Tracy Irani
Assistant Professor
University of Florida

Abstract

This study, using the Technology Acceptance Model as a theoretical framework, investigated the effect of prior experience and degree of innovativeness on subjects’ perceptions of the perceived usefulness and their intent to use Internet communications tools.

Results indicated that respondents who had relevant prior experience and those who scored high in degree of innovativeness had the most favorable perceptions of the perceived usefulness of these technologies. Further, those subjects who had high levels of experience and perceived usefulness were most likely to use Internet communications technologies, while those subjects who scored low in both of these areas were least likely. Linear regression analysis indicated that, for all subjects, experience and perceived usefulness were the strongest predictors of behavioral intent to use Internet communications tools.

The Internet is said to be one of the fastest diffusing technological innovations of all time (Nielson, 1995), with an estimated 71 million users worldwide (Matrix Information and Directory Services, 1997). As a new and rapidly diffusing communication technology, adoption of the Internet as a communications tool represents a potential opportunity for agriculture, where developing more effective communications and a stronger frame of reference, whether it be with traditional stakeholders, extension clientele or the general public, has always been a key objective.

In the educational setting, one of the oft-cited advantages of Internet use is the degree of interaction and asynchronous information exchange potentially achievable between sender and receiver through adoption of interactive communication tools such as email, World Wide Web-based bulletin boards and online discussion forums designed to augment or extend instruction and information delivery. For example, some studies have found slightly higher student achievement levels when mode of instruction includes interactive computer applications that facilitate communication and collaboration (Martin & Rainey, 1993; Means, 1993). Yet, within the traditional stakeholder audiences of agricultural students and extension clientele, the user base is still relatively low. In a three year longitudinal study, Suvedi, Campo & Lapinski (1999) found that, although the percentage of respondents who used the Web to gain extension-related information increased from 1.4 % to 10%, the vast majority of respondents did not use it. Trede and Whitaker (1998) found that beginning farmers rated "cutting edge", Internet-delivered instructional technologies much lower than traditional instructional techniques, perhaps owing to lack of familiarity and prior experience with these technologies.

Usage of Internet communications tools may be seen as a way to meet the challenge to increase the effectiveness of extension program delivery methods and the communication needs of students enrolled in on and off-site agricultural programs (Donaldson & Thompson, 1999; Miller & Pilcher, 1999); however, understanding the factors which influence adoption and user perceptions is still a critical need. In a number of studies focusing on attitudes toward technology, information technology researchers such as Davis (Davis, 1989; Davis, et al, 1989; Hendrickson & Collins, 1996; Chau, 1996)) have examined the relationship between perceptions and adoption of new technologies. Drawing on Fishbein and Ajzen's Theory of Reasoned Action (1975), Davis (1989) developed the Technology Acceptance Model (TAM) which posits that individual perceptions as to the perceived ease of use and perceived usefulness of a technology can predict its usage. Research suggests, however, that these factors, in turn, may be influenced by other external factors which might prove useful in helping to predict the likely users of a technology, as well as their attitudes and subsequent usage behavior.

The objective of this study was to examine the assumption that two contextually relevant external factors, prior experience and degree of innovativeness, might exert an influence on perceived usefulness, defined in the TAM model as the degree to which a user believes that using a technology will be beneficial in some way. Using the TAM as a theoretical framework, this study was designed to examine the effect of prior experience and degree of innovativeness on intent to use Internet-based interactive communication tools to complete a communication task, with a view toward ascertaining how these factors influence adoption of interactive technologies. Understanding how these factors influence adoption and user perceptions will be important in the development of Web-based initiatives hoping to use these tools to enhance communication and information delivery to agricultural audiences.

The Technology Acceptance Model, or TAM, stems from the Theory of Reasoned Action, or TORA (Fishbein & Ajzen, 1975), well known as a seminal work in attempting to understand and predict behavior and behavioral intentions. The basic proposition of both models is that in order to predict a behavior B (such as using a technology to complete a task), one must try to measure an individual's intent to behave, or BI (such as intent to adopt a technology for this purpose), itself a function of attitudes or perceptions toward the target behavior (and, in the case of the TORA, subjective norms). In both the TORA model and the TAM, attitudes are a function of beliefs about and assessments of perceived benefits/risks of acting in a certain way, such as beliefs about the advantages or disadvantages of using a new technological innovation.

The TAM attempts to explain user acceptance and adoption of a technology based on two specific behavioral beliefs, perceived ease of use (EOU) and perceived usefulness (U), the influence of which determine an individual's behavioral intention to use (BI) a technology. (See Fig. 1). Perceived ease of use is the extent to which it is believed that a technology will be easy to use, while perceived usefulness is the extent to which it is believed that using a technology will be beneficial in some way (Venkatesh, 1999).

Two different formulations of TAM exist in the literature. Although many studies, especially in the IT literature, omit attitude, the original model shows the perceived usefulness and perceived ease of use variables influencing attitude toward use, which subsequently impacts usage behavior (Hubona, G.S. & Geitz, S., 1999).

Fig. 1. The Technology Acceptance Model. (Hubona, & Geitz, 1999).

Davis et al (1989) suggested that external variables such as documentation and user support might influence perceived usefulness and ease of use, but empirical research on the effect of external variables has been limited. Of the limited research that has been done, Agrawal and Prasad (1997) conducted a study which showed that innovation characteristics, i.e., an individual’s perception of the characteristics of an innovation, can predict acceptance behavior. In a subsequent study, the researchers identified a set of individual difference variables, including prior similar experience, that exerted significant influence on TAM's belief constructs (Agrawal & Prasad, 1999). Doll, Hendrickson and Deng (1998) used multi-group invariance analysis to assess a series of incremental cross-validation studies, the results of which, while providing support for the validity and reliability of the model, also revealed variation from other sub-groups for individuals with no prior computing experience.

Some researchers have argued that behavior is largely a function of an individual’s perceptions of an event and its potential outcomes (Fazio, 1995). In this context, one of the critical aspects related to user perceptions of new communications technologies might be relevant prior experience. Studies have shown that the attitudes of people who have had direct prior experience with an attitude object were moderately related to subsequent attitude-relevant behaviors, whereas attitudes of people without direct experience had slight or no relationship (Fazio, & Zanna, 1978a).

Along these same lines, direct experience of Internet -based communications tools such as e-mail, bulletin boards and online discussion forums should serve to strengthen user perceptions and enhance the consistency of the attitude-behavior relationship with respect to usage of these tools. Within the context of Internet communications technologies, subjects with direct experience would presumably be more likely to hold stronger perceptions as to ease of use and perceived usefulness of a technology, based on their ability to generate more beliefs and past behaviors related to their experience. Yet, in a domain where weakly held attitudes based on limited experience are the norm, behavior and intention to behave might be influenced by a variety of factors that could make predicting outcomes difficult.

Attitude toward use has usually been conceived of, as in TAM and also the TORA, as a variable constructed on the basis of a subject's belief perceptions and evaluations of the consequences of engaging in some behavior. In their original conceptualization of attitude toward use within the TAM model, Bagozzi, Davis, & Warshaw (1989) found three distinct attitude components: attitudes toward success, failure and the process of learning to use or use a technology. Hubona and Geitz (1999) saw attitude as a moderator variable within TAM, influenced by the belief perception constructs and directly influencing intentions to use a technology.

In his research, Fazio (1986) took a different approach from both the TORA and the TAM, focusing instead on accessibility and automaticity of attitudes. In Fazio’s view, attitudes were often automatically (without conscious thought) activated on a subject’s being confronted with an attitude object. Through a process of selective perception, combined with the immediate perception of the attitude object, the subject developed a definition of the event, itself modified by both norms and a definition of the situation or context for the behavior. According to Fazio, definition led directly to the behavior, "simply following" from perceptions without any necessary conscious thought (Fazio, 1986, p. 237).

Fazio contended that variables such as direct experience strengthen the attitude-behavior correlation because they are more accessible, i.e., more easily called up from the subject’s memory upon contact with the attitude object. From Fazio’s perspective, attitudes can be activated upon exposure to an attitude object, either called up from memory or automatically activated upon exposure. Attitudes can therefore have a greater or lesser degree of accessibility. Fazio held that the more accessible an attitude, the stronger it would be, and the stronger and more consistent the relationship between attitude and subsequent behavior.

One of the motivating forces which underlies formation of attitudes and beliefs with respect to adoption of new technologies in general is innovativeness, an innate personality characteristic which has been explored extensively in the consumer behavior literature. Innovativeness, a construct that evolved out of diffusion theory, was originally associated with the adoption and use of new technological innovations (Rogers and Shoemaker, 1971). Many subsequent consumer behavior studies have used the concept of consumer innovativeness to examine purchase behavior related to adoption of new products.

In its original conception, Rogers defined innovativeness as "the degree to which an individual is relatively earlier in adopting an innovation than other members of his or her social system," (Rogers & Shoemaker, 1971, p. 27). Hirschman (1980) defined innovativeness as the desire for new experience, and traced the development of the construct to its roots in the diffusion and personality literature. According to a study by Venkatraman and Price (1990), consumer innovativeness can be defined as a latent personality trait that predisposes people to buy new products.

In the 1970's, Leavitt and Walton (1975) critiqued the results of several previous diffusion studies on the basis of smaller than expected variance in the dependent variable of adoption. Calling personality variables the "soft underbelly" of the problem, they postulated that a trait might exist that would underlie rational media choice behaviors. The researchers made the argument that the many psychological studies of close mindedness, dogmatism rigidity, etc., could be counterbalanced by an attempt to scale a new open-minded, constructive trait they called "innovativeness." The subsequently developed Leavitt and Walton innovativeness scale has been extensively tested for predictive validity and reliability by subsequent researchers (Craig & Ginter, 1975; Goldsmith, 1984).

Some researchers have also attempted to relate innovativeness to the internal need for stimulation, arguing that as stimulation, variously categorized as complexity, arousal, enjoyment of risk, etc., falls below a certain level, individuals will seek out stimulation through behaviors such as exploration and variety seeking (Price and Ridgeway, 1983). As such, the construct is closely related to novelty seeking (Flavell, 1977), and to creativity, especially productive thinking and problem solving (Welsh, 1975; Guilford, 1965).

In a subsequent study, (Venkatraman, et al, 1990) the researchers employed a categorization based on Roger's diffusion typology of relative advantage, compatibility, complexity, trialability and communicability in an attempt to differentiate innovators further, by looking at demographic and information processing differences. Results of the study indicated that innovation tendencies did impact adoption behavior, a result that enabled the researchers to construct innovator profiles based on demographic and personality trait differences. This work suggested that innovators tended to be young, male, more highly educated than the general population and to monitor a greater number of media vehicles for information. Innovators also tended to buy new products and visit new stores earlier than others.

Although significant evidence supporting TAM exists in the literature, limited research has been conducted on the effect of external variables and their influence on the perceived usefulness and perceived ease of use belief constructs. Further, researchers such as Robertson and Gatignon (1986) have argued that most research dealing with diffusion of technological innovations has typically utilized survey methodologies, as exposed to experimental approaches designed to illuminate causal processes. Therefore, the rationale for this study is based on using a quasi-experimental approach to examine the effect of prior direct experience and degree of innovativeness as external model variables impacting perceived usefulness and intent to use Internet based communications tools to complete a communication task. Based on Fazio's direct experience research, as well as the TAM user acceptance studies focusing on individual differences, it can be expected that subjects with prior direct experience of the technology will be more likely to use Internet communications tools than those who lack experience.

H1: Perceived usefulness will be significantly higher among subjects with a high level of experience of Internet-based communications technology compared to those with a low level of experience.

Diffusion theory postulates that early adopters, i.e., innovators, will be first to adopt new technological innovations (Rogers and Shoemaker, 1971). Diffusion researchers have also looked at individual personality traits that might influence adoption behavior. Midgley and Dowling (1978) re-conceptualized the adoption of behavior approach as less a measure of the time it takes to move from awareness to adoption than a personality construct which an individual could possess to a greater or lesser degree. According to Midgley and Dowling, innovativeness is "the degree to which an individual is receptive to new ideas and makes innovation decisions independently of the communicated experience of others." (p 236). Therefore, within the context of this study, it can be expected that subjects who possess a high degree of innovativeness will be more likely to accept and adopt new communications technology to complete a communication task than those who have a low degree of innovativeness.

H2: Perceived usefulness will be significantly higher among subjects who possess a high degree of innovativeness as compared to subjects who possess a low degree of innovativeness.

In addition to predicted main effects, this study sought to make predictions as to the effect of model relationships on the basis of an experimental manipulation of the perceived ease of use variable. According to TAM, perceived ease of use and perceived usefulness are moderating variables that influence attitude toward use and behavioral intent to use. Therefore, by manipulating subjects’ perceptions through exposure to a stimulus message framing use of Internet communication tools according to either the benefits or risks associated with perceived ease of use, it can be expected that subjects in the benefits-oriented perceived ease of use condition who also have a higher level of experience will have a stronger behavioral intent toward the target adoption behavior, while those subjects in the risk-oriented framing condition who have a lower level of experience will have a lower level of behavioral intent. Further, exposure to the stimulus message should serve to similarly affect subjects who are high or low in innovativeness.

H3: There should be a three-way interaction between experience, perceived usefulness and the perceived ease of use stimulus such that:

H3a: Behavioral intent will be highest for those subjects in the high perceived usefulness condition who also have high levels of prior experience;

H3b: Behavioral intent will be lowest for those subjects in the low perceived usefulness condition who also are low in prior experience.

H4: There should be a three-way interaction between degree of innovativeness, perceived usefulness and the perceived ease of use stimulus such that:

H4a: Behavioral intent will be highest for those subjects in the high perceived usefulness condition who also are high in degree of innovativeness;

H4b: Behavioral intent will be lowest for those subjects in the low perceived usefulness condition who also are low in degree of innovativeness.

H5: Perceived usefulness and prior experience will prove to be the most significant predictor variables of behavioral intent for subjects with and without direct experience of the target adoption behavior.

Subjects were drawn from a random sample of college students (n=120) enrolled in an agricultural writing class. The research design was a 2x2x2 factorial consisting of experience (two levels), innovativeness (two levels), and perceived ease of use (two levels). To conduct the study, a questionnaire instrument was developed which included 67 five point bipolar semantic differential scale items. Experience was measured on the basis of a four item index designed to measure subjects’ experience with Internet communications tools, specifically, email and online discussion forums. Degree of innovativeness was measured by a series of 24 scale items, half of which were reverse coded, derived from form B of Leavitt and Walton’s Innovativeness scale (1975). Perceived ease of use was manipulated on the basis of exposure to a message designed to frame usage of Internet communication tools as either easy to use and beneficial to the user, or as difficult to use and not beneficial. The dependent variables measured in the study, which included the 12 item perceived usefulness index, the ten item attitude toward use index, and the five item behavioral intent index, were derived from Hubana and Geitz’s (1999) TAM scale.

The questionnaire instrument was reviewed by a panel of judges, and a manipulation check was included to insure the validity of the perceived ease of use experimental manipulation.

At the beginning of the experiment, subjects were randomly assigned to one of the two perceived ease of use conditions, which were incorporated into the color-coded copy of the questionnaire booklet each subject received. After filling out the scale items that measured experience and degree of innovativeness, subjects were instructed to read a one-paragraph message statement and then complete the rest of the questionnaire. Subjects in the high perceived ease of use condition were exposed to the following message:

Sending a document electronically, either through an email message that contains an email attachment or by posting to an online bulletin board forum, is one way of making sure that your communication gets there right away – and you can save a copy for yourself to prove you sent it. It’s efficient, because such messages don’t require that you print out a hard copy version, so you save on paper, and convenient because you can do it right on your computer.

Subjects in the low perceived ease of use condition were exposed to the message that follows:

Sending a document electronically, either through an email message that contains an email attachment of by posting to an online bulletin board forum, may be a problematic form of communication, since your communication could get lost or deleted without your being aware of it. It requires that you have access to a computer that’s fast enough to access the Internet and run the special software that is needed, and it may not be very convenient, since you need to learn how to use the software in order to send your document.

In the items which followed, subjects were asked to indicate their perceptions as to the perceived usefulness, as well as their attitude and behavioral intent toward using two specific forms of Internet communication, sending an email attachment and posting a message to an online discussion forum, to complete a communication task involving communicating details about an assignment required in the class they were taking. Finally, at the end of the questionnaire, subjects were asked to re-read the perceived ease of use message statement, and then to answer a series of four items designed to serve as a manipulation check on respondents’ interpretation of the message statement contents as either a benefits or risk oriented description of the perceived ease of use of the specified Internet communication tools.

Exploratory factor analysis was conducted on all of the variable indices in the study, resulting in a one-factor solution for all of the indices used in the analysis, with the exception of degree of innovativeness, which returned a seven-factor solution, representing the seven subscale factors as in Craig and Ginter's (1975) validation of the original scale. For all hypotheses, descriptive statistics were obtained and mean splits were used to recode the independent variables of experience and degree of innovativeness into high and low levels for each variable. Reliability analyses for all of the indices used in the study were subsequently run using Chronbach's alpha statistic. The resulting standardized item alpha for the experience scale was .62. Standardized item alpha for the degree of innovativeness scale was .70. Standardized item alpha for perceived usefulness was .90; for attitude .89; and for behavioral intention .72. Standardized item alpha for the four-item manipulation check was .84.

Descriptive statistics were then calculated for all indices, which yielded the resulting means table reporting means and standard deviations for the full design. (See Table 1.) Scores for the items rating perceived usefulness of Internet communications tools were recoded to range from 1, indicating that perceived usefulness was highly unlikely, to 5, indicating that perceived usefulness was highly likely.

Table 1. Table of Means for Effect of Experience, Degree of Innovativeness and Perceived Ease of Use on Perceived Usefulness of Internet Communications Tools in Completing Communication Task.

A manipulation check, developed to insure that the observed responses were in fact due to the perceived ease of use manipulation, was conducted. To conduct the manipulation check, a four-item index was constructed which asked respondents to indicate whether or not the message to which they had been exposed represented a high (benefits) or low (risks) level of perceived ease of use. For this index, item scores ranged from 1 =strongly disagree to 5 = strongly agree. A full factor 2 (experience) x 2 (degree of innovativeness) x 2 (perceived ease of use) ANOVA was run, using the manipulation index as the within subjects factor. The results, as anticipated, were non significant for all groups F (1,80)=1.53, p < .2, indicating that the manipulation was successful in terms of all subjects similarly perceiving the stimulus message (M = 4.93, SD = .67).

Hypothesis 1, which predicted that perceived usefulness would be higher for subjects with a high level of experience of Internet communications tools than for those subjects with low levels, was supported. To test this hypothesis, a 2 x 2 x 2 ANOVA model was run, utilizing experience (two levels) by degree of innovativeness (two levels) by perceived ease of use (two levels) as between subjects factors. A main effect was found for experience, F (1, 119) = 9.62, p < .01, which indicated that subjects with higher levels of experience (M = 3.44, SD = .75) had a more favorable perception of the usefulness of Internet communications tools than did subjects with a lower level of experience of these technologies (M = 3.14, SD=.79).

For hypothesis 2, which predicted a main effect for degree of innovativeness, results revealed the main effect, F (1,119) = 5.31, p < .02, indicating that subjects who possessed a higher degree of innovativeness were more likely to favorably perceive the usefulness of Internet communications tools to complete a communications task (M = 3.50, SD = .75) than those who possessed a lower degree of innovativeness (M = 3.10, SD=.74).

For hypothesis 3, which predicted a three way interaction between level of experience, perceived usefulness and perceived ease of use on the within subjects factor of behavioral intent, perceived usefulness was recoded on the basis of a mean split into high and low levels. This hypothesis was not supported, F (1,117) = 1.41 = p < .2, but a two way interaction was found between experience and perceived usefulness, F (1,117) = 4.48, p < .04, and main effects were found for experience F (1, 86) = 7.32, p < .01 and perceived usefulness, F (1, 86) = 19.88, p< .01. Comparison of means revealed that behavioral intent was highest for subjects who were high in level of experience and perceived usefulness and lowest for subjects who were low in level of experience and perceived usefulness. (See Table 2).

Table 2. Means Table for Effect of Experience and Perceived Usefulness on Behavioral Intent.

Hypothesis 4, which predicted a three way interaction between degree of innovativeness, perceived usefulness and perceived ease of use on the within subjects factor of behavioral intent, was not supported, F(1, 86) = 2.46, p < .1, but a main effect was found for perceived usefulness, F(1, 86), p< .001.

Hypothesis 5, which predicted that perceived usefulness and experience would be the strongest predictor variables of behavioral intent to use Internet communications tools, was supported. To test this hypothesis, all TAM predictor variables were loaded into a linear regression model that utilized the behavioral intent index as the dependent variable. Linear regression analysis was performed, and the regression proved to be significant, F(1, 5) = 13.97, p < .001. Results indicated that, for all subjects, experience and perceived usefulness were the most significant predictors of behavioral intent to use Internet communications tools. (See Table 3).

Table 3. Prediction of Behavioral Intent to Use Intent Communications Tools

**p < .01

This study provides support for the usefulness of the TAM model with agricultural audiences and within the context of Internet communications tools as a technological innovation. In addition, the study supports the argument that the external factors of prior experience and degree of innovativeness do play a role in acceptance of these technologies and ultimate usage behavior. It seems clear that individuals who are more innovative are more likely to accept Internet communications tools, and that those with relevant prior experience are also more likely to accept and use these technologies. Based on these results, an implication of these findings may involve a need to consider the level of relevant prior experience and tendency toward innovativeness of an audience when implementing communications technology in the agricultural classroom, or when attempting to reach external audiences.

The lack of any significant interactions between the perceived ease of use message stimulus and the other model variables seems to suggest that both experience and degree of innovativeness exert their influence on an individual’s perceptions of the benefits or risks associated with using a technology, as opposed to impacting subjects' evaluations of the perceived ease or difficulty associated with a technology's use. This seems logical, since both of these variables would seem to have a definite association with an individual’s determination of the usefulness, or lack thereof, of adopting some technology. On the other hand, it would seem likely that experience should also affect perceived ease of use, which was not specifically tested in the research design. Further research in this area, looking more specifically at the paths of interaction and direction of influence of the relevant prior experience variable, appears warranted on the basis of this study. A study of these same model relationships with other agricultural audiences is another area for future research.

In addition to the above, one of the key findings of this study involves the implication that while both prior experience and degree of innovativeness may exert an influence on an individual's sense of the perceived usefulness of a technological innovation, it is relevant prior experience that seems to interact with perceived usefulness and serves as a highly significant predictor variable of behavioral intent toward usage. Given the fact that the Internet is still a relatively young and evolving communication medium, the level of usage, and consequently, experience, within an agricultural audience is likely to remain low compared to other communication methods for some time. Even in the classroom setting, many students' experience of these technologies is limited to browsing a web page as part of a class assignment or to gain material for research.

Based on the results of this study, it would seem apparent that it is not only an audience's level of experience, but also the quality of that experience that will be a critical factor in determining usage behavior. From the institutional perspective, there are obvious incentives in developing communications that utilize technologically innovative techniques such as Internet communications tools. But, while early adopters may be intrinsically motivated to adopt a new technological innovation and ignore any minor disadvantages or risks, the larger populations of late adopters and early majorities may have quite different experiences, perceptions and motivations which drive their adoption behavior. To be successful, a technologically communication innovative communication tool may not only need to be perceived as effective by the institution, but also capable of being framed according to the benefits of its use and the positive prior experiences of at least some users who are also members of the potential audience.

On the other hand, the undeniable efficiency and potential of the Internet communication tools, in the classroom, in the field, in the county extension office and with the public in general, provides a compelling rationale for continued efforts aimed at growing the experience base and providing opportunities for our constituencies to access and use these tools to communicate about important agricultural issues. In the classroom setting especially, it seems even more critical that our students continue to develop skills and experience in these areas as well, for they will be the ones who most stand to benefit from the efficiencies and communications potential these tools can provide.

Agarwal, R., & Prasad, J. (1997). The role of innovation characteristics and perceived voluntariness in the acceptance of information technologies. Decision Sciences Journal, 28, (3), 557-582.

Agarwal, R., & Prasad, J. 1999). Are individual differences germane to the acceptance of new information technologies? Decision Sciences Journal, 30, (2), 361-391.

Chau, P.Y.K., (1996). An empirical assessment of a modified technology acceptance model. Journal of MIS, 13, (2), 185-204.

Craig, C.S., & Ginter, J.L. (1975). An empirical test of a scale for innovativeness. Advances in Consumer Research, 2, 555-562.

Davis, F.D., (1989). Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly, 13, (3), 319-339.

Davis, F.D., Bagozzi, R.P., & Warshaw, P.R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35, (8), 982-1003.

Doll, W. J., Hendrickson, A., & Deng, X. (1998). Using Davis’ perceived usefulness and ease-of-use instruments for decision making: a confirmatory and multigroup invariance analysis. Decision Sciences Journal, 29, (4), 839-869.

Donaldson, J.L., & Thompson, J.S. (1999). Interpersonal communication strengthens Web-based instruction. Journal of Applied Communication, 83, (3), 22-32.

Fazio, R.H. (1986). How do attitudes guide behavior, in R.M. Sorrentino, & E.T. Higgins, Eds., Handbook of motivation and cognition, New York: NY: Guilford Press.

Fazio, R.H. (1995). Attitude accessibility and motivation as determinants of biased processing: A test of the MODE model. Personality and Social Psychology Bulletin, 21, (7), 704-710.

Fazio, R.H., & Zanna, M.P. (1978a). Attitudinal qualities relating to the strength of the attitude-behavior relationship. Journal of Experimental Social Psychology, 14, 398-408.

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: an introduction to theory and research. Reading, MA: Addison-Wesley.

Flavell, J.H. (1977). Cognitive development. Englewood Cliffs, NJ: Prentice-Hall, Inc.

Goldsmith, R.E., (1984). Some personality correlates of open processing. Journal of Psychology, 116, 59-66.

Guilford, J.P. (1965). Intellectual factors in productive thinking. Productive thinking in education. Washington, D.C.: National Education Association.

Hendrickson, A.R., & Collins, M.R. (1996). An assessment of structure and causation of is usage. The DATABASE for Advances in Information Systems, 27, (2), 61-67.

Hirschman, E.C. (1980). Innovativeness, novelty seeking and consumer creativity. Journal of Consumer Research, 7, 283-295.

Hubona, G.S., & Geitz, S., (1999). External variables beliefs, attitudes and information technology usage behavior. [On-line]. Available at: http://www.isy.vcu.edu/~ghubona/Pub1.html. [1999, Oct. 15].

Leavitt, C., & Walton, J.R. (1975). Development of a scale for innovativeness. Advances in Consumer Research, 2, 545-554.

Martin, E., & Rainey, L. (1993). Student achievement and attitude in a satellite-delivered high school science course. The American Journal of Distance Education, 7, (1), 54-61.

Matrix Information and Directory Services. (1997). [On-line]. Available at: http://www.mids.org. [1999, Oct. 15].

Means, B. (1993). Using technology to support education reform. Washington, D.C.: Office of Educational Research and Improvement.

Midgely, D.F., and Dowling, G.R. (1978). Innovativeness: The concept and its measurement. Journal of Consumer Research, 4, 227-242.

Miller, G., & Pilcher, C. (1999). Desired and assessed cognitive levels of instruction: Are college of agriculture courses taught on campus and at a distance comparable? Proceedings of the 26^th national Agricultural Education Research Conference, 343-351.

Nielson, J., (1995). Multimedia and hypertext: the Internet and beyond. Boston, MA: AP Professional.

Price, L.L., & Ridgeway, N.M. (1983), Development of a scale to measure use innovativeness. Advances in Consumer Research, 10, 679-684.

Rogers, E.M., & Shoemaker, F.F. (1971). Communication of innovations. New York: The Free Press.

Suvedia, M., Campo, S., & Lapinski, M.K. (1999). Trends in Michigan farmers’ information-seeking behaviors and perspectives on the delivery of information. Journal of Applied Communication, 83, (3), 33-49.

Trede, L.D., & Whitaker, S. (1998). Perceptions of Iowa beginning farmers toward the delivery of education. Journal of Applied Communication, 82, (4), 22-33.

Venkatesh, V., (1999). Creation of favorable user perceptions: exploring the role of intrinsic motivation. [On-line]. Available at: http://www.mbs.umd.edu/is/venkate/myhomepage/misq99/misq1.htm. [1999, Oct. 15].

Venkatraman, M.P., & Price, L.L. (1990). Differentiating between cognitive and sensory innovativeness: concepts, measurement and implications. Journal of Business Research, 20, 293-315.

Venkatramen, M.P., Marlino, D., Kordes, F.R., and Sklar, K.B. (1990). Effects of individual differences variables on responses to factual and evaluative ads. Psychology and Marketing, 102-107.