Enhancing Learning Experiences in Partially Distributed Teams ...

Proceedings of the 42nd Hawaii International Conference on System Sciences - 2009

Enhancing learning experiences in Partially Distributed Teams: Training students to work effectively across distances Rosalie Ocker Pennsylvania State University [email protected]

Dana Kracaw Global Business Services [email protected]

Mary Beth Rosson Pennsylvania State University [email protected]

Abstract Three training modules were designed to decrease ingroup dynamics in Partially Distributed Teams, which have two or more geographically separated subteams. The action research oriented study included 84 student PDTs with nearly 700 members, working on high-level software requirements. Results indicate that the training improved outcomes in terms of shared identification, trust, awareness, coordination, competence, conflict, and team performance.

1. Introduction Information technology (IT) teams are often partially distributed teams (PDTs), consisting of two or more subteams that are separated geographically. While members of a given subteam are co-located, they collaborate remotely with members of other subteams. PDTs are increasingly prevalent for information systems development, with off-shoring, outsourcing, and insourcing practices. Often a PDT spans multiple time zones and countries, as in the case of global software development [2, 4]. Our prior work with regionally-based student PDTs revealed that few if any have experience collaborating in virtual teams in general, and in PDTs specifically [23, 43]. With the goal of providing students with deep learning experiences related to work in PDTs, we have been conducting a large-scale multi-semester investigation that has included students from universities in nine countries. Each semester teams work on a four-week project to develop the high-level requirements and user interface design for an emergency management information system. In this paper, we describe three training modules that were developed to scaffold

Starr Roxanne Hiltz New Jersey Institute of Technology [email protected]

Linda Plotnick New Jersey Institute of Technology [email protected]

students’ PDT collaboration behavior. Each “module” is a set of activities designed to meet specific goals; each is self-contained and is generic in the sense that it could be used for teams undertaking a wide variety of main tasks. Our research question is: How does training affect team interaction processes and outcomes, in terms of 1) overall team performance and 2) effects on six intervening variables that are in turn likely to affect performance in PDTs: trust, shared identity, awareness, coordination, conflict, and competence. This paper is organized as follows. We review problems that are common to Virtual Teams (VTs) in general and PDTs in particular, with emphasis on “us vs. them” ingroup team dynamics. We describe the six constructs measuring intervening variables that are likely to influence PDT interaction and performance, and summarize prior research on training for effectiveness in distributed teams. The research method, a form of action research, is then described, including the tasks performed by the teams, the collaboration tools used, the multiuniversity context of the research, and the contents of the training modules themselves. Because of the need to control for differences in performance among university sites, analysis of covariance is used for each of the seven variables of interest. Results of the analysis are presented and we conclude with limitations and plans for future studies.

2. Review of literature 2.1. Ingroup team dynamics: Us vs. Them Social categorization theory and Social Identity Theory [54] suggest that people derive social identity

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Proceedings of the 42nd Hawaii International Conference on System Sciences - 2009

primarily from membership in groups. Demographic differences spawn differences of opinion and divergent viewpoints which result in people categorizing themselves into “us vs. them” groupings. These subgroups develop separate identities and exhibit ingroup dynamics, defined as increased interaction with and preferential behavior towards members of one’s subgroup; reduced trust and team cohesiveness; and increased conflict between subgroups. Ingroup dynamics impairs team effectiveness and performance (e.g. [28]). In PDTs, team members within a site are physically co-located. They thus share the same work context and are able to communicate face-to-face, a communication mode that increases the likelihood that co-located team members will develop a shared identity [21]. Lack of a shared context between team locations can have significant negative effects on overall team development and performance [52]. Furthermore, team members at distant sites must rely upon information and communication technology (ICT) to communicate. Indeed, recent research indicates that PDTs are especially vulnerable to ingroup team dynamics [43, 47].

2.2. Variables likely to influence PDT interaction and performance Six variables have been shown to be key influencers of both traditional and virtual team interaction and performance; we also expect them to influence PDTs. Two of these variables – degree of shared identification and trust – are socio-emotional constructs, emphasizing how individuals feel about their team. A second pair of variables – degree of awareness and coordination – pertain to procedural aspects of team management. The remaining two – degree of perceived competence and conflict – have a more behavioral construal, capturing aspects of how members see their team interacting and operating. Because any of these variables can have important impacts on PDT processes, training aimed at addressing the problems of PDTs should consider each of these intervening variables. The three training modules we developed targeted these intervening variables, as described in section 3.4. Shared identification with the team by its members is important in terms of enhancing team cohesion, reducing conflict, and increasing motivation [29, 32]. Due to the reduced contact of members in a virtual context, the cohesion that is promoted by shared identification may be especially important to team functioning [21, 57]. Trust can be defined 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” [40, p. 712]. It includes beliefs that the trusted party, for example a distant subgroup, will fulfill its commitments [35], and that it will behave in an ethical [22] and socially appropriate [59] manner. Trusting relationships in any team reduce transaction costs, increase cooperation, promote respect, and lead to better outcomes [24]. However, trust is difficult to establish in a virtual context [25]. Awareness of members is important to the success of virtual teams [9, 56]. Awareness refers to an understanding of others’ activities and provides a context to interpret behavior [11, 12]. Weisband [56] describes five types of group awareness: self awareness is information about another’s activity at a specified time; activity awareness is knowledge of others’ project-related activities; process awareness is knowing what tasks fall within project phases; social awareness is knowledge about others outside the context of work; and availability awareness is knowing whether others are available to meet or participate in an activity. Coordination can be defined as the additional work required when multiple individuals work together to accomplish a goal, compared to individuals working alone [36]. Time-limited teams must coordinate their efforts temporally [39]. Temporal coordination mechanisms include milestones, schedule deadlines, time on tasks, and pacing of effort between team members [44]. Coordinating member efforts across distance is challenging, and becomes more difficult when the team encompasses multiple time zones and/or cultures [31, 48, 51]. Research indicates that teams who establish a temporal rhythm of work (a combination of synchronous and asynchronous communication) and norms for collaboration (e.g. acceptable turn-around time for feedback on work products) have more effective performance [41, 39]. Competence is concerned with beliefs about the ability of the team. It melds aspects of group potency and collective efficacy. Group potency is the collective belief of group members that the group can be effective [18]. Similar to group potency, collective efficacy is the members’ beliefs that the team can succeed at a specific task [34]. We include both of these concepts in the competence construct. Conflict can be defined as disagreements among team members due to perceived incompatibilities or differing viewpoints or goals [27, 47]. Not surprisingly, conflict is normally problematic for team performance [28], although some researchers have found that conflict tied to task disagreements may increase team creativity [1, 28, 49]. Research

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indicates that conflict may be more prevalent in virtual contexts [42, 21], perhaps because its emergence and resolution is more difficult to track. The lack of immediate feedback [30] as well as time zone and cultural differences may exacerbate conflict [13, 37].

2.3. Training for Partially Distributed Teams We did not locate any prior studies of training for PDTs, but numerous studies suggest that fully distributed VT members would benefit from training on the intricacies of working in a virtual team. For example, Zigurs [58] recommends training for virtual team leaders; Cramton [9] recommends educating virtual team members about the pitfalls of the failure to share situational information and the tendency to make assumptions about remote partners and locations. Training on diversity awareness in distributed teams is recommended by Sarker and Sahay [51]. Rosen et al. [50] note that organizations today do not adequately train members in virtual team work. The need to prepare students to be effective members of VTs is recognized, but to date, little headway has been made beyond introducing VT projects into the classroom setting (see [6, 45, 14] for recent case studies). Below we summarize the few empirical studies that manipulated VT training. Tan et al. [55] devised a dialogue technique designed to help virtual teams quickly establish a shared understanding among team members. The dialogue technique consisted of three stages, including ‘small talk” and collaboration to build a team mental model around good communication practices that the team agreed to adopt. The dialogue technique improved teams’ relational development and decision outcome. Beranek and colleagues conducted two studies regarding training [60, 61]. Trust training was developed for initial and later team stages based on the trust building and maintenance behaviors identified by Jarvenpaa and Leidner [25]. Relational Links training consisted of training on teamwork, drawbacks to electronic communication, and netiquette rules. Findings indicate that teams which received either or both types of training reported higher levels of cohesiveness, perceptions of the process and trust compared to teams that did not receive training.

3. Method 3.1. Participants and sites

students participated. Teams averaged 8 members, divided with four members at each of two sites. Participants were drawn from nine universities in three global regions (North America, Europe, and Asia) which provided considerable variation within each of three dimensions of distance. Geographic distance between subteams varied between a minimum of 190 miles to a maximum of ~8,000 miles. Temporal distance spanned eight time zones with a minimum of 0 hours to a maximum of 14 hours. A variety of national cultures were represented. The data set resulting from this diversity in selected sites increases the generalizability of research findings.

3.2. Distributed team projects The project task was designed to be appropriate for students from different geographic regions and cultures. We developed two project task descriptions involving emergency management information systems (EMIS); the projects were isomorphic in their specification and requirements. The project spanned four weeks, which gave us enough flexibility to accommodate a wide range of university calendars. We chose to focus on the front-end of the development process, (high-level requirements and user interface design) because of the relatively short time-frame and the heavy emphasis on communication and on developing a shared understanding of the problem area, key challenge areas in distributed work (for reviews see [19, 38, 46, 48]).

3.3. Collaboration Platform We implemented an open source web-based communication and content management system (Drupal 4.7, see drupel.org), enhanced with additional functionality (via third-party plug-ins). Upon logging in, the system presents participants with a description of the PDT project including instructions, milestones, templates, and deliverables. The system provides a threaded discussion board; a file sharing repository; shared document creation and editing; as well as a project calendar. Training modules were added in semester three. Each team had its own electronic workspace; if the team desired, the space could be divided into additional “private” spaces for subteams, leaders, or other individual team members. All project “deliverables” were required to be posted online, using the PDT system. The participants were free to use additional technologies such as instant messaging, email, and phone.

The research presented here occurred over three consecutive semesters of a field study conducted at multiple universities. A total of 84 teams with 689

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3.4. PDT project procedure Each PDT project spanned four weeks. Teams in all three semesters participated in the PDT project activities and deliverables, as shown in the top part of Figure 1. The teams began with a PDT tutorial, selfintroduction, and completion of a team contract. During the second week, team members brainstormed regarding the functions to be included in the EMIS. During the third and fourth weeks, teams worked to complete the EMIS proposal.. A proposal template was provided; teams had to complete sections pertaining to goals and users of the EMIS, high-level functional requirements and user interface design, Week 1 SelfActivity Introduction Project activities & Team Contract Deliverables (all Deliverable semesters) GOAL TRAINING ACTIVITIES & DELIVERABLES (added in semester 3)

ACTIVITY

MODULE 1 Getting off to a good start; awareness and coordination. 3 scenarios on PDT challenges Team Contract

and next steps. Only teams in semester 3 completed the PDT training modules shown in the bottom part of Figure 1. We designed training activities aimed at the intervening variables and processes that were identified. For example, the three scenarios in Module 1 gave fictional cases of problems in coordination and awareness that can occur when there is no face to face communication, and thus were meant to stimulate team members’ ideas about procedures that could be built into their team contract that would avoid these problems.

Week 2 Brainstorming list of EMIS functionality MODULE 2 From “Us vs. Them” to “We” trust , shared identity, perceived competence. Interview distant team members Team Web page

Week 3 Week 4 Work on EMIS project proposal EMIS proposal MODULE 3 Establish/maintain a positive team trajectory; decrease conflict and improve coordination. Team Assessment

Corrective Action Plan Figure 1. PDT Project Activities and Deliverables

DELIVERABLE

3.5. Data collection Both quantitative and qualitative data were collected during each of the semesters. A Background Survey administered prior to the start of each team project collected demographic data. The Post survey collected data pertaining to the dependent variables. Participants also completed weekly personal reflections, including team dynamics, problems, and concerns.

4. Research approach The design of training modules to enhance PDT performance falls within the realm of design science, a paradigm in which “knowledge and understanding of a problem domain and its solution are achieved in the building and application of the designed artifact” [20, p. 75]. Such a process is quite iterative; the artifact changes as feedback is obtained from users. Because the components of the artifact are a “moving target,” a form of action research, for instance the “Soft Systems

Methodology” described by Checkland [5], is appropriate to provide input into the evolving design. Action research can be viewed as a post-positivist research method that is “empirical, yet interpretive… experimental, yet multivariate… and observational, yet interventionist” [3, p. 236]; see also [10]. Iterative cycles – typically consisting of five repeating phases – have been proposed as a mechanism for introducing scientific rigor into action research [53, 3, 33]. These phases include: diagnosing; action planning; action taking; evaluating; and specifying learning. In the Diagnosing phase, the situation is analyzed and problems that may be aided by information technology are identified. In our case, we observed the problems that teams had in semesters one and two. In Action Planning, we began planning how a combination of software tools and a set of training modules for effective interaction between subteams could improve those observed problems. Our Action Taking implemented the designs for a modified tool (introduced in the second semester) as well as a set of

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training modules for students (introduced in the third described above, a significant challenge for PDTs is semester). In the Evaluation phase we are assessing finding a way to function as a coherent team rather whether the desired effects were achieved (i.e., is the than as separate subteams. While some participating artifact created likely to be adapted and used in such a faculty addressed the “us vs. them” tension in an way as to obtain the desired objectives). Finally, informal and ad hoc fashion, the pervasiveness and Specifying Learning occurs when lessons learned from seriousness of this phenomenon indicated that all iteration are documented and used to inform designers participants might benefit from formal training. regarding objectives for the next phase of design. 3) Recognizing and accommodating different To identify problems, in semester 2, participant “distancing” factors. When team members must weekly personal reflections were content coded, interact with members at other locations, several following the grounded theory methodology [17]. The different factors (e.g. geographic, cultural, and qualitative analysis suggested three areas in which to temporal) can increase the perceived distance, making enhance our PDT project materials. collaboration difficult. The simple fact that 1) Anticipating and supporting a team development communication is mediated rather than face-to-face has life cycle. Two fairly regular patterns of team evolution important implications. When subteams are from were identified. Up to the project mid-point, most different cultures, new complexities relating to cultural teams share a similar development path. At the start of norms can arise (e.g., use of formal versus informal the project, the majority of students express excitement language, explicit expression of respect or disrespect, about the unique experience of collaborating with deference to leadership). When some of the team students from other universities and cultures. This is members are in a different time zone, additional followed by a period of anxiety and concern, as they problems can arise, for example with perceived begin to experience the challenges of distance responsiveness under deadline pressure. Interestingly, collaboration. However, after the project mid-point, results indicated that teaming across time zones was two divergent paths emerge. For those teams on a especially difficult for members to adjust to, perhaps positive trajectory, separate subteam identities give even more so than cultural differences. Students need way to an overall team identity, as trust between to learn about each type of distancing factor, how to subteams increases based on initial constructive recognize when it is affecting the team’s interactions, interaction and shared accomplishments. These teams and strategies for resolving the problem. become very focused and task-oriented as parts of the project solution begin to develop, followed by a 4.1. The three training modules celebratory attitude as they see success emerging. For Research indicates that virtual teams with a solid those teams that experience a negative trajectory, a beginning are teams that are most successful [8]. downward spiral of frustration, conflict, and Therefore, the goal of the first of the three modules is disenchantment ensue as teams struggle to meet to get student teams off to a good start. Module One is deadlines; subteams maintain separate identities and completed during the first week of the project, and work against each other as they try to complete the introduces students to problems that they are likely to project. Both students and faculty need learning encounter during their four week PDT project, via a materials that will inform and assist them in series of three scenarios. The problems addressed in anticipating, analyzing and aligning their team each of the scenarios are listed in Table 1. development life cycle. 2) Diagnosing and addressing the “us versus them” tension. As evidenced by the negative trajectory Table 1. PDT Problems Addressed by the Scenarios Scenario 1: Typical problems encountered during week one (project start-up) 1. Lack of initial contact from subteam or part of subteam 2. Lack of response from some members 3. Slow start Scenario 2: Typical problems encountered during week two 1. Lack of interaction between subteams 2. Miscommunication regarding methods for communicating 3. Poor project management Scenario 3: Typical problems encountered during week three 1. Conflict within group 2. Different quality of work 3. Lack of communication on university events 4. Lack of collaboration

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Each scenario relates to one or more sections of the team contract. Each subteam works through the scenarios and prepares a draft of the team contract; subteams then compare and discuss the contract drafts to formulate a single team contract. The goal of Module 2, completed during the second week of the project, is to help subteams move from an “us versus them” mindset to a “we” or team mindset. Teams work through Module 2 as they begin actual work on the PDT EMIS project task. Module Two includes two activities with deliverables: conducting member interviews and creating a team web page. The Member Interviews and Team Web Page activity is designed to jump-start informal interaction between subteams through a fun and creative endeavor. In this activity, each student must interview a distant subteam member and write-up the results of the interview questions and answers. Using these interviews, the team is instructed to collaborate to create a Team Web Page. Interview questions are suggested and required team web page content is specified; teams are encouraged to personalize their page designs and add additional information. The goal of module 3 is to help teams establish and/or maintain a positive team trajectory, by helping teams in evaluating the trajectory they are on and in making necessary adjustments. This module consists of two parts: (a) the 3 Bin Assessment and (b) the Action Plan. In the 3 Bin Assessment, each subteam evaluates the team by sorting aspects of team interaction and performance into one of three “bins” – great, fair, and “not so great.” Subteams share their assessments with each other and then collaborate to complete the Action Plan, where they devise corrective actions to address the problem areas.

5. Data analysis and results The quantitative analysis presented here is based on data collected during the post-project survey administered during each of the semesters to all PDT members, after they had delivered their shared project. The survey contained several scales designed to measure the constructs relevant to our research model. The competence measure was adapted from Jarvenpaa et al. [25]. The conflict and shared identity scales were adapted from Mortensen and Hinds [42]. The trust measure was adapted from Jarvenpaa and Leidner [26] and was measured in the post survey at the individual level. The awareness scale was developed based on the literature, as we could not find a pre-existing scale. The ease of coordination measure was adapted from Faraj and Sambamurthy [15]. The team performance scale

was adapted from Mortensen and Hinds [42]. The awareness, competence, conflict, coordination and trust ratings gathered judgments about distributed subgroups; shared identity and performance were judged with respect to the team as a whole. All items were measured using a 7-point semantic differential response scale. Scale reliability: Rather than using Cronbach’s alpha, which represents a lower bound estimate of internal consistency due to its assumption of equal weighting of items, a better estimate can be obtained using the composite reliability [7, 16]. Unlike alpha, this measure is not influenced by the number of items in the scale. It is based on the ratio of construct variance to the sum of construct and error variance. The reliability of all of our measures quite high in most cases (around .9 or above), with the exception of the trust construct, which is still good at .80.

5.1. ANCOVA results Post survey responses were received from 462 participants across eight universities1: 100 from semester one, 96 from semester two, and 266 from semester three. With respect to the contrast of training conditions, 196 respondents from semesters 1 and 2 received no training, while 266 from semester 3 did receive training. The geographic, temporal, and cultural distance variations among universities (which of course is bound up with cultural differences in this crossnational study) were broad, but it was impossible to balance these across no-training and with-training semesters. An analysis of variance revealed a number of differences across universities on our dependent measures. Therefore, results presented in this section are based on an analysis of covariance, where the eight universities were included as covariates. The descriptive statistics and the results of the ANCOVA for the seven variables of interest are shown in Tables 2 and 3, respectively. The results show that participants who completed the training modules in semester three reported significantly higher levels of trust, shared identity, awareness, coordination effectiveness, and perceived competence of, and less conflict with, the distant subteam. Furthermore, these participants reported significantly higher levels of perceived team performance compared to participants who did not complete the training modules. The strongest effect of the training modules was on “awareness” of the other 1

There were no respondents from one university in Asia.

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team members and their activities, greatly lessening the tendency towards “out of sight, out of mind.” This is probably a key contributor to the increase in shared identity (more perceptions of the whole team as “we” and “us”), which in turn contributes to the improvements in team performance. Thus, these results suggest that training may be an important element for success in software development PDTs.

6. Discussion and conclusions In this paper we have described an instance of action research that led to the introduction of training materials specifically designed to ameliorate problems observed for student PDT teams in the early semesters of the investigation. In the Evaluation phase, we found that the training modules were quite beneficial in reducing the separateness of “us vs. them” induced by collaboration across distant sites, and in improving team performance. For instance, most groups “with Table 2. Descriptive Statistics for Dependent Variables

Trust

Shared Identity

Awareness

Coordination

Ability

Conflict

Team Performance

Training

Mean

Std. Deviation

without with Total without with Total without with Total without with Total without with Total without with Total without with Total

4.32 5.13 4.78 4.83 5.35 5.13 3.70 4.77 4.31 3.90 4.52 4.25 4.50 5.32 4.97 2.41 2.07 2.21 4.52 5.07 4.84

1.39 1.49 1.50 1.65 1.50 1.58 1.59 1.49 1.62 1.53 1.28 1.43 1.71 1.39 1.59 1.35 1.10 1.22 1.47 1.19 1.34

training” reported more positive ratings for many team variables of interest (e.g., trust, shared identity), with positive ratings in the range of 4+ on scales ranging from 1-7. It is notable that even though the results for

awareness were strongest, perceptions of awareness remain problematic for these teams; in this case the average for teams moved from 3.70 (a negative rating) to a just slightly positive 4.77. Thus, there is still much progress to be made in increasing the awareness of subteam members in PDTs about the status and activities of members of the remote subteam(s). The analyses we conducted treated the training modules as a single effect rather than as separate training interventions. However, we also included more detailed probes to investigate which module(s) the students experienced as most effective. Thus in the post survey, respondents were asked to rate each training module in terms of: increasing familiarity with distant team members, decreasing perceived distance between subteams, and helping subteams become a single team. We found that module two (member interviews and team webpage) was rated most highly for all questions, but especially in terms of increasing familiarity with distant members.

6.1. Methodological caveats The training modules, with their weekly activities and deliverables, introduced more structure into the project. Thus, the positive results may be attributable in part to this extra structure. However, even prior to the training modules, the weekly activities and deliverables required in semesters one and two provided a weekly rhythm. Because the introduction of the training modules occurred in the third iteration of this field study, rather than being randomly assigned throughout the study semesters, it is possible that the training is confounded with some other variable that also changed over time. However, the qualitative data from students and the informal reports of instructors reinforce the important role played by the training modules. Finally, the generalizability of studies that rely on student participants is always an issue. However, although the subjects in this study were students engaged in an academic project, they had “real world” types of tasks, motivation to do a good job since the project grade was a significant part of the course grades (generally 20% or more) and a substantial time period of four weeks in which to work, which simulate realistic conditions for partially distributed teams working on the high level requirements stage of systems analysis and design.

6.2. Future research plans The work reported here is part of a larger multiyear and multi-institutional project investigating the factors that influence the processes and outcomes of student PDTs. In this paper we have focused on the

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positive effects that we have observed for the training modules, and not surprisingly we have already planned a number of follow-on studies that will help us to better understand and leverage these effects. First, we have not yet considered the role of the instructor. Informally we have noted that different classes “operate” with different class cultures and we expect that this will interact with PDT projects in general, and with the student training modules in particular. Continuing the action research paradigm, we intend to design and incorporate instructor training modules. In parallel we will continue to refine the student training modules, based on student feedback and instructors’ observations. Our preliminary analyses suggested that team variables varied by university, perhaps as a result of

various distance dimensions contributing to PDT dynamics, such as culture, or perhaps due to other more specific variables like instructor or university demographics. But to better understand what is driving PDT experiences, we need to expand the study, adding more sites that will allow us to tease out the possible interactions of culture and time on training, so that we can refine the modules to better support the special problems caused by different dimensions of distance. This broader sample would also enable us to build and test a more accurate multivariate regression-based model of factors that impact PDT processes and performance as well as their interactions with training.

Table 3. ANCOVA Results for Training with universities as covariates Source Corrected Model

Training

Error

Type III Sum of Squares Trust Shared Identity Awareness Coordination Capability Conflict Team Performance Trust Shared Identity Awareness Coordination Capability Conflict Team Performance Trust Shared Identity Awareness Coordination Capability Conflict Team Performance

7. Acknowledgements

84.00 49.51 158.66 60.01 99.09 32.03 52.23 40.96 15.45 90.88 20.89 72.51 9.45 28.75 953.89 1107.01 1053.25 876.67 1059.85 652.64 777.30

df 8 8 8 8 8 8 8 1 1 1 1 1 1 1 453 453 453 453 453 453 453

Mean Square 10.50 6.19 19.83 7.50 12.39 4.00 6.53 40.96 15.45 90.88 20.89 72.51 9.45 28.75 2.11 2.44 2.33 1.94 2.34 1.44 1.72

F 4.99 2.53 8.53 3.88 5.29 2.78 3.80 19.45 6.32 39.09 10.79 30.99 6.56 16.76

Sig. 0.00 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.01 0.00 0.00 0.00 0.01 0.00

We would like to thank all of the instructors and their students for participating in the PDT project. Linda Plotnick, Matthew Peters, Robin Privman, Gregory Schwarz and Yang Zhang assisted with this research.

This work is partially supported by grants from the National Science Foundation (NSF HSD 0623047; NSF DUE 0736981); the opinions expressed are those of the authors and may not reflect those of the NSF.

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Proceedings of the 42nd Hawaii International Conference on System Sciences - 2009

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