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The authors surveyed faculty from a college of business and a college of education regarding their attitudes toward online education. Results of the survey were examined to determine the degree to which the technology acceptance model was able to adequately explain faculty acceptance of online education. Results indicate that perceived usefulness is a strong indicator of faculty acceptance; however, perceived ease of use offers little additional predictive power beyond that contributed by perceived usefulness of online education technology. [PUBLICATION ABSTRACT]

Employees tasked with using new technologies seldom wholeheartedly welcome the organizational changes associated with them. Online education embodies a shift away from traditional, classroom-based teaching activities typically associated with university education toward a technological realm where teaching requires the use of computers equipped with specialized course software systems, both synchronous and asynchronous computer applications, and the frequent frustrations associated with dependence on the Internet. Online education represents a dramatic step for universities- one that may be characterized as analogous to many organizations' technology- based change initiatives. As in other organizations, university administrators frequently view these technological changes as being a requirement for providing one's product or service on demand, reaching a broader demographic, and sustaining one's competitive advantage in an increasingly competitive market. However, despite the perceived necessity of new and sophisticated technology, the end users of such technology may not readily embrace such tools. Our study examines the degree to which the technology acceptance model (TAM; Davis, 1989) explains the acceptance of new technology, operationalized as online education, by faculty in both a college of business and a college of education at a large regional university.

The Technology Acceptance Model

Organizational change is not easy to accomplish, and technological changes cannot be implemented without resistance. The implementation of new technology is recognized by many as an event characterized by fear of the unknown, concern over organizational changes and their implications, and criticism from many constituents. Specific to online education, Cohen and Lippert (1999) commented that computer-based instruction "may be useful for skillsbased training but may not be useful for creative-thinking instruction or general management education" (p. 745).

Davis' TAM (1989) has been the dominant theory associated with understanding this phenomenon and remains an important and viable tool for researchers in this arena. We based our research model on the TAM not only because it is a well-accepted, theoretically grounded, general model of user acceptance of new information technologies, but also because it has been used in prior management education research (Arbaugh, 2000; Martins & Kellermanns, 2004). According to the TAM, perceived usefulness and perceived ease of use are hypothesized and empirically supported as the fundamental determinants of user acceptance of a given new technology. Perceived usefulness is defined as the extent to which a person believes that using a particular technology will enhance his or her job performance, and perceived ease of use is defined as the degree to which a person believes that using the system will be free from effort (Davis). In TAM research, user acceptance is characterized as a combination of a positive attitude toward the technology, intention to use the system, and actual use of the system (Davis; Taylor & Todd, 1995). The TAM's utility is evidenced by the numerous modifications and augmentations that have been made by researchers to address the question of technology acceptance as it relates to several variables. Gefen and Straub (1997) used the TAM and concluded that women and men differ in their perceptions, but not use, of e-mail, and Venkatesh and Morris (2000) identified gender differences with regard to the relative impact of perceived usefulness and perceived ease of use in predicting technology acceptance. User inexperience has also been found to play a role in the relative predictive power of the TAM's central constructs of ease of use and usefulness (Taylor & Todd).

Although technology acceptance research has made valuable inroads into the complexities of how and why humans choose to accept or reject technology- and the pace at which that acceptance or rejection occurs-many of the studies using the TAM or some variant thereof have centered on the technology acceptance dynamics associated with nonspecific user populations working in various occupational settings, using a wide spectrum of information technology solutions (Gefen & Straub, 1997; Taylor & Todd, 1995; Veiga, Floyd, & Dechant, 2001; Venkatesh & Morris, 2000). University faculty represent an unusual (although not unique) population-individuals who are highly educated, accustomed to having considerable autonomy, and who frequently work in highly politicized environments. Studying technology acceptance operationalized as online education represents a distinct contribution to this research field; the technology, user group, and organizational context are all new to the technology acceptance and adoption research domain.

Online Education

Distance learning is a broad term that encompasses both distance education (a term commonly used in academia) and distance training (a term commonly used in industry). We examined the acceptance of distance education as defined by Bourdeau and Bates (1997): education that is computer-based, remote, or asynchronous and supported by some instructional system. We use the term online education to more specifically describe the nature of distance education considered herein.

For universities and colleges, online education provides the opportunity to serve more students who desire an education. This influx of students is typically seen as encouraging, because although there are additional demands placed on the technological systems of the organization (e.g., computing networks, new hardware and software), there is no corresponding demand for increased physical space associated with on-site students. This may result in increased revenue from tuition with the increased expenses related to technology supported by the new student body.

Faculty frequently express apprehension regarding online education because of the technological problems associated with delivering the material, which may lead to student frustration and poor student evaluations. Faculty have also indicated concerns over the technological competence of students and their ability to use advanced synchronous online tools (Perreault, Waldman, Alexander, & Zhao, 2002). Likewise, concerns related to student learning and outcomes persist, despite several indications that online education results in comparable, if not better, educational results. Spooner, Jordan, Algozzine, and Spooner's (1999) summary of past studies that compared cognitive factors such as amount of learning, academic performance, achievement, and examination and assignment grades in distance learning and campus courses typically reflected no differences in cognitive factors between the distance and traditional classes.

Objective of the Study

With the increasing demand for online education and the need for faculty to embrace this as a viable teaching tool, user acceptance of technologically based teaching is an important issue. Drawing on earlier findings related to technology acceptance, our research extends the TAM by testing its efficacy in a distinctive population and organizational context. However, the defining characteristics discussed in this study are not unique to one organization or industry; therefore, we believe the findings will have far-reaching implications for many organizations engaged in change initiatives centered on technological innovation. Such insights can lead to new and innovative ways to mentor, train, and motivate technology users in diverse industries and organizations.

METHOD

Research Setting, Participants, and Procedure

As part of an ongoing, multiphase research endeavor examining online education and learning, faculty associated with both a college of business and a college of education from a large regional university were asked to complete an anonymous survey regarding their perceptions of online education. The response rate for the survey was 46.8%; 110 completed surveys (52% men, 45% women, 3% undisclosed) were received from the 235 faculty who were invited to participate. The average age of faculty participants was 48 years, with an average of 12.3 years teaching at the university level and an average of 2.1 years teaching online. A PhD, EdD, MD, or other terminal degree was held by 77% of respondents, and 23% had an MA, MS, MBA, or other master's level degree. With regard to academic rank, 33% were assistant professors, 22% were lecturers, 19% were associate professors, 19% were full professors, and 6% reported some other status or rank. Approximately 28% of participants reported teaching undergraduate courses online, and 49% reported teaching graduate courses online.

Survey Questions

The survey instrument used for the current study was based on questions derived from Davis' TAM (1989). Participants responded to questions measuring the central constructs of the TAM; the perceived ease of use of online education technologies and the perceived usefulness of online education. In all instances, respondents used a 5-point Likert-type scale with scores ranging from 1 (not at all) to 5 (very much so). Both the Perceived Ease of Use Scale and the Perceived Usefulness Scale were constructed of items modified to specifically reflect online education as the technology of interest.

To assess the criterion of technology acceptance, participants were asked to indicate the degree to which they agreed with a statement assessing their intention to use distance education technology in the future. This is highly consistent with previous TAM studies that have used intention to use technology as indicative of technology acceptance (Ferren, 2002; Gefen & Straub, 1997; Venkatesh, Morris, Davis, & Davis, 2003).

All survey items and corresponding measures of internal validity are shown in Table 1.

RESULTS

Initial exploratory analyses examined the relationships among the predictor and criterion variables. Table 2 presents the means, standard deviations, and intercorrelations of all variables in the model.

To examine the degree to which both perceived usefulness and perceived ease of use were associated with online education technology acceptance, we conducted two separate multiple regression procedures. The first analysis included the five variables associated with the perceived usefulness of online education and the second analysis included the four variables associated with perceived ease of use of online education teaching technologies. The regression equation with the perceived usefulness was significant, R^sup 2^ = .587, adjusted R^sup 2^ = .567, F(5, 104) = 29.517, p < .01. Likewise, the regression equation for perceived ease of use was significant, R^sup 2^ = .363, adjusted R^sup 2^ = .339, F(4, 105) = 14.986, p < .01. Based on these results, perceived usefulness measures appear to be better predictors of technology acceptance.

Next, a multiple regression analysis was conducted with all of the perceived usefulness and the perceived ease of use measures as predictors. The linear combination of the measures was significantly related to technology acceptance, R^sup 2^ = .602, adjusted R^sup 2^ = .567, F(4, 105) = 16.835, p < .01. The perceived usefulness measures predicted self-reported intention to use distance education technology significantly over and above the perceived ease of use variables, ΔR^sup 2^ = .239, F(5, 100) = 12.022, p < .01, but the perceived ease of use variables did not predict significantly over and above usefulness measures, ΔR^sup 2^ = .016, F(4, 100) = 0.993, p = .415. Based on these results, the perceived ease of use measures offer little additional predictive power beyond that contributed by knowledge of perceived usefulness of online teaching technology.

DISCUSSION

Although previous researchers have not used the TAM to examine university faculty acceptance of technology, nor online education in particular, similar results have been obtained when TAM has been used to examine technology acceptance of other highly educated persons. Hu, Chau, Sheng, and Tam (1999) focused on the technology acceptance of physicians, a population with similar characteristics as university faculty. As pointed out by Hu et al., professionals might subtly differ in their acceptance of technology when compared with individuals in an ordinary business setting. The findings indicated that the TAM was able to provide a reasonable explanation of the intentions of physicians to use telemedicine technology. Specifically, perceived usefulness was found to have a significant and strong influence on the physicians' intention to use telemedicine technology.

Contrary to the predictions of the TAM, perceived ease of use did not play a significant role in predicting technology acceptance in our study. For example, Arbaugh (2000) found that student satisfaction in online Master of Business Administration (MBA) courses was positively related to perceived usefulness but not related to ease of use. A possible explanation of this finding, as proposed by Hu et al. (1999), is that although physicians and university professors may exhibit considerable differences in general technology competence and adaptability, they are able to learn new technologies quickly and with less training than other employee populations. Agarwal and Prasad (1999) found that level of education was positively associated with ease of use, thereby offering additional support to this notion. Additionally, Taylor and Todd (1995) found that those without experience may focus first on ease of use, and as experience increases, users presumably overcome concerns about ease of use and may focus their attention on perceived usefulness. This suggests that the path from ease of use to attitude will be stronger for inexperienced users, whereas the path from perceived usefulness to attitude will be stronger for experienced users. Our findings were consistent with this; In the current population 69% of respondents described their personal level of computing competence as being either good or excellent; hence, restriction of range with regard to overall computing skills cannot be ruled out as impacting our findings.

It is likely that both professors and physicians tend to be pragmatic in their acceptance of technology and place more emphasis on the compatibility of the technology with their duties. In this context, perceived usefulness must be emphasized early on in the adoption process, whereas ease of use does not seem to be a major concern for this professional group. Early emphasis on usefulness can be critical because our research, among other studies (e.g., Dasgupta, Granger, & McGarry, 2002), has shown that perceived ease of use does not always have a positive impact on technology acceptance.

Although our results offer insight into faculty acceptance of online education, additional research is warranted. First, we suggest that this exploratory study be replicated at other universities to allow for the comparison of results. An obvious limitation of the current study is the use of a convenience sample; introducing additional institutions would likely increase the variance associated with types of online education systems used. Perceived ease of use varies based on individual characteristics, and is also likely to vary based on the types of technology used by a college or university and the support systems available for faculty using these centralized systems. Next, it would be of interest to incorporate samples of faculty from other academic disciplines to compare findings with regard to the TAM. Involving faculty from different academic fields would add to understanding of the acceptance of online education. Finally, additional research may examine possible relationships between demographic characteristics of faculty members and their acceptance of online education as a viable delivery method for higher education. Past research has indicated that both gender and age may play roles in technology usage and adoption patterns, and it would be of interest to examine whether this applies to a highly educated population such as university faculty.