Task-Tailorable Representations of Communication in ... - CiteSeerX

Envisioning Communication: Task-Tailorable Representations of Communication in Asynchronous Work Chrfifie M. Neutih James H. Moti Susan Harkness Regfi

Ravhder Chandhok Geoffrey C. Wenger

Witi Technology, he., Waynesburg, PA 15370 USA +1 724 S52-2599 {chandhok, wenger}@witi.com

Carnegie MeHon Universi~

Pitiburg~ PA 15213 USA +1 41226S-S702 Ok CQ shrl}@cmwedu ABSTRACT ~ls paper reports on our effofi to improve intefiws h asynchronous communication in which a group is communicating to solve a problem. We report restits ti an observational study and an experiment and use them as a basis for drawing design requiremen~ task-tiorable representations, emergent representations, emergent sharing, pubUc/private elements in a Iayouc increment form-o% and asynchronous awareness. We descrii an approach and proto@e that embodies some of the key requirements. Keywords inteb, Exlemd representations, Visatiog increment formtitiou awareness, asynchronous communication, electronic mti, collaborative work INTRODUCTION Few wodd deny that external representations play an important role in many tasks. me relative ~cti~ cf tntitiplying ~~ by LN vs. 47 by 54 is a pamdigm case; us”mg pencfl and paper while perfotig the multiplication steps vs. doing it “in your h@ is another. ~eories have been proposed and empirical res-h is accumulating in support of the view that extemd representations are not ‘tierely” inputs and stirmdi, but that tie form of a representation tiuences what information is perceive~ what processes are activat@ and what stictures are discovered [6,7, 27,31]. Our previous research examined the role of efiernd representations in the writing process [23] and in communicating *out *cts (dmfts of papers) [20, 21, 22]. k that researc~ we hypothestied that =erent externrd representations impose difi%renttiormation production and

amess costs, and demonstmted that such ~-= significantly tiect the amount and nature of communication and the perceptions participants form of each other [19, 30]. h the research reported here, we focus on extemd representations for asynchronous communication in which a group is communicating to solve a problem @ut not n-ss~y to create an artifact). mere are, of course, a great many ~erenm between* t~face and asynchronous communication [cf 1, 17]. When peopIe are dispersed in space and time, numerous aspects of communication m Wincluding the sequencing of messages, the flow of communication, and the time required for a communication cycle (composing the message, editing, transmission, receptio~ fdackacknowledgntent of receipt–and reply). We have chosen to concentrate on how to represent the state of the task. ~s is bemuse one of the most basic properties of asynchronous communication is that the participants forget what is going on. As a resul~ they must depend much more on extemd representations than they wotid in a synchronous interaction. ~us, as we shall argue, the design and maintenance of a Wk-specific representation is crucial. OUR APPROACH:

me methodology we have employed in our approach is iterative design based on benchmark tasks: ●

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TASK-DRIVEN DESIGN

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develop benchmarks tasks the benchmark tasks, observe subjects performing through laboratory studies and field tests, paying pardcular attention to difficulties encountere~ develop prototypes Mcdties;

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these

measure and compare the performance of subjects completing the tasks with and without the aid of the prototype. revise the tasks and prototype based on the results of the comparison and repeat

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Communication and problem-solving activities invoIved in tie task include reading and and-g spoofd messages, locating other SAS, developing a problem-solving strategy, requesting other people to do something for you (requesting other SAS to send lo=ti ~its), processing people’s repfies @y comparing login fists to suspect fists and updating dose fists), responding to others’ requests to do things h hem (and@g logs in response to requests from other SAS for login fists), and deciding what information to share with others (sending the resdts tim log analysis to other SASwho are attempting to iden~ a spoofer). The task has properties designed to ptilel ~mchronous communication tasks: ●

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rd-world

It simdates a situation in which a person is receiving mdtiple messages re==ding ~erent tasks (finding the identity of any given spoofer represents a task seved spoofers are active at any given time). To be most effecdv%participants must assess the state of the various tasks and decide which task given the state of*, it wotid be most strategic to work on new Some messages can be dedt witi relatively quic~y (e.g., finding where tie message was sent from and contacting the relevant administrator can be done in less than a minute provided the administrator’s identity is known>

1 me Spoofer Identification Task can dso easfly be played with one acti subject and three subjects simtiated by an exTetienter. ~Is structure Mows the experimenter to simdate conditions such as an uncoopemtive co~abomtor, a system administmtor with high ned tbr privacy, etc. As part of the Virtual Work Room projec~ we rdso developed a computer simtiation program fi network activity of n users and m spoofers to tic* genemtion of rerdistic logs for The Spoofer IdentifiAon Task this rdlows us to maniptiate the complexity of the task The Task and directions for using it are at http://mfihss.cmwedtivwr/wreb/indexhtml.

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other messages, however, require work before a response is possible (e.g., answering a request from another SA tbr information about who was logged in at a partictiar time). Thus, some messages cannot be dealt with immediately; the receiver must M do the work and get back to the sender. Participmts forget to whom they still need to send answers and who has not gotten back to them.

k our work we have attempted to design benchmark tasks that are simple enough to Wow repeatable, contro~ed laborato~ studies, yet complex enough to capture aspects of rerd-world tasks that impose “loaW’ on the system, loads that lead to problems sticing. Our work with a task ded The Spoofer Identication Task wi~ serve as an example of our approach. k this task four subjectsl act as System Atimistrators (SAs), mch of whom administers a machine. fich of the SAS r=ives electronic mti messages that have obviously been forged or “spoofed by users iden~g themselves with We user names or tiases (e.g., “The Phantom”). To iden~ the spoofers, the SAS have to use the message hder information to find out xvherethe message originate~ an~ for messages not ori=tiating on their own machine, fid the SA who admiiters the machine and ask Her to identify what users were logged in at the time a spoofti message was senL By process of e~iinatio% SAS eventu~y iden@ a spoofer as the ody user logged in at rdl times when spoofed messages were sent from a partictiar Nlas.

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. Some messages contain requests to do something h

someone else whereas others are enabhg messages that allow the participant to get more work done on hisker own tasks. Participants must decide on a strategy h balancing the work that will result in the most efficient overall solution. . The situation changes over time (e.g., new tasks m

added). The number of collaborators grows as the situation becomes more complex; participants must tmck down relevant collaborators and decide what information to share with them (e.g., should they sh~e suspect lists with SAS who have just entered the situation). ●

Participants develop a stable solution metiod md problem-solving rou~ines, routines help them petionn more rehably and fluently, only over time. As a result their representation of the problem evolves and with it, their idea of how best to visualbe the situation becomes more refid

OBSERVATIONAL STUDIES

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We conducted a series of observational studies of subjects engaged in the Spoofer Identication Task over seveti variants of the task. Participants were students, & and fictity at Carnegie Mellon University and were paid fi All were e~erienced email users, their participation. though not dl were famifiar with tie email system used in the study (those unfmtiar with it were given hard copy documentation customtid to explain all commands they would need). To avoid confounding with the load in their own inboxes, participants logged into special “system administration” email accounts when they worked on the task. We instructed them to try to login approximately once every hvo hours from 9-5 during the course of the study and work for about a hti-hour during each session. Subjects cotid Iogin more frequently and work longer if they desired and some did Due to other time commitments (e.g., classes, other meetings), some subjects were delayed in their Iogins. For most of the task variants, the study lasted approtiately two days before participants proposed a correct identication for the spoofe~s). We recorded all participants’ email communications, took notes and interviewed participants about their experiences. h genem participants reported tiding the task challenging, engaging, and plausible. The observations reported here fmus on those aspects of participants’ performance that were most relevant to drawing our design implications.

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of Message Processing not yet received the requested informatio~ “Answers Owed by Me” is the number of messages tie participant had remived that he or she had not yet answered by providing the requested information.

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Figure 1 depicts the patterns of messages for two of tiur pticipmts over a twrdy periodz for one of our observationti studies. Unprocessed SpooF are spoofs tiat a pticipant raived but for which he or she had not yet sent a emti message to the relevmt system administrator requesting login ~ormatior, “Responses Owed to Me” is tie number of messages the participant had sent to a relevmt system admiitor for which the participant had

k gened, participants developed a stable solution method and problem-solving routines by the end of the first day these routines helped them perform more refiably and fluently, though not rdways more effectively. As can be seen in Figure 1, subjects varied in the problem-solving routines that they adopted. Some subjects (e.g., System Administrator #1) spent most of their time answering requests from other system administrators; others made it a practice to always process a spoof as soon as they ~ived one (e.g., System Administrator W). k terms of

2 me x-~ represents hours in which subjects ac~y worked in the 2-day perio& hours tim 5pm to 9am in wylch no one worked have been etided 267

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minimiig the time it takes to solve the problem, the strategy of getting requests “off one’s des~ is a better one, since another system administrator may have time to provide the answer, but cannot help if he or she doesn’t know tie spoof has occurre& Previous restits from studies of c~located vs. distributed work wotid suggest that if these system administrators had been c&locate& channek of informal communication may have ficfitated the adoption of the more efficient strateg by d [& lm. As it was, some subjects remained unaware of the more efficient strategy throughout the course of the task

most subjects used paper to keep track of their progress. Figure 2 depicts a task-spmfic representation ~ical of those invented by subjects. Some subjects used representations like the one illustrated to help them remember which machines had been spoofed at what times (the “ToY “From; and “Time” columns), what work was outstanding (indicated in Figure 2 by a circle) and what work was completed (indicated in Figure 2 by a checkmark).

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Note tiat the representation helps users visua~ie key pof the situation “at a glance:’ These representations served as memo~ aids for subgoals and solution states, particularly because subjects worked at intervals-usually separated by a couple hours but as large as 18 ho~d had to reacquaint themselves with the situation each time they resumed work. Subjects using solely a chronological fist of email messages with no notes repofied that they paged through 10-20 messages at the start of the second day to recall what had taken place.

Look Ahead and Group Awareness “Look aheti’ refers to a problem-solving planner’s activity of imag-g and evaluating akemative sequences of actions before acturdly selecting an action. The basic idea is that for some tasks it is possible to do a complete “look ah~ at al akematives sequences of actions and choose the best sequenm of actions that leads to the gord. For other task it is not possl%leto do a (complete) Look ahead due to lack of information on which to base an evaluation function, task complexity, ~iited attention, or working memory ~iitations.

Some participants revised their paper representations over time as their understanding of the task (its scope, how to solve it and how best to represent it) improve~ some participants reported that they were dissatisfied with their representations (e.g., the subject who produced Figure 2), but did not revise it because it was too time-consuming to recopy everything and produce anew one. —-

h contrast to group members who are aware of each others’ work habits (e.g., Bob usually checks email in the rooming), most subjects did not develop awareness of each other’s patterns of work and few used tis information to “Look ahd’ in deciding what action to do neti One subject di< however, try to make use of the Mlted tiormation tiat tie ‘%gef’ command provides and ex~ressed a desire to have more awareness about when other SASwere Rely to be working to help him decide what to work on next For example, if he knew that another SA was Nely to log out in the next M hour, he might interrapt what he was currentiy doing in order to request information from him or her. The “fingef’ comman~ of course, is a primhive form of synchronous awareness @ Bob working now?) but does not answer the question mat is BOVS~~icd pattern of work?). men people m c~locatd in an offiw such information is more ready avdable. Support for richer awareness information * which patterns can be discerned is necess~ to support eficient “look ahea~ strate@es in asynchronous Communication

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Remembering the State of the Task

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As messages accumdat@ answem to key questions such as “Have I processed a spoof C.e., sent an email to the relevant system administrator)~ “~o do I owe a response to? “~o owes me a response? and “Have I processd a response fi.e., updated the suspect fist)? were diffictit for subjects to remember. The load of messages and related pieces of tionnation became ~cuk to manage & aa SA had received and begun processing approtiately two messages from four ~erent spoobg rdiases.

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DESIGN IMPLICATIONS

Use of External Representations

During our observations of The Spoofer Identification Task, we formed the hypotheses that (1) subjects with a tasktaflored efiemal representation could determine more quicuy at the start of a new session what had been done

Of partictiar interest is the M that the representation tiorded by the em~ system subjects used was apparently not adequate to represent the ~ contefi of the problem: 268

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and what still needed to be done than subjects working witi a basic chronological or=-tion of email messages and (2) a system that supported task-tio~le representations \\’odd significantly improve task petiormance. Of course, me our subjects, users u always use paper, but paper is more ~tit to share over distance rmd more ~ctit to revise as understanding of the task evolves. Users can &o btid such representations in a spreadshee~ but they wotid then loose the connection to their Ori=tid messages. Other work has argued for the utifity of retaining such connections [9]. Our observational studies and other studies in the Merature sug~est that nex~-generation asynchronous communication tools need to provide severrd key capabilities: ●

Task-tailorable representations. The task representations that people build need to be task-specfiq it is not possible for intebtiders to create every potentidy usefi representation of information in advance. An effectiveinteb must provide took by which users can create new representations as needed without Seat eti or ski~.

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Another issue concerns the cost of building md maintaining task-tiered representations. We felt that the cost would have to be ofiet by a big gain in task Wtiormance. Existing cognitive models of graphic and textural layouts are quite prelimin~ [2, 13] and did not eastiy lend themselves to predicting performance in advance, so we decided to run a study to memure changes in task petiormance using a task-tailored representation. We reasoned that it would be worthwtie developing a prototype system to support task-tiorable inteti provided the performmce gains were relatively large.

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STUDY: HOW MUCH DOES A TASK-TAILORED REPRESENTATION HELP? Participants were randomly assigned to one of two condhions: Task-Tailored htek and Chronological ktefice. Based on the paper representations we had observed subjects using, we developed a task-tailored representation to support subjects doing The Spoofer Identification Task @igure 3). The hypertextual tasktatiored representation provides an tiordance that the paper representations did noti subjects cotid have access both to the visual representation of situation and to the actual messages as background information. Highlighted text and check marks in this representation indicate active links to email messages.

Emergent sharing. People may be we~ into a task kfo~ they discover that hey shotid be working with others to solve a problen A system must Wow tiormation to be selected and combmed from mtitiple individual representations of the information created with heterogeneous systems. PubEc/private elements in a layout People may want to make @arts o~ their information (e.g., the suspect fist) available to others in the group, either for viewing or updating, while stifl retaining its position in their own task representation kcrementi formtiom People vary in the sophistication with which they can compose agents that would communications automatictiy ‘>lace” appropriately in a layout automatically. Moreover, the overhead involved in fomtig may be too much fw a task of short duration. A system must support fiormrd expression of layout and direction manipdation as we~ as automated layout (cf [4, 25]) as a way of supporting the ongoinS refinement of candidate representations. Asynchronous awareness. H av~able, people can use awareness of others’ activities to solve probIems more effectively (e.g., Before I tih with task Y, I shotid send a request to WIS person because he/she ~ic~y logs in at WIS time of the day). A great derd of work has been directed toward providing awareness in synchronous systems [S]. Asynchronous systems stiarly need to find ways to support awareness.

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These capabilities ze desimble in otier situations besides asynchronous communication Providing such capab%ties for asynchronous communicatio~ however, raises some special issues related to being able visu~e dynamic data

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(e.g., reco-g newlunread messages in a layou~ notication gramdarity for incoming messages, etc.).

Conditions

“ Emergent representations. People’s understanding of how to represent a task most effti’e~ evolves with exTetience in the task. A system must Wow people to modi@ representions easfiy. ●

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The control condition used a chronological list of email messages presented in the same browser as the experiment 269 -.

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leavethe gameafter the first day. Your task today will be to figure out what Carol knew when she Iefi the gamq and what you would have to do next if you were taking over for her. She has Iefi you nothing but her emd account to help you determine the current state of the situation. You’ll have to use this accoun4 setup as she created i~ to answer some questions. Before we ~ you’ll need some background information. FM of dl, the Woofers sending the email have been logged in to one of four dflerent machineswhen sending the messages: uxl.sp.cs.cmu.edu ux2.sp.cs.cmu.edu M.sp.cs.cmu.edu ux4.sp.cs.cmu.edu To fmd ~iely suspects, the% the system administrators of these machineshave been exchanging lists of what users were logged into each machine at the time tie spoofed emailwas sent

condition, with gened characteristics of the user in-, including background color, font and oved appeamnce kept constant @i=gure4). Subjects Subjects were twenty undergmduate students recruited* -egie NleNon University. Ten subjects completed -h condition (ChronoIo~c~ask-Tdored); each was paid $10.00 for their participation in the experiment AU pticipants \%7erehi~y -or with emafl and used it d&y.

Tasks and Measures Thetasks we asked subjects to complete were designed to test performance in figuring out what needs to be done, what responses are pending, and where crucird information is located Perfommce on each of these %ks was timed by an experimenter, who told subjects exactly when to turn a page to read each questiou the subjects were asked to say when they were ready to move on and the experimenter recorded the completion time. Answers were later scored h accuracy as we~. Here is the exact text of the questions: Yourjob is to find the answersto these three questions: ––-.,.- -,.. ———.. –-_ r-1)- 1ne sysrem “ aammIsrraIors ‘ ..’’--”-- were excnangmg reques~ Iur lists of who was logged onto particular machines at particular times. Carol Allison was the system administratorfor UX4,and she always kept copies of any responses she sent to other system administrators. Who did she owe lists to fi.e., who had asked her for lists but not receivedresponsesfrom her yet)? 2) Who owed Carol responses (i.e., which system administrators had not yet responded to a request for a fist horn ux4)? Bre wanted to focus on how wefl a subject cotid understand the state of a situation ~ returning tim a long break between work periods, as owurs often in asynchronous communication situations. For example, a person completes some work on a projec$ saves it in a sharsd folder, -and then returns to that folder to continue work after others have made new changes to the folder. To m~we the unfamiliarity of “forgetting the situation and having to incorpomte changes into one’s understanding, we decided to simtiate a turn-ver situation in a worLT1aw. when one shift passes on work to the ne- Thus, we used subjects unfamfiar with the @L provided them with an intiodnction to the basic ties, and then told them they were participating in the fo~owing scenario

3) The system administrators were -d that they might have missed sometilng in combiningtheir user lists into a suspect list for the perpetrator who crdled himselfThe Phantom. You don’t have to re-create the suspect list, but simply locate and print any user lists that Carol would have to examine to veri~ that the Phantom suspects were redly rdl logged on at the time of the Phantom spoofs. &r competing d three tasks, subjects completed a subjective questionnaire. Results

and Discussion

Subjects using the task-tailored representation were able to determine more quic~y what had been done and what still needed to be done than subjects who used only a basic chronological orgtition of emafl messages. bdee~ the amount of time was cut in hdf for two of the tasks with no

The Game is in Progr=s Four players have rdre2dybeen playing a game pursuing some spoofcrs. One of the players, Carol Alisom had to 270 .-

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~erence in awmacy detected Table 1 and 2 depict the means and standard deviations for time and accuracy in each of the two conditions. It is woti noting that the majority of the time subjects spent in the task-tiered rnteti was used in interpreting the _iar inteti (we did not train them on the iute~ in advance). A separate test of a subject Mar with the inte&e indicated a time of around 30 seconds to do Tmk 1. Thus, the times we observed are probably upper bounds. Task

Chronological

TaskTailored

294.2 (621)**

3. If%ere is Phantom data? 1S6.1 (65.0)

125.1 [34.2)** 162.2 (70.9)

* p ubtishes” tie renaming the fist other SAS by fist to private.carol~oadrunner to SA.wol.roatier and inviting other SAS whom she knows are rdso working on the task to register and look at it Emergeti

To r~u= the work in using parts of fields to represent messages and for manurdly putting messages in columns tbr wK1chit is difficuk to write sirnple des that make use of system-represented attributes of messages, we are exploring tie use of machine-learning techniques that Wow training of agents&at “look over the shotidef’ of usen and oti to ~ese twhniques & automate recurring activities. appropriate when the app~cation involves repetitive behaviorthat is potentitiy ditierent for ~erent users [la. RELATED RESEARCH Numerous studies of asynchronous communication have been conducted (for an exmllent review, see [17]). Most & tie research has looked at the socid-psychologid eof working -tmb vs. communicating asynchronously. Otier work on rnktim for asynchronous communication has focused on the social psychologicrd eof -t inte~s [26]. Our research extends and implements previous work by focusing on the cognitive e~at ~er intefices a have on asynchronous work When people must work ~mchronously, tools tith efftie inteb can minimii the disadvantages and m-e the advantages of communicating across space and time. Both cognitive and social effa are relevant to measuring eff=tieness.

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Numerous field studies have been concluded on asynchronous communication [e.g., 10, 12, 14, 29]. Our work supplements those studies with formative observational and laborato~ studies. We befieve that W these types of study are essential in making progress in supporting asynchronous communication and plan to do a field study of our prototype. Previous work on awareness has fomd primarily on synchronous awareness. Gu~in et al. iden@ seveti types workspace, orgtitiond situatiow infonnrd, social, and structi and have done much work on synchronous workspa= awareness [8]. me work reported here fmuses on situation awareness (i.e., unders~ding the state of a dynamic system). We have dso made a case fm asynchronous workplace awareness and are actively working on representations OC fm example, awareness of otiers intentions were are they going to be?). k terms of interface and architecture, the work reported hm is closely relatd to Ovd [16], Object Lens [11] (and its precursor, Mormation Lens), systems which display vrdues of sele~ed fields from objects (e.g., messages) in a table or tree and support end-user programming of agents (e.g., email agents). Like Oval and Obje~ Lens, our approach makes use of an object-oriented database that suppofi hypertext links. OW work extends this work by (1) separating tie view of the object from the data in the object. ~s allows, for example, parts of a field or even a “check m~ to be used as a representation of a fielt and (2) rdlowing direct editing of the object in the view rather than requiring the user to edit an object @pe or explicitly adding afield to an object imtance. For example, in Object Lens, displaying messages in the “Response Receive& column wotid require tie user to meate a new object type (e.g., a type ‘Message-for-which-a-reply-is-expected’ as a subtype of the object type Message); if object instances aheady existed in the system that did not have the type, they would have to be retyped k Oval, a user could edit an object instance directly by choosing Add Field from a menq Wls would result in au instances of the object (and the object type) having the new field value.

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h our system users are able to add’ a field by @serting a new column in the table and labeling it (e.g., “Response Received”). ~ey can either place responses in the cells by direct manipulation (which adds a field to the message placed in the cell but not to the related message) or write a tie that says “Ha message is a reply to the message in the previous column, put in this cell: We hypotheskethat such direct manipulation will have two advantages: (1) users wfll be able to get the information they want represent without a great dd of overhead and thinking users with minimal about types/subtypes, enabhg competence in concepturdiig types/subtypes to use the system (much as spreadsheet users may be unaware of computed values but still bd a spreadsheet usefil, k [18]> this was part of the motivation that Malone et al. [lq cite for moving from editing object types to editing object instances; and (2) for some problems, this representation will tim and the added cost of de~g such relationships for shofi-lived problems will be judged

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not to be worth the effot By etiating the requirement to always form~e representations, even for short-fived problems, we increase the ~e~ood hat users WMfind the oveti system cost-effective in terms oftime and effofi

experiment

AND FUTURE

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Interaction

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We have only examined one aspect of task @onnanw reestablishing an understanding of the situation & time au’aY horn the task me totrd cosg however, is a cost d building and maintaining, s wefl as using, a representation Our next step is to test whether people cau use task-tailorabiity of our prototype to easfiy build such representations for new, complex, and dynamic situations.

Workspace awareness in rd-time distributed groupwarti Framework widgets, and evaluation. h RJ. Sasse, A. Cunningham, and R. Winder @.) People and Computers X @p. 281-29S). SpringerVerlag. 9. Hotiq

M., Schreiweis, U., & Laugendbtier, H. (1990). An integrated approach of knowledge acquisition by the hypertext system CONCORDE. h A. Rik N. Strei@- & J. Audr6 @ds.) HPert&: pp. 166-179. Concepts, systems and applications, Cambridge University Press, Cambridge, UK.

hforeover, time and ~ are ody one measure of ~tiomance in group work We intend to do mer studies to examine other cognitive issues (e.g., memory h tie communication) and social issues (e.g., does being able to see “at a glance” who has not gotten back to you have a positive or negative -on your perception of a person?) raised by our approach to asynchronous communication.

10.

Assuming that our approach works, we plan to include au intethat tiows users to browse previously layout templates, use the template as a starting point and exlend ad custotie the tempIate as nded to ~ new situations [5, 2S]. Our initial prototype provides ody one layout type (a tabIe). We are actively working on other layouts that can form the basis for good efimd representations of other communication tasks.

KrauL R. E., Scherlis, W, Mukhopadhyay, T., Manning, J., Kiesler, S. (1996, Dec.) HomeNeti A field tid of residential htemet services. Communications of the ACM.

11.

Lai, K., Malone, R., & Yu, K. (1988). Object Lens: A “spreadsheet’ for cooperative work. ACM Trans. on Ofice In$ Systems, 6 (4), 332-353.

12.

LicMider, J.C.R., & Vess% A. Applications of information networks. Proceedings,

ACKNOWLEDGMENTS

13.

resach was tided by -A, Contract Number N66001-96-C-S515. The authors would Me to thank Anne Humphreys and Pad Erio~ who *O workd on the projec~ ~Is

14.

IEEE

641330-1346.

*

8, 353-3SS.

MacKay, W.E. (1989). Diversi& in the use & ACM electronic maik A pretiary inquiry. Transactions 3s0-397.

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Lohse, G.L. (1993). A cognitive model h understanding graphical perception. Human-Computer Interactiofi

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