Design of collaborative learning environments

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<ul><li><p>Design of collaborative learning environments</p><p>J. Lowyck*, J. Poysa</p><p>Centre for Instructional Psychology and Technology (CIP &amp; T) University of Leuven, Vesaliusstraat 2,</p><p>B-3000 Leuven, Belgium</p><p>Abstract</p><p>Designing collaborative learning environments is dependent upon the descriptive knowl-edge base on learning and instruction. Firstly, the evolution in conceptions of design towards</p><p>collaborative learning is described, starting from designing as an intuitive behaviour. Sec-ondly, collaborative learning is described from dierent angles, like individuals-in-context,learner communities, including motivational factors and distributed cognition. It is evidenced</p><p>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</p><p>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.</p><p>Keywords: Instructional design; Collaborative learning; Learning community; Learning environments;</p><p>Co-design</p><p>1. Introduction</p><p>Designing refers to systematic choices and use of procedures, methods, prescrip-tions and devices in order to bring about eective, ecient and productive learning.The outcome of any design activity is a plan or scenario that denes 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 denitions undoubtedly will need adaptation (Hannan &amp; Land,1996), since increased environmental complexity and learners concomitant higher-order learning call for more sophisticated models of design. Designing is no more</p><p>Computers in Human Behavior 17 (2001) 507516</p><p>www.elsevier.com/locate/comphumbeh</p><p>0747-5632/01/$ - see front matter # 2001 Elsevier Science Ltd. All rights reserved.PI I : S0747-5632(01 )00017 -6</p><p>* Corresponding author. Tel.: +32-16-32-62-44; fax: +32-16-32-62-74.</p><p>E-mail addresses: joost.lowyck@ped.kuleuven.ac.be (J. Lowyck), johanna.poysa@ped.kuleuven.ac.</p><p>be (J. Poysa).</p></li><li><p>an intuitive endeavour with a lot of instability and variability in its knowledge-base,as reected in Montaignes 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 eect 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</p><p>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-dened 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 &amp; Goodson, 1980). The quality of instructionaldesign highly depends on the t 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 dene 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</p><p>research on cognitive processing (Lowyck &amp; 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, &amp; 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 scaolding 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</p><p>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 rened 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 ow of information and communica-tion actually available on the Internet. However, as Van Merrienboer (1999)</p><p>508 J. Lowyck, J. Poysa / Computers in Human Behavior 17 (2001) 507516</p></li><li><p>contends, there is no direct link between content-driven web-based instruction andthe quality of (constructive) learning. Indeed, there is no automatic learning eect tobe expected from a mere technology.</p><p>2. Learning apart together: collaborative learning</p><p>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 eective than solitary learning(Littleton &amp; Hakkinen, 1999). Other studies stress possible eects of dierent 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 eective collabora-tive activity instead of focusing on products of collaboration. For an overview ofdevelopments in the eld 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 dierent angles: (1)</p><p>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</p><p>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 individuals 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-</p><p>tionships, which in turn can aect social-aective characteristics, like studentsmotivation and self esteem (Nastasi &amp; Clements, 1991). Collaborative learninginuences student motivation in terms of increased students self-ecacy, learn-ing goal orientation, and intrinsic valuing of the learning task. A rst factor thataccounts for these eects 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</p><p>J. Lowyck, J. Poysa / Computers in Human Behavior 17 (2001) 507516 509</p></li><li><p>perceived task diculty. Collaborative groups have higher levels of self-ecacyregarding the achievement task because they are challenged by group members tocope with diculties 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 fullled, like problem solving and discussion of competing hypotheses. Afourth factor is the need to make ones 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 inuencing learning outcomes.(3) Recently, the notion of distributed cognition attracts a lot of research atten-</p><p>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 aected by contextual aordances, 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 signicance 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 dierent resources.(4) If learning is dened as a process, which takes place in a participation frame-</p><p>work, it is the community, or at least the participants in the learning context, wholearn under this denition (Lave &amp; Wenger, 1991). The development of expertise isnot only related to the nature of an individuals knowledge structures, but also tothat persons 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 dierent interaction tools oers ample opportunities for learners</p><p>to collaborate with all kinds of people: peers, tutors, experts, professionals, andparents. Intensive electronic networking can oer added value to the existing net-works and collaboration facilities, since schools can be electronically linked with thebroader community. The specic properties of a technology determine both the kindof information that can be exchanged and the easiness of the communication pro-cess, though its eectiveness 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). Eectiveness 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</p><p>follows. Learning largely depends on students activities, especially on self-directionamong students. Students are forced to make own ideas explicit and to critically</p><p>510 J. Lowyck, J. Poysa / Computers in Human Behavior 17 (2001) 507516</p></li><li><p>argue, while confrontation with a variety of ideas and arguments enhances deepreection and explicit account, due to an increased visibility of dierent ideas(Scardamalia &amp; Bereiter, 1993). Moreover, groups of students may see how theirunderstanding of a particular problem or aspect of reality changes. In other words,the ow of the learning process becomes more visible too.Technologies used in learning settings can be situated on various dimensions.</p><p>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 (humanhuman, humanmachine, humanmachinehuman),number of participants, time (in)dependency, immediacy and place (in) dependency(see Dillemans, Lowyck, Van der Perre, Claeys, &amp; Elen, 1998). This complexityundoubtedly will require new and powerful types of organisation, redenition of theactors roles, in-depth analysis of the tasks and management of the intensive ow ofinformation.</p><p>3. Implications of instructional design models on learners and designers</p><p>The evolution in both the nature and the function of instructional design chal-lenges the search for adequate interventions in order to enhance ecient and eec-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, &amp; 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.</p><p>3.1. Student centred design</p><p>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:...</p></li></ul>

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