The term network communications as used in this study is similar to the research area known as computer-mediated communications. One of the common results of studies in educational reform as well as in computer mediated communications is the recognition that implementation is a lengthy and time-consuming process (Seashore and Miles, 1990; Sproull and Kiesler, 1991). As the combining of computers and networks is relatively new, this area also overlaps with studies of adoption of new technology. In a review of adoption of new technology studies, Cressey and Di Martino (1991) noted a survey of manual workers and shop stewards (Daniel, 1987) in which the perceived nature of change was critical to adoption or resistance. If the innovation was perceived primarily as a technological change, it was adopted. However, if the change was viewed as organizational in nature (e.g., changes in existing statuses), it was resisted, probably because of its likely effect on the reduction in personnel and earnings.
Although there is a significant thread of studies in this area since the turn of this century (as discussed in the following section under organizational change and implementation of innovations), there is a paucity of studies that specifically examine faculty adoption or use of network communications in an educational setting. Nonetheless, some recent studies are worth noting. Key to understanding this innovation is the notion that computer networks are not merely new technology, they are also a new communications medium (McLuhan and Powers, 1992). This represents a change in the way people interact, which is inherently social and organizational (Kranzberg, 1985). It also has potential advantages over traditional communications in that information in this media is malleable, cheap and compact, instantly distributed, and interactive (Katzen, 1982). Giacquinta, Bauer, and Levin (1993) note that home use of computers requires more than a quick technological fix like faster computers, it should include examination of the social context in which the computer technology is introduced and how that envelope can be changed at the time of its introduction to improve the prospects of successful implementation.
The notion that adopters and their environment must change along with the innovation itself during implementation is echoed in much of the adoption and implementation literature (Rogers, 1983; Grønhaug and Kaufmann, 1988). For users with organizational roles that offer greater discretion (such as faculty), Danziger and Kraemer (1986) found that computer use was largely determined by user characteristics and the organizational environment. Kiesler and Sproull (1987) note that slack (discretionary time and resources), expertise (knowledge that is shared among adopters), and zeal (enthusiasm) provided by change agents and early adopters are key environmental ingredients for faculty adoption and use of computer technology. As this study is concerned with use, faculty access to computers and network technology must be a given. Several studies confirm that on most campuses, faculty are provided with computer accounts which give them access not only to network applications, data, and devices, but also to communications applications that let them share information and ideas with each other (Gillespie and Dicaro, 1982; Kiesler and Sproull, 1987). Beyond its proliferation on campuses throughout the world and the increase in faculty use, this new medium has already altered the way that faculty communicate and conduct research (Holden and Wedman, 1993). As the first and most popular form of network communications, e-mail has been the focus of many studies of this medium. As it relies on text-based messages for interpersonal communication, e-mail has reduced social context cues. Yet this attribute has been associated with an increase in the quality and quantity of organizational communications (Sproull and Kiesler, 1986).
A 1985 survey of faculty and students at a university with a national reputation for computer use revealed that 56.8% of the faculty and 49% of the student respondents indicated frequent use of e-mail to communicate (Anderson, 1987). It should be noted that unlike traditional communications such as the postal system where almost everyone has a mailing address, e-mail can only reach someone who shares access to the same (inter)network (Baker, 1994). Markus (1987) points out that there is a “critical mass” that exists for the successful implementation of e-mail technology that is similar to the two decades of increasing use before fax technology took hold. Essentially, there must be a critical amount of people using it before there is an increase in the frequency of use on a per-person basis. This may explain in part why implementation of this and similar network communications is such a lengthy process. Nonetheless, e-mail has taken hold in academic and industrial research settings. One study showed that collaborative research is the primary reason for using e-mail in these settings and that 78% of university faculty used e-mail for joint collaboration with colleagues at other institutions (D’Souza, 1992). Cronin (1994) cites a 1993 survey of Internet users in the chemical field in which more than 50% of the respondents identified e-mail as their primary network communications activity. Of note is the fact that one-third of respondents listed research collaboration as their primary reason for using the Internet.
Network services extend beyond e-mail between individuals to accommodate more extensive means of communications, including equivalents of broadcasting, publishing, and database functions. For example, Internet “newsgroups” provide an online equivalent to group meetings or conferences. Mailing lists (listservs) provide a diverse range of informational equivalents of broadcast transmissions and/or mass mailings of periodicals based on voluntary subscription by users. Network communications also offer an equivalent to “real time” communications in the form a of a “chat mode” for text and videoconferencing for audio and video communications as the equivalents of phone or face-to-face communications. Online publication is also available through the World Wide Web (on the Internet). Users can navigate through online multimedia information (text, graphics, animation, sound, and/or video) that contain links to related documents in “hypermedia” format. With the ability to link to functions such as teleconferencing and video, network multimedia applications such as the World Wide Web can provide a medium for interactive collaborative research, distance learning, and other scholarly applications (Woo and Rees, 1994; Frivold, Lang, and Fong, 1994; Mayer-Kress, Bender, and Bazik, 1994; Dybvik and Lie, 1994; Meyer, Blair, and Hader, 1994).
In a book based on a survey of faculty activity preferences, Bess (1982) characterizes the dearth of research on faculty by quoting John W. Gardner: “Education is to professors as water is to goldfish. They swim in it but never think to study it.” Bess acknowledges several reasons why the academic department bears such a primary influence on faculty role and performance. For example, the reward system is based on a quantifiable aspect of performance, which in the case of research can be measured by publication output. Access to funding also relates to research performance. In his review of the literature on faculty productivity, David Dill (1986) states that although colleges and universities are organizational settings where research is regularly conducted, academic researchers represent a special sample of the overall research population in that they must conduct research in conjunction with the other activities of teaching and service.
This review also notes the ascendance (since World War II) of academic researchers and scholars to prominence in the field of higher education, including the active recruitment and rewarding of faculty who actively publish. Whereas 90% of all discoveries originate in institutions of higher education, Dill notes that increased emphasis on faculty research has not shown to be a powerful influence on individual research productivity. Instead, he states in his review that the most significant determinants gleaned from previous research are: “the faculty member’s core values and previous socialization, communication with colleagues in the profession, the structuring of tasks or workload, and the values and beliefs of colleagues in the department.” In general, Dill’s review identifies three main influences on faculty research performance: individual, task, and organizational factors. Individual characteristics include psychological variables such as attitudes and values, but also work habits, and demographics such as age and gender. The task structure includes both actual and expected time commitments under which a faculty member must perform teaching, research, and service. Organizational context includes institutional factors or policies that can impinge on the performance of a task. The social and collegial communications among researchers are significantly related to individual research performance (Blau, 1973; Reskin, 1977; Dill 1986). This relationship is an underlying assumption in this proposal, both as a measure of scholarly activity and an intrinsic reward. Collegial communications can stimulate involvement of researchers by offering ways to test their thinking, share in their discoveries, and enjoy the social aspects of interaction. However, academic field seems to play a role here as well. Several studies have found that faculty in the “hard sciences” (i.e., natural or physical sciences) seem to be more socially connected by working in teams and collaborating on publications more than their colleagues in the soft sciences (e.g., social sciences) (Biglan,1973; Wheeler and Creswell, 1985; Neuman and Finaly-Neuman, 1990). Also, the prestige of an academic department appears to play a role in that committed researchers in prestigious departments appear to show the strongest patterns of collegial communications (Parsons, T. and Platt, G. M., 1968; Bess 1982).
Although the influence of “self-expectation of professional values” accounts for as much as 30 to 40 percent of variance in measures of faculty productivity, academic reward systems continue to emphasize tangible perquisites such as tenure, promotion, and pay raises. These perquisites remain, despite the fact that there is no evidence that they motivate faculty to do more research (Dill, 1986; Blake and Tjoumas, 1990). Nonetheless, faculty of lower and middle rank are aware of and respond to this reward system (Clark, 1985). Other studies indicate that many faculty do respond to these monetary incentives, if only for the perks that accrue to the first published article (Tuckman, 1976; Creswell, 1986). To the extent that these rewards remain in place and because faculty are enculturated in this system as early as their graduate studies, the study will treat these traditional rewards as perquisites. As a measure related to professionalism and prestige, “professional recognition” will also be treated as a perquisite in the study. In reviews of the literature on faculty productivity with respect to age and tenure, (Blackburn,1972; Creswell, 1986), statuses of tenure, rank, and age were largely related for an aging, and increasingly highly ranked and tenured faculty population. Despite popular criticism that this aging population would be inherently slothful with respect to research productivity, measuring it as a function of age has not been mutually corroborating. Findings separately indicate a drop, a rise, and a saddle-shape rise-fall-rise with increasing age; all of these indicating that there are more and better measures of productivity than age alone and that no single measure can be used as a predictor of performance (Braxton and Bayer, 1986).
During early research on innovation and organizational change, several organizational factors emerged as determinants of receptivity to innovation. These factors include size, complexity, and social setting of the organization (Burns and Stalker, 1961) and its degree of centralization of authority (Blau, 1973). Researchers have identified several stages associated with the diffusion of innovation and their acceptance or rejection (Berman, 1981; Rogers, 1983).
In his study of innovation in schools, Berman (1981) identified three processes (mobilization, implementation, and institutionalization). Earlier, Giacquinta (1973) had identified these three stages as initiation, implementation, and incorporation. Although personal and demographic variables can contribute to the understanding of response to innovation, the results of research focusing on personal variables alone has not adequately explained variance in receptivity. This lack of explanative power is especially evident in studies where the same subject would be receptive to some innovations and reject others (Giacquinta, 1973).
Educational innovation has been examined within the context of schools as complex organizations. The concepts of status and risk arose within this context of inquiry, but initially along distinct paths. In early studies, actual or perceived risk associated with change was seen from the perspective of a threat to the status-quo which would generally be resisted (Miles, 1964). In their initial review of this literature, Rogers and Shoemaker (1971) identified several studies in which status characteristics were examined in studies of receptivity to innovation. Attributes of the innovation perceived by adopters were identified as predictors of rate of adoption, including the relative advantage it has over previous methods, its compatibility, complexity, observability, and its rate of adoption. In examining this review, Gross, Giacquinta, and Bernstein (1971) made the following distinction regarding the differences between innovations and the organizational contexts in which they occur. They distinguished between the simple organizational settings of many of these earlier studies (farms, etc.) and the more complex, bureaucratic settings in which educational change takes place. As an example of non-adoption in these complex settings, they cited the Carlson (1965) study where although audiovisual instruction in school was promoted at the Superintendent level, it was not successfully implemented.
Several factors emerged in studies of educational innovations that suggested the success or failure of implementation. Gross, Giacquinta, and Bernstein (1971) identified the following factors (as associated with success of implementation): clarity of role, adequate skills, necessary resources, compatible organizational structure, and receptivity by its members to the proposed innovation. In their review of the literature, Fullen and Pomfret (1977) recognized two other critical factors: clarity or explicitness and the complexity or difficulty of the change associated with an innovation. Fullan (1991) later identified the following factors as crucial to successful implementation: peer influence, clarity of purpose, training and support, and access or ubiquity.
The studies reviewed here have also identified organizational and non-organizational statuses which are highly correlated with faculty response to educational innovations (including computer technology) in higher education. These organizational statuses include: tenure, rank, seniority, department and school affiliation, and field of study (discipline). In addition, several critical factors for implementation have been identified in the literature and deserved treatment as organizational support variables that nonetheless are in part perceived by subjects as part of their assessment of benefit and risk in using new technology. These include peer influence, clarity of purpose, training and support, and access or ubiquity (Fullan, 1991).