Training Students to Work Effectively in Partially Distributed Teams

Training Students to Work Effectively inPartially Distributed Teams

ROSALIE OCKER and MARY BETH ROSSONThe Pennsylvania State UniversityDANA KRACAWIBMandS. ROXANNE HILTZNew Jersey Institute of Technology

Information technology teams are often partially distributed teams (PDTs). A PDT consists oftwo or more subteams that are separated geographically. This articles describes research focusedon the use of PDTs to engage students in “real world” IT team learning about the subject matterwhile also teaching them the skills they will need to work in global software development teams.Findings from a large-scale international study indicate that the introduction of training mod-ules enhanced perceived learning of appropriate PDT teaming behaviors; students with trainingreported improved shared team identification, trust, awareness, coordination, competence, andconflict with respect to distant subteam members, and higher overall team performance.

Categories and Subject Descriptors: K.3 [Computers and Education]; H.4.3 [Communications

Applications]; H.5.3 [Group and Organization Interface]

General Terms: Design, Experimentation, Human Factors, Measurement, Performance

Additional Key Words and Phrases: Virtual teams, distributed teams, partially distributed teams

ACM Reference Format:

Ocker, R. and Rosson, M. B. 2009. Training students to work effectively in partially distributedteams. ACM Trans. Comput. Educ. 9, 1, Article 6 (March 2009), 24 pages.DOI = 10.1145/1513593.1513599. http://doi.acm.org/10.1145/1513593.1513599.

This is a revised and expanded version of a paper presented at HICSS’09.This work is partially supported by grants from the National Science Foundation (NSF HSD0623047; NSF DUE 0736981); the opinions expressed are those of the authors and may not re-flect those of the NSF.Authors’ address: R. Ocker, College of Information Sciences and Technology, The PennsylvaniaState University; email: [email protected] to make digital/hard copy of all or part of this material without fee for personal orclassroom use provided that the copies are not made or distributed for profit or commercial advan-tage, the ACM copyright/server notice, the title of the publication, and its date appear, and noticeis given that copying is by permission of the ACM, Inc. To copy otherwise, to republish, to poston servers, or to redistribute to lists requires prior specific permission and/or a fee. Permissionsmay be requested from the Publications Dept., ACM, Inc., 2 Penn Plaza, Suite 701, New York, NY10121-0701 USA, fax +1 (212) 869-0481, or [email protected]© 2009 ACM 1531-4278/2009/03-ART6 $5.00 DOI: 10.1145/1513593.1513599.

http://doi.acm.org/10.1145/1513593.1513599.

ACM Transactions on Computing Education, Vol. 9, No. 1, Article 6, Pub. date: March 2009.

6: 2 · R. Ocker and M. B. Rosson

1. INTRODUCTION

Information technology (IT) teams are often partially distributed teams

(PDTs). A PDT consists of two or more subteams that are separated geograph-ically. In a PDT, the members of any given subteam are colocated, but theycollaborate remotely with members of other subteams. PDTs are an increas-ingly normal mode of operation for information systems development, as orga-nizational structures have diversified to encompass off-shoring, outsourcing,and insourcing development practices. Often the geographic distance separat-ing subteams spans multiple time zones and countries, as in the case of globalsoftware development PDTs [Carmel and Abbott 2007; Hanisch and Corbitt2007; Herbsleb and Grinter 1999].

Employers seek IT graduates who are “job ready.” The 2008 InformationTechnology Curriculum Guidelines call on IT educators to “ease the transi-tion from academia to the business world by teaching students to work inteams and providing significant project experiences” [Lunt et al. 2008, p. 45].The guidelines also state that “IT educational programs need to providestudents with experiences where they can apply international, intercultural,and workplace issues within the context of computing resources, teamwork,and projects” [p. 45].

With the goal of preparing students to work in a global team context, IT ed-ucators across the computing disciplines are striving to incorporate distributeddevelopment projects into their courses [Adya et al. 2008]. Notable multi-yearinternational efforts include the Global Studio Project [Richardson et al. 2007],the Runestone Project [Last et al. 2002; Hause et al. 2003], the Australian-Sweden collaboration [Clear and Daniels 2000; Clear and Kassabova 2008] andHKNET [Rutkowski et al. 2008]. Building on these efforts and with the goal ofproviding students with deep learning experiences specifically related to PDTsin IT education, we have conducted a large-scale three-semester investigationof 84 PDTs with nearly 700 participants. Students from universities in ninecountries worked on a four-week project to develop the high-level requirementsand user interface design for an emergency management information system.

In this article, we present three training modules that were developed toscaffold students’ PDT collaboration behaviors, and discuss their effects onteam interaction processes and outcomes. Each module is a set of activitiesdesigned to meet specific goals; each is self-contained and is generic in thesense that it could be useful to teams in a wide variety of task contexts. Ourresearch question is: How does training affect team interaction processes andoutcomes in terms of 1) overall team performance and 2) effects on six inter-vening variables that are likely to affect performance in PDTs: trust, sharedidentity, awareness, coordination, conflict, and competence.

This article is organized as follows. We review problems that are commonto virtual teams in general and PDTs in particular, with emphasis on “us vs.them” subteam dynamics that tend to emerge unless special steps are takento ameliorate these dynamics. Working from this literature, we introduce thesix constructs related to team interaction and performance that we analyzedin this field experiment. We next summarize prior research on training for


Training Students to Work Effectively in Partially Distributed Teams · 6: 3

Fig. 1. Partially Distributed Team (PDT) with two subteams.

effectiveness in distributed teams. We present our research method, a form ofaction research implemented as a series of field experiments with and withoutthe training modules, and summarize the student team projects, the tools used,the university contexts, and the training materials. After summarizing ourresults, we conclude by discussing the limitations of the research and plans forfuture studies.

2. REVIEW OF LITERATURE ON PARTIALLY DISTRIBUTED TEAMS

2.1 Ingroup Team Dynamics: Us vs. Them

Social categorization theory [Tajfel 1981] and Social Identity Theory (SIT)[Tajfel 1978; Turner 1981; Tajfel and Turner 1986] suggest that people derivesocial identity primarily from membership in groups. Demographic differencesspawn differences of opinion and divergent viewpoints which result in peoplecategorizing themselves into “us vs. them” groupings. These subgroups de-velop separate identities and exhibit ingroup dynamics, defined as increasedinteraction with and preferential behavior toward members of one’s subgroup;reduced trust and team cohesiveness, and increased conflict between sub-groups. Ingroup dynamics impair team effectiveness and performance (e.g.,Lott and Lott 1965; O’Reilly et al. 1989; Smith et al. 1994). Positive socialidentity results when one can make favorable comparisons between the groupto which one is a perceived member (i.e., the ingroup) compared to other ger-mane groups to which one is not a perceived member (i.e., the outgroup).

Figure 1 depicts a PDT configuration that spans two physical sites. Teammembers within a site are physically colocated, thus they share the same workcontext (e.g., access to the same work processes, work culture, resources, com-puter systems, etc.). Furthermore, face-to-face contact increases the likelihoodthat colocated team members will develop a shared identity [Amir 1969; Fioland O’Connor 2005; Hinds and Mortensen 2005]. However, lack of a sharedcontext between team locations can have significant negative effects on overallteam development and performance [Sole and Edmondson 2002]. The situa-tion is further exacerbated due to the lack of face-to-face interaction betweenteam members at distant sites, who must rely upon information and communi-cation technology (ICT) to communicate and collaborate (e.g., e-mail, electronicmeeting systems, Web-based applications, and teleconferencing).

Indeed, recent research indicates that PDTs are especially vulnerable toingroup team dynamics. In a qualitative study of 12 regional PDTs withina single university, Ocker et al. [forthcoming] report that colocated subteam



members became so polarized from their remote counterparts that they in-tentionally withheld information from each other. In a qualitative study ofeight globally distributed student project teams, across two universities in twocountries, Panteli and Davison [2005] found that subgroups formed in eachlocation, resulting in ingroup team dynamics. Bos et al. [2004] used a simu-lation game to study the behavior of groups composed of both colocated andisolated members. They found that ingroup dynamics were prevalent, withthe colocated members forming one subgroup, and the isolates banding to-gether to form their own subgroup. In a large-scale study of 45 global par-tially distributed student teams spanning either two or three countries, Polzeret al. [2006] found strong evidence of subgroup formation based on location.Ingroup dynamics were most apparent in teams configured across two (asopposed to three) locations.

2.2 Variables Likely to Influence PDT Interaction and Performance

Six intervening variables have been shown to be key influencers of bothtraditional and virtual team interaction and performance; we also expectthem to influence PDTs. Two of these variables—degree of shared identifi-cation and trust—are socio-emotional constructs, emphasizing how individu-als feel about their team. A second pair of variables—degree of awarenessand coordination—pertain to procedural aspects of team management. Theremaining two—degree of perceived competence and conflict—have a more be-havioral construal, capturing aspects of how members see their team interact-ing and operating. Because any of these variables can have important impactson PDT processes, training aimed at addressing the problems of PDTs shouldconsider each of these intervening variables. The three training modules wedeveloped targeted these intervening variables, as described in the next sec-tion, “Training for Partially Distributed Teams.”

Shared identification with the team by its members is important in termsof enhancing team cohesion, reducing conflict, and increasing motivation [Jehnet al. 1999; Kramer 1991]. Due to the reduced contact of members in a virtualcontext, the cohesion that is promoted by shared identification may be espe-cially important to team functioning [Hinds and Mortensen 2005; Wiesenfeldet al. 2001].

Trust can be defined as “the willingness of a party to be vulnerable to theactions of another party based on the expectation that the other will performa particular action important to the trustor, irrespective of the ability to mon-itor or control that other party” [Mayer et al. 1995, p. 712]. It includes beliefsthat the trusted party, for example a distant subteam, will fulfill its commit-ments [Luhman 1979], and that it will behave in an ethical [Hosmer 1995]and socially appropriate [Zucker 1986] manner. Trusting relationships in anyteam reduce transaction costs, increase cooperation, promote respect, and leadto better outcomes [Hung et al. 2004]. However, trust is difficult to establishin a virtual context. Studies of global virtual teams have suggested that so-cial interaction, an ability to cope with uncertainty, and individual initiativehelp to build initial “swift” trust, while deeper trust is promoted by predictable



communication behaviors, along with substantive and timely responses[Jarvenpaa and Leidner 1999].

Awareness of members is important to the success of virtual teams[Cramton 2001; Weisband 2002]. Awareness refers to an understanding ofothers’ activities and provides a context to interpret behavior [Dourish andBellotti 1992]. Weisband [2002] 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 knowl-edge about others outside the context of work, and availability awareness isknowing whether others are available to meet or participate in an activity. Todate, activity awareness has received the most attention [Carroll et al. 2003].Research indicates that the lack of a shared work context in a distributedteam reduces the amount of mutually shared knowledge among team members[Cramton 2001; Mark 2001] which reduces awareness of member activities andavailability, leading to misattributions [Weisband 2002].

Coordination can be defined as the additional work required when mul-tiple individuals work together to accomplish a goal, compared to individualsworking alone [Malone and Crowston 1994]. Time-limited teams must coor-dinate their efforts temporally [Massey et al. 2003]. Temporal coordinationmechanisms include milestones, schedule deadlines, time on tasks, and pacingof effort between team members [Ocker et al. 1995-1996]. Coordinating mem-ber efforts across distance is challenging, and becomes more difficult whenthe team encompasses multiple time zones and/or cultures [Kayworth andLeidner 2000; Powell et al. 2004; Sarker and Sahay 2002]. Research indi-cates that teams who establish a temporal rhythm of work (a combination ofsynchronous and asynchronous communication) and norms for collaborations(e.g., acceptable turn-around time for feedback on work products) have moreeffective performance [Maznevski and Chudoba 2000; Massey et al. 2003].

Competence is concerned with beliefs about the ability of the team. Itmelds aspects of group potency and collective efficacy. Group potency is thecollective belief of group members that the group can be effective [Guzzo andShea 1992]. Similar to group potency, collective efficacy is the members’ beliefsthat the team can succeed at a specific task [Lindsley et al. 1995]. We includeboth of these concepts in the competence construct. According to self-efficacytheory [Bandura 1982, 1986], collective efficacy affects how much effort mem-bers will put forth as a team, which in turn will influence their team outcomes.Both potency and collective efficacy are positively related to team performance(e.g., Hecht et al. 2002; Sivasubramaniam et al. 2002; Chen and Bliese 2002).Recent research has confirmed that they also influence the performance of vir-tual teams [Fuller et al. 2006-2007; Hardin et al. 2006].

Conflict can be defined as disagreements among team members due toperceived incompatibilities or differing viewpoints or goals [Jehn 1995; Polzeret al. 2006]. Not surprisingly, conflict is normally problematic for team perfor-mance [Jehn 1997], although some researchers have found that conflict tied totask disagreements may increase team creativity [Amabile 1983; Jehn 1997;



Robey et al. 1993]. Research indicates that conflict may be more prevalentin virtual contexts [Mortensen and Hinds 2001; Hinds and Mortensen 2005],perhaps because its emergence and resolution is more difficult to track. Thelack of immediate feedback [Kankanhalli et al. 2006-2007] as well as time zoneand cultural differences may exacerbate conflict [Dube and Pare 2001; Mannixet al. 2002].

2.3 Training for Partially Distributed Teams

Numerous studies suggest that virtual team members could benefit from train-ing on the intricacies of working in a distributed context. For example, Zigurs[2002] recommends training for virtual team leaders; Cramton [2001] recom-mends educating virtual team members about the pitfalls of the failure toshare situational information and the tendency to make assumptions aboutremote partners and locations. Training on diversity awareness in distrib-uted teams is recommended by Sarker and Sahay [2002]. Rosen et al. [2006]note that organizations today do not adequately train members in virtual teamwork. The need to prepare students to be effective members of virtual teams isrecognized, but to date, little headway has been made beyond introducing suchprojects into the classroom setting (see Shen et al. [2008], Olson-Buchananet al. [2007], and Egea [2006] for recent case studies). Below we summarizethe few empirical studies that have explicitly focused on training for virtualteams.

Tan et al. [2000] designed a dialogue technique aimed at helping virtualteams quickly establish a shared understanding among team members. Thetechnique was comprised of three stages. In the first stage (small talk), mem-bers shared information about themselves (e.g., name, gender, education, andhobbies) and contributed jokes. In the second stage (infinite container), teammembers listed good communication practices (e.g., mutual respect, clear goal),then built and shared mental models regarding these practices, including clar-ifications of members’ questions. In the third stage (laser generation), teammembers collaborated to build a team mental model around the positive com-munication practices that the team had agreed to adopt; this model repre-sented the team’s norms regarding interaction. A comparison of teams that didor did not receive the training showed that the dialogue technique improvedteams’ relational development and decision outcome.

Beranek and colleagues conducted two studies regarding training of virtualteams. One study [Beranek 2005] manipulated two types of training in a 2 X2 factorial design (trust/no trust training; relational/no relational links train-ing). Trust training was developed based on the trust building and mainte-nance behaviors identified by Jarvenpaa et al. [1998]. Relational links refersto the closeness among team members. Relational Links training consistedof training on teamwork, drawbacks to electronic communication, and ne-tiquette rules. Another study [Beranek and Martz 2005] focused solely onthe impact of relational training. In both studies, fully distributed virtualteams were composed of students within the same class who worked togetherover eight weeks; members were instructed to communicate only electroni-cally. Team members were introduced to mechanisms for addressing electronic



communication problems, and for adding socio-emotional cues to electroniccommunication. Findings indicate that teams which received any training(either or both types) reported higher levels of cohesiveness, perceptions ofthe process and trust compared to teams that did not receive training.

We found no studies of virtual team training that considered the caseof PDTs; the studies summarized above considered fully distributed teamsformed by students who were members of a shared class. All three studiesfound that the virtual teams who underwent training achieved “better” re-sults, either in terms of interaction processes (e.g., trust formation) or higherperformance.

3. METHOD

The research presented here occurred over three consecutive semesters of afield study conducted at multiple universities located in multiple geographicregions, involving multiple national cultures and time zones. A uniting factoracross semesters was a PDT project in which teams analyzed and specifiedhigh-level requirements and user interface design for an emergency manage-ment information system.

3.1 Participants and Sites

A total of 84 teams with 689 students participated. Teams averaged eightmembers, typically with four members at each of two sites (see Figure 1).Participants were drawn from nine universities in three global regions (NorthAmerica, Europe, and Asia). Geographic distance between subteams variedfrom a minimum of 190 miles to a maximum of ∼ 8,000 miles. Temporal dis-tance spanned eight time zones with a minimum of 0 hours to a maximum of14 hours. A variety of national cultures were represented.

3.2 Distributed Team Projects

The project task was designed to be appropriate for students from differentgeographic regions and cultures. We developed two project task descriptionsinvolving emergency management information systems (EMIS); the projectswere isomorphic in their specification and requirements. We focused on thefront-end of the software development process, (high-level analysis and de-sign) because of the heavy emphasis on communication and on developing ashared understanding of the problem area, key challenge areas in distributedwork (for reviews see Hertel et al. 2005; Martins et al. 2004; Pinsonneaultand Caya 2005; Powell et al. 2004). Each project spanned four weeks. Thistimeframe was commensurate with the weighting of the project (15-20% of thecourse grade). While both three- and four-week project periods were tested,pilot studies indicated that four weeks was more suitable to the task, with allteams able to complete the project within this longer project period. Addition-ally, four weeks provided enough flexibility to accommodate the wide rangeof university calendars across the participating universities (i.e., allowing fordifferent semester schedules and national and religious holidays).

The GRRR project (Grassroots Regional Resource Repository) involvesdetermining the functional requirements for a self-help regional emergency



Fig. 2. PDT collaboration system.

preparedness information system. The goal of the system is to provide a wayfor people living in a given geographic region (e.g., Peru) to manage and ef-fectively deploy the region’s resources (e.g., skilled labor, equipment, supplies)in a disaster, without waiting for external assistance. The BTMAPS project

(Bioterrorism Management and Planning System) involves determining thefunctional requirements to support the detection of bioterrorist threats as wellas management of resources needed for the associated response. BTMAPSshould include threat detection, executive decision-making, and generalemergency resource management for a region (e.g., Zurich).

3.3 Collaboration Platform

We implemented an open source Web-based communication and contentmanagement system (Drupal 4.71), enhanced with additional functionality (viathird-party plug-ins) needed for the team activities. Activities are supportedby a single central server, developed and maintained by the research team.Figure 2 shows a screenshot of the resulting custom collaboration systemdeveloped to support the project teams.

Upon logging in, the system presents students with a description of the PDTproject including instructions, milestones, and deliverables. The system pro-vides a threaded discussion board, a file sharing repository, shared documentcreation and editing, as well as a project calendar. Each team had its ownelectronic workspace; if the team desired, the space could be divided into addi-tional private spaces for subteams, leaders, or other individual team members.

1drupal.org



Fig. 3. PDT project activities and deliverables.

Project instructions and procedures were developed, piloted, and refinedprior to the three-semester field study reported here. The instructions provideda description of deliverables with reusable templates, a schedule of project duedates, tips for getting started, a project completion checklist, and a tutorial forthe PDT system. Training modules were added in Semester 3 (as describedin Section 4.2 “Training Modules Designed for Cycle 3.”). A project require-ment was that all deliverables (including the final project report) were postedonline using the PDT system. The participants were free to use other technolo-gies such as instant messaging, e-mail, or phone.

In semesters two and three, varying instructions for team leader selectionwere provided and teams were randomly assigned to conditions within a giventime period [Plotnick et al. 2008a, 2008b, 2008c].

3.4 PDT Project Procedure

Each PDT project spanned four weeks. As depicted in Figure 3, teams in allthree cycles participated in the EMIS project activities and deliverables shown



Table I. Sections of the Team Contact

Contact information for team members

Communication between subteams

Meetings between subteams

Project management & team leadership

Work submissions

Conflict between subteams

Decision making processes

above the timeline. Each semester constituted a research cycle (see Section 4.1“Research Method”). These consisted of:

PDT Tutorial: The tutorial reviews the functions of the PDT collaborationsystem, including information on how to post messages to a discussion forum,post files to the fileshare repositories, and create a calendar event. Studentswere required to complete the tutorial prior to the start of the PDT project.

Self-Introduction: During Week 1 of the project, students introduced them-selves to their team members via a discussion forum in the team space on thePDT system. They were asked to share something personal about themselves,such as their favorite type of music, food, or hobby.

Team Contract: Teams completed a team contract template during thefirst week of the project; the sections of the contract are listed in Table I.(During the training intervention in semester three, teams completed the con-tract during training Module 1, as described below).

Brainstorming of EMIS functionality: During the second week, team mem-bers brainstormed regarding the functions to be included in the EMIS. Usingthe template provided, each subteam prepared a brainstorming list which itshared with the distant subteam. Each subteam reviewed each other’s ideasand then created a single team list of EMIS functionality.

EMIS Proposal: During the third and fourth weeks, teams worked to com-plete the EMIS proposal, which centered on a description of the functionalrequirements and a user interface design. 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, and next steps.

Only teams in Cycle 3 completed the PDT training modules shown belowthe timeline. These are described in Section 4.2 “Training Modules Designedfor Cycle 3.”

3.5 Data Collection

Both quantitative and qualitative data were collected during each of the threecycles. Participants completed two surveys. The Background Survey was ad-ministered prior to the start of each cycle and was used to collect demographicdata. The Post survey was administered at the end of each cycle and was usedto collect data pertaining to the intervening variables (i.e., trust, shared iden-tity, awareness, coordination, competence, and conflict) and to the dependentvariable, perceptions of team performance. Participants also completed weekly



Table II. Description of Action Research Cycles

Phase Cycle 1 (Semester 1) Cycle 2 (Semester 2) Cycle 3 (Semester 3)

1. Diagnosing Students need Students need Students need trainingexperience working experience working on how to effectivelyin PDTs. in PDTs. collaborate in PDTs.

2. Action Develop and pilot Modify measurement Develop trainingPlanning collaboration system, instruments; line up modules that focus

project task, and participants. on betweenprocedures; develop subteam problemsmeasurement (e.g. “us vs. them”).instruments;line up participants.

3. Action Run cycle one Run cycle two Run cycle threeTaking PDT study. PDT study. incorporating three

training modules.

4. Evaluation Student feedback Conduct qualitative Conduct quantitativeobtained on analysis of student analysis of postcollaboration system weekly personal survey; conductand project procedures reflections; Identify qualitative analysisvia focus groups common problems; of weekly personaland in-class discussions. positive and negative reflections.

trajectories.

5. Specifying Incremental Us vs. them Write this paper.Learning modifications made significant problem

-clarifications to that negativelyinstructions and impacts interactionprocedures - collab. processes betweensystem–group teams.calendar added;account notificationmodified.

personal reflections where they wrote about their experiences during the mostrecent week of the project, including team dynamics, problems, and concerns.After Cycle 1, participant feedback was solicited via classroom discussions andfocus groups; a Collaboration System Feedback survey was also administeredto collect student feedback regarding the usability of the PDT collaborationsystem.

4. RESEARCH APPROACH

4.1 Research Method

We followed an action research method to study partially distributed teamsand the impact of training modules. Action research can be viewed as a post-positivist research method that is “empirical, yet interpretive . . . experimental,yet multivariate . . . and observational, yet interventionist” [Baskerville andWood-Harper 1996, p. 236; see also DeLuca et al. 2008].

Iterative cycles (see Table II)—typically consisting of five repeatingphases—have been proposed as a mechanism for introducing scientific rigorinto action research [Susman and Evered 1978; Baskerville and Wood-Harper1996; Lindgren et al. 2004]. These phases include diagnosing, action planning,



action taking, evaluating, and specifying learning. In the Diagnosing phase,we observed the problems that teams encountered during cycle one. In ActionPlanning, we began planning how a combination of software tools and a setof training modules for effective interaction between subteams could improvematters. Our Action Taking implemented the designs for a modified tool aswell as a set of training modules for students. In Evaluation, we assessedwhether the desired effects were achieved. Finally, Specifying Learning occurswhen lessons learned from each cycle are documented and are used to informdesigners regarding objectives for the next cycle.

Cycle 1 occurred during Semester 1, after the procedures and system werepilot tested. Participant feedback to gather general qualitative reactions wasobtained from the first author’s students via classroom discussions and focusgroups and completion of the Collaboration System Feedback survey. Analysisof these data resulted in incremental modifications to procedures and presen-tation of materials on the system. Additionally, a group calendar was added tothe system.

To evaluate Cycle 2 carried out in the second semester, the content of partic-ipants’ weekly personal reflections were coded, following the grounded theorymethodology [Glaser and Strauss 1967]. The qualitative analysis suggestedthree areas in which to enhance our PDT project materials:

1) Anticipating and supporting a team development life cycle. Two fairly regu-lar patterns of team evolution were identified. Up to the project midpoint,most teams share a similar development path. At the start of the project,the majority of students express excitement about the unique experienceof collaborating with students from other universities and cultures. Thisis followed by a period of anxiety and concern, as they begin to experi-ence the challenges of distance collaboration. However, after the projectmidpoint, two divergent paths emerge. For those teams on a positive tra-jectory, separate subteam identities give way to an overall team identity,as trust between subteams increases based on initial constructive interac-tion and shared accomplishments. These teams become very focused andtask-oriented as parts of the project solution begin to develop, followed bya celebratory attitude as they see success emerging. For those teams thatexperience a negative trajectory, a downward spiral of frustration, conflict,and disenchantment ensue as teams struggle to meet deadlines; subteamsmaintain separate identities and work against each other as they try tocomplete the project. Both students and faculty need learning materialsthat will inform and assist them in anticipating, analyzing and aligningtheir team development life cycle.

2) Diagnosing and addressing the “us versus them” tension. As evidenced bythe negative trajectory described above, a significant challenge for PDTs isfinding a way to function as a coherent team rather than as separate sub-teams. The reality of “us vs. them” ingroup team dynamics (increased in-teraction with and preferential behavior toward members in one’s subteam;reduced trust and team cohesiveness as well as increased conflict betweensubteams) is arguably the single most critical problem that PDTs need to



Table III. 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.

overcome. While some participating faculty addressed the “us vs. them”tension in an informal and ad hoc fashion, the pervasiveness and serious-ness of this phenomenon indicated that all participants might benefit fromformal training.

3) Recognizing and accommodating different “distancing” factors. When teammembers must interact with members at other locations, several differentfactors (e.g., geographic, cultural, and temporal) can increase the perceiveddistance, making collaboration difficult. The simple fact that communica-tion is mediated rather than face-to-face has important implications for thestyle and impact of different forms of communication. When subteams arefrom different cultures, new complexities relating to cultural norms canarise (e.g., use of formal versus informal language, explicit expression of re-spect or disrespect, deference to leadership). When some of the team mem-bers are in a different time zone, additional problems can arise, for examplewith perceived responsiveness under deadline pressure. Students need tolearn about each type of distancing factor, how to recognize when it is af-fecting the team’s interactions, and strategies for resolving the problem.

4.2 Training Modules Designed for Cycle 3

Based on the qualitative analysis conducted at the end of Cycle 2, threetraining modules were developed and implemented in Cycle 3. Each module isdescribed below.

4.2.1 Module 1. Research indicates that virtual teams with a solid begin-ning are teams that are most successful [Coppola et al. 2004]. Therefore, thegoal of Module 1 is to help teams get off to a good start. Module 1 is completedduring the first week of the project, and introduces students to problem sce-narios that they are likely to encounter during their four-week PDT project.The problems addressed in each of the scenarios are listed in Table III.

Each scenario relates to one or more sections of the team contract, which arelisted in Table I. Each subteam works through the scenarios and prepares adraft of the team contract, after which each subteam shares its contract draft



with the distant subteam. Subteams then compare and discuss the contractdrafts to formulate a single team contract.

4.2.2 Module 2. The goal of Module 2, completed during the second weekof the project, is to help subteams move from an “us vs. them” mindset to awe or team mindset. Teams work through Module 2 as they begin actual workon the PDT EMIS project task. Module 2 includes two activities with deliv-erables: conducting member interviews and creating a team Web page. TheMember Interviews and Team Web Page activity are designed to jump-startinformal interaction between subteams through a fun and creative endeavor.In this activity, each student must interview a distant subteam member andwrite up the results of the interview questions and answers. Using these inter-views, the team is instructed to collaborate to create a team Web page. Inter-view questions are suggested and required team Web page content is specified;teams are encouraged to personalize their page designs and add additionalinformation.

4.2.3 Module 3. The goal of Module 3 is to help teams establish and/ormaintain a positive team trajectory. Teams on a positive trajectory may haveexperienced some “rough spots” in collaborating with their distant subteamduring the first two weeks, but overall they have had a constructive experienceand are likely to have continued success during the second half of the project.Teams on a negative trajectory have experienced some significant difficulty,such as limited participation from several distant team members, communica-tion or coordination difficulties between subteams, or poor leadership. If teamsremain on this negative trajectory, they are likely to experience a downwardspiral of frustration, conflict, and disenchantment as they struggle to meetdeadlines and complete the project.

Module 3 is designed to help teams evaluate the trajectory they are on and tomake necessary adjustments. This module consists of two parts: (a) the 3 BinAssessment and (b) the Action Plan. In the 3 Bin Assessment, each subteamevaluates the team by sorting aspects of team interaction and performanceinto one of three “bins”: great, fair, and “not so great.” Subteams share theirassessments with each other and then collaborate to complete the Action Plan,where they devise corrective actions to address the problem areas.

4.3 Research Model and Measures Scales

A post-project survey was administered during each of the semesters to allPDT members, after they had delivered their shared project. The post surveycontained several scales designed to measure the constructs relevant to ourresearch model (Appendix A presents the final sets of items used for each con-struct). The competence measure was adapted from Jarvenpaa et al. [1998].The conflict and shared identity measures were adapted from Mortensen andHinds [2001]. The trust measure was adapted from Jarvenpaa and Leidner[1999]. The awareness measure was developed based on the literature, aswe could not find a preexisting scale. The ease of coordination measure wasadapted from Faraj and Sambamurthy [2006]. The team performance measure



was adapted from Mortensen and Hinds [2001]. The awareness, competence,conflict, coordination, and trust ratings gathered judgments about distributedsubteams; shared identity and performance were judged with respect to theteam as a whole. All scale items were measured using a seven-point semanticdifferential response scale.

Note that the survey also contained other items, for example a number ofratings that referred to student’s colocated subteams, and items that probedhow information technology was used, reactions to the different aspects of theproject, and so on. In this article we have focused only on scales relevantto the research model; other threads of the research program are examiningother sections of the survey as well as qualitative data that were gathered.Researchers interested in viewing the full survey are encouraged to contactthe first author.

5. DATA ANALYSIS AND RESULTS

To ascertain the effects of training on team interaction processes and perfor-mance in PDTs, the quantitative analysis presented below is based on datacollected during the post-project survey. Post survey responses were receivedfrom 462 participants across eight universities2 for a response rate of 67%(462/689): 100 from Cycle 1, 96 from Cycle 2, and 266 from Cycle 3. We beginby assessing the reliability of scales used to measure the seven constructs of in-terest. Then we present results of an analysis of co-variance. Finally, we wereinterested in the relative effectiveness of each individual module; we concludethis section with results of a secondary analysis of individual modules.

5.1 Scale Reliability

Rather than using Cronbach’s alpha, which represents a lower bound estimateof internal consistency due to its assumption of equal weighting of items, abetter estimate can be obtained using the composite reliability [Chin 1998;Fornell and Larcker 1981]. Unlike alpha, this measure is not influenced by thenumber of items in the scale. It is based on the ratio of construct variance tothe sum of construct and error variance. As shown in Table IV, the reliabilityof all of our measures are quite high in most cases (around .9 or above), withthe exception of the trust construct, which is still good.

A confirmatory factor analysis was conducted using the scale itemscontained in Appendix A. All items loaded onto their respective construct.

5.2 ANCOVA Results

The geographic, temporal, and cultural distance variations among universi-ties were broad, and because our partnerships were based on other faculty’sinterest and availability, it was impossible to balance these variables acrosswithout-training and with-training cycles. Thus we began our analysis bystudying the variation among our process and outcome measures (see Table IV)across universities. Not surprisingly, results revealed a number of differences

2There were no respondents from one university in Asia.



Table IV. Reliability of Measures

Constructs Composite Reliability

Trust 0.80

Shared Identity 0.95

Coordination 0.89

Awareness 0.90

Conflict 0.90

Capability 0.95

Performance 0.95

Table V. Descriptive Statistics for Intervening (Dependent) Variables

Training Mean Std. Deviation

Trust

Without 4.32 1.39With 5.13 1.49Total 4.78 1.50

Shared Identity


Awareness

Without 3.70 1.59

With 4.77 1.49Total 4.31 1.62

Coordination


Ability


Conflict


Team Performance


across universities on these measures. Therefore, our analysis of the trainingvariable employs an analysis of covariance, where the eight universities wereanalyzed as covariates.

With respect to the contrast of training conditions, 196 respondents fromCycle 1 and 2 received no training (without training), while 266 fromCycle 3 received training (with training). The descriptive statistics for theseven variables (six intervening and one outcome) are shown in Table V.Results of the ANCOVA indicate that participants who completed the trainingmodules in Cycle 3 reported significantly higher levels of the intervening vari-ables of trust, shared identity, awareness, coordination effectiveness, and per-ceived competence of, and less conflict with, the distant subteam (p < 0.01 forall variables). Furthermore, these participants reported significantly higherlevels of perceived team performance compared to participants who did notcomplete the training modules (p = 0.00). The strongest effect of the trainingmodules was on “awareness” of the other team members and their activities,greatly lessening the tendency towards “out of sight, out of mind.” This is prob-ably a key contributor to the increase in shared identity (more perceptions of



the whole team as “we”and “us”), which in turn contribute to the improvementsin team performance.

5.3 Secondary Analysis Comparing Modules

The ANCOVA analyses we conducted treated the training modules as asingle effect rather than as separate training interventions. However, wealso included more detailed probes to investigate which module(s) the studentsreceiving training experienced as most effective. Thus in the post survey, re-spondents were asked to rate each training module in terms of (1) increasingfamiliarity with distant team members, (2) decreasing perceived distance be-tween subteams, and (3) helping subteams become a single team. We foundthat Module 2 (member interviews and team webpage) was rated most highlyfor all three questions, but especially in terms of increasing familiarity withdistant members.

6. DISCUSSION AND CONCLUSIONS

In this article we have described an instance of action research that led to theintroduction of training materials specifically designed to ameliorate problemsobserved for student PDT teams in the early cycles of the investigation. In theevaluation phase, we found that the training modules were quite beneficial inreducing the separateness of “us vs. them” induced by collaboration across dis-tances, and in improving team performance. For instance, most teams “withtraining” reported more positive ratings for many intervening variables (e.g.,trust, shared identity) with ratings that were positive in the range of 5+ onscales ranging from 1-7. It is notable that even though the results for aware-ness were strongest, perceptions of awareness remain problematic for theseteams; in this case the average for teams moved from 3.70 (a negative rating)to a slightly positive 4.77. Thus, there is still much progress to be made inincreasing the awareness of subteam members in PDTs about the status andactivities of members of the remote subteam(s).

6.1 Methodological Caveats

The training modules, with their weekly activities and deliverables, introducedmore structure into the project. Thus, the positive results may be attributablein part to this extra structure. Note though that even prior to the trainingmodules, there were weekly activities and deliverables required that provideda regular structure and rhythm to the project.

Because the introduction of the training modules occurred in the third it-eration of this field study, rather than being randomly assigned throughoutthe study semesters, it is possible that the training is confounded with someother variable that also changed over time. However, the qualitative data fromstudents and the informal reports of instructors reinforce the important roleplayed by the training modules.

Finally, the generalizability of studies that rely on student participants isalways an issue. However, although the subjects in this exploratory studywere 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 partof the course grades (generally 20% or more), and a substantial time period offour weeks in which to work, which increased our ability to simulate realisticconditions for partially distributed teams working on the requirements stageof systems analysis and design.

6.2 Future Research Plans

The work reported here is part of a larger multi-year and multi-institutionalproject investigating the factors that influence the processes and outcomes ofstudent PDTs. In this article we have focused on the positive effects that wehave observed for the training modules, and not surprisingly we have alreadyplanned a number of follow-on studies that will help us to better understandand leverage these effects.

First, we have not yet considered the role of the instructor. Informally wehave noted that different classes operate with different class cultures and weexpect that this will interact with PDT projects in general, and with the stu-dent training modules in particular. Continuing the action research paradigm,we intend to design and incorporate instructor training modules. In fact in themost recent semesters, we have already begun to investigate training mod-ules for participating instructors. Our first module includes a real-time audioconference among the instructors from paired courses that contribute teammembers, facilitated by one or more project researchers. The instructors canbe considered akin to “higher management” in the participating organizations.They need to be prepared to support their subteams and interpret the policiesand guidelines for the projects in a consistent manner. In parallel we will con-tinue to refine the student training modules, based on student feedback andinstructors’ observations.

Our preliminary analyses suggested that intervening variables varied byuniversity, perhaps as a result of various distance dimensions contributing toPDT dynamics, such as culture, or perhaps due to other more specific variableslike instructor or university demographics. But to better understand what isdriving PDT experiences, we need to expand the study, adding more sites thatwill allow us to tease out the possible interactions of culture and time on train-ing, so that we can refine the modules to better support the special problemscaused by different dimensions of distance. This broader sample would also en-able us to build and test a more accurate multivariate regression-based modelof factors that impact PDT processes and performance as well as their interac-tions with training.

Appendix A: Constructs and Associated Items

AWARENESS

1. I was aware of the activities members were working on in the distantsubgroup.

2. I was aware when members were available to meet (either electronically orface-to-face) in the distant subgroup.



3. I was aware of what needed to be done next in the distant subgroup.

Response scale for each item:

Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree

COMPETENCE

1. I felt very confident about the members’ skills in the distant subgroup.

2. Members were very competent in terms of completing this project in thedistant subgroup.

3. Members were quite capable of performing the necessary tasks in thedistant subgroup.



CONFLICT

1. Much disagreement existed between subgroups.

2. There was a great deal of personality conflicts between subgroups.

3. A great deal of disagreement regarding project work existed betweensubgroups.



SHARED IDENTITY

1. I feel loyal towards my team.

2. I see myself as a member of my team.

3. I am proud to think of myself as a member of my team.



TRUST

1. I wanted to more closely monitor the work of members in the distant sub-group.

2. I was comfortable when members worked on a critical task or problem inthe distant subgroup.



COORDINATION

To coordinate member effort between subteams, there were:

1. Procedures for coordinating work.

2. Project milestones and delivery schedules.



3. Project documents and memos.

4. Regularly scheduled team meetings (face-to-face and/or electronic).

Response scale for each item

Small Extent 1 2 3 4 5 6 7 Great Extent

PERFORMANCE

Compared with other teams you have worked on, use the following dimen-sions to rate the performance of your team:

—Efficiency

—Quality

—Creativity

—Adherence to schedule

—Coordination between subteams

—Communication between subteams


Low 1 2 3 4 5 6 7 High

ACKNOWLEDGMENT

We would like to thank all of the instructors and their students for participat-ing in the PDT project. Linda Plotnick, Matthew Peters, Robin Privman, andGregory Schwarz assisted with this research.

REFERENCES

ADYA, M., NATH, D., SRIDHAR, V., AND MALIK, A. 2008. Bringing global sourcing into theclassroom: Lessons from an experiential software development project. Comm. AIS 22,33–48.

AMABILE, T. M. 1983. The social psychology of creativity, A componential conceptualization.J. Personal. Social Psych. 45, 2, 357–376.

AMIR, Y. 1969. Contact hypothesis in ethnic relations. Psych. Bull. 71, 319–342.

BANDURA, A. 1982. Self-efficacy mechanism in human agency. Amer. Psychol. 37, 122–147.

BANDURA, A. 1986. Social foundations of thought and action: A social cognitive theory. PrenticeHall, Englewood Cliffs, NJ.

BASKERVILLE, R. L. AND WOOD-HARPER, A. T. 1996. A critical perspective on action research asa method for information systems research. J. Inform. Tech. 11, 235–246.

BERANEK, P. M. 2005. A comparison of relational and trust training techniques for virtual teamcommunication: How much training is enough? In Proceedings of the 38th Hawaii International

Conference on System Sciences (HICSS’05).

BERANEK, P. M. AND MARTZ, B. 2005. Making virtual teams more effective: Improving relationallinks. Team Perform. Manage. 11, 5/6, 200–213.

BOS, N., SHAMI, N. S., OLSON, J., CHESHIN, A., AND NAN, N. 2004. In-group/out-group effectsin distributed teams: An experimental simulation. Comput. Supp. Coop. Work 6, 3, 429–436.

CARMEL, E. AND ABBOTT, P. 2007. Why “nearshore” means that distance matters. Comm. ACM

50, 10, 40–46.

CARROLL, J. M., NEALE, D. C., ISENHOUR, P. L., ROSSON, M. B., AND MCCRICKARD, D. S. 2003.Notification and awareness: Synchronizing task-oriented collaborative activity, Int. J. Hum.-

Comput. Stud. 58, 605–632.



CHEN, G. AND BLIESE, P. D. 2002. The role of different levels of leadership in predicting self- andcollective efficacy: Evidence for discontinuity. J. Appl. Psych. 87, 3, 549–556.

CHIN, W. 1998. The partial least squares approach to structural equation modeling. In Modern

Methods for Business Research. G. Marcoulides Ed., Lawrence Erlbaum, Mahwah, NJ, 295–336.

CLEAR, T. AND DANIELS, M. 2000. Using groupware for international collaborative learning. InProceedings of the 30th American Society for Engineering Education/Institute of Electrical and

Electronics Engineers Frontiers in Education Conference (ASEE/IEEE’00), Vol. 1, T. BatchmanEd. IEEE, 18–23.

CLEAR, T. AND KASSABOVA, D. 2008. A course in collaborative computing: Collaborative learningand research with a global perspective. SIGCSE Bull. 40, 1.

COPPOLA, N. W., HILTZ, S. R., AND ROTTER, N. 2004. Building trust in virtual teams. IEEE

Trans. Prof. Comm. 47, 2, 95–104.

CRAMTON, C. D. 2001. The mutual knowledge problem and its consequences for dispersedcollaboration. Organiz. Science 12, 346–371.

DELUCA, D., GALLIVAN, J. J., AND KOCK, N. 2008. Furthering information systems actionresearch: A post-positivist synthesis of four dialectics. J. Assn. Inform. Syst. 9, 2, 48–72.

DOURISH, P. AND BELLOTTI, V. 1992. Awareness and coordination in shared workspaces. InProceedings of the ACM Conference on Computer-Supported Cooperative Work (CSCW’92),107–114.

DUBE, L. AND PARE, G. 2001. Global virtual teams. Comm. ACM 44, 12, 71–73.

EGEA, K. 2006. Relationship building in virtual teams: An academic case study. In Proceedings

for Informing Science + Information Technology Education Joint Conference (InSite’02), 25–28.

FARAJ, S. AND SAMBAMURTHY, V. 2006. Leadership of information systems development projects.IEEE Trans. Engine. Manage. 53, 2, 238–249.

FIOL, C. M. AND O’CONNOR, E. 2005. Identification in face-to-face, hybrid, and pure virtualteams: Untangling the contradictions. Organiz. Science 16, 1, 19–32.

FORNELL, C. AND LARCKER, D. 1981. Evaluating structural equation models with unobservablevariables and measurement error. J. Market. Resear. 18, 39–50.

FULLER, M. A., HARDIN, A. M., AND DAVISON, R. M. 2006-2007. Efficacy in technology-mediateddistributed teams. J. Man. Inform. Syst. 23, 3, 209–235.

GLASER, B. G. AND STRAUSS, A. L. 1967. The Discovery of Grounded Theory: Strategy for Quali-

tative Research. Aldine Publishing Company, Hawthorne, NY.

GUZZO, R. A. AND SHEA, G. P. 1992. Group performance and intergroup relations in organiza-tions. In Handbook of Industrial and Organizational Psychology, M. D. Dunnette and L. M.Hough Eds., 3, 269–313.

HANISCH, J. AND CORBITT, B. 2007. Impediments to requirements engineering during globalsoftware development. Eur. J. Inform. Syst. 16, 6, 793–805.

HARDIN, A. M., FULLER, M. A., AND VALACICH, J. S. 2006. Measuring group efficacy in virtualteams: New questions in an old debated. Small Group Resear. 37, 1, 68–85.

HAUSE, M., PETRE, M., AND WOODROFF, M. 2003. Performance in international computerscience collaboration between distributed student teams. In Proceedings of the 33rd Annual

Conference on Frontiers in Education (FIE’03), 3, 5–8.

HECHT, T. D., ALLEN, N. J., KLAMMER, J. D., AND KELLY, E. C. 2002. Group beliefs, ability,and performance: The potency of group potency. Group Dynam.: Theory, Resear., and Prac. 6, 2,143–152.

HERBSLEB, J. D. AND GRINTER, R. E. 1999. In splitting the organization and integrating thecode: Conway’s law revisited. In Proceedings of the 21st International Conference on Software

Engineering (ICSE’99), 85–95.

HERTEL, G., GEISTER, S., AND KONRADT, U. 2005. Managing virtual teams: A review of currentempirical research. Hum. Resource Manage. Rev. 15, 69–95.

HINDS, P. AND MORTENSEN, M. 2005. Understanding conflict in geographically distributedteams: An empirical investigation. Organiz. Science 16, 3, 290–307.



HOSMER, L. T. 1995. Trust: The connecting link between organizational theory and philosophicalethics. Acad. Manage. Rev. 20, 379–403.

HUNG, Y. C., DENNIS, A. R., AND ROBERT, L. 2004. Trust in virtual teams: Towards an integra-tive model of trust formation. In Proceedings of the 37th Annual Hawaii International Confer-

ence on System Sciences (HICSS’04).

JARVENPAA, S. L., KNOLL, K., AND LEIDNER, D. E. 1998. Is anybody out there? Antecedents oftrust in global virtual teams. J. Man. Inform. Syst. 14, 4, 29–75.

JARVENPAA, S. L. AND LEIDNER, D. E. 1999. Communication and trust in global virtual teams.Organiz. Science 10, 6, 791–815.

JEHN, K. A. 1995. A multimethod examination of the benefits and detriments of intragroupconflict. Admin. Science Quar. 40, 2, 256–282.

JEHN, K. A. 1997. A qualitative analysis of conflict types and dimensions in organizational groups.Admin. Science Quar. 42, 530–557.

JEHN, K. A., NORTHCRAFT, G. B., AND NEALE, M. A. 1999. Why differences make a difference:A field study of diversity, conflict, and performance in workgroups. Admin. Science Quar. 44,741–763.

KANKANHALLI, A., TAN, B. C. Y., AND WEI, K. 2006-2007. Conflict and performance in globalvirtual teams. J. Man. Inform. Syst. 23, 3, 237–274.

KAYWORTH, T. AND LEIDNER, D. E. 2000. The global virtual manager: A prescription for success.Eur. Man. J. 18, 2, 183–194.

KRAMER, R. M. 1991. Intergroup relations and organizational dilemmas: The role of categoriza-tion process. In Research in Organizational Behavior, L. Cummings and B. Staw Eds., JAI Press.

Greenwich, CT. 191–228.

LAST, M. Z., DANIELS, M., HAUSE, M. L., AND WOODROFFE, M. R. 2002. Learning from stu-dents: Continuous improvement in international collaboration. SIGCSE Bull. 34 3, September.

LINDGREN, R., HENFRIDSSON, O., AND SCHULTZE, U. 2004. Design principles for competencemanagement systems: A synthesis of an action research study. MIS Quar. 28, 3, 435–472.

LINDSLEY, D. H., BRASS, D. J., AND THOMAS, J. B. 1995. Efficacy-performance spirals: A multi-level perspective. Acad. Manage. Rev. 20, 3, 645–678.

LOTT, A. AND LOTT, B. 1965. Group cohesiveness as interpersonal attraction: A review of rela-tionships with antecedent and consequent variables. Psych. Bull. 64, 259–309.

LUHMAN, N. 1979. Trust and Power. Wiley, New York.

LUNT, B. M., EKSTRONM J. J., GORKA, S., HISLOP, G., KAMALI, R., LAWSON, E.,LEBLANC, R., MILLER, J., AND REICHGELT, H. 2008. Information technology curricu-lum guidelines for undergraduate degree programs in information technology. ACM/IEEE.http://www.acm.org/education/education/curricula/IT2008%20Curriculum.pdf.

MALONE, T. W. AND CROWSTON, K. 1994. The interdisciplinary study of coordination. ACM

Comput. Surv. 26, 1, 87–119.

MANNIX, E. A., GRIFFITH, T. L., AND NEALE, M. A. 2002. The phenomenology of conflict invirtual work teams. In Distributed Work, P. J. Hinds and S. Kiesler Eds. MIT Press, Cambridge,MA.

MARK, G. 2001. Social foundations for collaboration in virtual environments. In Access to Knowl-

edge: New Information Technologies and the Emergence of the Virtual University, F. T. Tschangand T. D. Senta Eds. Elservier Science, Oxford, UK. 241–263.

MARTINS, L. L., GILSON, L. L., AND MAYNARD, M. T. 2004. Virtual teams: What do we knowand where do we go from here? J. Manage. 30, 6, 805–835.

MASSEY, A. P., MONTOYA-WEISS, M. M., AND HUNG, Y.-T. 2003. Because time matters: Tempo-ral coordination in global virtual project teams. J. Man. Inform. Syst. 19, 4, 129–155.

MAYER, R. C., DAVIS, J. H., AND SCHOORMAN, F. D. 1995. An integrative model of organizationaltrust. Acad. Manage. Rev. 20, 3, 709–734.

MAZNEVSKI, M. L. AND CHUDOBA, K. M. 2000. Bridging space over time: Global virtual teamdynamics and effectiveness. Organiz. Science 11, 473–492.



MORTENSEN, M. AND HINDS, P. J. 2001. Conflict and shared identity in geographically distrib-uted teams. Int. J. Conflict Manage. 12, 3, 212–238.

OCKER, R. J., HUANG, H., BENBUNAN-FICH, R., HILTZ, S. R. Forthcoming. Leadership dynamicsin partially distributed teams: An exploratory study of the effects of configuration and distance.Group Decision Negotiation. (Special Issue).

OCKER, R. J., HILTZ, S. R., TUROFF M., AND FJERMESTAD, J. 1995-1996. The effects of dis-tributed group support and process structuring on software requirements development teams.J. Man. Inform. Syst. 12, 3, 127–154.

OLSON-BUCHANAN, J. B., RECHNER, P. L., SANCHEZ, R. J., SCHMIDTKE, J. M. 2007. Utilizingvirtual teams in a management principles course. Edu. Train. 49, 5, 408–423.

O’REILLY, C., CALDWELL, D., AND BARNETT, W. 1989. Work group demography, social integra-tion, and turnover. Admin. Science Quar. 34, 21–37.

PANTELI, N. AND DAVISON, R. M. 2005. The role of subgroups in the communication patterns ofglobal virtual teams. IEEE Trans. Prof. Comm. 48, 2, 191–200.

PINSONNEAULT, P. AND CAYA, O. 2005. Virtual teams: What we know, what we don’t know.Int. J. e-Collaboration 1, 3, 1–16.

PLOTNICK, L., OCKER, R. J., HILTZ, S. R., ROSSON, M. B. 2008a. Leadership roles and com-munication issues in partially distributed emergency response software development teams: Apilot study. In Proceedings of the 41st First Hawaii International Conference on System Sciences

(HICSS’08).

PLOTNICK, L., HILTZ, S. R., OCKER, R. J., AND ROSSON, M. B. 2008b. Leadership in partiallydistributed emergency response software emergency response software. In Proceedings of the

International Conference on Information Systems for Crisis Relief and Management

(ISCRAM’08). CD-ROM.

PLOTNICK, L., HILTZ, S. R., OCKER, R. J., RUTKOWSKI, A.-F., AND ROSSON, M. B. 2008c.Leadership and trust in partially distributed software development teams. In Proceedings of

the Americas Conference on Information Systems (AMCIS’08). CD-ROM.

POLZER, J. T., CRISP, B., JARVENPAA, S. L., AND KIM, J. W. 2006. Extending the faultlinemodel to geographically dispersed teams: How colocated subgroups can impair group function-ing. Acad. Manage. J. 49, 4, 679–692.

POWELL, A., PICCOLI, G., AND IVES, B. 2004. Virtual teams: A review of current literature anddirections for future research. Datab. Advances 35, 1, 6–36.

RICHARDSON, I., MOORE, S., PAULISH, D., CASEY, V., AND ZAGE, D. 2007. Globalizing softwaredevelopment in the local classroom. In Proceedings of the 20th Conference on Software Engineer-

ing Education and Training (CSEET’07), 64–71.

ROBEY, D. L., SMITH, L. A., AND VIJAYASARATHY, L. R. 1993. Perceptions of conflict and successin information systems development projects. J. Man. Inform. Syst. 10, 1, 123–139.

ROSEN, B., FURST, S., AND BLACKBURN, R. 2006. Training for virtual teams: An investigation ofcurrent practices and future needs. Hum. Resource Manage. 45, 2, 229–247.

RUTKOWSKI, A-F., VOGEL, D., VAN GENUCHTEN, M., SAUNDERS, C. 2008. Communication invirtual teams: Ten years of experience in education. IEEE Trans. Prof. Comm. 51, 3, 302–312.

SARKER, S. AND SAHAY, S. 2002. Understanding virtual team development: An interpretive study.J. Assn. Inform. Syst. 3, 247–285.

SHEN, J., HILTZ, S. R., AND BIEBER, M. 2008. Learning strategies in online collaborative exami-nations. IEEE Trans. Prof. Comm. 51, 1, 63–78.

SIVASUBRAMANIAM, N., MURRY, W., AVOLIO, B., AND JUNG, D. 2002. A longitudinal model ofthe effects of team leadership and group potency on group performance. Group Organiz. Manag.

27, 1, 66–96.

SMITH, K., SMITH, K., OLIAN, J., SIMS, H., O’BANNON, D., AND SCULLY, J. 1994. Top man-agement team demography and process: The role of social integration and communication.Admin. Science Quar. 39, 412–438.

SOLE, D. AND EDMONDSON, A. 2002. Situated knowledge and learning in dispersed teams. British

J. Manage. 13, S17–S34.



SUSMAN, G. I. AND EVERED, R. D. 1978. An assessment of the scientific merits of action research.Admin. Science Quar. 23, 4, 582–603.

TAJFEL, H. 1978. Differentiation between social groups: Studies in the social psychology ofintergroup relations. Academic Press, London, UK.

TAJFEL, H. 1981. Human groups and social categories: Studies in social psychology. CambridgeUniversity Press, Cambridge, UK.

TAJFEL, H. AND TURNER, J. C. 1986. The social identity theory of intergroup behaviour. InPsychology of Intergroup Relations, S. Worchel and W. G. Austin Eds. Nelson, Chicago, IL.7–24.

TAN, B. C. Y., WEI, K.-K. ET AL. 2000. A dialogue technique to enhance electronic communicationin virtual teams. IEEE Trans. Prof. Comm. 43, 2, 153–165.

TURNER, J. C. 1981. The experimental social psychology of intergroup behaviour. In Intergroup

Behaviour, J. C. Turner and H. Giles Eds. Basil Blackwell, Oxford, UK. 66–101.

WEISBAND, S. 2002. Maintaining awareness in distributed team collaboration: Implications forleadership and performance. In Distributed Work, P. Hinds and S. Kiesler Eds. MIT Press,Cambridge, MA. 311–334.

WIESENFELD, B. M., RAGHURAM, S., AND GARUD, R. 2001. Organizational identification among

virtual workers: The role of need for affiliation and perceived work-based social support.J. Manage. 27, 213–229.

ZIGURS, I. 2002 Leadership in virtual teams: Oxymoron or opportunity? Organiz. Dynamics 31, 4,339–351.

ZUCKER, L. 1986. Production of trust: Institutional sources of economic structure, 1840-1920. InResearch in Organizational Behavior, B. Staw and L. Cummings Eds. JAI Press, Greenwich, CT.53–111.

Received September 2008; revised January 2009; accepted February 2009


Documents

Training Students to Work Effectively in Partially Distributed Teams