Instructional design for Computer-Supported Collaborative Learning in primary and secondary school

13
Editorial Instructional design for Computer-Supported Collaborative Learning in primary and secondary school 1. Introduction The study of Computer Supported Collaborative Learning (CSCL) has a rela- tively brief history, yet despite this there have already been substantial changes in the nature of the research being undertaken in this field. Initially, the primary aim was to determine whether collaborative learning was more effective than learning alone and if so in what circumstances. In fact, many studies highlight the positive effects of social interaction on learning (Dillenbourg, 1999; Koschmann, 1996) and indicate that collaborative learning would seem to be more in keeping with the needs of the ‘‘information society’’, in which cooperative relationships, shared decisions, diversity and communication are becoming the dominant values. Computers have typically been used for individual learning but, given the positive findings reported for collaborative learning and the need to educate individuals to work together, it has become apparent that the use of computers can constitute a particularly valuable context for social interaction. As a result, the need to design learning environments that facilitate social interaction, cooperation and collabora- tion in the classroom has gained growing recognition. Recently, research interest has shifted away from considering simply the outcomes and products of collaborative work, towards analysing interactions as a means of gaining insight into the processes of collaborative learning. The aim of such analyses is to identify what constitutes productive collaborative activity. Most of the research in collaborative learning has been focused in four different areas: (1) The study of cognitive differences: a comparison between learning alone and learning in groups adopting a variety of psychological approaches (develop- mental, sociocognitive, etc), (2) The design of systems to facilitate collaborative learning, (3) The analysis of the implications for curriculum design (role of teachers, students, etc.), and (4) The consideration of the nature of interactions. In reviewing these areas the paper focuses attention on the way in which current instructional design theories can be used to design collaborative learning environments in primary Computers in Human Behavior 17 (2001) 439–451 www.elsevier.com/locate/comphumbeh 0747-5632/01/$ - see front matter # 2001 Elsevier Science Ltd. All rights reserved. PII: S0747-5632(01)00016-4

Transcript of Instructional design for Computer-Supported Collaborative Learning in primary and secondary school

Editorial

Instructional design for Computer-SupportedCollaborative Learning in primary and

secondary school

1. Introduction

The study of Computer Supported Collaborative Learning (CSCL) has a rela-tively brief history, yet despite this there have already been substantial changes inthe nature of the research being undertaken in this field. Initially, the primary aimwas to determine whether collaborative learning was more effective than learningalone and if so in what circumstances. In fact, many studies highlight the positiveeffects of social interaction on learning (Dillenbourg, 1999; Koschmann, 1996) andindicate that collaborative learning would seem to be more in keeping with the needsof the ‘‘information society’’, in which cooperative relationships, shared decisions,diversity and communication are becoming the dominant values.Computers have typically been used for individual learning but, given the positive

findings reported for collaborative learning and the need to educate individuals towork together, it has become apparent that the use of computers can constitute aparticularly valuable context for social interaction. As a result, the need to designlearning environments that facilitate social interaction, cooperation and collabora-tion in the classroom has gained growing recognition. Recently, research interest hasshifted away from considering simply the outcomes and products of collaborativework, towards analysing interactions as a means of gaining insight into the processesof collaborative learning. The aim of such analyses is to identify what constitutesproductive collaborative activity.Most of the research in collaborative learning has been focused in four different

areas: (1) The study of cognitive differences: a comparison between learning aloneand learning in groups adopting a variety of psychological approaches (develop-mental, sociocognitive, etc), (2) The design of systems to facilitate collaborativelearning, (3) The analysis of the implications for curriculum design (role of teachers,students, etc.), and (4) The consideration of the nature of interactions. In reviewingthese areas the paper focuses attention on the way in which current instructionaldesign theories can be used to design collaborative learning environments in primary

Computers in Human Behavior 17 (2001) 439–451

www.elsevier.com/locate/comphumbeh

0747-5632/01/$ - see front matter # 2001 Elsevier Science Ltd. All rights reserved.

PI I : S0747-5632(01 )00016 -4

and secondary schools. In so doing the paper is divided in three parts. In the first ofthese, the main dimensions of CSCL are defined. In the second part, studies dis-cussing CSCL in primary and secondary school are reviewed. Finally, in the thirdpart, the focus moves to the development of new instructional design theories thatsupport collaborative learning, and issues concerning the evaluation and futureresearch of instructional design for CSCL are discussed.

2. The dimensions of Computer Supported Collaborative Learning (CSCL)

‘‘Collaboration’’ refers to the fact that a group of people work together on a task.However, much has been written about how best to define ‘‘collaborative learning’’.A frequent point of departure is to draw a distinction between two terms that areoften used interchangeably: ‘‘collaborative’’ and ‘‘cooperative’’ learning. The maindifference between these terms concerns the nature of the task being carried out andthe role of the group members in achieving the task. In a collaborative learningprocess, two or more people are required to learn something together; what has tobe learned can only be accomplished if the group works in collaboration. Therefore,the group needs to decide how to achieve the task, which procedures they will adopt,how they will go about dividing up the roles, etc. Communication and negotiationare fundamental in a collaborative learning process. In contrast, cooperative learn-ing requires a division of tasks among group members. For instance, the teacherproposes a problem that the group needs to solve and indicates who will beresponsible for obtaining references from the library, who will conduct a web search,who will report back on the findings, etc.Dillenbourg’s definition is clear on the matter: ‘‘a situation is termed ‘collabora-

tive’ if peers are (1) more or less at the same level and can perform the same action,(2) have a common goal, and (3) work together’’ (Dillenbourg, 1999, p. 9).While classical CBL (computer-based learning) and current multimedia are

designed to support an individual process of learning, in recent years an increasingnumber of systems that support group learning has been produced: programs thatencourage learning in collaboration, videogames to be played in a group (withoutany element of competition), systems that facilitate communication and negotiation,the production of materials that involve written collaboration, and so on.Based on the dimensions of collaborative learning identified by Kumar (1996), we

outline eight elements that should be addressed in the design, development and useof CSCL systems:

2.1. Control over collaborative interactions

The control over a collaborative interaction refers to the system’s mode of deliveryin the collaborative environment. Thus, a system might be involved in analyzing andcontrolling collaboration or act simply as a vehicle for collaboration. For instance,CLARE (Want, 1994), a computer supported learning environment that facilitatesmeaningful learning through collaborative knowledge construction, provides a

440 Editorial / Computers in Human Behavior 17 (2001) 439–451

semi-formal representation language and an explicit process model called SECAI.This allows an environment to be constructed that facilitates the negotiation, thedistribution of the task, and the whole process of problem solving in collaboration.Electronic mail and chat sites can be used as a way to support communication but,

in such cases, the system does not control the process, rather it is simply a vehicle forcommunication.

2.2. Tasks in collaborative learning

In a given collaborative learning environment those collaborating are faced withdifferent task-types to perform. All collaborative processes of learning are based onthe resolution of a task that focuses on either specific content or procedural learning.However, this distinction might not be very clear in practice because elements ofboth aspects might be present in the task. Nevertheless, the task will generally placemore emphasis on one or other of the two aspects.In general, collaborative learning becomes meaningful when different actions and

decisions are involved in working on a complex task or problem. It is perhaps,though, an error to make all learning activities a collaborative process because theindividual dimensions of learning are also very important.

2.3. Learning theories underlying collaboration

Three theories have been forwarded in seeking to explain the benefits of colla-borative learning: constructivism, cultural-historical theory and situated cognition.Constructivism originally developed out of Piaget’s theory of knowledge con-

struction and the research he conducted in developmental psychology. A growinginterest in the social context within which learning occurs led a number of neo-Piagetians (Doise & Mugny, 1984) to emphasize the importance of context duringthe construction of knowledge. This approach highlights an individual’s develop-ment with respect to their social interaction, without however differentiating thefactors that enhance collaborative learning.Another major influence on collaborative learning is the research conducted by

Soviet psychologists, principally Vygotsky (1978), who formulated the theory ofcultural-historical psychology. Each internal cognitive change, it is argued, is due tothe causal effect of a social interaction. Interactions between peers, on the one hand,and peers and adults, on the other, are crucial as they promote learning. An analogycan be drawn here with the way in which scaffolding is raised.The theory of situated-cognition views learning as a process of entry into a com-

munity of practice. The main goal is ‘‘to learn to use tools as practitioners use them, astudent, like an apprentice, must enter that community and its culture’’ (Brown,Collins, & Duguid, 1989, p. 33). From this perspective, the context within which thelearning occurs is very important. The main advantage of this approach is that it linkstogether the specific context and the knowledge to be learned; students learn how theycan apply their knowledge to new situations, and the acquisition of knowledge is thusmore practical in nature. For this reason, most research in this field adopts this theory.

Editorial / Computers in Human Behavior 17 (2001) 439–451 441

2.4. Design of collaborative learning environment

The design of the collaborative learning environment is concerned with how best tosupport effective collaborative learning. There are many possibilities: it might be twoor more peers in collaboration using the computer as a mediating tool or using anactive tutor who controls and directs collaborative interaction, two or more peersworking on the same problem at the same workstation, or on the same problem atdifferent places, etc. The use of communication technologies has expanded these pos-sibilities so that collaboration can occur in different places through synchronic andasynchronic interactions. For this reason, the possibilities afforded by the learningenvironment are enormous. Nevertheless, few specific models of instructional designhave been created for CSCL. As we shall see in the following section, most research isbased on a misunderstanding between the system itself and the design of the activity.

2.5. Roles in collaborative learning environment

The design of a collaborative learning environment needs to consider the numberor group size of collaborating peers and to establish and assign different roles.The role of each student in the group might change during the process but it is

necessary to establish certain responsibilities to facilitate the problem-solving pro-cess and to ensure that students learn to work in-group, in collaborative situations,where each is responsible for their own work. The distribution of roles requiresstrategies of communication and negotiation.The design of a collaborative learning environment also needs to consider the

number or group size of collaborating peers. Most experiments are conducted withsmall numbers of peers to reduce complexity. As Kumar (1996) pointed out ‘‘it isnatural to assume that the number of peers is dependent on the requirement of thecollaborative learning tasks’’.

2.6. Domains of collaborative learning

In general, collaborative learning is used in domains where peers engage in skillacquisition, planning, categorization and memory tasks. Peers are introduced to theprerequisites of the topic being studied and reinforce and internalize this knowledgeby using the collaborative environment. Usually, the domain knowledge is complex,hierarchical and requires a full understanding of each level in the hierarchy. It isdifficult to observe a conceptual change if the task is purely procedural and does notinvolve much understanding. Collaboration in some domains requires prerequisiteknowledge and it is through the application of this knowledge that peers mightreinforce their understanding of the domain.

2.7. Tutoring in collaborative learning

There are a number of tutoring methods that might support collaborative learn-ing. The following are perhaps the best known:

442 Editorial / Computers in Human Behavior 17 (2001) 439–451

1. Practice: the peer is asked to apply a previously learned goal to a specific problem.2. Socratic learning: the student is prompted with a series of questions about the

domain, to which the student reacts with a hypothesis or a question of his/herown.

3. Learning by teaching: supports learning by having the student teach the sys-tem, a variation on the use of a simulated student.

4. Situated learning: the student becomes a participant in socio-cultural practice,where the learning skills and the social process go together.

5. Negotiated learning: the student and the system negotiate mutually acceptablelearning goals.

6. Discovery learning: the student explores an environment specially craftedto encourage learning. Peers might take individual roles in discovering theenvironment.

Very often the use of one of these methods is confused with the collaborativelearning itself. However, in a collaborative learning process, more than one methodcan be adopted.

2.8. Collaboration mediated by telematic support

The use of the computer to support collaborative learning has undergone rapidchanges in recent years with the integration of telematic tools. Collaboration medi-ated by telematics may proceed synchronously or asynchronously. In synchronousinteraction, participants can collaborate together in real time while being geo-graphically dispersed, whereas in asynchronous interaction, the collaborators’ use ofthe tool may be dispersed in time as well as in space.Another important distinction that needs to be drawn is that between implicit and

explicit communication (Hansen et al., 1999, p. 172). From a designer’s perspective,the former refers to collaboration through the use of shared information resources,such as documents, images and spreadsheets, whilst the latter uses audio and/orvideo channels, or just simple text messages.The coordination of interactions also deals with implicit as well as explicit inter-

action within the group of users. Coordination of implicit interactions includes theprovision of consistent external representations of shared information. Coordina-tion of explicit interactions depends on the group size and on the group’s task. Theneed for coordination grows with the size of a group, the diversity of its membersand the complexity of the task.

3. CSCL studies in primary and secondary school

A large amount of CSCL research has been conducted in primary and secondaryschools (e.g. Dillenbourg, 1999; Koschmann, 1996). Joiner et al. (1999) proposethree reasons for studying CSCL. The first of these lies in the fact that a numberof theories of cognitive development suggest that social interaction is central to

Editorial / Computers in Human Behavior 17 (2001) 439–451 443

development. These theories, as mentioned above, currently hold considerableinfluence over our conceptions of learning and have indeed forced certain cognitiveapproaches to be modified so as to take into account social aspects not previouslyconsidered.A second reason for studying CSCL is to provide educational guidelines for the

optimal use of group activities of this type; while the third reason forwarded byJoiner et al. (1999) is the necessity to design computer systems that support colla-borative learning.Our main aim here is to review the areas of research currently being conducted

and to describe the activities being designed. In doing this we look at four specificaspects: the cognitive approach, the design of systems to support CSCL, curricularimplications, and the nature of interactions.

3.1. Cognitive approach

CSCL promotes greater cognitive development than that found during technol-ogy-assisted competitive or individual learning. Social-cognitive theory holds that inorder to create the conditions in which cognitive development takes place, studentsmust work cooperatively, challenge each other’s point of view, and resolve theresulting cognitive conflicts.Collaborative learning experiences promote higher achievement on technology-

assisted learning tasks when social skills are emphasized. A number of studies havefound that when teamwork procedures and skills are present, cooperative learningresults in higher achievement in technology-assisted instructional lessons. In studieswhere teamwork procedures and skills were not emphasized, reliable differences inachievement in cooperative and individual technology-assisted instruction were notfound.When providing a forum for collaboratively presenting arguments, raising learn-

ing issues, and reaching a consensus on new knowledge, students experience a senseof ownership of their contributions, and a sense of accomplishment in seeing howthey contribute toward the group’s learning.Disagreement exists as to whether CSCL should be composed homogeneously or

heterogeneously. The advocates of heterogeneous grouping point out that studentsare more likely to gain sophistication and preparation for life in a heterogeneoussociety by working cooperatively with classmates from diverse cultures, with a rangeof attitudes and perspectives rather than by learning in homogeneous groups orstudying alone. Academic discussion and peer interaction in heterogeneous groupspromote the discovery of more effective reasoning strategies than occurs in homo-geneous groups. In the best group interactions, group members with different pointsof view or levels of knowledge about a concept can promote critical examination ofthe concept from several points of view.Proponents of homogeneous-ability grouping state that heterogeneous-ability

grouping may fail to challenge high-ability students and that less academically suc-cessful students adopt a passive role and benefit at the expense of their moresuccessful partners.

444 Editorial / Computers in Human Behavior 17 (2001) 439–451

The results of these studies indicate that cooperative learning may be used effec-tively with both homogeneous and heterogeneous groups, but that the greatesteducational benefits may be derived when heterogeneous groups work with tech-nology-assisted instruction. In heterogeneous cooperative learning groups, low-ability students increase their achievement considerably, and high-ability studentsgenerally either increase their achievement level or achieve the same levels as theircounterparts in homogeneous high-ability groups (Dillenbourg, 1999).

3.2. Systems design

Many systems have been designed to support collaborative learning. As Hansen etal (1999) have pointed out, the tools that systems adopt can be analyzed in twoways: one can think in terms of the tools as compensating for difficulties, or in termsof the tools as facilitating new processes. In their compensating mode, tools alleviatethe difficulties users might encounter in communication and collaboration resultingfrom the distribution of collaborating partners in time and space. Such tools facil-itate the communication process. On the other hand, tools can facilitate humanthought through the appropriate processing and presentation of data in such a formthat is easier to understand. Such tools support new processes. With increasingprocessing power and multimedia, facilitation tools are becoming more and moreefficient.Based on this distinction we shall consider examples of both kinds of tool.

3.2.1. Tools to support communicationSystems used to support communication have been concerned with the design of

asynchronic communication facilities. According to Lubich (1995), tools can bestserve a compensatory purpose when they are transparent to the user. This meansthat the communication supported by these tools is, to a great extent, similar toface-to-face communication. This attribute can be used to evaluate the tool accord-ing to the degree of transparency and the ease of use.

3.2.2. Tools to support new processesIn recent years, several interesting projects in this field have sought to create tools

to support collaborative learning in the school. One such example is MEMOLAB(Dillenbourg et al., 1994). This is a learning environment that illustrates the dis-tribution of roles among several agents. It has been developed using artificial intel-ligence and the system supplies support through another agent (tutor) which alsomonitors the interaction. The distribution of roles is conceived in such a way thatthe agents are independent of the teaching domain and hence can be reused to buildother learning environments.Other systems support a particular collaborative project. This is the case of the

CoVis Project (Pea & Gomez, 1993) that has created a collaborator notebook basedon a collaborative hypermedia composition system designed to support within andcross-school science projects. The system focuses on project investigations ratherthan curricular content. During a project, the teacher or any student can pose a

Editorial / Computers in Human Behavior 17 (2001) 439–451 445

question or make a conjecture, which can be addressed by participants from othercities and countries. Conversations may be public or private. The collaborator pro-vides a structural scaffolding for conversations by requiring specific kinds ofresponse to messages. For instance, in order to support the conjecture a student mayprovide evidence to support it. This form of conversation results in more coherentdialogues. In addition to scaffolding conversation, the collaborator also produces anotebook record of the conversation for review and reconsideration by the learnersor the teachers.One of the main concerns in primary and secondary school has been the develop-

ment of the tools to facilitate collaborative writing. This is the case of CaMIE(Jonassen et al., 1999) developed by the Institute of Educational Technology inGeorgia. It is a collaborative NoteBase where students can create notes associatedwith group discussions. Each note added is a response to a note that someone elsehas contributed to the discussion. Students enter a comment note into an ongoingdiscussion. In addition to this, the student can include a QuickTime movie, graphic,sounds, etc.Finally, mention should be made of the Computer-Supported Intentional Learn-

ing Environments (CSILE) that incorporate a classroom model for student inquiryand knowledge generation developed by Scardamalia and Bereiter (1996). This pro-gram is based on the idea that schools have to be restructured as knowledge-buildingcommunities where members interact and share the objectives of learning. Learninghas to take place intentionally, in an active way. To achieve this goal, computers andtelematics can be used to support the construction of knowledge communities. Thesystem called CSILE has two important features:

1. A special computer program for developing a common information base,typically installed on a local network.

2. A systematic model of inquiry based upon the scientific method and informedby current research in cognitive psychology.

CSILE participants approach a problem, develop hypotheses or theories about theproblem, then seek to confirm, modify or discard their theories. Participants colla-borate, review each others’ work, and publish their results as professional scientistsmight.The four systems described are good examples of how CSCL can be used in

schools. Each provides an explicit structure for engaging in thoughtful, reasoned,written discourse. Some constructivist approaches are more radical and believe thatthe system should not be so explicit thereby giving the students the possibility oftaking decisions during the resolution of the task.

3.3. Curricular implications

The use of CSCL in primary and secondary schools has important curricularimplications. First of all, it is impossible to use CSCL without changing some tradi-tional approaches to formal learning. Any CSCL environment has to take intoaccount a great many aspects. For instance, in the ParlEuNet project we have studied

446 Editorial / Computers in Human Behavior 17 (2001) 439–451

the problems involved in designing a co-operative problem-based technologicalenvironment for enabling pupils to learn about the European Parliament. As aresearch project, ParlEuNet investigates the use of components of the learningenvironment and the effects of four pedagogical models. The ultimate goal ofresearch in the ParlEuNet-project is to contribute to the creation and elaborationof a knowledge-base for designing technologically rich, collaborative, problem-based learning environments. The elaboration of an instructional design model forsuch environments is an important step in this respect as it synthesises currentlyavailable knowledge and helps to apply that knowledge in specific situations. Assuch, instructional design models may help to bridge the gap between both theoryand practice.In the design of any learning environment, we need to distinguish between the

learner-related and the instructional-related parameters.Learner-related parameters are taken into account by considering previous

knowledge, cultural background, epistemological beliefs, motivation, etc. Instruc-tional-related parameters center on a problem-based methodology using differentpedagogical models: pro-active (planned, fixed in advance) and re-active on thelearners’ activities.Another important feature of the project has been to create a rich technological

environment in which a variety of communicational systems have been used: fax,telephone, videoconferencing, electronic mail, etc.The final results of the project are not completed processes. Nevertheless, a num-

ber of lessons have been learned that emphasize the complexity of undertaking suchactivities in school. In this sense, it is essential to:

1. Specify the objective of the activity and to include the teachers and students inthe decision-making process.

2. Make a number of pre-instructional decisions. The teacher has to decide on thesize of the group, the method of assigning students to groups, the roles of stu-dents, the materials needed to conduct the activity, the way the room should belaid out.

3. Ensure that participants’ understanding of the task and their knowledge of theuse of technologies are as homogeneous as possible.

4. Prepare the teachers and the students for possible system failures.5. Establish a clear role for the teachers and students.6. Monitor students’ learning and intervene within the groups to provide task

support or to increase the students’ interpersonal and group skills.7. Evaluate the process of the students’ learning and to help students determine

how well their group is functioning.

To sum up, in order to make collaborative learning useful in an instructionalcontext a number of conditions have to be met. Indeed, collaborative learning mayhelp learners to refine their knowledge through discussions with others and throughhaving to give explanations to others. For this to happen though students mustexperience simultaneously: (1) the active construction of knowledge; (2) peer teach-ing, with its opportunities for building oral explanation skills; (3) peer learning, with

Editorial / Computers in Human Behavior 17 (2001) 439–451 447

exposure to good models for problem solving and social interaction; and (4) themotivating feedback of other students (Dede, 1990). In other words, groups thatstimulate reasoning, higher order thinking and cognitive processing.

3.4. Nature of interaction

In a computer mediated collaborative learning situation, the level of interaction isvery important. As Barker (1999) points out, in order to achieve real learning,grounding and appropriation have to take place.Grounding is the name given to the interactive processes by which common

ground or mutual understanding between individuals are constructed and main-tained. Grounding can take place on pragmatic and semantic levels. Interactingparticipants need to understand each other, learn to collaborate and/or have acommon understanding, common domain of the task, meaning, etc.Besides the use of regular electronic mail and videoconferencing, new research

about the nature of interaction has been based on the use of MUDs and MOOs(Kiesler, 1997).These new forms of Internet-based multi-user environments, known as MUDs

and MOOs, are engaging learners in high-level conversations that support personalreflection. A MUD users group is a computer program that users can log into andexplore. Each user takes control of a computerized character. Originally derivedfrom on-line ‘‘Dungeons and Dragon’’ environments, some MUDs have an edu-cational focus such as MIT’s MicroMUSE. Users can enter the virtual environ-ment and travel between locations. Visitors not only interact, but, depending ontheir level of experience, can participate in the design and construction of theenvironment itself. Currently, MUDs are text-based. Motivation is maintained bythe sense that one is participating in a game. The practice and reinforcement ofliteracy skills can yield educational benefits for children participating in MUDenvironments.The nature of interactions can be affected by the cultural background. In CSCL,

multicultural relationships are promoted and communication is affected.

4. Instructional design for CSCL

Instructional design should offer explicit guidance as to the best way in which tohelp people learn and develop. If we consider the specific case of collaborativelearning, most of the articles found on this topic are guilty of confusing methods ofinstruction with instructional design itself. For instance, discussions, tutorials,learning by teaching are mentioned as instructional design models, but rather shouldbe seen as methods for instruction. Probably, the problem lies in the fact that mostclassical instructional design theories are based on individual processes of learning.According to Reigeluth (1999), there is a need for a new paradigm of instructionaldesign theory since many changes have occurred in education and the goals ofinstruction. The same author goes on to mention the need to include processes

448 Editorial / Computers in Human Behavior 17 (2001) 439–451

within this, including: team-based organization, cooperative relationships, shareddecision-making, initiative, diversity, autonomy, etc.The new paradigm needs to incorporate most of the knowledge generated by pre-

vious instructional design theories, but that knowledge needs to be restructured intosubstantially different configurations to meet the new needs of those whom we serve.CSCL has tended to focus much more attention on the system itself. But can a

computer tool support a socially based process of meaning appropriation? Compu-ters may serve as particularly useful tools for change, but such a change mustencompass the whole learning environment.Teams do not always function well. More often students collaborate poorly and

learn little more than when they work on their own. Not all collaborations are basedon a genuine opportunity for interdependence and grounding. Genuine collabora-tion needs genuine interdependence. Effective CSCL requires more than techno-logical design, what is needed is a systemic view of these changes and their context.One of the most interesting frameworks forwarded for understanding collabora-

tive knowledge construction within a systemic approach is that of cultural-historicalpsychology activity theory (CHAT). It is based on Vygotsky’s conception of theoryand human activity and has been used by Cole and Engestrom (1993) to analyze therole of tools in any mediated activity. In order to analyze the activity the followingvariables have to be taken into account:

The use of Cole and Engestrom’s model facilitates the development of the CSCLenvironment and research in this field.According to Salomon (1995), it is necessary to study the requisites of effective

CSCL and how we can evaluate the effects of this learning. It is argued that com-puters by themselves do very little. Critical analysis of collaborative learning andproblem-based learning environments needs to describe both the effects with and theeffects of problem-based and collaborative learning activities and environments.Effects with refer to learning that happens using a CSCL while effects of refer to

Editorial / Computers in Human Behavior 17 (2001) 439–451 449

learning that actually happens in CSCL contexts, that is, how group dynamicsdetermine what the collective learns through collaborative strategies, its transfereffects, the learner capability (learner as individual and as a group) to use newlyacquired knowledge in new situations outside the classroom, and thus to solve reallife problems.The study of CSCL is not easily handled with the research tools (particularly

experimental) that are currently available. There is a need to develop a more sys-temic approach that allows the influence of CSCL to be analyzed in the school (as awhole) considering its implications for the curriculum, teachers, students, tools, etc.In short, this field is only just beginning to develop and we feel it is necessary to

focus on:

1. The analysis of CSCL by identifying appropriate domains for collaboration.2. The examination of achievement as well as other outcomes (for instance,

impact on relationships among students) by incorporating notions of meaningnegotiation in social interaction, activity, cognition, level of group develop-ment, etc.

3. The identification of peers who collaborate effectively (in relation with theirability to use instructional technology), in a given domain, with or without agiven structure to the group processes, for a given learning strategy, anddepending on the characteristics of the peers and the role they assume.

4. The role of the technology promoting and facilitating intellectual conflictsamong students.

5. The assessment of how students use knowledge in group situations or an indi-vidual’s ability to share effectively with the group.

6. The implications of curricular changes.7. The way in which technology supports communication, communication modes

and an assessment of the impact of technological supports and the media inboth task performance and personal group processes.

8. The development of new ID models for promoting CSCL environments.

References

Baker, M., et al. (1999). The role of grounding in collaborative learning tasks. In P. Dillenbourg (Ed.),

Collaborative learning. Cognitive and computational approaches (pp. 31–64). Amsterdam: Pergamon.

Brown, J. S., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational

Research, 18, 32–42.

Cole, M., & Engestrom, Y. (1993). A cultural historical approach to distributed cognition. In G. Salomon

(Ed.), Distributed cognitions (pp. 1–47). Cambridge: Cambridge University Press.

Dede, C. J. (1990). The evolution of distance learning: technology-mediated interactive learning. Journal

of Research on Computing in Education, 22, 247–265.

Dillenbourg, P. (Ed.). (1999). Collaborative learning. Cognitive and computational approaches. Amsterdam:

Pergamon.

Dillenberg, P., et al. (1994). The evolution of research on collaborative learning. In: H. Spada & P.

Reimann (Eds.), Learning in Human Machines (pp. 189–211). Oxford: Elsevier.

450 Editorial / Computers in Human Behavior 17 (2001) 439–451

Doise, W., & Mugny, G. (1984). The social development of the intellect. Oxford: Pergamon.

Hansen, T., et al. (1999). Using telematics for collaborative knowledge construction. In P. Dillenbourg

(Ed.), Collaborative learning. Cognitive and computational approaches (pp. 169–196). Amsterdam:

Pergamon.

Joiner, R., et al. (1999). Comparing human–human and robot–robot interactions. In P. Dillenbourg (Ed.),

Collaborative learning. Cognitive and computational approaches (pp. 81–102). Amsterdam: Pergamon.

Jonassen, D., et al. (1999). Learning with technology. A constructivist perspective. London: Prentice-Hall.

Kiesler, S. (1997). Culture of the Internet. New Jersey: Lawrence Erlbaum Associates.

Koschmann, T. (1996). Paradigm shifts and instructional technology: an introduction. In T. Koschmann

(Ed.), CSCL: theory and practice of an emerging paradigm (pp. 1–24). New Jersey: Lawrence Erlbaum

Associates.

Koschmann, T., et al. (1996). Computer-supported problem-based learning: a principled approach to the

use of computers in collaborative learning. In T.Koschmann (Ed.), CSCL: theory and practice of an

emerging paradigm (pp. 83–124). New Jersey: Lawrence Erlbaum Associates.

Kumar, V. S. (1996). Computer-supported collaborative learning: issues for research. http://www.uib.no/

People/sinia/CSCL

Lubich, H.P. (1995). Towards a SCSW Framework for Scientific Co-operation in Europe. Berlin:

Springer-Verlag.

Pea, R., & Gomez, L. (1993). Distributed multimedia learning environments: the collaborative visualisa-

tion project. Available at: http://www.covis.nwu.edu.

Reigeluth, C. (Ed.). (1999). Instructional-design theories and models. a new paradigm of instructional theory.

New Jersey: Lawrence Erlbaum Associates.

Salomon, G. (1995). What does the design of effective CSCL require and how do we study its effects?

Available at: http://www.cica.indiana.edu/cscl95/outlook/62.

Scardamalia, M., & Bereiter, C. (1996). Computer supported for knowledge-building communities.

In T. Koschmann (Ed.), CSCL: theory and practice of an emerging paradigm. New Jersey: Lawrence

Erlbaum Associates.

Vygotsky, L. (1978). Mind in society: the development of higher psychological processes. Cambridge:

Harvard University Press.

Want (1994). CLARE: the approach and experimental findings. Available at: http://www.ics.hawaii.edu/

�csdl/techreports.

Begona GrosUniversity of Barcelona

Departament de Teoria i Historia de l’Educacio Passeig Vall d’Hebron171 08035 Barcelona

SpainE-mail address: [email protected]

Editorial / Computers in Human Behavior 17 (2001) 439–451 451