Jacobsen, D. M. (2000). Examining Technology Adoption Patterns by Faculty in Higher Education. Proceedings of ACEC2000: Learning Technologies, Teaching and the Future of Schools, July 6 to 9, Melbourne, Australia.

Examining Technology Adoption Patterns by Faculty in Higher Education

Dr. D. Michele Jacobsen
Faculty of Education, University of Calgary, Canada

The integration of technology for teaching and learning greatly appeals to some faculty in higher education, and not to others. Why is this the case? This investigation builds and extends upon a theory of the diffusion of innovations and adopter categories in order to describe current faculty innovativeness, as well as to explore the differences between early adopting faculty and mainstream faculty. A mixed-method research design was employed to investigate the difference between those who readily adopt technology for teaching and learning, and those who do not. Faculty members from across disciplines at two large North American universities were surveyed about computer use patterns, self-rated expertise, technology adoption patterns, changes to classroom environments, incentives and barriers, and preferred methods for learning about technology. This paper reports on the differences found between early adopters and mainstream faculty and the implications for technology integration plans in higher education. Recommendations are made for campus-wide technology integration plans based upon findings that early adopter and mainstream faculty prefer different methods for learning about technology, require different types of professional development and support, and report diverse motivators and impediments to integrating computer technology.


Information technology is no longer the novelty it was a number of years ago. No longer the exclusive domain of a small "technological priesthood" (Sabelli, 1998), computers have become an integral part of our daily lives, and in many ways, we cannot seem to function without them. Individuals use computers to book flights as well as to fly them. Computers are used to manage and direct the flow of information and currency by governments, banks, and stock markets. The past decade has seen exponential growth of the Internet and personal connectivity. Increasingly sophisticated technology at home and in the workplace has spawned unprecedented use of machines by men, women, and children (Weil & Rosen, 1997). Computers are also becoming standard equipment in education, as basic to teaching and learning as libraries, books, and pencils, and as essential to communication as telephones (Brown, Burg, & Dominick, 1998). Information rich institutions of higher education use technology for administrative management, information access and delivery in libraries, research and development, as a medium of communication, and for teaching and learning.

Recent estimates indicate that colleges and universities invest billions of dollars per year for the acquisition of computer technology (Geoghegan, 1994). Instructional technology (IT) may support and increase the efficiency of the teaching-learning transaction or even modify educational processes, especially with regards to distance education and "anytime, anywhere" access (Daniel, 1997). Formal evidence linking this investment to higher productivity (Schwalbe, 1996) and changes and improvements in the teaching and learning process is accumulating (Kulik & Kulik, 1980, 1987; Ehrmann, 1995). New research approaches and methodologies are being developed to adequately study the unique issues involved in educational technology (Bull, et al, 1994). In some cases, integrating technology into the teaching-learning transaction has been found to transform the teacherís role from being the traditional "sage on the stage" to also being a "guide on the side", and student roles also change from being passive receivers of content to being more active participants and partners in the learning process (Alley, 1996; Repp, 1996; Roblyer, Edwards, & Havriluk, 1997). Increased access to and use of the Internet is making a unique contribution to the teaching and learning process (Shaw, 1994) and will be an important part of future strategies to provide services to increased number of students in very diverse locations (Daniel, 1997).

Although there is a growing number of faculty who are very enthusiastic about adopting technology because of the potential of newer tools for their students, there is still a large number of faculty who seem hesitant or reluctant to adopt technology for their teaching tasks. Explanations for limited adoption may be found in the many barriers that still constrain use by enthusiastic beginners; user friendliness is a seductive term which misrepresents current technological reality. While acknowledging improvements in current design, computers and peripherals are still not well-designed, fault-free, and easy to use. As such, the evaluation of the success of educational technology still seems to depend largely on how well "early adopters" make it work. Given the size of investment in instructional technology in higher education, the increased demand for distance education in the future, and the demonstrated effectiveness with some educational outcomes, it seemed reasonable to investigate why the integration of technology for teaching and learning is so appealing to some faculty, and not to others.

Diffusion of Innovations A conceptual framework for analyzing faculty adoption of technology patterns is provided by Rogersí (1995) theory of the diffusion of innovations, which defines diffusion as the process by which an innovation is communicated through certain channels over time among the members of a social system. He defines an innovation as an idea, practice or object that is perceived as new by the individual, and diffusion as the process by which an innovation makes its way through a social system. For our purposes, the innovation is instructional technology for teaching and learning, and diffusion is the extent to which all faculty have adopted this innovation. Because individuals in a social system do not adopt an innovation at the same time, innovativeness is the degree to which an individual is relatively earlier in adopting new ideas than other members of a system. Rogers (1995) describes five adopter categories along the continuum of innovativeness (Figure 1.) which are ideal types designed to make comparisons possible based on characteristics of the normal distribution and partitioned by the mean and standard deviation. In this investigation, respondents were assigned to either the earlier adopter (i.e., innovators + early adopters = EA) or mainstream faculty (early + late majority + laggards = MF) subgroups using a scoring procedure developed by Anderson, Varnhagen, and Campbell (1997) in a similar study of faculty adoption patterns.
Figure 1: Adopter Categorization on the Basis of Innovativeness (Rogers, 1995)
Methodology The present investigation surveyed faculty members from across disciplines at two major North American universities. An invitation to participate was e-mailed to 400 faculty who subscribe to an educational technology list server at one institution, and via campus mail to a stratified sample of 500 faculty members at another. Information was gathered about technology use patterns, computer experience and use of technology for teaching, changes to teaching and learning, incentives, and barriers, using a web-based survey instrument (http://www.acs.ucalgary.ca/~dmjacobs/phd). Complete data was obtained from 76 participants (38% female, 62% male; return rate 8.4%), who were on average 45.5 years old, had an average of 12.5 years experience as faculty member, and hold various academic ranks within their institution (i.e., 19.7% assistant, 35.5% associate, 26.3% professor, 18.4% lecturers and sessionals). Over 65% of participants hold appointments that are tenured or leading to tenure. The majority teaches 100 or less students per semester, and represents a range of academic disciplines: Agriculture, Continuing Education, Education, Engineering, Environmental Design, Fine Arts, General Studies, Humanities, Kinesiology, Management, Medicine, Nursing, Science, Social Science, and Social Work. Computer Use in Classrooms In order to examine the adoption of technology using time as a measure of the diffusion of innovations, participants were asked to indicate the year in which they first used any of 44 types of computer software and tools in a course they taught. Rogersí (1995) identified the segment of the diffusion curve between 10 and 20 percent adoption as "critical mass" and it represents the transition from the early adopter level of innovativeness to the early majority. Of the 44 types of computer software and tools, 29 have been used in the classroom by more than 16% of respondents (Table 1) and thus, have exceeded critical mass. Of the 29 types of software/tools that have exceeded critical mass (i.e., adopted by early majority (EM)), 3 have diffused into the late majority (LM), which means that these technologies are used by more than 50% of the respondents in their teaching (i.e., word processing 60.5%, e-mail 67.1%, and WWW browsing and searching 56.6%).

Table 1. Percent of Total Adoption of Software by Individual Faculty for Classroom Use

Software and Tools
Classroom Use
Electronic mail
LM ß
Word processing
WWW browsing, searching
Text editing
EM ß
On-line DBs (&/or library catalogues)
WWW page creation/editing
Statistics package
Win 95
Presentation package
Desktop publishing
Grading package
Listservs, BBS
Win 3.x, NT
Any programming language
Drawing program
FTP (upload, download files) 

Changes to Teaching and Learning

Hadley & Sheingold (1993) indicate that significant changes can take place as teachers integrate computers into instruction. Faculty used a five-point scale (1.strongly agree, 2.agree, 3.neutral, 4.disagree, 5.strongly disagree) to indicate their level of agreement with statements about how the integration of technology may change the teaching and learning environment. EAs expressed statistically higher agreementt (74) = 2.05, p < .05 (Ms = 2.00 vs. 2.58) that "faculty are better able to tailor students' work to their individual needs" and that "faculty spend less time with the whole class practicing or reviewing material" t (74) = 1.99, p < .05 (Ms = 2.23 vs. 2.93) than MF. These differences may be explained by the greater amount of time needed, at least initially, by MF to integrate technology into teaching and learning. EAs may be enjoying the accrued benefits of this time investment more than mainstream faculty. Incentives to Integrate Technology in Teaching Given the time and effort required to integrate technology and teaching, different reasons tend to motivate and keep faculty engaged with this task. Participants used a five-point scale to indicate the extent of their agreement with 12 items. An estimate of the internal consistency of this subscale yielded a coefficient alpha of .88, which is a relatively high rating of item homogeneity and indicates that faculty responded consistently across items. While four of the five highest rated incentives have to do with providing enriched learning opportunities for students, the number one incentive for integrating technology is the personal gratification a faculty member gets from learning new computer knowledge and skills. EAs expressed statistically higher agreement t (74) = 2.72, p < .01 (Ms = 1.61 vs. 2.52) that they enjoy figuring out how to use computers effectively for a variety of teaching situations than did MF. The greater enjoyment that EAs experience figuring out how to use technology in teaching may be related to the incremental amount of time needed to add to their existing repertoire of computer knowledge and skills, and the greater success they may already have experienced using technology in their teaching. It seems fair to suggest that MF have to invest more time than the EAs to develop a repertoire of computer knowledge and skills, as well as investing time figuring out how to integrate technology into their teaching. Therefore, the greater amount of time needed by MF for these two tasks may not translate into the enjoyment that EAs experience experimenting with technology. Barriers to Integrating Technology Although many have developed impressive personal expertise and have adopted computers in their classrooms, to a greater or lesser extent, all faculty experience barriers when they attempt to integrate computers in their teaching. Participants used a five-point scale to indicate the level of their agreement with barrier items. The five items that faculty agreed with most were: 1) Faculty members lack enough time to develop instruction that uses computers, 2) There are problems scheduling enough computer time and/or resources for different facultiesí classes, 3) Financial support for computer integration from administration is inadequate, 4) There are too few computers for the number of students, and 5) There is inadequate financial support for the development of instructional uses of computers. EAs expressed stronger disagreement t (74) = 3.86, p < .001 (Ms = 4.07 vs. 2.58) than MF that they were unsure how to effectively integrate computers into instruction. EAs also expressed stronger disagreement t (74) = 2.12, p < .05 (Ms = 4.15 vs. 3.31) than MF that computers do not fit the course or curriculum that they teach. It is interesting to note that EA and MF did not differ about adequate training opportunities for faculty to acquire new computer knowledge and skills. Learning about Technology Individuals tend to have preferred methods for learning more about technology. Faculty were asked to rank the importance of different methods for learning about technology, getting help and support, and accessing information about innovations. In terms of media and methods for acquiring new computer application skills and knowledge, faculty ranked the following from most to least important in descending order: 1) hands-on experimenting and trouble shooting, 2) mixture of manuals and hands-on, 3) hardcopy materials, books, etc., 4) on-line manuals, 5) workshops and presentations, and last, 6) structured courses and guidance. In terms of help or assistance with using computers, faculty ranked the following sources of support from most to least important in descending order: (1) colleagues on campus, (2) one-on-one assistance, (3) experienced graduate students, (4) media center support staff, (5) hot-line, or telephone assistance, (6) outside professionals trained in technology use, and last, (7) colleagues at another institution. EAs rated experienced graduate students as more important t (74) = 2.10, p < .05 (Ms = 1.69 vs. 2.36) than MF. Depending upon the nature of the discipline, it is possible that many MF do not encounter graduate students who have helpful levels of expertise using technology. Early adopters (EA) rated 5 sources of information for keeping abreast of changes/innovations in the area of computers as more important than MF (Table 2). Perhaps because of their greater interest in the technology itself, EAs regard computer publications and meetings about computers as important sources of current information about technology.

Table 2. Sources of Information EAs Ranked More Important than MS for Keeping Abreast of Changes and Innovations

t (74)
Ms - EA vs MS
1. refereed computer journals
3.42 ***
2.38 vs. 3.44
2. popular computer magazines
2.70 **
2.00 vs. 2.90
3. innovative graduate students
2.57 *
1.46 vs. 2.23
4. conferences, demonstrations and workshops
2.38 *
1.92 vs. 2.71
5. on-line computer newsgroups and websites
2.00 *
2.00 vs. 2.66
* p < .05, **p < .01, *** p< .001

A good number of Technology Integration Plans suggest that faculty need more workshops and courses in order to acquire the knowledge and skills they need to adopt technology. However, future plans for professional development should be informed by faculty memberís expressed preference to get help from colleagues and graduate students, and get one-on-one assistance, rather than attending a "one-shot" workshop. Combined with the preferences expressed in the first part, it appears that the most successful professional development would be to have just-in-time, one-on-one access to colleagues and experienced graduate students when one runs run into trouble experimenting and playing around with new technologies.

Discussion Early adopters are more likely to have first used computers on campus as a student, and use computers for more hours per day than mainstream faculty. However, an unexpected result was that EAs have similar computer ownership patterns to MF for personal/home and professional use. As expected, EAs report higher levels of expertise than MF for 38 (86%) of the 44 types of computer software and tools, and earlier use in teaching for 27 of the 44 types of measured types of instructional technology. This result provides evidence for the breadth of EAsí relatively higher innovativeness; they are earlier in adopting many forms of technology than other members of the social system for both personal use and for use in teaching. Technology seems to hold a high, intrinsic attraction for early adopting faculty who view technology as fun and challenging. It is interesting to note that EAs tend to teach more students per semester than mainstream faculty (i.e., 125 vs. 75). This finding suggests that EAs are integrating technology beyond the pilot projects, beyond the smaller classes with more "experienced" students. With regard to changes to teaching and learning, EAs are confident that they can effectively integrate computers into instruction, and rate computers as compatible with the course or curriculum that they teach.

EAs tend to prefer certain methods more for learning about computers than MF. In terms of help or assistance with using computers, EAs ranked experienced graduate students as more important than MF. The EAsí self-confidence with the technology, and greater enjoyment figuring out how to use computers effectively for a variety of teaching situations, probably contributes to the value they place on graduate students who share this interest, speak their language, and may contribute to further building and extending their current knowledge and skills. This hypothesis finds further support in the higher importance that early adopters place on innovative graduate students for keeping abreast of changes/innovations in the area of computers.

EAs described their frustration with the annual review process and funding agencies that seem to undervalue their teaching and technology integration efforts. Further, for many EAs, who are working at the edge of their fields and developing new teaching and learning environments, it is disheartening to be evaluated by department heads and peers who may not share the same belief structure and often fail to understand the significance of and motivation for their work. EAs also describe frustration with the "insufficient evidence" argument put forth by peers who do not share their beliefs, or their familiarity with the literature, about the benefits of this type of research and teaching. Two EAs described the difficulty of doing experimental research on the benefits of technology integration with students because of equity concerns about the control group who does not get the technology intervention.

EAs offered some solutions for bridging the gap between themselves and MF. One faculty member described the potential trialability and reduced complexity benefits of giving each faculty member their own laptop computers, while another described a campus example where even gifts of computers did not encourage all faculty members to adopt technology. Another EA suggested providing training and support to increase the comfort level and how-to knowledge of other faculty so they can approach any piece of software and figure it out (i.e., perhaps to become more like an early adopter?). One individual called for increased standardization of hardware, software, and networking in order to make it very convenient for faculty and students to use the technology, and increase the amount of "just in time" training and support by building more critical mass technology skill and knowledge on campus. Another proposed solution from an EA was to give experienced faculty members course reductions so that they can invest time creating and developing technology-enhanced curricula that can be standardized throughout a department or faculty.

Recommendations For Encouraging Adoption by Mainstream Faculty The intent of this section is to present recommendations for technology adoption and integration plans that do not succumb to the individual-blame versus system-blame biases that often appear in diffusion research. Rogers (1995) defines individual-blame as the tendency to hold an individual totally responsible for non-adoption rather than the system of which the individual is a part; conversely, system-blame is the tendency to hold a system responsible for the slow or limited adoption of individual members. Findings suggest that both internal (individual) and external (system) factors make the integration of technology more appealing to some faculty respondents than others. Technology appears to be widely diffused among faculty respondents for professional and research tasks, and is becoming more visible on campus for teaching and learning. Results from this investigation provide evidence that some types of computer software and tools have diffused into the mainstream for teaching and learning tasks. It has been established that there are incentives that appeal more to EAs than MF, and barriers that constrain MF as well as EAs. Recommendations will be made for what EAs and MF might do to encourage further adoption and integration of technology efforts on campus, and also for what institutions might do to promote instructional technology as a way to fundamentally rethink teaching and learning.

The first recommendation is to focus on strategies for increasing the awareness and how-to knowledge about successful strategies for teaching and learning with technology. Mainstream faculty may be reluctant to make decisions about the use of technology in their teaching because they are unfamiliar with it, they may feel inadequate to assess the potential impact the technology will have on the teaching and learning environment, and they are not convinced it offers relative advantage over what they are doing now. Not every faculty member can or will become a technology expert. In order to increase the awareness and how-to knowledge of mainstream faculty, some method has to be found to share the experience, skills and knowledge of the early adopters, their "learned lessons", with the mainstream. Mainstream faculty need to understand what the technology can do, and be provided with evidence about the benefits, but they do not necessarily have to have procedural-knowledge about computers before evaluating the relative advantage of an innovation in their own teaching situation.

A second recommendation is to increase the observability and trialability of technology integration on campus. Observability is the degree to which the results of an innovation are visible to others (Rogers, 1995). Perhaps if early adopters modeled or demonstrated strategies for successful uses of technology one-on-one or with small groups of their mainstream peers then the gap between the convinced and unconvinced would begin to be addressed. The personal trying-out of an innovation is a way to give meaning to an innovation, to find out how it works under oneís own conditions, and tends to dispel uncertainty about the new idea. Early adopters can act as a kind of vicarious trial for mainstream faculty by modeling successful uses of technology for teaching and learning, and reducing uncertainty about this innovation.

A third recommendation is to help promote a culture of inquiry into teaching and learning with technology that begins with incremental steps rather than huge leaps into a maelstrom of options. A frequently mentioned incentive to further adoption of technology, "give me more time", and the highest rated barrier to integrating technology, "faculty lack time", may be related to the exponential rate with which new hardware and software tools are being developed. The steady rate with which new technologies become available leads to shorter and shorter innovation cycles, and therefore a continuous training and professional development requirement. This shortens the innovation-decision period, and when faced with the onslaught and never-ending cycle of new technologies, some faculty may just throw up their hands and give up, "I just cannot keep up." Mainstream faculty may regard the ever changing nature of technological tools and software as a chaotic stream that they do not wish to jump into for fear of drowning. Most early adopters admit that they still have a lot to learn, and often find themselves flying by the seat of their pants while trying unproved and innovative teaching methods. EAs who are interested in being role models have much to offer to the newer adopter who wants to just get started by helping to change the perception that technology adoption and integration for teaching comes easily to them, and instead starts with learning one thing well.

A fourth recommendation for early adopters who are excellent teachers is to conduct and widely disseminate applied educational research on the changing roles of teacher and student, and the shift from more behaviorist methods to more constructivist methods that have been facilitated by technology. An innovationís incompatibility with cultural values can block its adoption. Technology was originally designed for use in one culture, math and science, but it has now spread to a different culture, teaching and learning, with different cultural values. Excellence in teaching does not depend upon technology. Additional educational research is needed on the relationship between integrating technology and a shift from teacher-directed to more student-constructed learning environments in order to provide images of new pedagogical methods, and decrease uncertainty about these changes.

Recommendations for Institutions The first recommendation for institutions is to focus technology integration plans on increasing critical mass by investing in the professional development of faculty members. To make the products or results of early adopter efforts more widespread and their results used more comprehensively, incentives, training, support and reward structures from administration are needed to build a strong human infrastructure that supports the integration of technology for teaching and learning. Administration also has to address teaching and course release time, software ownership issues, research and development grants, and funding in order to encourage more inquiry into teaching and learning with technology. The key to diffusion will be training and support. Without investment in the human infrastructure nothing of sustainable value will be achieved (Foa, 1993). Institutions can do little to stem the exponential rate at which hardware and software tools are being developed. However, they can provide the necessary training and support with these tools as faculty face shorter and shorter innovation-decision cycles.

The second recommendation is based upon the need for a technological infrastructure (i.e., networks, hardware and software) to encourage adoption and integration. IT investments for teaching have to be closer to what is the state of the art in the world of work, as higher education prepares for the future. These ever-new investments cannot be left to uncoordinated departmental or individual initiatives, as they often exceed respective budgets (Bull, et al., 1994). Over 75% of respondents were dissatisfied with current campus investment in computer technology for teaching and learning. The most promising uses of technology for teaching and learning seem to be for communication, accessing and exchanging shared resources and information on-line, and faculty and student publishing on the web. Campus acquisition plans should direct resources to upgrading the infrastructure to accommodate more technology integration in all classrooms; adjustable lighting, adequate projection systems, and built-in network connectivity.

The third recommendation for institutions is to find ways to reward that which they purport to value. Administration must recognize that in order to drive change they will have to be aware of the culture they promote, and emphasize excellent teaching in their technology integration plans. In order to realize the benefits and value of investing in technology, a universityís culture should explicitly and intentionally promote instructional technology as a way to fundamentally rethink teaching and learning, and as a way to question and explore new approaches to writing, communication, and research. Promoting technology for technology sake is a recipe for failure.

A fourth recommendation is to create a different support infrastructure for mainstream faculty that leverages the expertise of the early adopters. It appears that system-wide changes will be needed in the reward system and training for faculty members in order to encourage broader diffusion of instructional technology in the mainstream. Further, a different support infrastructure is clearly needed for MF than that which sufficed for EAs. Proportionally more support and training services will be needed for the 80% or so of faculty members who are mainstream users of technology. Recognizing that mainstream faculty have different characteristics, and therefore needs, does not suggest that there is no role for early adopters in developing long-term plans for campus-wide adoption. Quite the opposite. Early adopters have discovered and overcome many barriers in their attempt to integrate this innovation, and have developed and contributed to a collective knowledge base concerning instructional technology. Change agencies must capitalize on this valuable human resource that exists on campus.

The fifth recommendation is find ways to include both EAs and MF in campus-wide decisions about integrating technology. Results in this study demonstrated that early adopting and mainstream faculty have strong and varied opinions about the changes to classrooms, incentives, barriers, and methods for evaluating integration. The views, beliefs, suggested solutions, and opinions of both advocates and critics should be elicited and included in the development of campus-wide technology integration plans. Communication strategies should be employed in order to move discussions about integrating technology beyond the early adopters and perceived "techno-cliques", and into the mainstream by promoting interaction and collaboration among and between faculties and departments. Groups that include their diverse members in decision making tend to be more inclusive and reflective of peopleís interests and needs, which in turn makes the change process more successful and less traumatic (Wilson, 1998). One method that has proved to be effective in getting cross-campus faculty members to communicate and work with diverse individuals in other departments and institutions has been to link project funding to the interdisciplinary nature of the investigation; for example, more governmental agencies are making it a qualifying criteria that more than one institution or faculty is involved in a funded project.

The sixth recommendation for institutions, faculties, and departments is to resist being autocratic in drafting plans for bridging the gap between early adopters and mainstream faculty. Change is hard work. While the administration may find it more expedient to lay down the law and declare that everyone will use computers, this strategy is likely to yield bitter fruit (Wilson, 1998). Faculty may become cynical, feel abused, and not listened to. Taking the major portion of the responsibility for instructional decisions out of the hands of faculty is a serious step. Faculty will, in turn, seek to undermine the technology agenda through passive resistance, disengagement, and covert sabotage, which means more work in the long run for an authoritarian solution. A more difficult and time consuming, but potentially more effective, strategy would be to elicit and include both EAs and MF in technology discussions, plans for acquisitions, and decisions about implementation. Administrative proclamations, press releases, pressure from software companies, and other forms of covert harassment will not train and support faculty members in their integration efforts, nor will these win faculty support for an agenda that they do not support.

A seventh recommendation for institutions is to put mechanisms in place that allow for cyclical and iterative development and assessment of technology in teaching and learning. Tolerance has to be build into the system for time lags, unexpected barriers, and longer innovation-decision periods. Technology integration constitutes a major change in peopleís lives. Such change does not happen quickly or easily. Even in the best of circumstances, teachers and students need high levels of support, training, and access to technology. While technology can open up new possibilities in teaching and learning environments, care should be taken to make sure that the technology fits the core values and goals of higher education, and not the other way around.

A final recommendation for institutions is to resist re-inventing the wheel. A number of system-wide initiatives have been implemented at various higher education institutions (see Burg & Thomas, 1998, Communications of the ACM special issue on campus-wide computing) which provide models for encouraging wider diffusion of technology for teaching and learning, and bridging the gap between early adopter success and more mainstream adoption.

References Alley, L. R. (1996). Technology precipitates reflective teaching: An instructional epiphany. Change, 28 (2), 49-54.

Anderson, T., Varnhagen, S., & Campbell, K. (1998). Faculty adoption of teaching and learning technologies: Contrasting earlier adopters and mainstream faculty. Canadian Journal of Higher Education, 28 (2-3) 71-98.

Brown, D. G., Burg, J. J., & Dominick, J. L. (1998). A strategic plan for ubiquitous laptop computing. Communications of the ACM, 41 (1), 26-35.

Bull, G. M., Dalinga-Hunter, C., Epelboin, Y., Frackmann, E., & Jennings, D. (1994). Information technology: Issues for higher education management. London: Jessica Kingsley Publishers.

Burg, J. J., & Thomas, S. J. (Eds.). (1998). Computers across campus. Communications of the ACM, 41 (1), 22-44.

Daniel, J. S. (1997). Why universities need technology strategies. Change, 29 (4), 11-17.

Ehrmann, S. C. (1995). Asking the right questions: What does research tell us about technology and higher learning? Change, 27 (2), 20-27.

Foa, L. J. (1993). Technology and change: Composing a four-part harmony. Educom Review, 28 (2), 27-30.

Geoghegan, W. H. (1994). Whatever happened to instructional technology? Presented at the 22nd Annual Conference of the International Business Schools Computing Association, Baltimore, MD.

Hadley, M., & Sheingold, K. (1993). Commonalities and distinctive patterns in teachersí integration of computers. American Journal of Education, 101, 261-315.

Kulik, J. A., Kulik, C. C., & Cohen, P. A. (1980). Effectiveness of computer-based college teaching: A meta-analysis of findings. Review of Educational Research, 50 (4), 525-544.

Kulik, J. A., & Kulik, C. C. (1987). Review of recent research literature on computer-based instruction. Contemporary Educational Psychology, 12, 222-230.

Repp, P. C. (1996). Technology precipitates reflective teaching: The evolution of a red square. Change, 28 (2), 49, 56-57.

Roblyer, M. D., Edwards, J., & Havriluk, M. A. (1997). Integrating educational technology into teaching. New Jersey: Prentice-Hall.

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

Sabelli, N. (1998). We are no longer a priesthood. Communications of the ACM, 41 (1), 20-21.

Schwalbe, K. A. (1996, March). A study of the relationship between investments in information technology and institutional outcomes in higher education. (Doctoral Dissertation, University of Minnesota, 1996). ProQuest - Dissertation Abstracts, AAC 9621911.

Shaw, M. L. G. (1994). Women, scholarship and information technology: a post-modern perspective. Transactions of the Royal Society of Canada: Series 4, 5, 112-131.

Weil, M., & Rosen, L. (1997). TechnoStress: Coping with Technology @Work @Home @Play. New York: John Wiley & Sons, Inc.

Wilson, B. G. (1998). Wise as serpents: Putting a human face on technology adoption and integration. Paper presented at the meeting of the Association for Educational Communications and Technology (AECT), St. Louis, MO, February 1998. [On-line]. Available: http://www.cudenver.edu/~bwilson/serpents.html

© ACEC and Dawn Michele Jacobsen 2000