Team Trust in Online Education: Assessing and Comparing Team-member Trust in Online Teams
Versus Face-to-Face Teams

Peggy M. Beranek and Monique L. French

VOL. 25, No. 3

Abstract

Trust is a key factor in enabling effective team performance and, in online teams, needs to be built quickly and early. As universities expand their online offerings, students are increasingly working in online teams. Understanding how trust development may differ in online teams versus face-to-face teams can have implications for online education development. This study compared trust levels in online and face-to-face teams at the beginning of the semester and at the end of the semester after the teams worked together on a series of tasks. The findings indicate that online teams do develop trust in their teammates, and actually have higher trust levels on a variety of trust dimensions.

Résumé

La confiance, un facteur clé permettant à une équipe d’être performante et efficace, doit être bâtie rapidement et le plus tôt possible lorsqu’il s’agit d’équipes en ligne. En raison du nombre sans cesse croissant de cours à distance offerts par les universités, les étudiants sont appelés à travailler, de plus en plus souvent, en équipes en ligne. Comprendre en quoi l’établissement de la confiance peut différer selon qu’il s’agisse d’équipes en ligne ou d’équipes travaillant en face-à-face, peut avoir des répercussions au niveau de l’élaboration de l’enseignement en ligne. Cette étude compare les niveaux de confiance existant au sein d’équipes en ligne et d’équipes travaillant en face-à-face au début du trimestre et à la fin du trimestre, alors que les équipes ont travaillé ensemble à la réalisation d’une série de tâches. Les données indiquent que les équipes en ligne développent de la confiance envers leurs coéquipiers et qu’elles ont, en effet, un niveau de confiance plus élevé au niveau de certaines dimensions de la confiance.

Introduction

Trust has a direct impact on team performance, and trust also plays a critical role in problem-solving organizational performance (Hart, Capps, Cangemi, & Caillouet, 1986) and organizational communication (Roberts & O'Reilly III, 1974). Many researchers indicate that building trust in online teams, while possible, takes more time than building trust in teams that work face-to-face Walther (1996) and that building trust in virtual teams is the greatest challenge in creating successful, effective virtual teams (Coutu, 1998; Jarvenpaa, Knoll, & Leidner E., 1998; Platt, 1999).

An online team is geographically distributed and members communicate primarily via computer technology. As the use of online teams, which communicate without the limits imposed by geography, time and organizational boundaries, grows within organizations, concerns about preparing members to work more effectively in a virtual environment increases. This increase in the use of virtual teams in organizations has created the need for higher educational institutions to prepare students to work in teams and to be effective team players (Hart Research Associates, 2010).

Online education systems are used to support meeting and task functions, to display and describe course material to students, to distribute and share notes among students and to support team interaction. These online education systems are commonly referred to as Learning Management Systems (LMSs) which is the term we will use in our discussion.

Allen & Seaman (2007) define an online class as one where the proportion of content delivered online is 80% or more. During the fall of 2008 over 4.6 million students were taking at least one online course (Allen & Seaman, 2009) which was a 17% increase from the previous year and in 2009 there was an additional 21% increase to approximately 5.6 million students taking at least one online course (Allen & Seaman, 2010).

Concerns have been raised in the online education environment about problems that can occur due to limited social interaction between the students. Problems cited are retention of students (Carr, 2000), a sense of learner isolation (Brown, 1996), and the problem of ‘fading back’ or non-participation (Haythornthwaite, et al., 2000). Social cues, social interaction and the development of trust have been shown to mitigate these problems. However, research has indicated that the development of trust among team members requires face-to-face communication, thereby making it difficult for online teams to develop the trust needed to help with these issues.

In an effort to better understand trust in online teams and its implications for online teaching, the role of trust development in an academic setting is investigated. This forms the basis of the research question addressed in this study:

“Can students in online classes who communicate virtually develop levels of trust comparable to those of students in traditional classes who communicate face-to-face?”

The remainder of the paper is organized into four sections. The next section will review the relevant literature. This will be followed by a description of the method used and results and discussion. The paper will conclude with a discussion of the implications of this research for online teaching, research limitations and suggestions for future research.

Literature Survey

Trust – Definitions and Measures

Trust has been studied in a variety of different academic environments with many different definitions and characteristics, one of which is the aspect of multi-dimensionality. Definitions of trust extend from assuming others will fulfill expectations (Rotter, 1967) to definitions referring to one’s feelings of vulnerability (Meyerson, Weick, & Kramer, 1996). Other definitions of trust focus on uncertainty and the necessity of monitoring (Gambetta, 1988) and propensity towards risk-taking (Luhmann, 1988). Meyer, Davis, and Schoorman (1995) define organizational trust as the “willingness of a party to be vulnerable to the actions of another party, based on the expectation that the other will perform a particular action important to the trustor, irrespective of the ability to monitor or control that other party”.

While most of the early literature on trust focuses on trusting relationships between two people, more recent literature focuses on trust in teams and groups (Ashleigh & Nandhakumar, 2007; Coppola, 2004; Jarvenpaa, et al., 1998; Sarker, Valacich, & Sarker, 2003). The role of trust is widely recognized in the literature on teams and team development and it has been described as a ‘need to have’ quality in productive online teams (Lipnack & Stamps, 2000).

In a review of the literature on trust, Sarker, et al. (2003) identified three streams of thought on trust relevant to virtual teams: 1) personality based trust, 2) institutional based trust, and 3) cognitive trust. They include in their paper an extensive discussion of other definitions of trust as well.

Personality-based trust is the level of trust that a person has developed at a young age and is shaped by the person’s caregivers, generally their parents (deVries, 1999). Rotter (1967) indicates that for many people this results in a general propensity to trust others. De Vries suggests that personality-based trust stays with an individual for life and that this influences their interactions with others (de Vries, 1999). Since it is not anticipated that personality based trust will change we did not measure this variable.

Institutional-based trust proposes that norms and rules of institutions that individuals are a part of influence their behavior. According to Berger, Berger, & Kellner (1973), these norms and rules manifest themselves in bureaucratic administrative structures as proper procedures, orderliness, predictability, and an attitude of moralized anonymity. This type of trust can potentially influence trust within a virtual team based on the belief that norms and institutional rules can influence an individual’s behavior when operating in the institutional environment. Brass, Butterfield and Skaggs (1998) state that organizational members typically have expectations of future interactions with others, and that these expectations instill at least minimal levels of trust.

Cognitive trust involves the idea that trust is based on our choices of whom to trust as we get to know people. Brewer (1981) explains it as based on “schemas or stereotypes” that individuals develop about their teammates from their impressions and other cognitive cues. McKnight, Cummings, & Chervaney (1988) indicate that cognitive trust can be further divided into three types of categorization processes that individuals use to develop trusting beliefs. These are 1) reputation categorization, 2) unit-grouping, and 3) stereotyping. Reputation categorization suggests that individuals with good reputations are trusted (McKnight, et al., 1988). Unit grouping refers to the concept that team members share common goals that make them see each other positively and trustingly (Kramer, Brewer, & Hannah, 1996). Stereotyping is described in detail below. All three of these categorization processes require time to get to know a person and to process that information for decision-making. However, Coppola (2004) suggests that since virtual teams in academia have limited time to become familiar with one another, they import trust and assign perceptions based on past personal and professional stereotypes.

Sarker et al. (2003) developed and validated a measurement instrument to measure institutional-based trust, personality-based trust and cognitive trust in virtual environments. Exploratory and confirmatory factor analyses were used to validate the instrument, following accepted research practice to ensure reliability and validity. In validating their measurement instrument, they further divided stereotyping into message-based stereotyping, technology-based stereotyping, and behavior-based stereotyping. Message-based stereotyping involves stereotyping based upon the messages exchanged by team members; technology-based stereotyping considers the knowledge of technology-related skill levels of remote teammates; and behavior-based stereotyping is based on perceptions of physical appearance and behaviors of the teammates. Table 1 lists the trust measures that Sarker, et al. (2003) identified in their analysis.

Table 1. Trust Measures.

Many studies indicate that building trust in virtual teams is the greatest challenge in creating successful, effective virtual teams (Coutu, 1998; Jarvenpaa, et al., 1998; Jarvenpaa & Leidner, 1998; Platt, 1999). According to Jarvenpaa & Leidner (1998), building trust in teams requires constant face-to-face communication and interaction, but this is the very quality that virtual teams lack. Kirkman, Rosen, Gibson, Tesluk, & McPherson (2002) state that the conclusion from research and consultants is that trust is very difficult to build and requires continual face-to-face communications. The challenge, therefore, for virtual teams is to build trust among members who rarely or never see each other.

Trust Development – Theoretical Background

According to Holton (2001), trust develops through frequent and meaningful interaction, where individuals learn to feel comfortable and open in sharing their individual insights and concerns. Several classic theories have questioned the ability of online systems to aid the development of the communication cues needed to develop trust and other interpersonal attributes that are needed to form successful teams. Three prominent theories addressing this are: (1) Media Richness Theory; (2) Social Presence Theory; and (3) Social Information Processing Theory.

Media richness theory suggests that media vary in the levels of richness according to the number of cues they are able to convey, the timeliness of the feedback, and the capacity of natural expression (Daft & Lengel, 1986). This theory suggests that rich media, such as face-to-face communication, are better suited for highly equivocal tasks, and leaner media, such as written or textual, are better suited for less equivocal tasks. Zack (1993) further indicated that face-to-face meetings are more appropriate for building a shared interpretive context among group members while online meetings are more appropriate for communicating within an established context.

Short, Williams, & Christie (1976) explain that Social Presence Theory suggests that the fewer channels available within a medium, the less attention is paid by the users to the presence of other participants’ interactions, and social presence declines as messages become more impersonal. It is felt this is caused in part by fewer nonverbal cues and social context cues innately found in LMSs which, in turn, negatively affect interpersonal impressions (Hiltz & Johnson, 1986; Rice, 1984).

However, other studies have found that virtual teams, if given enough time, do share relational information (Beranek, 2005; Chidambaram, 1996; Walther, 1992; Warkentin & Beranek, 1999) and that the sharing of this information may improve performance (Weisband, 2002). While it has been found that computer support initially lowers relational intimacy, the members of such teams will develop ways of exchanging socio-emotional communication, and, over a period of time, groups using computers will gradually develop close relational ties (Burke & Chidambaram, 1995; Chidambaram, 1996). Recent analysis of research on comparisons of traditional on-campus classes to web-based courses indicated that students in web-based courses do as well if not better than students in on-campus courses (Weber & Lennon, 2007).

Social Information Processing (SIP) theory suggests that relational intimacy may take longer to develop in virtual teams. Walther (1996) indicates that SIP theory recognizes that individual messages in virtual communication have less social information due to the lack of accompanying nonverbal cues. This implies that virtual teams may need more time to exchange enough social information to develop relational links as well as to manage the task at hand. The extension is that computer-supported groups, given adequate time, will exchange enough social information to develop strong relational links and thereby foster trust. Results indicate evidence of such shifts among members of computer-supported groups. Using these results, Walther (1996) suggests that virtual communication does not differ from face-to-face communication in terms of the substance, but in terms of a slower rate of transfer. However, most academic virtual teams meet over the course of a semester and are then disbanded, thereby not having enough time to develop the types of links needed for effective, efficient communication.

To further complicate trust development, research indicates that trust may have an impact on the effectiveness of team member communication (Beranek, 2005; Jarvenpaa, et al., 1998). So, continual face-to-face communication is needed to develop trust, but trust impacts the effectiveness of communication. Academic teams have the additional challenge of limited duration to further hinder trust development.

This study investigates trust development by measuring initial trust levels at the beginning of the semester, then measuring trust levels at the end of the semester. The change in trust over the course of a semester is examined for online teams versus face-to-face teams. Through this, the initial research question of whether students in online classes can develop the levels of trust comparable to those in traditional classes will be answered. In addition, this paper will present the evaluation of the differences in initial trust levels and a comparison of the difference in the rate of trust development between the two learning environments.

Method

Procedure

The data used in this study was collected through surveys conducted in two sections of a course in an MBA program at a major western university. One section was a traditional, face-to-face (FTF), on-campus class and the other was an online class offered through the online MBA program. Both programs are accredited by AACSB International, the Association to Advance Collegiate Schools of Business. The online course is defined as one in which 100% of the material is delivered online. In this environment, teams that work together communicate strictly through LMSs, and thus are online teams.

Both sections in the study covered identical material, were taught by the same professor, and used the same materials, assignments, cases and exams. Both courses lasted for 16 weeks and course material was scheduled for specific weeks with exam weeks and required due dates for assignments. The online course was not self-paced, but followed the same schedule as the campus class. The only difference was in the delivery of the material. The FTF class was taught with scheduled meeting times. The online class delivered the material through a LMS, using an asynchronous web-based course platform in which students could access course material at any time. There were no scheduled or required team meetings for either the online class or the face-to-face class. Furthermore, the students in the online course were geographically dispersed throughout the United States and internationally. Thus, it was necessary that students in the online course communicate electronically.

Throughout the semester, the students in each class were required to complete four team projects. These projects were detailed case analyses and generally one week was given from when material was covered to when the assignments were due. However, all students did have access to all four cases from the beginning of the semester, and could begin on them at any time.

Several steps were taken to emphasize the importance of the team projects. Each case was 10% of the final grade, for a total of 40%. As this represented a significant portion of the course grade, students tended to take them seriously. Also, team members were required to evaluate their teammates (and themselves) twice during the semester – at midterm and at the final exam. Members were rated from 1-4 with 4 being the highest on the following criteria:

• Participated in group discussions
  
• Performed assigned tasks
  
• Assisted other group members in learning
  
• Quality of participation

It was emphasized that team members’ grades could be adjusted negatively based on poor peer evaluation.

Teams in both classes were given pre-questionnaires to form a baseline for comparison and post questionnaires to track changes in trust perceptions. Figure 1 provides a timeline for the semester indicating when the questionnaires and evaluations were administered and when the teams were formed and the team projects were performed.

Figure 1. Timeline of Tasks, questionnaires, and evaluations.

Teams

The team selection procedure used was the same in both classes. Students were given the opportunity to establish their own teams during the first week of class. The FTF students could establish teams during the first class meeting, while the online students had access to the complete course roster and e-mail capability through the course platform. Those students who were not on a team at the end of the first week of classes were assigned to a team by the instructor. For the online course, 17 students self-selected team members. The instructor then assigned those who had not self-selected. Three teams were completely self-selected, three teams were completely instructor assigned, and two teams were partially self-selected with the instructor assigning additional students to reach a minimum of four team members. For the FTF class, all teams were self-selected.

The class sizes were similar with 39 students in the FTF class and 33 students in the online class for a total of 72 students. Final team sizes ranged from three to five in the FTF class and four to five in the online class. Table 1 summarizes the composition of the student teams for both the campus and online classes.

Table 2. Team Data by Class.

Measures

The measurement instrument used in this study was developed and validated by Sarker et al. (2003). The questionnaire was designed to measure the different dimensions of trust in virtual teams. The construct of trust was divided into institution-based trust and cognitive-based trust. Cognitive-based trust was further divided into message-based stereotyping, technology-based stereotyping, behavior-based stereotyping, reputation categorization, and unit grouping. The survey instrument contained 31 questions to measure each of the six dimensions.

Reliability and Validity of the Instrument

In developing and validating this instrument, Sarker et al. (2003) addressed content validity, discriminant validity, and convergent validity. Further, they used Cronbach’s alpha to further divide cognitive trust into the additional dimensions discussed above. In this study, there were four administrations of the survey instrument: beginning of the semester FTF, end of the semester FTF, beginning of the semester online, and end of the semester online. Cronbach’s alpha was computed to confirm reliability for each trust dimension on each of these survey administrations. The Cronbach’s alpha ranged from 0.770 to 0.987 with only 3 of the 24 measurements being below 0.800. These are well above the generally accepted threshold of 0.70 (Hair, Black, Babin, Anderson, & Tathem, 2006).

Details of the survey can be found in Sarker et al. (2003). Table 3 lists the final number of questions used to measure each dimension.

Table 3. Trust Measure Questions

For the pre-test and post-test administration, the instructions for completing the survey were slightly different. Both used Likert scales with ratings of one to seven with one being “strongly disagree” and seven as “strongly agree”. However, for the pre-questionnaire, the instructions were to consider “EXPECTATIONS” of working with a team in this class”, while for the post-questionnaire, the instructions were to consider “EXPERIENCES” of working with a team in this class”.

A few minor adaptations were made to the survey for use in this study. First, slight wording changes were made to accommodate the different technologies used in this course platform from those used in the Sarker et al. (2003) study. For example, several of the items measuring message-based stereotyping mention the use of videoconferences. As videoconferences were not used in this study, this was eliminated from the survey text. Also, since this instrument was developed for use for virtual teams, minor wording modifications were made for use with the FTF class.

Results and Discussion

Given that the survey was conducted both at the beginning and end of the semester, a Repeated Measures Analysis of Variance data analysis technique is appropriate to investigate our research question. Each of the six dimensions of trust will be investigated independently. With all surveys appropriately paired by respondent, our final sample size was 27. While the sample size is somewhat small and non-normality is a possibility, Green & Salkind (2003) indicate that departures from normality may result in decreased power of the test. With decreased power, some significant results may be missed, but incorrect conclusions would not likely be drawn.

In the following discussion, TIMING refers to the pre-questionnaire and the post-questionnaire administered as shown previously in Figure 1 and is the repeated measure variable. CLASS FORMAT refers to the FTF team responses (from the campus class) and online responses (from the online class) and is the between subjects variable. Scores were computed for each dimension shown in Table 3 by averaging the responses for each item measuring that dimension. These scores were then used for all subsequent analysis.

Given our research question: “Can students in online classes who communicate virtually develop levels of trust comparable to those of students in traditional classes who communicate face-to-face?”, both interaction effects and main effects are important. The interaction effect determines whether changes in trust over time differ for the two class formats. The main effect for TIMING shows whether the change in levels of trust overall was significant over the course of the study. The main effect for CLASS FORMAT investigates whether class format as a whole results in different levels of trust.

Analysis of Interaction Effect: TIMING*CLASSFORMAT

Consistent with standard practice, the interaction effect is considered first. The results indicate no significant differences. The p-values are shown in Table 4.

Table 4. F-test Results for TIMING*CLASSFORMAT.

*Significant at α = 0.10
**Significant at α = 0.05
***Significant at α = 0.01

The finding of no significant differences indicates that the online class was not at a disadvantage in terms of building trust among team members for any of the dimensions of trust. This is contrary to past research which indicated that building trust requires constant FTF communication and that students in online classes may have limited social interaction thereby endangering trust development (Jarvenpaa et al., 1998).

A possible explanation for this finding which has important implications for online teaching is that in this study the teams were required to work together in solving the cases and were therefore, in a sense, ‘forced’ to communicate on a regular basis with their teammates. Recent research indicates that there may be a link between early communication in virtual teams and the development of early trust (Jarvenpaa, Shaw, & Staples, 2004). This suggests that one strategy for teaching online courses is to develop situations where students are required to interact with fellow students. In this study the teams started work on the cases early in the semester and were required to interact online within their teams early on. They also worked within the same teams throughout the semester as they analyzed the remaining three cases. This might indicate that it is necessary for teams to continually interact to maintain high trust levels.

The primary research question in this study involves determining whether students in virtual teams can develop the levels of trust comparable to those of students in FTF teams. The analysis in Table 4 indicates that over time, the change in trust was the same for both class formats, but does not provide any information about the actual levels of trust developed.

Analysis of Main Effect: TIMING

While testing TIMING does not directly address the question of overall trust level differences between the two class formats, it does help show whether, with both class formats taken together, the levels for the trust dimensions changed over time. With the exception of Institution-based trust (I), which is based on the norms and rules of the individual’s organization (Berger et al., 1973), one would expect trust levels for the other dimensions to increase over the course of the semester. An increase would be expected because these are all dimensions of cognitive trust which are based on cognitive decisions and which all require getting to know a person’s reputation and interacting with them. As team members work together over the course of the semester and learn more about each other, one would expect these other dimensions to increase.

There were significant differences for Message-based trust (MS), Technology-based stereotyping (TS), Behavior-based stereotyping (BS), and Reputation categorization (RC). Table 5 shows the marginal means and p-values for differences due to TIMING. The marginal means indicate that, as expected, for all significant differences, the change was an increase over the course of the semester.

Table 5. F-test Results for Mean Difference for TIMING.

*Significant at α = 0.10
**Significant at α = 0.05
***Significant at α = 0.01

From Table 5 we see that for Institution-based trust (I) and Unit Grouping (UG) there was no significant change over the course of the semester. The result for Institution-based trust (I) is as expected. Institution-based trust depends on expectations of the institution and the norms and rules of the institution, which in this case was the university. One would not expect this to change over the course of the semester. Unit grouping (UG) refers to the common goals shared by team members. The questionnaire asked the respondent to rate whether the team members’ goals were the same as his or her own. One might expect the perception to change as the respondent got to know the team member. However, according to the data, over time the perceptions of fellow team members’ goals remained the same.

As expected, all three types of stereotyping increased significantly over the course of the semester as did reputation categorization. Each of these dimensions of trust requires getting to know the person’s reputation and interacting with them. Despite the short time frame of the semester, trust did increase over time for both course formats. While Walther (1996) indicated that teams communicating via online systems would need more time than their FTF counterparts to develop the relational links needed for trust development, these results combined with the prior result that change over time was the same for the two class formats indicates that the 16 week span of a semester was sufficient time for trust to improve. The implication for online learning is that given an appropriate course design that fosters early interaction regardless of course format, a typical semester-long course does provide sufficient time for trust development.

Analysis of Main Effect: CLASS FORMAT

For CLASS FORMAT, there were fewer significant differences. Message-based trust (MS), Behavior-based stereotyping (BS), and Unit Grouping (UG) all were significantly different for FTF versus online. For all three of these dimensions, the marginal means indicate that the online class scored each measure higher than the FTF class. The marginal means and p-values for differences due to CLASS FORMAT are shown in Table 6.

Table 6. F-test Results for Mean Difference for CLASS FORMAT.

*Significant at α = 0.10
**Significant at α = 0.05

Even though both classes taken together showed the same amount of change over the semester for all trust dimensions, the online class showed significantly higher levels of trust for message-based stereotyping (MS), behavior-based stereotyping (BS) and unit grouping (UG). This indicates that team members in the online class started with relatively higher levels of these types of trust and maintained these relatively higher levels through the end of the semester. This is an interesting finding as a concern based on the literature was that online students might not be able to develop the same trust levels as their on-campus counterparts. The findings clearly show that, in this study, online students actually have higher initial trust expectations of their teammates when compared to campus students. One explanation for these higher initial levels is that the online teams may have had higher expectations than the FTF teams. As online students have to rely solely on written messages, they may be more active in communicating early on and on a regular basis. In particular, interactions early on contribute most to successful team performance (Weisband, 2002).

Since message-based stereotyping involves correspondence, it is not entirely surprising to see that the online students rated this dimension higher than FTF. With the online students communicating with written messages, there would likely be a higher volume of individual communications compared to FTF teams meeting together. However, it is surprising to see behavior-based stereotyping higher for online students. The survey questions consider excitement, enthusiasm, and seriousness. One would expect that these behaviors are less evident to team members communicating strictly through written means.

Implications for Online Teaching

In an effort to better understand differences in trust development for online versus campus students, this study investigated whether students in online teams can develop levels of trust comparable to those of students in FTF teams during the course of a semester. There were three major findings in this study with implications for online teaching.

First, the change in trust levels over the course of a semester were the same for both course formats. This is an important finding as it indicates that despite the concerns of researchers (Holton, 2001; Jarvenpaa & Leidner, 1998) online teams may develop trust at the same rate as FTF teams. From an online teaching perspective, this means that the problems raised in the literature about online education that trust plays a role in mitigating retention of students (Carr, 2000), and the problem of ‘fading back’ or non-participation (Haythornthwaite, et al., 2000) may not be as much of a concern as previously thought, at least given the 16 week time span of this study. However, as mentioned in the results and discussion section, the course design in this study did require students to connect early and work together over the course of the semester and the “motivation” was included in the form of team peer evaluations potentially impacting grades.

A second finding is that over the course of the semester students in both classes had significant increases in four of the six trust dimensions. This has implications for academic teams in general in that despite the short duration of these teams, trust levels can increase over the course of the semester. From an online teaching standpoint, the fact that the students are communicating via a LMS does not appear to hinder their trust development.

A third significant finding is that even though the online and FTF teams both increased their levels of trust over the semester, the online teams had higher initial levels of trust. While this might be an isolated occurrence particular to this sample, one possible explanation is that students who have taken online classes previously may have higher expectations of the process and thereby start out with higher levels of trust. The course in which this study was conducted is one which has several prerequisites, so it would not be taken in the first semester of the student’s program of study. This finding may also be an indication that swift trust is occurring with the online students bringing in stereotypes from other situations (Jarvenpaa, Knoll, & Leidner, 1998; Meyerson et al., 1996).

Overall, this research offers some interesting implications for online education instructors, primarily from a course design standpoint. This study was undertaken in a typical 16-week semester. Online courses of shorter duration may suffer from learning issues related to trust development. Also, these findings suggest that student teams may benefit from being required to interact with fellow team members early on in the class by having a group exercise or project that the teams are required to start on early in the semester. Having team projects spaced throughout the course of the semester may also support trust development comparable to campus teams. Additionally, requiring peer evaluation and including grade implications may offer more incentive to the team members to interact and take part in the work.

Conclusion and Suggestions for Future Research

It appears, based on these findings, that course design may have contributed to the positive results obtained. Future research should include courses with different course design in order to further validate these findings and determine other beneficial design factors.

The finding of no difference in technology-based trust (TS) is another area that warrants further investigation. It may be that this is no longer a trust issue given the dramatic pace of technological change and the pervasive use of technology since these dimensions of trust were identified in 2003.

Another area for future research that arises from these findings is to determine the impact on trust levels, if any, of previous experience in online education courses. Future research should also look at trust development for academic versus industry teams following individuals longitudinally to consider whether academic team experience impacts future team trust development in industry settings. Findings from such a study would have implications for curriculum development.

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Peggy M. Beranek is an Associate Professor of Information Systems at the University of Colorado - Colorado. E-mail: mberanek@uccs.edu

Dr. Monique French is an Associate Professor of Operations Management at the University of Colorado - Colorado. E-mail: mfrench3@uccs.edu

Appendix

FTF Course Questionnaire Items