Proulx and Campbell – The Professional Practices of Faculty and the Diffusion of Computer Technologies in University Teaching

Michelle Proulx Department of Sociology McMaster University Hamilton, Ontario. Canada

[email protected]

Brian Campbell Department of Sociology and Anthropology Mount Allison University Sackville, New Brunswick. Canada

[email protected]

© 1997 Electronic Journal of Sociology

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Abstract

The adoption of computer assisted learning technologies in higher education must be understood in relation to the overall use of computers by university faculty. While computer use by faculty in higher education has become widespread, there has not been wide diffusion of computers in teaching. It is not clear whether the present minority of faculty using computers as a teaching technology are really a set of early adopters, as one would expect as part of a general diffusion model. Computer use in teaching depends upon faculty whose computer-based research and analytical needs lead them to be accomplished computer users. Since few low level computer users apply computers to teaching, computer assisted learning may have little internal momentum and may remain a spinoff of the high level of computer use attained by some academics in other areas of their professional activities. The analysis is based on a survey of faculty adoption of computer technology at a Canadian university. Consideration is given as to whether these findings are restricted to a particular stage in the development of computer assisted learning technologies, or of computers in general academic practice.

After decades of computer use the diffusion of computers into university teaching remains largely a promise. There has been widespread computerization throughout universities, and there are some interesting examples of the application of computer technologies to university instruction. But computer assisted pedagogy is not commonplace, and it is perhaps not clear to what extent computers will ultimately affect instruction.

We develop our perspective on the diffusion of technology into university teaching from within a sociological framework. As such we emphasize education as a locus for interaction. The dominant approach in the study of educational technologies has been to concentrate on teaching and learning activities as discrete isolatable phenomena. Few attempts, if any, have earnestly considered how these technologies are related beyond the scope of teaching to the immediate social context. This context, for the purposes of technology diffusion, is constituted by the interactional patterns in relation to teaching and technology in the social and cultural environment of faculty and students.

By broadening teaching and technology to the social setting of teaching and technological practice we do not intend to reduce the analysis to the macro actors of large social structures like class or corporate capitalism, at least not directly. In our study of the diffusion of computing technology into the teaching practices of university instructors, we have examined one aspect of this broader immediate context; that is, the overall ways in which computing is used by faculty, and the priorities that are attached to these uses. We argue that computing in university teaching is relatively uncommon, and further situate teaching with computers as dependent on high level computer use which is in turn an outgrowth of academic professional demands.

Low Levels of Computer Use in Teaching

Teaching with computers is not a mainstream activity. In general, the research on the diffusion of computer technologies into teaching has shown a low level of adoption. Estimates of computing use for instruction indicate that it is a minority practice. Faseyitan and Hirschbuhl (1992: 188) record 31% of faculty using computers in the classrooms of six Ohio universities. Mackowiak (1991) submits that 46.4% of faculty from a Washington, DC liberal arts university have used computers in at least one or more of their courses. In a more recent American national survey (Geoghegan, 1994) as few as 5% of faculty use computers as active teaching tools.

Geoghegan (1994) describes how computers in teaching have primarily been used to print handouts or for preparing overhead transparencies. Such “logistical” use has been but an extension of the blackboard and typewriter. There has been little application of computers for developing and assisting with explanation, illustration, access, analysis or synthesis of information.

There is a great deal of difficulty with precise comparisons in this research since it is not clear what counts as the application of computer technologies to education. Geoghegan has a restrictive definition which includes computer interactivity and communication tools, while excluding “logistical” computer use such as the preparation of handouts. Others, with higher estimates appear to have broader definitions. But overall these variations are slight. It is always a minority who adapt computing to teaching. Consistently, these findings and observations suggest a low level of computer use for instructional purposes.

Computers in Teaching as a Technology Diffusion Problem

We have conceived of the study of teaching and computing as an issue within both the sociology of education and the sociology of technology. In turning to technology, the study of the use of computers in teaching is a problem of technology diffusion.

The work of Everett Rogers (1983) is almost always invoked in discussing technology diffusion. One of Rogers’ contributions is a model of diffusion which looks like a bell curve. The front end of the curve has two types of technology adopters/users in the first 15% which he calls innovators and the early adopters. The middle 70% of adopters are referred to as the mainstream or majority which are divided into the early majority and the late majority. The final 15% are referred to as laggards. The entire scheme is teleological, since it is not possible to know where any person is on the continuum until the diffusion of the technology has run its course. Today’s innovator could be tomorrow’s laggard, if it turns out that the innovator was part of the last 15% of the adopting population.

These problems aside, Geoghegan has taken this diffusion model and has argued that teaching technologies have been stuck in this lead 15% of the entire population of teaching faculty. Geoghegan’s argument is that instructional computing technologies are stuck in a group of highly technically literate faculty and have not broken out into the mainstream. We will examine this assertion in our analysis.

The Study: Mount Allison University Faculty

Our findings are based on a survey conducted at Mount Allison University, Sackville, New Brunswick during the fall of 1994. [1] Seventy-one of the returned questionnaires were considered to be valid. Despite efforts to address all faculty, whether they used computers or not, the responses clearly tended to come from those faculty who had adopted the use of computer technology to some degree.

Mount Allison is an undergraduate liberal arts university which has been investing heavily in information technologies. In recent years Mount Allison has networked all classrooms, offices, residences and campus buildings. The university has also tapped provincial support for developing courseware and distance education. The facilities offered by this site have provided a setting which includes both those faculty who are dedicated to new technologies, as well as those faculty who are settled in more traditional academic patterns. This contrast in professional styles helps to frame the analysis of levels of computer use which we develop below.

Computer User Levels

In this paper we examine the diffusion of computer technologies into the educational practices of university faculty. In doing this we argue that there are considerable differences between high end users and others in their application of computer technology to teaching. The first methodological question then is who is a high end user.

We have developed a measure of relative computer use among faculty (Table 1) by dividing faculty into three categories of low, medium and high use. These levels are based on a combination of faculty’s self-assessments of computer expertise and self-reports of the amount of time spent using computers. Faculty rated their abilities as novice, basic, experienced, or advanced. On time-use, faculty indicated the amount of time per week that they used a computer. This time factor was recoded to include three categories of computer use: up to 10 hours, 11 to 20 hours, and over 20 hours. High users were those faculty who claimed to be advanced in their computer use, or who stated that they were experienced and used a computer more than 20 hours per week. Low users were those who used a computer less than 10 hours per week and referred to themselves as having novice or basic skills. Medium computer users were those in between. By thi s measure we divided 65 faculty into 17 high users, 23 medium, and 25 low users.

Table 1: Weekly Hours of Computer Use by Level of Self Assessment

Novice

Basic

Experienced

Advanced

Row Total

1-10

7
100.0%

18
64.3%

4
15.4%

29
44.6%

11-20

7
25.0%

9
34.6%

1
25.0%

17
26.2%

20+

3
10.7%

13
50.0%

3
75.0%

19
29.2%

Column
Total

7
10.8%

28
43.1%

26
40.0%

4
6.2%

65
100.0%

Number of Missing Observations: 6

Data Category Legend:

Low User Medium User High User

The General Diffusion of Computing Technologies

Almost all of the respondents to the questionnaire are dependent on computers. Respondents were asked the question “If you did not keep up with changes in computer technologies would you feel at a loss?”. The answers to this question are displayed in Table 2. Although there is a clear difference among user levels, even 72% of low users stated that they would feel at a loss without their computer.

Table 2: Feelings Toward Computers by Type of Computer User

Type of User

Answers to the question: If you did not keep up with changes in computer technologies would you feel at a loss?

Low

Middle

High

Row Total

Yes

18
72.0%

21
91.3%

17
100.0%

56
86.2%

No

7
28.0%

2
8.7%

9
13.8%

Column
Total

25
38.5%

23
35.4%

17
26.2%

65
100.0%

Number of Missing Observations: 6

It appears that some form of computer use has become almost universal among university faculty. We can see this pattern further in Table 3 which indicates where faculty use computers. There is a consistently high level of computer use at home and at the office. Interestingly, in the case of low users there are more faculty who use computers at home than at the office, although the differences are extremely small. Clearly, computer use is widespread.

Table 3: Locations of Computer Use by Type of Computer User

Type of User

Answers to the question: Where do you use computers?

Low

Middle

High

Row Total

At Home

22
88.0%

22
95.7%

16
94.1%

60
92.3%

At the Office

20
80.0%

22
95.7%

17
100.0%

59
90.8%

In Campus Labs

5
20.0%

5
21.7%

10
58.8%

20
30.8%

Column
Total

25
38.5%

23
35.4%

17
26.2%

65
100.0%

Percents and totals based on respondents
65 valid cases; 6 missing cases

The differences between types of users starts to become clearer when we consider the application of computers. Table 4 shows a list of various computer applications. The question was “For what purposes do you use computers?” and respondents were given a list of purposes.

Some trends are clear. High computer users are more likely to use every type of application listed. The only exception to this is the item “For amusement” where both medium and low users were more likely to indicate this application. Perhaps the intensive time commitment to computer applications on the part of high end users reduces the allure of computing as an amusement. The top applications overall are word processing (96.9%) and personal computer use (90.8%). The text in the question beside this latter entry included the sample list (letters, notebook, calendar, forms, etc.). Close behind these two applications was email (87.7%). In terms of an individual application email has become almost as common as word processing.

Differences in computer usage start to show when we consider other types of applications. Newsgroups, a slightly more complicated form of collective email, showed great differences among user levels ranging from 64.7% for high users down to 4% for low users. The quantitative uses of data-processing and spreadsheets also showed great differences. But this range of difference was not merely an expression of quantitative skills since networking and information retrieval, including library catalog use, also showed great differences. High level computer users use computers across a broad range of activities. For them computers are a polymorphous technology which can be applied and adapted to many tasks. In contrast, the other users concentrate on the quasi-clerical applications of word processing and email.

Table 4: Purposes of Computer Use by Type of Computer User

Type of User

Answers to the question: For what purposes do you use computers?

Low

Middle

High

Row Total

Word processing

23
92.0%

23
100.0%

17
100.0%

63
96.9%

Personal (letters, notebook, calendar, forms etc.)

20
80.0%

22
95.7%

17
100.0%

59
90.8%

E-mail

18
72.0%

22
95.7%

17
100.0%

57
87.7%

Course materials (handouts, syllabuses, overheads)

15
60.0%

23
100.0%

17
100.0%

55
84.6%

To assist academic research

16
64.0%

19.0
82.6%

15
88.2%

50
76.9%

Library catalogue

14
56.0%

14
60.9%

15
88.2%

43
66.2%

Data-processing

12
48.0%

15
65.2%

15
88.2%

42
64.6%

To develop instructional materials

7
28.0%

17
73.9%

16
94.1%

40
61.5%

Spreadsheets

7
28.0%

16
69.6%

15
88.2%

38
58.5%

Networking

8
32.0%

16
69.6%

13
76.5%

37
56.9%

Gopher system

4
16.0%

13
56.5%

15
58.2%

32
49.2%

Newsgroups

1
4.0%

13
56.5%

11
64.7%

25
38.5%

For amusement

5
20.0%

9
39.1%

3
17.6%

17
26.2%

To make or modify software

1
4.0%

2
8.7%

6
35.3%

9
13.8%

Other

1
4.0%

2
8.7%

1
5.9%

4
6.2%

Column
Total

25
38.5%

23
35.4%

17
26.2%

65
100.0%

Percents and totals based on respondents
65 valid cases; 6 missing cases

The items with specific reference to teaching applications further accentuate the differences among user categories. The course materials item (handouts, syllabuses, overheads) was very high overall (84.9%). All of the High and Medium users claim this use, along with 60% of Low users. However, this level of computer use for teaching is only at the level of a support function, and is perhaps best seen as a consequence of the automation of clerical office work. This is consistent with Geoghegan’s (1994) findings which reveal these logistical uses of computers as the predominant teaching aid. The other teaching related item on the application list separates out the user levels to a greater extent. The item “To develop instructional materials” had all but one of the High users (94.1%), most of the Medium Users (73.9%), and few of the Low Users (28%). There is ambiguity in this item since it could be read as a more elaborate clerical and presentation preparation for tradi tional classes, although it may also include instructional aids such as newsgroups. A high proportion of High Users (64.7%) claim newsgroup use, as compared to 4% for Low Users. Insofar as newsgroups are used in education this may indicate a further difference between different levels of users.

Overall, when we consider applications, we can see that computing technologies have diffused widely throughout this faculty population. However, broad diffusion is in the area of clerical support through word processing and in the newer area of electronic mail. High Users stand out in terms of their use of computers across a broad range of applications. For them computing is a polymorphous technology with many applications. Low Users have a far more restricted set of uses for computers. When we consider education more carefully we can see that the application of computers is not as wide-spread.

We asked faculty how important computers were to several areas of activity: teaching, research, administration, and personal. Table 5 shows the percentages of faculty who indicated any of these areas as very important. This has been combined with a category for anyone who failed to mention any of these areas as very important. The differences in levels of use are clear in this table. None of the High Users and only 1 Medium User, in contrast to 40% of the Low Users, listed the use of computers as not very important. The trend for High Users not to be the highest on personal use shows up again with this measure with Medium Users as the highest group. Interestingly personal uses were the second highest category, behind research, for Low Users. The importance of computers to research was the highest category for all levels of users. However, here we can see strong differences again among levels of users with 100% of High Users , 82.6% of Medium Users, and 48% of Low Users selecting very important for research.

The present use of computers in teaching is an outgrowth of high end computer practices. In fact High Users are the only user category with teaching as the second highest rating, and the only user category where teaching use of computers was seen as important by more than half of the respondents in a category. At 88.2%, High Users are almost unanimous in their selection of teaching as important. It is likely that many of these faculty actually teach some aspect of computer applications in their courses.

Although almost all faculty use computers for the auxiliary production of class materials, this is not a central aspect of the teaching enterprise for most. Another way to look at this is in relation to the Low Users. A central reliance on computers in teaching is almost unknown by the casual computer user. Teaching is a spin-off from high end intensive computer use. Teaching with computers enjoys virtually no autonomy. It is dependent on the development of computer use in other areas.

Table 5: Areas of Computer Use by Type of Computer User

Type of User

Answers to the question: How important are computers for you in the following areas?

Low

Middle

High

Row Total

Research

12
48.0%

19
82.6%

17
100.0%

48
73.8%

Teaching

3
12.0%

10
43.5%

15
88.2%

28
43.1%

Administration

6
24.0%

10
43.5%

10
58.8%

26
40.0%

Personal

7
28.0%

11
47.8%

7
41.2%

25
38.5%

Not very important

10
40.0%

1
4.3%

0
0.0%

11
16.9%

Column
Total

25
38.5%

23
35.4%

17
26.2%

65
100.0%

Percents and totals based on respondents
65 valid cases; 6 missing cases

Another measure of the importance of computers to teaching comes from the question “In relation to your own teaching, do you see computer technologies as: Supplementing the way you have traditionally delivered some courses, Significantly altering the way you have delivered some courses, or Replacing your involvement in the delivery of some courses”. The results of this question are indicated in Table 6. We have included a fourth category for any faculty member who did not indicate any of these broad types of effects as “No educational effects”. It is interesting that this is a forward looking question. It is not necessary for faculty to have implemented or experienced the changes listed. The overwhelming answer from all levels of users was for computers to supplement courses. Although we do not have the data to list specific supplemental activities, it is conceivable that email, newsgroups, computer assisted assignments, and tutorials could be part of this. Logically, those faculty who aggressively use these supplements may alter their courses to take advantage of them, thus the second most popular answer. However, only the High Users have a majority who have identified computer technologies as altering their courses. As might be expected there is a very strong rejection of the replacement of faculty members. It is plausible that this finding is influenc ed by the self-interest of faculty to be closely involved in the teaching process. At the same time, it is intriguing that small numbers of Medium and Low Users agreed with this statement while there was no such response from High Users. Perhaps familiarity with the complexity of the application of computer technologies to teaching may underpin such variance in user response.

Table 6: Perceived Effect of Computers in One’s Courses by Type of Computer User

Type of User

Answers to the question: In relation to your own teaching, do you see computer technologies as:

Low

Middle

High

Row Total

Supplementing the way you have traditionally delivered some courses?

17
68.0%

22
95.7%

16
94.1%

55
84.6%

Significantly altering the way you have delivered some courses?

7
28.0%

7
30.4%

10
58.8%

24
36.9%

Replacing your involvement in the delivery of some courses?

2
8.0%

2
8.7%

0
0.0%

4
6.2%

No educational effects

7
28.0%

1
4.3%

1
5.9%

9
13.8%

Column
Total

25
38.5%

23
35.4%

17
26.2%

65
100.0%

Percents and totals based on respondents
65 valid cases; 6 missing cases

Why Faculty Use Computers

One of the ways to appreciate the application of computer technologies in education is to consider the reasons faculty initially adopt computer technologies. The main forces for adoption have been from within the professional disciplinary context of faculty. The extent to which faculty agree with the statement that computers “…are necessary for your discipline” is displayed in Table 7. Here we can see marked differences among user levels. The disciplinary requirements of faculty are clearly far more important to High Users. There is a chain of events with the professional demands on faculty including research requiring computers. This together with the general importance of computers for clerical and communications functions reinforces the High User who extends the application of computers into education.

Table 7: Necessity of Computers For One’s Discipline by Type of Computer User

Type of User

Answers to the question: To what extent do you agree or disagree with the statement that computers are necessary for your discipline?

Low

Middle

High

Row Total

Strongly Agree

4
17.4%

10
43.5%

13
81.3%

27
43.5%

Agree

11
47.8%

10
43.5%

3
18.8%

24
38.7%

Neutral

4
17.4%

3
13.0%

7
11.3%

Disagree

3
13.0%

Strongly Disagree

1
4.3%

Column
Total

23
37.1%

23
37.1%

16
25.8%

62
100.0%

Number of Missing Observations: 9

The importance of the professional demands on faculty is also clearly evident in the answers to the question “Why did you begin working with computers?” The answers are displayed in Table 8. “For professional demands” was by far the most popular selection. Overall, 80% of respondents indicated professional demands as important, with little separating user levels (High 88.2%, Medium 82.6%, and Low 72.0%). The answer “Thought it would be interesting” was the distant and clear second most likely answer with 41.5% overall, again with little user level differentiation (High 47.1%, Medium 43.5%, Low 36%). High Users selected “For instructional purposes” as their third reason (29.4%), while Low and Medium Users listed the answer “Was available for use as their third choice. These results provide further indication to the pattern of computer adoption whereby the penetration of computer technologies into teaching has been secondary to othe r professional applications by each of the three groups of users. The organizational demands and support answers, “Pressure from the university” and “Assistance was available” received the least attention. Again, the professional push for faculty, rather than other factors, in this case the organizational climate of the university, has encouraged the development of computer skills.

Table 8: Reasons for Beginning Computer Use by Type of Computer User

Type of User

Answers to the question: Why did you begin working with computers?

Low

Middle

High

Row Total

For professional demands

18
72.0%

19
82.3%

15
88.2%

52
80.0%

Thought it would be interesting

9
36.0%

10
43.5%

8
47.1%

27
41.5%

Was available for use

6
24.0%

9
39.1%

3
17.6%

18
27.7%

For instructional purposes

3
12.0%

6
26.1%

5
29.4%

14
21.5%

Assistance was available

3
12.0%

3
13.0%

2
11.8%

8
12.3%

Other

5
20.0%

2
8.7%

1
5.9%

8
12.3%

Pressure from the university

1
4.0%

1
4.3%

1
5.9%

3
4.6%

Column
Total

25
38.5%

23
35.4%

17
26.2%

65
100.0%

Percents and totals based on respondents
65 valid cases; 6 missing cases

For High Users computers are a disciplinary imperative. This does not mean that high end computer use is monopolized by certain disciplines. Table 9 shows level of use by discipline. There is a tendency for science and social science faculty to be higher users. However, there is considerable variation within disciplinary groups. It seems likely that some disciplines may be more likely to use computers for specific aspects of instruction. For example, programming, statistical applications, or data analysis are more likely to be used in the sciences and social sciences.

Table 9: Faculty by Type of Computer User

Type of User

Answers to the question: You are a member of which faculty?

Low

Middle

High

Row Total

Science

8
33.3%

6
27.3%

9
52.9%

23
36.5

Social Science

4
16.7%

9
40.9%

7
41.2%

20
31.7%

Arts and Letters

9
37.5%

5
22.7%

1
5.9%

15
23.8%

Humanities

3
12.5%

2
9.1%

0
0%

5
7.9%

Column
Total

24
38.1%

22
34.9%

17
27.0%

63
100.0%

Number of Missing Observations: 8

Conclusions: Practice, Skill, Commitment, Mainstreaming, and Incrementalism in the Diffusion of Computer Technologies in University Teaching

The immediate social context for university faculty in the diffusion of computer technology into university teaching extends beyond the classroom into their general professional practices. We have shown that the use of computers for instruction is less common than their use throughout the professional practices of faculty; virtually all faculty use computer technologies for some tasks, but not necessarily as pedagogical tools. Most commonly, faculty use word-processing and electronic mail. Where computers are found in the classroom they are often applied by faculty for logistical, clerical, and preparatory support. Those faculty who extensively apply computers to teaching tend to have a strong set of computer skills and carry these into their teaching practices. These skills flow from the demands of academic professionalism in the traditional computing areas of word processing, image processing, data handling, and networking. Furthermore, unlike some other teaching tech nologies (such as chalk, slides, and video), the more interactive uses of computer technologies for teaching (such as the development of computer-assisted instruction) are dependent on a broad set of commitments to working with computers. Within the time frame of our study we can see computer use as a spinoff of the computerization of the general world of the faculty member. Faculty have not tradit ionally begun using computers solely for teaching. Computing is a generalized technology which is applied to teaching. There are no faculty who only use computers for teaching. On the other hand, there are many faculty who use other technologies such as chalk, slides, video, and video conferencing for teaching alone. The implementation of computing technology into university teaching is not an isolatable phenomenon. Rather, it has depended on the broad adoption of computing. It remains to be seen whether this pattern for computing teaching technologies changes as time goes on, or whether the trends that we see at this one institution are followed at others.

However, the future may see more of the same. The present pattern is one where generalized high commitment computing translates into educational application. A simple extrapolation of this dynamic into the future would suggest that if high commitment computing becomes more common among university faculty then it will be more frequently applied to teaching. But that depends on whether educational computing maintains its present dependencies. A mainstreaming of high commitment computing across academic life may be affected by increased professional pressures to adopt computing for a range of tasks. In the future it may be increasingly difficult for faculty to do without email, electronic search engines, web browsing, camera ready manuscript preparation, and other computer technologies. In addition, the present pattern of a restricted group of high end users as computing educators may also depend to some extent on the technical difficulty of many computer applications. I f computing technologies become easier to use then this may affect the extent to which high commitment computing becomes mainstream, and consequently affect current patterns of computer adoption into teaching .

The effects of computer use patterns outside of the classroom on teaching with computers may not simply be a reflection of overall computer commitment and skill. There could be links to specific uses of computers. For example, the teaching of data analysis in its various forms can be a direct extension of professional uses into teaching about, and often with, computing in the classroom. This crossover computer use between research and teaching can be a springboard for teaching applications. There is some evidence for this in our findings with those who use computers for data analysis also being more likely to be high end users and thus more likely to use computers in teaching. Other broadly diffused technologies may also pave the way for analogous teaching applications. It is likely that widely adopted computing technologies like email and other computer based messaging may become a significant form of communication in teaching because they have permeated the practica l da y to day life of many university faculty. Recent findings from the United States suggest that this may already be happening there. (Green, 1996) Finally, the university support infrastructure may be a factor in the diffusion of skills and practices in some instances. Faculty in this survey indicated little or no importance for university support for any aspect of their computing. But at this particular university in this study there has not been a comprehensive computing or teaching technology support infrastructure. Such institutional supports may provide another avenue for the diffusion of teaching technologies. Or perhaps highly skilled and committed computer users may disproportionately avail themselves of such services, thus preserving the relationships we have identified (Geoghegan, 1994).

Aside from mainstreaming high commitment and its spinoff effect on educational practices, and the link between particular broader professional uses of computers and their educational adaptations, there are other factors which may also more directly encourage computer mediated teaching applications. There may be direct effects on teaching if there are teaching technologies which are easy to use. If some new technologies can be easily learned and applied in teaching, then, as with chalk and overhead projection, they may become part of the classroom setting more readily than others. This is most likely with various forms of communication technologies such as video conferencing which could be easy to use insofar as they are extensions of the telephone and the television. In addition, new technologies which are close analogues to existing teaching practices may also penetrate pedagogy more easily since they may not require a paradigm shift. We may be seeing an incrementalis t pr inciple operating in the extension and development of computer applications. For example, the LCD overhead has a strong analogy in the acetate overhead, and in the slide projector. The computerization of these presentation technologies may have a large impact on teaching in traditional classroom settings if they do not involve a significant shift in existing practices.

In understanding the application of computing technology in education we must open the context of analysis to the wider social world of faculty practice, rather than restricting the analysis to teaching activity. In looking to the future it would seem that the widespread entry of computing technology into university teaching will depend on the patterns of adoption across a broad range of practical actions of university faculty. One of the themes associated with the possibility of the widespread development of the use of computers in education is that the classroom will be de-emphasized and transformed. Self-paced and cooperative learning strategies may broaden education beyond the confines of the classroom. It is a paradox that the present introduction of the concept of the de-emphasis on the classroom might re-sensitize us to the analysis of the existing relationships between the classroom and the immediate social environment. One of the lessons of sociology is that t he characteristics and impact of education are highly dependent on the social envi ronment, however that might be most appropriately conceived. For example, when studying student experiences of education we have learned the lesson that the classroom is not the limit of the immediate social environment. Who students are affects how they process information. Similarly when studying teacher and faculty experiences in their relationship to technology we should not be limited by the classroom and a narrow view of teaching practice.

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[1] The questionnaire was developed as part of a thesis on technology diffusion in higher-education which focused on the dynamics of computer use by university faculty (see Proulx, 1995).

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