UNIVERSITÀ DEGLI STUDI DI NAPOLI FEDERICO II

Transcription

1 UNIVERSITÀ DEGLI STUDI DI NAPOLI FEDERICO II SCUOLA DI DOTTORATO IN INGEGNERIA INDUSTRIALE Dipatimnto di Inggnia Economico Gstional TESI DI DOTTORATO IN SCIENCE AND TECHNOLOGY MANAGEMENT XXIV CICLO Knowldg shaing VS constuction in onlin-convsations: a Dbat Dashboad to suppot distibutd dcision making though th collaboativ constuction of shad knowldg psntations Coodinato dl dottoato Ch.mo Pof. Giuspp Zollo Tuto Ch.mo Pof. Luca Iandoli Ch.mo Pof. Giuspp Zollo PhD candidat Dott. Ivana Quinto

2 Tabl of Contnts Intoduction 4 Chapt 1 Wb 2.0: It is not a fad, but th nw nomal Intoduction A social volution: th Wb Wb 2.0 in oganizations 31 Chapt 2 Wb-nabld collctiv intllignc fo suppoting distibutd dlibation pocss Intoduction Using collctiv intllignc to mak btt dcision Cunt wb-basd tchnologis fo suppoting collctiv dlibation pocsss Shaing tools Funnlling tools Agumntation tools Conclusions 54 Chapt 3 Comput suppotd agumnt visualization Intoduction Agumntation thoy: a shot intoduction Toulmin s schm IBIS fomalism Th is of comput suppotd agumnt visualization Th agumntation systms Vitus and shotcomings of agumntation tchnologis 74 1

3 Tabl of contnts Chapt 4 Communicating Efficintly to Collaboat Effctivly: Th Common Gound Thoy Intoduction Common Gound: Clak s Contibution Common Gound In CSCW Gounding in Onlin Agumntation-Mdiatd Communication fo Suppoting Distibutd Dlibation Pocss A Thotical Modl Fo Augmnting Agumnt Mapping Tools Community Fdback Intaction fdback Absoption fdback Th dsign of th Dbat Dashboad A wb-basd Agumnt mapping Tool: Coh Th Dbat Dashboad 114 Chapt 5 Expimnt Dsign and Mthodology Intoduction Th Thotical Modl to tst Th Rsach s Hypothss Expimnt Dsign: A Fild Tst Masumnts Post-sssion Qustionnai Data Analysis Mthodology 142 Chapt 6 Data Analysis and Rsults Intoduction Dsciptiv statistics Data Analysis of Coh Databas Post-sssion qustionnai data analysis Vitual Machin Databas Stuctual Equation Modlling Analysis Masumnt Modl Stuctual Modl Mdiation Rsults Discussion Limitation 185 2

4 Tabl of contnts Appndix A Litatu viw on Visualization Tools 187 Appndix B Post sssion qustionnai 195 Appndix C SEM Gaph 198 Rfncs 200 3

5 Intoduction Th ability to collaboat is today on of th cucial capacity that oganizations hav to possss fo suviving in cunt tubulnt and highly comptitiv nvionmnt. Wb 2.0 sms abl to off adquat and mo fficint solutions to lt oganizations to collaboat with stakholds, customs and mploys and oth companis. Indd, on th Intnt th a sval tools that a abl to suppot lag, divs, and gogaphically dispsd goups to systmatically sha, xchang, co-cat knowldg and collaboativly com to dcisions concning systmic challngs. Th most common wb-basd collaboativ tools a blogs, wikis, foums, social ntwoks, which w tmd shaing tools [Josan, Isamil and Boyd, 2007]. Th wid succssful dpnds mainly on thi as of us and accss. Unskilld tchnical popl can asily paticipat to th cation and shaing of digital contnt. In litatu, th is vidnc that ths tools a vy fficint and ffctiv in suppoting collaboativ tasks at vy lag scal, such as accumulation, poduction and xchang of knowldg (.i. Wikipdia, InnoCntiv, Linux), but thy hav to fac also numous shotcomings whn applid fo suppoting collaboativ dlibation and dcision making pocsss aound complx poblms. On of th main citicism gads th way knowldg is captud and sntd. Indd, shaing tools oganiz captud contnt in a chonologically od, that is knowldg psntation is basd on whn th uss contibutions w postd. This way to psnt knowldg is considd th main caus of sval dysfunctions, such as: Low signal-to-nois atio: th small-voics a not listnd. Thy a vy cucial bcaus thy fost cativity and divsity by binging nw idas, opinions and pspctivs. 4

6 Intoduction Rdundancy: th captud contnt is oftn unsystmatic, ovwhlming and scattd. This ducs th possibility to idntify lvant infomation o not wll-covd aas, quiing mo attntion. Additionally, this hamps uss to cogniz goups consnsus. Conflicts: opposit viws may poduc clashs that block convsations (dit was and flam was) Lack of navigability: th captud contnt is oftn ovwhlming and do not show any connctions among latd pics of infomation. This hinds uss to mak sns of convsations, in paticula way, it impds nw coms to undstand and pitch into a discussion statd by oths. Oth kind of wb-basd tchnologis such as pdiction makts and -voting hav bn povd to b ffctiv at agggating individual opinions to dtmin th most widly/stongly hld viw [Wolfs & Zitzwitz, 2004], but povid littl o no suppot fo idntifying what th altnativs slctd among should b, o what thi pos and cons a. Additionally, thy do not lt uss to psnt th ational bhind a dcision. In od to addss ths shotcomings, altnativs tchnologis, abl to suppot a mo stuctud knowldg and conflicting points of viws psntation, hav bn dvlopd. In paticula, in this sach w focus on agumntation tools. Ths tchnologis ty to fill th abov mntiond gaps by hlping goups to psnt a dbat as a visual map composd of th lmnts: (i.) a st of issus to b answd, (ii.) positions (o idas) as altnativ solutions to issus and (iii.) suppotiv o challnging agumnts about poposd idas. Dbat is summaizd into a visual map conncting Issus, Positions and Agumnts though lablld links such as suppots to, objcts-to, suggstd by, placs. Such tools a supposd to b paticulaly suitd to fost dlibation and dcision making pocsss aound complx poblms as thy allow uss to psnt contntious and/o compting point of viws in cohnt stuctus mad up of altnativ positions on an issu at stak with thi associatd 5

7 Intoduction chains of pos and cons agumnts. Moov, by poviding a logical-basd dbat psntation, and by ncouaging vidnc-basd asoning and citical thinking, thy should significantly duc th pvalnc of som citical pitfalls that usually lad to dlibation failus in small scal goups and pomot a mo wll-suppotd dcision making. Agumnt mapping tools also fac som impotant shotcomings. Concns hav bn aisd about th ffctivnss of agumnt mapping to mdiat intaction: a cntal poblm is th psnc of communication fomats too constaining and intusiv that disupts th natual flow of f convsations, stpning th laning cuv and thfo incasing that uss cognitiv ffot ncssay to paticipat. Th stuctu of agumntation consids social and convsational cus as ilvant thus impding f communications and intaction. This has ntaild an objctification and fomalization of convsation aound th knowldg map, as wll as th loss of a ang of mtainfomation about paticipants and th intaction pocss though which th contnt is gnatd. Accoding to Clak and Bnnan [1991], th loss of this mta-infomation hinds f intaction and maks convsation lss fficint. Thfo, th tad off dpnds on th lack of tools abl to wisly mix social cus with knowldg oganization fomats. Shaing tools povid onlin uss with ich social and convsational infomation, but thy do not suppot an fficint and ffctiv knowldg oganization; on th contay, agumntation tools suppot a mo stuctud knowldg oganization, but thy nglct social cus, hinding f intaction. Rsach Qustion Th sach psntd in this thsis is motivatd by th dsi to impov agumntbasd convsations. In paticula, psnt study aims at nhancing th fficincy of agumnt mapping tchnologis in suppoting f intaction and mdiating wb-basd convsations among goups of individuals involvd in onlin distibutd dlibation and dcision making pocsss. Th basic assumption is that onlin agumntation tools 6

8 Intoduction could b th ight tchnologis fo suppotd distibutd dlibation and dcision making pocss, but thy hamp th f communication. W appoach this by addssing th paticula challng of making agumnt-basd convsations mo fficint in tms of communication costs that uss hav to ba. Th supposition is that, by pioitizing th fomal psntation of contnts gnatd by uss, sachs and dvlops hav nglctd social and communication aspcts which a vy impotant in fosting communication and mak paticipation mo ngagd. Actually, pvious sachs on th dvlopmnt of wb-basd agumntation tchnologis hav focusd on th constuction of appopiat knowldg fomat fo captuing and displaying uss contibution as wll-fomd agumntation maps, ath than on th povision of any social and convsational cus that suppot f and asy intaction and th cation of pop knowldg objct. This has aisd concns on th capability of agumntation to act as ffctiv mdiato and facilitato of intaction, notwithstanding th makably advantags that a xpctd fom its us. In this wok th aim is to invstigat how social and convsational agumntation tchnologis capabilitis can b impovd, and whth and to what xtnd ths impovmnts impact on uss pfomancs. Put diffntly, th aim is to impov th mdiation and intaction capability of agumnt tools by suppoting common gound constuction and updating duing agumnt-basd convsations. With this in mind, th cntal sach qustion is: How to tain th advantags of agumnt mapping and impov thi mdiation capability? Litatu Ovviw Poviding an answ to th qustion abov implis constituting a thotical basis fo btt valuating th stngthns and waknsss of agumnt mapping tools. 7

9 Intoduction Litatu has showd that agumntation tchnologis spct oth cunt taditional onlin tools, a abl to suppot ffctivly dlibation and dcision making pocsss. Onlin agumntation tools mak us of th agumnt thoy to mdiat and psnt dbats. Agumntation thoy dals with how humans should and do ach conclusions though asoning. It is basd on th ida that vy opinion can b bokn down into sub-lmnts that play ctain infntial functions in th discous, such as th conclusion o claim of an infnc and th pmis that lads to it. An agumnt map can b dfind as a visual psntation of an agumntation in which th functional lationships among claims a mad wholly xplicit using gaphical o oth non-vbal tchniqus [van Gld, 2003]. Th tm agumnt mapping indicats th act of poducing such maps, as wll as modifying, viwing and shaing thm. On th Intnt, th a numous xampls of wb-basd collaboativ agumnt mapping tools (fo a viw of cunt tools s that allow uss to navigat, co-cat and dit an agumnt map. Onlin collaboativ agumnt mapping tools can b usd to visualiz concpts, contnt (.g. annotations), knowldg soucs (.g. wbsits), as wll as links btwn knowldg lmnts. Th main fatu of agumnt maps is that thy allow uss to psnt complx asoning in an asy to follow, cla and unambiguous way. Th basic assumption bhind this appoach is that displaying knowldg visually though a spatial mtapho, is hlpful fo ky cognitiv tasks such as sns-making of lag amount of (conflicting) infomation [Un t al., 2006] and localization of lvant infomation. Additionally, such spatial-visual psntation suppots vidnc-basd asoning [Bx t al., 2003] by psnting contnt in a concis mann and making th logic bhind an analysis mo vidnt. By poviding a logicalbasd dbat psntation, and by ncouaging vidnc-basd asoning and citical thinking, should significantly ncouag individuals to mak wll-goundd and asond dcisions, futh to avoid som citical pitfalls that usually lad to dlibation failus. 8

10 Intoduction Nvthlss all ths advantags and th positiv impact on oganizational knowldg managmnt and in paticula way on dlibation and dcision making pocsss [Conklin, 2003; van Gld, 2003; Tgan, 2003], thy sm to stuggl to ach widspad diffusion both in th small and lag oganizations. In this sach w think that th limitd succss of onlin agumntation as a collaboativ tchnology dpnds mainly on th fact that ths tools nglct social and convsational aspcts that, in ality, mak convsation asi and mo ngagd. This has ntaild th loss of a ang of mta-infomation about paticipants and th intaction pocss though which th contnt is gnatd, hinding intaction and maks convsation lss fficint [Clak and Bnnan, 1991]. Accoding to Clak and Bnnan [1991], duing a convsation, paticipants xchang, in addition to infomation, vidnc and/o qusts fo vidnc ndd to undstand if th listns hav undstood o hav not undstood what th spak has said [Clak and Bnnan, 1991]. Onc such vidnc is gaind though convsational fdback offd by vbal and nonvbal communication acts, it is usd to updat paticipants shad infomation. Th pocss of making th undstood infomation pat of paticipants mutual knowldg, blifs, and assumptions is calld gounding pocss. Th ffctiv constuction of mutual knowldg is a ncssay condition fo a succssful convsation and knowldg accumulation and tansfomation. Gat amount of common gound lads to mo fficint communication, coodination, collaboation and pfomanc [Clak, 1996; Convtino t al., 2005]. Whn th convsation is mdiatd by any kind of communication tchnology, pat of th convsational fdback povidd in fac to fac discussion is ith unavailabl o can b povidd with som xta communication ffot. Consquntly th thoy of common gound stats that mdiatd communication is always lss fficint than fac to fac intaction and infficincy is chaactizd in tms of gounding costs. In lin with this, in th cas of agumnt mapping tools, th common gound building pocss is vy complicatd and cognitivly costly. 9

11 Intoduction Clak and collaboatos [Clak and Bnnan, 1991; Kaut t al., 2001] poposd that spcific communication contxts can b dscibd in tms of sts of gounding constaints (Tabl I.1). Ths constaints a dsiabl to duc th ambiguity and gounding costs in convsation. Indd, th high th numb of missing constaints, th lss abl th mdium will b fo facilitating common gound building and fficint communication. Tabl I.1. Affodanc in communication mdia Affodanc Clak t al. s dfinition Ou adaptd dfinition Audibility Copsnc Cotmpoality Mobility Paticipants ha oth uss and sound in th physical nvionmnt Uss sha th sam physical nvionmnt B civs at oughly th sam tim as A poducs Uss can mov aound physical spac Paticipants ha oth uss and sound in th vitual nvionmnt Paticipants a mutually awa that thy sha a vitual nvionmnt Paticipant civs th mssag at oughly th sam tim as th oth poducs (in al tim) Popl can mov aound in a shad vitual nvionmnt Rviwability B can viw A s mssag Mssag do not fad ov tim but can b viwd Rvisability B can vis mssag fo B Mssag can b visd bfo bing snt Simultanity Squntiality Tangibility A and B can snd and civ at onc and simultanously. A s and B s tuns cannot gt out of squnc. Paticipants can touch oth popl and objcts in th physical nvionmnt Paticipants can snd and civ mssags at onc and simultanously Paticipants can undstand and s th ply stuctu Paticipants can touch oth popl and objct in th vitual nvionmnt Visibility A and B a visibl to ach oth Paticipants s th actions of th oths us in th shad vitual nvionmnt Following Clak and Bnnan s thoy, w valuat agumntation tchnology in tms of th tchniqus it allows building common gound and thus in tms of gounding costs that uss hav to ba to communicat in an fficint way. In paticula, in th cas of agumnt mapping tools, gounding cost is vy high sinc ight out of tn constaints a missing. 10

12 Intoduction Thfo, th main ason fo a poo mdiation and communication pfomancs of agumnt mapping tools in tms of gounding costs is that thy a objctd-ointd tchnologis: th pimay objctiv of an agumnt mapping tool is to gnat a knowldg objct in th fom of map abl to captu and oganiz knowldg povidd by many contibutos duing a dbat. Diffntly fom oth collaboation tchnologis, thy a not xplicitly dsignd to suppot intaction and kping tack of th communicativ acts dvloping duing th pocss. Thfo, tchnology mdiation, objct-ointation, fomalization and spatial oganization of infomation ntail high gounding costs and consquntly difficultis in dvloping common gound and suppot fficint/ffctiv communication. Th difficultis of building common gound may pvnt uss to xploit th bnfits usually associatd to th us of agumntation tchnologis; such bnfits actually assum th availability of wll-fomd maps o at last that uss a in th conditions to cat such maps. If gounding costs a high, th chancs fo uss to cat good maps will b low, unlss substantial ffot is povidd by xtnal modatos chagd with th task of mapping in al tim th contibutions povidd by many uss. Unfotunatly modation can bcom vy costly whn th uss numb is not small. In od to tackl this poblm th ida is to dvlop an augmntd agumnt mapping tool abl to tain th taditional advantags offd by agumntation tchnologis and to dliv at th sam tim a ich st of mta-infomation aimd at fosting social intaction among uss and suppoting th constuction of mutual undstanding. W call such an augmntd Dbat Dashboad bcaus th mta-infomation is dlivd mostly though visual widgts, built upon and connctd to th agumntation tool, that a xpctd to suppot paticipant convsations. Th basic ida of th Dbat Dashboad is to mak visibl infomation that in fac-to-fac convsation is immdiatly availabl, whil in comput mdiatd communication a hiddn o missing. 11

13 Intoduction Numous sachs hav bn focusd on th analysis of th impact of convsational fdback and hiddn infomation on quality of discussion, its outcom and intaction pocsss among uss. Shnidman [2000] agud how disclosing pattns of past pfomanc, poviding ich fdback about uss and gnatd contnt a bst pactics fo suppoting onlin convsations. Eickson t al. [2002] discussd th impotanc of making socially-lvant hiddn infomation visibl in intactiv communitis in od to suppot smooth, flctiv and poductiv convsations though synchonous and asynchonous tools. Oth sachs hav built systms attmpting to povid lag amount of infomation about th psnc and activity of thi uss in a consolidatd and asy-to-ad way. [Donath t al., 1999; Vigas & Donath, 1999; Dav t al., 2004; Suh t al., 2008]. Ou goal is to st up a Dbat Dashboad in od to aid uss to monito and mak sns of discussions, showing thm fdback about paticipants, thi activitis with spct to th convsations and th volution of th gnatd contnt. In oth wods, dawing on gounding cost thoy, w dfind th catgois of fdback that a supposd to duc collaboativ cognitiv ffot, as wll as fost gounding pocss: Community (who): this st of fdback allows uss to know who a th community mmbs, to visualiz th community stuctu and to dvlop a sns of mmbship [Kim, 2000]. Intaction (how): this class of fdback allows uss to undstand how th mmbs of onlin community intact and what is happning in th onlin community. Absoption of knowldg (what): this fdback is about th contnt gnatd though intaction among uss and its oganization. As alady mntiond, by poviding such convsational fdback it is possibl to suppot th constuction of mutual undstanding which is usually caid by vbal and nonvbal communication acts in odinay convsations and is patially lost whn convsation is mdiatd by a tchnology. 12

14 Intoduction Ths classs of fdback a supposd to suppot uss in communicating in btt and asi ways, ducing misundstandings, facilitating th gounding pocss and diminishing its latd costs. Moov, w xpct that th impovmnt in th gounding pocss may also impov som uss pfomancs such as fficincy and outcoms. Th fdback a povidd though diffnt visual widgts whos fatus w dfind on th basis of sults of both a litatu viw on thity alady implmntd visualization tools and a suvy of th most famous social ntwoks, chats, blogs such as Twitt, Skyp, Facbook tc. All th visualization tools, that compos th Dashboad, wok in a closly coupld way, thfo any manipulation and chang of valus in on viw cats a simila chang in th linkd ons. This allows uss to look at data though diffnt pspctivs, pciv nw infomation and discov nw insights. Th Dbat Dashboad has bn built upon a wb-basd agumnt mapping tool, namly Coh and an xpimntal vsion is availabl at Coh is a wb-basd asynchonous agumnt mapping tool whos pupos is to suppot an on-lin collctiv agumntativ dbat. This agumnt mapping tool applis th IBIS appoach [Issu Basd Infomation Systm, Kunz & Rittl, 1970]. With Coh uss can cat posts to xpss thi thoughts and pick up an icon to associat to thm, which xplain th htoical ol of that post in th wid discussions. Moov with Coh uss can xplicitly connct thi post to oth post which is lvant to what thy want to say. By stuctuing and psnting onlin discous as smantic ntwok of posts Coh nabls a whol nw way to bows, mak sns of, and analyz th onlin discous. W chos Coh fo th valuation tst bcaus it is alady abl to povid som of ou individualizd fdback. This implicats mino ffot to mak th platfom adaptd to ou aims. Anoth impotant ason fo which w chos Coh is that it is a wb- 13

15 Intoduction basd asynchonous agumnt mapping tool. Th asynchonicity maks mot, mdiatd convsation, as wll as th gounding pocss, mo complicatd. Thfo, th utilization of fdback in this contxt maks sns and could b vn mo appopiatd, as wll as mo challnging. Expimnt This study wants to tst th impact of visual convsational fdback on Mutual Undstanding (MU) and, in tun, th impact of MU on uss pfomancs, using onlin collaboation agumnt mapping tool. In Figu I.1, w psnt th hypothsis gaphically: P MU F Lgnd: P MU F Pfomanc Mutual undstanding Fdback Affct positivly Figu I.1. Simplifid Thotical Modl Though this xpimnt, byond to valuat if visual fdback impovs and suppot th MU, w aim at valuating th impact of MU and visual fdback on th diffnt kinds of pfomanc (P), that is: Usability: Th vaiabls considd a pcivd as of us, us satisfaction, pcivd usfulnss [Davis, 1989; Vnkatsh and Davis, 2003] 14

16 Intoduction Quality of collaboativ pocss: This vaiabl is masud though th uss pcptions of quality of collaboation, th amount of collaboation (numb of connctions catd duing onlin discussion) Quality of outcom: This vaiabl is masud though th uss pcptions and misalignmnt btwn th goup dcision and th ight solution ; in oth wods th aim is th masuing th accuacy of th goup dcision. Pocdu In od to tst th hypothss, an valuation of th impact of th visual fdback povidd though th Dbat Dashboad on gounding pocss and on uss pfomanc, such as quality of collaboation, quality of outcom and Coh usability was pfomd in Jun 2011 at th Univsity of Napls with a community of aound 60 undgaduat studnts. Th studnts w all pat of th sam class fom a gaduat pogam in Industial Engining, ag Studnts paticipatd in a singl-facto, asynchonous, wb-basd goup dcision making xpimnt. Paticipants w andomly assignd to two goups (A and B). Th goup A was composd of 25 studnts, 56% mal; th goup B was composd of 36 studnts, 64% mal. Each goup wokd on a spcific collaboativ dcision making task fo two wks. Th dcision making tasks a conomic poblms that quid studnts to focast th valu of an conomic vaiabl within th allottd tim. In ou cas, studnts hav focast th oil and gold pic in th shot piod (th months). Duing two wks, ach goup dvlopd and wokd on a collaboativ map that flct knowldg, pspctivs and opinions of uss, as wll as suppot collctiv dcision making pocss on thi spcific task. Th fild tst was basd on btwn-subjct dsign with two goups which hav bn usd only onc and b pat of tatmnt goup o contol goup. Th mmbs of th tatmnt goup (goup A) usd an augmntd vsion of Coh ( that is an agumnt mapping tool intgatd with th visual widgts (th Dbat Dashboad). Tabl I.2 shows how ach fdback has bn implmntd and what fdback could not b alizd bcaus of tchnical fatus of Coh and tim constaints. 15

17 Intoduction Tabl I.2. Affodanc in communication mdia Affodanc Copsnc Cotmpoality Mobility Simultanity Squntiality Visibility Pofil Community histoy Social Stuctu Contxtualization Rlvanc Stuctuing Visual Widgts List of uss. Uss onlin a gn, whil ons offlin a d (Popl&Goup tab on Coh Hom Pag and on Goup Pag) Not povidd Not povidd Not povidd Not povidd Stats about uss activity (Stats tab Uss tab on Goup Pag) Us s psonal pag Stats about catd idas (Stats tab Idas tab on Goup Pag) Social ntwok visualization (Social Ntwok on Goup Pag) TagCloud sach ngin (click to ach TagCloud to visualiz all th idas with that TagCloud) TagCloud (TagCloud tab on Hom Pag and Tags tab on Goup Pag) Agumnt map Moov, w tackd and codd uss activity in od to monito and collct data on what fdback thy usd, as wll as thi fquncy of us. Th mmbs of contol goup (goup B) usd a plain vsion of Coh ( that is without th nw intoducd fdback. Bfo stating th xpimnt, th was a ppaatoy phas, duing which studnts had fou 2 hous of sminas about: i. Collctiv intllignc and its cunt Intnt applications; ii. Agumntation, with a focus on IBIS fomat; iii. Th main chaactistics dfining th Gold and Oil Makt; iv. An instuctional dmo of th Coh. Th studnts w also givn fw adings matials: nwspap and magazins aticls th topics. Moov, a wam up phas of on wk was pfomd duing which uss could us and pactic with th nw fomalism. Aft th compltion of dcision tasks, th mmbs filld out a follow-up qustionnai. Th qustionnai is mad up of 28 psychomtic scal masuing paticipants pcption about quality of collaboation, th outcoms, Coh usability and mutual undstanding. 16

18 Intoduction Masumnts In od to valuat th impact of visual fdback on Mutual Undstanding and on uss pfomancs, w hav to masu th fou following vaiabls. In paticula: Us of Fdback: was masud though th fquncy of fdback utilization. W collct this data by using Vitual Machin (dvlopd by a sach goup of Univsidad Calos III) abl to tack and cod uss onlin uss activity (uss chonology). In this way, w could comput th us of fdback fo ach us (fquncy). Mutual Undstanding: was masud though Likt scals by administing a follow-up qustionnai. Quality of Collaboation: was masud though Likt scals by administing a follow-up qustionnai and though a quantitativ masumnt as numb of catd connctions (Infomation bok + Compad thinking) Quality of Dcision: this vaiabl was masud though Likt scals by administing a follow-up qustionnai and though a quantitativ masu, that is th accuacy of studnts fosight Usability: this vaiabl was masud though Likt scal by administing a qustionnai. Data Analysis This disstation us Stuctual Equation Modlling to analyz th thotical modl. Th main multivaiat gssion tchniqus sha on common limitation: ach tchniqu can xamins only singl lationship at a tim [Hai t al., 2006]. Ths taditional tchniqus do not nabl us to tst th sach s nti thoy with pocdus that consid all possibl infomation. 17

19 Intoduction Stuctual Equation Modling (SEM) is a family of statistical modls that sk to xplain th lationships among multipl vaiabls. It can xamin a sis of dpndnc lationships simultanously. So, a hypothsizd dpndnt vaiabl bcoms indpndnt vaiabls in subsqunt dpndnc lationship. SEM has sval advantags ov fist gnation tchniqu lik pincipal componnts, facto analysis and multipl gssions. Fist, SEM allows sachs to modl lationship among multipl pdicto and cition vaiabls [Chin, 1998]. Scond, SEM nabls sachs to masu latnt (unobsvabl) vaiabls. Thid, SEM allows sachs to assss th masumnt modls and stuctual modls simultanously. Thus, masumnt os can b analyzd as pat of th modl. Finally, SEM stimats a sis of spaat, but intdpndnt, multipl gssion quations simultanously by spcifying a stuctual modl. Ths attibuts nabl sachs to answ a st of intlatd sach qustions in a singl, systmatic, comphnsiv analysis [Gfn t al., 2000]. Consquntly, as SEM is wll suitd to modling complx pocsss, w think that it is wll adaptd to th analysis of ou thotical modl. Rsachs hav two mthods of SEM analysis to choos fom, such as covaiancbasd SEM o last squas-bass SEM. PLS was chosn ov th oth on bcaus PLS suppot xploatoy sach and th data distibution assumptions a lss stingnt than th assumptions bhind covaianc-basd SEM. Additionally, PLS is capabl of assssing indict ffct such as th mdiation ol of Mutual undstanding btwn us of fdback and uss pfomancs. Rsults Rcall that th ovaching goal of this disstation is to invstigat th influnc of visual convsational fdback on MU and, in tun, th impact of MU on uss pfomancs (quality of collaboation, quality of dcision and usability). 18

20 Intoduction Fo data analysis, th diffnt databass w usd, in paticula: Coh databas. It includs all data gading uss activity pfomd on Coh platfoms (goup A and goup B). Follow up qustionnai databas. It includs data collctd though th follow up qustionnai administd to all paticipants at th nd of th xpimnt (goup A and goup B) Vitual Machin databas. This databas contains only data latd to studnts of Goup A. By using th vitual machin, th us of ach fdback has bn tackd and codd though thi spctiv URLs. It was possibl, bcaus ach visual widgt, by which w povid diffnt individualizd fdback, has an own wb pag and, thus, an URL (only goup A). Each of ths databass has bn analyzd to tst ou hypothsis and ach analysis has confimd as w supposd and xpctd. In paticula, fom th analysis of Coh databas is mgd that goup A wokd mo than goup B notwithstanding goup A is small than goup B (spctivly 25 and 36) (Tabl I.3). Tabl I.3. Dsciptiv statistics Coh databass Us s activity Goup A Us s activity Goup B # Posts 269 # Posts 334 # Connctions 412 # Connctions 380 Total 681 Total 714 Avag 27,24 Avag 18,31 St. Dviation 22,98 St. Dviation 16,28 On-tail T Tst on uss activity lvl confims that goup A was significantly mo activ than goup B. By using follow-up qustionnai mad up of 28 psychomtic scals, it has bn possibl to masu and collct data about cucial vaiabls of thotical modl, such as quality of collaboation, quality of dcision, usability and 19

21 Intoduction mutual undstanding. By pfoming on-tail T tst fo ach latnt constuct of qustionnai, it is mgd that uss pfomanc and Mutual Undstanding building of goup A a always significantly btt and gat than uss pfomanc and Mutual Undstanding of goup B. Fom ths analyss, w can conclud that th goup A, which usd th Dbat Dashboad, had btt pfomanc than th goup B that usd th plain vsion. As th two goups w not significantly diffnt (it was tstd though t Tst on an acadmic pfomanc indicato) w can conclud that th btt pfomanc dpnds on th povision of individualizd fdback. Futh analysis w pfomd to undstand th ol and th impact of ach fdback on common gound building and uss pfomancs, as wll as, th mdiation ol of mutual undstanding in impoving uss pfomancs. In paticula, in od to tst th poposd thotical modl, basd on a st of statmnts of colations btwn vaiabls, th Stuctual Equation Modlling was usd. In oth wods, by using SEM tchniqus, w aim at masuing th impact of visual fdback on MU and, in tun, th ffct of Mutual Undstanding on th th lvl of pfomancs, namly Quality of Collaboation (QofC), Quality of Dcision (QofD) and Usability (Usab), as wll as th impact of fdback on uss pfomancs. In this thid phas of data analysis, w usd only Goup A databass. Fom SEM analysis is mgd that ou hypothsis a suppotd. In paticula, it is possibl to claim that visual convsation fdback impact significantly on incas of mutual undstanding among onlin uss ov tim. Additionally, visual fdback impact significantly on lvl of uss pfomancs. By using SEM, it has bn possibl to vify th mdiation ol of Mutual Undstanding. In paticula, mdiation occus whn th caus-ffct lationship btwn a pdicto vaiabl (us of fdback) and a cition vaiabl (uss pfomancs) happns though an intvning vaiabl (Mutual undstanding). Mdiation lationships a of intst bcaus thy go byond simpl dscibing 20

22 Intoduction colations to xplain how pocss wok. Th hypothsizd mdiation ffcts w tstd using PLS. In od to pfom th mdiation analysis a simpl modl was catd that dpict a lationship btwn th indpndnt vaiabl (us of fdback) and th dpndnt vaiabl (uss pfomancs). Thn, a scond modl was catd that includ th mdiato vaiabl (Mutual Undstanding). Th sults dmonstat that th R 2 of th mdiatd modl was high than th simpl modl (Tabl I.4). Th mdiatd modl xplains mo of th vaianc of uss pfomancs than simpl modls. In nutshll, Mutual Undstanding mdiats ffctivly th intaction among fdback and uss pfomancs. Th sults a summaizd in Tabl I.4. Tabl I.4. R 2 compaison Path Simpl Modl R 2 Mdiatd Modl R2 (without MU) COMMUNITY --> MU --> USAB INTERACTION --> MU --> USAB 0,544 0,605 ABSORPTION --> MU --> USAB COMMUNITY --> MU --> QofC INTERACTION --> MU --> QofC 0,602 0,71 ABSORPTION --> MU --> QofC COMMUNITY --> MU --> QofD INTERACTION --> MU --> QofD ABSORPTION --> MU --> QofD 0,312 0,318 Implication This study aims at impoving agumntation mdiation capabilitis in od to xploit thi inhnt advantags and, at th sam tim, fosting f intaction among onlin uss. To addss this limitation, a Dbat Dashboad has bn implmntd. It is mad up of a st visual widgts abl to povid fdback about uss, intaction pocss and gnatd contnt. 21

23 Intoduction Though a fild tst, w tstd th fou of hypothss: i. th impact of visual fdback on Mutual Undstanding, ii. th ffct of Mutual Undstanding on th uss pfomancs, iv. th impact of fdback on uss pfomancs. iii. th hypothsizd mdiation ffcts of Mutual Undstanding btwn fdback and uss pfomancs. Th sults confim as supposd. Gnally, goup A show a significantly btt pfomancs (QofC, QofD, Usab) and MU than goup B. Additionally, it is mgd that visual fdback impacts on incasing of Mutual Undstanding and on uss pfomancs. Mutual Undstanding affcts uss pfomancs and mdiats (affct positivly) th lationship btwn fdback and pfomancs. Pactical and thotical contibutions has mgd fom this study. Fist, th findings fom th analysis of stuctual quation modl confim that visual, social and convsational fdback impact on mutual undstanding and on uss pfomancs. Scond, th sults indicats that mutual undstanding has a ol of mdiato and catalyst among visual fdback and uss pfomancs. Thid, in od to suppot fficint and ffctiv distibutd dcision making pocss, onlin collaboativ tools hav to b abl both to fost f intactions and to aid a mo stuctud knowldg oganization. Socialization/Intaction and knowldg oganization a two cucial condition fo suppoting dlibation and dcision making succssfully. Last, this study can b considd as an initial stp in th dvlopmnt of btt platfom abl to lvag th wisdom of diffnt distibutd individuals. Limitation Th fist limitation of this sach is that paticipants w dawn fom a singl acadmic cous. Th scond limitation of this sach is th siz of sampls. Indd, th basic ida is to xpand th sampls in od to btt masu th ffctivnss and fficincy of visual fdback in mdiat and suppot lag discussion goups. Th thid limitation of this study is that w did consid in ou analysis dmogaphic vaiabls that could b instd in SEM modls. Th fouth limitation of this disstation gads 22

24 Intoduction th us of Likt scal to collctd data and, in paticula, of clos-ndd qustions. Indd, this typ of qustions could lad uss to giv sponss not asond o fo satisfying th intviw, lad to inaccuat data analysis and sults. on of th main citicism is that Likt scal uss clos-ndd qustions. Th last limitations gad th st up of Dbat Dashboad; indd, not all individualizd fdback was bn implmntd bcaus of tchnical Coh fatus. Any analysis o studis has bn un about th dsign of visual widgts usd. Conclusion Th satisfactoy sults psnt an impotant ncouagmnt to xtnd this wok and to conduct futh xpimnts nlaging th sampl and involvd xpt communitis. A significant common gound building though agumntation psnts an impotant motivation to mak compaison tst with altnativ tools. Additionally, w aim at implmnting th oth individualizd fdback, in od to hav a mo complt and dtaild ida about th ol of diffnt fdback. Anoth impotant futu stp could b th impovmnt of th dsign of cunt visual widgts in od to btt suppot us s gounding pocss. 23

25 Chapt 1 Wb 2.0: It is not a fad, but th nw nomal 1.1 Intoduction Th ya 1989 witnssd on of th majo and most impotant vnts fo human histoy: th invntion of th Wold Wid Wb by Tim Bns-L. Dispsd comput communicating though packt-switching ntwok allowd scintific sachs of th CERN to communicat and to b linkd. This invntion was tansfoming human communication and poduction of knowldg [Hanad, 1991]. Th advnt of Wold Wid Wb, lat mad it mo accssibl by Mosaic bows and its succssos, poducd a hyplinkd systm of documnts though which to psnt visual infomation as wll as to connct uss to a powful ang of knowldg. Ths tchnological innovations hav tansfomd th comput into a volutionay nw mdium fo intpsonal, goup and mass communication and hav intoducd uss to a dazzling aay of nw communicativ capabilitis. Th Wb is changing th way th wold is doing things fficintly. 1.2 A social volution: th Wb 2.0 On th 25 th of Dcmb 2006, th TIME magazin assignd th titl of th Man of th Ya not to a paticula psonality, but to th Intnt us. Th choic of TIME Magazin to piz this gass-oot phnomnon is a good indication of how intnsivly this tnd has pmatd ou cultu. Indd, th aticl mphasizd how th phnomnon, commonly tmd as Wb 2.0, is affcting th way individuals communicat, collaboat, lan, nttainmnt thmslvs, mak dcisions, cat and sha infomation. 24

26 Chapt 1 It's a stoy about community and collaboation on a scal nv sn bfo. It's about th cosmic compndium of knowldg Wikipdia and th million-channl popl's ntwok YouTub and th onlin mtopolis MySpac. It's about th many wsting pow fom th fw and hlping on anoth fo nothing and how that will not only chang th wold, but also chang th way th wold changs [Gossman, TIME Magazin U.S]. Th tm Wb 2.0 was poposd by Tim O Rilly [2005] to indicat cutting-dg wb dvlopmnts. Actually, though th tm suggsts a nw vsion of Wb tchnology, it fs instad to changs in th communicativ uss of th undlying platfom. As Bns-L affims, Wb 2.0 offs nothing adically nw sinc th potntial fo a high lvl of paticipation and collaboation has always bn inhnt in th wb fom its outst [Clak, 2006; Laningham, 2006]. Th cucial changs w ctain tchnical impovmnts, which hav allowd uss with littl tchnical skills and knowldg to constuct and sha thi own digital poducts though th nw platfom. Indd, th Wb 2.0 applications a considd simpl, at last fom uss pspctivs. Thus, th lowing of tchnical bais sms to b th main ason of Wb 2.0 hug paticipation and of its widspad adoption. In this wok, th adoptd dfinition of Wb 2.0 is: Wb 2.0 is th ntwok as platfom, spanning all connctd dvics; Wb 2.0 applications a thos that mak visibl th most of th intinsic advantag of ths platfoms, that is dliving softwa as continually updat svic that gts btt th mo popl us it, consuming and mixing data fom multipl soucs, including individual uss, whil thy povid thi own data and svics in a fom that allows mixing by oths, cating ntwok ffcts though an achitctu of paticipation and going byond th pag mtapho of Wb 1.0 to dliv ich us xpinc [O Rilly, 2005] 25

27 Chapt 1 Phaps, th most complling aspcts of Wb 2.0 platfom, which diffntiat it fom th fist gnation of th Wb, a th ol of uss and th nw achitctu of paticipation. In Wb 1.0, th contnt catos w fw and th vast majoity of uss simply acting as consums of ths matials; instad in Wb 2.0 any paticipant could cat contnt and numous tchnological aids hav bn implmntd to maximiz th potntial of this phnomnon. Whil th ali Wb allowd popl to publish contnt, which oftn ndd up in isolatd infomation silos, th nw Wb s achitctu allows mo intactiv foms of publishing of any kind of digital contnt (both txtual and multimdia), paticipation, and ntwoking though vy common collaboativ tchnologis, such as blogs, wikis, foums, social ntwok sits. This achitctu is basd on softwa, wh uss gnatd contnt and its oganization appas spontanously though th action of millions of uss. Additionally, th systm is dsignd to tak uss intactions and utiliz thm to impov itslf. Bit Tont, fo instanc, dmonstats this ky Wb 2.0 pincipl; that is th ntwok of download povids both th bandwidth and data to oth uss so that th mo popl paticipat, th mo soucs a availabl to th oth uss on th ntwok. Us is a vital facto fo all catgois of Wb 2.0 applications, not only as a consum, but mainly as a contnt contibuto. Indd, popl play an activ ol in gnating and pooling knowldg that thy sha ach oth, which is subsquntly mixd, -distibutd and -consumd by oths [Haison and Bathl, 2009]. Th Wb is pincipally about paticipating ath than about passivly civing infomation [Tapscott and William, 2006] and it is inhntly social so that uss a cntal to both contnt and fom of all matial and soucs [Hady, 2007]. This fatu maks Wb 2.0 a liv mdium, which is constantly updatd and nichd by uss with nw digital poducts, infomation and knowldg. On th Intnt diffnt collaboativ tchnologis xist. In th following, a basic classification basd on application typs dividd into ight catgois is poposd: Blogs: th most known and fast-gowing catgoy of Wb 2.0 applications. Thy a onlin jounal wh uss can publish contnt. Oftn, blogs a combind with podcasts, that is digital audio o vido. On of th most famous blog is Slash.dot [ 26

28 Chapt 1 Wikis: is a wbpag o a st of wbpags that can b asily ditd by anyon who is allowd accss. Wikis a widly cognizd as tools abl to suppot collaboativ wok. Th most famous wiki is Wikipdia, th lagst ncyclopadia of th wold ( Social Ntwoks: allow uss to build a sot of psonal wbsits accssibl to oth uss fo xchang of psonal infomation and contnt and fo communications. Thy can b pofssional o social ntwoking sits that facilitat mt popl. Thy a th most popula wb-basd applications and popl spnd th most pat of thi Intnt total tim visiting thm. Exampls a: Contnt Communitis: allow uss to oganiz and sha paticula typ of contnt. Exampls a applications of vido shaing (.g. o photo shaing (.g. Foums/bullt boads: lt uss to sha idas and infomation usually aound spcific intsts. Data mash-ups: pull togth data fom diffnt soucs to cat a nw svic. Th main chaactistics of th mash-ups a combination, visualization, and agggation. It is impotant to mak xisting data mo usful fo psonal and pofssional us. RSS and Syndication: is a family of fomats which pmit uss to fully customis th wb contnt that thy wish to accss. Infomation fom th Wbsit is collctd within a fd and pipd to us in a pocss known as syndication. Tagging and social bookmaking: a tag is a kywod that is addd to a digital objct (photo, vido, wbsits) to dscib it. On of th fist lag-scal applications of tagging was sn in dl.icio.us wbsit, which launchd th social bookmaking phnomnon. Social bookmaking allows uss to cat lists of 27

29 Chapt 1 favouit, to sto thm cntally and to sha thm with oth uss of th systms. Wb 2.0 is pvasiv and it is adically modifying th way popl communicat, find and sha infomation and collaboat to cat collctiv outputs. Bing connctd to th wold aound us has nv bn mo asy and accssibl than it is today. Th ubiquity of th Wb 2.0 has volutionizd how w intact with ach oth. Fom th advnt of mail, bulltin boad systms, to cunt social ntwoking sits, tchnology has bn incasingly intgatd with communication to bcom a pominnt focus of th nw digital ag. It has ld up a social volution that is taking ov th Intnt and nting into ou al livs. Indd, Wb 2.0 tchnologis a abl to affct individual s bhavious and thi dcisions and choics. At th bginning, many sachs and pactitions claimd that Wb 2.0 would hav bn only a tnd that would b gon away in fw tim. But it is still h and it is claly th nw nomal. In od to btt undstand how Wb 2.0 applications a th nw nomal and, in paticula, how wb 2.0 tchnologis hav dply volutionizd ou daily lif, in th following som wb-basd stois, poving thi intns impact, will b psntd. Ths xampls mphasiz th way Wb 2.0 tchnologis hav changd how w communicat, intact and cat collctiv output. On of th most famous xampls of collaboativ knowldg building systms is Wikipdia with mo than 400 millions of uniqu visito monthly. It is an onlin ncyclopadia in which any ad can also b an dito, with thi changs immdiatly visibl to subsqunt visitos. Its slogan is Anyon Can Edit vn ungistd popl can contibut to th constuction of knowldg bas. Millions of anonymous and voluntay uss cat and updat daily aticl pags of lagst ncyclopadia of th wold. This massiv paticipation (th a mo than activ contibutos) has sultd in a highly popula sit with a lag amount of contnt tanslatd in 270 diffnt languags and with nintn millions of aticls (almost on million of aticl in Italian Wikipdia alon). Though this succssful stoy, I would lik to mphasiz how Wb 2.0 collaboativ tchnologis has mad possibl to thousands of individuals to collaboat to th 28

30 Chapt 1 cation of th lagst ncyclopadia of th wold. Indd, English Wikipdia vsion counts aound 4 millions of aticls and 609 millions of wods, xcding Bitannica Encyclopadia which in Dcmb of 2004 countd 120,000 aticls and 77 million wods. Wb-basd tchnologis hav mad possibl such lvl of paticipation and collaboation, which was unimaginabl fw yas ago. In 2009, Twitt was an fficint mans to supassing th cnsu that Ianian Govnmnt applid duing th movmnt against th lctions sults. Twitt was launchd in 2006 and allows twitts to post what thy want in a mssag mad up of not mo than 140 chaacts. Onc that th mssag is snt, all subscibs who follow him/h civ updats. Bcaus of Ianian cnsoship on infomation flow though th mdia fom th county, suppots of th Mi- Hossin Mousavi potstd against th sults of th lctions that w in favou of Ahmdinjad by using Twitt. What maks Twitt suitabl tools fo a mass potst was both its as of us and vy had fo any cntal authoity to contol. Additionally, by using hash tag uss can tag thi posts facilitating thi goupd and sach fo topic, as wll as thi tansmission by oth uss. Twitt has boadcastd what had happnd in Ian. Claly, Twitt did not stat th potsts in Ian, no did it mak thm possibl. But suly it has ncouagd th potsts, infocd thi conviction that thy a not alon but populations outsid Ian w ngagd and followd thi situation in a way that was nv possibl bfo [souc: Gossman, 2009, TIME Magazin]. Hundds of thousands of activists contibutd to Baack Obama s lctoal campaign playing a significant ol in influncing th lctoal outcom and now pusuing opn-lobbying on th Psidntial agnda though th Intnt. Many consid that Baack Obama is th fist "Social Mdia" Psidnt. A nw ag of digital dmocacy wh popl play an activ ol in govnmnt now and ov tim is bginning. In Jun 2011, Th Whit Hous publishd a blog post that indicats that th Whit Hous is indd listning in social mdia. Though wbbasd collaboativ tchnologis govnmnt and lads could ncouag fans and follows to contibut to any campaign o mission. In doing so, Wb

31 Chapt 1 tchnologis volv fom infomation channls to ngagd communitis with th ability to affct popl s bhavious. Though Intnt-basd application th futu of politics isn't catd, it's co-catd [souc: Sois, FastCompany]. Facbook was launchd in Fbuay 2004 and th Wb sit's mmbship was initially limitd Havad studnts. Mo than half of studnt collg signd up within th fist month. Today, Facbook counts mo than 800 millions of uss aound th wold. It is th siz of th nti Intnt in It is th top onlin dstination in a lot of countis aound th wold (.g. USA, UK, Italy, Bazil, Gmany, Fanc), bcoming synonymous with Wb 2.0 us [Nilsn pot, 2011]. Popl us Facbook vyday to kp up with finds, upload an unlimitd numb of photos, sha links and vidos, and lan mo about th popl thy mt. Uss a xpincing a nw way to stay constantly in contact with oths. In gnal, by using social ntwoking sits, onlin uss continually updat thi status and sha thi momnt-by-momnt activitis. W a living in a socity, wh w sha almost vything: what w at, wh w shop, what w a watching on tlvision. Slowly but suly vything is losing its status of "sacd", sct, with shaing bcoming th nom. Social scintists calld this incssant onlin contact ambint awanss. In som way, though this constant updating, it is lik bing physically na somon and picking up on his mood though things thy do. By agggating all th updats, snippts coalsc into a supisingly sophisticatd potait of ou finds and family mmbs livs. Bing tightly connctd to th wold aound us has nv bn simpl than it is at th momnt. Intnt mad possibl to ach popl with mly a click of button, but social ntwoking sits hav mad th wold small! Ths a only fw xampls about how Wb 2.0 tchnologis hav povidd uss with nw foms and spacs fo social intactions, community fomation and social and pofssional ntwok cation and maintnanc. As mgd, ths nw applications and svics hav had an nomous impact on how infomation is pocssd, publishd 30

32 Chapt 1 and consumd by uss, as wll as thy hav maningfully modifid th way in which uss intact ach oth and with th tools. Finally, all indications point to th fact that Wb 2.0 applications and svics a h to stay. It is not a fad, but th nw convntional ways to intact, communicat and collaboat on a scal nv sn bfo. 1.3 Wb 2.0 in oganizations Claly, such social volution has had a vy pofound impact also on businss wold. Th gat succss of nw Wb 2.0 applications and svics has ncouagd oganizations to wi th way thy think about and un thi businsss. Sinc its advnt, th scond gnation of th Wb has nabld nw ways fo companis to connct th intnal ffot of mploys, build lationship with supplis and stakholds, ach thi customs and pomot thi band. Incasingly, oganizations a xploing nw mods to lvag opn and diffusion collaboation as a nw comptitiv appoach. Applications lik blogs, wikis, pdiction makt, mash-ups and social ntwoks hav apidly bn adopting by th ntpiss. Tapscott and Williams [2006] claim that Wb 2.0 has poplld th businss wold in a nw a, on of th Mass Collaboation. Indd, th opnnss, scalability, slfoganization, loos-coodination and adquat, low cost collaboativ tools hav allowd lag goups of uss to achiv outstanding sults in knowldg cation, xchang and shaing, such that thy a bcom a souc of inspiation fo both oganizational sachs and fims [Gloo, 2006; Raymond, 2001; Tapscott and Williams, 2006, von Hippl, 2001; von Kogh and von Hippl, 2006]. Nw businss appoachs a alady dvlopd and stablishd, which impact on th way oganizations manag diffnt oganizational pocsss. In paticula, oganizations a using ths nw collaboativ tchnologis fo fosting innovation, suppoting makting and knowldg managmnt statgis, aiding poblm solving and dcision making pocsss. Mass collaboation is ncouaging customs, mploys, supplis 31

33 Chapt 1 patns and comptitos to sha knowldg and idas. This is adically modifying th taditionally accptd businss modls. Vtically oganizd hiachis and closd businss systms a giving way to flat oganizations and opn platfom. Collaboation is nothing nw, but what has changd sinc th advnt of Wb 2.0 tools has bn its badth and its dpth. In 2006, Andw McAf, a Havad Businss School, suggstd th tm Entpis 2.0 to dscib and indicat thos platfoms that companis can buy o build to mak visibl th pactics and outputs of thi knowldg woks. Wb 2.0 platfoms a poviding ntpiss with nw modls and tools fo sustaining and impoving collaboation and co-cation, accumulation and shaing of knowldg. Ths collaboativ tchnologis a considd th nw, ight tools fo knowldg wok. Wikis, blogs, goup-mssaging softwa and th lik can mak an oganization intant into a constantly changing stuctu built by distibutd, autonomous ps [McAf, 2006]. Not only woks can collct a hug amount of knowldg and slf-idntify th contnts that a most lvant fo thi activity but thy a also abl to st up th stuctus and th collaboativ pocsss that a adquat to thi nds. In this way, vitual collaboatos co-dsign collaboativ platfoms that flct th way wok ally gts don [McAf, 2006]. Oth impotant aspcts of Entpis 2.0 tchnologis a thi adaptability and flxibility to th diffnt wok applications; thy do not impos on uss any pconcivd notions about how to wok, how stuctud and catgoizd th gnatd contnt, but thy lav that ths aspcts of knowldg wok mg spontanously. Dfinitly, th wid adoption of wb-basd tchnologis divs also fom th failu of taditional Knowldg Managmnt tools which chaactiz to b too igid, fomal and stuctud. In fact, in his studis, Davnpot [2005] found that all knowldg woks suvyd a not satisfid and happy to us th platfoms and channls availabl to thm, such as Intant, copoat Wb sit, Infomation potals, - mail and pson-to-pson instant mssaging. Additionally, a scond mo cucial poblm of taditional Knowldg Managmnt tools flt fom woks was that such tchnologis did not a good job of captuing thi knowldg; indd thy do not lt thm to asily acqui, sha and -us oganizational knowldg. On th contay, th 32

34 Chapt 1 nw wb-basd applications lt woks an infomal, lss stuctud and mo spontanous knowldg-basd wok of oganizations. Oth two impotant advantags diving fom th us of Wb 2.0 tchnologis a: ltting tam mmbs, gogaphically dispsd, to collaboat [Haydn, 2004], captu, xchang and sha knowldg in asi, chap and mo pvasiv way than taditional Knowldg Managmnt systms [Duffy, 2000], without any tim and spac constaints. pmitting oganization to fog clos lationships with customs, supplis, businss patns and stakholds, which a ssntial fo succss and suvival in incasingly tubulnt and highly comptitiv nvionmnt [Baum, Calabs and Silvman, 2000; Dy and Noboka, 2000;]. In gnal, by collaboating, oganizations lan fom oths, sha soucs, isks and costs, accss to nw and divs knowldg, know-how, comptncis and pspctivs and dvlop nw oppotunitis. Nowadays, th us of Wb 2.0 tchnologis in th oganizations is a nw ality. Indd, as mgd fom McKinsy suvy on Businss tchnology [2011], on-thid of spondnts (3.249 xcutivs acoss a ang of gions, industis and functional aas) uss Wb 2.0 tchnologis in thi oganizations. Th sha of companis that mploys wb-basd tchnologis continus to gow, in paticula with gad to utilization of social ntwoking (40%) and blogs (38%). Fom McKinsy suvy sults mgs that th main masuabl bnfits diving fom th us of Wb 2.0 a th incas spd of accss to both intnal and xtnal knowldg and xptis (spctivly 77% and 57%), th duction of communication costs (60%), th incasing of mploys, customs and patns satisfaction (spctivly 41%, 50%, 45%), as wll as th incasing of ffctivnss of makting politics (63%) and th duction of opational and makting cost (spctivly 40% and 45%) and of tim to makt of poducts/svics (29%). 33

35 Chapt 1 Blogs, wikis, foums, social ntwoks and th lik lt oganizations to captu th pow of paticipation and collaboation. With th so-calld Entpis 2.0 tchnologis citical knowldg no long languishs in oganizational silos, but it bcom a dynamic asst that gows oganically as anyon gab it, add to it and us it fo diffnt aims. Incasingly, mploys a using ths nw wb-basd applications to collaboat and fom ad hoc communitis which span oganizational boundais. Closd, hiachical wokplacs, chaactizd by tight mploymnt lationships a bing tansfomd into slf-oganizd, distibutd and collaboativ human capital ntwok, that daw knowldg fom both within and outsid th fims. By hanssing syngis among uss, ths tools may hlp oganizations compt globally and ach nomous comptitiv advantag. Claly, Intnt and onlin collaboativ tools may also contibut to fost innovation as collaboativ output among globally distibutd collaboatos [Tapscott and Williams, 2006]. Intnt had opnd up accss to talnt makt thoughout th wold. Numous companis lik IBM and Eli Lilly hav bgun to xpimnt with th nw concpt of opn innovation, lvaging on anoth s innovation assts (vn comptitos), such as poducts, intllctual popty and popl [Huston and Sakkab, 2006]. Th shift to Opn Innovation modls has bn cognizd as a majo chang in th way companis and oth actos involvd in th innovation valu chain cat and manag innovation. Opn Innovation is dfind as th us of puposiv inflows and outflows of knowldg to acclat intnal innovation and to xpand th makt fo th xtnal us of innovation spctivly [Chsbough, 2003, 2006]. Put diffntly, th cntal ida of Opn Innovation is that in a wold consisting of widly distibutd knowldg, oganizations cannot ly ntily on thi own sach activitis and skills, but thy should xploit xtnal knowldg and comptncis and find ways to pofit fom intnal invntions o idas that thy cannot o do not want to xploit intnally. In th Opn Innovation paadigm, makt-basd mchanisms to captu xtnal knowldg o to valoiz intnal idas such as acquisition of Intllctual popty ights, spin-offs and nw vntu cation a mixd with non-makt valu cation mchanisms basd on collaboation among companis, R&D cnts, indpndnt poblm solvs and vn final uss [Bnkl, 2011; von Hippl, 2005]. Collaboation 34

36 Chapt 1 bings many bnfits to mmbs of innovativ communitis including shaing of R&D xpnss and isk and f accss to divs know-how, idas and skills dvlopd by communitis of pactics. On th intnt, sval applications abl to suppot Opn Innovation xist. On of th most famous is InnoCntiv s Challng Platfom ( It is an opn innovation company that nabls oganizations to solv thi unsolvd R&D poblms by conncting thm to divs and numous soucs of innovation including mploys, customs, patns, comptitos and anyon is intstd. It givs cash awads fo th bst solutions to solvs who mt th challng citia. In oth wods, it is abl to match dmand and off of innovation solutions by using th wb-basd platfom. InnoCntiv has postd mo than 1,300 challngs to its global solv community. InnoCntiv cuntly nabls challngs in a wid vaity of disciplins, including businss and ntpnuship, chmisty, comput/infomation tchnology, ngining and dsign, food and agicultu, lif scincs, math and statistics, and physical scincs. InnoCntiv s solv community now consists of naly a quatmillion cativ and talntd individuals fom mo than 200 countis, which collaboat to find th ight solution fo complx poblms. Additionally, oganizations a, v mo, dvloping wbsits and oganiz vnts to suppot an opn and collaboativ innovation appoach, involving mploys, customs, stakholds and anyon wants to collaboat to th alization and implmntation of innovations. Sinc 2011, fo instanc, IBM oganizs th IBM Innovation Jam vnt. It is an onlin bainstoming sssion that involvs IBM mploys, customs, patns, consultants and stakholds fo fw days to pomot innovation. Th basic ida is to bing diffnt minds and diffnt pspctivs togth to discov nw solutions to long-standing poblms. IBM's Jams and oth Wb 2.0 collaboativ mdiums a opning up tmndous possibilitis fo opn and collaboativ innovation, that is a nw ways of woking acoss industis, disciplins, and national bods. 35

37 Chapt 1 Anoth impotant initiativ fo suppoting collaboativ innovation pocsss was poposd by Dll in 2007, namly Dll IdaStom. Th latt is a wbsit allows oganization "to gaug which idas a most impotant and most lvant to" th public. It is an onlin foum wh onlin uss can suggst nw businss idas, vot fo thi favouit submissions and intact with Dll. Th sit is so popula that oth companis (such as Canonical, an opn souc advocat) a copying th concpt, such as Stabucks, RadioShack, Canonical Ltd. By using ths wbsits, oganizations, not only, can involv customs and oths stakholds in thi innovation pocsss, but can also gath impotant infomation about custom nds. In this way, oganizations, indd, a abl to cat stong lationship with thi clints, bcaus thy fl listnd and pat of th company. As alady mntion, Wb 2.0 applications hav psntd businsss with nw challngs, but also nw oppotunitis fo gtting and staying in touch with thi customs, laning about thi nds, xploiting thi opinions and idas, as wll as intacting with thm in a mo dict and psonalizd way. This nw kind of Intntbasd tools has shapd and is still dtmining a nw class of consums. Indd, th claim that th custom is th king has always soundd hollow, but now th digital maktplac has mad it tu. Wb 2.0 has affctd th pow stuctu in th makt plac, causing a substantial migation of makt pow fom poducs and slls towads customs. This happns bcaus mainly nowadays customs can accss to a pviously unknown quantity of infomation and knowldg. Indd, clints dcisions and opinions about th poducts and svics a not basd xclusivly on infomation maks availabl by company though taditional mass mdia o its wbsit, but thy a incasingly basd on inputs povidd by oths uss o patis not contolld by poducs (p viws, fals, blogs, foums tc.). In paticula, oganizations a vn mo xploiting th pow of social mdia to build and dvlop mo intactiv and dict lationships ov tim with thi customs. As social mdia is bcoming th fist channl though which customs lan about a band, many companis a, of cous, dvloping a psnc within custom ntwoks such as Facbook, Twitt, and YouTub. By using Social Mdia, companis hav found a nw way to b tightly connctd, xplo and xploit thi idas and nds and off mo and mo 36

38 Chapt 1 psonalizd poducts and/o svics. A nw wav of digital advtising svics and poducts off bands th ability to go byond thi xisting communitis. Indd, as mgd fom Nilsn findings [2011] 60% of popl who us th o mo digital mans of sach fo poduct puchass land about a spcific band o tail fom a social ntwoking sit. And, 48% of ths consums spondd to a tail's off postd on Facbook o Twitt. Thus, nw channls and mdia hav bn dvlopd and oganizations hav to quickly lan to xploit thm as makting tools if thy want to compt and suviv. Incasingly, consums a co-innovating and co-poducing th poducts that thy consum as wll. Th gap btwn poducs and consums is bluing. A nw kind of custom is bon: th posums. It indicat incasing ngagmnt of consums into poduction pocsss. Tapscott and Williams [2006] claimd that th most activ uss fom thi own onlin communitis, wh thy sha infomation about poducts, collaboat on customizd pojct and povid tips and suggstions. Thfo, comptitiv and smat companis will bing customs into thi businss wbs and giv thm a lad ol in dvloping nw poducts and svics. This mans that oganizations Wb 2.0 has tansfomd and is still tansfoming how businsss a managd. Th last common multipl of ths stois is th incasing involvmnt of mploys, customs, supplis, patns and stakholds in vaious and diffnt oganizational pocsss though wb-basd tchnologis. Th basic ida is that Wb-basd tchnologis allow hanssing collctiv output, not only of th nti wokfoc, but of th whol ntwok of xtnal patis on a scal nv sn bfo. In nutshll, collctiv intllignc can b dfind as th ability of goups to ach outstanding pfomancs than ach of its mmbs can [Hylighn, 1999]. Th lsson is: oganizations that a abl to ffctivly adopt and xploit Wb 2.0 tchnologis will giv thmslvs an nomous comptitiv advantags and lt thmslvs to wok globally. Companis has to opn thmslvs up to idas fom outsid thi boundais. Thy hav to, not only to think globally, but thy hav to act globally to ffctivly tap a global talnt pool. 37

39 Chapt 1 Intnt-basd tchnologis can suppot diffnt oganizational pocsss, but in this wok I focus on onlin distibutd dlibation and dcision making pocsss. In paticula, in th nxt Chapt, I will xplain how Wb 2.0 tools, by hanssing Collctiv Intllignc, can fost onlin distibutd dlibation pocss. Moov, I will put mphasis on diffnt chaactistics of cunt wb-basd tchnologis xplaining thi stngthns and waknsss with gads thi ability to suppot th mntiond oganizational pocsss. 38

40 Chapt 2 Wb-nabld collctiv intllignc fo suppoting distibutd dlibation pocss 2.1 Intoduction In th pvious Chapt, I discuss on how Wb 2.0 tchnologis hav dply pmatd ou al livs, adically modifying th way popl intact, communicat, sach and xchang knowldg and cat collaboativly collctiv outputs. In this Chapt, I focus on th pow of Wb 2.0 to hanss Collctiv Intllignc [O Rilly, 2005; Malon and Klin, 2007; Malon t al., 2010]. Wb 2.0 tools, by ltting wid amount of knowldgabl and intstd individuals to fly communicat, intact and gnat contnts in slf-oganizd and loosly coodinatd way, has apidly catd nw oppotunitis and foms of Collctiv Intllignc [O Rilly, 2005; Malon t al., 2010]. Collctiv Intllignc is basd on th ida that lag goups of individuals a makably intllignt and thy a abl to com up with dcisions o solutions to a poblm in a btt way than ach of its mmbs can [Hylighn, 1999; Lvy, 1997]. Evn whn most pat of popl within a goup a not spcially will-infomd o ational, th goup may still ach a collctivly wis dcision. This is a vy supising, sinc that human bings a not abl to mak optimal dcisions bcaus of thi boundd ationality [Simon, 1972] Howv, und th ight conditions, whn ou impfct judgmnts agggat, ou collctiv intllignc could b oftn xcllnt. Although Collctiv Intllignc is an ancint phnomnon, nw wb-basd collaboativ tchnologis a allowing vast amount of popl ov th wold to wok togth in a syngic and cumulativ ways that w nv bfo possibl in th histoy of humanity. Exampls of nw flouishing foms on Intnt a: Wikipdia (millions of volunts aound th wold paticipat in witing th wold's lagst ncyclopadia), Googl (it uss th knowldg millions of 39

41 Chapt 2 popl hav stod in th Wold Wid Wb to povid makably usful answs to uss' qustions), Linux (hundds and hundds of individuals constantly us, chang and impov its dsign though th availability of its souc cod). Ths succssful stois in tun hav inducd many sachs and pactitions to think that it is possibl to hanss this nw foms of Collctiv Intllignt ov Intnt fo a numb of diffnt oganizational tasks lik collctiv Knowldg Managmnt [Zttsu and Kiyoki, 2006], collctiv pdiction [Sunstin, 2006], collctiv dlibation [Klin, Cioffi and Malon, 2007], collctiv poblm solving [Iandoli t al., 2009]. This sach focuss on collctiv dlibation pocsss suppotd by Wb 2.0 tools abl to nabl Collctiv Intllignc. Th basic ida is to xploit Collctiv Intllignc of Wb uss as basis fo suppoting ffctiv dlibation pocsss. Moov, stngthns and waknsss of cunt Intnt-basd tchnologis will b assssd spct thi ability to suppot succssful dlibation and dcision making pocsss. 2.2 Using collctiv intllignc to mak btt dcision Th human bain is an incdibl instumnt that has volvd ov thousands of yas to allow us to suviv and posp in many diffnt conditions. Notwithstanding, ou volvd dcision huistics hav ctain limitations, which hav bn xtnsivly studid ov th last fw dcads, in paticula by sachs in th fild of bhavioual conomics [Simon, 1972; 1982; 1991]. Th way in which ou bains a biasd may not b wll suitd to suppot dlibation pocsss in cunt conomic nvionmnts chaactizd by tubulnc and hyp-comptitivnss. Fast-pacd wold of businss quis oganizations incasing shot sponss tim, mo accuat dcisions and a gat xploation of potntial oppotunitis. In od to fac this nvionmntal complxity, in th last dcads, many oganizational dcisions migatd fom individual to distibutd dcisions basd on th contibutions offd by lag, divs goups of individuals within a fim o vn fom xtnal fims [Shim t al. 2002]. Th good nws 40

42 Chapt 2 is that, thanks to Wb 2.0 collaboativ tchnologis, oganizations can now daw togth wid amount of divs knowldg soucs and comptnt individuals on a gat scal than v bfo. Claly, th ol of wb-basd collaboativ tools is not to plac mankind, but to pomot th constuctions of intllignt communitis in which ou social and cognitiv potntial can b mutually dvlopd and nhancd [Lvy, 1997]. Th incasing us of wikis, pdiction makts, social ntwoks, foums and th lik to suppot collaboativ and distibutd dlibation and dcision making pocsss constituts an impotant oganizational paadigm shift. Indd, Intnt sms to off th ight and ffctiv solution to suppot fficintly and ffctivly dlibation pocsss. Indd, th advnt of Wb 2.0 has givn is to many nw and nichd applications of xisting tchnologis abl to pomot mo consistnt and wllsuppotd dcision making by nabling a lag numb of uss to paticipat and, thus, pomoting a boad xploation of th solution spac. In paticula, nw applications hav mad fasibl fo oganizations to put togth knowldgabl and intstd individuals gogaphically dispsd with divs skills in a chap and fficint way [Camton, 2001], without tim and spac constaints. Cunt wb basd tools which could b usd to fost a pvasiv paticipation a innumabl. Although th most common wb-basd tools (blogs, wikis, social ntwoks) a noticably basic compad to goup dcision suppot systms, thy allow lag goups of uss to achiv outstanding sults in knowldg shaing and accumulation. Numous sachs hav povd that thy fost, by ducing cost of paticipation, wid voluntay contibutions which in tun can lad to makably powful mgnt phnomna, that includ: Ida syngy: th ability fo uss to sha thi cations can nabl a syngistic xplosion of cativity, sinc popl oftn dvlop nw idas by foming novl combinations and xtnsions of idas that hav bn gnatd by oths [Tapscott and Williams, 2006]. 41

43 Chapt 2 Th long tail: social computing systms nabl accss to a much gat divsity of idas and allow to small voic to hav a significant impact [Sunstin, 2006]. Many ys: social computing ffot can poduc makably high-quality sults by vitu of th fact th a multipl indpndnt vifications [Linus law] [Raymond, 2001; Sunstin, 2006]. Collctiv Intllignc: lag goups of indpndnt, motivatd and comptnt individuals can collctivly mak btt judgmnts than thos poduc by its smatst mmb [Suowicki, 2005]. In accodanc to this, it is now possibl to suppot th syngistic and cumulativ channlling of th vast human and tchnical soucs now availabl on Intnt and to xploit it fo nabling collctiv appoachs fo making wll-suppotd and accuat dcisions. Claly, th concpt of Collctiv Intllignt is not so nw, but it is always xistd Indd, fo instanc, familis, companis and countis a all goups of individual doing things that at last somtims a intllignt. Bhivs and ant colonis a xampls of goups of inscts doing things lik finding food soucs that a intllignt. Th only al diffnc is that, nowadays, it is possibl to xploit th potntialitis of ths tchnologis to hanss th Collctiv Intllignc on a vy lag scal that was compltly impossibl fw yas ago. Th ida bhind Collctiv Intllignc is that a lag goup of individuals can collctivly mak btt judgmnts than thos poducd by th singl individuals that compos it. Oftn goup s pfomancs xcd also th ons achd by xpts, as thi collctiv judgmnt cancls out th biass and gaps of ach mmb. So, intllignt bhaviou mg fom th syngy of individuals in a goup [Hylighn, 1999]. Th pow of Collctiv Intllignc fo suppoting dlibation pocsss dpnd also on th ability to xploit th divsity. Divsity is vy impotant bcaus it nsus that th goup has a wid ang of infomation. Basically, if a goup consists of naly 42

44 Chapt 2 idntical popl, it is unlik to b wis, bcaus th goup will not know mo than individuals of whom it is composd. Raymond [2001] statd givn nough yballs, all bugs a shallow ; this is th manta of Opn souc movmnts and it indicats th gat ability of lag goups to find and fix vntually bugs. Lag goups a abl to mak btt dcisions bcaus th a divs point of viws, comptncs and knowldg which a cucial to btt undstanding and analysis of th poblms, as wll as a gat xploation of solution spac. Anoth impotant advantags diving fom th utilization of lag goups fo suppoting dlibation and dcision making pocsss is that, in this way, it is possibl to involv popl that woks in diffnt filds. Oftn, th a popl out th who can hlp oganizations to solv poblms, and, moov thos individuals a not ncssaily wh somon might xpct thm to b. Many tims poblm solutions com fom industis, filds o aa which a not vn thinkabl. Divs comptncis and xptis can contibut to a btt undstanding of th poblm [Plld t al., 1999], as wll as can allow a ich and mo complt poblm analysis and valuation [Pag, 2008] and mitigat slf-sving bias and blif psvanc [Bonabau, 2009]. Th impotanc of divsity was povd by Pag [2008] though a st of xpimnts. Th sult showd that th divsity is a cucial condition to mak a goup mo abl to solv a poblm and that only th intllignc is not nough bcaus it dos not nsu that th poblm will b sn fom diffnt viws as wll. Adding lss xpt popl, but with diffnt comptncis, th pfomanc will b btt than on achd by a goup of savvy individuals. Accoding to Pag, this happns bcaus intllignt popl a simila and thy know appoximatly th sam things. Too homognous goups hav mo difficultis to lan and updat thi knowldg, bcaus thi mmbs bing too littl nw infomation. If nw mmbs a intoducd, vn if lss xpt and capabl, gnally th goup bcoms smat and should incas th poductivity [Plld t al., 1999; Vnnix, 1996]. Howv th sam divsity may hamp collaboation as positd by th Absoptiv capacity concpt poposd by Cohn and Lvinthal [1990]. Thfo, not all collaboations hav bn succssful [Baon, 2003], bcaus th a situations wh th divsity of knowldg can hind ffctivnss o som goups may ovmphasiz cohsion and nglct citical thinking, hamping a pop analysis of 43

45 Chapt 2 altnativ solutions [Janis, 1982]. Th lsson h is that oganizations that mak us of collctiv appoach to suppot dcision making pocsss hav to find th ight balanc btwn divsity and xptis. Th fou majo causs of failu of goups involvd in dcision making pocss a [Sunstin, 2006]: Hiddn pofils: goups may not b abl to ach th ncssay outcom bcaus som goup mmbs do not licit all th lvant infomation hld bcaus of th psnc of social pssus (low infomation disclosu). Indd, in all goups involvd in dcision making pocsss th a two kinds of infomation, that is common infomation availabl to all paticipants and pivat infomation hld by a singl mmb. Whn a hiddn pofil is psnt only th common infomation will b usd and it will suppot a sub-optimal altnativ. On th contay, if th ach goup mmb disclosd both common and pivat infomation and valuatd it in an unbiasd way, it would pf a diffnt, supio altnativ. On of th lading causs is that goups dispopotionatly discuss common infomation as opposd to th goup mmbs pivat infomation [Stass and Stwat, 1992]. Oth factos includ infomation ovload (too much infomation fo individuals to mmb) and biasd call that favous th altnativ that ach mmb s p-discussion infomation indicats as th bst altnativ [Stass and Titus, 2003]. Eo Amplification: social dynamics mostly wok in favou of th goup o isk. Accoding to Condoct Thoy, goups a o-pon if most of thi mmbs a likly to blund. In this cas, th pobability of a coct answ, by a majoity of th goup, dcass towad zo as th siz of th goup incass. Cascad ffcts: Whn goup mmbs xpss thi opinions in a squntial way and whn th majoity of thm val initially thi idas in suppoting of a ctain viw, thos who follow would fl pssu to hav to mak th sam choic. This poblm could b much high whn th follow is indcisiv. A 44

46 Chapt 2 simila ffct can b obsvd bcaus of th putational concns whn popl suppot a viw, not bcaus thy bliv in it, but just bcaus thy do not want to look foolish in font of oths. Th sult would thfo b a pmatu and fak convgnc of idas. Th main aspct of cascad ffct is that, at a ctain momnt, popl dcid to not consid own infomation and knowldg and bgin to follow th oths bhaviou. Gladwll [2000] poposd anoth xplanation of why cascad ffct occus. H claimd that such phnomnon aiss bcaus of th psnc of som influnt popl. Ths influnt individuals a xpts. Thfo, th cascad ffct is not dtmind by a st of popl that imitat ach oth, but ath individuals a affctd by social lationship and pssus Goup Polaization: is th tndncy of popl to bcom mo xtm in thi thinking following th goup discussion [Isnbg, 1986]. Ovconfidnc that may is as sult of bing suppotd by th goup can infoc xtmist viw as wll. Th a two main causs, xtnsivly invstigatd, fo goup polaization, namly social compaison and psuasiv agumnts. Accoding to Social Compaison Thoy, goup polaization occus bcaus popl a motivatd to psnt thmslvs in a socially dsiabl light duing discussion [Bown, 1965; Sunstin, 2002]. Social influncs may tak a cucial ol as wll. Popl continually compa thi opinions with oths ons. Th mchanisms that facilitat this phnomnon a on-upmanship and plualistic balanc. Onupmanship is th tndncy of popl to ty to outdo ach oth in th socially valud diction [Fomkin, 1970]. Plualistic balanc is th dsi of popl to achiv a compomis btwn thi pfnc and th positions of oths. Th scond xplanation, mphasizing th ol of psuasiv agumnts, is basd on th ida that any individual s position is function of which agumnts psntd within th goups sm convincing [Sunstin, 2002]. Th choic thfo movs towads th most psuasiv position dfndd by th goup. 45

47 Chapt 2 On th contay, th following two conditions sm to suppot goup to outpfom vn thi bst mmbs [Iandoli t al., 2009]: Th coct solution is widly suppotd by th goup mmbs bfo stating dlibation. In th xtm cas, at last on of th goup mmbs knows th ight solution and is abl to psuad and convinc th st of th goup. Goup mmbs bliv that th poblm has a cla, coct and wll-known solution. This happns whn th poblm in hand is a so-calld uka qustion o whn a slf-vidnt supio solution xists Th abov mntiond main causs of dlibation and dcision making failu hav bn invstigatd mainly though xpimnts with small, closd and physically collocatd goups, but it is possibl to think that ths poblms could also appa in lag-goup collaboating though Intnt. In any cas, th xploitation of collctiv appoachs nabld by wb-basd tchnologis could b sn as possibl solutions fo oganizations to btt dal with nvionmntal complxity which qui incasingly companis cucial and accuat dcision in shot spons tim. Nowadays, sponsivnss and action spdy a impotant lmnts that could nsu th suvival and succss to th companis [Bonabau, 2009]. In th nxt paagaph, onlin tchnologis will b valuatd with spct thi ability to ffctivly suppot collctiv dlibation pocsss. 2.3 Cunt wb-basd tchnologis fo suppoting collctiv dlibation pocsss Oganizations outinly mak dcisions that qui th involvmnt of a collctivity [Sankaan and Bui, 2008]. Moov, collocatd mtings a vy xpnsiv, limit th badth of intaction and th divsity of knowldg and a pon to sious dysfunction such as polaization, hiddn pofil and cascad ffct [Sunstin, 2006]. Cunt wb-basd tools could psnt a staightfowad tchniqu to nabl a chap 46

48 Chapt 2 and asy way fo collcting a wid amount of knowldgabl and skilld popl, nsuing a ctain dg of divsity of infomation and a wid xploation of solution spac. Thfo, in od to btt analyz th stngthns and th limitations of ths tools in suppoting dlibation and dcision making pocsss, it is hlpful intoduc thm dividing thm in th catgois: Shaing tools, Funnlling tools and Agumntation tools [d Moo and Aakhus, 2006; Klin, Cioffi and Malon, 2007] Shaing tools Th Intnt ows mainly of its succss as collaboativ platfom to this catgoy of tools. Indd, by fa most commonly usd wb-basd tools a wikis, foums, blogs, social ntwoks a th so-calld shaing tools [Josan, Isamil and Boyd, 2007]. A wiki is a st of wb-pags that can b asily ditd by anyon who is allowd accss [Ebsbach t al., 2006]. Anyon can add a nw aticl and/o dit and vis xisting on. Wikipdia s popula succss has allowd to fully and widly undstand th concpt of th wiki as a collaboativ tool that facilitat th poduction of a goup wok. Th main stngthns of wikis in suppoting wok goup a th as of us, vn playfulnss, thi xtm flxibility and opn accss [Ebsbach t al., 2006; Lamb, 2004]. A waknss of wikis is that thy captu, by contovsial topics, th lastcommon-dnominato consnsus btwn many authos. Put diffntly, any nonconsnsus lmnt psumably will b ditd out by thos that do not ag with it. Blogs a th most common wb-basd tools. It lts popl to publish contnt continuously. It fs to a simpl wb pag wh popl can nty opinions and facts in a jounal styl, aangd in a chonologically od. On of th most famous blog is Slashdot.og. As th blogs a tim-cntic tool [Klin, 2010], wh th contnt oganization is basd on whn a post is catd, thy fac som shotcomings fom th pspctiv of nabling collctiv dlibation [Sunstin, 2006]. Th contnt in timcntic tools is typically scattd, so it is had and tim-consuming to b abl to find all th contibutions about a topic of intst. Additionally, this fosts unsystmatic 47

49 Chapt 2 covag of th topic as it is no simpl quickly undstand which aas a wll-covd and which nd an in-dpth xamination. It is notoious that contnt captud though ths tools is voluminous, dundant and ovwhlming. This could imply th occuing of th phnomnon of low signal-to-nois atio. Th latt maks difficult to idntify th novl contibutions that should inspi popl to gnat cativ nw idas. Foum is an onlin discussion sit wh popl can hold convsations in th fom of postd mssags. Thy diff fom chat ooms bcaus mssags a at last tmpoaily achivd. Moov, dpnding on th accss lvl of a us o th foum st-up, a postd mssag might nd to b appovd by a modato bfo it bcoms visibl. With th dvlopd of Wold Wid Wb, foums had a widspad diffusion by attacting popl who do not hav tchnical skilld. Foums psnt th sam shotcomings of th oth kind of tim-cntic tools, such as blogs and chats. Additionally, foum discussions do not scal wll bcaus it is vy difficult fo latcoms to mak sns of a convsation alady statd by oth paticipants [Gukan t al., 2010]. In nutshll, shaing tools hav makably succssful at nabling a global xplosion of knowldg shaing and accumulation, but thy hav to fac numous shotcomings whn applid fo suppoting dlibation and dcision making pocsss aound complx poblms. Fist, shaing tchnologis do not lt to idntify a goup s consnsus. Thi inability dpnds mainly on th way which contnt is captud, which is oftn unsystmatic, dundant and highly vaiabl quality. Moov, such tools do not suppot citical thinking and valid agumntation; thfo contibutions a oftn bias-ath than vidnc- o logic-basd [Iandoli t al., 2009]. Shaing tools a not abl to ffctivly mdiat contovsial discussions and th psnc of loos-stuctu caus th so-calld phnomna flam was o dit was. Uss patdly -dit o undo o vs th pio us's dits in an attmpt to mak thi own pfd vsion of a pag visibl. Edit was could b also th sult of a disput on a tivial issu such as th nationality of Copnicus o of Fddi mcuy. Thfo, unpoductiv dbats could tak plac also in xpctd uncontovsial ons. Flaming is a simila vnt, but it 48

50 Chapt 2 occus in onlin foums. Usually, flam was duc th signal-to-nois atio discouaging popl to stay in th onlin community Funnlling tools Funnlling tools a abl to suppot agggation of infomation and individualization of most widly hld viw. This class of wb-basd tchnology includs -voting and infomation agggation makts (IAMs). E-voting systms apply simply lction pincipl. Thy can b succssful whn th a makt incntivs and a stuctud voting pocss. Numous studis povd that IAMs a ffctiv at agggating infomation povidd by a lag goup of indpndnt and divs individuals. Paticipants hav to bt on thi supposd coct answ and civ a financial wad if th bt is coct. Phaps th bst known pdiction makt among conomist is th Iowa Elctonic Makt, un by th Univsity of Iowa, which poducs accuat stimations about Amican lctions. Th is vidnc that such makts can hlp to poduc focast of vnt outcoms with low pdiction o than convntional focasting mthods. In paticula, sval sachs mphasiz th potntial of pdiction makts to impov dcisions [Hanson, 1999; Snowbg t al., 2007]. Th ang of applications is vitually limitlss, such as hlping businss mak btt invstmnt dcisions o hlping govnmnt mak btt fiscal o montay policy dcisions. Additionally, thi accuacy has alady ncouagd many pivat oganization to us thm, such as Googl [Cowgill, 2005], Yahoo [Cowgill t al., 2008], IBM, Fanc Tlcom, Hwltt Packad [Wolfs and Zitzwitz, 2004], Intl, Micosoft. Th succss of pdiction makts dpnds on thi dsign and implmntation. Som ky dsign issus includ th xistnc of makt incntivs, which motivat popl to sach fo ational choics, and of simplicity of poblms, that is if it is possibl to dfin a st of known and limitd possibl altnativ solutions. Put diffntly, pdiction makts cannot b usd to dlibat on complx poblms, wh it is not possibl to dfin a pioi a st of solutions. Moov, oths cucial lmnts abl to guaant unbiasd outcom a th indpndnc of individuals and th lack of intaction. 49

51 Chapt 2 Th main waknss of pdiction makt is that thy do not suppot onlin uss to dvlop a shad undstanding of th poblms and to popos futh altnativs. Th options a povidd bfo intaction. Ths tools do not mak visibl how uss sach, agggat and cat nw knowldg Agumntation tools Onlin agumntation tools mak us of th agumnt thoy to mdiat and psnt dbats. Agumntation thoy dals with how humans should and do ach conclusions though asoning. Th a diffncs in agumntation thoy on how to dfin an agumnt. Th basic ida is that an agumnt is a st of statmnts, mad up of th lmnts, such as a conclusion, a st of pmiss and an infnc fom th pmis to conclusion. An agumnt can b suppotd o attackd by oth agumnts. Agumnt diagamming is oftn cognizd as a powful mthods to analyz and valuat agumnts [van dn Baak, 2006], as wll as to suppot coct asoning. Usually, an agumnt diagam is a box and aow psntation, with boxs cosponding to popositions and aows displaying th smantic lationships among thm [van Gld, 2002]. A ang of mapping appoachs, thn tanslatd in softwa tools, w dvlopd, but all nabl to dcompos an agumnt into its constitunt componnts, ltting to psnt contnt in a concis and asy to follow mann and making th logic bhind th asoning mo vidnt and visibl. Diffnt typ of agumnt mapping tchniqus a psntd. Concpt mapping (Figu 1) was dvlopd by Novak in 1972 on th basis of Ausubl thoy. This thoy claimd that laning taks plac whn nw concpts a connctd to what is alady known. Concpt map, thfo, lts uss to psnt knowldg as a gaph, wh concpts a nods linking though wods that indicat lationship thus foming a poposition. Usually, concpts a psntd in a hiachical od, fom most gnal and inclusiv concpts at th top th last inclusiv and spcific ons at th bottom. This typ of agumntation tools a widly usd in th valuation of studnts 50

52 Chapt 2 laning in th school systm [Novak and Gowin, 1984]. An xampl of tool that apply ths agumnt mapping tchniqu is Cmap Tools is an ducational agumntation tool. Diffnt studis [Novak and Gowin, 1984; Canas and Novak, 2008; Maiot and Tos, 2008] showd that CmapTool is an ffctiv tool fo suppoting laning and dp undstanding of a topic. Indd, it is oftn usd as an atfact though which studnts can collaboat and discussd about a spcific topic, bcoming a stating point of th laning [Canas and Novak, 2008]. Agumnt and Evidnc Mapping (Figu 2) was poposd by Wingmo [1990] as tchniqu abl to suppot taching and analysis of cout cas. Th ky lmnts of an agumnt map a Claims, Evidncs and Pmiss which a connctd though suppoting/challnging lations. Thfo, in an agumnt map, th functional lationships among claims a mad wholly xplicit using gaphical o oth nonvbal tchniqus [van Gld, 2003]. Th aim is to visually psnt th stuctu of an agumnt, in paticula how vidnc is bing usd in od to claify th status of th dbat. Agumnt maps hav bn usd fo suppoting diffnt tasks, such as taching and dlibation pocsss aound complx poblms. Figu 1. Concpt Map catd with Cmap tool [Okada t al., 2007] 51

53 Chapt 2 Figu 2. Agumnt Map catd with Rational tool [Okada t al., 2007] Issu mapping (Figu 3) allows uss to psnt agumnt by using Issu Basd Infomation Systm (IBIS) fomat which was poposd by Rittl in 1970s. IBIS schm was catd in od to suppot uss in tackling wickd poblms, by hlping goups to psnt a dbat as a visual map composd of a st of issus to b answd, positions (o idas) as altnativ solutions to issus and suppotiv o challnging agumnts about poposd idas. Th th ky lmnts a connctd though lablld links such as suppots to, objcts-to, suggstd by, placs. Conklin [1988] tanslatd IBIS fomat in a hyptxt data modl suppoting dialogu visualization. Figu 3. Issu Map catd with Compndium tool [Okada t al., 2007] 52

54 Chapt 2 Agumntation tools allow uss to psnt complx asoning in a concis, asy to follow, cla and unambiguous way, making th logic bhind an analysis mo vidnt. This fosts uss to idntify lvant infomation. Th main fatu of agumnt tools is to ncouag caful citical thinking [Buckingham Shum t al., 2006; van Gld, 2007], by implicitly quiing that uss xpss th vidnc and logic in favou of th options thy pf. Moov, th agumnts a captud in a compact fom that maks asy to undstand what has bn discussd and, if dsid, add contibutions to it without ndlss duplication. In this way thy a xpctd to nabl incasd syngy acoss goup mmbs as wll as non-dundant knowldg accumulation ov tim. Such tools a supposd to b paticulaly suitd to fost dlibation and dcision making pocsss aound complx poblms as thy allow uss to psnt contntious and/o compting point of viws in cohnt stuctus mad up of altnativ positions on an issu at stak with thi associatd chains of pos and cons agumnts. This ducs th isk of goup polaization phnomnon. Additionally, as ach contibution appas just onc, it adically incass th signal-to-nois atio. In gnal, by poviding a logical-basd dbat psntation, and by ncouaging vidnc-basd asoning and citical thinking, should significantly duc th pvalnc of som citical pitfalls that usually lad to dlibation failus in small scal goups and pomot a mo wll-suppotd dcision making. Notwithstanding, agumntation tools also fac som impotant shotcomings. Fist, agumnt maps do not scal wll: whn th numb of uss incass th constuction of pop collctiv maps appa to not b slf-sustainabl and slf-oganizd and quis intnsiv modation [Gükan t al., 2010]. Th assumption is that, by pioitizing th fomal psntation of contnts gnatd by uss, sachs and dvlops hav nglctd oth impotant social and communication aspcts which a vy impotant in fosting communication and mak paticipation mo ngagd. This has aisd concns on th capability of agumntation to act as ffctiv mdiato and facilitato of intaction. Indd, a cntal poblm is th psnc of communication fomats too constaining and intusiv that disupt th natual flow of f convsations. In tun, th us of fomalism too stict ntails a stp laning cuv: a 53

55 Chapt 2 poficint us of agumnt mapping tools quis a ctain amount of gula pactic and taining [Twady, 2004]. Scaling poblms, inffctiv mdiation, nd fo pactic and taining imply mo intns cognitiv ffot fo uss willing to paticipat to an agumnt-basd convsation than it is quid by cunt convsational tchnologis. 2.4 Conclusions Incasingly, oganizations hav to cop with complx poblms. This is consqunc of ising of nvionmntal complxity. In litatu, th is vidnc that a ight way to fac with such complxity is to xploit th potntialitis of Wb 2.0 in hanssing Collctiv Intllignc [Bonabau, 2009]. In th pvious paagaphs, a shot viw of th main collaboativ tchnologis abl to fost Collctiv Intllignc and, thus, dlibation and dcision making pocsss aound wickd poblms has bn psntd. In litatu, th a vidnc that to suppot fficint and ffctiv dcision making it is impotant to involv lag goup of indpndnt and comptnt individuals with divs skills and knowldg and no past xpinc. Shaing tools hav showd to b succssful to gath vy lag goups of individuals unlss th divsity lads to contovsial situations and thfo unpoductiv dbats though th psnc of high lvl of stuctu. Moov, shaing tools a oftn citicizd on how knowldg is captud and psntd. Indd, thy tnd to poduc dundant and ovwhlming contnt at th psnc of lag goups. Agumntation tools a supposd to handl btt massiv xchang of knowldg, ducing dundancy thanks to a compact psntation of it. Funnlling tools a abl to suppot an ffctiv agggation of infomation and to hold th widly suppot solution, but do not mak visibl th asoning bhind that bt and how nw knowldg has bn catd. On of th stngthns of agumntation tools is xactly th capacity to mak th logic bhind a dcision visibl. 54

56 Chapt 2 Though th is vidnc that agumntation tools could b th ight tool fo mdiating onlin lag dlibation pocsss on complx poblms, it is not flawlss. Fist, th psnc of paticipation and communication fomalisms implis a stp laning cuv with spct to th oth onlin tools. Scond, th stuctu of agumntation consids social cus as ilvant thus impding social communications. Notwithstanding, social communication has bn found to b influntial in cating tust [Chidambaam, 1996] which in tun has consquncs on tam ffctivnss. Moov, by pioitizing th fomal psntation of contnts gnatd by uss ov th tmpoal flow and tun-taking stuctu typical of convsations, mak this tchnology too constaining in absnc of cla and immdiat visibl bnfits pcivd by uss. This has ntaild an objctification and fomalization of convsation aound th knowldg map, as wll as th loss of a ang of mta-infomation about paticipants and th intaction pocss though which th contnt is gnatd. Th loss of this mta-infomation hinds f intaction and maks convsation lss fficint [Clak and Bnnan, 1991]. In th Chapt II, a mo dpnd analysis of agumntation tools will b psntd in od to btt undstand and valuat th stngthns and waknsss of such tools fo ffctivly suppoting dlibation and dcision making pocsss. 55

57 Chapt 3 Comput suppotd agumnt visualization 3.1 Intoduction As mgd in th pvious chapt, Intnt would b a staightfowad mans fo allowing a wid amount of gogaphically dispsd individuals to dlibat and mak collctiv dcisions. Th ways popl can collaboat though wb 2.0 a innumabl givn th boad ang of onlin tools and applications availabl. Although, taditional onlin tools, such as blogs, foums and wikis hav showd a makabl succss in nabling fficint and ffctiv knowldg shaing and accumulation on lag scal, thy appa to b lss suppotiv of knowldg oganization and -us [Iandoli t al., 2009]. In od to tackl this poblm, numous altnativs hav bn poposd to povid onlin communitis with suitabl tools and mchanisms fo suppoting dlibation pocsss. Chapt I ndd with th conclusion that agumntation tchnologis could b th dsid mthod fo mdiating onlin communitis dlibations pocsss. Thfo, in this chapt, a mo dtaild viw and analysis on agumntation tools is psntd in od to btt undstand thi vitus and shotcomings. 3.2 Agumntation thoy: a shot intoduction Th ability to agu is an ssntial human skill involvd in a wid vaity of pofssional and daily lif situations. Agumntation concns with how conclusion can b achd fom a st of pmiss though th application of a asoning. Accoding to agumntation appoach, vy opinion can b bokn into diffnt lmnts, such as th conclusion that it maks and th pmiss that lad to that conclusion. In nutshll, it 56

58 Chapt 3 is th pocss by which popl ach a conclusion though a logical asoning [Ca, 1999; Toulmin, 1958]. Popl gulaly ngag in agumntativ pactics, fo instanc, whn thy advanc in dfnc of ctain asstions o actions and whn thy act to opinions put fowad by oths. Ral lif cass of xcis of agumntation appoachs a, fo instanc, whn an mploy tis to convinc his boss to invst mony in a nw pojct, o whn a politician agus fo a nw national montay policy o whn a lawy has to but an indictmnt to dfns his clint. Agumntation can b dfind as a vbal, social and ational activity aimd at incasing (o dcasing) th accptability of a contovsial standpoint fo th listn o ad, by advancing a constllation of popositions justifying o futing th poposition xpssd in th position [van Emn t al., 1996]. In dtail, it is vbal activity bcaus it is nomally conductd in an odinay languag. An individual uss ctain sntncs to ply to qustions o jction, to asst somthing o to but a claim put fowad by oths. As oth vbal activitis, agumntation may wll b com with th us of nonvbal mans of communication, such as facial and body xpssions and gstus, but not to th xtnt that th vbal xpssions a compltly placd by th nonvbal ons. Agumntation is a social activity bcaus usually it is dictd at popl that individuals ty to convinc about own idas. Finally, agumntation is an activity of ason. Putting fowad an agumnt mans that th agu attmpts to show th ational of his o h position on th matt. Sinc th tim of th ancint Gk philosophs, and vn ali, in Chins cultu, many diffnt thotical and pactical appoachs to agumntation hav bn poposd, which vay on th basis of th typ and numb of lmnts though which is possibl to scaffold an agumnt. Although, diffnt appoachs xist, thy sha som basic pincipls, such as both suppoting and attacking claims should b tokn in account and claims should b wll-goundd. In gnal, such agumntation 57

59 Chapt 3 appoachs, by ltting popl to dcompos opinions into thi constitunt lmnts, nabl mo vidnc-basd and cohnt asoning and mak, in paticula, a logic bhind a asoning mo visibl and vidnt [Buckingham Shum, 2006; Cho and Jonassn, 2002; van Gld, 2003]. In oth wods, agumntation thoy offs a fomalism and a st of uls which may guid popl to th cation of wll-asond agumnt. Thus, thy may b a powful mthods to suppot individuals to ason mo ffctivly [van dn Baak, 2006]. Diffnt agumntation fomalisms hav bn dvlopd to suppot uss in th constuction and visualization of agumnts. By intoducing agumntation fomalisms, such systms, hnc, allows uss to build gaphical psntation of th asoning pocss undlis any typ of discussion. As this task is laboious, many sachs and pactitions hav dvlopd diffnt softwa tools as mans fo suppoting discussion psntation basd on agumntation thoy. Such tchnologis aid uss to cat, manipulat and viw thi agumnts as wll. Ths platfoms a collctivly fd to as Comput-Suppotd Agumnt Visualization (CSAV) tchnologis [Buckingham Shum, 2003]. In th following, I povid a bif dsciption of two basic and wll-known agumntation fomalisms, such Toulmin s schm [1958] and Issu Basd Infomation Systm [IBIS, Kunz and Rittl, 1970; Rittl and Wbb, 1973] Toulmin s schm On of th most known agumntation fomalism is that poposd by Toulmin in his book Th Uss of Agumnt [1958]. Toulmin s oiginal aim was to analyz as agumnts wok. In oth wods, h wantd dvlopd a modl though which it is possibl to assss th validity of a logical asoning. Toulmin blivd that asoning is lss an activity of infnc, involving th discoving of nw idas, and mo a pocss of tsting and shifting of alady xisting idas. Toulmin blivd that a good agumnt 58

60 Chapt 3 should b abl to povid justifications fo a claim. This, thfo, should nsu it stands up to citicism and ans a favouabl vdict. His analysis of th logical stuctu of an agumnt ld him up to dfin a spcific famwok. This agumnt famwok suggsts that a statmnt is mad up of six constitunt lmnts that hav diffnt functions [Toulmin, 1958]: Th Datum: is th facts, vidnc o xpt opinions that suppot individual s conclusion. Th Datum is th basic pmis on which th st of th agumnt is built; it is th tuth on which th claim is basd. Claim: is th conclusion mad in an agumnt and that will b agud. It can b mant as a statmnt that popl ask th oth pson to accpt. Th Waant: is th infnc mchanism o th bidg that allow to connct th datum and th claim. In oth wods, it is usd by individuals to justify why data is lvant to th claim. It dos not ncssaily hav to b a causal ul, but its ol is to fost aching of conclusions though a logical stp. Backing: is th st of infomation o cdntials that suppot th waant. Backings a usd to stablish th gnal conditions that stngthns th accptability of th waants so that th connctions among data and claim will not b analyzd. Qualifi: st of statmnts that xpss th dg of foc o ctainty of th claim. Rbuttals: count-agumnts o st of statmnt that constitut xcptions o limitations to th validity of th claim. Toulmin dfind th pocss of constucting a scintific agumnt mainly as th pocss of using data, waant and backings to convinc th oths of th validity and accptability of a spcific claim. Thfo, th stngth of an agumnt dpnds on th psnc o absnc of ths diffnt stuctual lmnts. Thfo, stong 59

61 Chapt 3 agumnts contain mo of ths componnts than wak agumnts. In light of this classification, th statmnt may b psntd as Figu 4. As it possibl to vinc fom th figu, agumnts a gnally xpssd with qualifis and buttals ath than asstd as absoluts. This nabls individuals citical thinking skills and mak visibl to oths th logic o th asoning bhind th claim. Toulmin poposd this gaphical fomat fo laying out th stuctu of an agumnt as mans to analyz and assss th ationality and goodnss of agumnts. Fo ths asons, Toulmin famwok has oftn bn usd as modl of fnc to valuat th validity of agumnts in numous studis [Suths, 2003; Gukan t al., 2010]. It was initially basd on lgal agumnts, but it may b applid also in th fild of htoic [Ca, 2003] and communication. Figu 4. An xampl of Toulmin s fomalism [Toulmin, 1958] Toulmin s thoy has had an nomous impact on many disciplins and it has found wid application in many agumnt-basd comput systms (i.. Blvd, Rason!Abl). As Toulmin s fomalism is not asy fo novics to undstand and lan to us [Voss t al., 1983; Voss, 2005], gnally Toulmin-basd platfoms hav ty to simplify his thoy to th point to mak his appoach a highly usabl stuctu (i.. by dlting xplicit waant, which a gnally lft implicit in vyday asoning). 60

62 Chapt 3 As alady mntiond, an xampl of Toulmin-basd platfom is Rason!Abl platfom [van Gld, 2003]. It is an agumnt diagamming tool that suppot an asy and quick constuction and modification of agumnt psntation [van Gld, 2003]. Its ky lmnts a: i. Positions (claim); ii. Rasons (datum and waant); iii. Objctions (buttals). This agumnt mapping tools was not dsignd to mdiat collaboativ discussion, but it has mainly bn usd as agumntation aid in ducational stting and to suppot oganizational dlibation pocss in fac-to-fac mting with th psnc of a facilitato and sponso of th tchnology. Anoth platfom which applis loosly Toulmin s fomalism is th Blvd platfom [Suths and Win, 1995; Suths, 1999; Suths and Hundhausn, 2001]. Initially, Blvd implmntd compltly Toulmin s fomalism, but som studis dmonstatd that studnts hav difficulty to fully undstand th maning of th povidd lmnt, that intfing with th studnt s ability to communicat ach oth [Suths, 1999]. This sach findings ld th Blvd s catos to simply th st of availabl pimitivs. Nowadays, Blvd allows to psnt agumnts as gaph wh uss contibutions a visualizd as nod and th links among nods psnt th lationships among contibutions. Th a not studis that confim th impovmnt of th usability of this ducd fomalism IBIS fomalism Anoth stand of agumntation tchnologis hav thi oigin in th Issu Basd Infomation Systms (IBIS) mthodology. It was poposd to tackl th so-calld wickd poblms, and spcifically wickd poblms. Rittl and Wbb [1973] dfind wickd poblms in contast to tam poblms. Tam poblms a not ncssaily tivial poblms, but can b tackld with mo confidnc and it is cla whn a solution has bn achd. Wickd poblms lack a singl, agd-upon fomulation o wll-dvlopd plans of action, a uniqu and hav no wll-dfind stopping ul, bcaus th a only btt and wos, ath than ight and wong solutions. Closu is oftn focd by pagmatic constaints, such as managial o 61

63 Chapt 3 political, ath than ational scintific pincipls [Rittl, 1972]. As such poblms could not b solvd by fomal modls o mthodologis, an agumntativ appoach smd mo appopiat. Indd, an opn-ndd, dialctic pocss of dfining and dbating issus in a collaboativ way may psnt a powful mthod to discov th stuctu of th wickd poblm. This nd motivatd and ld to th dvlopmnt of IBIS as mdium abl to ncouag th opn dlibation of issu. As psntational schm (Figu 5), IBIS lts uss to psnt a dbat as a visual map composd of a st of Issus to b answd, Positions (o idas) as altnativ solutions to issus and suppotiv o challnging Agumnts about poposd idas. Th ky lmnts can b connctd ach oth though lablld links such as suppots to, objcts-to, suggstd by, placs. Issu can futh sub-classifid as: Factual Issu: Is X th cas?. Dontic Issu: Shall X bcom th cas? Explanatoy Issu: Is X th caus fo Y? Instumntal Issu: Is Y th ight way to aliz Y in this situation? Th pow of IBIS appoach dpnds on its intinsic fatus, that is it lts uss to map complx thinking into stuctud analytic diagams. By using IBIS platfom, uss can oganiz lag amount of infomation and knowldg in a compact and asy to follow visual map. This typ of fomalism imposs a spcific stuctu. This has two impotant implications. On on hand, th mo spcific an agumntation visualization tchniqu is, th btt it should suppot poblm analysis, th asi it should b to mak sns of th poblm and solv it. On th oth hand, th mo stict and spcific a fomalism is, th mo difficult and tim-consuming is to lan to us. This is an impotant tad off that this typ of tchnologis should ty to fac. 62

64 Chapt 3 Figu 5. Basic IBIS stuctual units and links gibis is an aly comput-basd implmntation of IBIS appoach [Conklin and Bgman, 1988]. Th systm was assssd as an oganizational collaboativ Knowldg Managmnt tools. Empiical findings, though showd som limitations on th fomalism itslf, hav povd th succss of gibis among mploys, both as collaboativ tool and as a tool fo annotating, stuctuing and coding idas and knowldg. Diffnt tools that apply IBIS fomalism xist, such as QustMap, Compndium TM, Cop_it!, Canads, Dlibatoium. Th applications of ths systms a not limitd to solv wickd poblms, but thy has bn also usd as ducational tool fo suppot scintific agumntation (Compndium TM, Cop_it!), as dlibation and dcision suppot systm (Cop_it!) o to tach lgal agumntation (QustMap). Conklin [2003] pots som sults about a study on th us of QustMap tool in oganizational stting. H noticd that th pow of IBIS platfom as annotation tool dpnds on its ability to oganiz, accumulat and sto all infomation, knowldg and assumptions of uss bcoming an oganizational mmoy and a point of fnc fo suppoting futh discussions about th facd issu. Additionally, Conklin obsvd that uss found th 63

65 Chapt 3 platfom usful only whn thy a bcom poficint with th fomalism. Thus, as mntiond abov, th main agumntation limitations, mgd fom his study, gad th psnc of a stp and long laning cuv and th nd fo oganization to hav a chlad abl to sponso and to pomot th us of th tchnology. 3.3 Th is of comput suppotd agumnt visualization Agumntation can b dfind as th ability to agu and dfnd a spcific position. Th point of agumntation is to influnc oth s attituds by mans of agumnts. In accodanc with this, human bings continually us thi agumntation capabilitis in vyday livs. Unfotunatly, many popl a not so abl agus [Khun, 1991; Tannn, 1998]. Kuhn has cafully documntd th ways in which popl fail to pactic good agumntation in thi own vyday activitis. H sach vals a numb of concns about human bings ability to agumnt poply and ffctivly. Two of th most citical Kuhn s wois a: Popl a typically unabl to distinguish btwn agumnt and vidnc ndd to suppot it. Popl a not vy good at using vidnc to valuat compting claims. This gap motivatd many ducational and laning scinc sachs to invstigatd how comput tchnologis could suppot and fost th laning of agumntation in diffnt filds, such as th law [Alvn and Ashly, 1997; Pinkwat t al., 2006], scinc [Ranny and Schank, 1998; Suths t al., 2001], convsational agumntation [McAlist t al., 2004; d Goot t al., 2007], htoic [Ca, 2003]. As sult of ths sachs many and divs agumntation systms hav bn dvlopd and implmntd. Softwa that suppots th constuction of agumnts, usually though visual psntations calld agumnt maps. It is impotant to undlin that not all agumntation tools us th sam psntation fomat, but, suly, th most common is th gaph styl. This aspct will b discussd dply in th nxt paagaph. this kind 64

66 Chapt 3 of activity is fd to as Comput Suppotd Agumnt Visualization (CSAV) platfoms. Thfo, most common CSAV systms a abl to combin and lvag th advantags diving both fom th us of agumnt mapping tchniqus and th inhnt fatus of comput-basd tchnologis (i.. widspad adoption, spdy, supio availability as compad to human tachs, high ability to sto infomation tc.). In oth wods, agumntation systms lts uss to cat, dit, navigat and viw agumnt maps. An agumnt map can b dfind as a visual psntation of a ason in which th functional lationships among claims a mad wholly xplicit using gaphical o oth non-vbal tchniqus [van Gld, 2003]. Th main fatu of agumnt maps is that, thy allow uss to psnt complx asoning in an asy to follow, cla and unambiguous way. Moov, by displaying knowldg visually though a spatial mtapho and by poviding a logical ath than chonological knowldg oganization, agumnt maps a hlpful fo ky cognitiv tasks such as sns making [Wick, 1995] and citical thinking [Buckingham Shum t al., 2006; van Gld, 2007]. Ov tim, sachs hav, in paticula, focusd on th bnfits diving fom th us of agumntation tchnologis and th main mpiical sults show that xplicit psntations of vidnc-basd asoning suppot citical thinking [Buckingham Shum t al., 2006; van Gld, 2007], ncouag paticipants to claify thi thinking [Bna t al., 2001] and to mak it visibl to oths [Bll, 1997]. Additionally, accoding to van Gld [2003] agumnt maps a btt than pos to psnt th stuctu of a asoning and agumnts fo fou main asons: Pos quis intptation: pos quis ads to lay out th lationships among th claims. This is not a simpl wok bcaus ach ad could com up with a diffnt asoning intptation givn diffnt individuals knowldg, skills and backgounds. Pos nglcts psntational soucs: pos maks littl o no us of any kind of colou, shap o psntational objct to povid infomation about th stuctu of th asoning. In ality, th bain can pocss lag amount of 65

67 Chapt 3 infomation convyd though visual psntations by ducing cognitiv ffot [Donath t al., 1999; Vigas and Donath, 1999; Dav t al., 2004; Nguyn and Zhang, 2006; Suh t al., 2008]. Agumnt map xploit this advantag making lag us of colous and shaps to psnts th diffnt componnts of an agumnts. Whil, in pos uss has to intpt th claim and its contxt to undstand its ol in th agumnt. Pos is squntial, agumnt a not: this xacbats th difficulty that a ad has in undstanding a asoning. Indd, ads hav mntally to constuct th non-squntial logical stuctu fom th squntial sntntial stuctu of th pos. Whil, agumnt maps psnt th whol asoning, all at onc, in its pop od. Pos cannot visually display mtapho: individuals can povid additional infomation, such as what th mo impotant claim is o how stong an objction is than oths by using symbols and mtapho (i.. siz of uss contibutions o spatial location tc.). Ths advantags hav aousd a wid and dp intst among both Comput- Suppotd Collaboativ Laning (CSCL) and Comput-Suppotd Coopativ Wok (CSCW) sachs and pactitions which ld to th alization of lag amount of diffnt agumntation tools. As alady mntiond, with gads CSCL fild has paid much attntion to ability of agumntation tchnologis to fost taching of agumntation skills and on how studnts could bnfit fom thm [Andissn, 2006; Stngmann t al., 2007; Suths t al., 2001]. In this fild, collaboativ agumntation systms a sn as a way though which studnts can lan to agu about any issu o topics in od to aiv at an agd-upon position among mmbs of a goup [Schu t al.,2010]. By scaffolding dialogus though agumntation tchnologis, individuals, not only lan to agu and citical thinking skills [Andissn, 2006; Bansfod t al., 1999], but also thy lan about spcific domain topics (aguing to lan). Ths two aspct of agumntation a mutually dpndnt and oftn no claly divisibl [Koschmann, 2003]. In oth wods, th acquisition of agumntation and domain skills 66

68 Chapt 3 gos togth. This has ousd a gat notic and, as sults, ov th last dcads, a lag and ich aay of agumntation tchnologis as ducational systms hav bn activly dvlopd and tstd in numous sachs [Schu t al., 2010]. Th basic ida is that ths platfoms impov citical thinking by hlping popl to suppot and scaffold thi vidnc-basd asoning and to facilitat sns making by suppoting mmoy and undstanding though knowldg xtnalization. Numous studis on agumnt-basd tools hav shown thi ffctiv in taching agumntation skills whn thy a usd as ducational mdia [Twady, 2004; van Gld, 2006; Toth t al., 2006; Okada t al., 2008]. Ths sults hav ncouagd th dvlopmnt of CSCW systms basd on agumntation as wll [Hua and Kimboough, 1991; Kaacapilidis and Papadias, 2001; Conklin, 2003; van Gld, 2003; Kaacapilidis t al., 2009]. CSCW has mainly focusd on th dsigning and building of tools abl to suppot diffnt oganizational tasks and pocsss, such as dlibation [van Gld, 2003; van Gld, 2006], dcision making [Kaacapilidis t al., 2009; Kaacapilidis and Papadias, 2001], poblm solving [Cho and Jonassn, 2002], dvlopmnt of oganization mmoy [Conklin, 2003]. Th agumntativ aspct of convsations and discussions fo accomplishing oganizational goals a on of th most impotant challngs of CSCW, that is how thy nabl popl to coopat at conflicts [D Moo and Aakhus, 2006]. Indd, on of th main advantags of agumntation tchnologis, spct to th oth mo taditional CSCW tchnologis, is that thy a abl to btt manag contovsial discussions by ltting popl to psnts poply conflicting point of viws. In th nxt paagaph, I intoduc som of th availabl agumntation tools in od to btt dal with thi fatus and functionalitis. 3.3 Th agumntation systms Ov tim, numous agumntation systms has bn dvlopd that diff ach oth fo sval and divs fatus, such as applid psntation fomat, usd ontologis, 67

69 Chapt 3 typ of nabld intaction among uss (synchonous o asynchonous). In this studis, in od to psnt som of th main agumntation tools cuntly availabl, I will distinguish thm on th basis of thi ability to suppot o not collaboation. Whit this in mind, th ang of collaboation altnativs that a today availabl a: Singl-us agumntation systms suppot individuals to stuctu thi opinions and thoughts and/o to aang an agumnt psntation. Th wllknown xampl of singl-us systms a: ConvincM, Canads, Aaucaia, Athna. Suly, som of singl-us systms can also b usd by small goups that sha a singl comput; Small goup agumntation systms mdiat discussion among a lativly small numb of lans and off, usually, synchonous communications. Ths collaboativ agumntation tools allow uss to intact ach oth and with th systms, nabling th dvlopmnt of agumntation skills and discussions about diffnt point of viws. Thfo, ths tools has to suppot both agumnt and communication aspcts. Agumntation systms that blong to this catgoy a: Blvd, QustMap, Digalo, Cop_it!, gibis; Community agumntation systms: a vy simila to th small goup systms, but a abl to suppot lag goup of uss (mayb mo than hundd) and, thfo, a abl to psnt vy lag agumnt maps. Bcaus of th psnc of a lag numb of uss, communication is oftn asynchonous to avoid coodination poblms and psntation fomats a mo igoous. It is a vy cnt typ of agumnt tool. Th uniqu xampls of lag-scal agumntation tools a: Dbatgaph and Dlibatoium. Som of th cuntly agumnt mapping tools fo ach idntifid catgois a psntd. Th choic of ths tools among th wid ang of agumntation systms availabl dpnds on th nd to mphasiz also thi futh impotant fatus and functionalitis, as wll as thi main diffncs. 68

70 Chapt 3 As instancs of singl-uss agumntation systms, I psnt two of thm, that is ConvincM [Ranny and Schank, 1998] and SnsMak [Bll, 1997]. Th choic dpnds on th fact that ths two agumnt tools lt m to intoduc two impotant aspcts, namly i) thi ability to povid tutoial fdback (ConvncM) and ii) a diffnt agumnt psntation (SnsMak). Both th systms suppot th constuction of scintific agumnt and a usd xclusivly as ducational mdia. In paticula, ConvincM suppots scintific asoning in ducational contxt and lts uss to cat vidnc map, by conncting mo scintific-focusd pimitivs such as hypothsis and data though xplain and contadict links. Additionally, it allows studnts valuating agumnts by spcifying a blivability atings fo individual agumnt lmnts. This tool povids uss with fdback on th accptability of componnts in th catd gaph by unning a computational modl of asoning calld ECHO. This systm displays thn th valuation modl togth with studnts blivability assssmnt fo th sam popositions to hlp vntually uss stuctu thi agumnts and/o vis thi atings [Schu t al., 2010]. SnsMak is a singl-us agumntation platfom, it has bn usd also by small goup of studnts in font of th sam comput. It distinctivnss fatu is that it is on of th fw agumntation tools that applis a contains psntation styl of th agumnts. Indd, it allows to visualiz agumntations stands blonging togth gaphically though a fam which sv as contains. Each fam, thus, th claim and th vidnc that suppot o attack it. Anoth agumntation systms that applis this agumnt psntation is Dbatpdia ( and Room 5, a systm fo lgal agumntation [Loui t al., 1997]. Th main advantags of contains fomat is that it is asy to s which agumnts componnts blong togth and a latd, whil th disadvantags is that it dos not allow to hav an ovviw of agumntation as a lag maps bcaus of th missing of lations among contibutions which a xpssd implicitly by th blonging to th sam fam (o contain). With gads to small goup agumntation systms, I psnt Blvd, Cop_it! and QustMap. Th choic of ths diffnt agumntation platfoms dpnds on th possibility to dal with impotant chaactistics of ths tools, that is i) a diffnt 69

71 Chapt 3 psntation fomat (Blvd) and ii) th intgation of diffnt fomalisms to sha and psnt knowldg with divs lvl of fomalization (Cop_it!). Instad, QustMap has bn chosn bcaus it is on of th most known xampl of CSCW platfom. Phaps, th bst and wll-known of all ducational agumntation systms is Blvd [Suths t al., 2001]. Blvd was dvlopd to suppot studnts in thi scintific agumntation, as wll as to ncouag slf-flction about discussd topic. It is a collaboativ agumntation systms and allows studnts to psnt knowldg and discussions as gaphs. Suly, this psntation fomat is th most common among th diffnt agumntation platfom. Indd, oth gaph-basd modling knowldg a Aaucaia [Rd and Row, 2004], Lago [Pinkwat t al., 2006], Digalo [Schwaz and and Glassn, 2007] Cop_it! [Kaacapilidis t al., 2009], Compndium [Buckingham Shum t al., 2006; Okada and Buckingham Shum, 2008], Dlibatoium [Iandoli t al., 2009], DbatGaph. Mayb, its succss dpnds mainly on th fact that it is highly xplicit and cla, making agumnt maps widly intuitiv. In Blvd, agumnt contibutions a psntd as nods and links among th nods indicat th psnc of lationships among th diffnt contibutions. This gaph psntation fomat is an intuitiv fom of knowldg modlling [Suths t al., 1995] that allows an asy analysis of agumnt tanscipts and a quick undstanding of th stat of th dbat [van Gld, 2003; Buckingham Shum t al., 2006]. In th last vsions, Blvd has intgatd also an additional agumnt psntation fomat, that is matix styl. It aims at showing implicit o missing lationship among agumnt lmnts in which agumnts componnts a th ows and th column, and th clls psnts th lations among thm. Th main advantags of this agumnt visualization tchniqu is to mak immdiatly visibl th lack of link among diffnt aspcts of agumnts [Suths, 2003]. Howv, this styl is lss intuitiv than gaph styl. In last vsion of Blvd it is possibl to us contmpoaily both th psntation fomats and, hnc, hypothtically to bnfit fom both thi stngthns. As ConvincM, also Blvd povids studnts with on-dmand txtual fdback to chck fo possibl waknss in thi agumnt gaphs and civ tips on how to pocd. In paticula, this systm is abl to mak diffnt typs of agumnt analysis: i. Domain-spcific pattns (allows to valuat th validity of agumnt stuctu at a 70

72 Chapt 3 syntactic lvl, i.. a quid contibution typ is missing o invalid connctions typ); ii. Poblm-spcific pattns (th systm analyzs diffncs among btwn studnts and poblm spcific xpts diagams). Th psnc of on-dmand fdback has impotant advantags, that is th fdback will b povidd only whn qust, studnts will not b floodd with unncssay mssags, a f to dcid whn thi diagams a ady to hav a chck and mssag will sm lss authoitativ [Suths, 2001]. Cop_it! is a wb-basd agumntation systms suppoting collaboativ laning [Kimbl t al., 2000] and discussions. It povids a wb-basd wokspac fo psnting, stoing and tiving shad and xchangd mssags, contnts and documnts of paticipants, which may b appopiatly pocssd, tansfomd and usd in futu discussions [Kaacapilidis and Tzagaakis, 2007]. Cop_it!, moov, is abl to suppot dcision making pocsss as it uss a st of altnativ asoning mchanisms. Ths mchanisms may tak into account paamts such as opinion wights, pfncs, numb of activ position in favou o against an altnativ [Kaacapilidis and Tzagaakis, 2007] to suppot th dcision making. This platfom povids onlin uss with an appopiat mans to collaboat towads th solutions of divs issus. Cop_it! offs th diffnt psntation fomats that a chaactizd by th lvl of fomalization: i Dsktop viw: is th low lvl of fomalization. It allows uss to add contnts in th most us-findly way, without focing thm with p-dfind communication uls; ii. Fomal viw: a pdfind algoithms of convsion allowd to convt dsktop viw contnts in an IBIS map; iii. Foum viw: this psntation fomat allows to aang contnt in a tmpoal squnc, showing contnts and nod typ (i.. statmnt, agumnt, documnt typ tc). Anoth famous small goup agumntation systm is QustMap. I intoduc it bcaus is on most usd CSCW agumntation platfom. Indd, it has bn usd oganizational mmoy as it allows woks to captu knowldg. Th ky componnt of QustMap is th us of a display systm, much lik an on-lin whitboad, that captus th ky issus and idas duing mtings and cats shad undstanding in a knowldg tam. Fo instanc, th mssags, documnts, and fnc matial fo a collaboativ pojct can b placd on th whitboad, and th lationships btwn 71

73 Chapt 3 thm can b gaphically displayd. Uss nd up with a map that shows a histoy of th convsations that ld up to ky dcisions and plans. QustMap is bing usd by majo copoations fo statgic planning, nvionmntal planning, businss pocss ngining, and nw poduct dsign. Th uniqu xampls of lag-scal agumntation tools a: Dbatgaph and Dlibatoium [Iandoli t al., 2009]. DbatGaph is a wb-basd agumntation tool that allows uss to collaboativly cat fomal psntation of dbat aound complx poblms. It suppot asynchonous agumnt-basd dlibation pocsss and povids multipl agumnt psntations, such as gaph and thadd txt. An impotant fatu of this wb-basd platfom is th us of local viw [Schu t al., 2010] to duc th complxity of lag agumnt maps. This way to visualiz agumnt map is basd on th ida to hiddn its potions. DbatGaph maks us of th agumnt visualizations, that is Bubbl viw, Box viw and thadd viw. Dlibatoium is an IBIS-basd agumntation tool dvlopd to suppot vy lag goups ngagd in dlibation pocsss aound complx poblms. It povids a simpl wb-basd us intfac that allows us to co-cat, dit and navigat an agumnt map, as wll as to communicat ach oth. Th systm includs diffnt tools with divs fatus and that allow uss vaious actions, such as th agumnt map, sach and histoy (allows uss to find th posts that hav givn kywods and to know what oth uss hav don), popl and hom (vy uss hav a psonalizd hom pag which lists which aticls and commnts thy hav addd), mail, chat and foum (this tools suppot diffnt typ of communication among uss, that is spctivly on-to-on communication, public synchonous contxt and public asynchonous thadd communication), watchlist (allows uss to spcify which aticls o post thy a intstd in so that thy can civ automatically notification of vntually its changs), suvy (allows uss to povid fdback about th tool), hlp tool (povids dmos and guidlins to suppot uss in doing pactic with th tool). Fom this vy shot viw of som agumntation systms a mgd ctain impotant lmnts gad to th ths platfoms, that is: 72

74 Chapt 3 Th a diffnt agumntation psntation fomats, such as gaph, matix, contains and thadd appoachs that hav thi own chaactistics, stngthns and waknss. A fw agumntation tools apply at th sam tam diffnt visual psntation of agumnts, combining thfo, thi potntialitis; Som ducational agumnt tools automatically analyz uss agumnts and povid thm with intllignt fdback that and xpss thi blivability o accptability; Mainly sachs and pactitions hav dvlopd ducational systms to suppot th laning of agumntation skills, but givn thi ability to ncouag citical thinking and vidnc-basd asoning, ths tools hav found lag applications also in diffnt filds; indd th is vidnc that agumnt mapping tools can b ffctiv tchnologis in suppoting collctiv dlibation [Conklin, 2003; van Gld, 2003], paticipatoy planning pocss [D Liddo and Buckingham Shum, 2010], knowldg managmnt [Conklin, 2003; Tgan, 2003], dcision making pocss [Kaacapilidis and Tzagaakis, 2007] Th a too fw agumntation tools abl to suppot vy lag scal agumntation. This is an impotant gap that could psnt a stimulus fo futu sachs. Agumntation systms apply diffnt ontologis xplicit spcifications of a concptualization [Gub, 1993]. Ontologis can b dfind as a st of concpts within a domain, and th lationships btwn thos concpts. In Agumntation systms, Ontologis may combin both thotical pspctivs and pagmatic considations diving fom mpiical tsts. Fo instanc, both Stgmann t al., [2007] and Suths [2003] simplifid th oiginal Toulmin s modl to impov its usability. Suly, th most known and usd agumntation ontologis a Toulmin s schm and IBIS fomalism. 73

75 Chapt 3 In th nxt paagaph, th stngthns and waknss of agumntation tools will b discussd spct to thi ability to ncouag collctiv dlibation and dcision making pocsss. 3.4 Vitus and shotcomings of agumntation tchnologis Agumntation thoy dals with how human bings should and do ach conclusions though asoning. Ov tim, numous agumnt-basd tchnologis hav bn dvlopd to suppot individuals and goups to us agumntativ appoachs fo impoving thi asoning skills. Th basic ida is that ths platfoms suppot and guid uss in thi asoning though th cation of visual objcts. Agumntation systms povid uss with comput-basd intfacs that allow thm to cat, dit and navigat an agumnt map. Agumnt maps can b usd to visualiz concpts, contnts (.g. annotations), knowldg soucs (.g. wbsits), as wll as links among knowldg lmnts. Waving connctions among nods in th maps is th most flxibl way to bing idas and infomation togth in a cohnt, concis and compact way. Moov, by displaying knowldg visually though a spatial mtapho, agumnt-basd platfoms a hlpful fo ky cognitiv tasks such as sns-making of lag amount of (conflicting) infomation [Un t al., 2006]. This happns bcaus agumnt maps mak infntial lationships among pics of infomation vidnt, mo asi to s and undstand [Suths, 2008]. Moov, shad, visual psntations giv nw oppotunitis fo focusing collctiv attntion, nvisaging nw scnaios, coodinating actions and impoving comphnsion and tntion of knowldg [Okada t al., 2008]. Th us of gaphical psntations may b bnficial fo many and divs cognitiv tasks, bcaus thy foc uss to xpss thi idas and opinions to on anoth in an xplicit fom, hlping to oganiz and maintain cohnc, and sving as convsational soucs [Andissn, 2006]. Empiical studis suggstd that xtnal visual psntations may guid uss towads mo xtnsiv and complt laboations of infomation, considation of countagumnts and 74

76 Chapt 3 intgation of infomation [Suths, 2008; Suths and Hundhausn, 2003; Nussbaum t al., 2007]. In litatu, th is vidnc that agumnt-basd tools a abl to tach and impov agumntation skills (laning to agu) [Okada t al., 2008; Pinkwat t al., 2007; Toth t al. 2006; Twady, 2003; Schank, 1995; Stgmann t al., 2007; van Gld, 2006]. Fo instanc, Suths [2003] potd som mpiical vidnc about th ability of ths tools in impoving studnt s asoning abilitis; indd, studnts that us vidnc maps a abl to stat ali and mo hypothss and vidnc than goup that do not us Gaph styl psntation. As uss hav to confom to spcific fomalisms basd on logical ath than chonological knowldg oganization, ths agumntation systms ncouag vidnc-basd asoning and, thfo, pomot ational thoughts and impov citical thinking [Buckingham Shum t al., 2006; van Gld, 2007]. Moov, sachs hav claimd that xplicit psntations of knowldg though agumnt maps ncouag paticipants to claify thi thinking [Bna t al., 2001], mak this thinking visibl to oths [Bll, 1997], fost infomation and knowldg awanss [Englmann and Hss, 2010] povid soucs fo convsation [Roschll, 1996] and can function as a convgnc atifact that xpsss th goup s mging consnsus [Hwitt, 2001; Suths, 2001]. Ths sults hav ncouagd sachs and pactitions to dvlop collaboativ agumnt-basd CSCW platfoms abl to suppot diffnt oganizational task, such as i. dlibation pocss [van Gld, 2003; Conklin, 2006; Iandoli t al., 2009; Klin, 2009], ii. dcision making pocss [Kaacapilidis, 2009; Kaacapilidis and Papadias, 2001], iii. poblm solving [Cho and Jonassn, 2002], iv. knowldg managmnt ( oganizational mmoy ) [Conklin, 2003]. In paticula, this wok focuss on ability of collaboativ agumnt-basd tools to suppot distibutd dlibation and dcision making pocss. Diffnt agumnt mapping tools abl to suppot dlibation and dcision making pocsss hav bn dvlopd, such as Hms, Cop_it!, QustMap, Dlibatoium. Accoding to sval scholas, divs ational motivations xist to justify th us and implmntation of ths tools fo suppoting this oganizational pocss [Conklin, 2003; Klin, 2009; Iandoli t al., 2009; Gukan t al., 2010; Kaacapilidis, 2009]. Fistly, 75

77 Chapt 3 gnally spaking, collctiv discouss and dbats can hlp goup mmbs to ason btt and agumnt-basd platfoms can ncouag citicisms and compaison of divs, altnativ and conflicting point of viws. Additionally, on of th pimay stngthn of agumnt-basd tools is th way captud knowldg is psntd and aangd. Indd, ths tools tak an agumnt cntic appoach which allows goups to systmatically captu and psnt thi dbats as agumnt gaphs (o maps) wh knowldg is oganizd logically ath than chonologically. Ths psntation fomats hav many advantags. Fistly, by suppoting citical thinking [Buckingham Shum t al., 2006; van Gld, 2007], agumntation tchnologis may lad to mo fficint and ffctiv dbats and wll-goundd dcisions [Conklin, 2003; Twady, 2003; van Gld, 2007]. This happns bcaus uss a quid to xpss th vidnc, facts and logic in favou of o against an option [Ca, 2003]. Scondly, sachs claim that agumntation tchnologis, by suppoting logical ath than tim-basd psntation of dbats, should duc som of citical pitfalls of dlibation and dcision making pocsss, such as low signal-to-nois atio, hiddn pofil, balkanization, goup polaization [Klin, 2009; Iandoli t al., 2009; Gukan t al., 2010]. In paticula, as vy contibution appas just onc, it adically incass signal-to-nois atio and, thus, it maks asi to not novl contibutions o to listn th so-calld small voics that inspi popl to gnat cativ nw idas. Anoth impotant advantag is that as all latd posts appa clos, all contnt on a givn aspct of th discussion is asily idntifiabl and localizabl. This has many implications. Fistly, this maks simpl to find what has and has not bn discussd on any topic, fosting a mo systmatic and complt covag of it. Scondly, it hlps countact balkanization and goup polaization pitfalls by putting all compting idas and agumnts nxt to ach oth. On th contay, uss of tim-cntic tools, usually, tnd to slf-assmbl into goups with individuals sha th sam opinions and, thus, to s only a subst of issus and agumnts potntially lvant to a poblms. This lads to popl to ovmphasiz thi opinions, as thy infoc ach oths, and to mak mo xtm, but not wll infomd, dcisions. Lastly, this psntation fomat ducs dundancy of captud contnt duing th dbat. This poblm is typical of shaing tools, wh contnt is oganizd chonologically and widly scattd; this 76

78 Chapt 3 maks vy had to find all contibutions that dal with a spcific aspcts of intst and, thus, might fost unsystmatic covag sinc uss a not aidd to idntify which aa a alady wll-covd and which nd mo attntion. Futhmo, mpiical findings hav showd that agumntation tchnologis a abl to favou knowldg licitation and full infomation disclosu in collaboativ dcision making stting [Inton, 2009]. H found that his tool [Rason] is abl to significantly duc a wllknow goup dcision-making pitfall, that is hiddn pofil ffct. Th incasing of licitd knowldg by using agumnt-basd tools is confimd in Jaupathiun and Zahdi s mpiical sults [2007]. This is anoth cucial lmnts fo nsuing ffctiv dlibation and dcision making pocsss. Anoth impotant bnfits diving fom th us of agumnt mapping tools is th incasing of discussion cohnc. Cho and Jonassn [2002] found vidnc that th utilization of agumnt-basd tchnologis in poblm solving stting suppots uss in th cation of mo cohnt agumnt and nabls mo poblm solving actions. This dpnds mainly on th fomalism that uss hav to us to dbat though agumnt map that ncouag uss to ason by using vidnc and facts. In gnal, stuctuing and xtnalizing a potntial aids to incas consistncy and cohnc of asoning [Sillinc and Sadi, 1999]. Thfo, agumntation fomalism can b considd as a potntial mdy fo on of poblm that a typically ncountd in communications suppotd by taditional cunt tools (i.. chats), that is incohnc. Accoding to Suths [2008] agumnt maps might incas discussion cohnc bcaus th concptual lvanc of uss contibutions bcom mo vidnt and obvious whn paticipants can fs to componnts of agumnt map. Moov, th addition mntal dmands of agumnt map cation may lad to mo igoous and wll-concivd agumnts [Buckingham Shum t al., 1997]. On of th most impotant stngthn of agumntation tchnologis, also spct to most common cunt wb-basd and not wb-basd oganizational tchnologis, is that thy can b usd to build fomal, computabl and usabl knowldg psntations [Conklin, 2003]. Indd, whn usd collaboativly ths platfom suppot th constuction of shad knowldg visualizations which can, additionally, ncouag 77

79 Chapt 3 knowldg xchang, shaing and accumulation. Fo instanc, in litatu, th a sval platfoms that a usd as oganizational mmoy; this knowldg bas can b, thfo, -usd, modifid and -mixd in futu discussions [Kaacapilidis and Tzagaakis, 2007; Conklin, 2003]. In paticula, whn ths tools a usd as poblmsolving o dcision-making suppot systms, captud knowldg can psnt a stating point o a gnal fnc fo nxt simila poblms. Dspit all ths advantags, agumntation tchnology sms to stuggl to ach widspad diffusion both in oganizations and onlin communitis. Evn whn usd succssfully, agumnt mapping quis uss to undgo intnsiv taining to bcom poficint with th fomalism [Twady, 2004; van Gld, 2003], stong intnal sponsoship, individual commitmnt and facilitation [Conklin, 2006], and high coodination and modation costs whn th dlibation involvs many uss [Gukan t al., 2010]. Many studis hav showd that agumnt-basd fomalism is had to us without xtndd taining. Suths [1999], fo instanc, in his aly wok to dvlop an agumnt platfom, found that stict adhnc to an stablishd agumnt fomalism, that is Toulmin s famwok [1958] ld to usability poblm; in oth wods, Suths found that too many agumnt componnts mad studnts psntation wos bcaus of th incoct us and undstanding of th lmnts. Thus, h should dastically simplify his agumntation systm, namly Blvd. Similaly Buckingham Shum [2006] nots that th complxity of IBIS-basd systms can b a hudl to thi wid adoption, but suggsts that this may b an invitabl lmnts of agumnt platfoms. Moov, h claimd that th woth of ths platfoms justify th initial uss cognitiv ffot. Ths findings a confimd by Conklin [1988; 2006] studis about application of agumnt mapping tools in wokplac sttings. His mpiical findings mphasizd th impotanc of chlads and facilitatos that sponsod and suppotd th us of ths tchnologis. Finally, sval studis dmonstatd that agumnt-basd tchnologis impov agumntation and citical thinking skills only aft xtnsiv taining and pactic piod, usually though facilitatos qualifid in th agumntation thoy. Th long and intnsiv taining is quid bcaus popl do not 78

80 Chapt 3 hav, on avag, good agumntation skills [Kuhn, 1991] and a subjct to sval agumntation fallacis [Walton, 1996]. In this wok, howv, a diffnt thinking to xplain th low at adoption of agumntation platfoms is followd. Indd, a futh souc of costs can b associatd with psntation mod usd to oganiz and visualiz agumnts. As agumnt-basd tools constain uss to follow a spcific fomalism in dvloping wll-oganizd agumnts whn usd as mdium fo dbats, gaphical psntations can b flt unnatual and unintuitiv compad to oth possibl foms of asoning such as convsation [Clak, 1996]. Moov, agumnt mapping tools, by pioitizing th fomal psntation of contnts gnatd by uss ov th tmpoal flow and tuntaking stuctu typical of convsations, mak this tchnology too constaining in absnc of cla and immdiat visibl bnfits pcivd by uss. Indd, a substantial amount of sach on onlin agumntation has focusd mainly on knowldg psntation issus in od to find suitabl knowldg fomats fo psnting uss contibutions. On th oth hand, agumnt mapping sachs hav nglctd social and convsational aspcts of onlin intaction. As a consqunc th us of agumnt maps in a collaboativ fashion can imply an objctification and fomalization of convsation aound th knowldg map, as wll as th loss of a ang of mtainfomation about paticipants and th intaction pocss though which th contnt is gnatd. As with any mdiation tchnology, th loss of this mta-infomation hinds f intaction and maks convsations lss fficint [Clak and Bnnan, 1991]. Th basic ida is that such a loss is vn high in th cas of mapping tools bcaus thy a stongly objct ath than human-ointd. This has aisd concns on th capability of agumntation to act as ffctiv mdiato and facilitato of intaction. notwithstanding th makably advantags that a xpctd fom its us. In this wok th aim is to invstigat how social and convsational agumntation tchnologis capabilitis can b impovd, and whth and to what xtnd ths impovmnts impact on uss pfomancs. With this in mind, th cntal sach qustion is: 79

81 Chapt 3 How to tain th advantags of agumnt mapping and impov thi mdiation capability? Thfo, in od to tain th advantags offd by agumnt mapping tools but at th sam tim to impov thi capabilitis to mdiat intaction, in th nxt Chapt, a nw tchnological solution, abl to povid al-tim visual convsational fdback, will b dply xplaind. It is daw on Gounding Cost thoy poposd by Clak and Bnnan [1991]. Indd, following Clak and Bnnan s thoy, th availability of mtainfomation containd into convsational fdback dos not only mak th convsation mo plasant fom th social point of viw, but abov all it hlps to facilitat th gounding pocss, that is th constuction of shad undstanding among paticipants, thus incasing th fficincy of a convsation. 80

82 Chapt 4 Communicating Efficintly to Collaboat Effctivly: th Common Gound Thoy 4.1 Intoduction Chapt 3 ndd with conclusion that low adoption at of agumntation tchnologis dpnds on thi poo ability to suppot f intactions and convsations. Rsach on agumntation has focusd mainly on knowldg psntation issus in od to find th suitabl knowldg fomat fo visualizing uss contibutions disgading social and communication aspcts of intaction, which a vy impotant fo fosting intaction and making paticipation mo ngagd. Additionally, th utilization of stict knowldg psntation fomats hav ld to an objctification and fomalization of convsation aound a knowldg objct (agumnt map), as wll as to th loss of mtainfomation, mbddd into convsation, about paticipants and intaction pocss though which th contnt is gnatd. Accoding to Clak and Bnnan [1991], th loss of this mta-infomation hinds f communications and maks convsations lss fficint. In this sach, a nw tchnological solution, th Dbat Dashboad, abl to impov agumnt-basd systms mdiation abilitis will b poposd. In paticula, dawing on Common Gound and Gounding Cost thoy [Clak and Bnnan, 1991], th Dbat Dashboad is abl to povid al-tim visual fdback aiming at compnsating th loss of social and convsational infomation du, mainly, to th mdiation of th tchnology. In th following Chapt, fist, Common Gound and Gounding Cost thoy will b intoducd and thn, in lin with this communicational thoy, a possibl solution to tackl th poblm will b poposd. 81

83 Chapt Common Gound: Clak s Contibution Languag is instumntal fo hlping popl to vy day do things [Clak, 1996], such as fo planning activitis (wok, vacations, lisu), discussing, tansacting, buying somthing, taching and laning, and so on. In od to convs, popl hav to psuppos to sha infomation and knowldg with thi audinc. What spaks psuppos guid both what thy choos to say and how thy intnd what thy say to b intptd [Stalnak, 2002]. Claly, ach paticipant has own psuppositions about convsation, but it is common knowldg only that pat of psuppositions that also all paticipants psuppos: on psupposs that only if on psupposs that oths psuppos it as wll [Stalnak, 2002]. Ths psuppositions a what is considd by spaks to b common knowldg of paticipants in th convsations. This lads to th notion of common gound - mutual knowldg, blifs, assumptions and attituds among paticipants [Clak and Calson, 1982; Clak and Mashall, 1981; Lwis, 1969; Schlling, 1960] built and updatd though thi joint collaboativ activity [Clak and Bnnan, 1991]. Common gound at tim t i dpnds on th common gound at an ali tim t and on th cous of th convsation btwn t and t i. In lin with this, common gound not only to f to th cunt status of convsation, but also to th pocss that ld to that condition. Clak and Schaf [1989] idntifid two impotant lmnts fo ffctiv common gound building: Basis: th is a supposd common gound among paticipants in a convsation on which thy ag. Accumulativnss: Paticipants build knowldg on th basis of th psupposd common gound and this dpnds on making th ight addition of knowldg at th ight tim. Clak and his collaboatos [1991; 1996] claimd that convsation is an xampl of joint action, bing it caid out by two o mo individuals which act in coodination ach oth. In gnal, a joint action is not a simpl xcution of actions (i.. danc, play a dut, convs) among two o mo popl, but it quis an activ involvmnt by all paticipants, that is thy hav to coodinat ach oth. Clak [1996] distinguishd 82

84 Chapt 4 btwn two typs of coodination ncssay in vy kind of joint activity: contnt and pocss. Coodination of contnt dpnds on th shad knowldg about th subjct o aa of intst (know that). Coodination of pocss dpnds on shad undstanding of uls, pocdus and mann in which th intactions will b conductd (know how). Whil contnt coodination quis a vast amount of shad infomation, pocss coodination quis a continual updating of paticipants common gound, momntby-momnt. Thfo, accoding to Clak and his collagus all collctiv actions a built on common gound and its accumulation. Th ffctiv constuction of common gound (o common undstanding) is a ncssay condition fo a succssful and fficint communication and collaboativ wok sinc it hlps popl to convs and undstand ach oth. Fo instanc, whn popl talk ach oth thy hav to do mo than just listn and undstand; thy hav to coodinat on th contnt and on th pocss [Gic, 1975, 1978]. Fo instanc, whn Katja spaks about h poppis, Saah must ach th mutual blif that sh is fing to h daughts; in addition, Katja hav to ty to spak only whn Saah is attnding to, listning and tying to undstand what sh is saying and sh has to guid h by giving Katja vidnc that sh is doing just this. Duing convsation, paticipants kp tack of thi common gound and chang it momnt-by-momnt as paticipants com to sha incasingly infomation. It is incmntally built on th histoy of joint actions btwn communicatos [Clak, 1996]. Accoding to Clak and Bnnan [1991], duing a convsation, paticipants xchang, in addition to infomation, vidnc and/o qusts fo vidnc, ndd to assss whth th listns hav undstood o hav not undstood what th spak has said. Onc such vidnc is gaind though convsational fdback offd by vbal and nonvbal communication acts, it is usd to updat paticipants shad infomation. In oth wods, paticipants ty to gound what has bn said duing a convsation, that is thy mak it pat of thi common gound wll nough fo thi cunt pupos [Clak and Bnnan, 1991; Clak and Schaf, 1989]. Th pocss of updating of common gound is calld gounding pocss. Thus, th building of common gound is viwd as a dynamic and collaboativ pocss. Indd, fom this pspctiv, 83

85 Chapt 4 Clak and his collaboatos poposs an xtnsion of th taditional modl of communication by xpanding th famwok of convsational analysis fom th singl uttanc (o unit) to an intactionally-dvlopd contibution. In th taditional modl, th spak has to poduc an undstandabl uttanc and th addss has to undstand it. In th collaboativ modl, instad, paticipants has to do mo at th sam tim, that is thy hav to poduc uttancs and, thn, thy hav to constantly acqui vidnc that ths a had and undstood. It is just this pocss of mutual signalling and chcking to b collaboativ. Accoding to this viw, th pocss of contibuting to a convsation consists both poducing contnt and poviding vidnc about th undstanding of it. So contibuting to convsations divids into phass [Clak and Bnnan, 1991, p. 130]: 1. Psntation phas: A psnt an uttanc u fo B to consid. H bass so on th assumption that, if B givs him an vidnc o stong, h can bliv that sh undstands what h mans by u; 2. Accptanc phas: B accpt uttanc u by giving vidnc that sh thinks sh undstands what A mans by u. Sh bass on th assumptions that, onc A gists that vidnc, h will also think that sh undstands. Gounding is mainly vidnt in th accptanc phas. Indd, at th nd of A s uttanc (psntation phas), on th basis of intlocuto s undstanding of th uttanc, addss pcivs himslf in on of fou following stats fo all o pat of th uttancs. Th fou stats a situatd along th spctum of not haing th statmnt to undstanding what th spak mant [Clak and Bnnan, 1991, p. 130]: Stat 0: B did not notic that A poducd an uttanc u Stat 1: B noticd that A poducd an uttanc Stat 2: B coctly had u Stat 3: B undstood what A mant by u. 84

86 Chapt 4 In oth wods, whn B achs stat 3 with gad to A s uttanc, thn paticipants can gound what has bn said. Without an accptanc phas, gounding pocss cannot b bgun. Thfo, onc a spak has uttd somthing, h has to wait fo an vidnc (positiv o ngativ) about his uttanc. Ngativ vidnc indicats that addss hav misundstood o mishad somthing and, thfo, spak has to ty to pai th poblm. Whil, th common foms of positiv vidnc: Acknowldgmnt: intlocuto assts accptanc though som foms of backchannl sponss, such as uh huh, yah, ally and so on; Rlvant nxt tun: addss uttd somthing of appopiat that inducs spak to think that h o sh hav undstood; Continud attntion: civ shows to listning o attnding to th convsation Evidnc is a cucial lmnts of gounding pocss, bcaus it allows popl to undstand if thi audinc hav undstood o hav not undstood what thy hav said. It is th p-condition to gt going gounding pocss. A cntal pincipl of Clak s modl is that th gounding pocss is always adaptiv to th cunt contxt of communication. In oth wods, it may b affctd by two factos, pupos what popl ty to accomplish in thi communication and mdium th tchniqus availabl in it fo accomplishing that goal and th cost to us thm. Additionally, Clak and Bnnan claimd that spaks and intlocutos gound what has bn said duing a convsation by using thos tchniqus availabl in mdium. Thy will tnd to us thos mthods that lad to th last collaboativ ffot. In gnal, popl tnd to consv thi ffot o to minimiz it in doing what thy intnd to do. Popl do not want to wok had than thy hav to do. Accoding to th pincipl of last collaboativ cognitiv ffot, in a convsation paticipants ty to minimiz th wok that thy hav to do to gound what has bn said, that is th ffot that popl do fom initiation of ach contibution to its mutual accptanc. 85

87 Chapt 4 A possibl way to masu th xtnt of collaboativ cognitiv ffot is to valuat th costs of gounding [Clak and Bnnan, 1991]. Ths costs vay on th basis of th mdium that popl us to communicat. Indd, whn th convsation is mdiatd by som kind of communication tchnologis, pat of th convsational fdback povidd in fac to fac convsation is ith unavailabl o can b povidd with som xta communication ffot. In oth wods, visual, aual and contxtual clus such as facial xpssions, body gstus and objcts, which may convy additional infomation, a lacking in any convsation mdiatd by a tchnologis. Indd, futh infomation suppot and hlp mutual undstanding and gounding pocss. Fo instanc, in a phon call paticipants nith can ly on body languag to chck that th listn undstands o that s/h is paying attntion to th convsation, o can f to anything in paticipants spac to fost th mutual undstanding about topic of convsation. Consquntly th thoy of common gound stats that mdiatd communication is always lss fficint than fac to fac intaction and infficincy is chaactizd in tms of gounding costs. Th fficincy of a convsation in tms of gounding costs dpnds on th psnc of a sts of gounding constaints [Clak and Bnnan, 1991; Kaut t al., 2002]. Ths constaints a dsiabl to duc th ambiguity and gounding costs in convsation. Indd, th high th numb of missing constaints, th lss abl th mdium will b fo facilitating common gound building and fficint communication. In th following, th tn constaints as dfind by Clak and his collaboatos a poposd [1991; 2002]: 1. Audibility: Paticipants can communicat by spaking. Fo instanc, tlphon, mobil phon and som wb-basd systms, such as Skyp and tlconfnc tools, hav this constaint, allowing, hnc, popl to ha ach oth. 2. Copsnc: Uss a mutually awa to sha sam physical nvionmnt. In fac-to-fac convsation, paticipants, shaing th sam spac, can asily and pomptly s and ha who is psnt, what ach oth is doing and looking at. Shaing th sam spac allows spaks and intlocutos to us mchanisms 86

88 Chapt 4 that stablish fnc to th physical and social wold. Th a not oth mdia that allow to do it. 3. Cotmpoality: B civs at oughly th sam tim as A poducs. In most convsations (i.. fac-to-fac, on tlphon, vido-confnc tc.) an uttanc is civd just whn it is poducd and undstood without dlay. It dos not happns in oth mdia, such as mail. 4. Mobility: Uss sha th sam physical nvionmnt and can mov aound it. This constaint is impotant bcaus, fo instanc, popl could us objcts to xplain quickly somthing and, thus, fost mutual undstanding and gounding. Claly, this is possibl only in th fac-to-fac convsations. 5. Rviwability: Uttancs do not fad, but can viwd bfo bing snt. In som mdia, such as mail, onlin chats o ltts, convsations bcoms an atifact and can b viwd lat by paticipants o, vn, thid pats. 6. Rvisability: B can vis mssag fo A. Som mdia, such as mail, shot txtbasd mssags o wb-basd chats, allow an individual to vis and coct it pivatly bfo snding it to his intlocutos. On th contay, in fac-to-fac and phon convsations, popl hav to coct thi uttanc publicly. 7. Squntiality: A s and B s tuns cannot gt out of squnc. Usually, in fac-tofac, phon and vido call, tuns odinaily fom a squnc that dos not includ intvning fom diffnt convsation with oth individuals. With oth mdia, such as mail and ltts, a mssag and its ply could b spaatd by numous ilvant o not ptinnt mssags and activitis. 8. Simultanity: A and B can snd and civ at onc and simultanously. Somtims mssags can b snt and civd by both spaks and intlocutos at onc, as whn an intlocutos nodding in agmnt duing spak s uttanc. In gnal, mdia do not allow simultanity, but only 87

89 Chapt 4 cotmpoality, such as onlin chats that lt to convy mssag just whn it is poducd. 9. Tangibility: Paticipants can touch oth popl and objcts in th physical nvionmnt. This constaint woks as mobility constaint in suppoting mutual undstanding and gounding. 10. Visibility: Paticipants a visibl ach oth. Cuntly, numous mdia allow popl to s ach oth whil convsing (i.. platfoms and tchnologis that suppot vido-call Skyp and vidophon) Th mo constaints a mdia can povid, th btt th mdia is fo fosting gounding pocss and, thfo, fficint convsations and collaboation. Whn on of ths constaints is missing, th will b a high cost of th convsation, bcaus mdiation focs popl to us altnativ gounding tchniqus. Thfo, th high th numb of missing constaints, th high gounding costs is. In oth wods, without ths constaints, a majo collaboativ cognitiv ffot is ncssay fo th paticipants in a convsation to undstand ach oth and gound what has bn said. Fo instanc, a vido call impovs communication ov a phon calls bcaus th vido-tlphony adds visibility o th littl pncil icon in a chat givs vidnc that th spak is not away but is witing somthing in that vy momnt. On th oth hand, txt-basd comput mdiatd communication (CMC) is viwabl, allowing paticipants to -ad mssag bfo snding and to asily achiv it [Gnspan t al., 2000]. In this way, CMC uss hav mo tim to pocss infomation. Each mdium and its associat constaints impact diffntly on collaboativ cognitiv ffot of paticipants that thy hav to ba to stablish and updat thi common gound. In tun, this may affct th choic of mdium has to mdiat and suppot convsation in wokspac. 88

90 Chapt Common Gound In CSCW Fom th bginning of CSCW fild, sval htognous thois hav bn applid to as fnc famwok fo suppoting and nabling th valuation and dsign of pop collaboativ platfoms. Th wid and vaious ang of thois commonly tansfd to CSCW vais fom Anthopology fild (i.. Distibutd Cognition) to psychology (i.. Activity Thoy and Situatd Action thoy) and oganizational scinc (i.. Coodination thoy). In this sach w focus on human languag us [Clak, 1996] and psycholinguistic studis that hav povidd a thoy on social and cognitiv factos in communication vy usful and impotant fo Human Comput Intaction (HCI), CMC and, obviously, CSCW studis. Indd, th constucts of common gound and gounding pocss a oftn usd in this sach aas to valuat th ability of diffnt communication mdia to facilitat mot intactions and how collaboation can b ffctd by infomation and communication tchnologis. In lin with this numous mpiical xpimnts hav bn pfomd to masu and assss th ffct of th utilization of diffnt tchnologis on th constuction of mutual undstanding. In oth wods, many studis in CSCW aa hav bn focus on th ffct of vaious mdia on gounding. In th following, som of ths xpimnts will b intoducd, abov all, to show th impotanc and th impact of Clak s thoy in CSCW fild. McCathy t al. [1991] compad two foms of txt-mdiatd communication, that is pu onlin chat and onlin chat intgatd with a shad pot spac. Thy hypothsizd that th intoduction of shad pot spac could facilitat th mutual undstanding and th gounding pocss by insting two impotant constaints: visibility and co-psnc. Th aim of pais of subjcts was to solv a dsign poblm communicating only by using th onlin chat. Som goups usd pu onlin chat, whil oths usd augmntd onlin chat (with shad pot spac). Th goups w compad in tms of numb of solutions and agumnts codd, and th dg of disagmnt was assumd to b invsly latd to th dvlopmnt of common gound in ach dyad. Th sults confimd Clak s thoy about th impotanc of impact of dmonstatd that stablishing common gound was mo difficult fo subjcts woking with th pivat pot [McCathy at al., 1991]. 89

91 Chapt 4 Anoth impotant xpimnt was potd by Vinott t al. [1999]. Th aim of this mpiical tst was to assss gounding pocss in pais of nativ English and non-nativ English spaks. Th a two communicating conditions: only audio and audio supplmntd with talking-had vido. Th basic ida was that th intoduction of vido (visibility) would impov gounding spcially fo non-nativ spaks who psumably stat convsations with lss common gound. Nativ spak pfom btt than non-nativ spak, but th latt showd mo impovmnt of pfomanc whn statd to us also th vido. Fussll, Kaut and Sigl [2000] studid th ffct of communication mdium on gounding. In thi sach, woks w askd to pfom manual pais on a bicycl. Thy compad th diffnt mdia conditions: i. sid-by-sid; ii. Patns spaatd but abl to communicat though a full-duplx audio (visibility); iii. Audio supplmntd with vido (visibility and audibility). Th authos hypothsizd that gounding and mutual undstanding should b asi in th sid-by-sid communicativ conditions and had in th audio condition. Rsults confimd as hypothsizd by thm. Convtino and his collaboatos hav pfomd sval xpimnts to assss how common gound dvlops in a coopativ wok stting, in paticula, in distibutd and synchonous collaboation [2004; 2005; 2006; 2008]. In thi studis, sachs [2004] intoducd an impotant novlty in od to btt assss th common gound concpt applid to collaboativ wok. Indd, so fa, th pincipal unit of analysis in Clak s modl and subsqunt mpiical studis was th dyad. Accoding to Convtino, th dyad is, howv, a faily dgnat cas of collaboativ wok goup. Spcifically, thi studis focus on how a go-collaboativ pototyp, mad up of visualization tools abl to suppot th visibility on tam mmbs actions and th (vitual) co-psnc [2005], fosts common gound dvlopmnt within woking tam. This CSCW pototyp povids also additional functionalitis, such as a shad visual spac to xchang futh infomation about coopativ task and pocss. Sval impotant findings has bn divd fom thi studis about th building of mutual undstand in convsation mdiatd by CSCW systm. Fist of all, mpiical sults showd that 90

92 Chapt 4 common gound incass ov tim givn that paticipants incasingly lan about ach oth, as wll as, about th coopativ wok pocsss. Ths findings suppot Clak s claim that common gound incass though th joint xpinc of a task ov tim [Clak, 1996]. Additionally, thy found vidnc that tamwok, which us augmntd CSCW systms (intgatd with multipl visualization tools) pfom btt than fac-to-fac tamwok. Howv, in this cas, th is also th impact of th us of a tchnology with spcific functionalitis, abl to suppot tam s job, on th goup s pfomancs. In nutshll, Convtino s studis psnt anoth impotant fnc point fo ou sach fo two cucial ason: i. focus on goup as unit of analysis (instad of dyad) and ii. Us of visualization tools to suppot common gound building. Following this body of litatu, in this wok, wb-basd agumntation tchnologis hav bn valuatd in tms of gounding constaints in od to btt figu out thi communication and mdiation abilitis. In od to do it, an agumntation systm has bn assssd by using Clak and his collaboatos modl [1991; 2002]. Additionally, in lin with Convtino s sachs, although w hav land much fom th studis of common gound in dyadic, in this sach, th unit of analysis is th tamwok composd of mo than two mmbs pfoming a spcific coopativ task. As w a studying agumntation tools as tchnology abl to suppot dlibation and dcision making pocss, w aim at analyzing th pocss of building common gound in coopativ wok stting. In distibutd, asynchonous dlibation pocss is quit diffnt fom th knowldg xchang pocss that suppot convsations [Convtino t al., 2008] as it involvs not only ffctiv and fficint communication, but also th coodination of actions and gnation of solutions. 4.4 Gounding in Onlin Agumntation-Mdiatd Communication fo Suppoting Distibutd Dlibation Pocss On of th main advantags of cating a co-locatd tam is that its mmbs incmntally lan about ach oth and dvlop mutual undstanding ffotlssly by 91

93 Chapt 4 woking in clos coodination, via fac-to-fac mtings [Convtino t al., 2009]. Notwithstanding, Wb 2.0 tchnologis has povidd companis with nw tools and modls abl to nabl tam mmbs, gogaphically dispsd, to collaboat [Haydn, 2004] and coopat without any kind of tim and spac constaints [Camton, 2001]. In this wok, w focus on wb-basd tchnologis abl to suppot mo fficint and ffctiv distibutd asynchonous dlibation and dcision making pocss. Th main Wb s ffcts on dlibation and dcision making pocsss hav bn: i. incasing infomation accss, ii. fosting mo apid and dp dissmination of lvant infomation to all dcision maks implid in th pocss vn if gogaphically dispsd, as wll as ducing thi associatd costs [Shim t al., 2002] and iii. dawing togth a wid amount of knowldgabl and intstd individual on a scal that has nv bn imagind. In oth wods, with th intoduction of wb-basd platfoms, collaboation among tam mmbs has bcom incasingly distibutd in spac and asynchonous in tim. Notwithstanding, this gat flxibility in th stting, th ability to asily sha lag amount of data and put togth sval individuals coms with a cost that paticipants hav to ba fo maintaining and dvloping common gound. Th impotanc of common gound fo suppoting fficint communicat, collaboat and wok has bn showd in numous studis. [Clak, 1996; Convtino t al., 2005]. As alady discussd in th pvious chapts, wb-basd agumntation tchnologis appa to b th bst candidat as tchnology abl to suppot mo ffctiv and fficint distibutd asynchonous dlibation and dcision making pocss. Notwithstanding sval advantags diving fo th utilization of ths tchnologis, thy sm to b not abl to fficintly suppot f mdiation and intaction. As sachs hav mainly focusd on knowldg psntation issus in od to find suitabl knowldg fomats fo psnting uss contibutions, thy hav nglctd social and convsational aspcts of onlin intaction. Thfo, th us of agumnt maps in a collaboativ fashion implis an objctification and fomalization of convsation aound th knowldg map, as wll as th loss of a ang of mtainfomation about paticipants and th intaction pocss though which th contnt is gnatd. As with any mdiation tchnology, also in th cas of agumnt mapping tools, th loss of this mta-infomation hinds f intaction and maks convsations 92

94 Chapt 4 lss fficint [Clak and Bnnan, 1991]. Such a loss is vn high in th cas of mapping tools bcaus thy a stongly objct ath than human-ointd. Gnally, th availability of mta-infomation containd into convsational fdback dos not only mak th convsation mo plasant fom th social point of viw, but abov all it hlps to facilitat th gounding pocss, i.. th constuction of shad undstanding btwn paticipants, thus incasing th fficincy and ffctivnss of a convsation [Clak and Bnnan, 1991; Convtino t al., 2008]. In od to btt undstand th amount of th loss infomation w usd Clak s and his collaboatos modl [1991; 2002] to valuat th fficincy and ffctivnss of thm to suppot communication [Fussl t al., 2000; Kaut t al., 2002; Convtino t al., 2008]. In oth wods, w aim at assssing thi communication and mdiation abilitis. In paticula, an agumntation tchnology has bn valuatd in tms of gounding constaints that it is abl to povid uss. Indd, accoding to Clak and his collaboatos, th mo constaints a mdia may povid, th btt th mdia is fo fosting common gound building and, thus, fficint convsation. As this sach focuss on onlin distibutd, asynchonous convsation mdiatd by agumnt-basd tchnologis, th dsciptions of constaints poposd by Clak and his collaboatos [1991; 2002] has bn modifid and adaptd to ou application contxt. In Tabl 1, th list of constaints with oiginal and ou adaptd dfinitions is showd. Thus, accoding to Clak s thoy, whn popl communicat and collaboat by using agumnt mapping tools, thy hav to ba vy high gounding costs. This dpnds on th lack of numous constaints; in fact, ight out of tn constaints a missing, namly Copsnc, Audibility, Visibility, Tangibility, Mobility, Cotmpoality, Simultanity and Squntiality. Instad, in onlin agumnt mapping tools, uss contibutions can b both viwd by all uss (viwability) and visd pivatly bfo bing snt (visability). In oth wods, agumnt mapping tools do not allow uss to s ach oth, sha th sam nvionmnt, know who is (vitually) paticipating to th discussion, what uss hav don in thi past paticipations, th ply stuctu of convsation and so on. 93

95 Chapt 4 Tabl 1. Affodanc in communication mdia Affodanc Clak t al. s dfinition Ou adaptd dfinition Audibility Copsnc Cotmpoality Mobility Rviwability Rvisability Simultanity Squntiality Tangibility Visibility Paticipants ha oth uss and sound in th physical nvionmnt Uss sha th sam physical nvionmnt B civs at oughly th sam tim as A poducs Uss can mov aound physical spac B can viw A s mssag B can vis mssag fo A A and B can snd and civ at onc and simultanously. A s and B s tuns cannot gt out of squnc. Paticipants can touch oth popl and objcts in th physical nvionmnt A and B a visibl to ach oth Ou adaptation fom Clak and Bnnan [1991] and Kaut t al. [2002] Idm Paticipants a mutually awa that thy sha a vitual nvionmnt Idm Popl can mov aound in a shad vitual nvionmnt Mssag a stod in onlin positois fo lat visions Mssag stod in th positoy can b visd bfo bing snt Idm Paticipants can constuct th ply stuctu Paticipants can touch oth popl and objcts in th vitual nvionmnt Paticipants s th actions of oth uss in th shad vitual nvionmnt Compad to fac-to-fac convsations, povid lss fdback and fw contxtual cus; indd, in agumnt-basd convsations th povision of convsational fdback and contxtual cus is usually mo xpnsiv as popl a focd to us altnativ tchniqus ath than th chapst facial xpssions, postus, body signals and fnc too objcts. Put diffntly, usually convsation is a multi-modal pocss, that is it involvs mo than vbal communication, such as facial xpssions, body gstus and postus that hlp woks to communicat, undstanding ach oth and gounding what has bn said. In gnal, any convsation mdiatd by a tchnology is considd lss fficint and lss-ich than fac-to-fac convsation, bcaus it ducs th possibility to us non-vbal and lss costly communication foms. Fo instanc, in fac-to-fac convsation, intlocutos could nod in agmnt o fo showing attntion, whil in oth mdiatd convsation, such as phon-call o 94

96 Chapt 4 comput mdiatd convsation, thy hav to say o typ th wod somthing. Claly, th cost of this acknowldgmnt is high in mdiatd than fac-to-fac convsation, as woding and typing is suly had and mo costly than nodding in agmnt. Th tchniqus that popl may us fo communicating and gounding dpnds on th mdium and th constaints that it imposs on convsation. Th main ason xplaining th poo pfomanc of agumnt mapping tools in tms of gounding costs is that thy a objctd-ointd tchnologis: th pimay objctiv of an agumnt mapping tool is to gnat a knowldg objct in th fom of map abl to captu and oganiz knowldg povidd by many contibutos duing a dbat. Diffntly fom oth collaboation tchnologis, thy a not xplicitly dsignd to suppot intaction and kping tack of th communicativ acts dvloping duing th pocss. Thfo, th lack of sval constaints, objct-ointation, fomalization and disuption of th convsation ply stuctu du to spatial oganization of infomation ntails high gounding costs and consquntly difficultis in dvloping common gound and suppot fficint/ffctiv communication. In addition, bing agumnt-basd convsations asynchonous, paticipants loos also all al-tim fdback and back-channl cus that a so usful fo minimizing misundstanding and showing attntivnss. This implicats a futh collaboativ ffot to th paticipants as thy should us altnativ tchniqus to ach th sam sults (i.. typ somthing o ask a claification). Th difficultis of building common gound may pvnt uss to xploit th bnfits usually associatd to th us of agumntation tchnologis; such bnfits actually assum th availability of wll-fomd maps o at last that uss a in th conditions to cat such maps. If gounding costs a high, th chancs fo uss to cat good maps will b low, unlss substantial ffot is povidd by xtnal modatos chagd with th task of mapping in al tim th contibutions povidd by many uss. Unfotunatly modation can bcom vy costly whn th tool is intnsivly usd by a lag nough goup of uss. In od to dal with this poblm and to impov th cost/bnfit atio of using agumntation tchnology ou poposal is to dvlop an augmntd agumnt mapping tool abl to tain th taditional advantags offd by agumntation tchnologis and 95

97 Chapt 4 to dliv at th sam tim a ich st of mta-infomation aimd at fosting social intaction among uss and suppoting th constuction of mutual undstanding. W call such an augmntd Dbat Dashboad bcaus thmd-infomation is dlivd mostly though visual widgts, built upon and connctd to th agumntation tool, that a xpctd to suppot paticipant convsations. Th basic ida of th Dbat Dashboad is to mak visibl infomation that in fac-to-fac convsation is immdiatly availabl and that in comput-mdiatd communication is hiddn o missing. In th following paagaph, a modl abl to suppot and impov agumnt-basd tchnologis mdiation and communication abilitis will b intoducd and xplaind. 4.5 A Thotical Modl fo Augmnting Agumnt Mapping Tools Onlin agumnt mapping tools lav uss blind to a ang of infomation that is commonly adily availabl in fac-to-fac intaction [Smith and Fio, 2001], hamping f communication. Indd, as claimd by Clak and Bnnan [1991], whn a convsation is mdiatd by a connction tchnology, most of that infomation pomptly and ffotlssly accssibl in fac-to-fac convsation a missing. As mgd in th pvious paagaphs, this infomation is vy cucial fo succssful, ffctiv and fficint discussions sinc it fosts and hlps uss undstand ach oth and gound what has bn said with last collaboativ cognitiv ffot. Thfo, accoding to Gounding thoy, in od to nabl f, asi and smooth intaction and communication, w should mak availabl and visibl all that mta-infomation. In addition, sinc th gnal aim of this sach is to impov agumntation tchnologis mdiation and communication capabilitis and, contmpoaily, tain th advantags diving fom thi utilization, w should consid oth two citical inhnt aspcts (o limits) of onlin convsation mdiatd by ths tchnologis. 96

98 Chapt 4 Thy a: Th nd to build of uss sns of mmbship in vitual community. This aspct concns mainly inhnt chaactistics of collaboation and paticipation in onlin communitis. Indd, in litatu th is vidnc that sval onlin communitis fail bcaus of th lack of involvmnt and paticipation by thi mmbs [Kim, 2000]. Th psistnc of onlin convsation lads to infomation ovload. Indd, whn th numb of paticipants incass, th numb of contibution can b substantial, lading to cluttd and had-to-ad agumnt maps [Schu t al., 2010]. Thfo, in lin with as mgd fom cafully analysis of distibutd, asynchonous convsations mdiatd by agumntation tchnologis and fom litatu viw, in od to augmnt agumntation tools mdiation abilitis, tain th advantags diving fom thi utilization and suppot thi widspad adoption, w should povid uss with th diffnt typ of mta-infomation about: Onlin uss Intaction pocss though which th contnt is gnatd Gnatd contnt duing convsations On th basis of ths idntifid cucial lmnts fo ffctiv and fficint convsations, th diffnt catgois of fdback has bn dfind. Ths diffnt classs of fdback aim at compnsating th lost of cucial mta-infomation that may mak convsation, mutual undstanding and gounding pocss asi, cognitivly chap and smooth (Figu 6): Community fdback (who): this st of fdback allows uss to know who a th community mmbs, to visualiz th community stuctu and, in paticula, to fost th dvlopmnt of a sns of mmbship. 97

99 Chapt 4 Intaction fdback (how): this class of fdback lt uss to undstand how th mmbs of onlin community intact and what is happning in th onlin community, suppoting mutual undstanding and gounding pocss Absoption fdback (what): this fdback is about th contnt gnatd though intaction among uss and its oganization. This fdback should hlp uss mak sns of lag amount of poducd contnt. In nutshll, th basic ida is that, by poviding this fdback, popl can b aidd to communicat in btt and asi ways, to duc misundstanding and to duc cognitiv costs associatd with th us of a connction tchnology to communicat and collaboat. Figu 6. Suppoting common gound building famwok 98

100 Chapt 4 In th following paagaphs, ach indntifid class of fdback that w want to povid though nw tchnological dvic in od to suppot common gound building. Moov, fo ach class of fdback, w thn idntify th attibuts that nd to b considd in od to compnsat th lack of infomation Community Fdback By poviding this class of fdback, w aim at suppoting th dvlopmnt of a sns of community in a vitual stting and to impov th acquaintanc of oth community mmbs and knowldg about past actions of community. Indd, in litatu th is vidnc that th caus of failu of onlin community is just th lack of th sns of mmbship and blongingnss to a goup. In litatu, th is no univsally accptd dfinition of th tm sns of community, although th a sval usful and intsting concptualizations. Among ths, w show dsciptions that btt adapt also to th vitual contxt, that is thos that focus on what mmbs fl and do togth, ath than wh and though mans thy do things. Fo instanc, Ung and Wandsman [1985] dfind sns of community as fling of mmbship and blongingnss to community o a social goup. Anoth intsting dfinition is that poposd by Saason [1974] that dscibs th sns of community as th pcption of similaity to oths and th cognition of xistnc of intdpndnc with oths. Accoding to both dfinitions, th most cucial fatus of community a mutual intdpndnc among mmbs, sns of blonging, connctdnss and shad valus and goals. In thi studis, Blanchad and Makus [2002] found that th dvlopmnt and th maintnanc of th sns of community dpnds mainly on th cation of idntity and th idntification of oth mmbs. By cating idntity fo thmslvs (i.. though poviding psonal infomation o though fquncy and contnt of contibutions) and allowing th idntifications of oths, onlin community mmbs bing a community out of anonymous and invisibility. Thfo, th namlss and faclss, in sam way, a cognizd and bcom popl to whom on fl an attachmnt and mutual obligation 99

101 Chapt 4 [Blanchad and Makus, 2002]. This is a vy cucial facto that diffntiats vitual communitis fom th physical ons; indd, this distinction may dpnds on th fact that paticipants in vitual communitis can appa and fl much mo anonymous than mmbs of physical communitis. Sval sachs povid vidnc that stong flings of mmbship may not only incas paticipation in th community, but may also incas th flow of infomation and knowldg among all mmbs, coopation among mmbs, commitmnt to goup goals, mmbs ngagmnt in community activitis and satisfaction with goup ffot [Buff, 1993; Dd, 1996; Royal and Rossi, 1996; Wllman, 1999]. Thfo, in lin with this, th dvlopmnt of a sns of mmbship should pincipally implicat th incasing of uss paticipation and ngagmnt, as wll as impovmnt of goups pfomancs. In od to do it, th diffnt sub-classs of fdback hav bn povidd: Pofil: community mmbs psonal infomation, such as nam, ag, plac of bith, job/occupation, hobbis tc. Th basic ida is to suppot a btt mutual acquaintanc among mmbs and suppot th cation of idntitis fo thmslvs and th idntifications of oths. Accoding to Cutl [1996] th mo on disclos psonal infomation, th mo th oths will cipocat, and th mo individuals know about ach oth (p. 326). Social stuctu: shows social ntwok stuctu of onlin community. Th phas social ntwok fs to th st of actos and th tis among thm. In oth wods, social ntwoks a abstact visualization stuctus that hlp individuals undstand th lationship among intconnctd individuals. Social Ntwok Visualization could b dfind as on of appoach to studying collaboativ nvionmnt, as wll as collaboativ ntwok. This fdback is vy impotant bcaus allows mmbs to gath much infomation about onlin community and its dynamics. Fist, mmbs can btt know who spaks to whom and th fquncy of lationships. Additionally, thy can gath futh infomation about uss ol in th onlin community. Anoth impotant 100

102 Chapt 4 lmnts is that, by knowing us s psonal social ntwok, it is possibl to undstand and know futh aspcts about th singl uss. This fdback should lt to incas both th sns of mmbship (by visualizing own social ntwok, individuals fl pat of it) and mutual knowldg. Community s histoy (about catd contnt): holistic viw about community past activity. In this cas, uss can hav concis and compact infomation about th most cnt, popula and connctd uss contibutions. This fdback povids infomation about activity and paticipation lvl of community as whol. In gnal, this fdback aims at suppoting onlin uss to mak sns of stat of th onlin community and discussion. Th basic ida is to motivat uss paticipation by visualizing th community and th lvl of paticipation of all community mmbs, xpcting that such social visibility may stimulat uss to ngag in convsations. By paticipation w man thos activitis which th community bnfits and that indicat involvmnt in it, such as contibuting to th convsation though th cation of posts and links. Thfo, in lin with this, th povision of this fdback should cat awanss about th oth uss and aid thm to gath infomation that, in tun, should hlp thm to pitch into convsation asily and fl pomptly pat of a community. Additionally, th gathing futh infomation about oth community mmbs suppot th dvlopmnt of mutual knowldg about ach oth that may hlp popl undstand btt and, thus, gound what has bn said Intaction fdback As spcifid in th pvious paagaphs, Clak and Bnnan [1991] and Kaut t al. [2002] idntifid tn constaints that a mdium can impos on th communication btwn popl to fost mutual undstanding and gounding pocss. Whn on of ths constaints is missing, th is a high cost of th convsation, bcaus mdiation focs popl to us altnativ gounding tchniqus. In lin with this, th 101

103 Chapt 4 povision of intaction fdback aims at compnsating th lack of ths constaints that a cucial in suppoting th constuction and dvlopmnt of common gound. Following Clak and Bnnan s thoy, agumntation tchnology has bn valuatd in tms of st of gounding constaints that thy a abl to povid and, thus, in tms of gounding costs that uss hav to ba to communicat in an fficint way. Indd, as alady discussd in th pvious paagaph, in th cas of onlin agumnt mapping tools, ight out of tn constaints a missing. Whil ths platfoms lt uss to both viw (viwability constaint) and vis (visability constaint), thy do not hav th following constaints: co-psnc, audibility, visibility, tangibility, mobility, cotmpoality, simultanity and squntiality. Moov, it is ncssay to mak a pcision about what fdback w can and want to povid. Indd, of cous, w do not consid fdback aimd at compnsating th loss of Tangibility and Audibility giv th difficulty o impossibility to dliv thm in a vitual stting. With gad to th Simultanity, anoth impotant claification has to b intoducd. Accoding to Clak and Bnnan [1991], th psnc of this constaint lts paticipants to a convsation to snd and civ at onc and simultanously diffnt mssags. Fo instancs, in fac-to-fac convsation, it happns whn an individual smils duing spak s uttanc. In this cas, in th sam momnt, th is both psntation phas and accptanc phas, givn that th smil may b intptd as an signal of attntivnss and undstanding. Simultanous uttancs a possibl also by using som tlconfnc systms that show what both patis wit ltt by ltt in two distinct spac of th scn. As sach s focus is onlin asynchonous convsations, this constaint is not adquat and not possibl to th application contxt and, fo this ason, w dcid to not consid it. Thfo, by poviding this class of fdback, w aim at suppoting asi and smooth convsation, th constuction of common gound and mutual undstanding among uss. With in mind this and in lin with Clak s modl and inhnt fatus of agumnt-basd tchnologis, th povidd fdback, blonging to this class, is: 102

104 Chapt 4 Copsnc: though this fdback, uss can know who is onlin, thfo, thy a mutually awa whit whom thy sha a vitual nvionmnt. Th knowing who is onlin contmpoanously, should nabl convsation mo asily. In oth wods, this fdback may push popl to ngag a convsation with uss that a onlin, bcaus whn popl vitually mt thy a mindd about thi xistnc, know thi availability fo communication and hav th fling to b listnd. Rpatd vitual ncounts suppot th dvlopmnt of common gound. Cotmpoality: as w a focusing on asynchonous convsations, paticipants to th discussion cannot b civd mssag at oughly th sam tim as it is poducd. Whn th is this constaint popl can adily civ and undstood th mssag without dlay; instad, it is not possibl in asynchonous mdia. Th dlay maks had th constuction of common gound. By intoducing this fdback, popl can immdiatly know whth and whn a post has bn catd, ducing th tim intval among post s poduction and its cption, as wll as undstood o misundstood. Indd, if somon dos not undstand th contnt of th mssag can ask a claification and spaks at onc pai th faults. Indd, as faults tnd to snowball, spak should want to pai thm as quickly as possibl [Clak and Bnnan, 1991]. Mobility: povidd infomation concns wh onlin uss mov in th vitual nvionmnt. Claly, w should simulating uss movmnt among diffnt topics o discussion goups. This may suppot th building of common gound bcaus uss can gath futh infomation about oth mmbs, such as which discussions thy paticipat in, what a th last movmnt, what a thy favouit topics. This st of infomation shaps th basis of onlin uss common gound and that will b updatd though joint xpinc ov tim. Squntiality: in th cas of onlin agumnt mapping tools, uss contibutions a povidd in a logical ath than tim-basd psntation. Thus, th lack of th squntiality constaints is a choic. In th sam tim, this 103

105 Chapt 4 popty, which is supposd to b an impotant lmnt of onlin agumnt mapping tool, it is actually on of th majo sponsibl of disuption of smooth intaction. This happns bcaus spaks do not hav immdiat vidnc about has undstanding of thi uttancs and so thy cannot pai vntual misundstanding. This involvs a futh cognitiv ffot to gound xchangd knowldg duing a convsation. Th basic ida is to povid uss with a tmpoal psntation of convsation so that thy can visualiz th ply stuctu. W aim at intoduc a systm abl to poduc ply stuctu. Visibility: though this fdback, w want to povid uss with infomation about oth mmbs actions lativ to th spcific discussion o collaboativ task. Th infomation that w would lik to povid a som stats about uss activity, such as numb of posts and connction catd about a spcific topic. In this way, uss actions a visibl to th oth community mmbs. This should povid uss with additional infomation on th oth tam mmbs and, thus, incas common gound Absoption fdback In litatu, th is vidnc that whn th numb of paticipants incass, as consqunc, th numb of boxs and aows intnsifis and agumnt maps bcom cluttd and had-to-ad [Schu t al., 2010]. Indd, whn agumnt maps a too lag, it is vy difficult to hav an ovviw and gasp all infomation. This lads to th so-calld spaghtti imags [Hai, 1991; Loui t al., 1997]. Additionally, bcaus of pmanncy of th onlin convsation on agumntation tchnologis, ov th tim infomation and knowldg tnd to accumulat, lading to infomation ovload that, in tun, maks had uss sns-making of this wid amount of knowldg. As alady mntiond, fo ffctiv and fficint communication, popl nd to associat th sam maning fo th sam pic of infomation. Whn it occus at th community lvl, a common sns has bn built fo th nti community. Howv, aching common sns at community lvl qui a pocss of sns making. Sns making is a 104

106 Chapt 4 motivatd and continuous ffot ncssay to undstand connctions among diffnt popl, concpts and vnts, in od to anticipat thi tajctois and act ffctivly [Klin t al.,. 2006]. Th way popl mak sns of situations dpnds on thi pxisting fam (o scipts) which a intnal imags of xtnal ality [Rudoloph, 2003]. Th pupos of a fam is to dfin th lmnts of th situation, dscib thi lations, filt out ilvant mssags and highlight lvant mssags. Indd, th fam cognizs th infomation as thy bcom availabl and, in th sam tim, it is changd by thos infomation. Indd, whn popl aliz that data do not fit into th fam that thy a using, a supis is gnatd and sns making stats to modify th fam o plac it with a btt on. In oth wods, though th sns-making, popl stuctu th unknown [Watman, 1990]. Th poblm is that whn agumnt maps bcom too lag and thfo, had-to-ad, not cla and undstandabl to paticipants, thy a not so abl to suppot th sns making pocss [Slvin and Buckingham Shum, 2009]. Claly, th lack of suppot fo uss sns-making pocss implicats a high complxity in th constuction of mutual undstanding and gounding pocss. Indd, sns-making can b considd a pliminay phas of mutual undstanding and of gounding pocss. Indd, as collctiv actions stat nw infomation lads to a continuous updat of individual famwoks (o fams) which in tun shifts th undstanding at a community lvl fom on stat to anoth. Thfo, suppoting individual sns-making mans suppoting collctiv common gound building. In od to tackl this poblm, w dfind this class of fdback. Indd, th povision of it aims at suppoting sns-making of convsation and hlping uss to mutually coodinat on th contnt [Clak, 1996]. In addition, absoption fdback should allow uss to undstand th stuctu of th discussion and its volution, as wll as to suppot its xploation and analysis. In oth wods, though this fdback, th usability of th knowldg-objct, that is th map, should impovs, allowing uss to pitch in th convsation in th ight plac. 105

107 Chapt 4 Th sub-classs of fdback w hav idntifid fo this catgoy a: Rlvanc: w will povid fdback that hlps uss individualiz and cogniz chunk of lvant infomation (.g. topic clusts). This fdback is vy usful whn th map dvlops and infomation accumulats, bcaus th uss hav many difficultis to mov though it and this qui a majo cognitiv ffot to thm; thanks to this fdback th usability of th map impovs, allowing uss to find topics of thi intst. In nutshll, this fdback hlps xplo a lag amount of infomation into mo managabl pics [Yi t al., 2008] and pitch in th convsation in th ight plac. Stuctuing: this fdback may hlp uss cat lations and links btwn diffnt chunk of infomation. In this way, popl can find tnds, pattns o stuctus in a hug amount of data. Though this pocdu, popl may not only find what thy look fo but also discov nw knowldg that thy did not xpct to find. Contxtualization: this fdback is xpctd to hlp individuals duc th gap btwn nw infomation and us s mntal modl, thby ducing th cognitiv load to fam th nw infomation. It is supposd to aid uss to contxtualiz nw infomation. In oth wods, it suppots popl to xtact contxtualizd infomation fom th convsational contxt and to hlp thm dcid on what infomation is lvant and what xplanations a accptabl [Salancick and Pfff, 1978]. Extactd infomation povids points of fnc fo linking idas to own psonal fam. W xpctd that incasing of mutual undstanding and impovmnts of gounding pocss dpndd on th cucial onlin convsation dimnsions, that is fdback about vitual community, intaction pocss though which th contnt is gnatd and gnatd contnt. 106

108 Chapt 4 Fist, by cating a sns of community, uss fl to blong it and sha with it valus and puposs. In this way, collaboation is mo satisfying and gatifying and uss tnd incasingly to paticipat. In lin with Clak s claim [1996], this lads to incasing of common gound as paticipants vn mo lan about ach oth, as wll as, about th coopativ wok pocsss. Scond, though intaction pocss, w aim at ducing collaboativ cognitiv ffot that uss hav to ba to undstand ach oth and gound what has bn said. Th basic ida is to allow uss gathing infomation that a lost bcaus of th lack of cucial mdia constaints. Accoding to Clak and Bnnan, th psnc of ths constaints hlps uss communicat and undstand ach oth, ducing collaboativ ffot bcaus thy lt thm to us costly convsational and gounding tchniqus. Thid, by poviding absoption fdback, w aim at suppoting sns-making of lag amount of infomation and knowldg. Indd, whn maps a too lag, it is mo complicatd gasp and mak sns of all th gnatd contnt. Individual sns-making of th convsation is th fist stp fo bing abl to fost succssful common gound building at community lvl. In conclusion, by poviding ths catgois of fdback, w aim at suppoting fficint and ffctiv common gound constuction among onlin uss involvd in distibutd asynchonous dlibation pocss. Th following paagaphs dal thooughly with how ths catgois of fdback hav bn povidd uss. As alady mntiond, ou poposal is to st up a nw tchnological dvic, th Dbat Dashboad, abl to tain th taditional advantags offd by agumntation tchnologis and to dliv at th sam tim a ich st of mta-infomation aimd at fosting social intaction among uss and suppoting th constuction of mutual undstanding. 4.6 Th dsign of th Dbat Dashboad Numous sachs hav bn focusd on th analysis of th impact of th povision of convsational fdback and hiddn infomation, by using visualization tools, on 107

109 Chapt 4 quality of discussion, its outcom and intaction pocsss among uss. Shnidman [2000] agud how disclosing pattns of past pfomancs, poviding ich fdback about uss and gnatd contnt a bst pactics fo suppoting onlin convsations. Eickson t al. [2002] discussd th impotanc of making socially-lvant hiddn infomation visibl in intactiv communitis in od to suppot smooth, flctiv and poductiv convsations though synchonous and asynchonous tools. In addition, oth pvious studis hav shown that infomation visualization tools may facilitat infomation shaing, poblm solving pocss and collaboation both in collocatd goup [Edlson t al., 1996; Ryall t al., 2004] and in mot stting [Mak t al., 2003; Auna t al., 2008]. Infomation visualization tools a abl to duc task compltion tim and incas poductivity on many infomation tival task and data analysis as wll [Hndix t al., 2000; Stasko t al., 2000; Vasamy t al., 1996] Oth sachs hav built infomation visualization systms attmpting to povid lag amount of infomation about th psnc and activity of thi uss in a consolidatd and asy-toad way [Donath t al., 1999; Vigas and Donath, 1999; Dav t al., 2004; Suh t al., 2008]. Accoding to Cad t al. [1999], th main aim of Infomation Visualization is to povid insights and hlp uss idntify tnds, pattns, unusual occuncs and mak compaisons in datasts. Infomation visualization tools could psnt a way to dictly pciv data and discov knowldg and insights [Nguyn and Zhang, 2006], to s infomation that is hiddn o unavailabl in a txtual psntation, making it appant, to hlp th ad undstand and apphnd th discussion's stuctu and histoy, to bcom familia with its community, to pmit asy and intuitiv intaction with th lag amount of infomation [Dav t al., 2004], and to xplo and to undstand th infomation [Stit t al., 2008]. In th last yas, in Human Comput Intaction (HCI) and Comput-mdiatd Communication (CMC) litatu, many sachs and pactitions popos th us of visualization tools to povid diffnt typ of infomation and fdback about vitual community, uss activity and paticipation by using diffnt mtaphos. Fo instanc, th Babbl Systm [Eickson and Kllogg, 2004] visualizs a convsational aa (a 108

110 Chapt 4 chat oom) as a cooki and onlin uss as mabls. Th mabls of activ popl a psntd na th cnt of th cooki, whil ons of inactiv popl a psntd na th piphy. Mabls outsid of th cooki symboliz popl involvd in diffnt convsation. In Chat Cicls [Vigas and Donath, 1999] popl a psntd by coloud cicls. Thy bightn whn an us dits a post and thy gow to accommodat th txt insid thm. Thy fad and diminish in piods of silnc, though thy do not disappa compltly so long as th paticipant is connctd. In subsqunt vsion of Chat Cicls (Chat Cicls II) [Donath and Vigas, 2002], th cicls mov aound th scn simulating uss movmnts among diffnt topics in th chat, laving a tac that fads ov tim. In Coti [Donath, 2002] uss a psntd as coloud ovals that bounc and bcam bight whn an us spaks though th onlin chat. Diffnt mtaphos to psnt uss past intaction and activity in foum and nwsgoups has bn usd in PoplGadn [Xiong and Donath, 1999], BulB [Mohamd t al., 2000], Communication-Gadn Systm [Zhu and Hsinchun, 2008]. Fo xampl, PoplGadn uss flows and gadn mtapho. Uss a psntd by a flow and th long thy hav bn involvd, th high th stm. Th ptals psnt th posts and initial postings a in d, whil plis in blu. Each thad (o discussion goup) is a gadn full of flows. In BulB th stms psnt th thad and thi hight psnts how long thy a activ. Th stm-had can psnt ith th dvlopmnt of thad (ach lin is a post) o us thad paticipation (ach colou is an us). Communication-Gadn Systm has two diffnt visualizations. Thad visualiz mploys a floal psntation to gaphically dpict th livlinss of a thad. Th flow psntation allows to psnt th numb of mssags (ptals), numb of paticipants (lavs) and tim duation (hight of stms). Popl visualiz mploys th sam flow, but th povidd statistics gad to th singl uss. In this psntation th flows (uss) hav th facs to diffntiat fom thad visualiz. By using intuitiv mtaphos and poxis that do not qui complx intptation, sachs a abl to povid lag amount of infomation about uss, thi paticipation, activitis and lationships that should impov systms usability and duc cognitiv ffot fo undstanding, pciving and xploing pattns and tnds in datast. Infomation visualization offs th uniqu mans that nabl uss to handl 109

111 Chapt 4 abstact infomation and facilitat cognition by taking advantag of thi visual pcption capabilitis [Nguyn and Zhang, 2006; Cad t al., 1999] and to compnsat humans limits. Though visual psntations, it is possibl fo human bings to us mo of thi pcptual abilitis in undstanding and pocssing infomation. This ability of th human mind to apidly pciv visual infomation maks infomation visualization a powful and ncssay tool fo infomation discovy. Thus, it is possibl to claim that th intntion of infomation visualization tools is to optimiz th us of ou pcptual and visual-thinking ability in daling with phnomna that might not adily lnd thmslvs to visual-spatial psntations [Chaomi Chn, 2002]. In lin with as mgd fom th litatu on visualization tools, w dcid to xploit visualization tools capabilitis and stngthns to ffctivly and fficintly povid idntifid convsational and social fdback. In paticula, w chos to dfin and implmnt a st of visualization tools built upon and connctd to th agumntation tool, that wok in a closly coupld way. This mans that multipl psntations a linkd togth in a way that any manipulation and chang of valus in agumnt map viw cats a simila chang in th linkd ons. Moov, as uss a abl to us this visual psntations also to xplo th data, w think that this will allow uss to look at data though diffnt pspctivs, pciv nw infomation and discov nw insights. Thfo, w slctd and catd a st of visualization tools that constitut th Dbat Dashboad. In accodanc with Fw [2004], th Dbat Dashboads can b dfind as a visual display of th most impotant infomation ndd to achiv on o mo objctivs, consolidatd and aangd on a singl scn so th infomation can b monitod at a glanc. It allows to visualiz lag amount of infomation and to povid fdback in a consolidatd and asy-to-ad way. Th choic of visual widgts dpnds on th nd to avoid to qui uss futh cognitiv ffot to undstand and intpt data and infomation sinc, as alady discussd, th us of agumnt mapping tools is not so simpl and without cognitiv load. Th dvlopd Dbat Dashboad is abl to povid uss with th catgois of visual convsational and social fdback, as dfind in th pvious paagaphs, about: i. uss, ii. th intaction pocss though 110

112 Chapt 4 which contnt is gnatd, and iii. th gnatd contnt. In oth wods, th main aim is to st up a Dbat Dashboad in od to aid uss to monito and mak sns of discussions, showing thm fdback about paticipants, thi activitis with spct to th convsations and th volution of th gnatd contnt. Th dashboad not only maks th data availabl in appopiat and concntatd fashion, but also psnts ths data in asy-to-follow way. Thfo, th dashboad can b sn as a mdiating systm btwn th mapping tchnologis and th nd fo infomation [Buschl, 2008]. W distilld th Dbat Dashboad fatus by building on sults of a litatu viw on Wb 2.0 tools fo data visualization. In paticula, w hav thooughly viwd thity visualization tools (mo dtails in Appndix A) and a suvy of th most famous social ntwoks, chats, blogs such as Twitt, Skyp, Facbook tc [Quinto t al., 2010]. W assssd ach visualization tools in tms of th fdback famwok potd. In th viw, w focusd pincipally on thos visualization tools alady implmntd and in us in al onlin communitis. Som of ths visualization tools a availabl onlin and us can dictly upload thi data and thn poduc gaphic psntations fo oths to viw and commnt upon (i.. s Though th viw of all ths tools w hav to cay out a quimnts analysis in od to undstand what thi ky fatus a, how thy wok, what kind of fdback thy povid, what kind of fdback is considd th most impotant in litatu, what a th bst pactics usd; in oth wods, thy psnt ou bnchmak and w usd thm to inspi th dsign and in th implmntation of th visual widgts that compos th Dbat Dashboad. In conclusion, th Dbat Dashboad is supposd to suppot uss in communicating btt and mo asily, ducing misundstandings, facilitating th gounding pocss and diminishing its costs. Moov, w xpct that th impovmnt in th gounding pocss may also impov som uss pfomancs such as fficincy and outcoms. 111

113 Chapt 4 As alady mntiond, th Dbat Dashboad has bn built upon a wb-basd agumnt mapping tool, namly Coh (an xpimntal vsion is availabl at In th following paagaphs, w dal with, fist, Coh and thn w psnt ach visualization tool that composs ou dashboad A wb-basd Agumnt mapping Tool: Coh Coh is a wb-basd asynchonous agumnt mapping tool whos pupos is to suppot on-lin collctiv agumntativ dbats. It is a Knowldg Mdia Institut tchnology, dvlopd by a tam goup composd by Simon Buckingham Shum (Tchnology Champion), Michll Bachl (Dvlop) and Anna D Liddo (Rsach Associat). Viwd though th lns of contmpoay wb tools, Coh sits at th intsction of wb annotation (.g. Diigo; Sidwiki), social bookmaking (.g. Dlicious), and mindmapping (.g. MindMist;), using data fds and an API to xpos contnt to oth svics [D Liddo and Buckingham Shum, 2010]. Coh adopts th IBIS appoach (Issu Basd Infomation Systm) [Kunz and Rittl, 1970], which allows to cat an agumnt maps (Figu 7) mad up of th ky lmnts: i. issu to b answd, ii. positions (o idas) as altnativ possibl solutions to issus, iii. suppotiv o challnging agumnts about poposd idas. With Coh uss can cat posts to xpss thi thoughts and pick up an associatd icon psnting th htoical ol of that post in th wid discussions. Moov, uss can xplicitly connct thi posts to any oth which is lvant to what thy want to say. Thy can do so by making a connction btwn posts, which xplain th htoical mov thy want to mak in th convsation. Finally, thy can cat discussion goup to convs and dbat about any kind of topic o thm. 112

114 Chapt 4 Figu 7. Coh s nvionmnt in which onlin dialogu is psntd as smantic ntwok of posts Coh allows psnting dbats in mo compact way compad to taditional txtual psntation by cating smantic ntwoks. By stuctuing and psnting onlin discous as smantic ntwok of posts Coh nabls a whol nw way to bows, mak sns of, and analyz th onlin discous. Indd, though poviding a logical ath than chonological oganization of discussions, Coh suppots th psntation of th concptual stuctu of a dbat. In addition, Coh allows flcting on concptual stuctu of dbats and thfo to suppot th uss in th answing to cucial qustions such as: What a th ky issus aisd in th convsation? How much suppot is th fo this ida? Who disags, and what vidnc do thy us? Usually, this infomation is hiddn in th f-txt contnt, thfo paticipants hav simply to ad th whol onlin convsation to mak sns of it. This psntation fomalism is supposd to impov th quality of collctiv dcision making outcom, and mo gnally, knowldg psntation and shaing as it should fost th mgnc of mo plausibl, wll-suppotd and shad conclusions about a givn poblm. 113

115 Chapt 4 Using Coh as a sach vhicl, w built on th top of it a numb of visual widgts aimd at dliving som typs of convsational fdback dscibd in ou famwok. W chos Coh as sach vhicl on which built th Dbat Dashboad fo two impotant ason. Fist, bcaus it is alady abl to povid som of ou individualizd fdback, that is lvanc, social ntwok visualization, visibility and community histoy. This implicats mino ffot to mak th platfom adaptd to ou aims. Scond, Coh is a wb-basd asynchonous agumnt mapping tool, bcaus w want to tst if ou fdback a abl to aid mot, asynchonous mdiatd convsation and suppot th gounding pocss among onlin uss. Th asynchonicity maks mot, mdiatd convsation, as wll as th gounding pocss mo complicatd. Thfo, th utilization of ou fdback in this contxt maks sns and could b vn mo appopiatd, as wll as mo challnging. In th following paagaph, w showd and xplaind ach visual widgts usd fo poviding fdback, its fatus and how it woks Th Dbat Dashboad Th gnal aim of th Dbat Dashboad is to impov agumntation systms mdiation and communication abilitis in od suppot onlin uss mutual undstanding and gounding pocss. Dawing on gounding cost thoy, a st of visual widgts has bn dvlopd abl to povid uss with missing social and convsational fdback. Each visual widgt, which compos th Dbat Dashboad, has bn dvlopd in collaboation with Coh s sach goup at Knowldg Mdia Institut, namly Michll Bachl, Anna D Liddo and Simon Buckingham Shum. This augmntd agumnt mapping tool is availabl onlin at In lin with individualizd and dscibd fdback, in Tabl 2, w show bifly how ach fdback is povidd. As mgd fom th tabl som fdbacks hav not bn implmntd bcaus of th chaactistics of th wb tchnology usd to implmnt Coh; in paticula Coh is 114

116 Chapt 4 not abl to wok in a synchonous fashion and its upgad in that diction would hav bn too costly at this stag of th sach. Tabl 2. How social and convsational fdback a povidd Affodanc Pofil Community histoy Social Stuctu Copsnc Cotmpoality Mobility Simultanity Squntiality Visibility Contxtualization Rlvanc Stuctuing Visual Widgts Us s psonal pag Ral tim Stats about catd idas Social ntwok visualization List of uss. Not povidd Not povidd Not povidd Not povidd Ral tim Stats about uss activity TagCloud sach ngin TagCloud Agumnt map Figu 8 shows Coh hom pag. As it is possibl to not, onlin uss can adily hav to accss to two impotant fdback, that is Rlvanc (d ctangl) and Copsnc (gn ctangl) fdback. Figu 8. Snapshoot of Coh s Hom pag intgatd with visual widgts 115

117 Chapt 4 If uss click on Popl&Goup button, thy can know and visualiz who is onlin. As showd in th Figu 9, a list of uss opns wh th offlin uss a indicatd by a d cicl, whil onlin uss a psntd by a gn cicl (Figu 10). This visual psntation of Copsnc fdback is usd by th most famous onlin chat systms, such as Skyp o Mssng Instant Mssaging. Though this fdback uss can know with whom thy a spaking and thy do not fl alon in th vitual nvionmnt. In oth wods, thy a awa that thy a shaing a vitual spac. Figu 9. Snapshoot of Coh Uss can know who is onlin with gads both to all community mmbs (Figu 9) and to a spcific discussion goup (i.. discussion goup on th tnd of gold pic in th shot piod Figu 10). In Figu 10, in ality, only Ivana has gn cicl. It mans that sh is onlin and sh is using Coh. If uss want to visualiz oth uss pofil and thi psonal pag has to click on uss nam. Uss psonal pag opns and it is possibl to visualiz all infomation about that uss, that is his/h psonal infomation, what and how many goup h/sh paticipats in, what idas and connctions h/sh cats and his/h social ntwok (Figu 11). 116

118 Chapt 4 Figu 10. Snapshoot of Coh Copsnc fdback (all community) Figu 11. Snapshot of Us psonal pag (Pofil fdback) By using this infomation, uss, not only, lan incasingly about ach oth, making convsation and common gound building is asi, but, fist of all, it allows uss to 117

119 Chapt 4 know oth community mmbs and cogniz thm, thus, fosting a sns of community and mmbship. Sns of mmbship is a cucial dimnsion fo th succss of a vitual community [Kim, 2000]. By clicking on TagCloud button on Coh hom pag, uss can visualiz all th TagCloud usd by th oth onlin uss (Figu 12). Th TagCloud nabls uss to s how fquntly wods appa in all Coh mdiatd convsations. Th siz of a wod dpnds on th fquncy of us of it. Th tag a usually singl wods, nomally listd alphabtically, and, as alady mntiond, th impotanc of ach tag is shown with font siz. This visual fomat is usful fo quickly pciving th most pominnt tms and fo locating a tm alphabtically to dtmin its lativ pominnc. Th basic ida is to suppot uss in xploation of an agumnt maps, spcially, whn it stats to bcom too lag o aid nwcoms in asily making sns about what topic a discussd in Coh community as thy xpss th intsts of community. Figu 12. Snapshot of Coh TagCloud (all tags usd in Coh dbats) Coh is abl to povid uss with two typs of TagCloud visualizations; in oth wods, uss can visualiz both all th tags usd in Coh dbats (Figu 12) and th top 50 tags usd in ach discussion goup (d ctangula in Figu 13). Th 118

120 Chapt 4 psntation is compact and daw th ys towads th lagst, and psumably th most impotant itms. Though this psntation th impotant lmnts a simultanously psntd, that is th wods thmslvs, thi lativ impotanc and alphabtical od [Hast and Rosn, 2008]. Notwithstanding thi advantags, TagCloud has a cucial dawback fom a pcptual pspctiv, that is it is difficult to compa all of th tags with a simila siz. In od to tackl this poblm, w add a fatus, that is whn uss oll ov th mous on ach tag, thy can visualiz th fquncy of us of that tag. Figu 13. Snapshot of Coh TagCloud discussion goup (Rlvanc fdback) Additionally, in Coh TagCloud is usd also as a sach ngin o navigation tool. Indd, if a us clicks on a tag, all th idas with that tag a sachd and visualizd. This could hlp uss to contxtualizd (Contxtualization fdback) th us of that wod and btt undstand th maning. Anoth impotant thing is that, as ach ida show its autho, uss can collct futh infomation about th oth uss, mak compaison among that pson s intsts and own on s, s what is shad and what divgs. In th Figu 14, fo instanc, a us clicks on shlt goods and th list of idas containd that tag appas. In this way, th uss can know why community spak about it, what is community ida about it, who spaks about it and so on. This fdback 119

121 Chapt 4 hlps to gasp numous infomation about Community and its discussions, suppoting thi xploation and analysis. Figu 14. Snapshot of Coh TagCloud sach ngin (Contxtualization fdback Th last two Community fdback that w psnt a: Social Ntwok Visualization (Figu 15) and Community Histoy (Figu 16). By using Social ntwok visualization, uss can gath sval infomation about discussion goup: who spak to whom: it is indicatd by th psnc of link fquncy of lationships: th width of th link psnts how much uss spak uss ol in th onlin community: w calculat th dg cntality of ach us. Dg cntality is dfind as th numb of links incidnt upon a nod (i.., th numb of tis that a nod has). Dak pink a th most connctd uss, 120

122 Chapt 4 whil th gy a th slightly connctd ons. Th most connctd uss may b th most activ and ngagd in th discussion. kind of lationships: dg colou indicats th typ of lationship and it dpnds on th pvalnc of on of th possibl links. In oth wods, if two uss mainly suppot ach oth idas and opinions, th link will b gn, if thy attack ach oth, th link will b d, it thy a nutal spct to thi mutual pspctivs, th link colou is gy. Whn th link is black mans that th is not a stong pvalnc. Figu 15. Snapshot Social Ntwok visualization Though this fdback uss can visualiz thi community and s thmslvs as pat of it. This is vy impotant to suppot th dvlopmnt of a sns of community. Anoth impotant lmnts is that, by knowing us s psonal social ntwok, it is possibl to undstand and know futh aspcts about th singl uss by considing all infomation collct though th oth visual widgts as wll. Th last Community fdback that w psnt in this sach is Community Histoy. Th aim of this fdback is to povid uss with infomation about lvl of Community activity in ach discussion goup (Figu 16). Indd, uss, by clicking on Stats tab (in 121

123 Chapt 4 ach discussion goup) and thn on Idas button, can visualiz diffnt infomation about gnatd contnt. In paticula, w povid infomation about th most connctd, cnt and popula ida, th typ of links and posts catd. This fdback povids infomation about activity and paticipation lvl of community as whol and it is supposd to hlp uss undstand if Coh community is livly and push uss paticipation. Figu 16. Snapshot Community histoy fdback Finally, th povision of Visibility fdback aims at suppoting mutual undstanding and building of common gound (Figu 17). Though this fdback, w want to povid uss with infomation about oth mmbs actions lativ to th spcific discussion o collaboativ task. W want to povid a holistic viw about uss activity, such as numb of posts and connction catd about a spcific topic. In this way, uss actions a visibl to th oth community mmbs. In od to accss to this infomation uss has to click on Stats tab and thn on Us button. As showd in th Figu 17, uss can know what th most activ uss a; in oth wods, it is possibl to visualiz th list of both th most activ connction builds and nod build, as wll as th most connctd uss. 122

124 Chapt 4 Figu 17. Snapshot Visibility fdback In conclusion, th Dbat Dashboad is a wb application intgatd with an agumnt mapping tools that povids multipl viws of a lag datast. As datast is updatd, th visualizations chang to flct th nw data. This Dashboad aims at tacking and psnting social and convsational aspcts of psistnt dbats in onlin communitis. Ou goal is to st up visualization tools and knowldg maps into a singl application that is abl to suppot and impov agumntation tchnology mdiatd convsations. Dawing on Gounding costs thoy, th Dbat Dashboad, by poviding th diffnt classs of fdback, tis to, on on hand, suppot common gound building, impov uss sns-making pocss and fost a sns of community, and on th oth hand, to tain and impov agumntation systms inhnt advantags. In th nxt Chapt, w psnt th mthodology that w follow to valuat th Dbat Dashboad and its ability to ach th fixd puposs. 123

125 Chapt 5 Expimnt Dsign and Mthodology 5.1 Intoduction Notwithstanding th sval advantags of agumntation tchnologis in suppoting dlibation and dcision making pocss [van Gld, 2003; Conklin, 2006; Kaakapilidis and Tzagaakis, 2007), thy sm to b lss fficint in mdiating and fosting onlin f intaction and communication. In this study, th focus is th ffctivnss and fficincy of agumntation tchnologis in poviding and facilitating onlin asynchonous communication among mot uss. In ality, it is impotant to not that fficint communication dos not nsu succssful onlin distibutd dlibation and dcision making pocss givn th psnc of additional quisits, such as paticipation of knowldgabl and intstd individuals, incntivs, tc. In this study, in od to addss this poblm, in lin with communicational thoy poposd by Clak and Bnnan [1991), w popos to st up a Dbat Dashboad abl to povid visual social and convsational fdback aims at impoving agumnt-basd tchnologis communication abilitis. In this Chapt, w psnt how th Dbat Dashboad has bn assssd and tstd (fild xpimnt), th usd instumnts to suvy and collct data, th mthodology usd to pfom data analysis. 5.2 Th Thotical Modl to tst Basd on litatu viw about agumntation tchnologis, in th Chapt 3 w stat th following cntal sach qustion: How to tain th advantags of agumnt mapping and impov thi mdiation capability? 124

126 Chapt 5 In od to tackl this poblm w popos to dvlop an augmntd agumnt mapping tool (th Dbat Dashboad) abl to tain th taditional advantags offd by agumntation tchnologis and to dliv at th sam tim a ich st of mtainfomation aimd at fosting social intaction among uss and suppoting th constuction of mutual undstanding. Th Dbat Dashboad is abl to dliv diffnt kinds of mta-infomation mostly though visual widgts, built upon and connctd to th agumntation tool, that a xpctd to suppot paticipant convsations. Th basic ida of th Dbat Dashboad is to mak visibl infomation that in fac-to-fac convsation is immdiatly availabl, whil in comput mdiatd communication a hiddn o missing. In this Chapt, w psnt th fild xpimnt aiming at tsting th ffct of th Dbat Dashboad, in paticula, of visual, social and convsational fdback on mutual undstanding, as wll as on common gound building and updating. Moov, in lin with as mgd in th litatu about th positiv ffct of mutual undstanding on goup s coodination, collaboation and pfomancs [Clak, 1996; Convtino t al., 2004; 2008; 2009], w aim at assssing th impact of mutual undstanding on goup s pfomancs. In paticula, w masu th diffnt dimnsions of uss pfomancs, that is: i. Quality of th Outcom (accuacy of dcision); ii. Quality of collaboation pocss (amount of shad and xchangd infomation, pcptions about collaboation tc) and iii. Usability (as of us, njoymnt, us satisfaction, pcivd usfulnss) [Davis, 1989; Vnkatsh and Davis, 2003). Anoth impotant aspct that w aim at valuating is th impact of ach visual fdback on uss pfomancs. Indd, numous sachs hav analyzd th impact of visual and convsational hiddn o missing infomation on collaboation pocss, quality of discussion, its outcom, communication and intaction pocss [Shnidman, 2000; Eickson t al., 2002; Balakishnan t al., 2008). In nutshll, w aim at analyzing th impact of th catgois of fdback on mutual undstanding and on goup s pfomancs; in tun, w want to masu th impact of mutual undstanding on uss pfomancs. In Figu 18, w show ou thotical 125

127 Chapt 5 modl that w tstd though th fild xpimnt that was pfomd with a community of aound 60 studnts at th Univsity of Napls Fdico II. In th nxt sction, th diffnt hypothss and th ational bhind thm a psntd. Community fdback Usability Intaction fdback Mutual Undstandin g Quality of Outcom Absoption fdback Quality of Collaboatio n Figu 18. Thotical modl Th Rsach s Hypothss Basd on thooughly litatu viw psntd in Chapts 3 and 4, w dfind a st of sach hypothss which hav bn tstd though a fild tst. Th sach s hypothss considd w dividd, thn, in fou blocks to invstigat spcifically th ky componnts of ou famwok. In th modl, th us of diffnt catgois of fdback is an xognous vaiabls that is usd to xplain and pdict th incasing of mutual undstanding among onlin 126

128 Chapt 5 mot uss. Dawing on Gounding Thoy [Clak and Bnnan, 1991), th amount of utilization of ths classs of fdback is supposd to mak simpl mutual undstanding and common gound building. In oth wods, by poviding this fdback, w aim at compnsating th loss of infomation that a immdiatly and asily availabl in fac-to-fac convsation. As alady discussd, any mdiatd convsation by a connction tchnologis is lss fficint than fac-to-fac convsation in suppoting gounding pocss. In addition, th loss of this mtainfomation hamps f intaction and communication. In th cas of agumnt mapping tools this poblm is wosn bcaus of futh inhnt fatus of thm that additionally hind f convsations. Thfo, in lin with as mgd fom th litatu, th sach hypothss a: H1: Community fdback impact significantly on Mutual Undstanding H2: Intaction fdback impact significantly on Mutual Undstanding H3: Absoption fdback impact significantly on Mutual Undstanding Th scond st of sach hypothss aims at valuating th impact of mutual undstanding on uss pfomancs, that is quality of outcom, quality of onlin collaboation pocss and agumnt mapping tools usability. Numous sachs hav showd that incasing in common gound among paticipants to convsation sults in impovmnt of goup pfomancs, such as coodination [Clak, 1996), communication, tam ffctivnss [Convtino t al., 2007), collaboation, quality of dcision [Convtino t al., 2008). In oth wods, common gound is paticulaly lvant fo suppoting tam of divs knowldgabl individuals collaboating on dcision making and poblm solving pocss [Convtino t al., 2007]. H4: MU impact significantly on Quality of Collaboation H5: MU impact significantly on Quality of Dcision. H6: MU impact significantly on Usability 127

129 Chapt 5 In lin with th litatu that mphasizd th ffct of povision of hiddn and/o lacking infomation on quality of discussion, uss intaction and quality of th outcom of collaboation pocss, w ty to valuat th impact of ou fdback on uss pfomancs. Indd, sval studis hav analyzd th positiv impact of visualization tools and, hnc, of visual mta-infomation on uss abilitis to pciv nw and futh infomation, pattns and tnds [Donath t al., 1999], convsation poductivity [Eickson t al., 2002], knowldg shaing [Edlson t al., 1996; Ryall t al., 2004], data xploation and navigation [Xiong and Donath, 1999]. Thfo, accoding to it, th st of sach hypothss is: H7: Community fdback impact significantly on Quality of Collaboation H8: Community fdback impact significantly on Quality of Dcision H9: Community fdback impact significantly on Usability H10: Intaction fdback impact significantly on Quality of Collaboation H11: Intaction fdback impact significantly on Quality of Dcision H12: Intaction fdback impact significantly on Usability H13: Absoption fdback impact significantly on Quality of Collaboation H14: Absoption fdback impact significantly on Quality of Dcision H15: Absoption fdback impact significantly on Usability Finally, th last st of hypothss that ou sach aim at valuating is about th ol of mutual undstanding. In oth wods, accoding to sval sachs, incasing of mutual undstanding impovs uss pfomancs. In lin with this, w think that mutual undstanding can hav a ol of catalyst btwn visual fdback and uss 128

130 Chapt 5 pfomancs. In oth wods, w xpctd that mutual undstanding could stngthn th positiv ffct of visual fdback on uss pfomancs, that is on quality of collaboation, quality of dcision and agumntation tchnologis s usability. H16: Mutual Undstanding will mdiat th lationships btwn Community fdback and Quality of Collaboation H17: Mutual Undstanding will mdiat th lationships btwn Community fdback and Quality of Dcision H18: Mutual Undstanding will mdiat th lationships btwn Community fdback and Usability H19: Mutual Undstanding will mdiat th lationships btwn Intaction fdback and Quality of Collaboation H20: Mutual Undstanding will mdiat th lationships btwn Intaction fdback and Quality of Dcision H21: Mutual Undstanding will mdiat th lationships btwn Intaction fdback and Usability H22: Mutual Undstanding will mdiat th lationships btwn Absoption fdback and Quality of Collaboation H23: Mutual Undstanding will mdiat th lationships btwn Absoption fdback and Quality of Dcision H24: Mutual Undstanding will mdiat th lationships btwn Intaction fdback and Usability In Figu 19 w show ou thotical modl whit th hypothss that w want to tst by pfoming a fild xpimnt. 129

131 Chapt 5 Us of Community fdback H7 H1 H8 H9 H12 H6 Usability Us of Intaction fdback H2 Mutual Undstanding H5 Quality of Dcision H3 H10 H11 H15 H4 Us of Absoption fdback H14 Quality of Collaboation H13 Figu 19. Thotical modl with hypothsis 5.3 Expimnt Dsign: A Fild Tst In od to xamins th sach hypothss discussd in th pvious paagaph, in this sction w dal with th fild tst and ach its phas. A fild tst has bn pfomd in Jun of 2011 at th Univsity of Napls Fdico II (Italy) with a total community of mo than 60 studnts. Uss w gaduatd studnts who paticipatd in a singl-facto, asynchonous, wb-basd goup dcision-making xpimnt; in oth wods thy w askd to dlibat and focast th valu of two conomic vaiabl (mo dtails about th task and th topic of dbats will b discussd lat in this Chapt). Th studnts w all pat of a sam class fom a gaduat pogam (Economics and Businss Oganization cous) in Industial Engining, ag Th paticipation has bn facultativ and voluntay and 130

132 Chapt 5 paticipants to th xpimnt w compnsatd with xta acadmic cdits. Invitably, this ld studnts to fl th xpimnt as a cous task fo which thy will b valuatd by pofsso. In addition, studnts know ach oth and this could sults to som typ of social pssus fo thi fllow studnts. All ths cicumstanc mad th application contxt diffnt fom an opn and distibutd onlin community and psnt a significant limitation of this sach. As w aim at masuing th impact of th visual fdback on common gound and gounding pocss, as wll as on uss pfomancs, w nd to us a btwn subjct xpimnt dsign with two diffnt goups. In oth wods, w nd to compa th uss mutual undstanding and pfomancs diving fom th utilization of two diffnt agumntation systms, that is on abl to povid visual fdback and anoth that dos not povid it. Th basic ida bhind a btwn subjct xpimntal appoach is that paticipants can b pat of th tatmnt goup o th contol goup, but cannot b pat of both. This typ of dsign is oftn calld an indpndnt masu dsign bcaus vy paticipant is only subjctd to a singl tatmnt. This lows th chancs of paticipants suffing bodom aft a long sis of tsts o, altnativly, bcoming mo accomplishd though pactic and xpinc, skwing th sults. Moov, this appoach has bn oftn usd to avoid th cayov ffcts that can occu in within subjcts dsigns, such as laning, pactic and fatigu ffcts. Th poblm of this xpimnt dsign is that it dos not allow to compltly contol th diffncs among paticipants. Notwithstanding, in od to annul th influncs of lvant diffncs btwn two goups on th sults, th tatmnt and contol goups hav to b matchd o homognizd. To do it, w pfomd a andom assignmnt of subjcts to two conditions (tatmnt and contol goup). In lin with xpimntal quimnts, studnts hav bn dividd in two goups (A and B). Each goup usd a diffnt vsion of Coh platfom duing th xpimnt. Indd, th goup A usd th so-calld Augmntd Coh vsion ( that is an agumnt mapping tool intgatd with a st of visual widgts abl to povid social and convsational fdback. Th goup B, instad, usd th Pistin Coh vsion ( that is an agumnt 131

133 Chapt 5 mapping tchnologis without any kind of visual fdback. Both th vsion has bn co-dvlopd with th sach goup of Knowldg Mdia Institut, composd of Simon Buckingham Shum, Anna D Liddo and Michll Bachl. In conclusion, th goup A is th Tatmnt goup, whil th goup B is th contol goup. Th tst dvlopd in fiv phass: i. Idntification of domain of dcision making task ii. Ppaatoy wok iii. A two wks piod, in which studnts w qustd to populat th platfoms with contnt and collaboativly mak a dcision iv. Follow-up qustionnai v. Data analysis Th idntification of th domain was not so simpl, bcaus many diffnt vaiabl should b simultanously considd. Fist of all, it should b somthing along th continuum btwn a simpl lab task and a al wold poblm. On th lft sid of th continuum w find mud mystis. On th ight sid, th is mo alistic cas such as th diagnosis of a a disas. As th paticipants to th xpimnt a undgaduat studnts of Economics and Businss Oganization cous, w cannot us too alistic issus givn that thy quis th involvmnt of al pofssionals. Thfo, taking in account this, w considd conomic o businss poblms givn that studnts hav th ncssay skills and knowldg to wok on th task. Additionally, w considd also th following list of gnal constaints and dsidata to idntify th domain: 1. Indpndnc fom th fomalism: th poblm should b nutal to th fomalism, i.. no candidat fomalism should b claly btt than th oths to psnt th chosn poblm (fo instanc, agumntation can b a btt 132

134 Chapt 5 fomalism to psnt lgal asoning bcaus of th agumntativ tadition psnt in this domain), 2. Comptnc: th subjcts w involv in th study should hav th ncssay backgound, skills and motivation to ngag in th solution of th poblm, 3. Applicability: th poblm should b as much as possibl na to a alistic choic ath than to a fictitious choic poblm typically usd in lab xpimnts, 4. Contol: a solution xists and w hav to know it. 5. Richnss and divsity of infomation: w nd a domain allows studnts to discuss and confont ach oth. 6. Amnabl to modlling: It must b possibl to modl solutions in th domain with som dg of accuacy. 7. Attactivnss: th topic/poblm should attact th intst of studnts, othwis, a possibl ffct could b a low paticipation at. Indd, as th valuation tst will not b synchonous and in an univsity lab, w could not contol and ncouag th paticipation; thfo, w hav to find diffnt motivational lv to stimulat studnts paticipation and involvmnt. In accodanc to ths constaints diffnt possibl poblms w poposd, such as to focast th makt sha of a poduct o an innovation tchnology at a givn dat, i.. FIAT makt sha o % of lctic/hybid FIAT cas sold in th shot piod o % of sold ipad 2 in Amica in on month. At th nd, th slctd poblms w conomic poblms, that is th focasting of th tnd of an conomic vaiabl in th shot tim (th months). In paticula, goup A has had to focast th tnd of gold pic, whil th goup B has had to focast th tnd of oil pic. Both th slctd poblms spct th abov mntiond constaints. Spcifically, both poblms sm to b indpndnt fom th fomalism and conomic analysis dos not sm to b btt don with agumnt mapping tool (1); involvd subjcts, in pat, alady hav th ncssay 133

135 Chapt 5 knowldg and skills bcaus of thi Univsity pogam and, in pat, futh knowldg and backgound skills hav bn taught though th cous (2). As w ask uss to focast th tnd of an conomic vaiabl in th shot piod, a ight answ xists. Additionally, numous infomation that studnts can us to suppot thi choic a availabl and f on th wb ( (4). In od to favouit th ichnss and divsity of infomation, duing th Economics cous w povidd studnts with additional matials about th spcific topic that was slctd. Notwithstanding, all th studnts civd th sam infomation and knowldg duing th cous, w xpctd a som dg of divsity in knowldg psntd in th agumnt map as it is supposd that th studnts sach and gath futh infomation on th discussion matt (5). Finally, th topic is not intinsically intsting fo studnts, but motivation can b incasd by cognizing som xta points to th studnts that paticipat to th xpimnt fo th final xam gad. Finally, w chos two diffnt topics to b assignd to ach goup of studnts to avoid any xchang of infomation among studnts blonging to diffnt goups as w aim at vifying if, at th nd of xpimnt, th goups achiv diffnt pfomancs. In th ppaatoy phas, studnts had fou 2 hous sminas about: Collctiv intllignc and its cunt applications Agumntation thoy, with focus on IBIS appoach and agumnt-basd tchnologis th Gold and Oil Makts. Th studnts w also givn fw ading matials and wbsits about discussion topics to stat to gain an ovviw of thm. Th aticls w takn fom nwspaps and magazins (i.. Economist, IlSol24O, Tims). An instuctional dmo of Coh. 134

136 Chapt 5 Additionally, a wam up phas of on wk was pfomd duing which uss could us and pactic with th tool on a diffnt topic. In paticula, studnts discussd on topical agumnt, that is about th us of nucla ngy and th building of nucla plant in Italy. W chos this subjct bcaus it is contovsial, so that community could xplo diffnt pspctivs and solutions and bcaus it is a topical subjct, so that studnts can asily accss to infomation. Duing this phas, studnts can pactic and lan to us th agumntation fomalism, which, usually, qui uss to climb a stp laning cuv. As th xpimnt lastd two wks, w wantd to avoid that studnts usd that piod to bcom quit skilld at using th tool, but w wantd that thy focusd on th collaboativ task and on th discussion. As alady mntiond, two goups (A and B) of studnts paticipatd in a singl-facto, asynchonous, wb-basd goup dcision making xpimnt. Each goup wokd on a spcific collaboativ dcision making task fo two wks. Duing ths two wks, th goups dvlopd and wokd on a collaboativ map that flcts us knowldg, pspctivs and opinions, as wll as suppots collctiv dcision making pocss on a spcific task. In paticula, studnts of goup A discussd about and focastd th tnd of Gold Pic, whil goup B dbatd and pdictd th tnd of Oil pic. Instad of giving studnts mpty maps, a fist lvl of qustion and idas (possibl solutions) w povidd at th bginning. In paticula, th qustions w: What will b th tnd of Gold/Oil pic in th shot piod (t months)? Th possibl answs w: i. Th pic will tnd to incas, ii. Th pic will tnd to duc, and iii. Th pic will b stabl. By using agumnt mapping tools, uss can psnt contntious and/o compting point of viws in cohnt stuctus mad up of altnativ positions on an issu at stak with thi associatd chains of pos and cons agumnts. Finally, th xpimnt has bn un in an asynchonous way in od to: i. spct Coh fatus, ii. allow studnts to incmntally cat a map, iii. stimulat paticipants to xtnaliz all thi knowldg, and iv. lt uss to xplo a big nough dcision spac and thfo mak a mo accuat and wll-suppotd dcision. 135

137 Chapt 5 At th nd of th xpimnt, all paticipants compltd a follow-up qustionnai (mo dtails in Appndix B) composd of 28 itms (7-point Likt scal). W thooughly psnt and xplain constuction pocss of th qustionnai in th nxt paagaphs Masumnts As discussd in th fist sction, ou thotical modl consists of svn vaiabls, that is: 1) us of Community fdback; 2) us of Intaction fdback; 3) us of Absoption fdback; 4) Mutual Undstanding; 5) Quality of onlin collaboation; 6) Quality of dcision; 7) Agumnt mapping tool Usability. Th masumnt of this vaiabls is discussd blow. Th fist th vaiabls concn th us of th diffnt catgois of visual, social and convsational fdback that th Dbat Dashboad is abl to povid. As this fdback a masud and codd in th sam way, in this paagaph hncfoth, w f to ths th catgois of it by using a mo gnal tm, namly Us of Fdback. This vaiabl has bn masud though th fquncy of us. In oth wods, w aim at knowing whth and how many tims studnts us ach catgois and, hnc, sub-catgois of individualizd fdback. As alady mntiond pviously, th sach vhicl usd in this xpimnt is Coh. Unfotunatly, Coh is not abl to cod and tack all uss activity o thi xploation and navigation activity, but it can only gist whn uss accss to and xit fom th systms (log in and log out) and whn cat a nod o a link. Givn that w ndd to know whn studnts us th fdback, w had to mploy a systm abl to gist and tack uss bowsing in Coh. In od to do it, w scan and viw diffnt systms abl to tack studnts activity, such as wb analytics softwa (i.. Googl Analytics, Yahoo! Wb analytics, StatCount), systms of contnt-contol and scn vido captu softwa (i.. Camtasia). Each of this systm was not suitabl spct ou aim. In paticula, wb analytics softwa povid collctd and codd data in agggat way, instad w nd to know this data fo ach studnts. Systms of pantal contol do 136

138 Chapt 5 not allow to tack all diffnt uss activitis, but mainly thy a wb filting softwa. Finally, th us of scn vido captu softwa would hav quid a vy long tim to viw and xamin mo than 60 vidos (bcaus th a mo than 60 paticipants) of sval hous. Fo instanc, Camtasia would hav allowd a vy dply analysis of uss bhavious that it is not ncssay in this phas of th xpimnt. Additionally, if uss had usd systms of contnt contol o scn vido captu softwa, at th nd of th xpimnt, thy would hav had to snd us thi tackd and codd infomation, quiing to th studnts a futh wok and making mo complicatd ou data collction. In lin with this, w dcidd to us a Vitual Machin that was dvlopd by a sach goup of Univsidad Calos III d Madid, composd of Ablado Pado and Dick Lony. A Vitual Machin is a compltly isolatd gust opating systm installation within a nomal host opating systm. A Vitual Machin is a softwa implmntation of a machin (i.. a comput) that xcuts pogams lik a physical machin. It povids a complt systm platfom which suppots th xcution of a complt opating systm (OS). Thfo, studnts hav installd th Vitual Machin on thi computs and thy usd it to wok and bows in Coh. As only goup A usd th augmntd Coh vsion, w ndd to tack and codd only thi us of visual fdback; hnc, w askd only to paticipants of goup A to install it. All tackd and codd data a snt and stod to a cntal sv of Univsidad Calos III d Madid. Th Vitual Machin lts to tack and gist all th URL that uss usd. Fo this ason, w askd to Coh s dvlops that any fdback was idntifid by a Wb pag, that is, by its own URL. This atific has mad possibl th counting of individual viws, and thfo th quantification of th us of ach individual fdback by vy us. At th nd of th xpimnt, w had a complt databas of all vitual movmnts in Coh mad by th paticipants duing th two wks and, consquntly, has mad possibl a sis of quantitativ analysis latd to th us of ach individual fdback povidd. Th most cntal vaiabl of ou thotical modl is Mutual Undstanding. In litatu it is possibl to distinguish two main tchniqus to suvy and masu mutual 137

139 Chapt 5 undstanding and common gound building, that is though th contnt analysis o contnt stuctual analysis [Bs t al., 2007; Bs t al., 2006; McCathy t al., 1991; Suths, 2006] and though post-sssion qustionnai [Convtino t al., 2005; 2007; 2008; 2009; McCathy t al., 2001; Monk and Watts, 2000; Whittak t al., 1998]. Contnt analysis suffs fom sval disadvantags, both thotical and pocdual. In paticula, contnt analysis can b xtmly tim consuming, xpnsiv and laboious, is pon to incasd intptation and subjctivism o, may b oftn dvoid of thotical bas, o attmpts libally to daw maningful infncs about th lationships and impacts implid in a study, may b inhntly ductiv, paticulaly whn daling with complx txts, oftn disgads th contxt that poducd th txt, as wll as th stat of things aft th txt is poducd [Wimm and Dominick, 2010]. Fo ths asons, w dcidd to us post-sssion qustionnai to masu and suvy mutual undstanding and its building ov tim. Indd, post-sssion qustionnai is lss tim consuming and xpnsiv and duc possibl intptation o by valuatos. Additionally, w dcidd to us this suvy instumnt (qustionnai with 7-point Likt scals) bcaus, in this way, w can us it to masu also th oth vaiabls of th modl. Finally, th last vaiabls of modl to consid a uss pfomancs, in paticula: Quality of onlin Collaboation: this vaiabl has bn masud though a quantitativ masumnt, namly numb of catd connctions and though post-sssion qustionnai (7-point Likt scals). Spcifically, w can know th numb of catd connctd by uss bcaus Coh platfom is abl to cod uss activitis with gad to th nods and link cation. As w want to masu th quality of collaboation, w consid, fo this vaiabl, only th cation of link among diffnt uss nods. Th cation of link can b considd as a poxy of collaboation, bcaus cation of link may b mant as knowldg xchangd and pspctivs and idas shaing. Fo this ason, w do not consid link that uss cat among thi own nods. In paticula, w usd two masus: Infomation boking and Compad thinking. In oth wods, sinc conncting is an xplicit, flctiv act in Coh, it is staightfowad to 138

140 Chapt 5 count how many tims studnts cat smantic connctions btwn nods authod by oths (Infomation boking). Though ths analytics, w can th dg to which uss act as infomation boks btwn oths. With fnc to Compaing thinking statistic, it counts th connctions in which th link autho is also autho of on of th two connctd posts. Quality of Dcision: this vaiabl was masud though 7-point Likt scals and though a quantitativ masu, that is th accuacy of studnts fosight by compaing goups dcision (i.. th pic will incas, th pic will duc and th pic will b stabl) and al pic. Usability: this vaiabl was masud by using post-sssion qustionnai. Th itms usd to masu this constuct w mainly adaptd by Davis poposal [1989] and its subsqunt modifications. Claly, th instumnt usd to captu and masu Coh s Usability has bn contxtualizd to th study. Fo this ason, w consid also oth simila woks fo dfining th latd itms [Vnkatsh and Davis, 2000; Vassilva and Sun, 2007, Convtino t al., 2007; Daily- Jons t al., 1998; Vnkatsh, 2000]. Accoding to as mgd in this paagaph, thfo, w usd th diffnt databas to tst ou hypothss, in paticula: 1. Coh databas. It includs all data gading uss activitis pfomd on Coh platfoms (goup A and goup B). 2. Post-sssion qustionnai databas. It includs data collctd though th follow up qustionnai administd to all paticipants at th nd of th xpimnt (goup A and goup B). 3. Vitual Machin databas. This databas contains only data latd to studnts of Goup A. By using th vitual machin, th us of ach fdback has bn tackd and codd though thi spctiv URLs. It was possibl, bcaus ach visual widgt, by which w povid diffnt individualizd fdback, has an own wb pag and, thus, an URL. 139

141 Chapt Post-sssion Qustionnai A suvy instumnt was usd to collct data in this sach. A suvy is a mans of gathing data and infomation about th chaactistics, opinions and attituds of a goup of individuals [Tanu, 1982]. In paticula, w dvlopd a post-sssion qustionnai which was administatd to all paticipants at th nd of th two wks duing which uss wokd, collaboatd and discussd about thi dcision making tasks by using Coh. Though th qustionnai th fou latnt constucts w invstigatd. Each constuct masus on vaiabl of thotical modl, namly Mutual Undstanding, Quality of onlin collaboation, Quality of Dcision, Coh s Usability. Th qustionnai is composd of 28 itms goupd in clusts, on fo ach of th masus mntiond abov. A Likt scal is a typ of psychomtic spons scal oftn usd to obtain paticipant s pfncs o dg of agmnt with a statmnt. In paticula, spondnts hav to indicat thi lvl of agmnt with a givn statmnt by using an odinal scal. Th point scal angs fom Stongly disag to Stongly disag. Most commonly usd is a 5-point scal, but w us a 7-point scals to add additional ganulaity. Th itms of ach constuct hav bn dfind on th basis of litatu on common gound building in mdiatd convsation, onlin collaboation and Tchnology Accptanc Modl. In paticula, Tabl 3 dscibs th 28 qustionnai itms, th 4 clusts and th soucs fo ach clust. As showd in th tabl, th Quality of onlin collaboation and th Mutual Undstanding a masud both by 9 itms (spctivly Q1-Q9 and Q14-Q22), Quality of Dcision by 4 itms (Q10-Q13) and Usability by (Q23-28). 140

142 Chapt 5 Tabl 3. Qustionnai itms, Constucts and main soucs # Qustionnai itms Constucts Soucs Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 Q19 Q20 Q21 Q22 Q23 Q24 Q25 Q26 Q27 Q28 Th intaction lvl dvlopd duing Coh-mdiatd convsation was satisfying I found th onlin discussion intsting and ngaging Collaboation was ffctiv to solv assignd poblm I found it difficult to kp tack of th convsation Th agumnt map was hlpful in facilitating knowldg shaing among tam mmbs I shad my own knowldg about th task with my tammats I found that my tammats hav shad own thi knowldg about th task Th goup dvlopd a good amount of wok Th goup mad a good job I think that, at th nd of onlin dbat, th goup has a common position about th discussion topic What is you initial dcision bfo discussing with oth goup mmbs? What is you dcision at th nd of onlin dbat? What is goup s dcision at th nd of th discussion? In gnal, I hav not had poblms to undstand th maning of oth tam mmbs posts In gnal, I think that th oth tam mmbs hav undstood my contibutions without difficulty I could asily undstand (tll) what my tammats had don on Coh I could asily undstand who has don what I could asily say who is onlin on Coh My tammats and I dvlopd btt undstanding about ach oth ov th two wks My tammats and I dvlopd shad undstanding about th task ov th tim I found onlin convsation is oftn dundant I found th a many ilvant posts spct th assignd task Intaction with th systm dos not qui a lot of my mntal ffot I find th systm to b asy to us I njoyd collaboating with my tammats using Coh I would njoy woking with my tammats again using Coh It was asy to communicat ffctivly givn th tools availabl Coh suppots and facilitats collaboation among onlin uss Quality of onlin Collaboation (QofC) Quality of Dcision (QofD) Mutual Undstanding (MU) Usability (Usab) Slln t al., 1992 Vandgiff, 2006 Adaptd fom: Daily-Jons t al., Convtino t al., 2007 Vandgiff, Monk and Watts, 2000 Whittak t al., 1998 Adaptd fom Convtino t al., 2004; 2007; 2008; 2009 McCathy t al., 2001 Vnkatsh and Davis, 2000 Vassilva and Sun, 2007 Convtino t al., 2007 Daily-Jons t al., 1998 Vnkatsh,

143 Chapt Data Analysis Mthodology This sach maks us of Stuctual Equation Modlling (hncfoth SEM) to analyz th thotical modl psntd in th pvious paagaphs. SEMs a multivaiat tchniqus combining aspcts of multipl gssion (xamining dpndnc lationships) and facto analysis (psnting unmasud concpts with multipl vaiabls) to stimat a sis of intlatd dpndnc lationships simultanously [Gfn t al., 2000, p. 72]. SEM has sval advantags ov fist gnation tchniqus lik pincipl componnts analysis, facto analysis, disciminant analysis, and multipl gssion. Fist, SEM allows sachs to modl lationships among multipl pdicto and cition vaiabls [Chin, 1998]. Scond, SEM lts to xamin a sis of dpndnc lationships simultanously. In oth wods, a hypothsizd dpndnt vaiabl can bcom indpndnt vaiabls in a subsqunt dpndnc lationship. Instad, th main multivaiat gssion allow to xamin only singl lationship at a tim [Hai t al., 2006]. Thid, SEM nabls sachs to masu latnt (unobsvabl) vaiabls. Finally, SEM allows sachs to assss th masumnt modls and stuctual modls simultanously. Thus, masumnt os can b analyzd as pat of th modl. Ths attibuts nabl sachs to answ a st of intlatd sach qustions in a singl, systmatic, comphnsiv analysis [Gfn t al., 2000]. Consquntly, SEM is wll suitd to modlling complx pocsss [Gfn t al., 2000] such as common gound building. Rsachs hav two mthods of SEM analysis to choos fom. Rsachs can us covaianc-basd SEM o thy can us patial last squas-basd SEM. PLS was chosn ov covaianc-basd SEM bcaus PLS suppots xploatoy sach and th data distibution assumptions of PLS a lss stingnt than th assumptions bhind covaianc-basd SEM [Andson and Gbing, 1988]. Also, PLS is capabl of assssing indict ffcts such as th ons in hypothss H16-H24 [Chin t al., 2003]. SEMs [Bolln, 1989; Kaplan, 2000] includ a numb of statistical mthods that allow to stimat th lationships, as dfind in a thotical modl, which connct two o mo latnt complx concpts (latnt constucts), masud by a numb of obsvd vaiabls (manifst vaiabls). Thy psnt a point of union btwn xploatoy 142

144 Chapt 5 facto analysis [Thuston, 1931] and th path analysis [Tuky, 1964; Alwin and Haus, 1975]. Path modls a considd a logical xtnsion of th gssion modls bcaus thy involv th analysis of simultanous multipl gssion quations. Indd, whil a path modl is a lational modl with dict and indict ffcts btwn th obsvd vaiabls, multivaiat multipl gssion modls tak into account only th dict lationships btwn indpndnt vaiabls and th dpndnt vaiabls. In SEM, whn vaiabls within modl a latnt, and thfo masud by manifst vaiabls, th path analysis [Wight, 1934] aims at computing th impact of ach manifst vaiabl on latnt ons though th so-calld path cofficints. As alady mntiond, in this sach, w usd Patial Last Squa Path Modling (PLS-PM) o Patial Last Squa appoach to SEM (SEM PLS). This mthod was dvlopd as a flxibl tchniqu fo th tatmnt of a vast amount of data chaactizd by missing valus, highly colatd vaiabls and small sampl siz compad to th numb of vaiabls. Ths stuctual quation modls w bon to b initially applid to th mtic vaiabls, which a chaactizd by th xistnc of a unit (o account), thn thy w thn applid to wll-dfind odinal vaiabls as wll. SEM tchniqus can b sn as th sult of two sach aa, an conomtic pspctiv, whos main focus is on pdiction, and a psychomtic pspctiv, whos thotical constucts a latnt vaiabls (unobsvd) that a indictly stimatd fom th obsvd masumnts o manifst vaiabls. Th constitunt unit of a stuctual quation modl is th gssion quation (in th SEM is dfind stuctual quation) and xpsss, though th mathmatical fomalization, th lationship btwn a dpndnt vaiabl and sval indpndnt vaiabls. By a mathmatical viw, th stuctual quation modls can b xplaind though a st of systms of lina quations (1), ach of which psnts a causal link among vaiabls. In oth wods, thy a a st of causal lationships among vaiabls, fomalizd, as a whol, though a systm of algbaic quations, on fo ach dpndnt 143

145 Chapt 5 vaiabl, wh th latt is xpssd as a function of th indpndnt vaiabls that affct it:.... (1) Each of ths quations xpsss th lationship btwn a dpndnt vaiabl (tagt of a on-way aow) and a numb of oth vaiabls. Th ight sid of quation is mad up of th indpndnt vaiabls that affct and xplain th dpndnt vaiabl (lft sid) and b cofficint, whos valu say how much th dpndnt vaiabls dpnds on ach of indpndnt ons. Th scond mmb of th quation is hnc givn by th sum of its pats as th a vaiabls which act on th dpndnt vaiabl containd in th fist mmb of quation. Each lmnt of ight sid of quation is th sult of th poduct of ach indpndnt vaiabl (i.. in th gaph is th stating point of th aow) fo th ths summands that a mad by th poduct of ach indpndnt vaiabl (stating point of th aow) fo th cofficint associatd to th lationship (i.. in th gaph th lationship is psntd by th aow). In addition, as a final lmnts, it should b addd to th stochastic o. Th quations a as many as th dpndnt vaiabls. This appoach is th only tuly appopiatd to povid a psntation of complx al pocsss, although it is a simplifid modl. In fact, it taks into account not only th multiplicity of causs (indpndnt vaiabls) that act on a dpndnt vaiabl (multivaiat analysis), but also th connctions among th diffnt causs. Th al pocsss should b intptd as a complx ntwok of lations among vaiabls; on of th stngthns of this appoach is just th possibility to dfin th stuctu of this ntwok by using systms of quations (fo this ason, Stuctual Equation Modlling). 144

146 Chapt 5 As consqunc, ach quation of systm is calld stuctual quation and b cofficints a dfind stuctual paamts. On of th ason that ncouagd us to us this statistical modl to valuat and tst th sach hypothss is that th vaiabls can b, in th sam stuctual quation modl, both dpndnt and indpndnt, that th indpndnt vaiabl in an quation can b dpndnt in anoth. By using conomtic tminology, w should us xognous and ndognous tms to indicat th vaiabls, wh th fist a thos outsid th modl, and thfo, can only act as indpndnt vaiabls, whil ndognous vaiabls, bing intnal to th modl, can, altnativly, b, in diffnt quations, dpndnt o indpndnt vaiabls (in any cas, th ndognous vaiabls has at last to b dpndnt in an quation). Th xognous vaiabls a also calld p-dtmind vaiabls, to undlin th fact that thi valu is dtmind outsid th systm of quations (not xplaind by th modl) and do not dpnd on intnal vaiabl to th modl o os. Th stuctu of a stuctual quation modl is dfind by: i. th cofficints b, ii. vaiancs and co-vaiancs of xognous vaiabls (X) and iii. th o vaianc and covaianc (). Th stuctual paamts, that xpss th stngth of causal lationships btwn vaiabls, a dividd into cofficints γ and cofficints β; this distinction dpnds on whth thy lat to causal links fom xognous vaiabls (makd with X) o ndognous (makd with th Y). Th cofficints γ and β dfin th stuctu of lations btwn th diffnt ndognous vaiabls (Y) and btwn X and Y. In addition, whil vaiancs and co-vaiancs of xognous vaiabls dfin th stuctu of lations among thm, vaiancs and co-vaiancs of o dfin th stuctu of lations among thm: Th gaphical psntation of th stuctual quation modls uss th sam symbols intoducd by path analysis. Th citia that govn th gaphical psntation of a stuctual quation modl a th following: 145

147 Chapt 5 Th latnt vaiabls, also known as thotical constucts a usd to psnt thos aspcts of a phnomnon that cannot b dictly masud. Ths vaiabls can b ith xognous, if indpndnt in th whol systm of quations psnting th modl, o ndognous, if at last dpndnt fom an quation and a psntd by a cicl o llips; Th manifst vaiabls, which cospond to th masuabl aspcts of a phnomnon, which a usually dtctd by a qustionnai, a psntd by a squa o ctangl; Th dict lationship btwn two vaiabls is indicatd with a pointing aow that is dictd fom indpndnt vaiabl (caus) to dpndnt vaiabl (ffct). Each SEM is mad up of two sub-modls: Stuctual Modl (o Inn Modl) and Masumnt Modl (o Out Modl). Stuctual Modl is a st of on o mo dpndnc lationship linking th hypothss modl s constuct. Th stuctual modl is most usful in psnting th intlationship of vaiabls btwn constucts. In this cas, th paamts to stimat a th path cofficints (βij), i.. th gssion cofficints conncting th latnt vaiabls to ach oth (psnting th lationships among latnt vaiabls), and th o tms fo any gssion in th stuctual modl. Th stuctual modl undlying th stuctual quation modl is: wh η is th vcto of latnt vaiabls ndognous, ξ is th vcto of latnt vaiabls xognous; B is th matix of stuctual cofficints btwn th ndognous vaiabls; Г is th matix of stuctual cofficints btwn ndognous and xognous vaiabls, and finally ζ idntifis th vcto of siduals, i.. th os of th stimation modl. Th vctos η and ζ contain m lmnts (i how many a th ndognous vaiabls η), th vcto ξ contains n lmnts (as th a xognous vaiabls ξ). Th matix B contains m*m lmnts, i.. a squa matix of dimnsion qual to th numb of 146

148 Chapt 5 ndognous vaiabls η. In addition, its diagonal is always mad up of all 0, sinc thy cospond to th gssion cofficints of ach vaiabl with itslf. Th matix Г is instad of od m*n, wh n is th numb of xognous vaiabls. Th masumnt modl spcifis th indicatos fo ach constuct and nabls an assssmnt of constuct validity. In oth wods, it is th spcification of masumnt thoy that shows how constucts a opationalizd by st of masud vaiabls. Thfo, it dfins th lationships btwn th latnt vaiabls and thi obsvd indicatos, namly th cosponding manifst vaiabls (sinc w assum that η and ξ a masud by indicatos obsvd). It is fomulatd as follows: Th fist quation xpsss th masumnt modl th lationship btwn th ndognous latnt vaiabls and obsvd vaiabls. In this quation, Y psnts th vcto of ndognous obsvd vaiabls, η psnts th vcto of ndognous latnt, and ε th vcto of os. Th vctos Y and ε contain p lmnts (as many as th obsvd vaiabls Y), th vcto η contains m lmnts (as many as a th latnt vaiabls η). Th matix of stuctual cofficints btwn th obsvd vaiabls and latnt vaiabls (that is th matix of gssion cofficints of η on Y), psntd by th symbol Λy in th quation, contains p*m lmnts. Th scond quation xpsss th lationship btwn th obsvd and latnt xognous vaiabls. In this quation, X psnt th vctos of obsvd xognous vaiabls, ξ psnt th vcto of latnt xognous vaiabl and δ is th vcto of latnt xognous vaiabls os. Th vcto X and δ a mad up of q lmnts (numb of obsvd xognous vaiabls X), whil th vcto ξ is composd of n lmnts (as th a latnt xognous vaiabl). Th matix of stuctual cofficints btwn th obsvd and latnt vaiabls (th matix of gssion cofficints of ξ on X) is indicatd though Λx and it is of od q*n. 147

149 Chapt 5 In th SEM, two diffnt typs of masumnt modl xist, namly fomativ and flctiv modl (Figu 20). x 11 x 11 x 21 ξ 1 ξ 1 x 21 x 31 x 31 Fomativ modl Rflctiv modl Figu 20: Fomativ and Rflctiv masumnt modls A fomativ masumnt thoy is modld basd on th assumption that th masud vaiabls caus th latnt constuct. In this cas, w assums that th diction of th causal lationship is th opposit, namly that th masus a to caus th constuct, so th st of indicatos jointly dtmin th maning of th constuct [Bolln and Lnnox, 1991; Diamantopoulos and Winklhof, 2001; Javis t al., 2003]. Th choic btwn a fomativ modl ath than flctiv dpnds on th causal pioity btwn th indicato and th constuct. Th causal stuctus linking constucts to masus can b also chaactizd by th psnc of dict and indict ffcts and can b gadd as spuious whn it finds on o mo common causs and masus to constuct. In contast, a flctiv masumnt thoy is basd on th ida that latnt constucts caus th masud vaiabls. In od wods, w assum that th undlying constuct causs th obsvd vaiabls (i.. th mpiical indicatos) and, thfo, vaiations in th constuct caus changs in th masus. Fo this ason, th masus flct o a a manifstation of th constuct. Thus th aow a daw fom latnt constuct to masud vaiabls. 148

150 Chapt 6 Data Analysis and Rsults 6.1 Intoduction In od to tst th sach hypothss psntd and xplaind in th Chapt 5, w pfomd a fild tst in Jun 2011 at th Univsity of Napls with a community of 64 undgaduat studnts. Th basic ida is to pdict and valuat th impact of visual, social and convsational fdback, povidd studnts with visual widgts, on Mutual Undstanding and, in tun, th impact of Mutual Undstanding on uss pfomancs. Futhmo, in lin with as mgd fom litatu on visualization tools, w aim at assssing th impact of visual widgts dictly on th uss pfomancs. In Figu 21 a vy simplifid vsion of thotical modl to tst is showd. P MU F Lgnd: P MU F Pfomanc Mutual undstanding Fdback Affct positivly Figu 21. Simplifid Thotical Modl As showd in th modl, th Mutual Undstanding is both vaiabl dpndnt on th fdback and indpndnt with gad to pfomanc. It is impotant to highlight th fact that it has bn valuatd also th mdiation ffct of Mutual Undstanding on uss pfomancs, namly Quality of Onlin Collaboation, Quality of Dcision and 149

151 Chapt 6 Usability. Indd, w xpct that gat amount of common gound sults in btt uss pfomancs. Th data fo this sach w collctd by using two xpimntal vsion of Coh platfoms (uss activity and lvl of paticipation), post-sssion qustionnai (uss pcptions about mutual undstanding and th lvl of uss pfomancs) and a Vitual Machin (to tack and cod th us of visual fdback of studnts goup A). Fo this ason, w analyzd th data of th diffnt databas fo ach of suvy instumnt usd. In this Chapt, w psnt and show th data analysis pfomd and th obtaind sults. Two diffnt softwa w usd to undtak th xamination, namly SPSS 17.0 and SmatPLS 1. SPSS (Statistical Packag fo th Social Scincs) is among th most widly usd pogams fo statistical analysis in social scinc. W usd SPSS to comput som dsciptiv statistics, t-tsts, cofficint of liability fo Likt scals (Conbach s alpha), nomality tsts. Instad, SmatPLS is a softwa application that nabls uss to pfom path modlling with latnt vaiabls using th patial last squa (Ringl t al., 2005). SmatPLS was dvlopd by a tam fom th Univsity of Hambug School of Businss. 6.2 Dsciptiv statistics A fild tst, to valuat th impact of th us of Dbat Dashboad on th gounding pocss and on uss pfomancs, was pfomd in Jun 2011 at th Univsity of Napls with a community of 64 undgaduat studnts. Th studnts w all pat of a sam class fom a gaduat pogam in Industial Engining, ag Studnts paticipatd in a singl-facto, asynchonous, wb-basd goup dcision-making xpimnt. 1 Smat PLS is availabl fo f download at 150

152 Chapt 6 Th paticipation was facultativ and voluntay. At th bginning, studnts that dcid to paticipat w 123 (Tabl 4). Tabl 4. Dmogaphic statistics fo gnd of initial population Sx Fquncy Pcntag Mal 74 60% Fmal 49 40% Total % Ths studnts w andomly assignd to th two goups (A and B), in od to nsu intnal validity [van dn Baak t al., 2006]. W usd RAND Excl fomula to assign automatically and casually a numb btwn 0 and 1 to ach studnt; thn by using a if-thn Excl function w dividd all paticipants in two goups. In paticula: fo studnts hav bn add to th goup A, fo studnts hav bn add to th goup B. In od to vify that th w no diffncs btwn two goups, a t-tst was pfomd. W usd an acadmic poficincy indicato to tst th unifomity of two goups and, thus, to avoid to hav goups with diffnt chaactistics that could lad to invalidat th obtaind sults. Th fomula to calculat this acadmic poficincy indicato is: Aft andomization pocss, th two goups was mad up spctivly of 59 (goup A) and 64 (goup B). Tabl 5 shows th man and standad dviation of both goups. Th sults of T-tst show that th diffnc btwn two goups a not significant; indd, t calculatd is qual to 0.16, lss than citical t valu (1.658) (df=121; α=.05). 151

153 Chapt 6 Tabl 5. Dsciptiv statistics on studnts Univsity Pfomanc Indicato Goup N Man Std. Dviation A 59 81,88 26,39 B 64 75,70 29,66 Duing wam up phas, numous studnts gav up th xpimnt. Thfo, at th nd of this pliminay phas th goups w spctivly composd of 34 (goup A) and 42 (goup B). Bfo stating th xpimntal phas, oth studnts dcid to not paticipat, that is 9 fo goup A and 3 fo goup B. Thfo, bfo stating th xpimnt, th two goups was so composd: th tatmnt goup (goup A) had 25 studnts and th contol goup (B) has 39 studnts. Tabl 6 and Tabl 7 show statistics about paticipants gnd and ya of study p goup. Tabl 6. Dmogaphic statistics fo gnd of Goup A and Goup B Sx Goup A Goup B Mal 14 (56%) 25 (64%) Fmal 11 (44%) 14 (36%) Total Tabl 7. Statistics fo ya of study Ya of study Goup A Goup B Scond 21 (84%) 35 (89%) Thid 4 (16%) 4 (11%) Total In th following paagaph, w psnt th data analysis pfomd and th obtaind sults p ach of usd databas, namly Coh databas, post-sssion qustionnai databas and vitual machin databas. Finally, SEM sults will b showd. 152

154 Chapt Data Analysis of Coh Databas Coh is wb-basd agumntation tool which lts uss to cat agumnt maps flcting thi opinions, knowldg and idas. In gnal, agumnt mapping tools not only allow paticipants to contibut to th convsation by adding posts (nod), but also to mak smantic connctions btwn thm. Paticipants can xplicitly connct thi posts to th posts which is lvant o ptinnt to what thy want to say. Th connction btwn posts xplains th htoical mov uss want to mak in th convsation. By using Coh databas, w analyzd uss activity and paticipation lvl of both goups in od to stat to xplo th ability of visual, social and convsational fdback to impov uss pfomancs. Th basic ida is that th uss of th augmntd platfom, thanks to th availability of fdbacks, would incas thi lvl of mutual undstanding and xpinc a mo fficint dlibation. In oth wods, by making agumnt mapping-mdiatd convsation asi and mo fficint, uss pfomanc should impov in tm of fficincy. In this cas, uss pfomancs a masud assssing uss activity in Coh. As alady mntiond, Coh lts uss to paticipat convsation by cating posts and links. Fo this ason, w masu uss activity on th basis of th total connctions and posts catd by ach of thm. In oth wods, us s contibutions indicats th sum of posts and connctions catd by ach us. Lt s stat with som data laboation in od to btt analyz th utilization of Coh and uss paticipation. Duing th xpimnt, Coh was activ 24 hous p day and w can obsv a high lvl of us paticipation in both th goups ov tim (Figu 22). Th uss in th tatmnt goup contibutd significantly mo than uss in th contol goup on a day-to-day basis xcpt at th nd of th xpimnt. This data shows that pobably th uss of th augmntd platfom did not xpinc any paticula difficulty associabl to th us of a ich and potntially mo difficult to us tool. 153

155 Chapt 6 Figu 22. Gowth in numb of posts and connctions ov tim As showd in th nxt figus, th intnsity of paticipation vaid widly among uss (Figus 23 and 24), oughly following th pow law distibution that has bn found to b typical of most onlin community [Wilkinson, 2008]. Figu 23. Distibution of numbs of post and connctions p uss (Goup A) 154

156 Chapt 6 Figu 24. Distibution of numbs of post and connctions p uss (Goup B) This data confims what has mgd fom pvious studis [Wilkinson, 1998] on how popl contibut to p poduction, i.. a fw vy activ uss account fo th most of contibutions. Whil this pattn is common to both goups, th mmbs of th Dbat Dashboad goup w mo activ and in this goup th was a high popotion of pow uss (24% of uss with mo than 40 contibutions Vs 13% in th contol goup). Ovall, in two wks th onlin community postd 603 posts and catd 792 connctions. Th following tabls show th numb of posts p ach goup (Tabl 8), th numb of connction p goup (Tabl 9) and th gand totals of catd posts and connctions fo ach goup (Tabl 10). Tabl 8. Dsciptiv statistics on uss actvity Post Goup A Goup B # catd post Avag numb of post 10,76 8,56 St. dviation 5,72 7,34 155

157 Chapt 6 Tabl 9. Dsciptiv statistics on uss activity Connction Goup A Goup B # catd connction Avag numb of connction 16,48 9,74 St. dviation 20,12 10,05 Tabl 10. Dsciptiv statistics on uss activity Us s activity Goup A Us s activity Goup B # Posts 269 # Posts 334 # Connctions 412 # Connctions 380 Total 681 Total 714 Avag 27,24 Avag 18,31 St. Dviation 22,98 St. Dviation 16,28 Sinc goup A is small than goup B (spctivly 25 and 39), as showd in Tabls 8-10, it sults to b mo activ. Indd, on avag, th uss of goup A hav paticipatd to th discussion with mo contibutions, namly aound 27 p uss vsus 18 contibutions p us of goup B. Anoth impotant statistic to consid is th standad dviation. In both goups, th is a high standad dviation. It maks what is mgd fom th Figus 23 and 24, that th is a small numb of uss that catd th most pat of contibutions (posts and connctions). Moov, by xamining Tabls 8-10, it is possibl to not that th goup A had a mo collaboativ appoach to th discussions; this mg fom th analysis of th numb of connctions catd which is high than on of goup B (spctivly, 412 and 380). Th following figus compa th two goups on th basis of post typ (Figu 25) and links typ (Figu 26) usd by both goups. In paticula, uss could us only 4 posts typ among all thos poposd by Coh, namly Qustion, Ida, Po (idas that suppot oth uss posts) and Con (idas that attack oth uss posts). Whit gad to link typ, uss could us only suppots, against and spond to typologis. As showd, goup B sms to hav had a mo contovsial discussion, indd, th numb of Con 156

158 Chapt 6 posts and Attack links is high than in goup A. Additionally, goup A did not mak os in post and link typ choic. Likly, this may dpnds on th gat visibility on oths goups mmbs activity and wok that hlps and guids uss in collaboativ discussion pocss and, thus, in a btt goup s pfomanc. Figu 25. Compaison btwn Goup A s and Goup B s usd posts typ Figu 26. Compaison btwn Goup A s and Goup B s usd links typ 157

159 Chapt 6 In od to tst th hypothsis that uss in th tatmnt goup hav bn mo activ in th discussion than uss in th contol goup, w pfomd a on-tail Indpndnt Sampl T-tsts using SPSS (Statistical Packag fo th Social Scincs) to assss if visual fdback impact on uss activity. In paticula, th hypothss to tst a: H 0 : Uss activity a = Uss activity b H 1 : Uss activity a > Uss activity b In this cas w usd a on-tail T tst bcaus w want to tst th hypothsis that Uss activity of goup A is gat than uss activity lvl of goup B. As in SPSS th is no option to spcify a on-taild tst, w nd to look in a tabl of citical t valus to dtmin th citical t and to compa it with th obsvd t valu. Th citical t with 62 dgs of fdom, α = 0.05 and on-taild is Th dcision ul to dtmin if w can jct th null hypothsis o not is: if th on-taild citical t valu is lss than th obsvd t valu and th mans a in th ight od (, thn w can jct H 0. In ou cas, th citical t valu is and th obsvd t valu is 1.820; thfo, as T citical <T obsvd and as (spctivly 27,4 and 18,38), H 0 is jctd and H 1 is accptd. Put diffntly, it is possibl to claim that uss activity lvl of goup A is significant high than uss activity lvl of goup B. Thus, w can conclud th goup A that usd th Dbat Dashboad had btt pfomanc than th goup B that usd th plain vsion. As initially th two goups w not significantly diffnt, it is possibl to conclud that th btt pfomanc dpnds on th povision of individualizd fdback. In od to masu th magnitud and diction of th diffnc btwn tatmnt goup and contol goup, w pfomd an Effct siz (ES) tst basd on mans (Cohn s d) (Cohn, 1988). In oth wods, ESs povid this infomation by assssing how much diffnc th is btwn goups. By computing ESs w can analyz th stngth of th findings of an mpiical sach. 158

160 Chapt 6 In gnal, Cohn s d is dfind as th diffnc btwn two mans dividd by a standad dviation poold fo th data: d = Th fomula to calculat S poold is: In this cas, Cohn d ES is qual to 0.47, thfo, w can affim that th is an ES. This mans that th intvntion ffct, that is th us of visual fdback, not only had an ffct on uss pfomancs, but, in lin with Cohn [1988] it can b considd a mdium ffct. In oth wods, by calculating Cohn s d, w valuatd th statistical significanc of ffct. Futh analysis should b pfomd in od to btt masu th impact of visual fdback on common gound building and th ffct of mutual undstanding on uss pfomancs. 6.4 Post-sssion qustionnai data analysis A futh instumnt usd in th xpimnt to collct data was a follow-up qustionnai fo both goups. It is composd of 28 itms (7-point Likt scal) to masu fou latnt constucts of thotical modl, namly Mutual Undstanding, Quality of onlin Collaboation, Quality of Dcision and Usability. Bfo pocding with analysis of post-sssion qustionnai databas, w assssd th liability and validity of th masumnt instumnt. Th latt, indd, to b ffctiv, must b liabl and valid to not lad to th invalidation o inaccuacy of suvyd data. In simpl tms, liability mans that an instumnt will consistntly 159

161 Chapt 6 masu somthing; validity mans that it will masu what it is intndd to masu [Spcto, 1992]. Masumnt liability fs to th popotion of vaianc attibutabl to th tu sco of th latnt vaiabl [DVllis, 1991]. Th masumnt liabilitis of th constucts w valuatd using Conbach s α and Avag Vaianc Extactd (AVE). In litatu, Conbach s α is on of th most common indx usd to valuat intnal consistncy. Conbach s α is a masu of th popotion of vaianc among a goup of indicatos that is attibutabl to a common facto [Conbach, 1951]. Conbach s α povids an indx sco that angs fom 0 to 1. Th α fo a good scal should b gat than 0.7, maning that 70 pcnt of th vaianc among th indicatos is common. In Tabl 11, w show th Qustionnai itms, th movd itms, th latnt constucts which w want to masu and alpha valus. In paticula, by analyzing int-itm total colation matix, w found som itms that had a low int-colation at that impact ngativly on Conbach s alpha valus. Indd, by dlting thos itms, th alpha valus of th latnt constucts incas. In paticula, as showd in Tabl 11, th dltd itms a: Q4, Q14, Q21, and Q22. By dlting Q4 (Quality of Onlin Collaboation clust), th Conbach s alpha vaid fom 0.67 to Whil by dlting Q14, Q21, Q22 in Mutual Undstanding clust, th alpha valus changs fom 0.55 to In addition, in th cas of Quality of Dcision, w considd Conbach s Alpha standadizd itms bcaus individual scal itms a not th sam. Indd, itms Q11 and Q12 ask uss to indicat thi psonal dcision bfo and aft goup discussion; whil Q13 asks uss to indicat what goup dcision is. Thfo, th α fo ach of th scals usd in this study xcds 0.7. This confims th stngth of th instumnt usd in masuing th latnt constucts. In paticula, th invstigatd itms sults to b pfctly colatd to th constuct to which thy f. 160

162 Chapt 6 Tabl 11. Qustionnai itms, Rmovd Itms, Latnt Constuct and alpha valus # Qustionnai itms Rmovd Itms Latnt Constuct Conbach s α Q1 Th intaction lvl dvlopd duing Coh-mdiatd convsation was satisfying Q2 I found th onlin discussion intsting and ngaging Q3 Q4 Collaboation was ffctiv to solv assignd poblm I found it difficult to kp tack of th convsation Low intcolation at Q5 Th agumnt map was hlpful in facilitating knowldg shaing among tam mmbs Quality of onlin Collaboation Q6 I shad my own knowldg about th task with my tammats Q7 I found that my tammats hav shad own thi knowldg about th task Q8 Th goup dvlopd a good amount of wok Q9 Th goup mad a good job Q10 I think that, at th nd of onlin dbat, th goup has a common position about th discussion topic Q11 What is you initial dcision bfo discussing with oth goup mmbs? Quality of Dcision Q12 What is you dcision at th nd of onlin dbat? Q13 What is goup s dcision at th nd of th discussion? Q14 In gnal, I hav not had poblms to undstand th maning of oth tam mmbs posts Low intcolation at Q15 Q16 In gnal, I think that th oth tam mmbs hav undstood my contibutions without difficulty I could asily undstand (tll) what my tammats had don on Coh Mutual Undstanding Q17 I could asily undstand who has don what Q18 I could asily say who is onlin on Coh 161

163 Chapt 6 # Qustionnai itms Rmovd Itms Latnt Constuct Conbach s α Q19 My tammats and I dvlopd btt undstanding about ach oth ov th two wks Q20 Q21 Q22 My tammats and I dvlopd shad undstanding about th task ov th tim I found onlin convsation is oftn dundant I found th a many ilvant posts spct th assignd task Low intcolation at Low intcolation at Mutual Undstanding (as abov) (as abov) Q23 Intaction with th systm dos not qui a lot of my mntal ffot Q24 I find th systm to b asy to us Q25 Q26 I njoyd collaboating with my tammats using Coh I would njoy woking with my tammats again using Coh Usability Q27 It was asy to communicat ffctivly givn th tools availabl Q28 Coh suppots and facilitats collaboation among onlin uss A scond masumnt usd to valuat th liability of qustionnai was th Avag Vaianc Extactd (AVE). It masus th amount of vaianc captud by th indicatos in lation to th amount of vaianc du to masumnt o [Fonll and Lack, 1981]. AVE should b gat than 0.5 [Chin, 1998]. With spct to th data collctd fo this study, all AVE scos fo th masus usd xcdd th 0.5 thshold (Tabl 12). Tabl 12. Avag Vaianc Extactd valus Constucts AVE Mutual Undstanding 0,909 Quality of Collaboation 0,807 Quality of Dcision 0,832 Usability 0,

164 Chapt 6 Th Conbach s α and Avag Vaianc Extactd valus xcdd th commndd thsholds. Thfo, th masumnts usd fo this study xhibitd adquat intnal consistncy liability. In od to valuat th validity of masumnt instumnt, w computd Squa-Root of AVE. Validity fs to th xtnt to which th intptation divd fom a masumnt pocdu o th infncs mad on th basis of masumnt a coct. In paticula, disciminant validity is th xtnt to which masus of diffnt concpts a distinct [Byant, 2000]. Disciminant validity was assssd using th mthod pscibd by Gfn and Staub [2005]. Th pocdu to assss disciminant validity is th AVE analysis. Th AVE analysis is pfomd by compaing th squa oot of th AVE with th colation btwn th constuct and vy oth constuct. Th squa oot of th AVE has to b lag than th colations with th oth constucts [Fonll and Lack, 1981]. Unfotunatly, th a no dfinitiv guidlins to indicat how much lag th squa oot of th AVE has to b. In ach cas, th squa oot of th avag vaianc xtactd is much lag than th colations of th constuct with th all of th oth constucts. Thfo, th data passd th tst of disciminant validity as wll. This mans that th indicatos (itms) usd to masu th latnt constucts hav much mo in common with th constuct that thy should masu ath than with th oth latnt vaiabls in th qustionnai. Tabl 13. Disciminant validity CONSTRUCT AVE SIC Mutual Undstanding 0,909 0,564; 0,234; 0,805 Quality of Collaboation 0,807 0,564; 0,234; 0,624 Quality of Dcision 0,832 0,234; 0,234; 0,199 Usability 0,883 0,624; 0,805; 0,199 Thfo, both liability and validity analysis of masumnt instumnt confim and validat its goodnss (Tabl 13). H a also th dsciptiv statistics lating to th collctd data though post-sssion qustionnai usd fo both th goup A to goup B. 163

165 Chapt 6 Tabl 14 shows th mdian, mod, ang and int-quatil ang fo all th collctd data dividing data indicating pfomanc among th constucts and analyzd by compaing th 2 goups of th xpimnt, so to facilitat compaison btwn th tatmnt goup and contol goups. Bfo pocding with data analysis, it is impotant to highlight that spons at of Goup A was 100%, that is all paticipants to th xpimnt compltd th post-sssion qustionnai, whil in th goup B only 36 out of 39 studnts filld in it (i.. spons at 92 pcnt). Tabl 14. Dsciptiv Statistics Goup A and Goup B Constuct Itms Mdian Mod Q1 Q3 Rang IQR Quality of Collaboation Quality of Outcom Quality of Dcision Coh usability A B A B A B A B A B A B Q , ,25 2 Q Q Q Q Q Q , ,25 Q Q Q15 5 5, Q , , ,25 1,25 Q , ,25 1 Q Q , ,25 2 Q Q27 6 5, Q Q Q30 5 4, Q Q

166 Chapt 6 In od to valuat th impact of visual, social and convsational fdback on uss mutual undstand and on uss pfomancs, w pfomd T-tst to vify whth th two goups a significantly diffnt. Bfo pocding with th computation of T- tsts, w nsud th nomality of sampl distibution. Indd, a basic assumption is that ach of th two databas collctd though post-sssion qustionnai follows a nomal distibution. In this study, w tstd nomality by using th Shapio-Wilk nomality tst. W usd Shapio-Wilk tst as it is mo appopiat fo small sampls (x<50). W computd this tst fo ach of ou masud constucts fo both goup, namly Mutual Undstanding, Quality of onlin Collaboation, Quality of Dcision and Coh Usability. In Tabl 15, w show th sults of Shapio-Wilk nomality tst. Tabl 15. Nomality tst Constuct Mutual Undstanding Quality of Collaboation Coh Usability Goup Shapio-Wilk Statistic df Sig. A B A B A B Th sults confimd that ou sampls a nomally distibutd as all Sig. valu> This lts us to accpt th null hypothsis (H 0 ), confiming that th data coms fom sampls nomally distibutd. In od to dtmin nomality gaphically Figus 27, 28 and 29 show th Q-Q Plot (output of SPSS). If th data a nomally distibutd thn th data points will b clos to th diagonal lin. If th data points stay fom th lin in an obvious non-lina fashion thn th data a not nomally distibutd. As it is possibl to not fom th nomal Q-Q plot blow, in ou cas, th data is always nomally distibutd. 165

167 Chapt 6 Figu 27. Data distibution of Mutual undstanding constuct fo Goup A and Goup B Figu 28. Data distibution of Quality of Collaboation constuct fo Goup A and Goup B Figu 29. Data distibution of Coh Usability constuct fo Goup A and Goup B 166

168 Chapt 6 Ensud th nomality of th data with th abov tsts, it was possibl to pfom th t- vify if social and convsational fdback povidd by th Dashboad Dbat hav impovd mutual undstanding and uss pfomancs. W pfomd on-tail T tst, bcaus w hypothsizd that uss pfomancs and mutual undstanding of goup A a btt than ons of goup B. In paticula, th st of hypothss a: Mutual Undstanding: H 0 : MU a = MU b ; H 1 : MU a > MU b ; Quality of Collaboation: H 0: QofC a = QofC b ; H 1 : QofC a > QofC b ; Coh Usability: H 0 : Usab a = Usab b ; H 1 : Usab a > Usab b ; Rgading th fist 2 hypothss about QofC and MU, it was possibl to jct H 0 at 95%, givn that t citical valu is 1,671 (df = 59; α =. 05) is lss than t valus obsvd fo th 2 constucts (Tabl 16). Whil, fo Usability, w hav to accpt H 0 fo α =. 05 as t citical valu is gat than t obsvd. In ality, w xpctd that usability of th Augmntd Coh vsion could duc bcaus of th psnc of mo widgts and diffnt fatus than Plain vsion. In oth wods, augmntd vsion could b sultd mo complicatd to usd and thfo ask uss a high ffot. Tabl 16. Rsults On-Tail T tst Mutual Undstanding Quality of Collaboation Quality of Dcision T obsvd t tab α=.05 (df=59) t tab α=.01 (df=59) t > t tab (α=.05) t > t tab (α=.1) 1,965 1, jct H 0 jct H 0 1,908 1, jct H 0 jct H , accpt H 0 jct H 0 Coh Usability 1,075 1, accpt H 0 accpt H 0 167

169 Chapt 6 As showd in Tabl 16, th sults suppot th most pat of ou hypothss. Thus, w can stat that visual fdback impact positivly on mutual undstanding and uss pfomancs. In oth wods, it is possibl to affim that social and convsational fdback incass and suppots mutual undstanding (α =.05) among mmbs of goup A and impov th quality of collaboation (α =.05) and quality of dcision (α =.1). In paticula, by having analyzd th two goups bfo xpimnt phas on th basis of acadmic poficincy indicato, and not having found no significant diffncs, w can affim that th btt sults do not dpnds on inhnt uss abilitis, but thy may b attibutd to th povidd fdback. In nutshll, mutual undstanding, quality of collaboation and quality of dcision of goup A is significantly diffnt fom mutual undstanding and uss pfomancs of goup B. As alady mntiond in th pvious Chapt, Quality of Dcision is masud by valuating uss dcision accuacy. Also in this cas (Figu 30), goup A has bn abl to focast th ight tnd of gold pic, whil goup B was not abl to focast th coct on. In paticula, both goups focast that oil and gold pic incasd; in ality, gold pic incasd fom $ 1535,30 ( ) to $ 1840,00 ( ), instad oil pic vaid fom $ ( ) to $ ( ). Figu 30. Compaison among uss dcision fo Goups 168

170 Chapt 6 In od to masu th magnitud and diction of th diffnc btwn tatmnt goup and contol goup, w pfomd an Effct siz (ES) tsts basd on mans (Cohn s d) [Cohn, 1988] fo ach T-tst. In this cass (Tabl 17) w can affim that th ESs a mdium. This mans that th intvntion ffct, that is th us of visual fdback, had an ffct on uss pfomancs and mutual undstanding. Only in th cas of Usability pfomanc, th ES is considd small. Tabl 17. Effct siz tsts Effct siz Mutual Undstanding 0,51 Quality of Collaboation 0,50 Quality of Dcision 0,40 Usability 0,26 In conclusion, it is possibl to stat th uss pfomancs of goup A was btt than ons of goup B bcaus of th povision of social and convsational fdback. In accodanc with Cohn [1998], ths diffncs a statistically significant as wll. In th nxt paagaphs w pfomd futh analysis to btt undstand th ol and th impact of ach visual fdback on uss mutual undstanding and uss pfomancs; in addition, w un som tsts to analyz whth and th ol of impovmnt of mutual undstanding on uss undstanding. 169

171 Chapt Vitual Machin Databas In od to tack and cod th utilization of visual fdback, studnts of goup A installd on thi computs a Vitual Machin and thy usd it to wok and bows in Coh. By using th Vitual Machins it is possibl to know what URLs uss hav usd. As ach visual fdback has an own URL, as consqunc, w can know what fdback and count how many tims studnts us it (fquncy). Bfo pocding to th data analysis of Vitual Machin databas, w cland up it. Indd, fist, w dltd all thos URLs that do not gad Coh us. Fo instanc, studnts usd vitual machin also to look fo infomation about thi collaboativ task i Scond, w movd all URLs lating to uss login and logout, as wll as hom pag and own us psonal pag. Thid, w liminatd all URLs ptaining to uss poducing activity. In oth wods, w movd URLs gading th cation of posts and connctions. Th basic ida is to focus xclusivly on uss bowsing activity in Coh, bcaus w think that this activity is cucial fo uss to gath futh infomation about oth goup mmbs activity and onlin discussion. In oth wods, w did not dlt all thos URLs lating to th visualization of nods list, connctions list and discussion goup pag. Indd, by bowsing in ths pags, uss can visualiz infomation about discussion contnt dvlopmnt and uss paticipation. In addition, w supposd that this infomation could suppot th cation of mutual undstanding about uss and discussion contnt. Onc cland up th databas, w pocdd to valuat th fquncy of th us of ach visual fdback (Figu 31) in all th goup. In oth wods, w countd how many tims ach fdback was usd by goup A and calculatd th pcntag of utilization fo ach of it, also spct to th oth uss bowsing activity. 170

172 Chapt 6 Figu 31. Fquncy of us fo ach fdback As it is possibl to not, th most usd fdback is Copsnc, whil th last usd is Rlvanc fdback. This shows that fo uss is vy impotant to know with thy a spaking. In gnal, absoption fdback a th last usd fdback. Mayb, this could dpnd on th inhnt fatus of Coh, that alady suppots uss in th snsmaking of discussion, notwithstanding th dvlopmnt of th map. Oth oftn-usd fdback a: Community s histoy (4,5%), Social Stuctu (4,4%) and Visibility (4,2%). Th fist two fdback blongs to th Community Fdback catgoy, whil th last blongs to th Intaction Fdback class. This mans that uss nd of social and convsational infomation which a lacking o hiddn and, thfo, mo difficultly dducibl. In conclusion, not only visual fdback hav a significant impact on mutual undstanding and uss pfomancs, but som fdback is considd also vy usd by studnts. Futh mo in-dpth analysis should b pfomd on th us of divs fdback to valuat diffnt its aspcts, such as its dsign, its fficincy and vntually possibilitis of impovmnt. In th following paagaphs, w show th sults of SEM analysis in od to undstand th ol of ach sub-classs of fdback on mutual undstanding and uss pfomancs. Moov, w valuat th mdiation ol of mutual undstanding among th diffnt classs of fdback and uss pfomancs. This dpnds on th 171

173 Chapt 6 ida that incasing of mutual undstanding should sult in impovmnt of uss pfomancs. 6.6 Stuctual Equation Modlling Analysis Rcall that th ovaching goal of this disstation is to invstigat th impact of visual fdback on mutual undstanding and on uss pfomanc. A thotical modl was poposd basd on a st of statmnts of colations btwn vaiabls. In th sctions that follow th thotical modl is tstd using th collctd data. Th data analysis pocds in two stps. Fist, th masumnt modl was assssd fo validity and liability. Thn th stuctual modl was assssd. In this phas w usd SmatPLS to undtak th xamination. As alady mntiond, SmatPLS is a softwa application that nabls th us to pfom path modlling with latnt vaiabls using th patial last squas mthod. In paticula, in th following paagaphs, fist w valuat masumnt modl and thn th validity of th stuctual modl and th hypothss that th stuctual modl was dsignd to valuat Masumnt Modl As mntiond in th pvious Chapt, th masumnt modl (o outlin modl) shows how constucts hav bn opationalizd and, thus, masud by using manifst vaiabls. Th analysis of th masumnt modl was undtakn to assss th liability and validity of it. Indd, to b ffctiv, masumnts should b liabl and valid. In simpl tms, liability mans that an instumnt will consistntly masu somthing; validity mans that it will masu what it is intndd to masu [Spcto, 1992]. In th following w dscib th pocdus that w undtakn to assss th liability and validity of th masumnts usd in this study. 172

174 Chapt 6 W hav to mak a pcision about th valuation of masumnt modl. In this cas, w a masuing th liability and th validity of all ou thotical modl. Thus, ths analysis a quit diffnt fom ons pfomd fo post-sssion qustionnai. In oth wods, w consid all th colation lationship among all th vaiabls of th modl. Th masumnt liabilitis of th constucts w valuatd using Conbach s α, composit liability, and avag vaianc xtactd (AVE). Conbach s α is a masu of th popotion of vaianc among a goup of indicatos that is attibutabl to a common facto [Conbach, 1951]. Th sults a shown in Tabl 18. Tabl 18. Conbach s alphas, Composit Rliability, AVE sqt-ave Rliability Masu MU QofD Usability α 0,788 0,675 0,711 Composit Rliability 0,853 0,793 0,813 AVE 0,507 0,547 0,51 Sqt-AVE 0,712 0,74 0,714 Bfo pocding to th analysis of ach liability masumnts usd in this study, w hav to mak a pcision about Quality of Collaboation constuct. In ou modl w dfind th itms that masu Quality of Collaboation constuct as fomativ and not as flctiv. In nutshll, flctiv vaiabls a causd by th constuct and flct its vaiation; whil fomativ vaiabls caus th latnt constuct. W dcidd to tat ths itms as fomativ ath than flctiv vaiabls fo two asons, bcaus: i. thy a caus of constuct and not vicvsa, and ii. this chang hav impovd th quality of th modl. Indd, accoding to litatu, th us of fomativ vaiabls, in som cass, such as businss and managmnt studis, could impov th modl and, thus, to b btt than flctiv vaiabls [Diamantopoulous and Siguaw, 2006; Podsakof t al, 2006]. As such itms a considd fomativ, SmatPLS do not comput th liability masus shown in Tabl

175 Chapt 6 Lt s to analyz ach of computd masumnts. As alady mntiond, Conbach s α valus should ang fom 0 to 1. Th Conbach s alpha should b gat than 0.7 to hav a good scal. In ou cas, all th alpha valus xcd this thshold, xcpt that in Quality of Dcision constuct. This could b du to th fact that w usd only two itms to masu this constuct (Q10 and Q12) and bcaus on of thm is a dichotomic vaiabl. Th oth two vaiabls w dltd aft pfoming a fist un of SEM analysis and as thi path cofficints w ngativ, w dcidd to xclud thm fom th analysis. Composit liability is simila to Conbach s α. It is dsignd to assss th sam fom of liability: intnal consistncy liability. Lik Conbach s α Composit liability povids an indx sco. Th diffnc is that Conbach s α assums that all of th indicatos hav th sam liability, whil composit liability dos not. Consquntly, th sults fo th two indxs a diffnt and th standads fo valuating thm a a littl diffnt. Fo xploatoy sach, composit liabilitis should b gat than 0.6. With spct to this study, all valus w gat than 0.7, which povids futh vidnc that th masumnt instumnts usd in this study a liabl. Accoding to Chin [1998], AVE should b gat than 0.5. With spct to ou modl and, thus, latnt vaiabls, all AVE scos fo th masus usd xcdd th 0.5 thshold. In conclusion, th Conbach s α, composit liability, and avag vaianc xtactd valus xcdd th commndd thsholds. Thfo, th masumnts usd fo this study xhibitd adquat intnal consistncy liability. With gad to validity of masumnt modl, in SEM two foms of validity a usually assssd: convgnt validity and disciminant validity. Convgnt validity is th dg to which multipl masus of th sam constuct dmonstat agmnt o convgnc [Byant, 2000]. Convgnt validity is attaind whn multipl masus of an itm psnt th sam undlying constuct. Such masus should b stongly and significantly colatd. Convgnt validity was assssd by th using th AVE valu 174

176 Chapt 6 psntd in Tabl 18. In od to xhibit adquat convgnt validity, th AVE of a constuct must b gat than 0.5. In oth wods, th constuct must account fo mo than half of th vaianc of its indicatos. Fo this sach, th AVE was gat than 0.5. Consquntly, th data was dmd to xhibit adquat convgnt validity. Disciminant validity is th xtnt to which masus of diffnt concpts a distinct [Byant, 2000]. Disciminant validity was assssd using th mthod pscibd by Gfn and Staub [2005], that is th AVE analysis. Th AVE analysis is pfomd by compaing th squa oot of th AVE with th colation btwn th constuct and vy oth constuct. Th squa oot of th AVE should b much lag than th colations with th oth constucts [Fonll and Lack, 1981]. In Tabl 19 w show colations btwn constucts and th squa oot of th AVE. Tabl 19. Disciminant validity Constucts SRAVE SIC Mutual Undstanding 0,712 0,425 ; 0,666 Quality of Dcision 0,739 0,425 ; 0,356 Usability 0,714 0,666 ; 0,356 In ach cas, th squa oot of th avag vaianc xtactd is much lag than th colations of th constuct with th all of th oth constucts. Thfo, th data passd th tst of disciminant validity. Onc valuatd and nsud th liability and validity of masumnt modl, w can pocd to th valuation of th stuctual modl and, thus, to tst ou hypothss Stuctual Modl In this paagaph, w assss th stuctual modl and tst th validity of ou hypothss. Th assssmnt of th stuctual modl consists of an xamination of th R 2 and stimation of path cofficints [Hnsl t al., 2009]. 175

177 Chapt 6 Th stuctual quations in PLS a calculatd using OLS multipl gssion. Consquntly, thy a intptd in th sam mann as th standadizd bta cofficints of odinay last squas. Th bta cofficints fo ach path a psntd in Tabl 20. Th significanc of th path cofficints was assssd using th bootstapping tchniqu. Bootstapping is a comput-basd mthod fo assssing th accuacy of statistical stimats [Efon and Tibshiani, 1998]. Bootstapping ptitivly -sampls with placmnt in od to cat an stimat of th distibution of a statistic [Moony and Duval, 1993]. PLS uss bootstapping to cat a bootstapping distibution fo ach path cofficint. Th man and a standad o can b calculatd fom th bootstapping distibution. Th man and standad o allow a t-valu to b calculatd [Hnsl t al., 2009] which can b usd to stimat th significanc of th path cofficints [Chin, 1998]. To un th bootstapping pocdu in PLS w hav to st th numb of -sampls This numb should b gat than 100, but gat than 200 is pfabl. Sinc lag numbs of -sampls lad to mo asonabl stimats of standad o [Tnnhaus t al., 2005], th bootstapping pocdu was undtakn with 250 sampls. Th sults of th modl a psntd in Figu 32. Figu 32. Stuctual modl sults Bootstapping tchniqu 176

178 Chapt 6 Th t-statistics and bta cofficints a psntd in Tabl 20. Fom th analysis of sults, thitn hypothss of dfind modl a suppotd and just two a jctd. It is impotant to highlight that a cofficint is significant if t-statistic is high than 1,96. Tabl 20. Bootstapping sults Hypothss Path Bta t-statistic Validation H1 CF MU 0,568 8,236 Suppotd H2 IF MU -0,137 3,36 Suppotd H3 AF MU -0,511 21,591 Suppotd H4 MU QofC 0,979 20,257 Suppotd H5 MU QofD 0,293 6,119 Suppotd H6 MU Usab 0,519 9,996 Suppotd H7 CF QofC -0,517 2,663 Suppotd H8 CF QofD -0,096 0,873 Not suppotd H9 CF Usab -0,114 1,078 Not suppotd H10 IF QofC 0,325 2,012 Suppotd H11 IF QofD 0,344 3,824 Suppotd H12 IF Usab 0,286 4,762 Suppotd H13 AF QofC 0,267 3,435 Suppotd H14 AF QofD -0,258 2,806 Suppotd H15 AF Usab -0,346 3,386 Suppotd Ths hypothss a xploatoy in natu. No pvious studis hav povidd quantitativ vidnc on th influnc of visual fdback on mutual undstanding and on uss pfomancs. Rath ths hypothss w basd on qualitativ studis. Fo this ason, this sach could b intndd to vify and quantify th sults of th qualitativ studis. As showd in Tabl 20, hypothsis 1, hypothsis 2 and hypothsis 3 w suppotd. This st of hypothsis was intndd to valuatd th impact of visual fdback on 177

179 Chapt 6 Mutual Undstand. It is possibl to stat that all th fdback affct significantly mutual undstand givn that thi t-statistics a always high than 1,96. In od to analyz th typ of lationship among th indpndnt vaiabl (in this cas th classs of fdback and) th dpndnt vaiabl (that is, th mutual undstanding), w hav to consid also th bta valu. In paticula, th sults show that amount of Intaction and Absoption fdback w ngativly latd with Mutual Undstanding (spctivly β = -0,137 and β = -0,511). Ths sults a contay to xpctations and a contay to th sults potd in pvious sachs. Indd, both fdback is supposd to fost common gound building both on pocss (Intaction fdback) and on contnt (Absoption fdback). Ths findings a not alignd with pvious qualitativ and quantitativ sachs by Clak and Bnnan [1991] and Convtino and his collaboatos [2004; 2008; 2009], which potd that th psnc of intaction fdback facilitats mutual undstanding constuction. Ths sults could dpnd on th fact that w w not abl to povid all fdback individualizd by Clak and Bnnan du to th inhnt fatus of Coh. With gad to th scond st of hypothss, th hypothsis 4, hypothsis 5 and hypothsis 6 w suppotd by SmatPLS findings. In paticula, mutual undstanding significantly and stongly impact on uss pfomancs, namly Quality of Collaboation (t-statistic = 20,257; β = 0.979), Quality of Dcision (t-statistic = 6.119; β = 0.293) and Usability (t-statistic = 9,996; β = 0.519). Ths findings confim both as xpctd and as mgd fom litatu about th positiv ffct of common gound on goup coodination, collaboation and ffctivnss as wll [Convtino t al., 2004; 2008; 2009]. As alady mntiond, w aim at masuing also th ffct of social and convsational fdback on th th lvl of uss pfomancs. W analyzd ths sults by ach class of fdback. In paticula, Community fdback dos not impact significantly on Quality of Dcision and on Usability. With gad th impact of visual fdback on quality of dcision is in lin with as mgd fom litatu. Indd, sval studis show that anonymous impovs quality of dcision as individuals a not affctd by social aspcts, such as putation and social accptanc. Additionally, gading 178

180 Chapt 6 Community fdback, it is plausibl that it ducs th Coh usability givn that uss hav mo fatus that that can b usd. Instad, Community fdback impacts significantly on Quality of Collaboation, but ngativly (β = ). With gad to th impact of Intaction fdback on uss pfomanc, th sults show a significant and positiv lationships among vaiabls. In oth wods, hypothsis 10, hypothsis 11 and hypothsis 12 a suppotd (spctivly, β = 0.325; β = 0.344; β = 0.286). This mans that visual fdback about intaction pocss, in paticula co-psnc and visibility fdback, impact on Quality of Collaboation and Dcision and on Usability. Ths sults confim as mgd in litatu. Indd, sval sachs hav povd that th povision of convsational fdback and hiddn infomation impact positivly on quality of discussion, its outcom and intaction pocsss among uss [Shnidman, 2000; Eickson t al., 2002; Edlson t al, 1996; Ryall t al., 2004]. Finally, hypothsis 13, hypothsis 14 and hypothsis 15 a suppotd. In paticula, it is mgd that Absoption fdback impact significantly and positivly on quality of collaboation (t-statistic = 3,435; β = 0.267). This sult confims as w oiginally supposd. Indd, by poviding this fdback, w aim at suppoting onlin uss to mak sns of discussion and to pitch into it in th ight way. Th oth two sults a contay to what w supposd. Indd, findings show that absoption fdback impact significantly, but ngativly on quality of dcision and Coh usability (spctivly, t- statistic = 2,806; β = and t-statistic = 3,386; β = ). With gad to Usability pfomanc, w think that th poblm is th dsign and th fatus of visualization tools that mak had th us of th platfom. Rspct to th quality of dcision, w xpctd that, by poviding compact infomation about gnatd contnt, th quality of outcom may impov. 179

181 Chapt Mdiation Rsults Rcall that th mdiation ffcts w hypothsizd (H16 H24). Mdiation occus whn th caus-ffct lationship btwn a pdicto vaiabl and a cition vaiabl occus though an intvning vaiabl. Whn th intvning vaiabl accounts fo all of th influnc of th pdicto vaiabl on th cition vaiabl th lationship is said to b fully mdiatd. Whn th dict path of influnc fom th pdicto vaiabl to th cition vaiabl is ducd but not bought to zo whn th intvning vaiabl is intoducd into th modl th lationship is said to b patially mdiatd. Mdiation lationships a of intst bcaus thy go byond simply dscibing colations to xplain how pocsss wok [Pach and Hays, 2008]. Th hypothsizd mdiation ffcts w tstd using PLS tchniqu. In od to pfom th mdiation analysis, a was catd that dpictd a lationship btwn th indpndnt vaiabl (visual fdback) and th dpndnt vaiabl (uss pfomancs) (Tabl 21). Thn a scond modl was catd, namly th mdiatd modl that includs th mdiato vaiabl (Mutual Undstanding) (Tabl 22). Th scnshots of two modls diving fom SmatPLS laboations a psntd in th Appndix C. Th two modls w tstd by using PLS. Th path btas and R 2 w codd. Th t- valus w usd to assss th significanc of th lationships. Ths hypothss aim at assssing th ol of Mutual Undstanding as mdiato. In oth wods, Mutual Undstanding was hypothsizd to mdiat th lationships among visual fdback and uss pfomancs. It was xpctd that th influnc of visual fdback on uss pfomancs was though its influnc on Mutual Undstanding. 180

182 Chapt 6 Tabl 21. Rsults of Simpl Modl Simpl Modl Indipndnt Dpndnt Path Bta t-valus R 2 COMMUNITY USABILITY 0,351 2,833 INTERACTION USABILITY 0,251 2,516 0,544 ABSORPTION USABILITY -0,748 7,407 COMMUNITY QofC 0,44 1,614 INTERACTION QofC 0,725 5,186 0,602 ABSORPTION QofC -0,506 3,176 COMMUNITY QofD 0,085 0,46 INTERACTION QofD 0,385 3,792 0,312 ABSORPTION QofD -0,474 5,746 Tabl 22. Rsults of Mdiatd Modl Mdiatd Modl Indpndnt Dpndnt Indpndnt Mdiato Mdiato Dpndnt Path bta t-valus bta t-valus bta t-valus R 2 COMMUNITY MU USAB -0,114 1,078 0,568 8,236 0,519 9,996 INTERACTION MU USAB 0,286 4,762-0,137 3, ABSORPTION MU USAB -0,346 3,386-0,511 21, COMMUNITY MU QofC -0,517 2, ,979 20,257 INTERACTION MU QofC 0,325 2, ABSORPTION MU QofC 0,267 3, COMMUNITY MU QofD -0,096 0, ,293 6,119 INTERACTION MU QofD 0,344 3, ABSORPTION MU QofD -0,258 2, ,605 0,71 0,318 As showd in Tabl 23, th hypothsis 21, hypothsis 22, hypothsis 23 and hypothsis 24 w not suppotd. In paticula, th sults dmonstat that th R 2 of th mdiatd modl was high than th simpl modl. Indd, whn Mutual Undstanding was 181

183 Chapt 6 addd to th modl as a mdiato, th R 2 fo th modl incasd, spctivly to 0.605, 0.71 and In oth wods, th mdiatd modl xplains mo of th vaianc in uss pfomanc than th simpl modl. Actually, this mans that th mutual undstanding xplains a pat of vaianc of uss pfomancs. Additionally, whn th indpndnt vaiabls and mdiato vaiabl w gssd on th dpndnt vaiabl (uss pfomancs), also th bta fo th paths among th indpndnt vaiabls (classs of visual fdback) and th dpndnt vaiabls (uss pfomancs) ducd. This indicats that a potion of th impact of visual fdback on uss pfomancs is though Mutual Undstanding. With gad to th hypothsis 21, hypothsis 22, hypothsis 23 and hypothsis 24, th bta paths did not duc, but incas. In paticula, this mans that mutual undstanding dos not mdiat th lationship and no potion of th influnc of absoption fdback on uss pfomancs is though mutual undstanding. Th sam happns with gad to intaction fdback on usability pfomancs. Tabl 23. Mdiation sults Hypothss Path Compaison (β1 - β2) Validation H16 COMMUNITY MU QofC 0,957 Suppotd H17 COMMUNITY MU QofD 0,181 Suppotd H18 COMMUNITY MU Usab 0,465 Suppotd H19 INTERACTION MU QofC 0,4 Suppotd H20 INTERACTION MU QofD 0,041 Suppotd H21 INTERACTION MU Usab -0,035 Not suppotd H22 ABSORPTION MU QofC -0,773 Not suppotd H23 ABSORPTION MU QofD -0,216 Not suppotd H24 ABSORPTION MU USAB -0,402 Not suppotd 182

184 Chapt Discussion This sach uss a common gound and gounding appoach in od to assss agumntation s mdiation capability in suppoting onlin distibutd dlibation and dcision making pocss. Accoding to th gounding thoy, agumntation tools a not so abl to fost asi, smooth and f communication and intaction. Indd, a substantial amount of sach on onlin agumntation has focusd mainly on knowldg psntation issus in od to find pop knowldg fomats fo psnting uss contibutions. On th oth hand, agumnt mapping sachs hav nglctd social and convsational aspcts of onlin intaction. As consqunc, agumnt mapping tools a objct-ointd ath than human ointd, lading to th objctification and fomalization of convsation aound th knowldg map, as wll as th loss of a ang of mta-infomation about paticipants, th intaction pocss though which th contnt is gnatd and gnatd contnt. Accoding to Clak and Bnnan [1991] th lacking of this mta-infomation hinds f intaction and maks convsations lss fficint [Clak and Bnnan, 1991]. In ality, th availability of mta-infomation containd into convsational fdback dos not only mak th convsation mo plasant fom th social point of viw, but abov all it facilitats th gounding pocss, i.. th constuction of shad undstanding btwn paticipants, thus incasing th fficincy and ffctivnss of a convsation [Clak and Bnnan, 1991; Convtino t al., 2008]. This has ngativly impactd on th us and widspad adoption of agumnt mapping tools as tchnologis abl to mdiat f intaction and communication. Thfo, in this sach, in od to tain th advantags offd by agumnt mapping tools but at th sam tim to impov thi capabilitis to mdiat intaction, w popos a nw tchnological solution, namly th Dbat Dashboad. It can b dfind as an augmntd agumntation platfom abl to dliv al-tim, visual convsational fdback to facilitat mutual undstanding and impov uss pfomancs. 183

185 Chapt 6 In od to tst ou appoach and, in paticula th Dbat Dashboad, a fild tst has bn pfomd at th Univsity of Napls Fdico II. In gnal it is possibl to stat that th obtaind sults confim th most pat of poposd sach hypothss. Thfo, visual fdback ffct mutual undstanding and uss pfomancs. In oth wods, it is possibl to affim that social and convsational fdback incass and suppots mutual undstanding among mmbs of goup A and impact on th quality of collaboation and of dcision. In nutshll, mutual undstanding, quality of collaboation and quality of dcision of goup A is significantly diffnt fom mutual undstanding and uss pfomancs of goup B. Fom SEM analysis is mgd that all visual fdback impact on mutual undstanding and on uss pfomancs, xcpt Community fdback that dos not impact on quality of dcision and on usability. In addition, mutual undstanding plays a cucial ol as mdiato and catalyst among visual fdback and uss pfomancs, xcpt among Absoption fdback and uss pfomancs (Quality of Collaboation, Quality of Dcision and Usability) and among Intaction fdback and Coh Usability. What w did not xpct that Intaction fdback affctd ngativly on Mutual Undstanding, but this could b xplaind by two main ason: i. Th dsign of visual widgts that povid this fdback is not appopiat and, thus, mo analysis hav to b pfomd, and ii. Th ducd numb of povidd fdback spct to that individualizd by Clak and Bnnan [1991]. In conclusion, this study maks impotant thotical and pactical contibutions. Fist, th study dvlopd and tstd a thotical modl of th influnc of visual fdback on mutual undstanding building among onlin distibutd uss involvd in collaboativ convsation mdiatd by agumnt mapping tools. To th bst of th sachs knowldg, no pvious study hav intgatd agumnt mapping tools with visual fdback. Futh, no pvious sachs has usd common gound appoach to impov agumntation tchnologis mdiation capabilitis. In addition, th conclusion that onlin collaboativ tools should b abl both to fost f communication and to aid a mo stuctud knowldg oganization has impotant 184

186 Chapt 6 pactical implications. Indd, ou findings show that social intaction and knowldg oganization a two cucial conditions fo suppoting succssful onlin collaboativ tasks, such as dlibation and dcision making pocss. Ths two aspcts should b considd as two souls of a sam lmnt that coopat in suppoting and nsuing ffctiv distibutd communication and collaboation. This has impotant pactical implications, in paticula fo who dvlops collaboativ knowldg managmnt tchnologis. Indd, though this sach, w know that th abov mntiond lmnts a cucial, but futh analysis has to b pfomd to btt undstand how and in what dosag ths two ingdints has to b mixd. 6.8 Limitation Although this study maks sval pactical and thotical contibutions, it has numous limitations which should b acknowldg. Th fist limitation of this sach is that paticipants w dawn fom a singl acadmic cous. Consquntly, th contxt is quit diffnt fom a fully opn onlin community. This psnts a significant limitation of this study, also bcaus th blonging to th sam goups mans that som studnts alady know ach oth and a fist lay of common gound was dvlopd. Th impact of this limitation has bn ducd though th andomization of goups. Anoth impotant consqunc of it, is that th gnalizability of findings a limitd. Indd, bfo th sults of this study can b gnalizd should b plicatd with oth community of xpts (i.. doctos, ngins and so on). Th scond limitation of this sach is th siz of sampls. Indd, th basic ida is to xpand th sampls in od to btt masu th ffctivnss and fficincy of visual fdback in mdiat and suppot lag discussion goups. This should allows us to obtain stong and mo accuat sults. 185

187 Chapt 6 Th thid limitation of this study is that w did consid in ou analysis dmogaphic vaiabls that could b instd in SEM modls. Th considation of dmogaphic vaiabls, such as ag, ya of study, avag xams, could giv us futh infomation about th us of visual fdback and, thus, on th impact of it on mutual undstanding and uss pfomancs. In oth wods, by contolling dmogaphic vaiabls, w could btt undstand th ol of visual fdback on uss mutual undstanding and pfomancs. Th final limitation of this disstation gads th us of Likt scal to collctd data. Indd, on of th main citicism is that Likt scal uss clos-ndd qustions. In this cas, th intviw can choos among a limitd ang of altnativs and may b ncouagd to giv an answ without flcting and psonal involvmnt [Russo and Vasta, 1988]. Anoth poblm is that th paticipants may b ncouagd to giv an answ though h/sh has nothing to say about th topic. Ths shotcomings could lad intviws to giv sponss not ational. In addition, as th itms a psntd squntially, paticipants could giv mchanic and always th sam sponss (so-calld spons st. In od to tackl this poblm, w intoduc som itms with an opposing smantic tndncis to mak vidnt vntual inconsistncis. Dspit th limitation idntifid abov, this disstation has povidd sval thotical and pactical implications. Non of th limitations dtact valu and igoous mthodological usd. 186

188 Appndix A Litatu viw on Visualization Tools In this appndix, w intoduc a litatu viw on a sampl of thity visualization tools abl to povid infomation about onlin community, its mmbs, intaction pocss and gnatd contnt. W built ou sampl by using solly tools that hav bn implmntd. Som of ths visualization tools a availabl onlin and us can dictly upload thi data and poduc gaphic psntations (fo instanc, s ManyEys and/o Pfus sits). Th visualization tools slctd and viwd hav bn ou bnchmak fo dfining ky fatus of visual widgts that compos th Dbat Dashboad; in oth wods, w usd thm to inspi th dsign and in th implmntation of a dbat dashboad. W analyzd ach of thm on th basis of ou poposd fdback to undstand. Tabl A1 shows all tools in ou sampl. This tabl psnts th visualization tools by ou dfind fdback catgoy, ou poposd fdback sub-classs and implmntation dsciption. 187

189 Tabl A1. Rviw of Visualization tools VISUALIZATION N TOOLS 1 Babbl (Eickson and Kllogg, 2000) 2 BulB (Mohamd t al., 2004) FEEDBACK CATEGORY Intaction Fdback Intaction and Absoption Fdback 3 Chang tmap Absoption Fdback 4 Chat Cicls (Vigas and Donath, 1999) 5 Chat Cicls II (Donath and Vigas, 2002) 6 Chatscap (Donath and Vigas, 2002) Intaction Fdback Intaction Fdback Community and Intaction Fdback FEEDBACK Copsnc Visibility Stuctuing Copsnc Visibility Cotmpoality Simultanity Copsnc Mobility Visibility Cotmpoality Simultanity Visibility Cotmpoality Simultanity Idntikit IMPLEMENTATION A cooki psnts th convsation aa and th mabls psnt th uss. Th mabls of activ popl a psntd na th cnt of th cooki, whil ons of inactiv popl a psntd na th piphy. Mabls outsid of th cooki psnt popl in diffnt convsation. Stms psnt ach thad and thi hight psnts how long thy a activ. Th stm-had can psnt ith th dvlopmnt of thad (ach lin is a post) o us thad paticipation (ach colou is a us). A Tmap is a visualization of hiachical stuctus. Tmaps nabl uss to compa nods and sub-ts vn at vaying dpth in th t, and hlp thm spot pattns and xcptions. Itms a dividd into catgois, subcatgois, and go on. This tool allow to visualiz changs in th stuctu of th data Th popl a psntd by coloud cicls. Thy bightn whn a us dits a post and thy gow to accommodat th txt insid thm. Thy fad and diminish in piods of silnc, though thy do not disappa compltly so long as th paticipant is connctd. Th cicls mov aound th scn simulating thi movmnt btwn diffnt topics in th chat. Thy lav a tac that fads ov tim. Chatscap intoducs bhavioual psntation. Actions chang th icon s appaanc; ths changs a divn by both th us s pfncs and th judgmnt of th oth paticipants.

190 VISUALIZATION N TOOLS 7 Commnt flow (Offnhub and Donath, 2008) FEEDBACK CATEGORY Intaction Fdback 8 CommnT Intaction Fdback 9 Communication-Gadn Systm (Zhu, and Hsinchun, 2008) 10 Convsation Map (Wan, 2000) Intaction and Absoption Fdback Intaction and Absoption Fdback FEEDBACK Squntiality (ply stuctu) Squntiality (ply stuctu) Squntiality (ply stuctu) IMPLEMENTATION This tool allows visualizing communication bhaviou. It consids th paamts: - th tmpoality of th ntwok (though th opacity of th nods), - on vs. two way communication, - quantity of infomation xchangd (though a maks along th dg). Uss a psntd as obs of diffnt colous psnting thi gnd, blu - mals and pink - fmals. Each us has an icon associatd with thm dpicting how much thy commnt. Lss talkativ individuals a shown with on spch bubbl, whas th most talkativ hav Th. Commnt acs a dawn btwn obs whn on us snds anoth a commnt. Whn an ob civs a commnt, it is lit bightly so that it can b asily dtmind who is cuntly snding and civing communication. As uss cas communicating thy fad away cating a visual dpth and allowing nw communications to b viwd asi. Thad visualiz mploys a floal psntation to gaphically dpict th livlinss of a thad. Th flow psntation psnts such statistic as numb of mssags (ptals), numb of paticipants (lavs) and tim duation (hight of stms). Popl visualiz mploys th sam flow. Th floal psntation psnts such statistic as numb of mssags (ptals), numb of discussions (lavs), and tim duation (hight of stms). In this psntation th flows hav th facs. It psnts social ad smantic ntwok. In th fom, th nods psnt paticipants and th links psnt cipocal quotations o sponss. Th shot link, mo fquntly thy cipocatd quot o spons. Th smantic ntwok is a t; it is plottd lik a spid wb, so that th child nods of th oot a dawn at a ctain adius out fom th oot, th childn of th childn a dawn a bit futh out in a ing aound th childn. If two nods in th smantic ntwok a connctd, thn mpiically thy hav oftn bn usd in th sam way in th achiv.

191 N VISUALIZATION TOOLS 11 Coti (Donath, 2002) FEEDBACK CATEGORY Intaction Fdback 12 map Intaction Fdback 13 Exhibit Community Fdback 14 Flowgadn Intaction Fdback 15 FoumRad (Dav t al., 2004) 16 Histoy Flow (Vigas t al., 2004) Absoption Fdback Absoption Fdback FEEDBACK Copsnc Visibility Simultanity Cotmpoality Squntiality (ply stuctu) Pofil Squntiality (ply stuctu) Stuctuing Stuctuing IMPLEMENTATION It psnts two ky lmnts: th activity of th paticipants and th stuctu of convsation. Uss a psntd as coloud ovals that bounc and bcam bight whn a us spaks. Som sntncs appa on th scn and cohsiv discussions hav a singl column, whil divgnt ons hav ntis scattd acoss th scn. It shows all uss pictus in a cicula way and whn uss talk ach oth, th is a link btwn thm. Th intnsity of th lationship is dtmind by th intnsity of th lin. It allows visualizing and filting infomation about mmbs on gogaphic maps and timlin. Each paticipant is psntd by a flow, with a ptal gowing on th flow in al-tim as a nw convsation is ntd. Th flows of individuals who hav convsd with on anoth a connctd by gn vins, and th clos two flows a distancd fom ach oth th mo thos popl hav spokn. Th concpts discussd btwn all paticipants a laid out in th backgound accoding to thi fquncy of us. It uss ctangls to psnt ach post in th discussion. Rctangl hight cosponds to th lngth of th post. Th mssag can b coloud with diffnt colous to highlight attibuts slctd by uss. It allows uss to slct a topic and highlight all of its posts o to povid a gadd colouing of posts simila to a slctd post (this systms uss kywods). To ach us is associatd a colou and ach his/h post is psntd with a vtical lin. Th lngth of th vtical lin indicats th amount of txt. Conncting th diffnt sgmnts (intvntion) of conscutiv vsions is possibl to undstand th volution both of th map and of th individual intvntion. Th gap (i.. that pat of th txt has no cospondnc in lat) indicats that th has bn th limination of th contibution. Th majo topics a psntd thanks to th width of ach flow.

192 VISUALIZATION N TOOLS 17 Loom (Donath, 2002) 18 NwsGoup Cowd and AuthoLins (Vigas and Smith, 2004) 19 PoplGadn (Xiong and Donath, 1999) FEEDBACK CATEGORY Intaction Fdback Intaction Fdback Intaction Fdback FEEDBACK Squntiality (Rply stuctu) Squntiality (Rply stuctu) IMPLEMENTATION Each post is psntd with a dot. Th links xisting psnt th connctions btwn squntial posts in a thad. NwsGoup Cowd: It is a scatt plot of ach autho is psntd by cicl and its siz dpnds on th amount of catd posts. Th colou of ach autho s cicl psnts how cntly authos hav bn activ. AuthoLins: Month nams a displayd at th top of th visualization panl. Vtical lins of cicls psnt wkly activity: ach cicl stands fo a convsation thad to which th autho has contibutd duing that wk. Th siz of th cicl psnts th numb of mssags. Oang cicls psnt thads that w initiatd by th autho; yllow cicls a thads statd by oth uss. It uss a flow and gadn mtapho. Uss a psntd by a flow. Th long thy hav bn involvd, th high th stm. Initial postings a in d, plis in blu. Each thad is a gadn full of flows. Th ply stuctu is psntd though a bud on th answd ptal.

193 VISUALIZATION N TOOLS 20 PostHistoy and Social Ntwok Fagmnts (Vigas t al., 2004) FEEDBACK CATEGORY Intaction Fdback FEEDBACK Squntiality (ply stuctu) IMPLEMENTATION PostHistoy intfac is dividd into two main panls: th calnda panl on th lft, which shows th intnsity of mail xchangs ov tim, and th contacts panl on th ight, which shows th nams of th popl with whom go has xchangd mail. In calnda panl, ach squa psnts a singl day. Th siz of it psnts th quantity of mail civd on that day. In contacts panl th a th visualization mods in th contacts panl: vtical, cicula, and alphabtical. Fo th fist and th scond mod, th most fqunt contacts a visually closst to go. Social Ntwok Fagmnts vals th factd contxts that popl systmatically cat. It compiss of two diffnt panls: th pimay social ntwok panl and a histoy panl. Th histoy panl dpicts ach tim slic as a two squas. Th out squa psnts th numb of awanss connctions that occu duing that tim piod whil th inn squa indicats th numb of knowldg tis. 21 SocialAction (P and Shnidman, 2006) 22 TagCloud (Hast and Rosn, 2008) 23 ThMail (Vigas t al., 2006) Intaction and Absoption Fdback Absoption Fdback Absoption Fdback Squntiality (ply stuctu) Stuctuing Contxtualization Rlvanc Rlvanc It is a gaph to psnts ntwoks. This tool allow to filt and to clust th infomation A tag cloud is a visualization of wods fquncy. Th siz of th wod cosponds to th quantity associatd with that wod. Whnv th mous is ov a wod, infomation about th occuncs of that wod and th contxt it was usd in will b shown in a tooltip. Tagcloud allows uss to compa two diffnt bodis of txt. Th intfac shows a sis of columns of kywods aangd along a timlin. Kywods a shown in diffnt colous and sizs dpnding on thi fquncy and distinctivnss. Yaly wods (usd th most usd tms ov an nti ya) a psntd as lag faint wods shown in backgound; whil monthly wods (th most distinctiv and fquntly usd wods ov a month) a psntd yllow and shown in fogound.

194 N VISUALIZATION TOOLS 24 ThmRiv (Hav t al., 2002) FEEDBACK CATEGORY Absoption Fdback 25 TimLin Absoption Fdback 26 TimPlot Absoption Fdback 27 TimVis Community Fdback 28 Tmap Absoption Fdback FEEDBACK Rlvanc Stuctu Stuctuing IMPLEMENTATION It uss iv mtapho. Th iv flows though tim, changing th width to dpict changs in th thmatic stngth. Thms o topics a psntd as coloud cunts flowing within th iv. Th iv is shown within th contxt of a timlin and a cosponding txtual psntation of xtnal vnts. It uss a tim chat whit month, day and hous; in this way it is possibl to psnt th vnts spcting chonological od. It is widgt fo plotting tim sis and ovlay tim-basd vnts ov thm. It is a social ntwok. A blu dot dnots a mal pson, whas a d dot dnots a fmal. Th dgs a also coloud dpnding on th invit s and invit's gnd. -fmal invits anoth fmal, w hav a d dg. -mal invits anoth mal, w hav a blu dg. -mal invits fmal, w hav a gn dg. -fmal invits mal, w hav a yllow dg. A Tmap is a visualization of hiachical stuctus. Tmaps nabl uss to compa nods and sub-ts vn at vaying dpth in th t, and hlp thm spot pattns and xcptions. Itms a dividd into catgois, subcatgois, and go on.

195 N VISUALIZATION TOOLS 29 WikiDashBoad (Suh t al., 2008) FEEDBACK CATEGORY Intaction and Absoption Fdback 30 Wodl Absoption Fdback FEEDBACK Rlvanc IMPLEMENTATION Aticl dashboad: that displays an agggat dit activity gaph psnting th wkly dit tnd of th aticl, followd by a list of th top activ ditos fo that pag. Th top summay gaph shows two tnds: a gay lin gaph psnting th dits mad on th aticl and a blu ba gaph dnoting th dits on th cosponding Talk discussion pag. Th wkly dit activity gaph of ach dito on th ight sid of th dashboad nabls uss to invstigat whn th dits by that dito w mad. A dak d ba dnots mo activity in a paticula wk. Blow th aticl dit summay, th activ uss of th aticl a odd by th numb of dits thy mad on th pag and its talk pag combind. Us dashboad: th top summay gaph shows th dito s wkly dit activity. Th summay gaph is followd by th list of Wikipdia pags wh th dito has mad dits. Th list is odd by th volum of contibution and includs th cosponding aticl-dito activity gaphs on th ight sid. A "Wodl" nabls us to s how fquntly wods appa in a givn txt. Th siz of a wod is popotional to th quantity associatd with that wod.

196 195 Appndix B Post sssion qustionnai # Qustionnais itms Likt Q1 Th intaction lvl dvlopd duing Cohmdiatd convsation was satisfying Q2 I found th onlin discussion intsting and ngaging Q3 Collaboation was ffctiv to solv assignd poblm Q4 I found it difficult to kp tack of th convsation Q5 Th agumnt map was hlpful in facilitating knowldg shaing among oth tam mmbs Q6 I shad my own knowldg about th task with my tammats Q7 I found that my tammats hav shad own thi knowldg about th task Q8 Th goup dvlopd a good amount of wok S t o n g l y D i s a g N u t a l S o m w h a t A g M o d a t l y A g S t o n g l y D i s a g N u t a l S o m w h a t A g M o d a t l y A g S t o n g l y D i s a g N u t a l S o m w h a t A g M o d a t l y A g S t o n g l y D i s a g N u t a l S o m w h a t A g M S t o n g l y D i s a g M o d a t l y D i s a g S o m w h a t D i s a g N u t a l S o m w h a t A g M S t o n g l y D i s a g M o d a t l y D i s a g S o m w h a t D i s a g N u t a l S o m w h a t A g M o d a t l y A g S t o n g l y D i s a M o d a t l y D i S o m w h a t D i s a N u t a l S o m w h a t A g M o d a t l y A g

197 Appndix B 196 # Qustionnais itms Likt Q9 Th goup mad a good job Q10 I think that, at th nd of onlin dbat, th goup has a common position about th discussion topic Q11 What is you initial dcision bfo discussing with oth goup mmbs? Q12 What is you dcision at th nd of onlin dbat? Q13 What is goup s dcision at th nd of th discussion? Q14 In gnal, I hav not had poblms to undstand th maning of oth tam mmbs posts Q15 In gnal, I think that th oth tam mmbs hav undstood my contibutions without difficulty Q16 I could asily undstand (tll) what my tammats had don on Coh Q17 I could asily undstand who has don what Q18 I could asily say who is onlin on Coh N u t a l S o m w h a t A g M o d a t l y A g S t o n g l y D i s a g N u t a l S o m w h a t A g M o d a t l y A g P i c i n c a s s P P i c i n c a s s P P i c i n c a s s P N u t a l S o m w h a t A g M o d a t l y A g S t o n g l y D i s a g N u t a l S o m w h a t A g M o d a t l y A g S t o n g l y D i s a g N u t a l S o m w h a t A g M S t o n g l y D i s a g N u t a l S o m w h a t A g M S t o n g l y D i s a N u t a l S o m w h a t A g M o d a t l y A g

198 Appndix B 197 # Qustionnais itms Likt Q19 My tammats and I dvlopd btt undstanding about ach oth ov th two wks Q20 My tammats and I dvlopd shad undstanding about th task ov th tim Q21 I found onlin convsation is oftn dundant Q22 I found th a many ilvant posts spct th assignd task Q23 Intaction with th systm dos not qui a lot of my mntal ffot Q24 I find th systm to b asy to us Q25 I njoyd collaboating with my tammats using Coh Q26 I would njoy woking with my tammats again using Coh Q27 It was asy to communicat ffctivly givn th tools availabl Q28 Coh suppots and facilitats collaboation among onlin uss S t o n g l y D i s a g N u t a l S o m w h a t A g M o d a t l y A g S t o n g l y D i s a g N u t a l S o m w h a t A g M S t o n g l y D i s a g N u t a l S o m w h a t A g M S t o n g l y D i s a g N u t a l S o m w h a t A g M S t o n g l y D i s a g N u t a l S o m w h a t A g M o d a t l y A g S t o n g l y D i s a g N u t a l S o m w h a t A g M o d a t l y A g S t o n g l y D i s a g N u t a l S o m w h a t A g M o d a t l y A g S t o n g l y D i s a g N u t a l S o m w h a t A g M o d a t l y A g S t o n g l y D i s a N u t a l S o m w h a t A g M o d a t l y A g

199 Appndix C SEM Gaph In this appndix, w psnt fou scnshots that show sults diving fom SmatPLS. Simpl Modl PLS Analysis Simpl Modl Bootstapping Analysis 198

200 Appndix C Mdiatd Modl PLS Analysis Mdiatd Modl Bootstapping Analysis Ths modls psnt th two stps of pocdu to pfom mdiation analysis to tst th hypothss that Mutual Undstanding mdiats th lationships among visual fdback and uss pfomancs, namly Quality of Collaboation, Quality of Dcision Usability. 199

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