Design of collaborative learning environments

Design of collaborative learning environments

J. Lowyck*, J. Poysa

Centre for Instructional Psychology and Technology (CIP & T) University of Leuven, Vesaliusstraat 2,

B-3000 Leuven, Belgium

Abstract

Designing collaborative learning environments is dependent upon the descriptive knowl-edge base on learning and instruction. Firstly, the evolution in conceptions of design towards

collaborative learning is described, starting from designing as an intuitive behaviour. Sec-ondly, collaborative learning is described from different angles, like individuals-in-context,learner communities, including motivational factors and distributed cognition. It is evidenced

that the adequate use of collaborative learning settings may contribute to the learning quality.Thirdly, the implications of collaborative theories on instructional design are outlined,centred around: student, knowledge, assessment and community. The interplay between these

perspectives is challenged in new models of (co) design. In the conclusion, an interactiveapproach of designing environments is advocated. # 2001 Elsevier Science Ltd. All rightsreserved.

Keywords: Instructional design; Collaborative learning; Learning community; Learning environments;

Co-design

1. Introduction

Designing refers to systematic choices and use of procedures, methods, prescrip-tions and devices in order to bring about effective, efficient and productive learning.The outcome of any design activity is a plan or scenario that defines the format,content and structure of the environment, the delivery systems and implementationstrategies (Reigeluth, 1983). With the rise of more open, electronic learning envi-ronments, these definitions undoubtedly will need adaptation (Hannafin & Land,1996), since increased environmental complexity and learners’ concomitant ‘higher-order’ learning call for more sophisticated models of design. Designing is no more

Computers in Human Behavior 17 (2001) 507–516

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* Corresponding author. Tel.: +32-16-32-62-44; fax: +32-16-32-62-74.

E-mail addresses: [email protected] (J. Lowyck), [email protected].

be (J. Poysa).

an intuitive endeavour with a lot of instability and variability in its knowledge-base,as reflected in Montaigne’s four centuries old adage: ‘du bon coeur, du bon sens etquelques petits trucs’ (a warm heart, common sense, and some handy tricks). In thisapproach, the ceiling effect is the designers’ individual competence in using recipesthat only work in contexts that are identical to those in which the recipes weredeveloped.Gradually, recipes were replaced by more systematic procedures developed within

a ‘systems approach’. It consists of task-analysis, problem-solving and testing by ateam of experts in complex domains. Instructional knowledge was documented andput into formal didactical models and procedures. Most models consist of pre-defined objectives (target position), description of trainee characteristics (actualposition), methods and content to bridge the gap between both positions, and con-trol of the outcomes (Andrews & Goodson, 1980). The quality of instructionaldesign highly depends on the fit between the design model and its ‘intelligent’ useby a designer. In this model external, programmed control, decomposition ofcomplexity, focus on content or subject matter, and ‘simple’ learning principlesare predominant. Designers entirely define and produce instruction, while teachersand learners are consumers of rather alienating design products at the end of thechain.Later on, a more cognitive position on design is taken, based on outcomes of

research on cognitive processing (Lowyck & Elen, 1993). Learning is an active, goal-oriented and self-regulated process during which the learner continuously constructsmeaning out of the environmental stimuli. The design process is aimed at support ofthe learners’ self-control (Merrill, Li, & Jones, 1990; Tennyson, 1992): learningenvironments aim now at enhancing cognitive and meta-cognitive processes. Sincelearning as a process is mainly the transition from a novice position towards that ofa (semi-) expert, instructional design is tailored to the idiosyncratic characteristicsof the learner in terms of both domain knowledge, (meta-) cognitive strategies andmotivation. Processes like ‘scaffolding’ and ‘fading’ that enhance the self-regulatingcapacity of learners become central in the design agenda. This longitudinal supportof learning puts designing on a developmental line and it creates links with curricu-lum design.While most theories on instructional design refer to the optimal adaptation of an

environment to the individual learner (see ‘intelligent tutoring systems’), the rise ofcollaborative learning theories results in team learning design (Collis, 1994).This refers to socio-constructivist theories of learning and design, where learners co-construct knowledge and co-design their learning environments. Design is now anon-linear, cyclical and iterative process. It starts from a rough prototype, which isgradually refined through feedback of users. In addition, the expansion of Internetas an encompassing technology supports this fundamental shift towards collabora-tion since learning takes place in a distributed knowledge environment (Dillenbourg,1996) in combination with information and communication technologies. Instruc-tional design is not restricted to the mere delivery and pacing of information,but learners are collaborating in a continuous flow of information and communica-tion actually available on the Internet. However, as Van Merrienboer (1999)

508 J. Lowyck, J. Poysa / Computers in Human Behavior 17 (2001) 507–516

contends, there is no direct link between content-driven web-based instruction andthe quality of (constructive) learning. Indeed, there is no automatic learning effect tobe expected from a mere technology.

2. Learning apart together: collaborative learning

Any instructional design rests upon a knowledge base in which outcomes ofresearch are represented in a given time and space dependent on the ‘Zeitgeist’. Therecent breakthrough of telecommunications in education (e-learning) as well asevolutions in socio-cognitive and socio-cultural learning theories directed interesttowards collaborative learning. It should be remembered that the state-of-the-art ofa certain knowledge domain is rapidly changing, and that therefore any meta-reviewshows severe limitations. The primary aim of research on collaborative learning wasto investigate whether this way of learning was more effective than solitary learning(Littleton & Hakkinen, 1999). Other studies stress possible effects of different vari-ables (e.g. task, medium, group structure) on learning and the intersection betweencollaborative (peer) learning in classrooms and learning with some types of compu-ter software. Recent research in collaborative learning analyses effective collabora-tive activity instead of focusing on products of collaboration. For an overview ofdevelopments in the field of collaborative learning (CL), computer-supported colla-borative learning (CSCL) and computer-supported co-operative work (CSCW), seeLehtinen, Hakkarainen, Lipponen, Rahikainen, and Muukkonen, 1998.In the next section, collaborative learning is described from different angles: (1)

the individual in a social context; (2) motivational aspects; (3) distributed cognition;and (4) learning community.(1) In the broad framework of a socio-cultural approach, human activities in

general are seen as socially mediated. Consequently, learning is embedded in a socialprocess of knowledge construction rather than being a solitary endeavour(Vygotsky, 1978). Indeed, individual knowledge results from internalisation pro-cesses of information from the surrounding culture or, in other words, internalcognitive behaviour gradually results from external overt behaviour. When an indi-vidual participates in a social system, both culture and communication tools, espe-cially language, shape the individual’s cognition as a source of learning anddevelopment. Knowledge emerges through the network of interactions and is dis-tributed among humans and tools that interact.(2) Learning under ‘positive contact conditions’ can facilitate interpersonal rela-

tionships, which in turn can affect social-affective characteristics, like student’smotivation and self esteem (Nastasi & Clements, 1991). Collaborative learninginfluences student motivation in terms of increased students’ self-efficacy, learn-ing goal orientation, and intrinsic valuing of the learning task. A first factor thataccounts for these effects is the positive motivational impact of peer support forlearning (Slavin, 1990). When peers recognise that success in learning depends uponthe success of their peers, they are more likely to provide emotional and tutorialsupport for learning. A second factor is the support of the group for facing the

J. Lowyck, J. Poysa / Computers in Human Behavior 17 (2001) 507–516 509

perceived task difficulty. Collaborative groups have higher levels of self-efficacyregarding the achievement task because they are challenged by group members tocope with difficulties and to persevere as well. A third factor is that group activitiesencourage students to display greater intrinsic value of the subject matter or the taskto be fulfilled, like problem solving and discussion of competing hypotheses. Afourth factor is the need to make one’s own knowledge explicit and hence disputableby other members of the group. Increased motivation will also increase time-on-task, one of the variables most clearly influencing learning outcomes.(3) Recently, the notion of distributed cognition attracts a lot of research atten-

tion. Knowledge and cognition do not reside in the head of each individual, butcognition is distributed over both individuals and their surrounds (Dillenbourg,1996). Any human activity is affected by contextual affordances, which include bothpeople and cultural artefacts. According to Pea (1993), the use of socio-culturallydeveloped cognitive tools, external representations and other artefacts can reducecognitive processing load and let solve more complex problems than would be pos-sible otherwise. The cognitive significance of distributed cognition is based on thefact that human beings’ cognitive resources, like time, memory, or computationalpower, are limited. (Hakkarainen, 2001). This ‘distributed’ knowledge becomespredominant in multimedia and telecommunication environments, in which mostinformation is distributed over different resources.(4) If learning is defined as a process, which takes place in a participation frame-

work, it is the community, or at least the participants in the learning context, wholearn under this definition (Lave & Wenger, 1991). The development of expertise isnot only related to the nature of an individual’s knowledge structures, but also tothat person’s access to relevant formal and informal cultural knowledge throughparticipating in an expert community or network. Until now, schools, homes, andworkplaces are isolated from each other and they mostly function because they aregeographically connected or linked by accident or circumstances, but seldom bycommon purpose and deliberate collaborative action (Center for Technology inLearning, 1994).E-learning with different interaction tools offers ample opportunities for learners

to collaborate with all kinds of people: peers, tutors, experts, professionals, andparents. Intensive electronic networking can offer added value to the existing net-works and collaboration facilities, since schools can be electronically linked with thebroader community. The specific properties of a technology determine both the kindof information that can be exchanged and the easiness of the communication pro-cess, though its effectiveness highly depends on how the properties are used.Numerous studies have been carried out that investigate the conditions for success-ful use (for a review: Wells, 1992). Effectiveness depends on the educational level ofstudents, the amount of time needed to participate in the interaction and the extentto which the environment is perceived to be interactive. Especially when collabora-tion at a distance is aimed at, pacing the work becomes highly important.Marttunen (1996) characterises computer-mediated communication (CMC) as

follows. Learning largely depends on students’ activities, especially on self-directionamong students. Students are forced to make own ideas explicit and to critically


argue, while confrontation with a variety of ideas and arguments enhances deepreflection and explicit account, due to an increased visibility of different ideas(Scardamalia & Bereiter, 1993). Moreover, groups of students may see how theirunderstanding of a particular problem or aspect of reality changes. In other words,the flow of the learning process becomes more visible too.Technologies used in learning settings can be situated on various dimensions.

Each dimension triggers a decision from the instructional designer, while the com-bination of decisions determines the outlook of the instructional support delivered.Design decisions should be made according to information modality, (non)linearity,type of interaction (human–human, human–machine, human–machine–human),number of participants, time (in)dependency, immediacy and place (in) dependency(see Dillemans, Lowyck, Van der Perre, Claeys, & Elen, 1998). This complexityundoubtedly will require new and powerful types of organisation, redefinition of theactors’ roles, in-depth analysis of the tasks and management of the intensive flow ofinformation.

3. Implications of instructional design models on learners and designers

The evolution in both the nature and the function of instructional design chal-lenges the search for adequate interventions in order to enhance efficient and effec-tive learning. This brings about the need for understanding the ‘conditions oflearning’ instructional agents are confronted with in order to build interactionsbetween learners and their environments. Taking an interaction perspective seems tobe the crux of any design of powerful learning environments which are studentcentred, knowledge centred, assessment centred and community centred (Bransford,Brown, & Cocking, 1999). Design is no more a linear, externally controlled endeav-our, but an adaptive and iterative process in which all agents play their role: learn-ers, peers, tutors, teachers, and parents.

3.1. Student centred design

Orientation in learning environment design focuses on several inputs from thelearner. Essential in the design of collaborative learning environments is the positionof the learner in his/her interaction with the environment. Not the designer, but thecomplex interaction between instructional and learning agents is the paramountobject of designing. Clarebout et al. (1998) point to the following issues: (1) the goalof designing is to support and not to withdraw cognitive processing of learners: thelearner has to be engaged in specific learning activities and processes, (2) learnerswill engage only if well adapted support is offered, and (3) support is not an objec-tive nor external measure, but it is mediated by many learners’ processes in terms ofperceptions, interpretations, and function attributions of the environmental char-acteristics (Elen & Lowyck, 1998). This means that learners need to have access tothe different functions embedded in a collaborative learning environment.Depending on their epistemological beliefs and instructional or learning experiences,


nominal stimuli in the environment will be (or not be) activated into effectivestimuli. Crucial is the balance between self-regulation by the learner and externalsupport.Research on learner control stems mainly from interactivity in multimedia settings

(Chung & Reigeluth, 1992). They differentiate learner control in (1) content control,(2) sequence control, (3) pace control, (4) display control, and (5) advisor strategy.Research outcomes show learner control to be a highly complex variable. It interactswith other variables such as learner characteristics (prior knowledge, ability, motiv-ation, aptitude, task persistence, age, training level, locus of control, and readiness),learner control variables (content, sequence, pace, display or strategy, and internalprocessing), and programme variables (advisement, adaptability, and learningmodel).In general, learner control may increase motivation to learn but not achievement,

can increase time spent in learning, and does not guarantee optimal decisions fromthe part of the learner. Considering the characteristics of learners, high achieverswho are knowledgeable about an area of study can benefit from a high degree oflearner control, while uninformed learners require structure, interaction, and feed-back to perform well. As to the relationship between learner control and programmevariables, learner control with advice seems superior to unstructured learner controlfor enhancing achievement and curiosity, promoting time-on-task, and stimulatingself-challenge. It still needs to be investigated, if and to what degree learner controlin a collaborative context may lead to similar conclusions, since the object of con-rol could differ seriously.

3.2. Knowledge centred design

Curricula are only partially fixed and result from a negotiation process betweenthe (group) of learner(s) and instructional agents. It may be expected that withgrowing maturity, increased self-regulating skills and more elaborated goal-directness of students, the negotiation process, will cover gradually more and moreaspects of the learning environment. Knowledge-centred environments focus on thekinds of information and learning activities that help students develop an under-standing of disciplines (Bransford et al., 1999). Knowledge-centred design has tosupport the learners to become meta-cognitive by expecting new information andasking for further clarification (sense making). It has been unclear until now howdistributed information environments can be turned into knowledge-centred designendeavours. It surely refers to the notion of ‘deep understanding’ in relationship to‘deep level’ structures of disciplines. Supporting students to grasp the essentials of agiven subject matter domain is a paramount task of design.

3.3. Assessment centred design

Assessment needs to reflect the basic philosophy of learning and instruction. Inorder to achieve a systemic design, authentic assessment is a major component ofthe learning environment, taking real-life problems into account (Glaser & Silver,


1994). Instructional agents at the micro-level have the responsibility to prepare andcoach students towards these external assessments. A distinction already estab-lished in some countries between the supporting instructional agent and the goalsetting and assessing function of instruction will most probably become the rulenot only at the secondary and tertiary education level but in all links of the edu-cational chain.Assessment is in line with the characteristics of constructive learning and learner’s

support. Students are responsible for their learning processes, including formativeevaluation of both processes and outcomes. Especially for the assessment of perfor-mances in authentic situations, self-evaluation as well as peer assessment are highlycomplex in terms of setting the right criteria, judgement of performances and crea-tion of meaningful feedback to control subsequent learning. Students need explicittraining in self- and peer-assessment skills in order to reach an acceptable level oflearning and performance (Sluijsmans, Dochy, & Moerkerke, 1999).

3.4. Community centred design

Technology can drastically alter the social structure of schools. Computer-networked environments give opportunities for socially mediated and distributedlearning and make it possible for students to interact and participate in morevarying ways than in traditional classroom settings. Rather than organising thesystem like a factory with groups of students arriving all at the same time andgetting the same kind of information to process, schools will be far more like aservice-company with tasks distributed over its different members. According toHakkarainen (2001), ‘There is a growing body of evidence that cognitive diversityand distribution of expertise promote knowledge advancement and cognitivegrowth. Distribution of cognitive efforts allows the community to be more flexibleand achieve better results than otherwise would be possible’ (p. 9). Methodologicaldifferences and even functions between education and training, or learning in andout school will gradually fade. Kearsly and Schneiderman (1998) refer to ‘engagedlearning’ that implies a group or team context, a project-based curriculum, and anoutside (authentic) focus.Opening schools implies turning learning environments into community environ-

ments. Finding ways to construct and support teacher communities and wider edu-cational professional communities, including parents, experts, principals, (Dillemanset al., 1998) needs investigating community building processes. Schwier (1999)states: ‘‘Emerging approaches to developing rich learning environments combinemultimedia, computer mediated communication, and a host of interactive strategiesto connect people in varied and robust ways. But traditional understandings oflearning environments and interaction usually stop short of the kind of engagementthat will allow learning communities to form’’ (p. 282).Dillenbourg (2000) proposes ‘the culture’ as a key answer. In recent theories,

learning is described as the process of becoming a member of the community andacquiring skills to communicate and act according to its socially negotiated forms(Lave & Wenger, 1991). Learning takes place in a participation framework and is


distributed among co-participants. The development of competencies is not onlyrelated to the nature of an individual’s knowledge structure but also to relevantformal and informal cultural knowledge in an expert community or network.

4. Conclusion

There is a clear evolution in the domain and processes of design. While in earlieryears educational methods and later on audio-visual media were targets of design,the rise of computers necessitated profound adaptation. As evidenced by the state-of-the-art in research, computers in education were designed to adapt instructionalobjectives, content and methods to the individual learner. Intelligent Tutoring Sys-tems (ITS) were the ultimate tools for individualisation, though their design, devel-opment and implementation were less successful than expected (De Corte,Verschaffel, & Lowyck, 1996). The ‘personal’ computer was shortening days.The interplay between theories of collaborative learning, telecommunication, and

community-based education paved the way for the design and organisation of morehybrid, collaborative learning environments. This mix of ambition and complexity,of external structure and self-regulation, of curriculum and co-construction ofknowledge necessitates brand new visions on and approaches of design.However, in line with the recent theories of collaborative learning, designers do

not focus directly on programmes, methods or tools, but rather on more complexrealities, like learning environments. Recently, this concept has begun opening andbroadening into the direction of learning ‘communities’ (Schwier, 1999) and ‘virtual’environments are considered as a new generation of computer-based educationalsystems (Dillenbourg, 2000). The challenge in the design of virtual environments isto explore, understand and integrate different new communication functions in apedagogically relevant way.Recent models of design reveal an increased complexity at the meso-level of

design. This means that design activities and procedures are focused on synergybetween learning theories, learning environment components and actors. Conse-quently, learning environments need to be designed as a package, not as a cluster ofisolated factors. The trend is toward integration of different tools. It might beexpected for instance that each student will have its own laptop that can be loggedto the network at school and in the home. This implies that the issue of technologyas such will gradually disappear, since technology will be embedded in the environ-ment as a natural and not as a dominant component. Not the technology itself, butits educational use becomes predominant as has been documented through the his-tory of educational technology. In the beginning of the art of printing or of theappearance of desk calculators, possible negative or positive effects of using thesetechnologies were questioned. After a period of adaptation the use of these tech-nologies rather than the technology itself became the important research topic. Thebasic idea will be that whatever we do or want to do in an educational setting, somekind of technology can be used. Technology becomes a mere tool for learning,embedded in sound methods and suitable content.


Along with the increasing complexity of learning environments or even learningcommunities, all actors play an important role. While in earlier design endeavoursthe teacher, instructional designer or instructional agent was a central actor, guidingthe activities of learners from the perspective of an external instance, nowadays theinterplay between all actors is crucial: teachers, designers, peers, teams. Design is atthe organisational level, managing the complexity of learning with the help of designstrategies in which the learner plays an increasingly important role. Participatorydesign reflects a systemic approach to designing (Wilson, 1999) while the boundariesbetween users and designers seem to blur. The former ‘end-users’ become co-designers of their learning environment, which calls for a systematic knowledgeabout learning and instruction. Instructional design changed interest from a linearand externally controlled design, development and implementation towards aniterative, self-regulated and systemic endeavour. To alter the field of ‘instructional’design into validated strategies for building a ‘learning community’ seems to be thechallenge of further research. The building blocks are already partially available andthey need to be integrated into a new systems design or, in other words, into a newarchitecture of learning and learning support.

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Design of collaborative learning environments