Improving the Effectiveness of Virtual Teams

Improving the Effectiveness of Virtual Teamsby Adapting Team Processes

Daniel J. Rice1, Barry D. Davidson1, John F. Dannenhoffer1 & Geri K. Gay21Department of Mechanical and Aerospace Engineering, Syracuse University, 151 Link Hall,Syracuse, NY 13244, USA (E-mail: [email protected]); 2Kenneth J. Bissett Professor ofCommunications & Information Science, Cornell University, 339 Kennedy, Ithaca, NY 14850-4623,USA

Abstract. Results are presented from a study on virtual teams and whether appropriate earlytraining can positively influence their effectiveness. Sixteen teams that worked together for periodsranging from three months to three years were studied. Team processes that emerged naturally fromlong-duration teams were formalized and taught to shorter duration teams. These shorter durationteams comprised three different cohorts, each of which received different levels of training. It wasfound that the adoption of formal procedures and structured processes significantly increased theeffectiveness of virtual teams. Tasks that lend themselves to a structured approach were mosteffectively accomplished during virtual meetings, whereas face-to-face interactions were better forrelatively unstructured, discussion intensive tasks. The performance of a virtual team wassignificantly improved when team processes were adapted to the affordances of the CMCenvironment. It is shown that this adaptation can occur very rapidly if teams are trained on thetechnology as well as on work processes that best exploit it.

Key words: brainstorming, collaboration, communication, computer-mediated, consensus,decision-making, dispersed, distance, geographically distributed

1. Introduction

Virtual teams are becoming increasingly common as a means to increaseproductivity (Carmel and Agarwal 2001), produce better outcomes (Martins et al.2004; Miles et al. 2000; West 1999), attract better employees (Henry and Hartzler1997; Martins et al. 2004) and reduce relocation costs (Henry and Hartzler 1997;McDonough et al. 2001; Sole and Edmondson 2002b; Townsend et al. 1998).However, traditional mechanisms for communications, command, and control ofthese teams often become strained or break down (Carmel and Agarwal 2001;Jassawalla and Sashittal 2003; Montoya-Weiss et al. 2001; Sole and Edmondson2002a). Compared to face-to-face collaborations (FFCs), virtual teams need toaddress issues associated with different patterns of communication (Citera 1998;Lipnack and Stamps 1999; Townsend et al. 1998), reduced member awareness

Computer Supported Cooperative Work (2007) 16:567–594 © Springer 2007DOI 10.1007/s10606-007-9070-3

(McKenna and Green 2002; Martins et al. 2004; Schmidt 2002), reduced“richness of information” (Daft and Lengel 1986; Graveline et al. 2000), greaterpropensity for miscommunication (Hinds and Bailey 2003; Montoya-Weiss et al.2001), new trust dynamics (Constant et al. 1996; Jarvenpaa and Leidner 1999;Meyerson et al. 1996), greater conflict (Montoya-Weiss et al. 2001) and culturaldifferences (Lee and Varey 1999). To this end, numerous studies of computer-mediated collaborations (CMCs) have been performed from several perspectives,including but not limited to technology adoption (Davis 1989; Legris et al. 2003;Ma and Liu 2004; Powell et al. 2004), decision support (DeSanctis and Gallupe1987; Fjermestad and Hiltz 1998, 2000; Gopal et al. 1992), psychological factors(Edmondson 1999; McKenna and Green 2002; Sia et al. 2002; Tidwell andWalther 2002; Sherman 2001) and technology-task fit (Fjermestad and Hiltz1998, 2000; Gaver 1992; Powell et al. 2004). With a few exceptions (Olson andOlson 2000, 2003), prior research has typically held the work process constant,attempting to replicate a FFC team paradigm within a CMC. However, while theliterature does not always agree or at times is contradictory on the issue of theproductivity and root causes for problems of virtual teams (Citera 1998;Edmondson 1999; Fjermestad 2003; Fjermestad and Hiltz 1998; Jarvenpaa andLeidner 1999; McKenna and Green 2002; Sia et al. 2002; Sole and Edmondson2002b; Legris et al. 2003; Powell et al. 2004; Wainfan and Davis 2004), it appearsthat successful CMCs will be characterized by more formal procedures andstructured processes than FFCs (Chinowsky and Rojas 2003; Hollan and Stornetta1992; Olson and Olson 2000, 2003; Vick 1998). It is also likely that the processesused by successful virtual teams will be different from those used in FFCs. In whatfollows, the authors define (team) process as a set of repeatable activitiesperformed by two or more individuals to accomplish a specific joint outcome.

The present work is part of a larger study (Cho et al. 2005, 2007; Davidsonet al. 2002, 2003; Lee et al. 2003; Lee and Gay 2004; Odom et al. 2004;Stefanone et al. 2004; Yuan et al. 2006) that, among other things, aims tounderstand the different processes used by successful teams that are virtual versusthose that are co-located and, to whatever extent possible, develop protocols,processes and guidelines that will improve the overall effectiveness andsatisfaction levels of virtual teams. To this end, 16 different geographicallydistributed teams that communicated primarily through CMCs were studied overa 3-year period. Of these, ten teams each worked on projects that lasted 3 months,five worked together for 9 months, and one team collaborated over the full 3-yearperiod. The long-term duration of this study is relatively unique and, particularlyfor the 3-year team, allowed team processes to evolve naturally. In addition, theCMC technologies available to all teams covered a significantly broader domainthan those considered in earlier works. That is, prior research has typicallydefined or limited “CMCs” to computer-mediated, text-based collaborations and/or boardroom or desktop videoconferencing (e.g., Citera 1998; Constant et al.1996; Fjermestad 2003; Fjermestad and Hiltz 1998, 2000; Jarvenpaa and Leidner

568 Daniel J. Rice et al.

1999; Montoya-Weiss et al. 2001; Powell et al. 2004; Schmidt 2002; Tidwell andWalther 2002; Wainfan and Davis 2004). However, CMC environments in usehave become significantly richer than this, and it is clear that a team’s behaviorsin adopting the technology and adapting their processes will be influenced by thefeature-set of the CMC environment that is used. Thus, in an expansion of whatperhaps is its more common usage, here the term “CMC” is used to encompassasynchronous interactions through a collaborative workspace, as well as e-mail,instant messaging, and synchronous interactions using a system that incorporatesdesktop videoconferencing, shared workspace, chat and other features.

The foci of this work were on process adoption, evolution and on whether teameffectiveness can be positively influenced by training team members in processesand protocols that are tailored for use in CMC environments. All teams werecomposed of knowledge specialists working within an engineering design process(Geisler and Rogers 2000; Hammon et al. 2005). Observations of the variousteams, and in particular the team that remained together for 3-years, provided dataon how processes evolved and how these processes were adapted to the CMCenvironment. For example, early teams that remained together for only threemonths all attempted to recreate FFC processes within their CMCs, whereas—after some “trial and error”—the 3-year team gradually adapted their processes totake advantage of the unique capabilities of the CMC environment. Thisapproach to adapt team processes to the capabilities or affordances of the CMCenvironment is consistent with prior research (DeSanctis and Poole 1994; Gaver1992; Gopal et al. 1992; Hammon et al. 2005; Hollan and Stornetta 1992; Olsonand Olson 2003). In order to understand the way in which training influencesCMC success, each new set of teams were trained in those processes andprotocols that had thus far been developed. Various assessment measurementswere then used to compare the effectiveness of these newly formed teams to thoseof teams that had come earlier and received less training, as well as to those thatcame later and received more. The final result is a series of protocols and processesthat are shown to increase the effectiveness of geographically distributed teams ascompared to the case where no training or other interventions occur.

2. Research setting, technology and participants

2.1. Background

In June 2001, Syracuse and Cornell Universities began the “Advanced InteractiveDiscovery Environment (AIDE) for Engineering Education” project (Davidson et al.2002). Among other goals, this project focused on (1) developing the AIDE—a virtual environment that integrates and advances the best features and “bestpractices” of virtual, collaborative engineering environments, (2) understandingthe manner in which geographically dispersed teams tend to collaborate ascompared to co-located teams, and (3) developing “best practices” for the

569Improving the Effectiveness of Virtual Teams

introduction and use of virtual collaborative environments to help facilitate thesuccess of geographically distributed teams. To this end, the AIDE (describedsubsequently) was used as an integral part of an undergraduate, two-semester,capstone engineering design course offered synchronously at Syracuse andCornell Universities. During regularly scheduled class times, student–facultyinteractions generally took place in distance learning classrooms using screen-sharing and videoconferencing technologies, or else using the AIDE withindesign studios that were set-up at both universities (Davidson et al. 2002, 2003).A central focus of the course was a team design project, where student teamswere required to develop candidate designs for portions of the structure andthermal protection system of a next generation launch vehicle (Davidson et al.2003). Annually, there were approximately 30 students in the course (15 per site)that were divided into five teams with three students from each institution oneach team, along with a single faculty “coach,” who could be from eitherinstitution. Outside of scheduled class hours, interactions involving geographi-cally distributed student teams and their coach took place via virtual meetings,i.e., using the synchronous conferencing tools of the AIDE, as well as through e-mail, instant messaging, document repositories, and a limited number of face-to-face meetings. Each year, there were six possible projects, each of which werevariations on the central theme, and each team worked on one of these variations.Coaching assignments from year-to-year were made such that increasingtechnical knowledge on the part of the faculty coaches was not unintentionallytransmitted to the student teams.

The above course provided the setting in which usage of the AIDE and theinteractions of geographically distributed teams could be studied. To facilitateinformation gathering, a variety of assessment tools were integrated into thecourse. These were used to evaluate technology effectiveness and teamproductivity, to make appropriate modifications to the AIDE, and to guide thedevelopment of improved usage protocols and training methods. During the firstyear, the AIDE was deployed as an in-house developed application, and wasfundamentally different from that used during years 2 and 3. There were alsosignificant differences in the course during year 1 versus years 2 and 3. Therefore,the period of work described in this paper primarily focuses on academic years 2(Fall 2002—Spring 2003) and 3 (Fall 2003—Spring 2004).

2.2. The advanced interactive discovery environment

The AIDE consisted of an implementation of the IBM Lotus QuickPlace™asynchronous and SameTime™ synchronous collaboration software. Asynchro-nous services consisted of a course web site that included announcements,document repositories, question and answer boards, threaded discussion boards,student drop-boxes (for course assignments), and on-line presence awareness.


Student team rooms were linked to this site and contained all the samefunctionality as well as project task planning and reporting tools. Synchronousservices were linked to the student team rooms and the course web site andsupported instant messaging and virtual (on-line) meetings. These meetingsincluded participant video, voice-over-IP, document or desktop sharing, a sharedwhiteboard, chat, hand raising features, and various other services, such as theability to post documents to the whiteboard prior to the meeting’s start. Usersaccessed the AIDE from desktop or tablet PCs configured with headsets,microphones, and PC cameras using the Microsoft Internet Explorer™ webbrowser.

Figure 1 presents three views of the asynchronous portion of the AIDE. Therear-most image shows the home page from the Fall 2003 semester. The left handtool bar provides links to general course information and to semester specificcontent. All information that is common to both semesters, such as contactinformation, course description, or the class roster is linked directly to this page.Semester-specific information is contained under the “Fall 03” and “Spring 04”links. For example, if one clicks on the “Fall 03” link, then the middle image isobtained. This page provides all of the information that is specific to thatsemester, for example, the course syllabus, all faculty presentations, homeworkassignments, additional informational materials, and access to team rooms. Notethat the image that is presented is the “faculty view,” i.e., the image that a facultymember would see when they access it, and therefore all student teams aredisplayed. Students, however, only saw—and were able to access—the singleteam room to which they belonged. Student teams were able to modify or createnew structures and/or appearances within their individual team spaces if they sodesired. This could be used to facilitate document organization that wasoptimized for their specific preferences and needs, or simply for aestheticpurposes. The front-most image in Figure 1 shows a customized team space.

Figure 2 shows a view of the synchronous AIDE. In this view, a team isengaged in a virtual meeting and is using the shared whiteboard to interactivelydiscuss the design of a thermo-structural configuration for a reusable launchvehicle. The video display toggles automatically to the team member that isspeaking; below this is a listing of everyone attending the meeting. At the bottomof the image, below the whiteboard, a chat session is evident, but this user haschosen to cover up much of it in order to view more of the whiteboard. That is,the chat window is always active, and each user may scale the size of thewhiteboard to their personal preference. Users may also “undock” the videoimage and place it elsewhere or hide it completely.

For virtual meetings conducted during year 2, two or three students at a givensite generally shared a single PC. For example, a team meeting might take placewith three Syracuse University (SU) students sharing a PC in a design studio atSU, three Cornell University (CU) students sharing a second PC in a designstudio at CU, and the faculty coach on a third PC in his or her office. In these


cases, the students’ PCs were configured with a shared microphone, desktopspeakers, and a web-camera. For reasons that will be discussed subsequently,during the third year, each student was provided with their own dedicated PCwith headset, microphone, and web-camera for all CMC events. This move to “1-PC-to-1-participant” represented a significant improvement in team functioning.All faculty members typically attended virtual meetings via their personal officePC, which was outfitted with a camera, headset and microphone.

Figure 1. Views of the asynchronous AIDE.


2.3. Student teams and technical training

This study included two types of teams: one- or two-semester duration teamscomposed of students, and a 3-year duration team composed of faculty members.At SU, students and faculty were all associated with the Aerospace EngineeringProgram within the Department of Mechanical and Aerospace Engineering, andthe associated course was required for all senior Aerospace Engineering students.At CU, the faculty and the majority of students were associated with either theSchool of Mechanical and Aerospace Engineering or the School of Civil andEnvironmental Engineering. The associated course was an elective at CU, and afew students from other engineering disciplines also participated. In general, thestudents were in their early twenties, were computer literate, and had minimalteam experience and fairly homogenous peer groups. These students are typicalof entry-level engineers. Approximately 24% of the students were female and23% were non-white; both of these groups were distributed essentially evenlybetween universities and across the three years of study. Social, economic andother “external factors” were not considered. For the purposes of this study, teamdemographics were assumed to be homogeneous groups with no specialtreatment or analysis made with respect to group demographic attributes.

The design projects required of the students all lasted one semester in length.The fall semester projects were the same during both years, whereas the springsemester projects were different. Further, during year 2, each student was a

Figure 2. View of the synchronous AIDE.


member of a different team during the spring than the fall semester, whereas theyear 3 team memberships were maintained for both semesters. In total, 15 teams ofstudents were studied: five teams during Fall 2002, five during Spring 2003, andfive during the 2003–2004 academic year. During Fall 2002, all teams had sixmembers: three from each site. During Spring 2003, one student from each sitedropped the course. Thus, three teams had three members per site and two had twomembers from one site and three from the other. During year 3, the same numbersof students were enrolled at each site for both semesters. Three teams had threemembers per site and two had four members from one site and three from the other.

Students were assigned to their team based on their preference of project,technical discipline interests and expertise, their existing social network, teammember compatibility using in-house metrics derived from the Harrison Inner-View profiling system (Harrison 2007), and an overriding subjective determina-tion by the faculty members that no team was “expected to fail” or was expectedto be significantly stronger or weaker than others. In all cases, student teamleadership was allowed to emerge naturally, i.e., as a function of peer groupdynamics. This produced a variety of types of teams, including those with singleleaders based on technical expertise, single leaders based on “popularity,” co-leaders by location, with each based on either technical or social considerations,and flat authority structures with decisions made by consensus. It also produced avariety of teams using various measures of social network structure (Lee et al.2003; Stefanone et al. 2004).

During both years of the research, the entire class was brought together early inthe semester (prior to teams being assigned) for “get to know you events.” Thisicebreaker approach was used to address team building and trust issues identifiedas a critical issue for geographically dispersed teams (Chinowsky and Rojas2003; Hinds and Bailey 2003; Olson and Olson 2000). Early lectures were givenin the distance learning classrooms and provided background material on theproject, teamwork, use of the asynchronous and synchronous AIDE, and on anoverarching design methodology. Following this, teams were split up for a seriesof separate, “discipline specific track” (DST) lectures. For a team comprised ofsix students, the three team members at each site (CU/SU) each attended lecturesin a different DST. One third of the DST lectures were given in the distancelearning classrooms and two-thirds were presented via the synchronous portion ofthe AIDE. Thus, on each six-person team, two students (one at each site), attendedlectures in each DST. In this manner, no single individual within the team couldachieve the project goal independently, and the group diversity necessary to createa cross-functional team was created (Sole and Edmondson 2002a).

2.4. Faculty team

The faculty team consisted of one full professor and one associate professor ateach institution, a research associate at CU, and an information systems manager


at SU. The five faculty members can be characterized as experienced engineerswith an average age of approximately 40, extensive industry experience,multiple team memberships, high computer technology competencies in theirindividual areas, and limited CMC experience at the time of project start-up.The faculty team was responsible for defining the course content and pedagogythat met with their individual university and programmatic standards and todevelop effective distance engineering education teaching practices. Further, theproject’s principal investigator (PI) was responsible for the project administra-tion and the coordination of both content- and technology-related details ofcourse delivery. The inherent grant-based project structure naturally positionedthe PI as a centralized leader over the life of the program. However, theauthority structure in the group was flat, and in this sense mirrored that of thestudent teams.

For the first year of work, all faculty team collaboration occurred throughFFCs, phone conversations, e-mail, and weekly videoconferences. Generally,both FFC and videoconferences followed traditional FFC planning and structure:the PI planned and distributed the meeting agenda, led the meeting discussion,and recorded and distributed the meeting minutes. As has been reportedelsewhere (Vaughan 1996), it was found that videoconferences tended toencourage site-specific “side conversations” that negatively impacted teammeetings. Thus, during year 2, an effort was made to conduct more CMCs usingthe AIDE, where each faculty member used their own PC with camera, headsetand microphone from their own office. These CMCs were also conducted in amanner similar to that of the FFCs. However, the FFCs were found to be moreproductive and satisfying to the team members than either videoconferences orCMCs. The typical thought process during this period of time was aimed atmaking videoconferences and CMCs support traditional FFC processes.

By the end of year 2, the faculty team was quite knowledgeable andexperienced in the strengths and weaknesses of both CMC and FFC as theypertained to the faculty team and the student teams from years 1 and 2. By thispoint in time, a significant change in the thought processes of the faculty hadoccurred: rather than make CMC technologies support FFC behaviors, CMCbehaviors should be tailored to CMC technologies. This is consistent withprevious observations of feature exploitation and process adaptation in newenvironments (DeSanctis and Poole 1994; Gopal et al. 1992; Hollan andStornetta 1992). Throughout this process, the faculty team used their collectiveexpertise to hypothesize, test, and refine a series of CMC “best practices,” i.e.,to develop tools, techniques, processes, and perspectives for improving theoverall team effectiveness. As will be described subsequently, the lessonslearned from this exploration were then communicated to the second semesteryear 2 and the year 3 student teams. During year 3, no faculty videoconfer-ences were held, and approximately 80% of the faculty team’s interactions werevia CMCs.


3. Assessment methods

A design-based research methodology was used for the duration of this project. Inthis methodology, a set of hypotheses and preconditions are formulated toproduce a desired set of outcomes. As the research is conducted, formative andsummative data are collected and analyzed to validate the initial hypothesis andto identify emerging research questions (e.g., “How can CMC be as effective asFFC for specified team activities?”). For the present research, the initial set ofdesired outcomes centered on educational outcomes in a dispersed educationalenvironment. Thus, the hypothesis was: “There exists a set of educational,technical, and administrative processes coupled with CMC technologies that candeliver collaborative engineering design course content effectively in a dual-university environment.” During the exploration of this hypothesis, and asdispersed team dynamics began to emerge, new research hypotheses on teamsocial networks, technology adoption, team productivity, and team formationwere formulated. Thus, the data used in the present study was often intended tomeasure other dimensions of the research project than those for which it wasultimately adopted. Also, the richness of data increased as the project progressedand new lines of inquiry were added.

For the student teams, survey instruments were the primary objective data-gathering tools. Three “technology adoption and social network developmentsurveys” (Cho et al. 2005, 2007; Lee et al. 2003; Stefanone et al. 2004) wereadministered each semester. These surveys were designed to quantitatively assessthe students’ attitude, performance, expectations, satisfaction and experiences.Surveys also asked open-ended questions on all aspects of the course and thetechnology. All surveys were introduced and collected through an independent“evaluations” group, which was comprised of members of CU’s Human–Computer Interactions Group and SU’s Department of Instructional Design,Development and Evaluation. Members of this group were not associated withcourse content or delivery. It was made clear to students that all responses wereheld strictly confidential, and that the faculty team would be provided only withdata; the identities of respondents would under no circumstances be released.Consent to participate was voluntary, and the entire process was performed withthe oversight of institutional review boards at both universities.

In addition to the above, every student filled out two peer- and two self-assessments each semester. In the peer assessments, each student assessed his orher teammates with respect to their perceived contribution to the team, reliability,use of time, and team support. The primary purpose of these assessments was toprovide the faculty with additional information about the functioning of eachstudent team. Often times, this information was used to make “targetedinterventions” to avoid dysfunctional team behaviors and/or outcomes. Theevaluations group also held a few focus meetings with individual students and withstudent groups to allow for in-depth evaluation of various issues. A group-level


analysis was used to identify anomalies among local and remote teammateassessments to determine if distance and thus communication mode (CMC)influenced the outcome. Student grades on oral presentations, written reports, andtheir final grades for each semester were also grouped by team and correlated withother data to help understand various results. For the faculty team, recordings ofextended interviews at the end of year 2 were made and analyzed by a member of theevaluations group, and a comprehensive survey was administered at the end of year 3(Wang et al. 2005).

4. CMC process adaptation

During the time that the faculty team worked together, CMC “best practices”gradually emerged that were reflective of the technology being used, their tasks,social structure, and experiences. Since the project tasks and managementstructures of the student teams were not dramatically different, it washypothesized that training the student teams in these “best practices” wouldimprove their effectiveness. Also, since the CMC “best practices” emerged overtime, different cohorts of teams were exposed to different amounts of training,thereby allowing the influences of the types of training to be differentiated. Thetraining and “interventional exercises” to which each cohort of teams wereexposed are described below, along with an assessment of their influences onteam effectiveness.

4.1. Fall 2002 (semester 1 of year 2)

During year 2, faculty coaches led a “project kick-off” team FFC and participatedstrongly in early team CMCs. However, individual coaches were given thelatitude to provide guidance in team organization, functioning and in the use ofthe AIDE according to his or her own style. Each team also performed an earlyCMC “space survival exercise” to improve their skills within the CMCenvironment prior to it becoming critical for their project-work. Here, each teamwas given the situation where they had crash-landed on the moon with a set ofsurvival tools. They were asked to provide a consensus rank ordering of the toolsby importance for survival. Beyond this, teams primarily “learned by doing.” Asindicated previously, during this semester and during the Spring 2003 semester,teammates at a given site generally shared PCs during CMCs.

4.2. Spring 2003 (semester 2 of year 2)

During the Spring semester of year 2, five different interventional “laboratoryexercises” were conducted to (a) identify various issues surrounding CMCs andFFCs, and (b) improve team performance in the CMC environment. All exerciseslasted one class period. Exercises (1) and (2) were held during the second and


third weeks of the semester. These consisted of teams solving an open-endedproblem that had a “brainstorming” activity followed by a “solution evaluationand selection” activity. The exercises concluded with the consensus-buildingactivity of developing a final short summary of the team’s results. These exercisesare consistent with typical engineering design problems that require bothdivergent (brainstorming) and convergent (consensus) tasks where the divergentactivities are constrained by the design-problem’s domain (Kerr and Murthy2004). Exercises (1) and (2) asked student teams to identify, evaluate and rankorder: (1) methods of removing a ping pong ball from a secured pipe (withoutdamaging it) using a set of given tools (e.g., light bulb, wrench, box of cereal),and (2) ideas to improve profitability of sales of a specific existing chair design.In the first session, problem (1) was given to all teams, but one-half of the teamswere in a CMC environment (each at a separate PC) and the other half were inFFC environments. In the second session, problem (2) was assigned, and thoseteams that had solved problem (1) via CMCs now used FFCs and vice-versa. Atthe completion of each session, all participants completed a short survey that wasdesigned to assess specific difference between FFCs and CMCs in terms ofindividual attitudes. After taking the surveys, short group focus sessions wereheld, where all participants that used a common collaboration environment (CMCor FFC) discussed their experiences together with a faculty member. The focussessions allowed faculty members to make direct inquiries into specific topics andto ask about various behaviors that they had observed.

The third interventional laboratory was held during the fourth week of theSpring 2003 semester. Here, the results from the previous two exercises wereshared and the students were invited to comment. Next, recommendations weremade for improved CMCs as well as for improved team functioning, regardlessof whether interaction was via FFCs or CMC. Recommendations for improvedCMCs presented to the students included (1) using the chat window for teambrainstorming, i.e., such that all team members could provide input simulta-neously without the “filtering” or process blocking that often occurs when asingle individual is transcribing all results, (2) using meeting agendas and otherdocuments to keep meetings focused, and (3) taking notes in real-time for all tosee and disseminating results shortly after meetings concluded. Generalteamwork recommendations also included using an agenda, learning how togive and receive constructive feedback, developing task plans, classical problem-solving strategies, and hindrances to effective problem-solving. As with allfaculty presentations, this was posted on the AIDE, and student teams wereencouraged to use it for their subsequent interactions during the semester. It wasintended that this information would improve team effectiveness by helping theteams to better formalize their CMC processes and structure their CMC events(Chinowsky and Rojas 2003; Olson and Olson 2000, 2003; Vick 1998).

The remaining two interventional exercises were held later in the semester asthe students became more immersed in their design projects. These exercises


were aimed at building skills that the faculty team felt were in need ofimprovement based on their observation during the Fall 2002 semester. The firstexercise focused on “normalizations” at the start of a CMC meeting and on CMCskill building exercises. Prior research has noted that as much as 50% of a CMCmeeting can be spent just getting the meeting started (Olson and Olson 2000).Here, CMC normalizations are defined as making sure that all participants areheard by all others at essentially equal volume, that the microphone sensitivity isappropriate so that parts of each team members speech would neither be“clipped” nor associated with excessive background noise, that the video imagesare all clear and focused on the speaker’s face, and that screen resolutions aresimilar to ensure that all participants are seeing the same image. For example, ifone team member has a lower screen resolution than all the others and is viewinga shared image (e.g., a PowerPointTM slide or ExcelTM workbook), then that teammember will need to use both vertical and horizontal scroll bars on their screen tosee the full image being discussed by the presenter, whereas the full image will bedisplayed appropriately on the remaining team members’ screens. In addition tothe above, talking protocols, such as unrestricted, request to talk, or talk and mutewhen finished (to reduce background noise) were introduced and tried by thestudents. The first skill building exercise consisted of listening and confirminginformation. This was followed by creating an agenda (using a template that wasprovided) for a meeting to address a specific issue within their design project,brainstorming on this issue using the chat window, evaluating the ideas proposed,building a consensus on which idea(s) to pursue, and creating a document thatlisted outcomes. The final interventional exercise asked students to create adetailed, 1-week plan to prepare for their “preliminary design review” thefollowing week. Specific steps were provided for this, as were templates forproject-planning, meeting agendas, and meeting minutes.

4.3. Year 3

The performance of the year 2 teams supported the hypothesis that CMCtechnologies are more effectively used when team processes are adapted to theaffordances of the CMC environment. The faculty team had sufficient time tomake this adaptation, however, it was believed that the student teams did not.Thus, a further hypothesis was that the adaptation process could be jumpstartedby training groups not only on the technology, but also on work processes thatcapitalize on this technology. To evaluate these hypotheses, the training providedduring year 2 was refined and was provided to the year 3 student teams earlierand in a more structured format. To this end, a series of new laboratory exerciseswere created and introduced during Fall 2003, i.e., during semester 1 of year 3.As described below, this training was focused into the areas of CMC normal-izations, brainstorming, and consensus-building.


4.3.1. CMC normalizations

Table 1 presents the CMC normalizations that were introduced to the studentteams. From the table, it may be observed that normalizations were broken downinto the dimensions of infrastructure, technology, communication protocols andmeeting processes. Except for the dimension of infrastructure, all of thenormalizations were introduced as part of a “mini-design project” that alsotaught the students the basic teamwork skills presented during the Spring 2003laboratory exercises 4 and 5.

At the infrastructure level, the use of 1-PC-to-1-participant was found to beextremely important for the effective functioning of the faculty team. That is, asindicated previously, early site-to-site faculty videoconferences tended to fracturediscussions into local subgroups of co-located members. Similar behaviors wereobserved for the year 2 student teams. These “sidebar conversations” typicallycontinued until consensus was reached within the local coalition, after which asingle speaker shared the resulting ideas with the whole team. This type ofinteraction produces site-to-site conflict and has been shown to result in a flaweddecision-making process (Vaughan 1996). Interestingly, both the student andfaculty teams typically arranged for traditional FFC meetings during the periodwhen this mode of distance interaction was being used and critical groupdecisions needed to be made. In contrast to the above, when each member

Table 1. CMC normalizations and methods.

Dimension Normalization Method

Infrastructure 1-PC-to-1-participant Ensure each team member been trainedon system and has PC with headset,microphone and camera

Technology Uniform audio levels Performed at the start of the meetingamong all participants

Appropriate microphonesensitivitiesCommon PC screen resolutionsClear video images

CommunicationProtocols

Selection of a speaking protocol Training on and practice with systemfeatures

Statements relevant to currentdiscussion topic (use chat for off-topic points)

Protocols sampled, discussed, andagreed upon by team

Positive confirmation of decisionsusing technology features

MeetingProcesses

Identification of meeting leader Prepare and post agenda and meetingaids prior to CMC event

Use of agenda, minutes templates,and other meeting aids


participated independently in CMCs, all members had an equal voice andopportunity to participate, and site-to-site distinctions, conflict, and competitionswere less likely to emerge. Moreover, during the Spring 2003 laboratory sessions,it was observed that students that were typically less likely to volunteer, speak up,or offer ideas during FFCs participated more during the 1-PC-to-1-participantCMCs. This finding is consistent with prior research on psychological factors ofCMCs (Edmondson 1999; Gutwin and Greenberg 2002; Mongeau and Morr1999; Sherman 2001; Sia et al. 2002; Tidwell and Walther 2002). During thesesame exercises, student team CMC discussions generally remained on topic andthe issues were debated on their merits, whereas student team FFCs oftenincluded verbal judgments of specific individuals or experienced other socialpsychological process losses (Pinsonneault et al. 1999).

As indicated in Table 1, the second CMC normalization dimension is that oftechnology. As discussed during the description of the final two interventionalexercises during Spring 2003, this consists of adjusting video images, audiolevels, microphone sensitivities and screen resolutions. In the lab exercise,students were first guided on the basic skills needed to configure and adjust theirheadsets, microphones, cameras, and displays. These skills were reinforced at thestart of each faculty-lead meeting, and subsequent exercises provided hands-onpractice to gain proficiency at resolving typical normalization problems.

The third dimension of Table 1 is communication protocols. Network latencycauses a short delay in the switching of audio and video among members as theybegin speaking. Thus, without some prior agreement on how long to wait beforetalking, it was observed that considerable time was lost repeating statements or,worse yet, individuals could become frustrated and stop communicatingaltogether. Use of the chat window or targeted instant messaging for off-topicpoints was also encouraged. The use of technology features such as the “raisehand” indicator was introduced as a means of obtaining rapid confirmations onissues discussed. This type of electronic voting has been found to be an effectivemechanism for achieving and maintaining team member agreement given thelimited media richness found in CMC environments (Daft and Lengel 1986;Graveline et al. 2000; Whitworth et al. 2001).

The final dimension of Table 1, meeting processes, follows that discussed aspart of the final two interventional exercises during Spring 2003. It was observedthat the use of meeting agendas and other aids helped to keep teams focusedduring CMCs. Conversely, student CMCs during the Fall 2002 semester oftendegenerated quickly and required multiple follow-up meetings to achieveoriginally planned team meeting objectives.

4.3.2. Brainstorming

The second focused training objective of the revised CMC “best practices” was todevelop effective brainstorming skills. A typical FFC brainstorming session is


comprised of a group of participants tasked with the generation of ideasconcerning a specific topic that is lead by a facilitator. A common approach is forthe facilitator to collect ideas from the group on a whiteboard or poster board forall to review and from which new ideas might spring. Common problems duringFFC brainstorming events include the transformation of an idea from the originalthought during the recording process, loss of ideas due to multiple ideas beingproposed simultaneously, domination by strong personalities, the reluctance ofreserved individuals to participate, and the tendency to move into an evaluationphase (or interject judgmental comments) before brainstorming is completed(Kerr and Murthy 2004; Mongeau and Morr 1999, Pinsonneault et al. 1999).There is also a second opportunity for ideas to be transformed if the results of thesession are later transcribed and distributed. Due to system latency and otherdifficulties associated with “rapid, free-form discussions,” applying the aboveFFC process to CMCs often produces poor outcomes. For example, during thefirst two Spring ’03 laboratory exercises, student CMC teams produced anaverage of 5.6 ideas per team during the brainstorming portion, as compared to anaverage of 8.7 ideas per FFC team. A Student t-test was performed, whichindicated a significant difference between these outcomes at a 95% confidencelevel (t(95)=2.2, p=0.04). Exercise observations and post-exercise discussionsindicated that the FFC environment was more natural and spontaneous, but thatreserved (“shy”) team members were more willing to share ideas during CMCsthan FFCs. Also, although most teams adopted the FFC process within the CMCenvironment, those teams that adopted a brainstorming protocol where allmembers typed in their own ideas liked the absence of interpretation by afacilitator. These observations suggested that CMCs can address many of theprocess blocking and social psychology problem areas associated with brain-storming while approaching a similar productivity level as FFCs, providing thatthe CMC brainstorming process is adapted to the strengths of the CMCtechnologies (Kerr and Murthy 2004).

In contrast to the behaviors of the student teams, when the faculty teamperformed the brainstorming exercises, all team members provided simultaneous-ly typed input using the chat window. A strict “no evaluations or judgments” rulewas adopted, and this resulted in a great deal of good-natured verbal banter asideas were typed in. Ideas were observed to build on each other in a natural way,and the team’s subjective assessment was that their output was at least as high, ifnot higher, than they would have achieved in an FFC. Further, all membersgreatly liked the absence of the “facilitator filter” and the overall pace of theprocess was much faster than typical FFC sessions. This is in keeping with earlierfindings on structured electronic brainstorming (Kerr and Murthy 2004; Mongeauand Morr 1999). As will be shown subsequently, brainstorming was one of thoseactivities that the faculty team developed a preference for performing in CMCsrather than FFCs. Student teams were taught this approach during the Fall ’03mini-design project activities. Although this improved outcomes, student teams


still showed a tendency to mix brainstorming and evaluation activities. This isperhaps a function of the students lacking process disciplines that come withexperience and maturity.

4.3.3. Consensus building

Common follow-ups to brainstorming include organizing the resulting idea setinto themes, discarding ideas that are not practical or appropriate given theproblem’s constraints, evaluating those ideas that remain, and obtainingconsensus on those idea(s) to pursue further. The evaluations phase is typicallyone of intensive discussions. Conversely, the consensus phase, which can bethought of as choosing amongst options, can be done quite rapidly. Its goal isprimarily to determine whether team members agree on a specific course of actionor whether further discussion is needed. Consensus building shares many of thesame process blocking and social psychological problems as brainstorming, andthere is a tendency to mix this phase with the brainstorming and evaluation activities.Thus, this activity presented another opportunity to improve team effectiveness byadapting team processes to take advantage of the CMC technologies.

Based on the faculty team’s insights and experiences, a consensus buildingprocess was developed and introduced to the student teams. The process wasbased on the assumption that one CMC is used for brainstorming and a second isused for consensus building. In between these two meetings, one or moretemplates are created similar to that shown in Figure 3. This particular figurepresents results from a faculty team CMC near the end of year 2 that focused onpotential modifications to the course for year 3. The left hand column presents theinitial of the team member that has proposed an idea. This is followed by adescription of the idea itself, and a “voting” space where members can use simplepen-strokes or keyboard entries to indicate their acceptance levels. Note that thevoting options are “agree, disagree, discuss, or pass.” During template mark-up,no discussions of merit are conducted. Rather, the shared chat space and verbalinteractions are used solely for idea clarification. The construct thereforeeliminates the tendency by many teams to combine this activity withbrainstorming and idea evaluation. Note that many variations on this theme canbe used based on the specific needs of the team and the team’s dynamics. Forexample, idea proposal and/or voting could be made anonymous.

Referring once again to Figure 3, following template mark-up, all members ofthe team can rapidly see which ideas are accepted and therefore do not require theexpenditure of meeting time for additional discussion. Thus, the meetingmoderator can facilitate discussion of the issues where there is disagreement ora desire for more dialogue. As the opinion of each team member is known, themeeting moderator can ask specific individuals to state their concerns, respond, orprovide input. In this way, the influence of dominant personalities is mitigated,and the meeting structure enforced through use of the template helps to keep the


team focused. As will be shown below, use of this process resulted in CMCconsensus building activities to be rated as highly effective in an absolute senseas well as in comparison to FFCs.

5. Findings

5.1. Influence of process change

Table 2 presents results from surveys of students at the end of each of the foursemesters comprising years 2 and 3. As indicated previously, the surveys thatwere used were intended to measure a variety of behaviors, and hypotheses

Figure 3. Example of CMC consensus template.


changed over the duration of the research. Thus, Table 2 contains those questionsthat were asked in all four semesters that measured various aspects of the waythat teams functioned within the CMC environment. As indicated, all questionswere on a 7 point Likert scale, with 1=strongly disagree, 4=neutral, and 7=strongly agree. For each semester the mean and normal standard deviation (SD)of all students and teams combined are presented. The p values following thequestion statements were obtained from a single-factor analysis of variance(ANOVA) with a 95% confidence level. Note that questions a and b indicated nosignificant difference among groups, whereas a significant difference wasobserved for questions c–e. Inter-group, two-tailed t-tests were performed toassess whether there were significant differences in mean responses between agiven test group and the one that immediately followed at a 90% confidencelevel. The t stat for these tests are presented after the SD data for the Fall 2002(F02), Spring 2003 (S03) and Fall 2003 (F03) groups. Questions c and d, whichare two of the three questions identified by the ANOVA test as being significant,showed a significant difference from the fall to the spring semesters in both years.It is believed that the increase in the perceived effectiveness of the CMCenvironment (the AIDE) between F02 and S03 is a result of the five interventionallaboratory activities held during the S03 semester. It is likely that there is also aneffect of the students becoming increasingly familiar with the technology. Thedevelopment of social networks among students was observed not to significantlyaffect the results (Cho et al. 2007). Since student teams changed from the F02 toS03 semesters, increasing familiarity of team members with one another is likelynot a strong factor. Improvements from F03 to S04 are hypothesized to be a resultof the increasing familiarity with the CMC environment and, since teams were notchanged during year 3, from the transition to a more smoothly functioning team.

Table 2. Survey responses from all students over the four semesters studied.

Question (7 point scale: 1=stronglydisagree; 7=strongly agree)

Fall 2002 Spring 2003 Fall 2003 Spring2004

Mean (SD) tstata

Mean (SD) tstata

Mean (SD) tstata

Mean(SD)

a. Discussions during meetings stayon track (p=0.66)

4.81 (1.49)0.66

4.85 (1.26)0.51

5.09 (1.51)0.35

5.22(0.97)

b. Time in meetings is time well spent(p=0.52)

4.52 (1.22)0.13

4.85 (1.54)0.69

4.69 (1.64)0.09

5.07(1.17)

c. Use of AIDE significantly increasesquality of team work (p=0.00)

3.93 (1.47)0.01

4.85 (1.17)0.68

4.72 (1.28)0.08

5.26(1.35)

d. Use of AIDE increases effectivenessof performing team tasks (p=0.01)

4.22 (1.37)0.00

5.15 (1.17)0.18

4.72 (1.28)0.08

5.41(1.42)

e. AIDE increases quantity of outputfor same amount of effort (p=0.00)

3.48 (1.37)0.10

4.11 (1.60)0.34

4.50 (1.48)0.29

4.96(1.43)

aFor a two-tailed Student t-test between the current group and the immediately following group (α=0.1)


Increasing social networks were shown to have negligible influence on these results(Yuan et al. 2006).

Applying the inter-group, two-tailed t-tests at a 90% confidence level forquestions c–e to the F02 and F03 responses yielded significant differences in themeans for questions c and e (t(90)=1.67, p=0.03 and t(90)=1.67, p=0.01),respectively. Question e also showed a significant difference in the mean fromS03 to S04, with (t(90)=1.67, p=0.04). This is likely a combined effect of thechange to 1-PC-to-1-participant and the training on teamwork, CMC normal-izations, and “best practices” that were introduced at the start of the F03 semester.This is particularly impressive, as early FFCs were required during the F02semester but not during F03, and during F03 roughly half the teams chose not tohave any FFCs. Interestingly, comparing the F02 and S04 groups, questions c–eall showed a significant mean difference, all with probabilities of (t(90)=1.67, p=0.00). Thus, in addition to the changes from fall to spring in any given year, thereis a significant improvement from the first year to the second.

5.2. CMC versus FFC perceptions

Table 3 presents survey responses from the faculty team and the year 3 studentteams on the use of CMCs for various types of activities. Note that the questionswere not posed identically: members of the faculty team were asked to rate FFCversus CMC (1=FFC better; 7=CMC better), whereas questions were posed tothe students in an absolute sense (1=strongly disagree; 7=strongly agree). Thus,although the numerical scores cannot directly be correlated, a faculty assessmentfavoring the CMC condition and a student assessment in strong agreement withthe CMC condition both indicate a positive perspective of the CMC conditionbeing evaluated. The faculty team, who used the brainstorming and consensus-building protocols described above, scored these two activities the highest.

Table 3. Survey responses from faculty team and year 3 student teams.

Question (7 point scale) Facultya Spring 2004Studentsb

Mean SD Mean SD

1. Brainstorming 4.40 2.07 4.88 1.802. Evaluating ideas 3.90 0.22 5.08 1.623. Consensus 4.40 1.67 4.88 1.144. Sketching 3.00 1.22 4.96 1.225. Communicate effectively 3.60 0.55 5.12 1.536. Accomplish goals in CMCs v FFCs 4.60 0.89 4.40 1.68a1FFC better, 7CMC better. All questions asked: “Evaluate your team’s effectiveness to perform inCMC vs FFC”b1Strongly disagree, 7strongly agree. Q1–4: “The AIDE was useful for...”. Q5: “I couldcommunicate effectively using the AIDE.” Q6: “My team was as effective in CMCs as FFCs.”


Student teams also rated these activities highly, but gave an even higher absoluteranking to “evaluating ideas” during CMCs. It is believed that this is due to thefact that, even after the Fall 2003 training, student teams still tended to mixbrainstorming, evaluating and consensus activities together. Students appear tohave rated the CMCs better for sketching than faculty, perhaps because many ofthem used tablet PCs whereas the faculty primarily utilized a desktop PC duringCMC events. The difference in student and faculty scores on question 5 is likely amanner of phrasing (shown in the table’s footnotes). Faculty members responsesto other survey questions indicated that they believed that they communicatedeffectively in CMCs, yet still felt FFCs to be more effective overall. The apparentcontradiction between this point and the faculty response to question 6 is resolvedwhen one realizes that faculty used CMCs for meetings with very specific, pre-defined goals (task-based), whereas they used FFCs to address more difficult,open-ended problems (negotiation-based).

Table 4 presents survey responses at the end of year 3 from the faculty teamonly. Responses to the first two questions reflect the faculty members’ strongbelief that moving to 1-PC-to-1-participant during year 3, where each participanthad their own headset and microphone, was an extremely important step towardsincreasing the effectiveness of the student teams. Question 3 indicates that thefaculty team felt that adopting the normalization processes of Table 1significantly increased the effectiveness of their own CMCs. The next questionin Table 4 indicates that the faculty team believed that video, as it was configuredwithin the synchronous CMCs (cf. Figure 2) was relatively unimportant. Asimilar attitude was reflected in the behaviors of the student teams, who generallywere unconcerned about the clarity or quality of the video, and in many instancesstudent team members turned their own cameras off. This is not to say that videois unimportant altogether, however. Rather, recall that the only video imagedisplayed is that of the speaker and, as such, there is no visual feedback from

Table 4. Survey responses from faculty team.

Question (7 point scalea) Mean SD

1. Impact of 1-PC-to-1-participant on student team effectivenessb 6.40 0.892. Impact of individual headset & microphone on student team effectivenessb 6.00 1.733. Importance of “normalization” of audio/video to meeting effectiveness 5.80 1.104. Importance of speaker’s video image 2.60 1.525. How valuable is it to see multiple (or all) participants 5.20 2.056. Importance of technical proficiency with CMC tools 6.40 0.897. Recent CMCs used time efficiently compared to FFCs 5.20 1.308. Importance of meeting agendas in CMCs compared to FFCs 4.80 1.309. Recent CMCs remained focused/on-track compared to FFCs 5.20 1.30aQ1–6: 1Minimal, 7significant. Q7–9: 1FFC better, 7CMC betterbQ1–2 asked faculty team members’ opinions on student teams; Q3–9 asked about the facultyteam’s effectiveness


listeners nor sense of connectedness when speaking. Question 5 and its associatedopen-ended comments revealed that the faculty team would have preferred theoption of seeing any or all team members at any time. This would allow one to bemore in-touch with non-verbal cues, particularly whether or not all team memberswere focused on the current topic. In fact, this was rated as one of the mostdesirable technology improvements among all those that were suggested. Theremaining questions in Table 4 mirror the findings described above.

5.3. Summary of data

Table 5 presents a summary of all process adaptations and technology adoptions.These represent integrated findings from numerical and open-ended responses onthe student and faculty surveys, from student focus group meetings, reviews ofrecorded CMC sessions, questionnaires distributed after the laboratory exercisesduring Spring ‘03, and the recorded faculty interviews at the end of year 2. Thetable is broken up into aspects relating to meeting preparation, meeting dynamics,and post-meeting outcomes dissemination. Those issues that appear in this tablebut not in previous ones, such as developing conceptual understanding ornegotiating, were asked multiple times in a variety of formats. However, this wasnot done in a consistent method across teams or years that facilitates numericalcomparisons. Thus, the more subjective approach of Table 5 is used.

As might be expected, Table 5 indicates that it is easier to schedule CMCs, butteam leaders indicated that to run one effectively required a great deal morepreparation time and effort than was typical of FFCs. For meeting activities, thebrainstorming and consensus activities essentially agree with results presentedpreviously. Document creation and task assignments were favored in the CMCenvironment due to the ability of all team members to participate and see results inreal-time. Teams also took advantage of the technology to provide confirmationson many items and sub-items during meetings without disruptions. Immediatedissemination of meeting outcomes without the filtering process inherent intranscribing notes was seen as highly favorable. In summary, Table 5 and thepreceding data indicate that many aspects of CMCs can be equal to or moreeffective than FFCs providing that team processes are adapted to the CMCenvironment. It is also pointed out that “equal effectiveness” is generally viewed asfavorable to CMCs, as this environment is associated with additional benefits suchas reduced travel costs, the ability to attract better employees, and/or the avoidanceof employee relocation costs (Fjermestad 2003; Fjermestad and Hiltz 1998, 2000;Ocker and Yaverbaum 1999).

6. Conclusions

A study was conducted on virtual teams that interacted primarily via computer-mediated collaborations. These CMCs included asynchronous interactions withina team workspace and synchronous interactions using a system that incorporated


desktop videoconferencing, shared workspace, chat and other features. The studyexplored process changes in virtual teams that took advantage of the CMCtechnologies to enhance their effectiveness, and assessed how these processchanges affected team functioning in an absolute sense as well as in comparison

Table 5. Summary of findings.

Task or attribute Moreeffectiveformat

Reason Comment or improved CMC“best practice”

Meeting preparationSchedule meeting CMC Anytime, anyplace meeting

format–

Prepare documents FFC CMCs require more up-frontpreparation, as agenda and“discussion-guiding”documents seen as essentialto successful outcomes

These documents also aide inFFCs, however, easier to“get-by” without them

Meeting dynamicsFlow of conversationand work-process

FFC “More natural” 1-PC-to-1-participant andsystem normalizationprotocols significantlyimproved CMC dynamics

Develop conceptualunderstanding

FFC Discussion-intensive System performance hindersCMC effectiveness

Brainstorming CMC Eliminates “filtering” andinfluence of dominantpersonalities

Result requires CMC-optimized simultaneousinput method

Evaluating ideas FFC Discussion-intensive System performance hindersCMC effectiveness

Negotiating adesired outcome

FFC Discussion-intensive, requiresnon-verbal social cues

High potential for unresolvedconflict in CMCs

Choosing amongoptions

Neutral Appropriate CMC-processallows equal input frommembers

Result requires CMC-optimized method

Document creation CMC Allows document to beviewed and input to bereceived from all members

Requires adoption ofassociated meeting protocol

Confirmations CMC Natural tendency observedfor confirmations to occurmore readily in CMCs

System features allowconfirmations during CMCsthat are easy and non-disruptive to adopt

Task assignments CMC Can be done as real-timedocument creation

Real-time buy-in by teammembers

Dissemination of meeting outcomesDistribute outcomes CMC Minutes and resolutions kept

in real-time may bedistributed immediately;results “unfiltered”

Requires adoption ofassociated meeting protocol


to face-to-face collaborations. In many respects, the suite of integratedtechnologies used by the virtual teams was considerably richer than in therelated works that have been cited, and in this sense the present work provides animportant new contribution. It also provides a unique perspective in that, for thefaculty team, changes in team processes were observed over an extended (3 year)time period, and the effect of introducing the new paradigms developed by thisteam were observed for teams that were newly introduced to CMCs.

Similar to that which has been reported previously, this study found that theadoption of formal procedures and structured processes significantly increased theeffectiveness of virtual teams. Extending this concept, it was found that thosetasks that lend themselves to a structured approach are most effectivelyaccomplished during CMCs. Examples of this include brainstorming, consen-sus-building, and “status update meetings” for disseminating and describingrecent results. In contrast, FFCs appear to be better suited for relativelyunstructured, discussion intensive tasks, such as developing a conceptualunderstanding of a problem or evaluating key ideas and negotiating how toproceed. Further, it was found that the performance of a virtual team can besignificantly enhanced when team processes are adapted to the affordances of theCMC environment, and that this adaptation can occur very rapidly if teams aretrained on the technology as well as on work processes that best exploit it.

In order to help newly formed teams more rapidly adapt to CMC environ-ments, targeted, relevant training methods for CMC teams on the technology,methodologies for team functioning, and CMC-appropriate protocols andprocesses were developed. This training was shown to produce significantimprovements in the performance of short-duration teams, and it is likely that itwill help CMC teams of longer duration adapt and reach a level of highperformance more quickly than they otherwise might. Normalizations across thedimensions of infrastructure, technology, and communication protocols wereproposed to help the team obtain proficiency in the technology and to haveproductive meetings. These normalizations, coupled with formalized meetingprocesses, should allow teams to leapfrog many of the typical start-up problemsof virtual teams. Team processes for brainstorming and consensus-building werealso proposed. This type of training will not only teach these specific andeffective CMC processes, but more broadly will teach teams to exploit theinherent advantages of the CMC environment. That is, the most important aspectof the proposed training is its emphasis that one should not simply try to instituteFFC processes within CMC environments, but rather that teams need to developand implement processes that are aligned with the technologies being used.

Acknowledgements

This work was supported by NASA Langley Research Center under CooperativeAgreement NCC-1-01004 and Grant NNL05AA08G, by the Empire State


Development Corporation under Project Q181, and by the AT&T Foundationunder Grant 000203938.

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Improving the Effectiveness of Virtual Teams

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