Designing computer systems to support peer learning

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  • European Journal of Psychology of Education1m, Vol. VII, n? 4, 339-352 1992, I.S.P.A.

    Designing Computer Systems to Support Peer Learning

    Claire O'MalleyUniversity of Nottingham, UK

    This article begins with a review of the various roles which computershaveplayedin supporting collaborative learning and argues that, whateverrole it plays, technology is not neutral with respect to interactions withand between users. Interfaces to learning environments embodyparticularrepresentational schemes which have the potentialeitherfor competingwith representations of the learning domain or for giving access to it.In this respect, the learner-machine interface has 'Epistemic significance'and its design is as important as the design of the materials and activitiesto which it interfaces.

    Introduction

    Until relatively recently, one of the main advantages put forward for the use of computersin education was their potential for providing individualised, adaptive instruction. Despiteadvances in research on intelligent tutoring systems (ITS), this trend seems to have changedto some extent. Many early proponents of ITS now recognise the need to support the socialconstruction of knowledge (e.g., Brown, 1990) and computers are being seen increasingly aspotential tools for enhancing cooperative learning.

    The pressure for this change is partly pragmatic, due to limitations on the resources andorganisation of classrooms. There are also pedagogical reasons for using computers to supportgroup work. Several studies suggest that it increases levels of interaction and encourages childrento cooperate and help each other. There is also a good deal of research in developmentalpsychology suggesting that peer interaction and peer tutoring provide advantages overindividualised instruction, whether or not computers are involved.

    Although for various reasons the current interest in computer support for collaborativelearning is a good thing, there has unfortunately been rather little progressmade in understandingits implications for the design of educational software. With the exception, perhaps, of softwaredesignedspecifically for communication across a network (e.g., computer conferencing in distanceeducation), most software described in the literature on computer assisted learning and onpeer interaction with computers, is still designed with individual users in mind, although theactivities around the computer may be designed for cooperative work. This is a ratherimpoverished way of using what could be a powerful technology for mediating collaborativelearning.

    One useful outcome of research in this area would be guidelines for designing, configuringand using the technology, given the particular role it is to play in interactions between learners.

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    Unfortunately, there is at present little specific guidance from the available psychological andeducational literature which might inform interface design for such systems.

    This paper is concerned with making two specific points as a step towards understandinginterface design for collaborative learning environments. Firstly, technology is not neutral withrespect to learning and collaboration (nor are any other activities, come to that); it changes,not merely supports, interaction. Secondly, interfaces to learning environments embody theirown representational schemes apart from representations of the domain. These mayor maynot correspond with, or map onto, the learning activities to which they interface. It followsfrom these points that interface design is just as much the domain of educationalists as isthe design of curricula and learning activities. We need to take this seriously if representationsat the interface are not to compete with representations of the domain being learned.

    Towards principles for designing effective computer support for collaboration

    The role of the computer in collaborative settingsThere seem to be three main roles which the computer has played with respect to

    collaboration, ranging from the merely passive to the more active:

    Learning around the computer. This approach involves seeing the computer as a catalystor object for reflection on some joint activity (e.g., Bamberger, 1983; Sheingold, 1987). Herethe computer doesn't necessarily have any particular special properties with respect to supportingcollaboration, although it may have special properties with respect to the type of activity inwhich users can engage (e.g., simulations), and software is generally designed for individualuse, requiring turn-taking on the part of users within pairs or groups.

    Learning through the computer. Computers can also be used to support communicationbetweenpairs or groups of students engaged in joint activities. This approach sees the computeras a medium for joint activity, as embodied in, for example, computer conferencing or emailsystems (cf. Hiltz, 1988; Mason & Kaye, 1989), although it doesn't necessarily supportcollaborative activities much more than being a means for transmitting information, similarto a telephone or other communication medium.

    Learning mediated via the computer. This view is slightly different to either role justdescribed, in that the computer is seen as contributing something quite different in collaborativesettings to that provided by any other kind of resource. In this view, the computer is a toolwhich augments collaborative learning, supporting not only communication but also jointactivities in some particular way. In this case, the system is designed with pairs or groupsof users in mind. In its most extreme form, this approach sees the computer as being a potentialparticipant in the interaction (cf. Chan & Baskin, 1990; Dillenbourg & Self, 1992).

    There is probably a continuum of roles for the computer in supporting collaborativelearning, rather than this simple tripartite classification. Each of these views of the role ofcomputers in facilitatingcollaborativelearning has its advantages and disadvantages. Proponentsof computer-mediated communication (e.g., conferencing systems) argue that the advantagesof asynchronous interaction include allowing learners time to reflect and react more to thecontent of the message than the attributes of the sender. The fact that messages can be storedalso increases accessibility to the: process and results of interactive communication, preservingand extending interactions in space and time (Henri, in press; Kaye, in press).

    On the other hand, others argue that there are distinct advantages to using computersfor synchronous interaction. Roschelle and Thasley (in press) point out that the computer canbe used as a means for disambiguating language, in that students may not have a precisenor shared vocabulary for describing things but can use the computer simulation to support

  • DESIGNING SYSTEMS 10 SUPPOKf PEER LEARNING 341

    their talk. The computer interface also provides another means for producing conversationalturns (e.g., through the use of the mouse) and for resolving impasses in joint problem solving.

    In actuall practice, there may not be a hard and fast distinction between asynchronoussystems such as conferencing tools and synchronous systems. For example, Newman discussesan implementation of local area networks which combine both of these features (Newman,in press). Another way to support co-presence in distributed learning situations is via the useof video and audio integrated with the computer environment (e.g., Smith, O'Shea, O'Malley,Scanlon, & Taylor, 1991). Work by Boyle and Anderson (1992) suggests that face-to-faceinteraction, in particular where there is eye contact, produces more effective and efficientinteraction in joint problem solving tasks than audio-only conditions. Roschelle and Thasley(op, cit.) also note the importance of actions and gesture in creating a shared understandingin co-present interactions.

    Factors influencing effective collaborationThere are numerous studies reporting computer support for joint activity in a variety

    of ways. It is difficult to distil principles from this body of research since the studies differwidely in terms of tasks, settings, methodology and theoretical approach. We can infer someof the general factors affecting computer supported collaborative learning, but these are largelyto do with the settings in which collaborative learning occurs, such as the size and compositionof groups, rather than the design of the technology itself:

    Group size. We know something about the relative advantages of different types ofgroupings for collaborative learning. Evidence suggests, for example, that pairs are more effectivethan larger groups, that groups of three tend to be competitive, whilst pairs tend to be morecooperative (,e.g., Trowbridge, 1987). However, other studies have shown no such differencesin group size when children are also given the opportunity to interact with others in the class(Colbourn & Light, 1987; Light, Colbourn, & Smith, 1987).

    Gender. We know something about the social dynamics and composition of groups withrespect to more or less effective collaborative learning with and around computers. The researchsuggests that gender and friendship groupings are important factors. Jackson et al, (1986)found that teachers prefer to organise mixed gender groups rather than single gender groups.This has some support from studies showing that girls, at least, do worse in single genderpairs than in mixed gender pairs (Hughes & Greenhough, 1989). However, other studies havefound that in mixed gender groups boys tend to be socially dominant and girls less motivated(e.g., Siann & Macleod, 1986). Gender influences seem to depend on the type of task.Underwood et al. (1990) found that mixed pairs performed less well than same gender pairson a language task, as opposed to the programming task used in the studies just cited.Underwood and Underwood (1990) argue that there may be two reasons for the different resultsfound in these studies: programming tasks rely heavily on spatial skills rather than the verbalskills of the language task. The second reason they give serves as a good example of theimportance of interface design: the tasks used by Hughes and Greenhough (1989) constrainedthe responses of students when an error was made, whereas the task used by Underwoodet al. was more tolerant of errors by students.

    Ability mix ofparticipants. There are also some sources for guidelines on the most effectivemix of abilities of participants in collaborative learning. Research stemming from a Vygotskianperspective tends to focus on asymmetrical pairs; usually employing adult-child pairs, or pairinga less advanced with a more advanced child. Research from a neo-Piagetian perspective tendsto emphasise equivalent intellectual abilities within the pair, although there are usually slightdifferences in the knowledge of each child within the pair. Explanations for the mechanismsunderlying conceptual change also differ according to these perspectives. Studies focussing

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    on asymmetrical pairs tend to appeal to guidance or tutoring mechanisms, whereas thoseemploying symmetrical pairs USI~ explanations based on cognitive conflict. Very few studieshave attempted to synthesise these: different accounts. Verbaand Winnykamen (1992) investigatedthe difference between relations based on expertise in the domain and those based on generalintellectual differences within the pair. They argue from their studies that no single mechanismcan account for conceptual change: it depends on the particular differences in expertise withinthe pair. They looked at high ability children who had been paired with low ability childrenunder two conditions: in one condition the high ability children were experts in the domainwhilst the low ability partner was a novice; in the other condition the low ability child wasthe expert and the high ability child was the novice. Pairs where the high ability child wasthe expert were characterised more by tutoring and guidance than pairs where the high abilitychild was a novice, in which case there was more cooperation than tutoring.

    Type of task. The benefits of peer interaction, as well as explanations given for underlyingmechanisms, also differ depending on the type of task. Crook (1987) found that the mostsuccessful tasks for promoting effective collaboration were those involving problem solvingand discussion of competing hypotheses. Blaye and Light (in press) report a study which showsthat working in pairs leads to more anticipatory planning, use of information for planningand regulation of problem solving than individuals working alone. Gauvain & Rogoff (1989)also show superiority of pairs over individuals in planning strategies, but this only happenswhen pairs demonstrate shared task responsibility during the interaction.

    Explanations for the benefits of collaborationAs mentioned above, there are differences in the explanations offered for the benefits

    of peer interaction, but which account is most plausible seems to depend on the type of taskand the ability mix of participants. The two main explanations that have been put forwardare conflict-based accounts and accounts based on tutoring and co-construction. Some studies(e.g., Fraisse, 1987) suggest that children perform better and interact more when the computerprovokes conflict with their ideas, However, recent work by Howe et al. (in press) suggeststhat facilitation depends upon the particular type of conflict engendered. This study involveda computer based task concerning freefall under horizontal motion. Students had to inputpredictions about the paths which objects would follow when they fell and interpret the feedbackprovided by the computer simulations of the motion. Pairs were arranged so that studentswere either similar or different with respect to their initial predictions and initial conceptionsabout the paths, as obtained in pre-tests. Students whose pairings differed on both predictionsand conceptions showed more pre- to post-test change than any of the other groups.

    These results suggest that, for conflict to promote learning, there should be differencesin underlying concepts as well as judgements or predictions. One explanation for this mightbe that, although differences in predictions may provide an initial destabilisation of students'explanations, actual change requires promotion of discussion in order to construct and attemptto reconcile alternative accounts. This seems to be fostered in conditions where there are initialconceptual differences. This fits with studies suggesting the importance of peer interactionin promoting verbalisation and discussion (e.g., Fletcher, 1985; Forman & Cazden, 1983; Crook,1987). However, a recent replication of the study by Howe et al. suggests that discussion maynot be necessary for promoting change (Payne & O'Malley, 1992). In this study the partnerwas the computer, rather than another student, although subjects were told that the predictionsand explanations given by the computer were those of the previous subject.

    The suggestion that conceptual conflict can provoke internal individual change withoutdiscussion is supported to some extent. Blaye (1988) found that when pairs of children wereforced to make joint decisions by both of them entering a command (one by lightpen andthe other via the keyboard) they did better than pairs who were not so constrained. Lightet al. (1987) found similar results when pairs were forced to make joint decisions via dual

  • DESIGNING SYSTEMS 10 SUPPORf PEER LEARNING 343

    key input. Light and Blaye (1990) suggest that the most likely mechanism underlying progressin these studies seems to be the destabilisation of initial inefficient strategies. This is supportedby Howe et at. (in press), whose findings suggest that conflict is most useful when it involvescompeting strategies for attempting solutions (which is probably more likely to be found incomplex tasks), than when it involves simple rules or procedures.

    Other studies suggest that peer learning is more effective in cooperative rather thanconflictual or competitive conditions. Johnson et al. (1985) compared children workingindividually with those who worked in groups of four under two conditions: one involveda competitive task, the other involved cooperation, where children were assigned specific rolesin rotation. The children who worked in both groups did better on severalperformance measuresthan those who worked alone; those working in cooperative groups also did "better than theother two conditions. Howe et al. (in press) also found that when predictions and strategieswere the same for participants, progress was made, but not to the same extent as when theywere different. Roschelle and Thasley (in press) also concur with this account, seeing collaborativeproblem solving and learning as involving the construction of a negotiated and shared conceptualspace, via the external mediational framework of shared language, situations and activity.However, what emerges as a shared understanding within the course of the interaction maynot be what learners end up internalising. There may be social pragmatic factors affectingthe interaction, such as wanting to appear to cooperate, without it leading to any lasting change,or subjects may indeed co-construct a solution to a problem within the interaction, butindividually internalise very different solutions to each other (cf. Miyake, 1986).

    The computer as a mediational resource

    As Roschelle and Teasley (in press) point out, computers can provide external mediationalresources for shared language, situations and activities in collaborative learning (cf. alsoNewmanet al., 1989; Sheingold, 1987; Rubtsov, 1991). This idea of interface as resource, rather thanas a barrier or gulf (cf. Norman, 1986), has also been put forward by Payne (1991). In thisview, the sense in which interfaces-as-artifacts mediate activity is not as simple channels ortransmitters of communication - they actively change (mediate) the nature of users' tasks(Norman, 1991). This point is illustrated here with an example taken from a study carriedout with an integrated computer and video environment, which suggests that such technologymay change the way in which participants act in interesting ways.

    In this study, pairs of adults used a system called SharedARKI (Smith et al., 1991), whichallows users at separate workstations to interaet in real time with the same world of simulatedphysical objects. Like ARK (Smith, 1990), the system upon which it is based, these objectsbehave as if they were real physical objects: they can be manipulated in similar ways to realobjects via the use of a mouse-operated hand, they obey the laws of physics, and so on.Unlike the real world, these laws themselves can be changed. What is different about SharedARKis that several users can interact with these objects and laws within the same world, in realtime, even if these users are physically separated at different workstations. In addition, userscan work separately in different areas of the same world, by scrolling their windows overthe two-dimensional plane, or work together, by bringing their windows into coincidence witheach other. SharedARK thus provides a means for supporting distributions of tasks and rolesin joint activity which are difficult to achieve with conventional single-user systems. Providingflexibility in the distribution of activities in collaborative work can have important consequencesfor learning (cf. Hutchins, 1990).

    In this study, users worked together with the system to run experiments to solve a physicsproblem', 'Iwo users were located in separate rooms with a workstation each, and couldcommunicate: through an audio link and a camera-monitor device called a videotunnebr',which enabled them to have direct eye-contact with each other. We compared this with threefurther conditions. The second condition involved two pairs working in separate rooms with

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    an audio link only. In the third condition subjects were in the same room and worked withtwo workstations arranged back-to-back on a table, diagonally opposite each other, with aphysicalgap (a simulated tunnel) through which they could look at each other. In the fourthcondition subjects worked side-by-side at a single workstation.

    We were interested in observing how and when video was used and what difference itmade to the nature of users' interactions, Despite its potential artificiality in simulating co-present interaction, the technology seemed quite natural to users. Often, subjects in thevideotunnel condition seemed to forget that their partner could only see a head-and-shouldersview and would start pointing ail the computer screen with their real hands (as opposed tousing the mouse). This didn't occur in the other conditions (except very occasionally in theaudio-only condition). Subjects in the videotunnel condition also sometimes gestured at theirpartner through the videotunnel with one hand, while gesturing with their virtual hand(i.e., the cursor) with the other hand.

    Establishing eye-contact seemed to be important when discussing meta-level issues (e.g.,strategies for conducting the experiment). While the subjects carried out a set of manipulationsin order to collect some data, for example, their eyes were normally on the computer screenso that they could manipulate objects, adjust controls, or watch the progress of the experiment.On the other hand, when subjects discussed what they had observed, formulated hypotheses,clarified questions, or suggested strategies, they typically looked towards their partner. Thismeta-level activity tended to be accompanied by a fairly high degree of non-verbal cues suchas gesture and facial expression.

    We were also interested in the extent to which this technology might affect task or roledivision. In general, the SharedARK interface - in particular, the use of overlapping (shared)and non-overlapping work areas - seemed to encourage role division and role exchange. Interms of how task division wasachieved, however, the videotunnel condition seemed to involveless explicit negotiation than the simulated videotunnel or audio-only conditions. In thecase of the audio-only condition this is not very surprising; the bandwidth for communicationis much more narrow. Subjects iin the other two conditions could make use of non-verbalchannels of communication in parallel with verbal means. What was surprising is that thesimulated videotunnel pairs did not show this reduction in explicit negotiation of the task.

    In general, subjects in the videotunnel condition seemed to behave as if their partnerwas seated beside them, with the same view of their computer screen, which may explainwhy their task division negotiation was more similar to subjects who were co-present andside-by-side. This is supported to some extent by the finding that subjects in the videotunnelcondition quite often pointed at the screen, even though their partner couldn't see this. Thishardly ever happened in the co-present simulated videotunnel condition, where subjects couldsee that their partner's workstation was turned the other way round, a constant reminderthat the pair may have different views on the virtual world. This sense of being side-by-sidemay be important for achieving fluid task division.

    When technology such as this is introduced as a medium for interaction, one might expectthat the sense of distance between participants would be increased, due to loss of qualityin the audio and video channels, the limited visibility of one's collaborator, and the twodimensional representations on the computer and video screen. However, the combination ofsynchronous interaction via Sharl:dARK and the videotunnel seemed to change participants'sense of physical space. In the SharedARK world, one's collaborator is represented as adisembodied hand (i.e., the cursor) whose orientation is similar to that which is achieved inside-by-side interaction in the real world. This hand, however, appears unconnected to one'spartner's face, which is seen directly opposite (via the videotunnel). Whereas being side-by-side in the real world puts one's partner ninety degrees off to the side, this is not a limitationhere. It becomes possible to be side-by-side (facing the same working surface within thecomputer) whilst at the same time being face-to-face (through the videotunnel). Being bothside-by-side and face-to-face simultaneously seems to reduce the sense of distance which onewould otherwise expect to be increased.

  • Summary

    DESIGNING SYSTEMS TO SUPPOIU PEER LEARNING 345

    In order to design systems which are proactive in supporting collaborative learning, weneed to be conscious firstly of the range of possible types of interaction which might besupported by different forms of technology. Secondly, we need to examine the effects thatdifferent forms of technology and their configurations have upon users' interactions with eachother. Technology is not neutral with respect to either individual interactions nor to interactionsbetween pairs or groups of users. It mayor may not support collaboration in effective ways,but it certainly changes it. The example of SharedARK and the videotunnel illustrates oneof the ways in which this might happen.

    So far I have only considered factors affecting learner-machine interaction at a rathergross level of analysis. In what remains of this paper I will illustrate some other importantdesign issues at a much finer grained level. These examples are used to argue that the designof interfaces to learning environments, even at very low levels of detail, should be driven byeducational theory specific to the domain being represented in that interface.

    Designing the learner-machine interface

    It is somewhat surprising that the learner-machine interface is such a neglected aspectof research in computer assisted learning and intelligent tutoring systems, since it is probablyone of the most important aspects on which to focus (Frye & Soloway, 1987; Wenger, 1987;O'Malley, 1990). There is little chance of fostering learning about the domain if the user hasto struggle with learning and using the interface to that domain. This is not simply an issueof reducing the time taken to learn to use a system. In certain cases, the way in which theinterface is designed may actually foster misconceptions about the domain which wereunintended. We know from research in cognition, learning and development that the way inwhich the task is presented can affect that which is being measured in experiments - viz.the criticisms of many Piagetian experiments (e.g., Donaldson, 1978), the findings that simplechanges in the form of the task alter our abilities to solve problems (e.g., Johnson-Laird &Wason, 1977), etc. We cannot simply assume that what is intended by designers or authorsof learning systems is going to be obvious to the learner: it is a matter for careful design,driven by pedagogical theory.

    Many researchers in human-computer interaction have argued that interfaces should notbe barriers to users achieving their goals, but should be as transparent as possible. Norman(1986) talks about interface design as bridging the gulf between the user and the system. Brown(1990) refers to the need for glass-box technology with respect to learning environments:in other words, designing systems such that users see through the interface to the domain itself.

    There are two ways in which one might interpret transparency here. The first way isto simply focus on making interfaces as usable as possible, so that they become obviousor invisible in the sense of being unproblematic for learners. The second way to achievetransparency is to map the interface as closely as possible onto the domain itself. Let meexplain this point a little further. In any learning environment there are at least three levelsof representation (see Figure 1). One level is the domain itself - in this case, those conceptsand procedures which represent the educational goals of the interaction, or that which theteacher/author intends the user to learn. A second level of representation is embodied in thetasks or activities which teachers or authors have designed for learners, in order to acquirethe knowledge of the domain. The interface to that learning environment is a third level ofrepresentation, embodying the input, output and interaction techniques with which users cancarry out these tasks", Just as the tasks or activities designed by teachers are ways of mediatinglearning of concepts in the domain, so is the interface a way of mediating these learningtasks (see Figure 1).

    There are three points to be drawn from this:

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    a) Simply making the interface easy to use does not guarantee that representations atthe interface will not compete with representations at the task level.

    b) Any representational scheme (e.g., a speed/time graph) carries with it aspects that areto be taken as background, given, or unmarked (in the sense in which linguistsrefer to topic and comment in discourse) and aspects which are foreground, newor marked. This point is particularly clear in cases of analogy (e.g., the orbit of electronsaround an atom is analogous to the orbit of planets around the sum), where only certainaspects of the representation (i.e., the analogy) are relevant. As designers we need tomake it clear for learners which aspects of the interface as a representational schemeare relevant to the task, and which aspects are not (cf. Amigues & Caillot, 1990).

    c) It follows from (b) that there may be situations in which it is desirable to make theinterface actually opaque to the user, rather than transparent, in order to make salientwhat would otherwise be glossed over. This suggestion is similar to that made by Lewisand Norman (1986) when they refer to forcing functions as a way of avoiding errors(e.g., forcing the user to confirm a command, such as deleting a file, before executing it).

    interface task domain

    Figure 1. Levels of representation in learning environments

    Decisions about details of the interface are therefore educational decisions. This is thepoint made by Wenger (1987), who argues that the interface to learning environments has'epistemic significance'. This issue is illustrated below, using examples from an environmentfor learning physics in which the input, output and behaviour of interface objects were designedto provide explicit metaphors for the physics concepts being taught via the system (Iwiggeret al., 1991).

    Promoting conceptual change in physics

    Many of the problems which students have in learning physics appear to stern from amismatch between deeply entrenched prior conceptions and the formal concepts and lawsoperating in the physics domain. These prior conceptions - whether or not one calls themtheories (McCloskey, 1983) or more fragmented beliefs (DiSessa, 1989) - are probably rootedin very early development (see, for example, Spelke, 1991). These underlying conceptual structuresprovide a sensible framework for understanding and describing the world from the child'spoint of view. However, children's alternative concepts tend to be poorly differentiated, therelations between them lack precision and their explanations for physical phenomena are onlypartial or context-specific. These alternative conceptions tend to be robust and resistant tochange because they often do actually accord with everyday experience. A common exampleis the belief that motion requires a force - which is of course consistent with most of ourexperience in a world with friction.

    If one is to convince students about the physical laws actually underlying their own personal

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    experiences with the physical world, one needs to begin with those experiences and userepresentations which will bridge betweenthe incorrectand correct views of physics. Simplypresenting the scientist's view of reality is not necessarily sufficient for conceptual change;neither is simply presenting counter-examples to prior conceptions (cf. Howe et al., in press),since learners tend to distort information to fit their existing models. Successful interventionsshould begin with promoting learners' awareness of the limitations of their current conceptionsand models of the world. Since individuals may develop severalconflicting models to accountfor different aspects of a domain or even different instances of the same phenomena (cf. Spiroet al., 1989), revealing the inconsistencies or conflicts amongst their different models is alsoimportant in facilitating change. However, one needs to go beyond this and assist childrenin refining their alternative conceptions, by enabling them to develop and use a frameworkwhich is internally coherent and which fits with their own experiences of the world.

    Computer based activities potentially have an important role to play in promotingconceptual change in this way. Interactive simulations are particularly useful because they enableusers to explore and visualise the consequences of their reasoning. Simulation environmentsalso have certain advantages in that one can clean up the real world and ignore certainvariables (e.g., friction) if necessary, or permit the separation of what is normally a complexset of interacting variables and effects. Using a computer thus enables the simulations of eventswhich would otherwise be practically impossible, and can turn abstract conceptsand relationshipsinto manipulable objects and phenomena. Simulations can also allow students to see theconsequences of changing the laws of physics, for example, as in the Alternate Reality Kit(Smith, 1990).

    However, computer based activities alone are unlikely to be successful in promotingconceptual change, There is a danger that students will regard experiences with computersimulations, for example, in much the same way as they do practical laboratory activities,where they tend to concentrate on laboratory procedures for data collection and obtainingthe right answer, and to view classroom science as divorced from everyday experience. Thenew conceptions, rules and procedures developed in one context need to be extended to arange of contexts and require pupils to explore inconsistency in the use of their ideas. In otherwords, explicit bridges need to be made between real world experiences, classroompracticaland written work, and computer based activities.

    Representational issues

    As Sheingold (1987) points out, the computer is a symbolicmedium. Representing physicalobjects and concepts in a computer simulation is already one form of abstraction. The waythe domain is represented in the form of particular tasks or activities is another form ofabstraction. There are thus at least two orders of abstraction in microworlds. If the computeris to serve as a vehicle for students' experiments with the world of physics, the links betweenthese abstractions or representations should be made as clear as possible. The process ofdesigning the interface to these systems thus becomes a process of pedagogical engineeringand not merely an issue of usability. It therefore raises some important issues concerningthe design of representations with which to reason about the domain being learned. Theseissues are illustrated here using examples taken from a study of the use of simulations topromote conceptual change in Newtonian mechanics, described in more detail in 1\vigger etal. (1991) and Hennessy et al. (in press, a, b).

    Pairs and groups of students aged 12-13 years used computer simulations presenting avariety of scenarios and different representations of the underlying physics to exploreinconsistencies in the use of their ideas about force and motion. These computer-basedactivitieswerealso linked closely to practical laboratory work, in order to increase the variety of contextsand to convince pupils that the same rules which applied in the computer-based world applyin the real world.

    The specific focus was on fostering appreciation of qualitative relationships like as force

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    increases, acceleration increases. In particular, these activities were designed to remediate variousmisconceptions which these students had about force and motion. For example, studentsof this age believe that moving objects stop eventually and that a moving object has a forceor energy within it which acts in the direction of motion and keeps it going. The objectis thought to stop moving when the force within it gets used up. Another set of misconceptionsholds that a constant applied force produces constant motion, a larger force produces a largerconstant speed, and acceleration is produced by an increasing force. In general, all thesemisconceptions stem from a tendency to look for a single causal factor, lack of appreciationof all the (relevant) forces acting and their relative magnitudes and directions (i.e., a notionof balanced forces), and lack of appreciation of the combined effects of applied forces togive a nett force.

    In order to address these conceptions we developed a sequence of scenarios, representinghorizontal motion with friction (involving both impulsive and continuous forces), horizontalmotion with negligible friction, horizontal motion with velocity-dependent resistanceand verticalmotion under gravity. (Details of these scenarios and justifications for their design can befound in 1\vigger et al., 1991 & Hennessy et al., in press (a)).

    These scenarios were represented in the form of computer-based microworlds and in specificpractical activities, together with accompanying worksheets for recording results and posingproblems for the students. The software took two different forms: one was a modelling systemcalled Varilab, which allows children to reason about their own conceptions by expressing theircausal accounts of phenomena and events as qualitative models. The other was a softwareenvironment for creating interactive simulations or microworlds of motion under various forces(DM3, which stands for Direct Manipulation of Mechanics Microworlds). This was usedto create a series of microworlds embodying the scenarios outlined above.

    In designing our interventions, we were careful to build specific bridging representationslinking students' real-world experiences with classroom-based practical work, activities withinthe DM3 microworlds and modelling activities within Varilab. This was achieved in severalways. Firstly, the microworlds in DM3 were designed to represent objects and events whichhad real-world counterparts. However, these were simplified versions of what actually happensin the world we experience. In order to make this point clear, these microworlds were linkedto hands-on practicals, using similar representations of the underlying physics, such as tickertape, for example, to represent stroboscopic motion. Similar representations, in the form ofgraphical output devices and icons representing objects, also served to bridge between thebehaviour observable in the microworldsof DM3 and the models which students built in Varilabto explain what they had seen in DM3 The principle of inter-referential 1/0 (cf. Draper,1986), or stimulus-response compatibility, where input and output are mapped onto each other,wasused to represent in the interface behaviour the physics concepts being learned. For example,students have problems understanding the notion of a constant force. Our interventions beganby allowing them to explore force and motion using buttons that could be pressed by a mouse-operated hand to provide discrete impulses as forces. However, when students' moved onto microworlds in which constant forces operated, sliders were used instead, to represent acontinually acting force once the slider had been set to a particular value. Repetitive clickingof buttons were also used to bridge between impulsive and constant forces (i.e., the notionof a continually acting force was likened to a discrete impulsive force acting at regular timeintervals).

    Since the aims of our activities included getting pupils to construct progressively moreelaborate rules, to generalise their new conceptions across a range of contexts, and to extendthem to increasingly complex situations, the order in which activities were presented wasimportant. Particular cases were revisited in increasing detail: idealised ones which simplifiedthe underlying physics (e.g., frictionless worlds), and those which pupils had experiencedthemselves (e.g., the behaviour of everyday objects under friction). The particular microworldsthemselves thus also served as bridging representations: students would deal with cases ofspeed-dependent fluid resistance under horizontal motion before moving on to examine the

  • DESIGNING SYSTEMS 10 SUPPORT PEER LEARNING 349

    case of vertical motion under gravity and the effects of air resistance. We therefore createda sequence of interrelated computer worlds and practical situations increasing in complexity,by gradually introducing more variables, more difficult concepts and, in the computer worlds,more extensive functionality.

    Summary

    The detailed decisions concerning the design of the interface to Varilab and DM3 werenot made simply on the grounds of ease of learning or use of the system (although we certainlywanted to achieve this as well). They involved particular educational decisions about how bestto represent underlying concepts in the domain. Each of these design decisions was extensivelypiloted and changed, if necessary, via prototypes, before the eventual system was tested ina real classroom.

    These interventions were evaluated over a period of about 8 weeks, during the sciencelessons normally allotted to the class under investigation. (Full details of this evaluation studyare given in Hennessy et al., in press b). Although the constraints of .a field study run inthe normal classroom did not permit us to isolate in detail the effects of the interface designdecisions we had made, results of the intervention as a whole were positive. Students in theexperimental group produced more change in the numbers of correct responses to questionsabout Newtonian mechanics than those in control groups. These changes were also maintainedat delayed as well as immediate post-test.

    Conclusions

    This paper began by examining briefly the various ways in which computers have beenseen as providing support for collaborative learning. Each of these ways of using computershas its advantages and disadvantages, but whatever role it plays and whatever activities aredesigned for learners to engage in with computers, the technology itself is not neutral withrespect to learning activities. Several people have discussed how computers can be used toscaffold joint activity (e.g., Sheingold, 1987), but this suggests an inert and passive structure.Others have talked about the computer creating a 'zone of proximal development' (e.g., Pea,1987), but again this does not reflect the way in which the zone is actively constructed bothby users and by the technology as a symbolic mediator (cf. Newman et al., 1989). In orderto design more effectiveuses for the computer in supporting joint activity we need to understandthe ways in which it actively changes and mediates interaction. The SharedARK study offersone example of these kinds of changes.

    In addition, the particular ways in which interfaces to learning environments are designedembody certain representational commitments. These decisions are often made implicitly, withthe focus being more on the design of domain representations and learning activities. Of coursethe latter are important, but if the interface is ignored it may not matter how much efforthas gone into the other design decisions, since the former might end up competing with thelatter. Rather, we should take seriously the interface as a resource for learning and collaboration.The design of DM3 and Varilab was given here as one example of how one might apply this.This example also illustrates the point that the term interface can be seen to encompassmore than just interaction with the computer: it includes the context in which the computeractivities take place and the context of learners' prior conceptions about those activities.

    Notes

    SharedARK is a multi-user version of the Alternate Reality Kit (Smith, 1990).2 See Smith et aI. (1991) for more details of the system and this study.

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    This setup consists of a camera mounted on top of a monitor, with mirrors which place the camera's point of viewat the centre of the monitor. This enables users to have face-to-face eye contact with each other. These devices areplaced inside a box so that users only see each other's images through the 'tunnel' and don't see the camera (Smithet aI., 1991).There are actually other levels involved, such as the representations which learners bring to the interaction concerningthe interface, the learning tasks and the domain.

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    1\vigger, D., Byard, M., Draper, S., Driver, R., Hartley, R., Hennessy, S., Mallen, C, Mohamed, R., O'Malley, C., O'Shea,T., & Scanlon, E. (1991). The 'Conceptual Change in Science' project. Journal of Computer Assisted Learning,7, 144-155.

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    Key words: Computer support; Interface design; Peer interaction; Physics instruction.

    Received' June 1992

    Revision received' August 1992

    Oaire O'Malley. Department of Psychology, University of Nottingham, University Park, Nottingham NG7 2RD, UK.

    Current theme of research:Computer supported collaborative learning

    Most relevant publications in the field of Educational Psychology:O'Malley, C. E. (Ed.) (in press). Computer Supported Collaborative Learning. Heidelberg: Springer Verlag.O'Malley, C. E., & Scanlon, E. (1990). Computer-supported collaborative learning: Problem solving and distance education.

    Computers & Education, 15, 127-136.Smith, R., O'Shea, T., O'Malley, C, Scanlon, E., & Thylor, J. (1991). Preliminary experiments with a distributed, multimedia,

    problem solving environment. In 1. Bowers & S. Benford (Eds.), Studies in Computer-Supported Cooperative Work:Theory, Practice, and Design. Amsterdam: Elsevier Science Publishers.

    1\vigger, D., Byard, M., Draper, S., Driver, R., Hartley, R., Hennessy, S., Mallen, C., Mohamed, R., O'Malley, C, O'Shea,T., & Scanlon, E. (1991). The 'Conceptual Change in Science' project. Journal of Computer Assisted Learning,7, 144-155.

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