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A distributed collaborativescience learning laboratory onthe internetLaura R. Winer a , Martine Chomienne b & JesúsVázquez‐Abad c

a Assistant Professor at the Centre for UniversityTeaching and Learning , McGill University , 3700McTavish St., Montréal, Québec, H3A 1Y2 E-mail:b Project Officer at Centre collégial de formationà distance , P.O. Box 1000, Rosemont Station,Montréal, Québec, H1X 3M6 E-mail:c Department Didactique, Faculty of Education ,Associate Professor at the Université de Montréal ,Case Postal 6128, Succursale Centre‐ville,Montréal, Québec, H3C 3J7 E-mail:Published online: 24 Sep 2009.

To cite this article: Laura R. Winer , Martine Chomienne & Jesús Vázquez‐Abad(2000) A distributed collaborative science learning laboratory on theinternet, American Journal of Distance Education, 14:1, 47-62, DOI:10.1080/08923640009527044

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A Distributed Collaborative ScienceLearning Laboratory on the Internet

Laura R. Winer, Martine Chomienne, andJesús Vázquez-Abad

Abstract

A Distributed Collaborative Science Learning Laboratory (DCSLL)was designed, prototyped, and pilot-tested as the "Electrical CircuitSimulator." This laboratory was part of a module on electricitywithin an introductory distance course for postsecondary studentson the scientific method. The concept of DCSLL emerged fromwork in distance education and new technologies, cooperative/col-laborative learning, and science education. Instructional designprinciples derived from these areas are presented, and their imple-mentation in the DCSLL is described, followed by results from thepilot test. Analysis of the results led to the articulation of sixinstructional design guidelines, identified as being key to the devel-opment of such learning environments.

Introduction

One area that has proved particularly resistant to implementation in a dis-tance education context is the laboratory component of science courses.In order to offer distance students a full range of courses, however, newways must be found to provide this aspect of science courses. A growinginterest in collaborative work within the distance education communityfocuses on reducing high attrition rates, finding ways to provide cognitiveand metacognitive support, as well as addressing individual differences,both cognitive and affective. In exploring the potential of Internet-basedcollaborative learning, we were able to articulate preliminary principlesbased on existing work and use them as guides for the design of a proto-type Distributed Collaborative Science Learning Laboratory (DCSLL).The prototype was pilot-tested, and the results obtained were used toelaborate and clarify the design principles.

Origins of a DCSLL

The concept of a DCSLL emerged from work in distance education,cooperative/collaborative learning, and science education.

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Distance Education and New Technologies. The defining characteristicof distance education is the distribution of students across time and space,from the instructor or tutor and, often, from each other. The learners areusually adults who normally work part- or full-time while taking courses.Bourdeau and Bates (1997) provide guidelines for instructional designspecific to a distance education context. The challenges facing theinstructional designer include (1) responding to the high attrition ratecaused by student isolation, lack of a sense of belonging, and problemsin sustaining motivation and commitment; (2) adapting to individualcognitive and affective profiles; and (3) providing adequate cognitiveand metacognitive support to the learners. New technologies and collab-orative approaches offer the promise of alternative means and methodsthat may help meet these challenges.

Dede (1996) discusses the implications of new media for distanceeducation. He identified three new forms of distributed learning: collec-tive knowledge webs (complementing traditional information sources),virtual communities (complementing face-to-face interaction), andimmersive experiences in shared synthetic environments (extendinglearning-by-doing in real-world settings). These three forms of distributedlearning are presented as providing extensions of learning-by-doing in acollaborative mode. However, we feel that collective knowledge websand virtual communities can be more accurately described as "collabora-tion in discourse" and that immersive experiences in shared syntheticenvironments enter the realm of "collaboration in action." By collabora-tion in discourse, we refer to learning situations in which sharing isbased on conversation, whereas collaboration in action refers to learnersacting together to complete tasks.

The introduction of new technologies also has implications for thenature of interactions. Hillman, Willis, and Gunawardena (1994) add therelationship between the learner and the technological interface to thestandard learner-content, learner-instructor, and learner-learner interac-tions. This learner-interface interaction is especially significant whenworking within mediated communication. While many think this ismerely a novice's problem that will expire on its own as the populationbecomes more technologically sophisticated, Hillman et al. point out thateven experienced drivers may have problems operating the windshieldwipers on rented cars. The analogy is worthwhile because each techno-logical environment has its own idiosyncrasies that must be learned, nomatter how "standardized" they are.

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Many authors, notably Anderson and Garrison (1995), Dede (1996),and Hillman et al. (1994), have identified the need for appropriateinstructional design research that exploits the potential of new technolo-gies as the key to successful future developments in distance education.

With computer technologies creating opportunities for increased col-laboration, distance education is moving from an individual, soloendeavor to one that links the learner to others and involves him or herin social exchange and communication with both the tutor and otherlearners. For example, Thach and Murphy (1994) present a continuum ofinteractions that moves from collaboration by the designers, to student-to-student, class-to-class, and finally institution-to-institution. Along thesame lines, Anderson and Garrison (1995) present the concept of a com-munity of learners in which the emphasis is on developing, extracting,and refining existing knowledge from the group, rather than following ateacher transmission of knowledge model. This group interdependencedoes entail a loss of some of the flexibility and independence that dis-tance education learners have typically enjoyed. However, Anderson andGarrison found that most of the students enrolled in courses requiringgroup interactions found the trade-off between reduced independenceand increased interactivity one that was worthwhile. Similarly, Garrison(1993) highlights the potential for new technologies to sustain two-waycommunication and, therefore, facilitate the development of learningenvironments that move away from the traditional (distance education)behaviorist orientation to learning.

Cooperative/Collaborative Learning. According to the OxfordEnglish Dictionary, the terms "cooperative" and "collaborative" sharethe same meaning and have equivalent etymologies. Nevertheless, onefinds the words used both interchangeably and in opposition to eachother, and the distinctions made in some fields contradict those made inothers. We have chosen the term "collaborative" for our work based onSalomon's (1992) view; however, in the following discussion, werespect and use the particular author's choice of vocabulary.

The essential elements of traditional collaborative learning are face-to-face interaction, positive interdependence, individual accountability,cooperative social skills, and group processing (Johnson and Johnson1976). (Obviously, the requirement for face-to-face interaction wouldhave to be replaced if we are to create collaborative learning activities ina distance education environment.) Slavin (1983) concluded that theeffects of cooperative learning are primarily motivational, since working

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together toward a group goal creates peer support for individual learn-ing, and that, in turn, increases individual motivation both to achieve andto help others. Abrami et al. (1995) also found that "there is little doubtthat cooperative learning produces superior results when the objective isthe promotion of positive attitudes and feelings toward learning, class-mates, and self (196). As anyone familiar with distance educationknows, motivation is key. Therefore, the potential for cooperative learn-ing to increase a student's motivation by adding to their sense ofbelonging and commitment makes it worth investigating. Although dis-tance learners are already motivated enough to initiate their own learningactivities, their high attrition rates could be decreased by improving thequality and quantity of interactions.

Distribution and Collaborative Learning. The concept of distributionrefers to different kinds of distribution: across time, across space, andacross individuals. In distance learning, learners are distributed geo-graphically and temporally. To complicate this situation further, theresources needed for a given learning activity may also be at a distancefrom the student and/or the teacher. In addition to overcoming the tradi-tional pedagogical challenges, distribution introduces additionalchallenges to supporting authentic collaborative work; it increases thecomplexity of coordination and communication and also introduceslogistical hurdles such as working together on tasks, exchanging docu-ments, and arranging meetings.

Collaborative learning may also be seen as different individual cogni-tive systems working together toward a common goal. For example, in acollaborative approach, each student working on a laboratory activitybrings his or her own cognition to the activity. They not only bring theirexisting knowledge, belief systems, and cognitive abilities, but they alsobring their own way of building new knowledge. Team cognition is thusdistributed among its members, and team learning is, to some extent,dependent on the characteristics of this distribution. When different tasksare assigned to each member of a team, the interaction between eachindividual's cognition and the specific task assigned will influence thegroup outcome. The concept of distributed cognition has implications,therefore, not only for the way in which a group will work, but also forwhat the results of that work will be. Thus, depending on the composi-tion of the team, the team may choose to work by dividing roles and/ortasks according to the competencies that particular individuals bring tothe team. They should implement a strategy that either exploits an indi-vidual's strengths or strengthens their weaknesses.

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The Science Learning Laboratory. The science laboratory is seen ascentral to science teaching by those who believe that it promotes positiveattitudes toward science, scientific inquiry, conceptual development, andtechnical skills (Collette and Chiappetta 1994). Constructivist views ofscience learning consider the laboratory to be the primary instructionalenvironment for involving students in scientific inquiry. However, giventhe widespread use and importance of laboratory instruction in scienceeducation, it is surprising how little we know about the effects of labwork on learning (Gallagher 1987; Lazarowitz and Tamir 1994).

The laboratory is an environment that not only characterizes (in popu-lar culture) science as a profession, but also sets it apart from most otherdisciplines, such as the humanities and social sciences (White 1988). Asa learning environment and an instructional strategy, the science labora-tory includes practical work within planned learning experiences thattake place in a purposely assigned environment (Lazarowitz and Tamir1994). While a physical space or an assigned, structured sequence oftasks often defines science laboratories, the science learning lab does notnecessarily require either of these elements. The important aspect of ascience learning lab is the controlled nature of both the actions and theenvironment that ultimately permits students to generalize beyond thespecific instance under study. As such, a "laboratory" may be conductedin a traditional, controlled environment or out in the field with a teacher-provided protocol or a student-generated one.

For those who see the laboratory as practical work that leads to con-cept formation and the formulation of theories, each experiment shouldbegin with an existing theory and knowledge base and the identificationof a problem that then leads to a hypothesis, a plan, and finally, the exe-cution of an experiment (Arons 1993; Lazarowitz and Tamir 1994).Accordingly, science laboratories should provide concrete experiences,ways to help students confront their misconceptions, opportunities fordeveloping process and technical skills, and opportunities to constructknowledge. Even though these objectives are aimed at the individual,concerns related to the role of social interaction in knowledge construc-tion and motivation make it worthwhile to look at what cooperativelearning can contribute to instructional models of laboratories.

Cooperative Learning in Science. A large-scale survey of studentresults in introductory physics courses found that the use of interactiveengagement methods in the classroom can significantly improve courseeffectiveness (Hake 1998). In chemistry, Nurrenbern (1995) states that

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tasks in a cooperative learning activity must require students to makeindependent contributions toward task completion, as well as requiringsome group decision making on the process itself. These are presumablythe main characteristics to consider when designing an activity.

While noting the scarcity of research on cooperative science laboratorylearning, Lazarowitz and Tamir (1994) report on studies that show coop-erative work to be superior to competitive and individual work in termsof cognitive achievement but inferior in terms of process skills. However,when learner abilities were taken into account, no conclusive statementscould be generated from the results of the different studies. Not surpris-ingly, cooperative learning is superior to competitive approaches whenthere are cooperative tasks to be carried out, while competitive groupsare superior for tasks emphasizing individual achievement.

In science education, the concept of cooperative learning is oftenviewed as being essentially synonymous with group learning. Theadvantages of cooperative learning are seen in its elimination (or at leastreduction) of competitiveness between students and/or of student isola-tion by including team-building and team-learning activities (Colletteand Chiappetta 1994; Jones 1989). This makes it an approach that isappropriate and effective for teaching and learning science (Hassard1992).

The Challenge: Setting up a Distributed Collaborative ScienceLearning Laboratory through the Internet

Goal. Our project focused on exploring new applications of informa-tion and communication technologies in distance science learning. Ouroverall goal was to create principles for designing technological andteaching environments that would support distance learners in the col-laborative learning of scientific concepts. Our educational partner wasthe CCFD (Centre collegial de formation a distance/Center for CollegeDistance Education), based in Montreal. The center's mandate is to pro-vide college-level (postsecondary, pre-university) distance teaching forthe province of Quebec. In conjunction with the RECTO (Reseau dechercheurs pour la teleformation operationnalisee/Network ofResearchers for Operational Teleteaching) project and funded by theFonds de l'autoroute de l'information (Information Highway Fund), thecenter has created a new course designed to take advantage of the infor-mation highway (Potvin, Chomienne, and Boutin 1996).

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The CCFD chose a new introductory course on the scientific methodfor the project. The course objective was to familiarize non-sciencemajors with the fundamentals of the scientific method so that they wouldbe able to apply it in simple problem-solving contexts, specifically thoseinvolving concrete physical phenomena. A key element in the course'slearning activities was the distribution (in both time and space) of thevirtual laboratory experiences. Because this was a new course, it providedan opportunity to incorporate information and communication technolo-gies as an integral part of the design. The course material was designed fora hypermedia Web site and required both synchronous and asynchronousinter- and intra-team communication using tools such as electronic mail,chat rooms, teleconferences, and computer audioconferences.

The course designers chose physics as the content area from which toteach the scientific method, and they developed a modular course with acommon starting point—a chapter on the history of the scientificmethod. Students then completed three modules consisting of mechan-ics, optics and sound waves, and electricity. The course materialscontained embedded exercises and hypertext links. The module on elec-tricity was chosen to be the testbed for the design of a prototype DCSLL.

Description of the Prototype

In designing the electricity laboratory, we created three experimentsfor the learners to conduct. These experiments were not designed fordeductive verification of laws and principles. To produce individual syn-theses, some of the activities within the DCSLL component of the coursecovered concepts through concrete manipulation; these then served as abasis for negotiating a collective synthesis. Other activities reviewed aconcept so that the learners could gain a better understanding of it onboth a qualitative and quantitative level. Still others used the conceptsdiscussed to gain new knowledge through teamwork. The specificinstances where collaboration came into play are identified in Figure 1.

In the first experiment, experimentation was conducted with real arti-facts, and measurements were taken using real instruments. In the othertwo, experimentation was carried out by simulation, and the measure-ments were computerized. Collaboration began only during theinterpretation/conclusion phases of the first two experiments. The thirdexperiment required the learners to plan their experimentation from thebeginning, and then collaborate during both the analysis and interpreta-tion/conclusion phases.

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ExperimentationSimulated

No. 2 & No. 3

Measurement

1

RealInstruments

\ r

ComputerizedProcess

Analysis IndividualNo.l

Interpretation/Conclusion

Team Team Team

Figure 1. Collaboration in the Electricity Laboratory Experiments

Design Principles. The principles applied in the design of the DCSLLcame from four contributing areas: instructional design for distance edu-cation, science learning laboratories, information and communicationstechnology, and collaborative learning. The design principles are pre-sented in a tabular format in the results section.

The Three Electrical Circuit Simulator Experiments. Experiment 1consisted of a qualitative exploration of the behavior of simple circuitsand involved concrete manipulation of common electrical equipment—light bulbs, batteries, electrical wiring, etc. The experiment was carriedout with real (as opposed to simulated) objects, and measurements weretaken using real instruments. The learners analyzed their data individually,while the interpretation of results and the development of conclusionswere conducted as a team.

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Experiment 2 examined the relationship between current, potential,and resistance in a simple electric circuit (Ohm's law). Experimentationinvolved a number of activities using a simulator. The data measurementphase was done automatically by the computer. The learners analyzedtheir results individually, and again, both the interpretation and conclu-sions were the result of a team effort.

Experiment 3 studied the distribution of current and potential in a cir-cuit (Kirchhoff's laws). Experimentation consisted of a number ofactivities using a simulator. The team planned the experiment before col-lecting the data. Although data measurement was automated, the dataanalysis, interpretation, and conclusion phases were all conducted as ateam.

Pilot-Testing the Science Learning Laboratory

The prototype DCSLL on basic concepts of electricity was pilot-testedat the CCFD in July 1997 using a team of three participants who wererepresentative of the target population. Results indicate that distance col-laboration in the context of a distributed science learning laboratory ispossible. During the pilot test, the participants showed their commitmentand interdependency in the learning process.

Method. Data were gathered using the following means: group inter-views with the three participants (both before and after the pilot project),students' assignments, and participant observation by the three researchteam members. Interview questions examined content and also probedthe participants' ideas about science labs, collaborative work, and com-puter-based learning activities. Observations focused on the interactionsas well as on the technical and conceptual areas that posed difficulties.

Logistics and Computer Platform. To simulate distance, the three par-ticipants worked in different rooms, each equipped with a workstationand telephone that enabled telephone conferencing.1 The workstationsthemselves were PCs with Windows 95 and Internet access. Using abrowser (either Explorer® or Netscape®), the participants accessed thelaboratory site with a user name and password. By clicking on a desktopshortcut, they loaded NetMeeting™, through which they could share awhiteboard, use the annotation tools (the hand, the highlighter, etc.), typein comments and information, and use the screen capture tool. Whennecessary, the research team provided on-the-spot technical support.

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Results

The pilot test provided feedback on the success and appropriatenessof the different design principles used to create the DCSLL. Each set ofprinciples is presented below with the principle articulated in the leftcolumn and the results observed during the pilot test in the right column.Of course, since these results are based on a very limited number of par-ticipants, the significance of the results should be viewed withcircumspection. The results of the pilot test were used to define newtechnical specifications for the revised version of the laboratory that hasbeen implemented in the CCFD course.

Table 1. Distance Education

Prototype Design Principles Results

1. Begin with an individual task, and thenprovide a personal workspace accessible atall times to respect different cognitive andaffective profiles.

2. Develop readable, comprehensible learn-ing materials that are easily followed.

This proved important. Participants madefrequent recourse to the personal workspaceto work at their own speed and to try thingsout for themselves.

The collaborative aspects made this bothmore important and more difficult becauseshared, not just individual, understandingwas a factor.

3. Develop a variety of learning activities. This proved entirely feasible.

4. Anticipate errors and prevent them whenappropriate.

Conceptual errors were anticipated duringthe design phase. Nonproductive technicalerrors were prevented. Productive errors,which we did not seek to prevent, did notoccur with this group.

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Table 2. The Science Learning LaboratoryPrototype Design Principles Results

1. Practical exercises within planned learn-ing experiments carried out in anappropriate environment.

This proved feasible. Collaborative workraised the participants' awareness thatscientists generally work as a team.

2. Inductive approach: discovery of laws The approach based on cognitive conflictbased on a prediction followed by experi- did not suit all participants; this has implica-mentation and comparison of the prediction tions for the tutor. Participants were notwith the experimental results in order to foster always comfortable making predictions andcognitive conflict.

3. Allow learners to design and conducttheir own experiments.

4. Progression from qualitative data toquantitative data to graphic representationto formal representation by mathematicalequations.

had to be convinced of the importance oftheir "lay" predictions.

The participants specifically asked to gofurther (i.e., designing their own circuits onthe computer).

The progression was effective, and the par-ticipants established their own mathematicalequations. They grasped the relationshipbetween the various representation systems.

5. Free the learners from nonauthentic ornonproductive work by using the computerin "emancipatory" mode. The learnershould remain an active participant; do notautomate too many of the tasks.

The procedures were not too difficult, so theparticipants had no trouble following thesteps.

Table 3. Information and Communication TechnologiesPrototype Design Principles Results

1. Written, audio, and visual communica-tion.

2. Common work and visualization screenshared by all participants.

Both audio communication by telephoneand shared visualization of individualresults enhanced the learning experience.

Having a shared work and visualizationscreen proved essential.

3. Preservation of autonomy and balance by Care must be taken in sharing applications,carefully limiting application sharing. such as the simulator. This is related to the

importance of a personal workspace; ashared simulator would have encroached onthis.

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Table 4. Collaborative LearningPrototype Design Principles Results

1. Positive interdependency without face- The learning environment enabled theto-face interaction. development of positive interdependency;

the audio communication successfullyreplaced face-to-face interaction.

2. Develop competencies (related to content Individuals became accountable for theirand the collaborative method) and individual own learning and that of the team as aaccountability. whole.

3. Include sharing of the analysis and data The participants arrived at the plannedinterpretation. learning outcomes.

Guidelines for the Design of a DCSLL

The results of the pilot test from the DCSLL on electricity enabled usto make a number of recommendations to instructional designers wish-ing to develop distance science learning laboratories. A DCSLL, such asthe one we envisaged and realized, is a complex learning environmentintegrating contributions from different fields. The instructional designrecommendations particular to this environment reflect the integration ofthe different contributing areas and address the complexity and chal-lenges of their design. Some of these recommendations are equallyapplicable to learning environments that involve only some of the con-tributing areas, but in an environment as complex as a DCSLL, each ofthe following recommendations are essential.

1. Provide both a separate workspace for the individual and a com-mon space for the team. Even in collaborative learning situationswhere the team is the functional unit, the individual learner shouldretain his or her autonomy. An individual workspace permits eachlearner to proceed at his or her own pace, to confront commonmisconceptions individually and not just be "pulled along with thecrowd," and to confront idiosyncratic interpretations or concep-tions about the concepts under study. The common space isnecessary to allow the team to pool their findings and work togetherto accomplish the learning tasks.

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2. Conduct formative evaluations of the learning materials withgroups of learners to ensure that the instructions and vocabulary arenot only internally consistent, but also subject to the same interpre-tation.

3. Offer a variety of learning activities. When feasible and appropri-ate, hands-on activities should be included to provide students withthe opportunity to engage in concrete manipulation. Learnersshould be able to initiate experiments in addition to following pre-determined protocols. Learning activities should progress fromactive to symbolic, and data generated should progress from quali-tative to quantitative.

4. Error analysis must distinguish between productive and nonproduc-tive errors, so as to permit the former and prevent the latter.

5. Technology should enhance the learning experience by providingexperimental opportunities that would be otherwise unavailable, byfacilitating data manipulation and analysis, and by supporting com-munication (written, video, and audio) among team members andwith the tutor.

6. Each learner's contribution must be necessary but not sufficient forboth the individual and the group to succeed in the learning activity.No one student should be able to complete the learning activitiesindividually.

Conclusion

The test results of the prototype's pilot project, the "Electrical CircuitSimulator," demonstrated the feasibility of a Distributed CollaborativeScience Learning Laboratory. However, due to the somewhat artificialsetting of the pilot project, certain questions remain unanswered. Forexample, do the increased sources of feedback in a peer collaborationcontext improve the quality and nature of the interaction between stu-dents and tutors? Should opportunities for constructive technical errorsbe created? What are the implications for the tutor's role in an approachbased on cognitive conflict? Under what conditions and in what form isasynchronous communication appropriate? What are the various rolesplayed by the learners in a DCSLL? Many of these issues may beaddressed in a real delivery of this Internet-based course to clients of theCCFD.

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In conclusion, the Distributed Collaborative Science Learning Labo-ratory appears to be a practical way to provide authentic lab experiencesand reduce student isolation while respecting the fundamental con-straints of distance education. Careful attention must be paid to designand management issues raised by this new instructional approach, andthe increased technical complexity of the learning environment must betaken into account when designing the instructional activities. Overall, itseems that the DCSLL approach is a way to support learning within adistance context that allows distance education students to engage in col-laboration in action as well as collaboration in discourse.

Notes

1. Technological limitations prevent multipoint, Internet-based audio conferencing fromoffering satisfactory results. Therefore, in order to test the design principles withoutbeing limited by current technology, conventional telephone conferencing was substi-tuted.

Author's Note: This article reports on work undertaken as part of a project in the Tele-Learning Network of Centres of Excellence Research Program of the Canadiangovernment (http://www.telelearn.ca). Additional funding was received from theInformation Highway Fund (Fonds de l'autoroute de 1'information) of Quebec andthe Canadian Office of Learning Technologies. The authors would like to acknowl-edge Dr. Jacqueline Bourdeau of the Universite du Quebec a Chicoutimi for hersupport as project leader. The lead author was a Research Associate at the Faculty ofEducation of Universite de Montreal while the work reported was carried out.

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