The impact of goal focus, task type and group size on synchronous net-based collaborative learning discourses

The impact of goal focus, task type and groupsize on synchronous net-based collaborativelearning discoursesH.-R. Pfister & M. OehlInstitute of Experimental Industrial Psychology – LueneLab, University of Lüneburg, Lüneburg, Germany

Abstract Net-based collaborative learning discourses often suffer from deficiencies such as lack ofcoherence and coordination. It is suggested that the provision of two functionalities, referenc-ing and typing, which learners may optionally use to ground their contributions during a chat-based discourse, can improve collaborative learning. In particular, we examined if goal focus,type of task and group size affect learning outcomes and the use of these functionalities.Achat-based system, called a learning protocol, implements these functionalities and serves as a net-based collaborative learning environment. Results suggest that a learning protocol is morebeneficial for knowledge-acquisition tasks than for problem-solving tasks, and that the useof supporting functionalities increases when goal focus is on the group rather than on theindividual.Also, there is a tendency that learning outcomes improve as group size increases. Wepropose that learning protocols provide potentially valuable design features that can promotenet-based collaborative learning.

Keywords learning protocols, net-based learning, computer-supported collaborative learning, referenc-ing, typing.

The present study examines the question of how partici-pants of a distributed net-based learning group can besupported by a variant of scripted collaboration calleda learning protocol. More specifically, we investigatewhether synchronous learning discourses via text-basedchat-tools can be improved by providing particularfunctionalities such as referencing and typing toenhance the coherence and meaningfulness of theongoing discourse; and we ask under which conditionsthose functionalities are beneficial to improve learningoutcomes.

Alarge body of research has demonstrated the benefi-cial effects of scripted collaboration on collaborative

learning (Slavin 1996; O’Donnell & King 1999). Thisapproach has been extended to net-based learning whengroups of learners collaborate via the Internet (Juckset al. 2003; Bromme et al. 2005; Fischer et al. 2007).

However, in net-based collaborative learning it isunlikely that a productive discourse emerges spontane-ously simply because sophisticated communicationtools are available (Kreijns et al. 2003).Agrowing bodyof research demonstrates that typical deficits of net-based learning discourses are largely a result of prob-lems of discourse coordination, such as incoherenceof contributions and problems of maintaining themati-cally consistent threads of discussion (Herring 1999;Veerman et al. 2000; Lipponen et al. 2003; Soller 2004;Hewitt 2005). Participants are frequently not ableto identify the relationships among individualcontributions. That is, they fail to see the intended refer-ence of a remark, they fail to identify connected

Accepted: 12 May 2008Correspondence: Hans-Rüdiger Pfister, Institute of ExperimentalIndustrial Psychology (LueneLab), University of Lüneburg, Germany,Wilschenbrucher Weg 84, D-21335 Lüneburg, Germany. Email:[email protected]

doi: 10.1111/j.1365-2729.2008.00287.x

Original article

© 2008 The Authors. Journal compilation © 2008 Blackwell Publishing Ltd Journal of Computer Assisted Learning (2009), 25, 161–176 161

mailto:[email protected]

discourse segments, and they fail to join emergingthreads – a phenomenon called co-text loss by Pimentelet al. (2003).

A variant of scripted collaboration, previously intro-duced as the learning protocol approach (Wessner et al.1999; Pfister & Mühlpfordt 2002; Pfister et al. 2003;Pfister 2005), will be described in the next section. Wethen sketch the theory of grounding (Clark 1996) as arationale linking learning protocol support to the objec-tive of improving learning outcomes. Building on previ-ous findings (Pfister & Mühlpfordt 2002; Mühlpfordt &Wessner 2005), the aim of this study is to further explorethe specific conditions under which learning protocolsmight be helpful. The main section reports an experi-mental study testing the usage of referencing and typingin chat-based learning groups under variations of goalfocus, task type and group size, and how they affectlearning outcomes.

The learning protocol approach

Learning protocols are a variant of net-based collabora-tion scripts, using text-based chat as the primary com-munication device. Learning protocols provide twoessential functionalities:

(1) Explicit referencing: When submitting a contribu-tion, the learner can indicate the contribution’s referentby means of a graphical external representation, that is,he or she can establish an explicit reference to a previ-ous contribution, or to a segment of a contribution, or tosome additional instructional material. The segmentreferred to is marked with the mouse, and by a mouseclick, the relationship is established. This relationship isvisualized by an arrow visible for all participants duringthe learning session. A learner can thus reread a discus-sion thread by tracking back the arrows. The referencingfunction has been shown to be able to promote learningoutcomes (Pfister et al. 2003; Mühlpfordt & Wessner2005; Stahl et al. 2006).

(2) Typing of contributions: Each textual contribu-tion, that is, a single chat message, can be classified andlabelled by the contributing participant with respectto its communicative type, for example, as a question,explanation or critique. The learner deliberatelyattaches a label to her or his message, the label precedesthe message on the screen and remains visible for allparticipants. Thus, the primary purpose of one’s contri-bution, indicating its speech act type (Searle 1975), is

expressed unequivocally. Previous studies (Baker &Lund 1997; Soller 2004) have shown that typing canpromote task focus and reflective communication.

Furthermore, a turn-taking rule (one-after-the-other)controls the sequencing of contributions amongparticipants.

Obligatory and optional learning protocols

Dillenbourg & Jermann (2007; Dillenbourg 2002) havestressed the danger of over-scripting, that is, the riskof impairing collaboration by providing too strict andinflexible scripting rules. To avoid over-scripting, wedistinguish between obligatory and optional learningprotocols. With an obligatory learning protocol, the useof the supporting functionalities is mandatory, that is,learners are enforced by the system to type and to refer-ence each single contribution. Optional learning proto-cols, in contrast, provide these functionalities via amenu, but learners are free to make use of them when-ever they feel that it might be helpful. Hence, followingStahl (2007), optional learning protocols constitute situ-ated resources rather than strictly enforced rules forcollaboration.

In the present study, we investigated optional learn-ing protocols. Two questions were addressed: first, weask if and under what conditions learning with optionallearning protocols improves learning outcomes.Second, we investigate if the use of referencing andtyping actually is associated with improved learningoutcomes.

Related approaches

Related approaches have been proposed by, amongothers, Baker & Lund (1997; de Vries et al. 2002), byHron et al. (2000), by Rummel and Spada (2005), bySoller (2004), and by Weinberger et al. (2005; seealso Beers et al. 2005; Kollar et al. 2006). All theseapproaches are based on the assumption that improvingthe coordination of communication will lead toenhanced knowledge acquisition.

According to Dillenbourg and Jermann (2007), learn-ing protocols can be analysed with respect to the degreeof coercion as ‘follow-me scripts’when they are obliga-tory, or as ‘prompted scripts’ when they are optional;referencing and typing are then considered as affor-dances as opposed to enforced activities. Second, with

162 H.-R. Pfister & M. Oehl

© 2008 The Authors. Journal compilation © 2008 Blackwell Publishing Ltd

respect to granularity, learning protocols usuallyconcern the micro-level of scripting, scaffolding thebasic communicative units of a discourse while thestructuring of the macro-level is left to the learners(Dillenbourg & Jermann 2007).

Grounding with learning protocols

The theory of grounding in communication, as intro-duced by Clark & Brennan (1991; Clark 1996), hasprovided an important framework to understandcomputer-mediated communication in general and net-based collaborative learning in particular (Brennan1998; Baker et al. 1999; Pfister 2005; Dillenbourg &Traum 2006). Learning in groups can be conceived of asa collaborative process of constructing common ground,that is, a mutual understanding of the subject matterunder discussion (Beers et al. 2005, 2007).

According to Clark (1996), messages need to begrounded by feedback signals from the recipients ofmessages in order to establish a shared understanding.Positive feedback that a message has been understoodproved to be particularly important. If a contributionhas been sufficiently grounded, it becomes part of theshared knowledge of the group. The social activity ofovercoming a grounding problem, for example, bysupplying an extra explanation, can trigger cognitiveactivities that lead to improved understanding(Dillenbourg & Traum 2006; Dillenbourg & Jermann2007).

We suggest that referencing and typing of contribu-tions as implemented in learning protocols can serve asindicators of grounding efforts. First, assigning a refer-ence from the current contribution to a previous contri-bution conveys an instantly recognizable feedbacksignal. Even if the previous contribution has not beenperfectly understood, referencing can initiate a processof clarification among the participants in order to reacha common understanding (Brennan 1998).According toStahl (2006), referencing is at the core of creating whathe calls the ‘discourse fabric’, that is, the sharedmeaning of a narrative text.

Second, assigning a type to a contribution, forexample, declaring it explicitly as an explanation or as acritique, also serves as feedback to a previous message.Especially, typing can increase the occurrence of adja-cency pairs, such as question-answer, claim-critiqueor assumption-justification pairs. Adjacency pairs are

viewed as a basic mechanism of discourse coordination(Cahn & Brennan 1999; Stahl 2006).

In sum, we argue that explicit referencing and typingboth instigate cognitive processes that can help toground a discourse segment.

According to Clark’s (1996) principle of least effort,speakers try to minimize the effort they expend forgrounding. Hence, learners will not expend that effortroutinely, but will make use of optional referencing andtyping functionalities only as much as they feel that itis necessary to ground their current contribution. Weassume that the amount of effort participants are willingto expend will depend on contextual characteristics ofthe learning situation. Three kinds of contextual factorsare assumed to be of particular relevance: goal focus,task type and group size. We consider each in turn.

Contextual factors

Goal focus

Goal focus as used in this study refers to the distinctionbetween individual- and group-oriented performance.Group performance is frequently affected by the degreeof positive interdependence among its members. Onetype of positive interdependence that turned out to becrucial for the performance of collaborating groups isgoal interdependence (Johnson et al. 1989; Ortiz et al.1996). Johnson et al. (1989) define positive goal inter-dependence as a situation when a participant canachieve his or her goal if and only if all other membersof the group also achieve their goals. In collaborativelearning discourses, each individual’s goal is to achievea satisfying learning outcome; the goal focus normallyis on the individual learner. If, however, participants areawarded according to the average learning performanceof the entire group, the goal focus is on the group, andgoal interdependence is established.

In the present study we distinguish, accordingly,between two kinds of goal focus. If the relevant goal isfor each individual participant to perform as well as pos-sible, goal interdependence will be negative, constitut-ing an individual goal focus. If, in contrast, the relevantgoal is that the group as a whole performs as well as pos-sible, goal interdependence will be positive, constitut-ing a group goal focus. With a group goal focus, eachparticipant is accountable not only for her or his indi-vidual success, but also for the performance of the otherparticipants a well.

Impact of goal focus, task type and group size 163


A focus on the group is assumed to motivate learnersto make increased use of the referencing and typingfunctionalities in order to establish a higher degree ofshared knowledge. On the other hand, with an individualgoal focus, the individual learner is rewarded if he or sheoutperforms the other members of the group; it mightthen even be detrimental if an individual participanthelps others to understand the common subject matter.

Task type

Task type as used in this study refers to the distinctionbetween learning by acquisition of factual knowledgeand learning via problem solving. Problem-based learn-ing is centred on the principle that having to solve a con-crete problem leads to more reflective thinking and todeeper understanding than simply reading a presenta-tion or an explanation of the relevant concepts and facts(Dochy et al. 2003).

In the present study, task type is manipulated viainstruction: if the instruction explicitly asks to acquireknowledge about a domain, the focus of attention isdirected towards information acquisition. If, in contrast,the instruction asks to solve a problem derived from thedomain, the focus of attention is directed towards infor-mation application.

We assume that referencing and typing functional-ities are especially appropriate to support a problem-based scenario, because learning discourses promoteinteractive processes of negotiating promising solutions(Johnson et al. 1989; Pfister et al. 1999). Specifically,we expect that, under a problem solving instruction,participants are more inclined to employ optionalgrounding functionalities, compared to participantsunder a knowledge-acquisition instruction.

In practice, goal focus and task type will most likelyinteract. Even if the task is to acquire knowledge, a focuson the group will increase the need for collaboration.And, conversely, even if the task is to solve a problem, anindividual focus will reduce collaboration and ground-ing. Hence, the condition in which most grounding andlearning should occur is when learners solve a problemand receive a group reward.

Group size

As is well known, group size influences group perfor-mance and group behaviour (Yetton & Bottger 1983).However, collaborative learning in net-based environ-

ments has mostly been studied only for dyads (Kollaret al. 2006). Severe coordination and communicationproblems in discourses will potentially arise with morethan two participants (Clark & Brennan 1991). Forexample, the coordination of turn taking or the identifi-cation of the current speaker are minor issues when onlytwo participants are involved, but considerably moredifficult for more than two speakers. More generally,awareness problems will increase with an increasingnumber of participants (Carroll et al. 2003). Mostimportant, it becomes especially effortful to relateincoming contributions to previous threads of thediscussion. Preliminary findings indicate that group sizeis a determinant of learning outcomes in net-basedlearning groups (Pfister & Mühlpfordt 2002). In sum,we assume that participants will invest more groundingeffort when group size increases.

Hypotheses

The objectives of the present study are threefold: First,we want to identify contextual conditions under whichoptional learning protocols are conducive for net-basedlearning discourses. Second, we want to investigate ifthe use of grounding activities is related to contextualfactors. Third, we want to test if learning performance isrelated to the amount of grounding effort expendedduring learning. Thus, contextual factors serve as inde-pendent variables, and grounding effort as well as learn-ing outcome serve as dependent variables.

We derive the following hypotheses:

1 An optional learning protocol is assumed to be morebeneficial if the goal focus is on the group (groupfocus) as opposed to on the individual learner (indi-vidual focus) (Hypothesis 1a). Furthermore, learningoutcomes are expected to be better if learners areinvolved in a problem-solving task compared to aknowledge-acquisition task (Hypothesis 1b). Withrespect to group size, learning protocols are expectedto be more useful if group size increases (Hypothe-sis 1c).

2 It is hypothesized that more grounding activities asindicated by referencing and typing are instigatedif the goal focus is on the group in contrast to anindividual focus (Hypothesis 2a). Also, it is expectedthat more grounding effort will be expended whenlearners solve a problem in contrast to a knowledge



acquisition task (Hypothesis 2b). Additionally, weexpect that more grounding effort will be observed inlarger groups (Hypothesis 2c).

3 Learning outcomes are hypothesized to be positivelycorrelated with the amount of grounding effort (refer-encing and typing) expended by learners during thelearning discourse (Hypothesis 3).

Method

Participants

One hundred and forty students from different studyprogrammes (psychology, social sciences and eco-nomic sciences) volunteered as participants and wererandomly assigned to 40 learning groups, consisting ofthree or four members. Participants were paid 15 Eurosfor participation, plus an additional bonus dependingon the experimental condition. As a result of technical(software failure) and organizational (exclusion of non-native speakers) dropouts, a sample of N = 118 partici-pants (age: M = 25.03 years, sd = 4.07; gender: 70.10%female; years of study: M = 2.55 years, sd = 1.66) wasincluded for further analyses.

Materials and procedure

The learning protocol environmentThe experimental environment was based upon theConcertSuite software, a platform for collaborativelearning of distributed groups developed by the Fraun-hofer Institute IPSI.1 The user interface was identical forall participants (Fig 1).

Referencing and typing functionalitiesWhen it was a learner’s turn to make a contribution, heor she had the option to mark the segment to which thecurrent contribution referred with the left mouse button.This referenced segment was then automatically con-nected with the learner’s current contribution, visual-ized by a black arrow originating at the currentcontribution and pointing to the selected segment.Addi-tionally, participants were free to define the type of theircontribution before sending it. Typing was possible ontwo levels. Participants could choose from five first-level types and, optionally, from several additionalsecond-level subtypes: Question (with subtypes ‘. . .about definition’, ‘. . . about function’ or ‘. . . about

reason’), Explanation (with subtypes ‘. . . of a concept’,‘. . . of a function’, ‘. . . of a system’or ‘. . . of a reason’),Conjecture (with subtypes ‘. . . about an assumption’ or‘. . . about a prediction’), Comment (with subtypes ‘. . .as a justification’or ‘. . . as a commentary’) and Critique(with subtypes ‘. . . as a complement’, ‘. . . as a correc-tion’ or ‘. . . as an alternative’). According to theselected type and level (main type with or withoutsubtype), a specific textual label such as ‘EXPLANA-TION – of a concept:’ was inserted at the beginning ofthe learner’s message; the label was for all participantsvisible on the screen.

The learning domainThe learning domain was the catastrophe at the nuclearpower plant at Chernobyl in 1986. An initial introduc-tory text was compiled, including general informationabout the plant and the disaster, facts about the workingsof the power plant, as well as special information aboutthe events leading to the disaster. Any further informa-tion was to be contributed by the learners themselves,relying on their prior knowledge, or was to be con-structed in a self-directed manner during the discourse.The initial text was visible on the screen during theentire learning session.

Independent variablesTask type was manipulated via instruction. The learningtask was explained as either to learn as much about thedisaster as possible (knowledge acquisition condition),or to try to solve a problem (problem solving condition).The concrete problem to solve was to arrange a pre-defined set of 13 critical events into the correct causalorder that ultimately led to the disaster (e.g. ‘Powerdrops to 1%’, . . . ‘All pumps of the primary circuitare activated’, . . . ‘The emergency cooling system isactivated’). The critical events were listed in the mate-rial pane of the interface (lower left pane in Fig 1) andnumbered by lower-case letters, so that participantscould refer to them. No special tool was provided toarrange or represent these events.

Goal focus was also manipulated via instruction. Par-ticipants were either informed that they could earn anadditional amount of five Euros if they achieved the bestindividual test score within the group (individual goalfocus condition), or that they would receive an addi-tional amount of 5 Euros if all members of the groupachieved at least a 75% score on the post-test (group



goal focus condition). Note that this manipulationtries to change goal interdependence via rewardinterdependence. An individual reward should establishcompetition in so far as participants are motivated tomaximize their own monetary rewards. A group rewardshould establish group interdependence in so far asparticipants are motivated to support and help othermembers in maximizing their monetary reward. A dif-ferent way to establish goal interdependence wouldhave been via task specialization, but Slavin (1996)points out that without group reward team specializa-tion is usually not effective in improving achievement.

Group size was varied by randomly assembling three(triad) or four (quartet) participants into one learninggroup.

ProcedureThe learners worked in groups of three or four partici-pants, depending on group size condition, at standardPCs in isolated cubicles in a computer laboratory, simu-lating a distributed scenario; communication was onlypossible via the PC-network. First, a questionnaireabout participants’ experience with computers,e-learning, chat and the Web was administered, fol-lowed by a pre-test about subjects’ knowledge concern-ing the Chernobyl disaster. Participants were thenintroduced to the purpose, rules and handling of thelearning protocol in a detailed tutorial session. Then, theexperimental session started and the participants wereinstructed depending on the experimental task type andgoal focus condition. Then, the learning discourse

Fig 1 Screenshot of the user interface of the learning protocol environment (German version). Top pane shows the instruction of how touse referencing and typing in form of a decision tree. The lower left pane shows the introductory text about the learning domain, over-layed with a pop-up menu of available typing categories. The lower right pane depicts the chat window with contributions in sequentialorder, and an input field for one’s own contribution. A referencing line goes from the current contribution pane to the word ‘Graphit-bremsstäbe’ in the text pane.



started, with one session taking 40 min. Immediatelyafter the learning session, tests to assess learning out-comes were administered.

Measurements and design

A knowledge pre-test was administered to control forpossible a priori differences, consisting of one openquestion which asked participants to produce a shortdescription of what they know about the Chernobyldisaster. Each participant’s answer was rated by tworaters on a six-point scale from ‘knows nothing’ to‘knows a lot’. Learning outcome was measured afterthe learning session in two ways: (1) with a knowledgetest for factual knowledge, consisting of 15 four-optionmultiple choice items, tapping a representative sampleof concepts and events from the domain; and (2) witha problem-solving test, where participants were toarrange a set of 13 critical events that lead to the disas-ter in the correct temporal sequence. The multiple-choice test yielded scores from 0 to 15. For theproblem-solving test, the rank correlation between aparticipant’s generated event sequence and the correctcausal sequence of the 13 events was computed andused as test score. The average number of contributionsper participant and session that involved either a refer-encing and/or a typing activity was computed as anindicator of grounding effort.

A 2 ¥ 2 ¥ 2 three-factorial design was applied withtwo levels for each factor: goal focus (group versus indi-vidual focus), task type (knowledge acquisition versusproblem solving) and group size (three versus fourlearners). All factors were treated as between subjectsfactors, yielding eight independent experimentalconditions. As a result of experimental dropouts, thedesign was slightly unbalanced. The total of 118 partici-pants was distributed across 33 groups, yielding 14triads and 19 quartets, 15 individual-focus and 18group-focus groups, and 17 knowledge-acquisition and16 problem-solving groups.

Results

No differences between conditions were found concern-ing previous experiences with computers, nor concern-ing prior knowledge about the Chernobyl disaster.

Generally, the referencing and typing functionalitieswere used quite frequently in all conditions: 73% of all

messages involved at least one grounding activity, 58%involved both referencing and typing, 10% relied onlyon referencing and 5% only on typing. These high fre-quencies should not be taken for granted, because par-ticipants were not enforced or encouraged in any way touse these functionalities, although they might have feltinvited to use them as a result of mere availability. Thisconfirms, however, that an optional learning protocol isa viable way to provide supporting discourse function-ality as a learning resource that is accepted and usedfrequently and voluntarily.

Because of the hierarchical structure of the data, weemployed a multi-level approach in the following analy-ses (Hox 2002; De Wever et al. 2007), thus controllingfor the dependencies of learners within groups. Weapplied a simple random intercept model; becauseexplanatory variables are associated only with the grouplevel, a random slope model would be pointless (Hox2002). Although the small number of learners per group(three or four) and the number of groups (33) limit theaccuracy of parameter estimates, the data permit to testthe fixed effects of interest with sufficient precision(Maas & Hox 2004). Note that the small number of indi-viduals within a learning group constitutes a definingcharacteristic of the domain of small group research.

First, we report results concerning learning outcomesas a function of experimental conditions (Hypothesis 1).Then, findings concerning grounding effort are reported(Hypothesis 2). Finally, we report results on the rela-tion between grounding effort and learning outcome(Hypothesis 3).

Learning outcome as a function of goal focus, tasktype and group size

To assess learning outcome, the 15-item multiple-choice knowledge test and the one-item measure ofproblem-solving achievement were used. Cronbach’sa of the multiple-choice test is rather low (0.451);however, heterogeneity is intended in order to incorpo-rate the diversity of relevant concepts. We regard themultiple-choice test as comprising a representativesample of items from the population of knowledgeitems concerning the Chernobyl domain. Mean itemdifficulty (P = 0.64) is adequate, and the variation of theoverall score is fairly large (M = 9.63, sd = 2.16,min = 4, max = 14). For the following statistical analy-ses, both outcome scores were normalized to a range



from zero to 100, and a combined overall learningoutcome score was computed as their unweighted sum.This overall score does not significantly deviate from anormal distribution according to a Shapiro-Wilk test(P = 0.128).

First, we tested if learning outcome as measured bythe overall score is affected by manipulations of goalfocus, task type and group size. The intra-class correla-tion ICC1 of 0.487 (Table 1) indicates substantial varia-tion across learning groups. Group reliability asindicated by an ICC2 index of 0.769 indicates thatlearning groups are fairly homogeneous. A full multi-level model with task type, goal focus, and group size aslevel-two explanatory variables, including a randomintercept term, yields a significantly improved fit com-pared to the Null model according to a log-likelihoodratio test (P < 0.001). The reduction of intercept vari-ance from 489.43 to 343.48, thus accounting for 29.8%of the variation in the random intercept, is substantial(Table 1).

We find a significant fixed effect of task type (P =0.009),2 indicating that the overall learning outcome isgreater when the task is to acquire knowledge (M =131.80, sd = 26.70) than when the task is to solve aproblem (M = 107.00, sd = 30.50), contrary to thehypothesized direction (Hypothesis 1b). The interactionbetween task type and group size turns out to be margin-ally significant (P = 0.073), suggesting that the differ-ence between task types is more pronounced for groups

with three members (Fig 2). This pattern lends supportto Hypothesis 1c that larger groups benefit morefrom a learning protocol. The most pronouncedimprovement in learning outcome is observed whenproblem-solving groups increase in size from three tofour members.

Group size fails to reach significance (P = 0.12), eventhough groups with four members perform slightly

Triad Quartet

Group Size

Ove

rall

Lear

ning

Sco

re

0

20

40

60

80

100

120

140Knowledge AcquisitionProblem Solving

Fig 2 Mean overall learning score as a function of group size andtask type. Error bars indicate 95% confidence intervals.

Table 1. Model estimates for the multi-level analysis with overall learning outcome as dependent variable.

Parameter Null model Full model

Estimate Estimate (SE) P-value (via MCMCestimation)

Fixed effects1

Intercept 119.46 140.61 (10.15) <0.001**Task type -44.27 (16.58) 0.009**Task type ¥ Group size 42.53 (23.46) 0.073

Random effectsIntercept s2

u0 489.43 343.48Residual s2

e 515.29 515.61ICC1 0.487ICC2 0.769

Model fitD: log Likelihood-Ratio 64.09 <0.001**Proportional reduction in intercept variance 0.298

1Only fixed effects with P < 0.10 are tabulated.**, P < 0.1.



better (M = 120.60, sd = 26.88) than do groups withthree members (M = 117.80, sd = 37.88), as wasexpected.

The manipulation of goal focus turns out to have noeffect on learning outcomes at all, contrary to Hypoth-esis 1a.

In sum, it turns out that with an optional learning pro-tocol, substantially improved learning outcomes areobserved when the task is to acquire knowledge insteadof solving a problem, and that groups of larger size tendto benefit slightly more when the task is to solve aproblem. Including the amount of referencing andtyping as covariates yields virtually identical results.This suggests that the effects of task type and group sizedo not necessarily depend on a particular learningprotocol.

Grounding effort as a function of goal focus, task typeand group size

A grounding activity has been defined as the deliberateutilization of either referencing, typing, or the simulta-neous use of both functionalities with respect to one’scurrent contribution. Two numerical indicators ofgrounding effort were computed: First, a value of 1 wasassigned to each single contribution if the learner usedthe referencing function, otherwise, a value of 0; thisconstituted the referencing indicator.Asecond indicator

was computed by assigning a value of 1 to a contributionif it was typed on level 1 (main type), a value of 2 if itwas also typed on level 2 (including a sub-type), and avalue of zero otherwise; this constituted the typingindicator. A joint index for each participant representinghis or her average grounding effort was then created: foreach participant the reference indicator and the typingindicator were each averaged across all contributions ofthis participant. Then, a weighted sum of the referenceindicator and the typing indicator was computed with aweight of 0.5 for the typing indicator in order to com-pensate for its larger range (from 0 to 2). This joint indexserved as a proxy for the average grounding effortexpended by a participant per learning session.

A multi-level random intercept model was appliedwith grounding effort as the dependent variable, learn-ing group as a random effect, and task type, goal focusand group size as fixed-effect explanatory variables(Table 2). The intra-class correlation coefficient ICC1of 0.336 indicates that one-third of the variance is to beattributed to the group level (s2

u0 = 0.09; s2e = 0.178);

also, group homogeneity is fairly large (ICC2 = 0.641).A multi-level model including the full set of explana-

tory variables increases model fit significantly (P =0.048), and reduces intercept variation by 26.7%. A sig-nificant fixed effect was obtained for goal focus (P =0.038), indicating greater grounding effort under agroup focus compared to an individual focus. Marginal

Table 2. Model estimates for the multi-level analysis with grounding effort as dependent variable.

Parameter Null model Full model

Estimate Estimate (SE) P-value (via MCMCestimation)

Fixed effects1

Intercept 1.218 0.955 <0.001Goal focus 0.464 (0.221) 0.038*Group size 0.397 (0.216) 0.068Goal focus ¥ Group size -0.469 (0.250) 0.063

Random effectsIntercept s2

u0 0.090 0.066Residual s2

e 0.178 0.178ICC1 0.336ICC2 0.641

Model fitD: log Likelihood-Ratio 12.70 0.048*Proportional reduction in intercept variance 0.267

1Only fixed effects with P < 0.10 are tabulated.*, P < 0.1.



effects were found for group size (P = 0.068), indicat-ing greater grounding effort in groups with four partici-pants, as well as for the interaction of group size withgoal focus (P = 0.063). Fig 3 reveals that the increase ingrounding effort is especially pronounced under anindividual goal focus when groups increase from threeto four participants.

In sum, grounding effort is significantly greater whenthe goal focus is on the group (M = 1.28, sd = 0.50)compared to on the individual (M = 1.17, sd = 0.53),thus confirming Hypothesis 2a. Grounding effort tendsto be slightly greater in groups with four participants(M = 1.34, sd = 0.47) than in groups with three partici-pants (M = 1.03, sd = 0.53), providing some support forHypothesis 2c. However, contrary to expectation,grounding effort is not affected by task type.

Relations between grounding effort andlearning performance

We assume that increased grounding effort leads tobetter performance. As a straightforward test, we corre-lated the grounding effort variable with the threelearning outcome measures (knowledge test, problemsolving and combined overall score). We find a signifi-cant correlation of r = 0.28 (t(116) = 3.142, P = 0.002)

only between grounding effort and knowledge testscore: Participants who showed more grounding effortachieved higher scores on the knowledge test.

A multi-level analysis with knowledge test score asthe dependent variable (ICC = 0.438), learning group asa random effect, and amount of referencing and amountof typing as two explanatory variables, reveals that it isonly the amount of referencing (P = 0.023) which sig-nificantly increases learning outcome. Using specifictypes such as explanation or comment as predictorsdoes not yield significant relationships with learning.Thus, Hypothesis 3 could only partially be confirmed,although the general relationship is as expected: moregrounding effort promotes better learning outcomes.

As a more focused test, we carried out a series ofmediation analyses to test for a mediating role ofgrounding effort. Taking group focus, task type andgroup size, respectively, as the independent variable,test score as the dependent variable, and groundingeffort as the intervening mediator variable, it turned outthat grounding effort significantly mediates the effect ofgroup size on learning outcome (indirect effect = 0.468,Sobel’s z = 2.018, P = 0.022). We conclude that largergroups learn better if they expend more effort ongrounding, that is, on referencing and typing.

The content of referencing and typing

A closer look at the grounding components reveals thatthe typing categories are used with different frequenciesacross conditions. Across all contributions, conjecturesare applied most frequently (20.4%), followed by ques-tions (16.4%), comments (10.2%), explanations (9.8%)and critiques (6.4%); 36.8% of all contributions arenot typed. A test on independence shows that types areused differently depending on experimental conditions(c2(15) = 64.3, P < 0.001): In particular, questions areused much more frequently in the knowledge acquisi-tion conditions, and comments as well as explanationsare used more frequently in the group focus conditions.Overall, typing occurs more often under a goal focus onthe group than under an individual focus.

Also, referencing and typing mostly go together.26.8% of all contributions are neither typed nor refer-enced, but 58% are typed as well as referenced. Refer-ences can either point to other previous contributions,or to the introductory material made available on thescreen. Contribution references are significantly more

Triad Quartet

Group Size

Gro

undi

ng E

ffort

0.0

0.5

1.0

1.5Individual FocusGroup Focus

Fig 3 Mean grounding effort as a function of group size and goalfocus. Error bars indicate 95% confidence intervals.



often used under the group focus conditions, whereasmaterial references are evenly distributed betweengroup and individual focus conditions (c2(6) = 33.3,P < 0.001).

These findings suggest that task type and goal focusnot only influence overall grounding effort, but alsodetermine which particular types are selected and whichparticular kind of referencing is used. A full-fledgedcontent analysis is beyond the scope of this paper, butwe present two examples to provide some anecdotalevidence on the differences between high- and low-grounding discourses. Discourse Fragment A (Table 3)lists a discourse sequence from the learning group withthe highest grounding index, which is contrasted with adiscourse sequence from the group which showed aminimum amount of grounding activity (Discourse

Fragment B). Both fragments illustrate a phase duringwhich learners struggle to get the sequence of criticalevents in the proper order (events are symbolized bylower-case letters). In Fragment A, all contributions arereferenced as well as typed, whereas in Fragment Bneither referencing nor typing occurs.

Fragment A reveals that most references refer to theprevious contribution. Making this explicit might insti-gate the use of anaphoric references (‘That’s right’,learner 2; ‘That’s correct’, learner 3). It can also be seenthat the actual content largely corresponds to thedeclared type, for example, a critique as alternativestarts with an alternative proposal on how to deal withthe events (‘Shouldn’t we first . . .’, learner 3). Twocomplement types then actually extend the proposedsequence in a step-wise manner. Fragment B contains

Table 3. Examples of discourse fragments from a group with high degree of grounding (Fragment A) and a group with low degree ofgrounding (Fragment B).

Discourse Fragment A (degree of grounding: 1.92). Condition: problem solving, group focus, group size = 4:

Learner 2:REFERENCE→material‘EXPLANATION OF PURPOSE: That’s right, the points are not in the text I think we have to include them somehow. In my

opinion first point (g) (j) (a) then (l) turning off safety measures. I’m not sure when (f) comes in play’Learner 3:

REFERENCE→previous contribution‘CRITIQUE AS ALTERNATIVE: Shouldn’t we first bring all points in the text in some sequence and then try to make an

ordering. but well I think that after g comes e j and maybe d. That is correct, the points are not in the text.’Learner 4:

REFERENCE→previous contribution,→Material‘CRITIQUE AS COMPLEMENT: I would also say it makes sense to first get the points from the text in the right order. I think

the order is g, a, j, d, b, and then maybe m.’Learner 1:

REFERENCE→previous contribution‘CRITIQUE AS COMPLEMENT: sequence g-j-a-d-i-b-h-m; l must be somewhere at the beginning, if russians consider the

safety of humankind is a question’

Discourse Fragment B (degree of grounding: 0.27). Condition: problem solving, individual focus, group size = 3:

Learner 2:‘we shouldn’t think so long and write nothing. who say after 20 s knows nothing should click and hand over to the next

one. what about if we try to go from top to bottom I think f comes later, -g -i -j?’Learner 1:

‘yep faster – g j i I think , a – d – i I can’t figure out h’Learner 3:

‘I’m not sure about i, could be. Then b. I think everybody should make just one step, otherwise it becomes confusing. Icannot so fast, ok?’

Learner 2:‘after b e?’

Learner 3:‘again one after the other g-j-a-d-i-b, now k I would say, but we have to built in h – between a and d?’



more meta-utterances (‘we shouldn’t think so long . . .’,learner 2; ‘again one after the other . . .’, learner 3) abouthow to organize the discourse. Also, participants tend torepeat the evolving sequence of events before they makea complementing proposal, which might serve as a kindof implicit reference.

These examples give a hint on possible differencesbetween high- and low-grounding effort. In fact,learners who do not make use of the explicit functional-ities might still invest as much effort, for example, byhaving to repeat much of what has been contributedbefore, or by meta-comments that coordinate thediscourse. Although the overall structure seems not tobe very different, there is a certain elegance when refer-encing and typing is used. For the creator of a contribu-tion, the effort might be as great with as without explicitgrounding. For the addressees, however, the effort todecode might be lower because of the explicit represen-tation of references and types.

Discussion

We studied if and when learners use discourse support-ing functions such as referencing and typing during achat-based collaborative learning session. It was sug-gested that if learners put more effort into groundingthis would lead to improved learning outcomes.Alearn-ing environment which makes referencing and typingfunctionalities available for optional use, called anoptional learning protocol, was implemented and runwith 33 groups of learners. Three context factors, whichwe hypothesized to systematically influence groundingand learning, were examined: goal focus, task type andgroup size.

In sum, it turned out that with respect to learning out-comes optional learning protocols are more conduciveto support collaborative learning framed as a knowledge

acquisition task than a task framed as problem solving.Goal focus showed no effect on learning outcome. Fur-thermore, we found a significant propensity of partici-pants to apply more referencing and typing under agroup focus compared to an individual focus. Task type,in contrast, did not influence referencing and typingactivities. Generally, there was a slight tendency thatlearning protocols are more beneficial, in terms of learn-ing outcome as well as in terms of grounding, for largergroups of four participants than for groups of three par-ticipants; it seems justified to assume that with largergroups, say of five or six participants, this effect mightbe more pronounced.

Finally, it could be shown that participants whouse the referencing function more frequently are morelikely to perform better in a final multiple choice knowl-edge test. In particular, it turned out that referencingplays a mediating role: when group size increases, par-ticipants are more likely to use the referencing function,and thereby to improve their learning outcomes.

Previous research indicates that providing explana-tions might be particularly beneficial to foster under-standing (Chi et al. 1989; Webb 1989). However, nosignificant relationship was found between learningoutcome and the number of generated explanations; norwas there a relationship of any other typing categorywith learning outcome. We think that what the overallgrounding index captures is a learner’s willingness toexpend more effort to construct an intelligible contribu-tion; hence, under the group focus condition, learnersmight view it more worthwhile to expend the effort touse some functionality, no matter which one, to clarifytheir intended contribution.

Figure 4 provides an overview of the conceptualstructure of the study and the pattern of results.

We proposed that learning protocols would be moreconducive for problem solving than for knowledge

Fig 4 Conceptual structure of groundingeffort and learning performance, andmajor causal links of the contextual factorsunder study.



acquisition tasks, but just the converse turned out to bethe case. In their meta-analysis Dochy et al. (2003)found a positive effect of problem-based learning onskill acquisition, but a small negative effect on knowl-edge acquisition. In the present study, primarily, knowl-edge gain was measured, and skill acquisition wasneither aimed at nor assessed.

Furthermore, one of the shortcomings of our studyis its brief duration, that is, a single learning sessionof only 45 min. The findings of Dochy et al. (2003)indicate that retention period is a significant moderatorin problem-based learning: following problem-basedlearning, after a longer retention interval studentsremember more of what they learned in contrast tostudents learning in a more conventional setting.It is quite conceivable that learning by means ofproblem solving takes more time initially, but becauseof deeper processing, leads to better recollection in thelong run.

Afocus on the group increased the implementation ofgrounding mechanisms, but did not improve learningoutcomes. Again, a possible explanation is the timescale investigated. Ortiz et al. (1996) comparedachievement of groups with high positive goal interde-pendence and groups with no interdependence over a5-week period. Interestingly, after 1 week achievementscores of groups with no interdependence were higherthan the scores of high interdependence groups. After 5weeks, however, high-interdependence groups signifi-cantly outperformed no-interdependence groups. Aswith problem solving, one might speculate that theeffect of a focus on group performance might revealitself only after a longer time interval, though themechanisms of this process are not obvious (see alsoDillenbourg & Traum 2006).

We found that participants actually make use ofoptional grounding functionalities to a large extent. Thismight partly be because of demand characteristics of theexperimental session, and might be less pronounced inmore natural settings. We also found that groundingeffort is correlated with a modest gain in learning (Stahlet al. 2006). Note, however, that grounding as defined inthis study is entirely formal and does not take thecontent of a message into account. A detailed contentanalysis of each single contribution might possiblyhighlight different aspects of collaborative learning andgrounding (Beers et al. 2007), but is beyond the scopeof this study.

Stahl (2006) also emphasizes the importance of refer-ences as conversational devices that constitute groupcognition by connecting individual messages. Stahl’sdistinction between elliptical, indexical and projectivereferences, inferred from a detailed chat-log analysis,might be helpful to further clarify the significance ofreferencing on the group level. Likewise, Dillenbourgand Traum (2006) analyzed 18 pairs of participants of aMOO problem-solving task with respect to the ratio ofacknowledged messages, which they take as an indica-tor of grounding. They found no relationship withproblem-solving success, but a weak relationship withthe efficiency of the discourse. Dyads with a highacknowledgement ratio showed less redundancy in theirdialogues, hence higher efficiency.

Our results suggest that with an optional learningprotocol and sufficient instruction, learners are quitewilling to make use of the available functionality. Onemight conjecture that in the long run learners will adaptto the special conditions, constraints and possibilities ofa learning protocol; or, more generally, to any kind ofnet-based learning environment, and employ the avail-able functions in a natural way. Newlands et al. (2003)showed that learners adapt quickly to the constraintsof text-based computer-mediated communication, andmodify their communication behaviour accordingly.The notion of ‘fading’ suggests that it might even be anobjective and a design feature of scripted collaborationto support a smooth transition from the external to aninternal script (Carmien et al. 2007).

Instead of providing learning environments withfixed collaboration scripts, it might turn out to be morebeneficial to make flexible environments available,which are equipped with a set of functionalities fromwhich learners can select what seems helpful,and which learners or tutors might even employ in cre-ative ways not anticipated by the designer (Dillenbourg& Tchounikine 2007; Haake & Pfister 2007). This viewcorresponds to the probabilistic view of design or the‘designing for interaction’ approach as advanced byStrijbos et al. (2004). They showed that providingcritical prerequisites for interaction and participationincreases the likelihood of knowledge acquisitionthrough collaborative learning. The provision ofoptional learning protocols, we suggest, is one designfeature, among others, that might increase the useful-ness of chat-based learning environments for collabora-tive net-based learning.



Acknowledgements

This research was supported by the German ResearchCouncil (Deutsche Forschungsgemeinschaft DFG)under research grant PF330/1-2 to Hans-Rüdiger Pfisteras part of the special priority programme ‘Net-basedKnowledge Communication in Groups’(SPP 1081). Wewould like to thank Nicole Brandenburg and WernerMüller for their help in conducting the experiment. Wealso greatly appreciate the valuable comments of twoanonymous reviewers.

Notes

1See http://www.ipsi.fraunhofer.de/concert and http://sourceforge.net/projects/

concertchat/ for further developments. All other materials can be obtained from

the first author on request.2Statistical tests of parameter estimates are based on Markov Chain Monte Carlo

(MCMC) simulation, which is recommended to obtain robust estimates espe-

cially for small samples (Hox 2002). Computations were carried out with the R

Statistical Software (R Development Core Team 2007).

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The impact of goal focus, task type and group size on synchronous net-based collaborative learning discourses