Figure 1. Timeline
David Wilson, Senior Lecturer, Department of Information Systems, Monash University, Melbourne dwilson@is.monash.edu.au
In Figure 1 we see a time-line that illustrates the point that human life is one long continuum of change. More importantly, the time-line indicates a concern with knowledge and its dissemination. In particular, we see juxtaposed two decades of the microprocessor (microcomputer) development era with two centuries of 'industrial revolution.' Almost in contradiction of economic historians like John Maynard Keynes, Freeman and Perez portray this industrial development as five Kondriatiev cycles that have at their base, the adoption and diffusion of a number of vital technologies and the discovery and use of a number of key resources. (Freeman C. and Perez, C., 1988, pp.41-45.)
With the benefit of hindsight, we see the industrial revolution as a single event that had its impact in various countries at particular points in time. That is, it took time for an innovation such as James Watts' contribution to steam engine development in Scotland in 1769 to impact in other parts of the developing world. Such innovations diffused through separate nation-states over time, so that in reality there were a number of 'industrial revolutions'; Firstly in Britain, then in France, Belgium, Germany and in the United States, and next in Sweden and Japan and from this point in time to occur in parts of Latin America, the Middle East, Central and Southern Asia and lastly in Africa. (Lane, P., 1978.) The concept of early mover advantage, so ingrained in marketing science literature, first developed from this historical fact that through chance, or human intervention, innovations occurring in one place give the innovator nation strengths it might not otherwise have had.
Figure 1. Timeline
The industrial revolution may also be seen as a number of time lines wherein discoveries were made or adaptations took place and, diffusion of these innovations then occurred over a number of years: Early mechanisation, steam propulsion and railway development (1770 -1890s); Electrical and heavy engineering (1880s - 1940s) and; Fordist mass production (1930s - 1990s). (Freeman C. and Perez, C., 1988, p.47.) (Encarta 95, 1994.)
The Information Technology Era shown in the Figure 1 commences with the development of the microprocessor and proceeds into the foreseeable future. It encompasses the development of the microprocessor, and now involves technological convergence that sees a number of technologies merging through the activities of a range of commercial and government organisations. This is as true in North America or Asia as it is in Australia and Oceania. Of particular significance are computer hardware companies such as Intel and software developers such as Microsoft. Many other companies such as Apple Corporation and IBM, have found their fortunes waning as newer entrants including Netscape and Sun Microsystems have burst forth with their own innovations. Netscape has risen to fame through developing a WWW browser. Sun Microsystems are renowned for their high performance workstations and more recently for their development of an object-oriented programming language - Java - that readily permits integration of sound, vision and data within the hypermedia environment that the world wide web embodies. This is but one of many enhancement programs available for WWW programmers in 1996.
It was Gordon Moore, co-founder of Intel, who in the late 1980s documented the fact that every three years the chipmakers have been delivering four times the processing speed and memory capacity at roughly the same price. (Chen, A., 1990.) Where Intel's 4004 chip developed in the early 1970s consisted of 2,300 transistors, the i486DX chip developed in 1989 had 1.2 million transistors, the i486DX2 had 2.4 million transistors and the 1993 released Pentium had some 5 million transistors. Intel were aiming to build in 100 million transistors well before the turn of the century (Chen, 1990.) The Pentium released by Intel in 1993 cost $950, but it allowed a massive throughput of 100 MIPs or millions of instructions per second. This meant that the new cost per MIP was $9.50 - a drop of 97 percent over the period.(Port, O., Gross, N., Gross, N., Hof, R., Brandt, R., Burrows, P., and McWilliams, G., 1994, (July 4): pp.46-52.)
Figure 2. Transistor Counts in the Microprocessor Development Era
"There is a limit to speed however the micro- computer has some development left in it yet. Figure 3 illustrates the reductions in chip size achieved by Intel and their expectations for the future. Moore's Law depicted in Figure 2 predicts that for there to continue the doubling of the number of transistors on an Integrated Chip every two years, by the turn of the century silicon devices will be a 0.25 Micron process. This will be 40 times smaller than the starting point in 1971 shown in Figure 2. Such a processor, which Intel calls Micro 2000, would integrate between 50 and 100 million devices on an inch- long piece of silicon, and run at 250 MHz. Memory density would reach the 256-Mb to 1- Gigabit range." (Adam, S., 1993, p.6.)
The Information Technology Era is highly commercialised in the mid-1990s. The Era is not one smooth development curve, but rather a series of S-Curves that reflect the fact that new uses have been found for the microprocessor that are the equivalent of a soap powder manufacturer 'adding blue beads of brightness.' That is, the product lifecycle of the microprocessor has been enhanced by adding an innovation or feature to the circuitry of the microprocessor that hitherto was undertaken by a separate microchip or piece of equipment or perhaps by manual labour. Examples of this are the use of Z80 chips in early washing machines, and AT286 chips that once lay at the heart of IBM compatible microcomputers, which are now found in peripheral devices such as video graphics cards for the computer. Higher level microprocessors, once the domain of computers, are used in all manner of productive equipment even to the point of use in Global Positioning Systems (GPS) for motor trucks and cars. Further along the time continuum, it was the advent of local area networking (LANs) and wide area networking (WANs) that gave impetus to the capabilities of the microprocessor. This fitted neatly with the desires of chipmakers such as Intel, who saw competition increase dramatically when they lost a court case that permitted competitors such as American Micro Devices (AMD) to use the 386 nomenclature for their central processor chip (CPU). Maintaining competitive advantage in this industry means making smaller chips with more transistors. And in doing this, they have a symbiotic relationship with software developers to ensure there is a need for users to upgrade to the newer technology. However, the earlier industry profitability may disappear as it now costs much more to research, develop and build fabrication, or 'fab', plants to produce silicon chips of the type required.
Figure 3. Transistors Approach Virus in Size
More recently there has been explosive growth in the 'at home' market, to quote the first screen from Microsoft's raft of CD-ROM based products such as Encarta96 World Atlas for high-end Intel compatible machines running the 32-bit operating system Windows'95, as well as for Motorola-equipped Macintosh machines. CD-ROM disks and drives have developed from compact disk technology used initially to replay sound alone. A number of CD-ROM and CD- I (Interactive) standards have been developed, with more on the way. (See Figure 4.) This does not include video disc technology which may yet experience a revival.
In the commercial sector, CD-ROM "trails on-line services and World Wide Web Sites as a marketing tool." (Rubel, 1996, p.10.) However, CD-ROM is finding a new lease of life away from computer games and is used in tandem with the WWW. For example, Toyota combines the use of the two technologies. The Toyota Web site [HREF 1] features lifestyle aspects with cars taking second place. Their CD-ROM however, utilises the full motion video capabilities of CD-ROM to market car features. Like Toyota, other marketers such as Microsoft are using or planning to use the feature whereby Web site access derives from the CD-ROM. In this manner, information can be kept current.
As already pointed out, the most recent impetus to microprocessor development is the convergence of technologies that is represented in embryonic form by by the Internet, particularly the World Wide Web. This convergence involves the following technologies:
(Adapted from Adam, 1995 [HREF 2] , and Brenchley, 1996)
Figure 4. Twelve Multimedia standards 1992-94
There are many instances of what were seemingly good ideas, beneficial scientific advancements and product developments that despite their appeal to many, failed to be adopted by the numbers necessary for success - commercial or otherwise. Others have had immediate success. Why some innovations succeed, while others do not, has been the subject of much research. A pre-eminent diffusion researcher, as those who have delved into the nature of successful and unsuccessful adoptions have become known, is the sociologist Everett M Rogers. Rogers has studied the work of a range of scientists across a broad range of disciplines in order to gain an understanding of what leads to adoption and the nature of the diffusion process. As Engel, Blackwell and Miniard put it, "over 3,000 studies and discussions of diffusion processes have been published in at least 12 identifiable disciplines" (1993, p.728.),: Anthropology, Early sociology, Rural sociology, Education, Public health and medical sociology, Communication, Marketing, Geography, General Sociology and other traditions such as Economics, Political Science and, Industrial Engineering among others (Rogers, 1983). Studies in these and other fields continue, thus making the field of "innovation diffusion research one of the most multidisciplinary research topics in the social sciences today." (Frambach, 1993 p.22)
While there are a number of views of an innovation, it was Rogers who put forward the broadest view and one that marketing scientists have embraced, whereby innovation is "an idea perceived as new by the individual." (Rogers, 1962 p.13.). He explained that the main elements of the process of diffusion of innovation are as follows: an innovation; communication through particular channels; over time and; among members of a particular social system.
As already discussed, the time taken for an innovation to diffuse can vary between social systems. The reported adoption rate for mobile telephones as at August 1994 was lower in Australia than in Scandanavia, yet "Australia had the steepest growth curve." (Meredith, 1994b, p.36.). The mobile telephone is but one example of what is termed dynamically continuous innovation. That is, the innovation is but a continuuation of an existing technology. The use of fruit juice (lemon) in 1601 to prevent scurvy might be considered discontinuous innovation, as it is an example of a departure from existing practices. (Hawkins, Best and Coney, 1992 pp.156-157.) As Rogers points out, even though the experiment was a success, it took the Bristish Navy nearly 200 years, and the Merchant Marine 264 years before they adopted this innovation. The adoption of discontinuous innovation requires the greater degree of change in thought or action by the adopter, perhaps partially explaining the differences in diffusion time involved.
One might state that communication channels in the Information Technology Convergence Era are much different both in quantity and quality to that of the preceeding era; particularly prior to 1990. While this paper primarily concerns identification of predictors of educator adoption of a specific form of electronic technology, as opposed to organisational models of adoption, Frambach's conclusions in studying the latter category have relevance here: "The probability of an organization adopting an innovation (sooner) increases with the availability of information, the quality of the available information, and the value of the available information." (Frambach, 1993 p.26.)
Are all innovations adopted? In the educational field, as in the commercial, innovations may develop spontaneously. Some may be planned, such as in the commercial arena when a new calorie-controlled, portion-controlled, fixed weight chicken product is developed for sale to consumers at retail level because they are now cholesterol conscious and then diffuses to restaurants who in turn have expressed a need for such a product. Many developments have however occurred spontaneously from research with a different purpose, such as the many offshoots of the NASA space programs and the Internet from its 1967 beginnings as ARPANET.
Not all innovations are adopted by users, nor are innovations taken up by the entire potential market. For example, telephones are located in some 98 percent of Australian homes. Usage is however almost universal. In arriving at a decision to accept or reject an innovation, individuals pass from a state of unawareness to awareness and then on to forming a positive or negative attitude toward the innovation. Usually, a positive attitude is a pre-requisite to implementation of a new idea, however, the mere holding of a positive attitude is not enough to enable predictions concerning adoption and diffusion rates.
Once an innovation exists, the issue of diffusion comes to the fore. It has to be acknowledged that the many variables involved make it difficult to predict with accuracy whether there will be acceptance at a volume that will enable commercial success, and who will lead the charge to buy the innovation. Five adopter categories, and their relative size under what Rogers (1995) termed the diffusion curve, have been identified: innovators (2.5%), early adopters (13.5%), early majority (34.0%), late majority (34.0%) and laggards (16.0%). Rogers' model of the adoption process of innovation in the farming community assumed 100 percent adoption. While replicated to a degree by other studies, this is by no means a final statement on the matter.
A study by Mansfield and reported in Robertson (1967) established that there is a "bandwagon effect" whereby diffusion "snowballs" at Rogers' early majority stage. Thus the proportion who have already taken up an innovation in turn increase the rate of adoption by others.
There have been many studies that have sought to identify differences between innovators and early adopters versus late adopters. Relative to late adopters, early adopters have been found to be younger, but more highly educated, to have higher exposure to mass media, higher external social participation, to be more externally-oriented in their communication behaviour, to have more contact with change agents, to have greater interpersonal communication exposure, to have greater opinion-leadership in business and computer-related matters. (Huff and McNaughton, 1991) (Rogers, 1983 pp.260-261)
Given that Australian educators in the higher education sector had early access to the Australian Academic and Research Network (AARNET), now the Internet, it might be reasonable to expect that educators would tend to be the opinion leaders and now be further along the adopter continuum for the Internet and the World Wide Web than the community at large. One might also expect educators in the higher education sector to be heavier users of information technology. Before examining educator usage of such technologies, it is informative to examine, albeit briefly, the diffusion of information technology in the broader community.
The microcomputer adoption level by Australian households as reported by Keig & Co. in August 1995 is illustrated in Figure 5. The 46 percent usage level reported for August 1995 is to be contrasted with the 23 percent reported by the ABS in February, 1994 (ABS, Cat. 8128.0, 1994). This is a doubling of usage of computers at home, and ahead of IDC's 1994 predictions for the US, where home usage was predicted to lift from 30 percent of households in 1993 to 45 percent by 1997 and to 60 percent by the year 2000. It is also to be noted that the ABS reported that 3.9 percent of households used a modem in February, 1994 (Cat. 8128.0), whereas Keig & Co. report that this usage had grown to 6 percent one year later, and had grown to 10 percent by August 1995. Figure 5 also indicates that awareness levels for the Internet have risen rapidly. The ABS do not report such usage in their 1994 study, however, the Keig & Co.study indicates that almost half of their repondents were aware of the Internet in February, 1995 and that the diffusion of this information saw 81 percent aware of the Internet by August 1995.
| >Feb '95 | Aug '95 | |
| Internet Awareness |
47% |
81% |
| Internet Access |
7% |
11% |
| Home Computer Ownership |
40% |
46% |
| CD-ROM Ownership |
9% |
15% |
| Modem Home Ownsership |
6% |
10% |
| Video-on-demand |
34% |
39% |
Source: Adapted from "The New Media and Technology Monitor." Wave 2 Summary Report, Keig & Company, August, 1995, Sydney.
FIGURE 5. New Media & Technology Interest Over Time
The ABS reported that in February 1994, 2.9 percent of households used a CD-ROM (Cat. 8128.0) . In Figure 5, we see that CD-ROM ownership rose from 6 percent in February 1995 to 10 percent of housholds by August that year. This is perhaps not surprising given that the ABS reported that 62 percent of households where a computer was frequently used saw computer games in use, compared with a 10 percent level for communications software. Most computers were used to run wordprocessor software - 73.9 percent. (ABS Cat. 8128.0)
The diffusion study is a longtitudinal study carried out in two phases - one in 1995 and the other in 1996. This paper reports on the first phase entailing a mail survey of 146 Australian and New Zealand educators in the higher education sector who make the decision, or influence the decision, to adopt textbooks and other educational materials. The questionnaires in the first phase were posted in two waves, during February-March and May-June, 1995, to 750 educators in Chemistry (representing the Physical Sciences), Marketing (representing Commerce) and Psychology (representing the Humanities). A commercial database was used to identify the educators in question. Complete responses were received from 145 or 19.3 percent of the population surveyed.
The survey sought to identify usage, both at work and elsewhere, of 32 technologies:
Because respondents were required to use memory in recording usage, particularly of older technologies, they were asked to specify the year they started to use each technology as well as the year they stopped using a particular technology. This provided a form of validation. Additionally, respondents were asked to indicated their usage levels, ranging from weekly through monthly, quarterly and annual usage. A technology usage score was developed for each respondent using these two variables.
Respondents were also asked their usage patterns of various software applications:
Lastly, educators were asked to provide details of how their students currently used information technology and whether or not they might recommend student adoption of the following items:
It might be expected that the respondents to this survey would be those one might regard as the heavy users of the information technologies mentioned. That is, one might expect a bias toward those favouring use of these technologies. Given the earlier mentioned diffusion of information technology among housholds in Australia, and given the head start that educators might be presumed to have in using such technologies, the following results are disturbing.
Table 1. Educator Usage of Information Technologies
Table 1 illustrates educator information technology usage patterns at work. Usage of these technologies away from work was monitored, however this information is not presented in this paper. More than half the educators surveyed use technologies associated with classroom presentations: Colour TV, VCR and, Overhead Projector. Almost half the educators have used IBM PCs for over five years, with almost an equal number having used Mini or Mainframe computers for more than three years. This indicates that educators were using computers at work earlier than Australian households, based on ABS data (23 percent at February, 1994 - Cat. 8128.0). Almost half of those surveyed are connected to a local area network (LAN), and some 60 percent use electronic mail (E-mail). This is higher than household access of the Internet reported in Keig & Company's August 1995 study (7 percent at February, 1995 and 11 percent at August, 1995). The traditional teaching tools have been in use for over five years, but new technologies are a more recent adoption - less than one year of usage for most respondents. Interestingly, CD-ROM usage at work (17.9 percent) is only slightly higher than houshold usage reported by the Keig & Company study (9 percent at February, 1995 and 15 percent at August, 1995).
Table 2 indicates that 40 percent of educators have recently adopted a graphical user interface such as Windows at their work location, with half of the respondents using wordprocessing applications and spreadsheet applications for more than five years. World Wide Web (WWW) usage by educators was only 11 percent at mid-1995, the same level of adoption as reported for Australian households. Household awareness of the Internet (WWW) stood at 81 percent (Keig, 1995, p3.). Householders indicated they were quite or very likely to purchase computers (20 percent) and modems (13 percent) within the next 12 months, thus signalling that diffusion of WWW usage is likely to proceed unabated. (Keig, 1995 p.6.) Importantly for educators, 58 percent of computer owners or those planning to buy in the next twelve months were very or quite interested in educational usage of their computer (Keig, 1995 p.18.).
Table 2. Educator Usage of Software Applications
As indicated earlier, the study did not seek to establish whether educators used the technologies for research or publication purposes. However, it is clear that educators in the higher education sector are not using information technology to the fullest advantage in their teaching role. Table 3 sets forth educators' perceptions of computer usage by their students. It would be true to say that almost half the respondent educators are unaware of their students' use of information technology. Where they have responded positively it is evident that most of their students do not use information technology with the possible exception of spreadsheets (25 percent student usage reported).
Table 3. Student Use of Computers (as nominated by educators)
When looking to future educator usage of information technology in Table 4, it is evident that educators in the higher education sector in mid-1995, were not planning to use information technology tools to the fullest extent possible. For example, over 75 percent could not foresee usage of CD-ROM based textbooks by their students. In contrast, almost all educators preferred traditional paper-based textbooks. Some 38 percent saw their students using electronic access of libraries. It is not clear whether this meant accessing electronic catalogues in libraries, or via remote access using a computer and modem and the public subscriber telephone network (PSTN). The forecast lack of CD-ROM usage has implications for the Federal Government's Cooperative Multimedia Centre funding to seed development of the CD-ROM industry in Australia. Over 40 percent of respondents saw themselves as unlikely or never to recommend usage of the WWW by their students.
Table 4. Educator Recommendation: Adoption of Specified Technologies
Turning to the Technology Usage Rating (TUR) developed for each repondent, a composite technology score was created using the two earlier mentioned variables - length and frequency of use of information technology. (See Figure 6.) In deriving this rating, the length of use was multiplied by the frequency of use and converted to a total score in weeks. The technology score shown in Figure 6 shows a histogram of the TURs so derived. It can be seen that the distribution approaches a normal distribution with a mean of 3000 and a standard deviation of 1200. This means that on average educators used their combined technologies for 3000 weeks. To illustrate, if a respondent uses a technology for 20 years on a weekly basis, their TUR would be 20 times 50 or 1000 weeks. Thus the average TUR of 3000 suggests that educators use approximately three technologies on a weekly basis at work. The hypothesis was that the higher the TUR, the greater the liklihood that an educator would recommend usage of information technology adoption by their students. Cross-tabulations of Table 4 with TURs however fail to support this hypothesis. Chi-Square tests for each technology and TUR were not significant.
Figure 6. Technology Usage Rating (TUR)
The TUR consisted of all 32 technologies listed earlier. A refined TUR (RTUR) measuring only computer usage and WWW usage is shown in Figure 7. It can be seen that the WWW scores are generally low with most educators not having a score at that time. Cross-tabulations of Figure 7 indicate that RTUR discriminated for the following recommendations: Textbooks on CD-ROM / CD-I, Case Studies on CD-ROM / CD-I, Electronic communications hardware or software that allows student access to e-mail, the WWW and educational materials held in libraries and media resource centres. That is, those educators with a high rating derived from computer and related technologies (RTUR) are more likely to recommend that their students adopt the specific information technologies mentioned in their studies.
This study is part of a longitudinal survey of information technology adoption and diffusion among educators in higher education. Phase 2 is to proceed in mid-1996 and to survey the same population of educators. The rapid adoption of technologies necessitates that more than one snapshot is taken and accordingly, another survey will be conducted. Based on the results of the second survey, several cases will be developed of individual educators and their usage patterns will be investigated in detail, so as to better understand the nature of the diffusion of technological innovations in higher education.
Although Australian educators adopted information technology earlier than the broader community, they are not planning to use these technologies in the future in their teaching. They may well be using said technology in research and publishing the results of this research. This inference is drawn from the fact that of the 95 percent of educators who use computers, 90 percent use a wordprocessor application. While institutions may well be developing open learning and off-campus programs that utilise the converging technologies referred to by Adam (1995), individual educators seem to be laggards in their planned adoption of information technologies in the classroom. The study confirms the existence of a "bandwagon effect" as reported by Mansfield - as more educators learn to use the Internet and WWW, they stimulate diffusion of the technologies thus causing others to follow. A comparison of the results of the Keig household survey results with the educator technology usage study indicates that the former have adopted computers, modems, CD-ROMs and internet beyond the level of planned usage in teaching by educators in the higher education sector.
Adam, S., 1993, Using a DOS based Micro Computer. 2nd edition, Fontech, Melbourne, p.6.
Australian Bureau of Statistics (ABS), 1994 "Household Use of Information Technology." Commonwealth of Australia, Canberra.
Brenchley, F., 1996 "Mergers & Marriages - the new global giants." The Australian Financial Review. (January 8):p.9.
Chen, A., 1990 "The Incredible Shrinking Transistors." Microcomputer Solutions, Intel Corp., Santa Clara, Cal., (Sept/Oct).
Encarta 95, 1994, "Industrial Revolution." Microsoft Corporation and Funk & Wagnalls Corporation
Engel, J.F., Blackwell, R.D., and Miniard, P.W., 1993 Consumer Behaviour. Seventh edition, The Dryden Press, Florida.
Frambach, R.T., 1993 "An Integrated Model of Organizational Adoption and Diffusion of Innovations." European Journal of Marketing, Vol. 27, No. 5, pp.22-41.
Freeman C. and Perez, C., 1988, Structural Crises of Adjustment, Business Cycles and Investment Behaviour, in Dosi, G., Freeman, C., Nelson, R., Silverberg, G., and Soete, L., 1988, "Technological Change and Economic Theory," Pinter, London, Summary of Section on Keynes and on Samuelson.
Huff, S.L. and McNaughton, J., 1991 "Diffusion of an Information Technology Innovation." Business Quarterly, Vol. 56, No. 1, (Summer): pp.25-30.
"The New Media and Technology Monitor." Keig and Company, Wave 2 Summary Report, August 1995, Sydney.
Lane, P., 1978, The Industrial Revolution: The Birth of the Modern Age. Barnes and Noble Publishers, London.
Port, O., Gross, N., Gross, N., Hof, R., Brandt, R., Burrows, P., and McWilliams, G., 1994 "Wonder Chips." Business Week, (July 4): pp.46-52.
Robertson, T.S., 1967 "The Process of Innovation and the Diffusion of Innovation." Journal of Marketing, Vol. 31. (January):pp.14-19.
Rogers, E.M., 1995 Diffusion of Innovations. 4th edition, The Free Press-Macmillan, New York.
Rubel, C., 1996 "CD-ROM takes a back seat to other tools." Advertising Age, Jan 15: p.10.
HREF 1. http://www.Toyota.com - Toyota's home location.
HREF 2. http://www.scu.edu.au/ausweb95/papers/publishing/adam/ -The SCU home location for Adam, S., (1995) "Distributed Higher Education: Strategic Alliances in Hypemedia Publishing." AUSWEB95, Southern Cross University, Lismore. Also see http://www.bf.rmit.edu.au/~stewarta/disthed3.html for an update done for Campus Review, February, 1996.
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