creating hybrid distributed learning environments by implementing distributed collaborative writing...

IEEE TRANSACTIONS ON PROFESSIONAL COMMUNICATION, VOL. 47, NO. 3, SEPTEMBER 2004 171

Creating Hybrid Distributed Learning Environments byImplementing Distributed Collaborative Writingin Traditional Educational Settings

—PAUL BENJAMIN LOWRY, MEMBER, IEEE, JAY F. NUNAMAKER, JR., QUEEN ESTHER BOOKER,AARON CURTIS, AND MICHELLE RENE LOWRY

Abstract—This paper summarizes three field experiments involving distributed collaborative writing (CW)in traditional educational settings creating a hybrid form of distributed education. One finding shows thatspecialized collaborative tools allowed for parallel work, group awareness, and coordination, providingsubstantial advantages over traditional word processors in distributed CW. However, it was also found thatadvanced CW tools alone did not provide optimal results in distributed CW groups; such groups also neededhigh levels of process structure, which can be delivered through carefully constructed scripts. Moreover, it wasfound that introducing face-to-face meetings in distributed CW work did not necessarily provide advantagesover work that was performed in all-distributed settings. Given these findings, this paper concludes bydiscussing the contributions, implications, limitations, and future research possibilities for hybrid-distributededucation.

Index Terms—Collaborative tools, collaborative writing (CW), distributed education, distributed work, groupwriting, hybrid distributed education.

Improving distributed education has long been animportant research goal and pedagogical aspiration.When used effectively, distributed education can:

(1) increase the ability of teachers to reachnontraditional students and full-time employeeswho would otherwise have difficulty continuingtheir education

(2) improve diversity in education by incorporatingmore nontraditional students

(3) provide effective use of scarce educationalresources

(4) broaden the educational reach and impact ofan institution

(5) diversify learning experiences by introducing aunique method of educational delivery

(6) allow instructors to spend less time in theclassroom and more time mentoring theirstudents and developing curriculum

Manuscript received June 11, 2003; revised September 29, 2003.P. B. Lowry and M. R. Lowry are with the Kevin and DebraRollins Center for e-Business, Marriott School of Manage-ment, Brigham Young University, Provo, UT 84602 USA(email: [email protected]; [email protected]).J. F. Nunamaker, Jr. and Q. E. Booker are withthe Center for Management of Information,University of Arizona, Tucson, AZ 85721-0066 USA(email: [email protected]; [email protected]).A. Curtis is with the Information Systems Department,Kelly School of Business, Indiana University,Bloomington, IN 47405 USA.

IEEE DOI 10.1109/TPC.2004.833689

(7) foster more evenly distributed studentparticipation

(8) involve students who are normally uncomfortableparticipating in the classroom

(9) maximize resource use by creating hybridlearning environments that involve a mix oftraditional, face-to-face (FtF) interactions anddistributed education

Although many initiatives have implemented andresearched distributed education, few effortshave focused on distributed education involvingcollaborative groups. Instead, most distributededucation research focuses on delivery to individualstudents. Certainly, individual student delivery issalient; however, if institutions and instructors focussolely on this aspect of distributed education, theyrisk isolating their distributed students and denyingthem the rewards of group work.

Further, it is ironic that most coursework in educationfocuses on individuals, whereas most professionalwork is collaborative [1]. Collaborative work has longbeen recognized as an effective method of fosteringlearning in traditional FtF classrooms and is usefulin countering highly individualistic and sometimescounterproductive, competitive learning environments[2]. The use of distributed collaborative writing (CW)in education is the specific group activity on whichthis paper focuses. CW is a useful group activity tofocus on in education because of its prevalent use inmany settings.

0361-1434/04$20.00 © 2004 IEEE

172 IEEE TRANSACTIONS ON PROFESSIONAL COMMUNICATION, VOL. 47, NO. 3, SEPTEMBER 2004

CW is a complex yet critical form of professionalcommunication that is widely used in industry,academia, and government [3]–[6]. It is an iterativeand social process that involves negotiation andcommunication with multiple participants in thecreation of a coordinated document. The potentialscope of CW goes beyond the basic act of jointcomposition to include the likelihood of pretask andposttask activities, team formation, and planning.Based on the desired writing task, CW includes thepossibility of a variety of writing strategies, activities,document control approaches, team roles, and workmodes [7]. Given this background, we define CW asfollows:

an iterative and social process that involvesa team focused on a common objective thatnegotiates, coordinates, and communicatesduring the creation of a common document. Thepotential scope of CW goes beyond the more basicact of joint composition to include the likelihoodof pre- and post-task activities, team formation,and planning. Furthermore, based on the desiredwriting task, collaborative writing includes thepossibility of many different writing strategies,activities, document control approaches, teamroles, and work modes. [7]

Because CW is a complex and pivotal group processin academia, government, and industry, it hasprompted much interdisciplinary research, includingperspectives from rhetoric and composition, socialpsychology, communication, and informationsystems. Examples of interdisciplinary studiesinclude topics such as CW strategies [8], problemsencountered by MBA students using basic CWtechnologies [9], CW processes and practices in themilitary [10], CW in e-Government [6], authority inCW groups [11], CW engineering co-op experiences[12], CW in the workplace [13], large CW groups [14],ethnographies on large CW groups [15], CW usingcomputer-mediated communication (CMC) [16], CWhypertext technologies [17], CW specific technologies[6], [18], and so forth.

Since CW is widely practiced yet requires substantialtraining for effective execution because of itscomplexity, CW should be integrated throughouteducation [8]. Many factors make CW more complexthan single-author writing [19], [20], including theincreased need for coordination [21] and consensus[16]; increased social, intellectual, and proceduralcomplexity [16]; fluctuating group commitment [4],[22]; more conflicting commitments [23]; and moresocialization and communication [24], [25]. Alreadypivotal to many group processes, distributed CWis becoming more common because of the growingphenomenon of distributed work, which is expandingrapidly due to increased globalization, competition,and internet use. Thus, it is useful to teach studentshow to write in distributed groups so that they will

be able to work effectively in an increasingly globalwork environment.

However, the bulk of current CW research focuses onnonempirical studies of FtF CW groups, leaving theopportunity for more empirical research of distributedCW. An extensive review of 252 major CW researcharticles reveals some of the gaps in previous CWresearch [26]. For example, many studies focus onsimplistic CW scenarios, whereas approximately 16%of studies show empirical results. Discussion is usedas the primary research methodology in 38% of thestudies. Only 2.78% of the studies have high-powerstatistical results. Internet-based distributed teamscomprise 5% of the CW studies involving education.In summary, only a small minority of distributed CWresearch involves empirical studies in educationalsettings, and almost no research has focused oncreating hybrid distributed settings with CW, despitethe growing trend of hybrid CW use in the workplace.We believe incorporating hybrid CW into traditionalFtF classrooms can be an effective approach forimproving students’ preparation to perform suchwork.

The studies described in this paper represent ourefforts to research hybrid distributed CW in aneducational setting. We built an internet-baseddistributed CW tool and then implemented it in threehybrid distributed university environments. We notonly studied technologies to help facilitate hybridenvironments but we also looked at considerations ofhow work processes should be structured for CW andaddressed whether an optimal mix between FtF anddistributed work modes exists in student CW teams.The next section reviews these three studies.

OVERVIEW OF HYBRID DISTRIBUTED CWRESEARCH

Early in our research, we hypothesized that toolchoices would have a particularly strong impact ondistributed CW because CW groups need to be ableto conduct parallel work with group awareness andcoordination to be effective. Tool choices greatlyaffect these factors [20]. All three studies usedCollaboratus, a CW tool that allows parallel work,group awareness, and coordination. The next sectiondescribes Collaboratus and is followed by a summaryof our studies.

Collaboratus Overview Collaboratus is anexperimental, internet-based CW tool that is theresult of years of field work and research [6]. It isdifferent from previous CW software because it isbuilt entirely using Java, which allows Collaboratusto run through virtually any web browser, operatingsystem, and/or hardware platform without requiringthat end-users be aware of its technical details.Collaboratus also supports a virtually unlimited

LOWRY et al.: CREATING HYBRID DISTRIBUTED LEARNING ENVIRONMENTS 173

number of users, depending on the speed of thenetwork connections and the computers being used.

Collaboratus builds on previous CW tools bysupporting a full range of CW activities, such assetting up user roles and rights, creating groupagendas and plans, brainstorming contents,sharing group outlines, voting on group decisions,creating group papers, reviewing, and annotating.Collaboratus also allows group members to workeither asynchronously or synchronously in distributedwork modes or to use a mixture of both work modes.Fig. 1 highlights the CW features of Collaboratus. The

Fig. 1. Collaboratus writing (outline on left, editedsection on right).

group outline appears on the left of the screen. Groupmembers can access any section of the outline andedit its corresponding text. The text that appears onthe right of the screen is the section from the outline

that is highlighted by a user; each group member canwork in different sections of the outline while othergroup members work at the same time. Collaboratusalso supports several other activities with differentscreens, such as shared group brainstorming,voting, outlining, annotating, controlling documentversions visually, and listing active participants. Suchfeatures enhance parallel work, group awareness, andcoordination, features that are not fully supported byword processors, such as Microsoft Word (see Table I).

Collaboratus is more than a typical CMC product. Toframe Collaboratus in the context of other productivitysoftware, it is useful to build on concepts proposedby Nunamaker et al. [27]. Their study proposesthree categories of software based on varying degreesof group work: individual, coordinated work, andconcerted work levels. Software associated with theindividual work level promotes individual productivitywith no immediate group focus, as seen in wordprocessors and spreadsheets. Software used atthe coordinated work level involves software thatsupports group activities that are largely made upof coordinated but independent contributions. Mostsoftware that provides coordinated work includesCMC software, such as email, instant messaging,and bulletin boards. CMC systems are traditionallydesigned to enhance basic communication, as seenwith email or threaded chat boards. CMC systemsdo not provide support for advanced coordination,shared document updating, complex forms ofcommunication, detailed decision making, oradvanced levels of task and process structure (PS).The concerted work level represents the softwarethat is the most collaborative and requires concerted

TABLE ICollaboratus CW features versus Word CW features [20]


group effort and complex communication. This levelof software is the traditional realm of group supportsystems (GSS), where Collaboratus belongs. We depictthis overall framework in Fig. 2. The next sectiondescribes our studies using Collaboratus in hybriddistributed educational settings.

STUDY ONE: SYNCHRONOUS-DISTRIBUTEDCW TOOL STUDY

Background Study one involved a field experimentin a hybrid distributed educational setting in whichall participants worked in a synchronous-distributed(SD) work mode using either Collaboratus or Wordas reported in [20]. To focus comparisons on salientgroup awareness and coordination differencesbetween these products, all groups used MicrosoftNetMeeting for their communication.

Hypotheses Research comparing CW tools totraditional word processors or text editors shows thatgroups using CW tools have greater productivity [17],[18] and quality [17], [18], [28] than groups usingtraditional word-processing tools. Satisfaction amongparticipants of CW tool groups is often lower thanword processor groups in one-time experiments [18],but over time satisfaction levels of collaborative-toolgroup members in longitudinal studies increasesto a level either equaling or surpassing satisfactionlevels in noncollaborative tool groups [29], [30]. Theseresults can be attributed to the ability of collaborativetools to enhance group awareness (knowledgeabout the activities of other group members) and

coordination (the ability of group members to worktoward a common goal) among CW participants [31].

CW tools enhance group awareness throughspecialized technology features in the form ofinformation sharing mechanisms that show groupmembers the nature of other members’ activities andthe effects of those activities on the content of the CWdocument [32]. Group awareness provides a contextfor an individual’s activities in a collaborative setting[32].

Coordination is supported by CW technology featuresthat allow members to share information thatsupports the formation of and progress towardcommon goals. In CW activities, these coordinationmechanisms can be provided by advanced CW toolsthrough activity-centered modules (e.g., a groupoutliner, a group brainstorming module, and soon), as well as by annotation features and sharedediting. CW groups using tools that enhance groupawareness and coordination should, therefore, beable to complete their goals more efficiently andeffectively than if they were using tools that lack thesecapabilities.

Although contemporary word processors like Wordinclude basic features for tracking changes andinserting comments, these basic tools encourage asequential rather than parallel work mode, and theylack the shared interface necessary to efficientlysupport collaboration between more than two authorsat once (see Table I). Coauthorship, using word

Fig. 2. CW software compared to other forms of software.


processors, typically involves a number of possiblesequential work scenarios:

(1) Authors individually create separatesubdocuments that each focus on a distinctsection of a paper, and one author is ultimatelyresponsible for synthesizing the separatedocuments into a single paper.

(2) Authors make simultaneous revisions ondifferent copies of a document, with one authorresponsible for synthesizing the differentchanges into a single paper.

(3) One author creates a draft, which is revised by asecond author, who sends the paper on to a thirdauthor, and so on, leaving the last author tohave the last say on the final draft of the paper.

All three scenarios lack high levels of groupawareness, and this deficiency results in unbalancedcontributions and duplicate work, or evencontradictory work.

The supported differences in group awareness andcoordination between Collaboratus and Word lead toseveral constructs and theoretical propositions thatare further developed in [20], creating the followinghypotheses:

H1: Distributed CW groups that use Collaboratuswill experience higher productivity thansimilar groups that use Word.

H2: Distributed CW groups that use Collaboratuswill produce higher quality documents thansimilar groups that use Word.

H3: Distributed CW groups that use Collaboratusover time will experience higher satisfactionthan similar groups that use Word.

H4: Distributed CW groups that use Collaboratuswill experience better relationships with groupmembers than similar groups that use Word.

H5: Distributed CW groups that use Collaboratuswill experience better communication thansimilar groups that use Word.

Participants Forty-seven students from amanagement information systems course at a large,public, southwestern university participated in thisstudy for class credit. Participants were randomlyassigned to groups of three. The students had noprevious experience working together, as confirmed byquestionnaire data. Since they were sophomore-levelstudents, most participants had experience withrudimentary English composition but had notparticipated in an advanced writing course. Therandom assignment of students to groups negatedthe effects of some groups having an individual whohad strong composition skills or who was a dynamicleader, since the likelihood of a group in eithertreatment obtaining such a participant was equallyprobable.

Design The manipulation of tool choice for this studyentailed two conditions. (1) Control groups used Word

for CW and NetMeeting for all SD communication.(2) Treatment groups used Collaboratus for CW andNetMeeting for all SD communication.

Procedures All participants were randomly assignedto a condition, and then randomly assigned to agroup. Participants worked in one of two similar GSSrooms during class time in a simulated distributedenvironment where they could only communicate withtheir team members using NetMeeting (an example ofone of the GSS rooms is shown in Fig. 3). Collaboratus

Fig. 3. Example of GSS room used for experiments.

participants could use Collaboratus only forCW activities, not for synchronous, chat-basedcommunication. The field experiment took place overfour weeks with four different sessions. Session oneof the experiment involved group formation. Sessiontwo of the experiment involved idea generation andoutlining. The actual CW work sessions were held insessions three and four, from which observationalmeasures were derived.

To further improve experimental control, the sessionswere carefully scripted. Trained facilitators read frompretested scripts, strictly monitored team behavior,and carefully timed each activity and process toensure that all the participants conducted the majoractivities of CW (team formation, brainstorming,outlining, drafting, reviewing, revising, and finaldrafting) in a similar fashion for the same amountof time. Further details on the setup, control, andmeasures for this experiment are contained in [20].

Measures In addition to testing the traditionalCW constructs of productivity, quality, andsatisfaction, this study also tested relationships andcommunication. Measurements of these constructswere designed to capture the underlying theoreticalmeanings of the related constructs as closely aspossible, using multiple measurement approaches asdescribed by Lowry:

(1) Observed productivity measures were extractedfrom the group papers and session logs to


yield the size of group documents (number ofwords), production of words in chat sessions,time spent on CW activities, group participationpercentages, and group completion rates (i.e.,which groups completely finished every requiredactivity).

(2) External judges independently evaluateddocument quality to produce an intercoderreliability rating of 0.77.

(3) Multiple-item scales in the postexperimentsurvey yielded perceived measures related tosatisfaction, communication, and relationships.

(4) External judges coded and analyzed thechat logs of all groups to capture additionalcommunication and relationship measures. [26]

Full chat transcripts for all groups were capturedelectronically from NetMeeting and coded byexternal judges for different observed messagetypes representing communication and relationshipconstructs. The chat logs were analyzed for the keyCW working sessions (sessions three and four) andwere broken up into distinct fragments consistingof a subject and a verb (comprising a thought unit).Because a given message could be deconstructedinto several disparate subject-verb fragments, thecategories were assigned in a mutually exclusivefashion. All coding values were nominally rated bythe judges—no attempt was made to assess thedegree to which a category applied. The satisfactionmeasure that was derived from the chat logs involvedexpressions of confusion and dissatisfaction (sessionthree � = 0:96, session four � = 0:79). Several othermeasures were also directly derived by externalanalysis of the groups’ chat logs, as seen in [33]:

(1) Coordination (session three � = 0:99, sessionfour � = 0:97)—indicates how much observedcommunication occurs within a group that issolely for administrative and synchronizationpurposes. [33]

(2) Agreement or consensus (agreement positive,session three � = 0:95; agreement negative,session three � = 0:96; agreement positive,session four � = 0:82; agreement negative,session four � = 0:98)—the degree of accord agroup achieved in decisions related to their CWdocument work, as modified from [21] and [34].

(3) Positive affiliation (session three � = 0:98, sessionfour � = 0:88)—how group members regard andtreat each other as manifested through theircommunication, as modified from [35].

(4) Socialization (session three � = 0:95, sessionfour � = 0:99)—a modification of affiliation thatinvolves overt communication of a social orfriendship nature).

Results Analysis of study one’s results suggeststhat CW technologies such as Collaboratus canimprove the results of SD CW teams in hybrid(mix of FtF and distributed) distributed educational

settings (see Table II). H1 was supported in two ofthe three productivity measures. H2 was supportedby externally measured quality but not in terms ofperceived quality. H3 was not statistically supportedby the satisfaction measures. H4 was partiallysupported in terms of observed socialization, positivesupport, and negative support. Analysis of chat logsby external judges showed Collaboratus groups actingmore social than Word groups in the final session.Collaboratus groups also had stronger manifestationsof both negative and positive support than Wordgroups did. Finally, H5 was supported in terms ofsimultaneous communication use but not in termsof coordination.

Background Study two focused on asynchronousdistributed (AD) CW groups writing academic paperswhile being guided by written scripts that haddifferent levels of PS, as described in [36] and [37].This study addressed the influence of different levelsof PS (the amount of task guidance and detail givenfor a collaborative task), delivered through processscripts to nonfacilitated students working in AD CWgroups. The underlying prediction of this study wasthat students and other novice writers would performbetter with high rather than low levels of PS in ADconditions.

Hypotheses Research shows that increasing PScan be beneficial to group performance [38]–[40].Increased PS can often increase coordination amonggroup members, which enhances communication andoverall results [39]. Conversely, groups that are leftto figure out work processes for themselves tend tohave suboptimal results [41]; this is especially trueof novice groups [41]–[44]. Groups left to their owndevices suffered process losses [41], which tend tooccur in unstructured groups because such groupsare more likely to come to premature decisions[42], be more poorly coordinated [43], and have lesscohesion and quality communication [40].

Novice groups should benefit more from increased PSthan experienced groups because novice groups haveless procedural knowledge about target tasks and areless cohesive due to their lack of experience workingtogether. Procedural knowledge is more difficult fornovices to assimilate than declarative knowledge(facts regarding a domain) and is usually gainedonly after declarative knowledge [45]. Noncohesivegroups can benefit from structured management,which is afforded by breaking large tasks into smallercomponents [40].

The benefits of increased PS should also apply toAD CW groups. CW is an overall group processthat, when effectively conducted, requires planning,brainstorming, converging on brainstorming output,researching, outlining, drafting, reviewing, revising,and other common group tasks [16], [46]. Casestudies on CW groups have shown that structuredprocesses improve outcomes in synchronous,


distributed sessions [47]. A case study of advancedgraduate students with extensive CW experience findsthat graduate students given more PS outperformthose with less structure [44]. Field observations ofCW groups using GSS also concluded that structuredCW processes are vital to successful CW outcomes[27]. Field research involving distributed CW groupsusing CW tools also showed that highly explicit,repeatable processes (processes a group can easilyperform in the future without outside intervention)are beneficial to novice CW groups [6]. In summary,novice CW groups working on low-complexity tasks inAD environments will likely benefit from high levelsof PS delivered through highly repeatable processscripts combined with group technology; similargroups with low levels of PS will produce the worstresults, whereas similar groups with moderate levelsof structure will produce the second-best results.

Given this basic background on how PS should affectAD CW groups, hypotheses for this study were basedon several constructs and theoretical propositionsthat are further developed in [36] and [37]. Thefollowing were the hypotheses on PS that were testedfor this experiment.

H1: Novice CW groups with high PS will havegreater production than novice CW groups

with medium PS; medium PS groups will havegreater production than low PS groups.

H2: Novice CW groups with high PS will havegreater quality than novice CW groups withmedium PS; medium PS groups will havegreater quality than low PS groups.

H3: Novice CW groups with high PS will havegreater satisfaction than novice CW groupswith medium PS; medium PS groups will havegreater satisfaction than low PS groups.

H4: Novice CW groups with high PS will havebetter relationships than novice CW groupswith medium PS; medium PS groups will havebetter relationships than low PS groups.

H5: Novice CW groups with high PS will havebetter communication than novice CWgroups with medium PS; medium PS groupswill have better communication than low PSgroups.

Participants Study two and study three used theaforementioned set of 550 participants in an AD fieldexperiment in a hybrid distributed classroom setting.

Design PS was delivered in written scripts in oneof three conditions: low, moderate, or high PS. Themanipulation of PS was accomplished by changing

TABLE IIStudy one results, Word versus Collaboratus


the explicitness of the CW tasks that were provided ina given script. The high PS treatment had the highestamount of detail, whereas the low PS structure scripthad the lowest amount of detail. Participants in allconditions used Collaboratus in conjunction withNicenet, an internet-based chat tool that was used forall group communication.

Procedures All participants were randomly assignedfirst to a condition, then randomly assigned to agroup on a rolling basis as they completed theirasynchronous training. One live training sessionwas given to all participants in their classroomsat the start of the project; after this session, allthe participants went through the same individualtraining scripts for the tools used in the experiment.Participants were required to complete specifictraining tasks, which were reviewed to ensure theycompleted the training properly. Once the scriptedtraining was completed, no questions were answeredin terms of the research purpose or tools so that allparticipants would receive the same information.

After initial training, participants were given sixweeks to complete the writing assignment, which wasconducted asynchronously according to each group’space and individually desired work location (e.g.,using computers in their apartments, at work, or atan on-campus lab).

Measures Similar to study one, the dependentvariables (DV) examined during this experimentwere designed to measure the constructs ofproductivity, quality, satisfaction, communication,and relationships. The productivity measuresincluded chat length (number of words in a chatsession), document length (number of words ina document) [20], and time spent on each CWactivity. The measure of externally judged qualitywas based on the proven practice of having externaljudges independently evaluate document quality[47]. Externally judged quality had five questions,each of which received an alpha score above 0.95;three judges responded to each question for eachgroup paper, generating inter-coder reliability rateabove 0.95. Perceived measures were self-reportedby members on a 1–7 scale with 1 being the lowestscore and 7 as the highest score. The measure ofperceived process satisfaction (� = 0:91) was based onthe same measure by Tan, Wei, and Lee [48], whichis a self-reported measure that indicates one’s overallprocess satisfaction.

The relationship measures included perceiveddominance (� = 0:81), the extent to which overt controlwas practiced by a particular member of a team [49];perceived positive evaluation (� = 0:74), the degreeto which a particular member of a team providedjudgment and critical opinions in discussions [49];

perceived agreement (� = 0:92), the degree to whichparticipants believe consensus and agreement wasreached during CW [20]; perceived positivity (� = 0:94),how positive and friendly a particular team membercame across in group interactions [50]; and perceivedteamwork (� = 0:75), the degree to which a participantbelieved his or her team worked together [51].

The communication measures included perceivedcommunication appropriateness (� = 0:85), theappropriateness of a group’s communication[52]; perceived communication involvement(� = 0:87), the degree to which group memberswere engaged in discussions [49]; perceived groupmutuality (� = 0:91), the connectedness, receptivity,openness, and feelings of understanding andsimilarity in group communication [49]; perceivedcommunication richness (� = 0:85), the uniquenessand substitutability of information in communication[53]; and perceived task-discussion effectiveness(� = 0:94), the degree to which a group was effectivein communicating about the tasks they needed todo [54]. Further detail on the setup, control, andmeasures for this experiment is contained in [36] and[37].

Analysis All of the results were tested on thegroup level and most of the measures involvedhighly interdependent group data (as determinedby intraclass correlations). As a result, rather thanusing a basic ANOVA, which would have inflatedthe F-statistics, virtually all the data were analyzedusing regressions that factor out the effects ofintracorrelations, as advocated by Kashy and Kenny[56]. Thus, all F-statistics reflect these conservativeadjustments, with the exceptions of document lengthand chat length, both of which were group-level datathat were not intracorrelated.

Results Significant results from the causal fieldexperiment are summarized in Table III. The resultsshow that in our AD educational setting, high PSstudent groups outperformed low PS groups inevery measure: productivity, quality, satisfaction,relationships, and communication. High PS groupssurpassed moderate-structure groups in productivity,satisfaction, and in the relationship measure ofappropriateness; however, significant results were notfound in terms of quality and communication. Thelow PS groups and moderate-structure groups wereunable to outperform high PS groups in any measurein the field experiment. Finally, the statisticaldifferences between low PS groups and moderate PSgroups were largely inconclusive. The low PS groupsspent more time with team formation, brainstorming,and drafting than moderate PS groups; however,no other statistically significant differences wereobserved. These findings and relationships in PS aresummarized in Fig. 4.


TABLE IIIStudy two results, varying PS


STUDY THREE: PROXIMITY FIELD STUDY

Background Study three compared groups thatperformed all their work in an AD work mode togroups that performed part of their work FtF and partof their work in an AD work mode, which we refer toas mixed-mode work [26], [55].

Hypotheses A large body of research showsdistributed groups having worse results than FtFgroups. Examples include distributed groups havingless opportunity for rich interactions [56]; less groupawareness [57]; fewer nonverbal channels [58];reduced expressiveness [16]; less attention [40]; alack of necessary cues and mechanisms to coordinateinteractions [43]; less trust and more difficulty withteam building [58]; less familiarity [40]; poorer norms,culture, and authority [40]; less satisfaction [40];less productivity [40]; a more abstract shared socialsetting [40]; less motivation to participate [57]; moreside conversations [58]; and more restraint andresponsibility from participants [58].

Similar findings are shown in comparisons ofdistributed CW groups to FtF groups. A fieldstudy shows CW is difficult to support in ADsettings, especially with complex documents [59]. Anexperiment comparing SD CW groups with FtF groupsfound that SD CW groups have more fragmented

writing styles and take more time than traditional FtFgroups [60].

On the basis of these findings, research claimsthat adding FtF interactions to asynchronous(mixed-mode) work would create better results thanthose produced by groups performing all their workasynchronously. CW field research suggested thatasynchronous CW groups that conducted their initialplanning sessions and convergence process sessionsas FtF sessions should have better consensus,quality, and overall performance than groups thatdo all of their work asynchronously [61]–[64]. Caseresearch in synchronous CW finds that outcomesare improved if the participants first meet in person[63]. These findings support Galegher and Kraut’sclaim that FtF work in CW planning and revisingactivities is critical to AD group success, becausethese activities require the most amount of interactivecommunication [16], [64], [65].

This background led us to empirically test whetherthe FtF work mode would be beneficial during highlyconvergent activities (activities requiring substantialgroup interaction for decisions), as depicted inFig. 5, or whether AD groups given sufficient timewith collaborative technology could produce similarresults. The hypotheses for this study were based onseveral constructs and theoretical propositions that

Fig. 4. Significant differences in comparing three levels of PS.


are further developed by Lowry [26], [55], [57]. Thehypotheses were as follows:

H1: Mixed-mode CW groups will have betterrelationships than AD CW groups.

H2: Mixed-mode CW groups will have bettercommunication than AD CW groups.

H3: Mixed-mode CW groups will have moreproduction than AD CW groups.

H4: Mixed-mode CW groups will have higherquality than AD CW groups.

H5: Mixed-mode CW groups will have highersatisfaction than AD CW groups.

Fig. 5. Mixed-mode groups’ CW process (modifiedfrom [6]).

Design Proximity choices were delivered via twoconditions: AD CW groups using specialized CW toolsover time and mixed-mode group using specializedCW tools over time. Scripts were used to guide groupsas to when they were required to work AD and whenthey were required to work FtF (AD CW groupsnever worked FtF). All conditions used Collaboratusin conjunction with Nicenet. The participants,procedures, analysis, and measures for this fieldexperiment were the same as those used in study twoand thus are not repeated here.

Results The statistical results of study three largelydisconfirmed all of our proximity hypotheses. TheAD CW groups had similar productivity, quality,satisfaction, communication and relationships asmixed-mode groups. In other words, mixed-modegroups did not outperform AD CW in any meaningfulway. Table IV summarizes the significant causalresults of study three, which highlighted that underthe given experimental conditions, FtF interactionsappear to provide no added benefit to AD CW ineducation.

DISCUSSION OF RESULTS

This paper presents three streams of empirical fieldresearch that involved the study and implementationof distributed CW in hybrid distributed educationalsettings, as summarized in Table V.

Study one, which compared SD CW groups usingCollaboratus to those using Word, led to the overallconclusion that distributed student CW teams canbenefit from specialized CW software that providesparallel work, group awareness, and coordination.Conversely, using technologies (i.e., word processors)that do not support these features can causesuboptimal results. Thus, the common assumptionin education that word processors are adequate fordistributed CW should be reexamined.

Study two, which compared AD CW groups usingdifferent levels of PS in AD CW educational settings,led to the conclusion that high levels of PS can bebeneficial to distributed student writing groups.Since all the groups in this field experiment usedCollaboratus, this finding also buttresses the claimthat novice AD CW student groups can achieveoptimal results by using leading CW technologies inconjunction with high levels of PS. This researchreaffirms the notion that focusing on technologyalone to improve distributed work is suboptimal [65].Student CW groups with lower levels of PS produceddisjointed and uncoordinated work, resulting inprocess losses. Thus, providing students withadvanced CW tools alone will not necessarily optimizeperformance in distributed CW settings—studentsalso need high levels of PS.


CW processes require facilitation support by someonewho understands the correct CW processes for agiven task. Yet we showed that increased PS does

not necessarily need to be delivered directly byinstructors or facilitators; increased PS can be

TABLE IVSignificant results for FtF control variable

TABLE VSummary of studies one, two, and three


delivered effectively by written process scripts if theyare constructed and tested carefully by instructors.

One of the important considerations for increasedPS in distributed settings is to give students explicitinstructions and dated deliverables, and to implementother classroom procedures that encourage full groupparticipation. At the same time, grading proceduresand incentives also should encourage individualcontributions [66]. Misalignments between writingincentives and goals would likely undermine highlevels of PS.

Study three, which compared AD CW student groupswith some groups working via mixed-work modes,while other groups working only asynchronously,found that AD CW student groups did not havesubstantial process or outcomes losses whencompared to mixed-mode groups. This unexpectedfinding supported the notion that AD work modescan be appropriate for distributed CW in educationwhen CW groups were provided with the right toolsand process support, as well as when studentshave sufficient time to adapt to new technology.Thus, periods of close proximity were not necessarilybeneficial to distributed educational teams workingon papers.

There may be several possible ways to explainthe unexpected findings of study three. First,although FtF interaction may provide media richnessand communication benefits, such interactionsmay introduce offsetting process losses, such asdomination. Domination is seen in case researchthat compared all FtF student writing groups to SDstudent writing groups [67]. The study found thatthe amount of discourse participation did not differbetween these groups; that FtF groups were morelikely to have a dominant, self-appointed leaderemerge; that distributed groups were more likely tobe democratic and to have equal participation; andthat FtF groups spent more time discussing rules andprocedures whereas distributed groups spent moretime focused on the writing task itself. Aside fromdomination, other potential offsetting process lossesincluded airtime fragmentation, attention blocking,attenuation blocking, cognitive inertia, concentrationblocking, evaluation apprehension [68], conformancepressure [69], excessive group maintenance, negativegroup conflict, premature decision making, statuseffects [70], and groupthink [71].

The findings of study three could also be explained byGalegher and Kraut’s study [16] that used structuralcontingency theory to predict that CMC-based CWgroups should have more difficulty than FtF CWgroups because of a lack of interactive communicationin CMC [72]. Yet, in partial contradiction to theirprediction, they found that although CMC groups hadmore difficulty and took more time than FtF groups,the quality of CW outcomes did not differ, suggesting

a possible adaptation by the CMC groups in theless media-rich conditions [16]. Another experimentcompared 33 FtF and distributed CW groups thatused a specialized CW tool combined with GSS,working over a four-week time period, and foundno substantial differences between the FtF anddistributed CW groups [73]. Thus, it is possible asimilar adaptation occurred over time with membersof the AD CW condition.

Another possibility is that the AD CW groups mayhave been just as effective as the mixed-modegroups because the AD groups had fewer schedulingdifficulties. Postexperiment surveys for study threefound that a large portion of the students who wereassigned to the mixed-mode treatment were unhappythat they were required to schedule FtF meetings ontheir own time; conversely, a large portion of the ADCW students appreciated being able to work accordingto their own time and pace without having to schedulemeetings with group members. Similar schedulingproblems with FtF work have been found by otherresearchers [74]. Therefore, scheduling problems andthe resulting group conflict may have undermined theresults of the groups in the mixed-mode treatment.

The virtual lack of differences between the twoconditions in study three is a finding that can onlybe gained from having conducted a distributed fieldexperiment in actual hybrid distributed universityclasses. If we had conducted the FtF meetings atpre-appointed laboratory locations and times, orif we had paid for participation, the results of themixed-mode groups might have been artificially morepositive. The realism of this field experiment enablesa more accurate reflection of how students writetogether in AD modes.

ADDITIONAL CONTRIBUTIONS OF THIS RESEARCH

These studies yield additional contributions to hybriddistributed education as well as contributions totraditional distributed education. First, the researchwas conducted in hybrid distributed educationalenvironments using realistic tasks conducted overtime, as opposed to one-time laboratory studies.Although the findings are supported by less controlthan is seen in traditional laboratory experiments,the results are more generalizable to educationalenvironments.

Second, although this research focused on studentsin distributed environments, the research findingslikely have implications for practitioner groups. Inparticular, we believe the results would be fairlygeneralizable to novice distributed groups or to groupswith no previous experience working together.

Third, many innovative and multidimensionalmeasures were used to assess complex groupoutcomes in distributed settings. This research builds


on the traditional constructs of satisfaction, quality,and productivity by adding constructs related tocommunication quality and relationship quality. Weconcur with Galegher and Kraut that distributed CWoutcomes should be measured in multiple ways, andthat these measures have important relationshipswith each other [16].

These relationships require further research, butit is likely that the quality of communication andthe quality of relationships that student groupsexperience are important intermediary outcomes ofCW that directly affect the final outcomes, such asdocument quality, productivity, and satisfaction. Forexample, poor communication in student CW groupsis likely to undermine convergence on brainstorming,and good relationships are likely to enhance thereview and revision processes. The strong potentialinfluence of communication and relationships onother outcomes is substantiated by collaborativeresearch that shows that the social context for groupinteraction may have a greater effect on processesand outcomes than any technical intervention [43].

In terms of educational practice, we feel it isimperative that students be assessed on all measuresthat are important to distributed CW—not just writingquality. The business maxim “you get what youmeasure,” is equally true in distributed CW studentwork. Students need to understand that writing ahigh-quality document should not come at the cost ofdestroying relationships and satisfaction. However, ifinstructors measure document quality alone, grouprelationships are much more likely to suffer. Studentsneed to learn the importance of ongoing relationshipsand communication in group work so that they canperform effectively in future group work.

LIMITATION OF THIS RESEARCH

The primary limitation of these studies is that the CWtasks involved small groups of three participants whohad no previous experience writing basic academicpapers together and who were assigned to write basicacademic papers. Thus, the results of these studiesdo not necessarily offer generalizations for morecomplex tasks, such as term papers and academicjournal articles, nor do they offer generalizations forlarge groups. These results also cannot necessarilybe generalized to include distributed CW tasks innonacademic settings or to experienced teams.

Distinct differences exist between the way CW isperformed in academia and the way it is performedin industry [19]. One key difference is thatnonproductive (time-intensive) approaches to CWin academia are generally acceptable because evennonproductive approaches often benefit learning andsocialization, whereas in industry, productivity (interms of time on task) is a much more significantdriver of collaboration. As such, industry participants

tend to play different CW roles, do not share thewriting task equally, and tend to choose coauthoringonly when absolutely necessary [19]. Likewise,participants in industry are much more likely to playdistinctly defined CW roles according to expertise andtime commitments as opposed to more democraticdivisions of work that are seen in academia.

Another example of the limited generalizability ofthese findings can be seen in study three. Thebenefits of interspersing FtF work in AD CW groupscould be highly dependent on the nature of thetask being conducted; thus, the hypotheses mayhave been supported by a more complex task. Acollaborative technology study found that FtF groupshad higher consensus with preference tasks thannon-FTF groups [75]. In contrast, several GSS studieshave show that higher levels of consensus can beachieved in distributed GSS groups (compared toFTF groups) that conduct intellective tasks, asopposed to preference or decision-making tasks [30],[76]. These results indicate that the nature of thetask combined with the work mode can result indifferent levels of consensus and overall results. CWcan involve preference tasks, intellective tasks, anddecision-making tasks, depending on the nature ofthe project. Furthermore, other contextual aspectsof the task performed can change these outcomes,such as levels of ambiguity and difficulty, requiredlevels of coordination and integration betweengroup members, assessment of results, performancepressure, and length of time. For example, differentresults could occur between a mixed-mode group ofmanagement experts working on the creation of astrategy document versus a mixed-mode group ofadministrators working on a policy and proceduresmanual.

Another limitation in the generalizability of thesestudies is that they all involve hybrid distributededucational environments. Although extendingtraditional classrooms with distributed CWexperiences yielded more control than would haveoccurred in pure AD settings (because all orientationoccurred FtF, and the instructor and students hadstronger relationships than relationships typicallyobserved in virtual settings), more research needs tobe conducted before fully generalizing these findingsto traditional distributed education settings.

It is also important to recognize that all of thesestudies involved CW conducted over an extendedperiod of time; thus, the results have less than optimalinternal validity and experimental control thanwould be found in traditional one-time laboratoryexperiments. However, by conducting CW over time,these studies benefit from increased realism andexternal validity.

In addition, a specific limitation of study one wasthat the research was limited to comparisons between


Word and Collaboratus. Hence, these tools may haveintroduced technology-specific artifacts that limitthe generalizability of these results to other CWtools. For example, Word is a professional productthat has undergone thousands of hours of usabilitytesting and reengineering, whereas Collaboratus isa noncommercial research product that has hadextremely limited usability testing, resulting in fewerusability features than Word. Prior to the experiments,most participants had hundreds of hours ofexperience using Word, yet they received their onlyexposure to Collaboratus during these experiments.These exposure differences likely diminished thestatistical significance where Collaboratus was shownto be superior; with more exposure to Collaboratusover time, these positive differences would likely bestronger. For example, if students had more comfortand experience with Collaboratus, the results mayhave been even more positive, especially in termsof satisfaction due to adoption/diffusion. It is alsopossible that Collaboratus groups received artificiallypositive results from the novelty of using the softwarefor the first time. However, we believe this was not thecase because there were no statistically significantdifferences in satisfaction.

Moreover, a simplifying assumption of study one,which follows the norms of other collaborative toolresearch, was that the experiment compared bundlesof features against each other. The group awareness,coordination, and CW features of Collaboratus werecompared as a whole to all the group features in Word

for the same CW activities and the same task. Thismade it impossible to infer from the empirical datawhich feature was responsible for which outcome(e.g., that the group outliner in Collaboratus wasresponsible for x% of the outcome differences,whereas the group annotation feature was responsiblefor y% of the outcome differences).

Making such a determination would likely require ahigh number of participants using many differentversions of Collaboratus that have every possiblepermutation of group awareness and coordinationfeatures turned on and off (e.g., a version without agroup outliner, a version without group annotations,and so forth). A further complication of suchan approach is that the group awareness andcoordination features of Collaboratus were designedto be used in concert with each other, so a versionof Collaboratus that did not have the group outlinerwould undermine virtually every other groupawareness and coordination feature.

A similar limitation was seen in study two, in that theideal high PS script in this experiment was a bundle ofpredetermined activities and tasks representing basicCW processes, as based on CW literature, such as[7]. Hence, it is possible that only a few of the chosenactivities and tasks were responsible for the positiveoutcomes, whereas some of the chosen activities andtasks actually may have been counterproductive.The current data does not allow for unbundling andanalyzing this possibility.

Fig. 6. CW research framework [7].


Another caveat of study two is that although novicegroups performed the best with high levels of PS, thisshould not be interpreted to indicate that extremelevels of structure are optimal. Extreme levels ofstructure result in increased levels of constraint;thus, educators must balance the need for structurewith the need for flexibility and creativity.

Finally, this research also assumed that the low PSscripts represented natural interactions, but thisassumption may not be entirely accurate because thelow PS scripts in this study gave a minimal amountof guidance, and the research was conducted in anacademic setting.

FUTURE RESEARCH

Building on the limitations and opportunities of thisresearch, this section highlights some promisingfuture research opportunities involving distributedCW in education. Overall, researchers and instructorsare just beginning to explore the possibilities ofperforming distributed CW in hybrid and traditionaldistributed educational settings. Other input variablescan be manipulated and tested by considering themany possibilities for group, task, tool, and contextdecisions. Fig. 6 depicts a research framework thathas been extended to guide such future researchin CW. Rather than provide an exhaustive list ofresearch possibilities, we will suggest a couple ofresearch lines.

First, a clear opportunity for research is to applythese findings to purely distributed settings wherestudents never receive FtF instruction. The inclusionof high-richness media technologies in distributedsettings (i.e., virtual meeting rooms or high-qualityteleconferencing) is another area of opportunity.Moreover, although this research focused on CWperformed over time, a need still exists for morein-depth longitudinal studies.

Another area of opportunity for research involvesthe creation of auto-facilitating CW teams that workin hybrid and traditional distributed educationalsettings. One goal in creating such self-sustainingteams is to wean distributed CW groups from theneed for intervention by a professional instructor,thus freeing instructors from the substantial amountof time required to create custom process scripts forspecific CW tasks. Although complete independencemay not be possible for inexperienced student groups,we believe that groups can become more self-reliantover time by using generic process scripts, wizards,and process agents.

In addition, future research should consider severalimportant technologies for inclusion in CW tools.

These considerations include the integration ofmultimedia technologies such as multicasts, videoconferencing, RealAudio, and IP telephony. Anotherarea of exploration includes the use of advancedinformation retrieval, decision agents, visualization,and knowledge management techniques.

Finally, although these studies have focused onstudent participants in distributed educationalsettings, the results of these studies likely have wideimplications for distributed work teams in businessenvironments. Clearly, many business teams work indistributed work modes and prepare collaborativelywritten documents. Future research should ascertainthe degree to which these results can be generalizedto involve noneducational settings by extending suchresearch into business environments.

CONCLUSION

This paper summarizes three studies on hybriddistributed CW in educational settings and providescausal findings and insights on how to implement CWin hybrid distributed educational settings. Becausedistributed CW is increasingly important in industry,students need more direct training and experiencein distributed CW in traditional and nontraditionalclassrooms. Moreover, educators need moretraining and tools that they can use to implementdistributed CW in education. Merely assigning CWprojects to students without further support isinadequate—students can benefit substantially fromCW tools and high levels of PS to help them throughgroup formation, group dynamics, CW roles, andthe major CW activities; otherwise, student groupsmay end up having experiences that will negativelyaffect their CW efforts. By providing students withspecialized CW tools and process scripts, educatorscan help students in traditional distributed andhybrid distributed settings obtain optimal CW resultsin the classroom and in the workplace.

ACKNOWLEDGMENT

The authors appreciate contributions made by MarkAdkins, John Kruse, and Jim Lee, all from the Centerof the Management of Information (CMI) at theUniversity of Arizona. They also greatly appreciatethe development work conducted by Conan Albrecht(Brigham Young University), Abhiraj Jadhav, AnkurJain, and Hemanth Manda. They also acknowledgethe support and funding they received from DefenseEnvironmental Security Corporate InformationManagement (DESCIM) and the Air Force OperationalTest and Evaluation Center (AFOTEC). Finally, theyappreciate the assistance received from the Kevin andDebra Rollins Center for e-Business at the MarriottSchool of Management, Brigham Young University;as well as editing assistance from Don Norton, JoelKarpowitz, and Laura Rowlins.


REFERENCES

[1] D. H. Barbour, “Collaborative writing in the business writing classroom: An ethical dilemma for the teacher,”Bull. Assoc. Bus. Commun., vol. 53, no. 3, pp. 33–35, 1990.

[2] D. W. Johnson and R. T. Johnson, Learning Together and Alone: Cooperative, Competitive, and IndividualisticLearning, 5th ed. Boston, MA: Allyn and Bacon, 1999.

[3] B. Couture and J. Rymer, “Interactive writing on the job: Definitions and implications of collaboration,” inWriting in the Business Professions, M. Kogen, Ed. Urbana, IL: NCTE and ABC, 1989, pp. 73–93.

[4] E. Beck, “A survey of experiences of collaborative writing,” in Computer Supported Collaborative Writing, M.Sharples, Ed. Berlin, Germany: Springer-Verlag, 1993, pp. 87–112.

[5] R. Baecker, G. Glass, A. Mitchell, and I. Posner, “SASSE: The collaborative editor,” in Companion Proc. ACMConf. Hum. Factors Comput. Syst., 1994, pp. 449–460.

[6] P. B. Lowry, C. C. Albrecht, J. F. Nunamaker Jr., and J. D. Lee, “Evolutionary development and research oninternet-based collaborative writing tools and processes to enhance eWriting in an eGovernment setting,”Decision Support Syst., vol. 34, no. 3, pp. 229–252, 2002.

[7] P. B. Lowry, A. Curtis, and M. R. Lowry, “A taxonomy of collaborative writing to improve empirical research,writing practice, and tool development,” J. Bus. Commun., vol. 41, no. 1, pp. 66–99, 2004.

[8] L. Ede and A. Lunsford, Singular Texts/Plural Authors: Perspectives on Collaborative Writing. Carbondale,IL: Southern Illinois Univ. Press, 1990.

[9] J. Forman, “Novices work on group reports: Problems in group writing and computer-supported group writing,”J. Bus. Tech. Commun., vol. 5, no. 1, pp. 48–75, 1991.

[10] R. P. Rice and J. T. Huguley Jr., “Describing collaborative forms: A profile of the team-writing process,” IEEETrans. Profess. Commun., vol. 37, no. 3, pp. 163–170, 1994.

[11] L. Loehr, “Composing in groups: The concept of authority in cross functional project team work,” IEEE Trans.Profess. Commun., vol. 38, no. 2, pp. 83–94, 1995.

[12] M. L. Kreth, “A survey of the co-op writing experiences of recent engineering graduates,” IEEE Trans. Profess.Commun., vol. 43, no. 2, pp. 137–151, 2000.

[13] A. H. Duin, “Computer-supported collaborative writing: The workplace and the writing classroom,” J. Bus.Tech. Commun., vol. 5, no. 2, pp. 123–150, 1991.

[14] C. M. McIsaac and M. A. Aschauer, “Proposal writing at Atherton Jordan, Inc.,” Manage. Commun. Quart., vol.3, no. 4, pp. 527–560, 1990.

[15] G. A. Cross, “Collective form: An exploration of large-group writing,” J. Bus. Commun., vol. 37, no. 1, pp.77–100, 1998.

[16] J. Galegher and R. E. Kraut, “Computer-mediated communication for intellectual teamwork: An experimentin group writing,” Inform. Syst. Res., vol. 5, no. 2, pp. 110–138, 1994.

[17] R. Rada and W. Wang, “Computer-supported collaborative writing phases,” J. Educ. Technol. Syst., vol. 26, no.2, pp. 137–149, 1998.

[18] J. S. Olson, G. M. Olson, M. Storrosten, and M. Carter, “Groupwork close-up—A comparison of the group designprocess with and without a simple-group editor,” in ACM Trans. Inform. Syst., vol. 11, 1993, pp. 321–348.

[19] M. Lay and W. Karis, Collaborative Writing in Industry: Investigations in Theory and Practice. Amityville, NY:Baywood, 1991.

[20] P. B. Lowry and J. F. Nunamaker Jr., “Using Internet-based, distributed collaborative writing tools to improvecoordination and group awareness in writing teams,” IEEE Trans. Profess. Commun., vol. 46, no. 4, pp.277–297, 2003.

[21] R. M. Baecker, D. Nastos, I. R. Posner, and K. L. Mawby, “The user-centered iterative design of collaborativewriting software,” presented at the ACM Conf. Human Factors Comput. Syst., Amsterdam, The Netherlands,1993.

[22] K. O. Locker, “What makes a collaborative writing team successful? A case study of lawyers and social workersin a state agency,” in New Visions of Collaborative Writing, J. Forman, Ed. Portsmouth, NH: Boynton/Cook,1992, pp. 37–62.

[23] R. E. Kraut, J. Galegher, and C. Egido, “Relationships and tasks in scientific research collaboration,”Hum.–Comput. Interaction, vol. 3, no. 1, pp. 31–58, 1988.

[24] J. Trimbur, “Collaborative learning and teaching writing,” in Perspectives on Research and Scholarship inComposition, B. W. McClelland and T. R. Donovan, Eds. New York: Modern Language, 1985, pp. 87–109.

[25] K. A. Bruffee, “Writing and reading as collaborative or social acts,” in A Sourcebook for Basic Writing Teachers,T. Enos, Ed. New York: Random House, 1987, pp. 565–574.

[26] P. B. Lowry, “Improving distributed collaborative writing on the internet using enhanced processes and ajava-based collaborative writing tool,” Ph.D. dissertation, Dept. Manage. Inform. Syst, Univ. Arizona, Tucson,AZ, 2002.

[27] J. F. Nunamaker Jr., R. O. Briggs, D. D. Mittleman, D. R. Vogel, and P. A. Balthazard, “Lessons from a dozenyears of group support systems research: A discussion of lab and field findings,” J. Manage. Inform. Syst., vol.13, no. 3, pp. 163–207, 1997.

[28] A. C. Easton, N. S. Eickelmann, and M. E. Flatley, “Effects of an electronic meeting system group writing toolon the quality of written documents,” J. Bus. Commun., vol. 31, no. 1, pp. 27–40, 1994.

[29] R. O. Briggs, M. Adkins, D. Mittleman, and J. Kruse, “A technology transition model derived from fieldinvestigation of GSS use aboard the U.S.S. CORONADO,” J. Manage. Inform. Syst., vol. 15, no. 3, pp. 151–195,1999.


[30] A. B. Hollingshead, J. E. McGrath, and K. M. O’Conner, “Group task performance and communicationtechnology: A longitudinal study of computer-mediated versus face-to-face work groups,” Small Group Res., vol.24, no. 3, pp. 307–333, 1993.

[31] A. Kirby and T. Rodden, “Contact: Support for distributed cooperative writing,” presented at the 4th Eur. Conf.Comput.-Supported Coop. Work, Stockholm, Sweden, 1995.

[32] P. Dourish and V. Bellotti, “Awareness and coordination in shared workspaces,” presented at the Int. Conf.Comput.-Supported Coop. Work, Toronto, ON, Canada, 1992.

[33] P. B. Lowry and J. F. Nunamaker Jr., “Synchronous, distributed collaborative writing for policy agendasetting using Collaboratus, an Internet-based collaboration tool,” presented at the 35th Annu. Hawaii Int.Conf. Syst. Sci., Big Island, HI, 2002.

[34] A. Easton, “An Experimental Investigation of Automated Versus Manual Support for Stakeholder Identificationand Assumption Surfacing in Small Groups,” Ph.D. dissertation, Univ. Arizona, Tucson, AZ, 1988.

[35] J. P. Dillard, D. H. Solomon, and M. T. Palmer, “Structuring the concept of relational communication,”Commun. Monographs, vol. 66, no. 1, pp. 49–65, 1999.

[36] P. B. Lowry, “Research on process structure for distributed, asynchronous collaborative writing groups,”presented at the Amer. Conf. Inform. Syst., Dallas, TX, 2002.

[37] P. B. Lowry, J. F. Nunamaker Jr., A. Curtis, and M. R. Lowry, “The impact of process structure on novice,internet-based, asynchronous-distributed collaborative writing teams,” IEEE Trans. Profess. Commun.,submitted for publication.

[38] A. Van de Ven and A. Delbecq, “The effectiveness of nominal, delphi and interacting group decision-makingprocesses,” Acad. Manage. J., vol. 17, no. 4, pp. 605–621, 1974.

[39] C. A. Ellis, S. J. Gibbs, and G. L. Rein, “Groupware: Some issues and experiences,” in Commun. ACM, vol. 34,1991, pp. 39–58.

[40] S. Kiesler and J. N. Cummings, “What do we know about proximity and distance in work groups?,” inDistributed Work, P. Hinds and S. Kiesler, Eds. Cambridge, MA: MIT Press, 2001.

[41] J. Fjermestad and S. R. Hiltz, “An assessment of group support systems experiment research: Methodologyand results,” J. Manage. Inform. Syst., vol. 15, no. 3, pp. 7–150, 1999.

[42] N. Maier and L. Hoffman, “Quality of first and second solutions in group-problem solving,” J. Appl. Psychol.,vol. 44, no. 4, pp. 310–323, 1960.

[43] S. R. Hiltz, D. Dufner, M. Holmes, and S. Poole, “Distributed group support systems: Social dynamics anddesign dilemmas,” J. Org. Comput., vol. 2, no. 1, pp. 135–159, 1991.

[44] C. M. Barnum, “Collaborative writing in graduate technical communication—Is there a difference?,” J. Tech.Writing Commun., vol. 24, no. 4, pp. 405–419, 1994.

[45] I. Vessey and S. Conger, “Learning to specify information requirements,” J. Manage. Inform. Syst., vol. 10, no.2, pp. 177–201, 1993.

[46] M. Horton, P. Rogers, L. Austin, and M. McCormick, “Exploring the impact of face-to-face collaborativetechnology on group writing,” J. Manage. Inform. Syst., vol. 8, no. 3, pp. 27–48, 1991.

[47] J. S. Olson, G. M. Olson, M. Storrosten, and M. Carter, “How a group-editor changes the character of a designmeeting as well as its outcome,” presented at the Conf. Comput.-Supported Coop. Work, 1992.

[48] B. C. Y. Tan, K. Wei, and J. E. Lee-Partridge, “Effects of facilitation and leadership on meeting outcomes in agroup support system environment,” Eur. J. Inform. Syst., vol. 8, no. 4, pp. 232–246, 1999.

[49] J. K. Burgoon, J. Bonito, A. Ramirez, K. Kam, N. E. Dunbar, and J. Fischer, “Interactivity and communicationprocesses in interpersonal and mediated interaction,” J. Commun., vol. 52, no. 3, pp. 657–677, 2002.

[50] J. K. Burgoon and J. L. Hale, “Validation and measurement of the fundamental themes of relationalcommunication,” Commun. Monographs, vol. 54, no. 1, pp. 19–41, 1987.

[51] S. R. Glaser, S. Zamanou, and K. Hacker, “Measuring and interpreting organizational culture,” ManagementCommun. Quart., vol. 1, no. 2, pp. 173–198, 1987.

[52] J. K. Burgoon and J. B. Walther, “Nonverbal expectancies and the evaluative consequences of violations,” Hum.Commun. Res., vol. 17, no. 2, pp. 232–265, 1990.

[53] J. Burgoon, M. Burgoon, K. Broneck, E. Alvaro, and J. F. Nunamaker Jr., “Effects of synchronicity and proximityon group communication,” presented at the Annu. Conv. Nat. Commun. Assoc., New Orleans, LA, 2002.

[54] D. S. Gouran, C. Brown, and D. R. Henry, “Behavioral correlates of perceptions of quality in decision-makingand discussions,” Commun. Monographs, vol. 45, no. 1, pp. 51–63, 1978.

[55] P. B. Lowry, “Research on proximity choices for distributed, asynchronous collaborative writing groups,”presented at the Amer. Conf. Inform. Syst., Dallas, TX, 2002.

[56] J. D. Herbsleb, A. Mockus, T. A. Finholt, and R. E. Grinter, “Distance, dependencies, and delay in globalcollaboration,” presented at the Conf. Comput.-Supported Coop. Work, Philadelphia, PA, 2000.

[57] K. Aytes, J. Johnson, and J. Frost, “Supporting distributed GDSS,” in SIGOIS Bull.: Special Issue: PositionPapers . CSCW’94 Workshops, vol. 15, 1994, pp. 18–20.

[58] A. L. Barile, “Computer-mediated communication in collaborative writing,” in Psychology. Norman, OK:Univ. Oklahoma, 1998.

[59] S. G. Tammaro, J. N. Moseir, N. C. Goodwin, and G. Spitz, “Collaborative writing is hard to support: A field studyof collaborative writing,” Comput.-Supported Coop. Work: J. Collaborative Comput., vol. 6, no. 1, pp. 19–51, 1997.

[60] T. Cerratto, “Supporting collaborative writing and its cognitive tools,” presented at the 3rd Int. Cogn. Technol.Conf., San Francisco, CA, 1999.

[61] M. Adkins, J. Q. Reinig, J. Kruse, and D. Mittleman, “GSS collaboration in document development: UsingGroupWriter to improve the process,” presented at the 32nd Annu. Hawaii Int. Conf. Syst. Sci., Maui, HI, 1999.


[62] N. Romano, J. F. Nunamaker Jr., R. Briggs, and D. Mittleman, “Distributed GSS facilitation and participation:Field action research,” presented at the 32nd Annu. Hawaii Int. Conf. Syst. Sci., Maui, HI, 1999.

[63] M. Sasse and M. Handley, Collaborative Writing with Synchronous and Asynchronous SupportEnvironments. London, U.K.: Academic, 1996.

[64] R. Kraut, J. Galegher, R. Fish, and B. Chalfonte, “Task requirements and media choice in collaborative writing,”Hum.–Comput. Interaction, vol. 7, no. 4, pp. 375–407, 1992.

[65] R. Kraut. (1994) Research recommendations to facilitate distributed work. [Online]. Available:http://bob.nap.edu/html/distr_work

[66] J. D. Beard, J. Rymer, and D. L. Williams, “An assessment system for collaborative-writing groups: Theory andempirical evaluation,” J. Bus. Tech. Commun., vol. 3, no. 2, pp. 29–51, 1989.

[67] M. Mabrito, “Real-time computer network collaboration: Case studies of business writing students,” J. Bus.Tech. Commun., vol. 6, no. 3, pp. 316–336, 1992.

[68] H. Lamm and G. Trommsdorff, “Group versus individual performance on tasks requiring ideational proficiency(brainstorming): A review,” Eur. J. Soc. Psychol., vol. 3, no. 4, pp. 361–387, 1973.

[69] J. R. Hackman and R. E. Kaplan, “Interventions into group process: An approach to improving the effectivenessof groups,” Decision Sci., vol. 5, pp. 459–480, 1974.

[70] G. Burton, “The ‘clustering effect’: An idea-generation phenomenon during nominal grouping,” Small GroupBehav., vol. 18, no. 2, pp. 224–238, 1987.

[71] I. L. Janis, Groupthink: Psychological Studies of Policy Decisions and Fiascoes, 2nd ed. Boston, MA: HoughtonMifflin, 1982.

[72] P. R. Lawrence and J. W. Lorsch, Organization and Environment. Homewood, IL: Irwin, 1967.[73] K. Burke and L. Chidambaram, “Do mediated contexts differ in information richness? A comparison of

collocated and dispersed meetings,” presented at the 29th Hawaii Int. Conf. Syst. Sci., Maui, HI, 1996.[74] L. Kimball. (1999) Boundaryless facilitation: leveraging the strengths of face-to-face and groupware tools to

maximize group process. [Online]. Available: http://www.tmn.com/~lisa/bnd2.htm[75] K. S. Raman, B. C. Y. Tan, and K. K. Wei, “An empirical study of task type and communication medium in

GDSS,” presented at the 26th Hawaii Int. Conf. Syst. Sci., Maui, HI, 1993.[76] B. C. Y. Tan, K. S. Raman, and K. K. Wei, “An empirical study of task dimension of group support systems,”

IEEE Trans. Syst., Man, Cybern., vol. 24, no. 7, pp. 1054–1060, 1994.

Paul Benjamin Lowry (M’99) is an Assistant Professor of IS at the Marriott School of Management, Brigham Young University, and

a Faculty Researcher at the Kevin and Deborah Rollins Center for e-Business. His interests include internet-based collaboration,

virtual teams, distributed facilitation, collaborative software, e-Business, group-based HCI, heuristics, and scientometrics. Dr.

Lowry received his Ph.D. in MIS from the University of Arizona, and a B.S. in Information Management and an MBA, both from

Brigham Young University.

Jay F. Nunamaker, Jr. is Regents Professor and Director of CMI at the University of Arizona. He has published scores of articles

and has received many awards, including the DPMA EDSIG Distinguished IS Educator Award, the Groupware achievement award,

and the Andersen Consulting Professor of the Year award. The GroupSystems software resulting from his research has been

implemented in hundreds of organizations. Jay received his Ph.D. in systems engineering and operations research from Case

Institute of Technology, a M.S. and B.S. from the University of Pittsburgh, and a B.S. from Carnegie Mellon University.

Queen Esther Booker is a Research Scientist at the Center for the Management of Information at the University of Arizona. She

has worked with the Ford Foundation, where she was a Program Officer working with educational institutions and community

development. Her primary research interests include collaboration and community development. Dr. Booker received her Ph.D.

from the University of Mississippi and her M.B.A. from Harvard University.

Aaron Curtis s a Ph.D. student in MIS at Indiana University. He is a graduate of the Information Systems Ph.D. preparation track

of the Master’s of Information Systems Management (MISM) program at the Marriott School, Brigham Young University. Aaron has

been involved in several published co-authored research projects. His research interests include collaboration, ontologies, user

trust, appropriation of information systems, and website usability

Michelle Rene Lowry is a graduate student in the Master’s of Accounting (MACC) program at the Marriott School, Brigham Young

University. Lowry has been involved in several published co-authored research projects. Her interests include collaboration,

accounting information systems, audit automation, and behavioral issues in auditing. Lowry was selected for the MACC Ph.D.

preparation track at the Marriott School and will be enrolling in a Ph.D. program in the near future.

creating hybrid distributed learning environments by implementing distributed collaborative writing...

Documents