faculty without adequate training and support. Georgina and Olson (2008) found that asking colleagues was second only to small group faculty forums as the most effective manner to learn new computer-based technologies. This would support a number of research studies that found that the most effective training utilizes peer-to-peer training providing opportunities for the sharing of ideas and practice. (Ertmer, 2005; Mayo, Kajs, & Tanguma, 2005).
Instructional Technology: Faculty Training and Use Both mainstream and early adopters believed that a lack of training was an obstacle to widespread computer use, thus limiting its adoption by mainstream faculty. With training and support being the most critical factors in faculty adoption of instructional technology, it would seem logical that these would go hand in hand with Technology Classroom investments. Many colleges and universities do provide a wide range of instructional technology training to faculty. In addition, the Internet provides opportunities for training as well as self-guided tutorials provided by software companies. Wilson (2003) reported that faculty learn about use of instructional technology primarily through self-help,
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rather than university-provided sources. Some campus resources are more useful than others. Professional development and training are essential to the adoption process and the absence of these opportunities have been identified as barriers that deter higher education faculty adoption of technology.
Determining faculty utilization The Information Technology Services (ITS) department at a southeastern university installed their first two Technology Classrooms in Fall 2003. The Technology classrooms were equipped with identical instructional technologies (Pearson & Brook, 2002). As new classrooms were added each semester, all existing classrooms were upgraded in order to maintain continuity throughout. Each semester, more identical classrooms were added. The requests for new classrooms are generated by various departments across campus. These departments produce funding for the Technology Classroom and ITS supports the maintenance of these classrooms. With such a major commitment of resources, ITS began to investigate a method to determine the utilization and adoption of these technology classrooms. The key components that drove the ITS investigation were the economic outlook and budget cuts that are abounding in both the private and public sectors. Despite these budget cuts, higher education administration desires to continue to make substantial investments to provide instructional technology resources for faculty. In addition, a new type of student is populating university campuses. These students have entertainment at their fingertips and they want and expect information instantaneously. These students enter the classroom expecting faculty to integrate technology into their teaching and learning (Oblinger & Oblinger, 2005). In turn, faculty are expected to use the available technology in their instruction, but in many cases, the extent of use is not known or measured. Using Rogers’ (1995) diffusion of innovations theory in conjunction with social network analysis, the ITS staff leading the investigation hoped to gain an understanding of the applications and use of instructional technology by faculty
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teaching in the electronic classrooms. Based on their review of the literature they decided to study the pattern of who-talks-to-whom relationships and personal characteristics of adopters and nonadopters. In addition, data regarding training in the use of instructional technology was compiled and analyzed. In order to understand faculty’s use and integration of instructional technology in the Technology Classrooms, a threepart survey was designed. The first section was designed to measure knowledge and levels of use of the hardware available in the technology classrooms. The second section asked faculty whether they considered themselves adopters or non-adopters of the instructional technology, the names and rank/title of those the respondents communicated with about instructional technology, what training they had received and the source of that training. This information was used as the basis of the social communication network analysis determining who talks to whom about instructional technology. The third section collected demographic information. The target population of the survey would be those faculty who had either requested or been assigned to teach in one of the technology classrooms. At the time of the study, the university had 49 Technology Classrooms. Each classroom contained the exact same hardware and software. Initially, a pilot survey was administered to 22 faculty who had taught in the Technology Classrooms at the university, but were no longer affiliated with the institution. The results of the pilot survey were analyzed for validity by experts with graduate degrees in Communications, Educational Psychology, and Instructional Technology. Reliability was determined with a Conbach’s Alpha of .94. The link to the survey was then e-mailed to the 513 faculty who had taught in one of the 49 technology classrooms. There were 188 responses, which yielded a 37% return rate.
Survey findings The average age of the respondents was 46, with 14 years of experience teaching in higher education and 11 years of teaching experience at the current university. Seventeen percent
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of the respondents were assistant professors, 22% were associate professors, and 24 % were professors. The remaining 37% were non-tenure track faculty positions (e.g., instructor, lecturer, etc.). The majority of the respondents were in the College of Arts & Sciences (26%) followed by the College of Business and Industry (20%), the College of Agricultural and Life Sciences (17%), and the College of Education (17%). In terms of gender, 62% of the respondents were male and 38% were female. The majority of the respondents (88%) were Caucasian/White followed by African American (4%), Asian (3%), and Latino (2%). The remaining respondents indicated “Other” in response to the question about ethnicity. When asked if they identified themselves as adopters of the instructional technology in the technology classrooms, 91% identified themselves as adopters, while 9% referred to themselves as non-adopters. The ITS personnel reviewed the survey responses and first looked for possible correlations between demographic characteristics and the adoption/non-adoption status of respondents. No correlation was found between adoption status and the demographic characteristics of gender, ethnicity, years teaching, and age. The second area explored was related to the diffusion of innovations and social network analysis theories proposed by Rogers (1995). Once again no significant correlation was found between the adoption status and the social networks of the respondents. The investigation into training revealed that there was a positive correlation between adoption status and four sources of training: a) ITS, b) Center for Teaching and Learning, c) self, and d) Web-based training. The university had five different departments that make instructional technology training available to faculty. There were 12 training choices provided on the survey and respondents were asked to choose all that were applicable. Respondents indicated they received the most training from ITS (55%), followed by self tutorial (35%), the Internet (24%) and the Center for Teaching and Learning (20%). Analysis of the data indicated relationships between faculty adoption status and those who received training from ITS, self
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tutorial, and the Internet. This meant that training had a correlation to adoption. The data also indicated correlations between training and use, as well as adoption and use of the instructional technology in the Technology Classrooms. Finally, ITS investigated the use of actual hardware in the classrooms. A low correlation was found between adoption status and the use of the laptop connection, the PowerPoint advancer, and the wireless microphone. A moderate association was indicated between adoption status and use of the lectern computer, document camera, lectern, VCR, lectern DVD, lectern microphone, and flash drive.
Future research directions After reviewing the results to the survey, future research directions for the ITS group were identified. ITS decided to continue to pursue the social network analysis theoretical framework, but from an organizational perspective rather than the individual/ego perspective they took in this study. They also plan to explore the software that faculty are using in the technology classrooms. They further determined it would be beneficial to randomly select faculty utilizing these classrooms to add a qualitative component to their investigation into the utilization of the technology classrooms. Since faculty recognize the importance of training, it would be helpful to ask faculty to identify how they learned of the training in order to determine which methods have been most effective.
Conclusions The data from this study indicated that the instructional technology training offered by the university used in this research correlated positively with faculty adoption and use of the technology. Based on the results of the survey, ITS and the universities administration believed their instructional technology investments used for the Technology Classrooms were justified. A large majority of the faculty considered themselves to be adopters of the instructional technology used in the Technol-
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ogy Classrooms on campus. Responses to open-ended questions suggested a need for more Technology Classrooms, because the classrooms are constantly booked for classes with no openings. Consequently, the university has increased the number of technology classrooms from 49 to 72. The research and the data indicated that the Technology Classrooms were being used by faculty who considered themselves adopters. To further assist faculty and in an effort to make the training opportunities more efficient, the university combined the ITS user services division and the Center for Teaching and Learning into one unit. This new unit offers faculty training in software and use of the equipment in the Technology Classrooms, which are well-attended. In addition to workshops, ITS makes the handouts from these workshops available for viewing or downloading and offers Help Desk support to the university community. Faculty are able to submit a help ticket online regarding a specific problem or question, they may stop by the office, or call a consultant. In the Technology Classrooms, there is an emergency number faculty can use in the event of an equipment malfunction. A consultant is immediately dispatched to the location to resolve the issue. As another method of support, ITS offers faculty server space to store class files, which is accessible from the lectern computer in the technology classrooms. The type of students attending colleges and universities are using mobile communication devices, wireless communication, and whatever the next innovative technology marketed to that demographic. The investment colleges and universities make in instructional technology should continue to include provisions for training and support of faculty. The survey results support the relationship between training and faculty implementation of the technology. Higher education would be wise to invest in training and support of faculty in methods of leveraging the technology for teaching. The return on investment would be garnered through student learning and faculty use of the available instructional technology. ■
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