Computers in Human Behavior 27 (2011) 2078–2087

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Computers in Human Behavior

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Fostering sharing of unshared knowledge by having access to thecollaborators’ meta-knowledge structures

Tanja Engelmann ⇑, Friedrich W. HesseKnowledge Media Research Center, Konrad-Adenauer-Str. 40, 72072 Tuebingen, Germany

a r t i c l e i n f o a b s t r a c t

Article history:Available online 1 July 2011

Keywords:Computer-supported collaborative problemsolvingKnowledge and information awarenessUnshared knowledgeCollaborators’ meta-knowledge

0747-5632/$ - see front matter � 2011 Elsevier Ltd. Adoi:10.1016/j.chb.2011.06.002

⇑ Corresponding author. Tel.: +49 7071 979 239; faE-mail addresses: t.engelmann@iwm-kmrc.de (T. En

de (F.W. Hesse).

The present experimental study focuses on two problems occurring in computer-supported collaborativelearning situations: First, it has been empirically proven that groups discuss mainly shared information,that is, information already known to all group members, while unshared information, that is, informa-tion known to only one member, is often neglected. However, such unshared information could be task-relevant. Therefore, taking unshared information into consideration should be fostered. Second, Wegner’stheory of transactive memory system points out that groups perform better when the group members areinformed about their collaborators’ knowledge. However, acquiring correct knowledge about what othersknow is difficult. An approach for solving these two problems is introduced which provides the groupmembers with the collaborators’ meta-knowledge structures by means of digital concept maps. Thestudy compares 20 triads with spatially distributed group members that had access to their collaborators’meta-knowledge maps with 20 triads collaborating without these maps. Results showed, as expected,that the triads having been provided with such maps started sooner to discuss unshared information,applied more of their collaborators’ unshared information, and processed unshared information moredeeply. Additional results, however, demonstrated in contrast to Wegner’s theory that being informedabout the collaborators’ meta-knowledge is not sufficient to increase group performance.

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1. Introduction

In the current information society and times of globalization, theamount of information individuals encounter increases continu-ously and the problems that have to be solved are becomingincreasingly more complex. Very often even experts have only asmall amount of the information that is necessary to solve aspecific complex problem, for example in the field of environmentalpollution. Solving such problems requires the collaboration of dif-ferent experts. However, due to the necessarily distinct expertisetoday, experts that are needed to solve a complex problem are oftenspatially distributed and do not know each other. Therefore, collab-oration over distance has become increasingly important. However,computer-supported collaboration still causes a lot of problems. Be-side all the problems caused in connection with computer-support(e.g., the reduced contextual information), the group members alsohave to deal with problems regarding collaboration. The presentempirical study focuses on two collaboration problems that also oc-cur in computer-supported collaborative group work.

First, empirical studies (e.g., Stasser, Stewart, & Wittenbaum,1995) have demonstrated that groups mainly focus their discus-

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x: +49 7071 979 100.gelmann), f.hesse@iwm-kmrc.

sion on shared information, that is, information already known toall group members, while unshared information, that is, informa-tion known to only one member, is often neglected. As a result ofthis neglect, the task-relevant aspects of this unshared informationcould remain undiscovered, and thus would not be considered forsolving the group task.

Second, for effective working and learning in groups, it is impor-tant to know what the collaborators know (cf. Engelmann & Hesse,2010). However, it is not easy to acquire such knowledge (e.g.,Nickerson, 1999), especially for newly formed groups participatingin a computer-supported collaboration and, therefore, having todeal with reduced contextual information (Kiesler, Siegel, &McGuire, 1984).

In the present study an approach for solving these two collabo-ration problems is investigated.

In this paper, we explain first why sharing of unshared informa-tion is a problem in group situations and which approaches alreadyexist that try to solve this problem. Then we highlight why incollaborative learning settings it is important to know what thecollaborators’ know. Further we describe an approach that fostersawareness regarding the collaborators’ meta-knowledge structuresand explain why it should be effective in solving these two collab-oration problems. Subsequently, an empirical study is presentedinvestigating both whether the approach for fostering the aware-ness of other group members’ meta-knowledge structures

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increases sharing and processing of unshared information as wellas whether this approach also increases the acquisition of knowl-edge with regard to the collaborators’ meta-knowledge, and there-fore, improves computer-supported collaboration of spatiallydistributed group members. The paper ends with a discussion ofthe results and conclusions.

2. Reducing the communication bias in favor of sharedinformation

Intuitively one may think that groups outperform individuals,for example in decision tasks, because each member of a groupmay contribute his/her own unique information leading as a resultto more informed decisions (cf. Stasser & Titus, 2003). In fact, asseveral studies have demonstrated (e.g., Gigone & Hastie, 1993;Stasser, Taylor, & Hanna, 1989; Stasser & Titus, 1985, 1987), groupstend to focus their discussion on shared information and generallydo not effectively pool unshared information. Thus, the assumedgroup advantage is not gained.

The literature provides many approaches for explaining this of-ten replicated effect: For example according to the collective infor-mation sampling (CIS) model by Stasser and Titus (1987), the moregroup members there are who know a particular information ele-ment, the higher is the probability that this information elementwill be mentioned in the group discussion. This model was ex-panded by Larson, Foster-Fishman, and Keys (1994) in their dy-namic collective information sampling (DCIS) model by addingthe idea that in the course of a group discussion, the pool of sharedinformation not discussed becomes smaller, so that the probabilityof mentioning unshared information increases. However, this DCISmodel does not consider social aspects of group decisions, forexample that groups may discontinue their discussion too early(Stasser & Titus, 2003) or that group decisions are influenced byconformity or compliance aspects (e.g., Cialdini & Goldstein, 2004).

Another related problem is also demonstrated in the literature:It is not sufficient to share unshared information, in the sense ofmentioning it once and forgetting again that it exists. The unsharedinformation must also be used to form the decision, that is, it mustbe discussed with regard to its task relevance. As different studieshave shown, the probability of making use of a mentioned un-shared information element is considerably lower compared tothe probability of making use of a mentioned shared informationelement (Larson, Christensen, Abbott, & Franz, 1996; Stasseret al., 1989).

These findings by Stasser and colleagues that gave evidence thatgroups do not work effectively may also be explained by the theoryof transactive memory system of Wegner (1986). According toWegner, groups achieve a good performance if the group membersknow which member is expert for which topic and use communi-cation to get access to the others’ knowledge. A possible explana-tion for the reason why in the groups investigated by Stasser andhis colleagues the group performance was low could be that thesegroups did not have a transactive memory system, that is, that thegroup members did not know who was an expert for which topicand, therefore, could have had unshared, but task-relevant infor-mation. Thus, it has to be assumed that making the expertise ofthe other group members salient would foster sharing of unsharedinformation. This assumption was empirically tested for examplein a study by Stasser, Vaughan, and Stewart (2000). In their study,the following two conditions were compared. In a role-assignmentcondition the group members’ expertise was publicly identified atthe beginning of the group discussion by the experimenterannouncing who had additional information about a specific topic.In a control condition, there was no role assignment. It could beshown that role assignment increased sharing of unshared infor-mation, while there was no effect on sharing of shared information.

There have also been earlier studies investigating the effects of roleassignment in such scenarios, leading to similar findings (e.g., Stas-ser et al., 1995; Stewart & Stasser, 1995). However, the effect sizesare very small. For example, in the study by Stasser et al. (2000)role assignment increased the percentage of mentioning unsharedinformation from 29% to 34%.

Besides the effect of mentioning unshared information in groupdiscussion, such studies were also able to demonstrate that roleassignment also has an impact on the processing of already men-tioned unshared information. For example, in the study by Stewartand Stasser (1995), the role-assigned groups included more un-shared information in their written protocol compared to the con-trol condition.

Stasser et al. (1995) explained these two effects of role assign-ment with respect to the finding that role assignment increasesthe group members’ awareness of their own expertise as well astheir awareness of the other group members’ expertise. In addition,they could show that awareness of both their own expertise andthat of the other group members fosters sharing of unsharedinformation.

3. The importance of knowing what the collaborators know

Besides the communication bias in favor of shared information,collaborators have also to deal with other problems, for examplewith regard to knowing what the collaborators know. Different re-search fields have demonstrated the importance of knowing whatcollaborators know in order to be able to communicate and collab-orate effectively (cf. Engelmann & Hesse, 2010): First, research onaudience design gave evidence that knowing what the collaboratorknows may change certain behavior. For example, people writelonger texts if the addressee is a novice in this topic (e.g., Dehler,Bodemer, & Buder, 2007). Second, Nickerson’s approach (1999)pointed out that effective communication requires knowing whatthe communication partner knows. For example, having inaccurateknowledge of one’s partners’ knowledge may lead to misunder-standing. Third, the theory of transactive memory system (Wegner,1986, 1995) also highlights the importance of knowing what thecollaborators know. According to Wegner (1986, 1995) groupmembers need to know what knowledge is stored by which collab-oration partner and via communication, they have access to theircollaboration partners’ knowledge. There is a lot of empirical evi-dence that an effective transactive memory system increases thegroup performance (for an overview see Peltokorpi, 2008).

As these approaches – and also other approaches that could beadded, such as the common ground theory of Clark and Brennan(1991) – have demonstrated, knowing what the collaboratorsknow is important in group situations. However, this knowledgeis not so easy to acquire. While developing such knowledge manydifferent mistakes, such as wrong conclusion from what one hasheard, may occur (for an overview of different possible misjudge-ments, see Nickerson, 1999). In addition, groups need enough timeto establish an effective transactive memory system (Wegner,1986). A proven solution approach for this problem already exists,namely, the approach for fostering awareness regarding the collab-orators’ knowledge and information (e.g., Engelmann, Dehler,Bodemer, & Buder, 2009; Engelmann & Hesse, 2010; Engelmann,Tergan, & Hesse, 2010).

4. An approach for fostering knowledge and informationawareness and for improving group performance

In this chapter, an approach is described that is expected, on theone hand, to reduce the communication bias in favor of sharedinformation and, on the other hand, to increase group performance

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by fostering knowledge and information awareness. Engelmannand colleagues (e.g., Engelmann & Hesse, 2010) defined the term‘‘knowledge and information awareness’’ as being informed withregard to the collaborators’ knowledge structures and underlyinginformation and fostered it by providing the group members accessto both their collaborators’ knowledge structures and underlyinginformation both visualized via digital concept maps. These con-cept maps represented task-relevant and labeled concepts as wellas task-relevant and labeled relations between these concepts.The concepts and relations represented the knowledge structuresof the collaborators. In addition, the concepts were linked to infor-mation elements describing in more detail the correspondingconcepts. By mouse clicking on a concept the corresponding infor-mation element was provided in a small desktop window.

In several studies, it was demonstrated that this approach fos-ters the acquisition of knowledge and information awareness ofspatially distributed group members collaborating computer-sup-ported (e.g., Engelmann & Hesse, 2010; Schreiber & Engelmann,2010). Because the findings of Stasser et al. (1995) demonstratedthat being aware of one’s own expertise and that of the others helpsto reduce the communication bias in favor of shared information, itcan also be expected that the approach of Engelmann and col-leagues will foster sharing and processing of unshared information.

The studies by Engelmann and colleagues showed that their ap-proach not only fosters knowledge and information awareness, butalso increases the success of computer-supported, collaborativeproblem solving: In their first study, by supporting knowledgeand information awareness, they were able to enhance group per-formance of simulated virtual triads, that is, group members sittingin the same room, but separated by dividing walls so that theycould not see, but could speak with each other (Engelmann, Bau-meister, Dingel, & Hesse, 2010). In their follow-up study, theycould replicate these findings with real virtual groups, that is,groups with spatially distributed group members (Engelmann &Hesse, 2010). They were also able to give evidence for this effectwith other domain material and a more complex group task(Schreiber & Engelmann, 2010).

However, to date, it is not clear what causes the positive impactof this approach for fostering knowledge and information aware-ness on computer-supported collaborative problem-solving. Is itbecause it makes the collaborators’ concrete task-relevant knowl-edge available or because it makes the collaborators’ meta-knowl-edge available? The term ‘‘concrete task-relevant knowledge’’refers to knowledge elements that are needed to solve the grouptasks. Group members are aware of their ‘‘collaborators’ meta-knowledge’’ when they know which topics the collaborators haveexpertise in, without knowing the concrete task-relevant knowl-edge. This differentiation between concrete task-relevant knowl-edge and meta-knowledge is explained by the followingexample: To know that one collaborator knows that the pesticide‘‘Herm’’ combats ‘‘material bugs’’ very efficiently is concrete task-relevant knowledge and contains the two concepts ‘‘Herm’’ and‘‘material bugs’’ as well as the relation ‘‘combats very efficiently’’.Only to know that the collaborator knows something about‘‘Herm’’, ‘‘material bugs’’, and that they are somehow related is,however, not enough to solve the problem and, therefore, not di-rectly task-relevant. In this paper, such abstract knowledge iscalled meta-knowledge.

Concrete task-relevant knowledge was distributed among thethree group members in a way that each of the members had thesame number of unshared knowledge elements, with one othermember or both other members shared knowledge elements. In or-der to solve the group tasks, the three group members had to com-pile all shared and unshared knowledge elements. This concretetask-relevant knowledge of each collaboration partner was repre-sented to a group member by labeled concepts and labeled rela-

tions between the concepts. Collaborators’ meta-knowledgerefers to knowing in which topics the collaborators have expertise,without knowing the concrete task-relevant knowledge. Referringto Wegner’s theory of transactive memory (1986, 1995), it is suffi-cient for group members to know which experts had knowledge ofwhich topic, that is, meta-knowledge, without knowing the others’concrete knowledge.

Therefore, in the present study, a reduced approach for fosteringknowledge and information awareness was applied providing thegroup members only with the collaboration partners’ meta-knowl-edge structures, that is, without providing their collaborators’ con-crete task-relevant information. Such a reduced approach is muchless complex and, therefore, easier to apply compared to Engel-mann’s knowledge and information awareness approach appliedformerly (e.g., Engelmann & Hesse, 2010).

In addition, regarding the described problem of not sharing un-shared information, one must assume that this reduced approachwill also reduce the communication bias in favor of shared infor-mation, because the reduced approach also provides more infor-mation regarding the others’ expertise as the role assignmentapproach applied by Stasser and colleagues (e.g., Stasser et al.,1995).

5. Empirical study

The empirical study presented in this paper had two goals: First,we investigated whether the communication bias in favor ofshared information could be overcome by having access to mapsrepresenting the meta-knowledge structures of the collaboratorsas well as the information elements underlying this knowledge.More concretely, it was investigated whether the group membersshare more of their unshared knowledge and information, if theyare provided with their collaborators’ maps representing theirmeta-knowledge structures.

Second, we investigated whether it is sufficient to have accessto the meta-knowledge structures of the collaborators to improvecollaborative computer-supported problem-solving performanceof spatially distributed group members. More concretely, by meansof the present study, the question should be answered whether thefindings of Engelmann and Hesse (2010) could be replicated withmaps representing only the collaborators’ meta-knowledge (i.e., la-beled nodes and unlabeled relations between the nodes), instead ofcomplete concrete task-relevant knowledge (i.e., labeled nodes andlabeled relations between the nodes).

5.1. Method

In the present study, two conditions were compared: In thecontrol condition, the group members had access to a shared work-ing window and one’s own individual concept map containingone’s own knowledge structures and underlying information. Inthe experimental condition, the group members were additionallyprovided with two digital concept maps each representing themeta-knowledge structure of a collaborator.

5.1.1. ParticipantsParticipants were 120 university students (94 female, 26 male)

from different fields of study and with an average age of24.68 years (SD = 3.06). They volunteered to participate for eitherpayment or course credit. The participants were randomly as-signed to one of the conditions and took part in groups of three.Therefore, 20 control groups and 20 experimental groups wereinvestigated.

The group compositions with regard to gender was controlled:In each condition were one group with no women, one group with

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one woman, eight groups with two women, and ten groups withonly women. Also the degree of acquaintance between the groupmembers was controlled by questionnaire items asking the groupmembers whether they knew none or one or both of the collabora-tors. There was no significant difference between the conditionsregarding the degree of acquaintance (F < 1).

5.1.2. Setting and materialsThe setting and the materials were similar, but not identical to

those used in the study by Engelmann and Hesse (2010). In the fol-lowing description the differences with respect to this previousstudy are highlighted.

Each of the three group members was sitting in his or her ownroom that was equipped with a desk and a computer. The groupmembers were able to speak with each other by using Skype, anInternet phone software. They worked synchronously with differ-ent shared and unshared desktop windows.

The experimental environment used in the main phase of thestudy was generated by using CmapTools, a digital concept map-ping software developed by the Florida Institute for Human andMachine Cognition (USA).

The study was held in German. In this paper, all materials thatwere used in the study have been translated to English.

The domain focused on rescuing a fictitious type of spruce for-est and consisted of 13 concepts, 30 relations between the con-cepts, and 13 pieces of background information (in parts divisibleinto sub-elements). These elements were evenly distributedamong the three group members in a way that each member hadtwo unshared and five shared concepts, seven unshared and sixshared relations, five unshared and two shared pieces of back-ground information. The shared elements were shared with eitherone collaborator or both collaborators.

Several online questionnaires to be filled out individually wereused in the study.

First, participants filled out an online questionnaire assessingcontrol measure items, such as items regarding experience withcomputers, mapping techniques, and group work. The question-naire consists of 24 multiple-choice items designed as 5-point rat-ing scales ranging from complete agreement to no agreement.Item-examples are: ‘‘I like to work with a computer’’, ‘‘I have al-ready created a concept map’’, or ‘‘I like team work’’.

Second, in contrast to the study by Engelmann and Hesse(2010), three problem-solving tasks were included in the presentstudy in order to assess the processing of unshared information.They were not pre-announced to the participants and had to besolved individually after the collaboration phase. In order to beable to find the correct solutions, the group members neededknowledge about the unshared background information. Thesepieces of information were not task-relevant in the collaborativephase and therefore, might be considered as task-irrelevant bythe participants. For solving two of the three problem tasks, theparticipants needed to find the correct pesticide for a specific pesttype plague in different forests and had to give reasons for theirselection. Solving the third problem task required finding theneeded fertilizer. An item-example for one of these problem solv-ing tasks is as follows: ‘‘In a specific birch forest a plague of locustshas broken out. Locusts are very intelligent and eat only pure veg-etable things. They recognize artificial things immediately. Thegood news is that all types of pesticides act similarly with respectto locusts; however, the locusts have to eat it. Which of the pesti-cides should be used and why?’’

Third, an online knowledge test measuring what the groupmembers remember from their own and their collaborators’ knowl-edge and information was completed by participants. This test con-sisted of 36 multiple-choice test items and aimed at measuringknowledge of the collaborators’ background information, relations,

and concepts. These items were classified with regard to who pos-sessed the requested knowledge or information, resulting in fourtypes of items: (1) items asking for one’s own unshared elements,that is, items measuring knowledge that one alone had in his/herindividual map (Item example for Expert A: ‘‘Please mark which ex-pert(s) had information about the relation between RP/2 and fidget-grub – Expert A, B, or C?’’ Only Expert A had this information.), (2)items asking for the collaborators’ unshared elements, that is, itemsmeasuring knowledge that only one of the collaborators had (Itemexample for Expert A: ‘‘Please mark which expert(s) had informa-tion about the relation between Agrosol and phosphate – ExpertA, B, or C?’’ Only expert C had this information.), (3) items askingfor shared elements that one shared with one of the collaborators, thatis, items measuring knowledge that one had together with one ofthe collaborators (Item example for Expert A: ‘‘Please mark whichexpert(s) had information about the relation between spruce andnitrate – Expert A, B, or C?’’ Only Experts A and C had this informa-tion.), and (4) items asking for shared elements of the collaborators,that is, items measuring knowledge that only the two collaboratorshad (Item example for Expert A: ‘‘Please mark which expert(s) hadinformation about the relation between spruce and phosphate – Ex-pert A, B, or C?’’ Only experts B and C had this information.).

In the present study, this knowledge test is used as a manipula-tion check to assess the amount of acquired knowledge and infor-mation awareness. For this purpose, only the types of items fromcategories 2 and 4 are interesting and were analyzed.

Fourth, especially for this study, an online questionnaire wasgenerated for evaluating the study, the use of the concept mappingtool, team work, and in particular the contribution of unsharedknowledge. The items were assessed by 5-point rating scales rang-ing from 1 point for no agreement and 5 points for complete agree-ment. The questionnaire contained 45 items in the controlcondition; due to some additional items referring to the usefulnessof seeing the collaborators’ maps containing their meta-knowledgestructure and information, there were 63 items in the experimentalcondition.

Two paper-based instructions were provided to the groupmembers, according to the needs of this present study: one forexplaining and for practicing the use of CmapTools, and one forexplaining the next tasks before each test phase.

5.1.3. ProcedureFirst, each participant was asked to fill out the online question-

naire for measuring control measure items, before practicing howto use CmapTools. After ensuring that all participants were ableto draw digital concept maps with this tool, the main phase ofthe study started. By reading a paper-based instruction the groupmembers were informed that in this study they must pretend tobe three experts (Expert A, B, and C) who have to protect a spruceforest together. They were asked to imagine that each of them hadcreated in the past a digital concept map visualizing their ownknowledge and the underlying information that they have on thedomain of rescuing spruce forests. In an individual phase of thestudy, each of the group members had to review their own mapin order to be prepared for the collaborative phase. For this pur-pose, each member had access for 10 min to a pre-created digitalconcept map representing both one’s ‘‘own’’ conceptual knowl-edge, that is the concepts and the relations between them, andtheir ‘‘own’’ background information, that is information forexplaining in more details particular concepts.

After that the group members had to collaborate to solve twoproblems: First, they were asked to decide which pesticide theywould use to protect the spruce forest and how they justify theirdecision. Second, they had to decide which fertilizer they woulduse and how they justify this decision. They were informed thatfor each problem there was only one correct solution and that

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the correct answer of the second problem depended on the correctsolution of the first problem. Therefore, they were instructed tostart by solving the first problem, before starting with the secondone. For solving the problems, it was necessary to compile the con-ceptual knowledge of the group members. The background infor-mation was task-irrelevant. For this purpose, the group membershad access to a shared working window where they were askedto create a common digital concept map. They had 40 min to findthe answers for the problems and to write them on a sheet of pa-per. During this collaborative phase, they could speak with eachother by using Skype. In the control condition, the participantscould only see their own working window that contained theirown pre-created digital concept map and the shared working win-dow for creating a common digital concept map (see Fig. 1).

In the experimental condition, the group members also saw thepre-created maps of their collaborators. In contrast to the study byEngelmann and Hesse (2010), these pre-created maps of the col-laborators did not contain labeled relations connecting the con-cepts. The collaborators’ maps only contained labeled conceptsconnected by unlabeled lines, and background information. Thatis, the group members were only informed regarding the meta-knowledge of the others (see Fig. 2).

In this phase, log files of creating the group maps (by CmapTools),as well as video- and audio files (by Camtasia), were recorded.

Following this collaborative phase, each group member workedagain individually: First, each member was confronted with thethree unannounced problem-solving tasks requiring knowledgeof unshared background information. Second, they filled out the

Fig. 1. Collaborative phas

Fig. 2. Collaborative phase:

online knowledge test for measuring knowledge and informationawareness. Third, each group member completed the question-naire for evaluating the study and aspects of collaboration andproblem-solving. When working on these last three tasks, theyhad no time limits and no access to the experimental environment.

The procedure of the present study was similar, but not identi-cal to the study by Engelmann and Hesse (2010); for example,while the second individual phase was removed, an additionalindividual problem-solving one was included, as well as the focusbeing on sharing unshared information.

5.2. Expectations

First, it was expected that having access to the collaborators’digital maps representing their meta-knowledge structures willhelp to overcome the communication bias in favor of shared infor-mation. Second, it was expected that having access to the collabo-rators’ meta-knowledge structures improves computer-supportedcollaborative problem-solving.

5.2.1. Postulatedeffects regarding overcoming the communication biasin favor of shared information

Hypothesis 1. The groups in the experimental condition will startto discuss unshared concepts, unshared relations, and unsharedbackground information sooner compared to the groups in thecontrol condition.

e: control condition.

experimental condition.

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Hypothesis 2. Compared to the control condition, in the experi-mental condition, there will be more uptake events of unsharedinformation while creating the group map; that is, the group mem-bers of the experimental condition will include more unshared ele-ments in the group map that they do not possess themselves.

Hypothesis 3. Regarding solving the individual problem tasks thatrequires processing of unshared background information that wastask-irrelevant in the collaborative phase, the groups in the exper-imental condition will outperform the groups in the controlcondition.

Hypothesis 4. The willingness to share unshared information willbe mirrored in data from questionnaire items (item-example: ‘‘Didthe windows with the meta-knowledge maps of your collaboratorsmotivated you to contribute such information to the discussion,which the others still did not know?).

5.2.2. Postulated effects regarding improving collaborative problem-solving

Hypothesis 5. The group maps of the experimental condition willbe more suitable for solving the collaborative problem-solvingtasks compared to the group maps of the control condition.

Hypothesis 6. The groups in the experimental condition will out-perform the groups in the control condition regarding the two col-laborative problem-solving tasks.

5.3. Dependent measures

5.3.1. Dependent measures regarding sharing of unshared informationFor analyzing sharing of unshared information, the following

dependent measures were assessed:Discussing unshared information (to test Hypothesis 1). Three

variables were assessed: (1) the time when a group started to dis-cuss any specific unshared relation; (2) the time when a groupstarted to discuss any specific unshared concept; (3) the time whena group started to discuss any specific unshared background infor-mation. Discussing means that the groups not only mention an un-shared piece of information, but that they decide whether theinformation is task-relevant or not, or that they evaluate differentalternatives regarding their task-relevance. The unshared informa-tion has to be integrated into the problem-solving process in orderto be considered as discussed. The interrater agreements of twoindependent raters were calculated according to Shrout and Fleiss(1979) by means of intraclass correlation coefficients (ICC: one-way random single measures): for the start of the discussion of un-shared concepts ICC = 1.00, of unshared relations ICC = 0.99, and ofunshared background information ICC = 0.93.

Uptake events of unshared information while creating the groupmap (to test Hypothesis 2). The variable ‘‘uptakes regarding un-shared elements’’ was assessed by the number of events in whicha group member included a relation, a concept, or backgroundinformation into the group map that she/he did not possessedher/himself. Always when a group member included an unsharedelement of her/his collaborators in the group map, 1 point was gi-ven. According to Shrout and Fleiss (1979) the interrater agree-ment of two independent raters was ICC = 0.84 (two-way mixedsingle measure).

Problem-solving tasks based on unshared background informationto be solved individually (to test Hypothesis 3). The solution wascompared to the original one. For each correct answer to the three

problem-solving tasks, 1 point was given. If an answer was wrong,no point was assigned. Only if the answer was correct, the reasonsgiven as to why it was chosen were analyzed according to an ana-lyzing schema with 0 points for wrong reasons to up to 2 points formentioning the complete correct reasons.

Regarding the three problem-solving tasks, 3 points for correctanswers and 6 points for correct reasons could be received, that arein sum a maximum of 9 points. Interrater agreement was as fol-lows: for problem solving task 1 ICC = 1.00, for task 2 ICC = 0.88,and for task 3 ICC = 0.91 (two-way mixed single measures, cf.Shrout & Fleiss, 1979).

Descriptive data from questionnaire items (to test Hypothesis 4).Five 5-point rating scale items ranging from 1 for no agreementto 5 for full agreement were included in the experimental groupmembers’ questionnaire measured at the end of the study. Theseitems aimed at assessing motivational and behavioral aspects ofsharing unshared information.

5.3.2. Dependent measures regarding collaborative problem-solvingFor analyzing the impact of seeing the collaborators’ meta-

knowledge structure maps on collaborative problem solving, thefollowing dependent measures were assessed:

Problem-suitability of group maps (to test Hypothesis 5). For ana-lyzing the quality of the group maps that the group members cre-ated in the collaborative phase, five dependent measures wereassessed: the number of correctly drawn nodes, that is, nodes withcorrect labels (max. 13 attainable points), the number of correctlydrawn relations, which means the start and end node of the rela-tion as well as the label were correct (max. 30 attainable points),the number of incorrectly drawn nodes; these are nodes withwrong labels (attainable points: not limited), the number of incor-rectly drawn relations, meaning the start and/or end node and/orthe label were wrong (attainable points: not limited), the amountof background information (max. 13 attainable points).

In order to determine these dependent measures, the groupmaps were compared to an original map representing all correctconcepts, relations, and background information of the artificialdomain material. The groups received 1 point for each entry ofeach category (e.g., if the group map of Group 5 contained 8 cor-rectly drawn relations, this group received 8 points for the category‘‘correctly drawn relations’’). The interrater agreement wasICC = 0.85 for correct nodes, ICC = 0.92 for wrong nodes, ICC = 0.82for correct relations, ICC = 0.92 for wrong relations, and ICC = 0.98for the amount of task-irrelevant background information (two-way mixed single measures, cf. Shrout & Fleiss, 1979).

Quality of the problem solutions of the groups (to test Hypothesis6). For each correct answer to the two problem-solving tasks, 1point was given. Only if the correct solution was found, were thereasons given then analyzed according to an analyzing schemawith 0 points for a completely wrong answer and up to 3 pointsfor a completely correct answer. In order to determine the correct-ness of the reasons given, the answers were compared to the origi-nal correct reasons. For each problem, there was only one line ofargument. The interrater agreement of the two independent raterswith respect to the reasons given was calculated: Regarding thereasons given as to why they chose the correct pesticide, the inter-rater agreement was ICC = 0.96. With regard to the reasons given asto why they chose the correct fertilizer, the interrater agreementwas ICC = 0.91 (two-way mixed single measures, cf. Shrout & Fleiss,1979).

Descriptive data from questionnaire items. For corroborating thefindings regarding the research questions, subjective data were as-sessed by means of 5-point rating scales in a questionnaire in orderto determine, for example, aspects of communication and coordi-nation, as well as the use of CmapTools.

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6. Results

The experimental condition was compared with the controlcondition. All analyses presented here are based on the group le-vel. This was done for the following reasons: First, most of thedependent variables were variables on group level (e.g., thegroup answers, the group maps). Second, individuals in a groupare not independent of each other, therefore, variables measuredon the individual level were aggregated, that is, group meanswere calculated. This also assures having the same analysis levelas the group variables. Using groups as analysis level is an estab-lished method in small group research. According to Cress (2008),the analyses have to be based on aggregated data of individuals,for example in form of means, if groups are the units of theanalyses.

A factor analysis with Varimax rotation was conducted with the24 control measure items. It resulted in seven factors with eigen-values higher than 1. According to Bortz (1999), in a Varimax-ro-tated factor structure, only those factors are interpretable thathave at least four items with a loading >.60 or at least 10 itemswith a loading >.40. This criterion was met only by the factor ‘‘Pref-erence for Controlled Learning’’, that is, preference for learningwith a pre-created script and for individual learning. However, aunivariate ANOVA did not result in a significant difference betweenthe two conditions (F < 1). Therefore, the inclusion of a covariatewas not necessary.

As a descriptive index of strength of association between theexperimental factor and a dependent variable, partial eta-squaredvalues ðg2

pÞ are reported1 (Pierce et al., 2004).

6.1. Manipulation check

The goal of the manipulation check was to measure whetherhaving access to the pre-created meta-knowledge maps of thecollaborators results in more knowledge and informationawareness, that is, more knowledge regarding both the collabora-tors’ knowledge structures and the collaborators’ backgroundinformation.

In contrast to the expectations, the analyses did not result insignificant differences between the conditions: The analysis ofitems on knowledge that only one of the other two collaboratorshad resulted in F < 1 and also the analysis of items on knowledgethat only the other two collaborators had resulted in F < 1.Regarding the total value of items for measuring knowledgeand information awareness, the difference was also not signifi-cant: MC = 13.27; ME = 13.99; F(1, 38) = 1.08; MSE = 14.45;p = .30).

However, descriptive results of the questionnaire at the end ofthe study point to the helpfulness of having access to the collab-orators’ knowledge maps: The group members of the experimen-tal condition rated on a rating scale from 1 point for no agreementand 5 points for full agreement that having an overview regardingthe others’ knowledge was helpful (M = 4.32; SD = 0.64) and useful(M = 4.22, SD = 0.61). However, they also indicated that it wouldhave been better if they also would have been able to see thelabeling of the relations between the concepts (M = 4.33; SD =0.60) and that it would have been better if they would have beenable to see a complete concept map of the others (M = 4.15;SD = 0.52).

1 Partial eta-squared value of an experimental factor is defined as ‘‘the proportionof total variance attributable to the factor, partialling out (excluding) other factorsfrom the total nonerror variation’’ (Pierce, Block, & Aguinis 2004, p. 918). Due to thefact that classical eta-squared values for an effect are dependent upon the numberand the magnitude of other effects, partial eta-squared values are preferred in thispaper (Cohen, 1973).

6.2. Results on overcoming the communication bias in favor of

6.2.1. Results on starting to discuss unshared informationCompared to the control groups, the experimental groups dis-

cussed earlier both an unshared relation (MC = 13:27 min.;ME = 8:12 min.; F(1, 38) = 5.49; MSE = 647973184.7; p < .05; g2

p =.13) as well as an unshared concept (MC = 15:14 min.; ME = 8:13;F(1, 38) = 11.71; MSE = 544749930.0; p < .01; g2

p = .24). There wasno significant difference between the conditions regarding thestarting time to discuss unshared, but task-irrelevant backgroundinformation (F < 1). These results confirm to a large extent Hypoth-esis 1.

6.2.2. Results on uptake events of unshared information while creatingthe group map

There were more uptake events regarding unshared informa-tion in the experimental condition than in the control condition;that is, the group members of the experimental conditions in-cluded more such nodes, relations, and background informationin the group map, which they themselves did not possess(MC = 3.55.; ME = 6.55; F(1, 38) = 4.32; MSE = 20.84; p < .05;g2

p = .10). This confirms Hypothesis 2.

6.2.3. Results on the individual problem solving tasks based onunshared background information

Compared to the members of the control condition, the mem-bers of the experimental condition were significantly superior insolving the individual, unannounced problem tasks after the col-laboration task: They solved these tasks, which required knowl-edge of the unshared background information that was notneeded in the collaboration phase for solving the pesticide andthe fertilizer problem, more often correctly, including giving thecorrect reasons (MC = 2.90.; ME = 3.97; F(1, 38) = 4.19; MSE = 2.72;p < .05; g2

p = .10). This confirms Hypothesis 3.

6.2.4. Descriptive data from questionnaire itemsThe group members of the experimental condition were asked

to fill out 5-point rating scales assessing aspects of sharing un-shared information (1: no agreement; 5: full agreement). Becauseonly the experimental group members had to answer these items,only descriptive data can be reported.

In order to be able to share unshared information with the col-laborators, one must know which information is unshared: Theexperimental group members stated that the collaborators’ mapshelped them to recognize both differences between their ownmap and the collaborators’ maps (M = 4.17; SD = 0.66) and similar-ities of their own map and the collaborators’ maps (M = 4.31;SD = 0.58). In addition, these group members noted that they con-sciously looked at the maps to identify both their own unsharedelements (M = 3.73; SD = 0.80) as well as the collaborators’ un-shared elements (M = 4.15; SD = 0.65).

If one knows which information is unshared, one must be will-ing to share it: The experimental group members stated that thewindows with the meta-knowledge maps of their collaboratorshad motivated them to contribute such information to the discus-sion, which the others still did not know (M = 3.98; SD = 0.83). Thisresult confirms Hypothesis 4.

6.3. Results on the impact of seeing thecollaborators’ meta-knowledgestructure maps on collaborative problem solving

6.3.1. Results on problem-suitability of group mapsThe group maps of the control condition contained indeed more

correctly drawn nodes (MC = 12.1; ME = 10.7; F(1, 38) = 4.73; MSE =4.15; p < .05; g2

p = .11) and correctly drawn relations (MC = 17.2;ME = 13.9; F(1, 38) = 4.32; MSE = 25.24; p < .05; g2

p = .10). However,

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they included also more background information that was irrele-vant for the collaborative problem-solving tasks (MC = 6.4;ME = 3.0; F(1, 38) = 5.05; MSE = 23.57; p < .05; g2

p = .12). In addition,the group maps of the control condition contain more mistakesregarding both nodes (MC = 1.2; ME = 0.4; F(1,38) = 8.36;MSE = 0.77; p < .01; g2

p = .18) and relations (MC = 4.3; ME = 1.7;F(1, 38) = 9.16; MSE = 7.38; p < .01; g2

p = .19). These last results con-firm Hypothesis 5.

6.3.2. Results on quality of the collaborative problem solutionsIn contrast to our expectations, the analysis of the collaborative

problem-solving tasks showed no significant differences betweenthe conditions regarding the number of correct answers to the pes-ticide problem and with regard to the reasons given as to why theychose the correct pesticide (both Fs < 1). Regarding the number ofcorrect answers to the fertilizer, as well as regarding the reasonsgiven as to why they chose the correct fertilizer, also no significantdifferences could be found (both Fs < 1). These results are in con-trast to Hypothesis 6.

6.3.3. Results of questionnaire dataThe analysis of the questionnaire data did not result in signifi-

cant differences between the conditions (all Fs of the resultingfactors < 1).

7. Discussion and conclusions

The empirical study presented in this paper aimed at answeringtwo research questions, namely (1) whether the sharing of un-shared knowledge can be fostered by having access to maps repre-senting the meta-knowledge structures of the collaborators as wellas the information elements underlying this knowledge and (2)whether having access to the meta-knowledge of the collaboratorsimproves computer-supported collaborative problem-solving per-formance of spatially distributed group members.

With regard to the first research question, the results showed,as expected, that in contrast to the control groups having no accessto the collaborators’ meta-knowledge maps, the groups in theexperimental condition that were provided with their collabora-tors’ maps (1) started earlier to discuss unshared information (inaccordance with Hypothesis 1), (2) had more uptake events regard-ing unshared information (in accordance with Hypothesis 2), and(3) performed better in a problem-solving test that had to besolved individually and by processing unshared background infor-mation (in accordance with Hypothesis 3).

These results gave evidence that having access to the meta-knowledge structures of the collaborators encourages groups notonly to consider and discuss unshared information earlier, but alsoto process unshared information more intensively: As it is demon-strated by the results on the uptake events, the group members ofthe experimental condition used the others’ unshared informationmore often and, as it is shown by the results on the individualproblem solving test, they could apply the others’ unshared infor-mation more effectively, compared to the control condition. As ex-pected in Hypothesis 4, the descriptive results of the questionnairealso confirmed a high willingness of the members in the experi-mental condition to share their unshared information. In addition,the descriptive results corroborated the assumption that the rea-son for the effectiveness of having access to the collaborators’meta-knowledge maps is due to the fact that these maps makethe expertise of the others’ salient and therefore, evoke awarenessregarding the others’ expertise.

The result that visualized information encourages consideringunshared knowledge could also be found in the study by Parksand Cowlin (1996): Groups that were able to ask for access to writ-

ten records of unshared information considered such unsharedinformation more often than groups that did not have the possibil-ity of acquiring the written records. The authors postulated thatunshared information known to only one person becomes moreprominent in the group discussion if it is possible to demonstratethat this information exists.

The results by Parks and Cowlin (1996) highlights the impor-tance of being able to give evidence that one’s own unshared infor-mation is existing and is not imaginary. It can be assumed that thiscould also be an explanation for our finding. However, this has tobe investigated in a further study.

The results of the study presented in this paper are also in linewith results of studies on role allocation that demonstrated thatknowing who is an expert for which topic is helpful for reducingthe communication bias in group discussions in favor of sharedinformation (e.g., Stasser et al., 2000). In contrast to the role alloca-tion approach in which the group members were informed abouttheir collaborators’ expertise by the experimenter verbalizing therole of each group member, the approach presented in this paperrepresented the collaborators’ expertise via external representa-tions of the collaborators’ meta-knowledge structures visualizedby labeled nodes (i.e., the concepts) and unlabeled relations be-tween the nodes.

Just mentioning who is an expert for which topic is undoubt-edly an easy method for increasing the focus on unshared informa-tion in group discussions. However, in real group situations there isno experimenter who may give information about the differentroles of the group members. As outlined, groups often have prob-lems acquiring knowledge about what the others know.

Being able to represent the meta-knowledge structures of groupmembers in real situations requires that the group members them-selves create these representations. On the one hand, this meansadditional activity for the group members is asked for. However,on the other hand, a positive side effect of this activity is that it fos-ters meta-cognitive reflections (cf. Engelmann et al., 2009). In addi-tion, having access to the externalized knowledge of others mayalso foster further important group processes: As shown in thestudies of Engelmann and colleagues, it increases computer-sup-ported collaborative problem solving performance, especiallyregarding complex problems (e.g., Engelmann & Hesse, 2010;Engelmann et al., 2010). In addition, empirical results have demon-strated that having access to the collaborators’ knowledge mapssupports the development of a transactive memory system (Schre-iber & Engelmann, 2010).

With regard to the second research question on the helpfulnessof the meta-knowledge awareness approach to computer-sup-ported collaborative problem solving, the results on group mapspoint to different strategies used in the control condition in com-parison to the experimental condition: The group maps of the con-trol condition contained indeed more correct nodes and correctrelations, but also contained more wrong nodes and relations,compared to the maps of the experimental condition. Additionally,there were more task-irrelevant background information elements,that is, links to information describing corresponding concepts inthe control condition compared to the experimental condition. Tosum up, the group maps of the control condition contained moreinformation, independent of the fact whether it was task-relevantor not. This leads to the assumption that the groups in the controlconditions used their group map mainly for compiling information,while the groups in the experimental condition used their mapmore as a tool for solving the problems and only included task-rel-evant information. These findings confirm Hypothesis 5 that thegroup maps of the experimental condition are more suitable forsolving the group tasks compared to the maps of the control con-dition. This is in line with findings of Engelmann et al. (2010)and Engelmann and Hesse (2010). However, despite the two

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conditions using different strategies regarding their group mapcreation, there were – in contrast to the Hypothesis 6 – no signif-icant differences between the conditions with regard to the resultsof the two collaborative problem solving tasks. This is in oppositionto the findings of prior studies that provided the group memberswith a tool for fostering awareness regarding not only the collabo-rators’ meta-knowledge, but also their concrete task-relevantknowledge (cf. Engelmann & Hesse, 2010; Engelmann et al.,2010). As already explained, in this paper the term ‘‘concrete-taskrelevant knowledge’’ refers to knowledge that is needed to be ableto solve a particular task, while the term ‘‘meta-knowledge’’ refersto rather abstract knowledge, namely, knowledge that is necessary,but not sufficient to solve it. Providing access to the collaborators’meta-knowledge seems not to be enough for fostering computer-supported collaborative problem-solving: Following the results ofthis present study, it is not enough to know which knowledge ispossessed by which collaborator. Instead it seems to be importantto have access to the concrete task-relevant knowledge of thecollaborators.

These results are in contrast to Wegner’s theory of transactivememory systems (1986, 1995), because he postulated that know-ing who knows what in the group, without the need to know theothers’ concrete knowledge, is enough to foster group perfor-mance. But Wegner’s theory also highlights the importance ofcommunication between the group members in order to get accessto the others’ knowledge. Following this statement, a group mem-ber may acquire concrete task-relevant knowledge by asking theparticular collaborator having the required knowledge.

One may assume (1) that having access to both the collabora-tors’ meta-knowledge structures and concrete task-relevantknowledge does not require communication in order to fostergroup performance, while (2) having access only to the collabora-tors’ meta-knowledge structures does require it.

There are two arguments against these assumptions: Regardingthe first assumptions, another study by Engelmann (Engelmannet al., 2010), that compared individual problem solvers having ac-cess to their collaborators’ knowledge maps with groups providedwith their collaborators’ knowledge maps, showed that such indi-vidual problem solvers are not as effective in solving the problemsas such groups. This indicates that communication is also neededfor increasing performance in cases in which the collaborators’concrete task-relevant knowledge is provided.

Regarding the second assumption, in both conditions of thepresent study, the group members could communicate. In theexperimental condition, they also had access to their collaborators’meta-knowledge maps. However, no difference between the condi-tions was found regarding the group performance. Therefore, thereseems to be no added value when the group members had accessto the meta-knowledge structures of their collaborators. This find-ing suggests that having access to the meta-knowledge structuresis not enough to increase group performance.

It should be pointed out that a further difference exists betweenthe present study and previous studies. In prior studies there was ashort, second individual phase in which the group members of theexperimental condition had 5 min for viewing their partners maps,before the collaborative phase started. This phase was included inorder to assure that the group members use the collaborators’maps. However, it is doubtful that the missing second individualphase in the prior study is the reason for the missing effect ongroup performance: On the one hand, Schreiber and Engelmann(2010) conducted a study without this second individual phaseand nevertheless found the expected awareness effect on groupperformance, even though they used more complex material anda different domain and task. On the other hand, the descriptivequestionnaire data of the present study corroborate the assump-tion that the reason for the missing effect results from the absence

of the labeling of the relations between the concepts in the collab-orators’ maps, because the group members of the experimentalcondition indicated that it would have been better to have beenable to see also the labels of the relations and to see the completeconcept maps of their collaborators. This suggests that the missingeffect of the awareness tool on the collaborative problem-solving isdue to the fact that only the collaborators’ meta-knowledge wasprovided, and not like in prior studies both the collaborators’meta-knowledge and the collaborators’ concrete task-relevantknowledge. Due to this finding, as a recommended design for a toolfor fostering knowledge and information awareness, the external-ized knowledge structures should contain meta-knowledge andconcrete task-relevant knowledge of the collaborators.

It should be pointed out that the participants in this study werestudents who had to familiarize themselves with their role in thestudy. It remains to be investigated whether using real experts toanswer the two research questions would result in similar findings.

To sum up, even though the effect sizes of the results in thispresent study ranging from .1 to .24 indicated rather small effects,it can be stated that having access to the collaborators’ meta-knowledge structures fosters sharing of unshared informationand leads to better processing and application of unshared infor-mation. Therefore, this present approach for fostering the sharingof unshared information can be regarded as effective as Stasser’srole allocation approach (e.g. Stasser et al., 2000). In addition, alongthe lines of the knowledge awareness tool of prior studies, it re-sults in a different strategy regarding group map creation. How-ever, in contrast to Wegners’ theory of transactive memorysystem (Wegner, 1986, 1995), the results give evidence that it isnot sufficient to know who knows what in the group, that is, tobe informed about the others’ meta-knowledge to increase groupperformance in computer-supported collaborative problem-solv-ing tasks. Further studies are needed to explain why just knowingthe collaborators’ meta-knowledge is not enough.

Acknowledgments

This research project was supported by the German ResearchFoundation (DFG), by the European Social Fund, and by the Ministryof Science, Research and the Arts Baden-Württemberg (Germany).We especially thank Antonia Baumeister, Kathrin Schag, Sven Bisc-hof, and Solveig Schudeiske for their support in data collection andanalyses as well as the Media Development Group of the Knowl-edge Media Research Center for their technical assistance.

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