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Collaborative learning in an educational roboticsenvironment

Brigitte Denis*, Sylviane Hubert

Service de Technologie de l’Education, Centre de Recherche sur l’Instrumentation en Formation

et Apprentissage, Universite de Liege au Sart-Tilman,

Bat. B32, 4000 Liege, Belgium

Abstract

Learning to collaborate is an important educational goal. The concept of collaborative

learning is differently defined by several authors. Problem solving and problem-based learningare also important in our educational framework. We shall situate and clarify here theinstructional design concepts used in an educational setting based on a ‘‘collaborative and

problem based learning environment’’ applied to educational robotics. Educational roboticsactivities are developed at several school levels (primary, secondary) and in adults’ trainingcontexts. The instructional design of such learning activities is based on a constructivist

approach of learning. Their educational objectives are varied. In our approach, the goal is notonly that the learners acquire specific skills (e.g. knowledge on electricity, electronics, robot-ics. . .), but also and mainly demultiplicative, strategic and dynamic skills. The methodologyfocuses on collaboration to design and develop common projects and on problem solving

skills development. The pupils work in small groups (2–4). In the reported research, somelearners’ interactions have been observed during the activity in a primary school with anobservation grid. The analysis of the verbalisations between the learners and their actions on

the computers, and the robotics materials coming from those observations offer the opportu-nity to study the way the learners are collaborating. # 2001 Elsevier Science Ltd. All rightsreserved.

Keywords: Constructivism; Collaboration; Educational robotics; Evaluation; Educational technology;

Problem based learning

Computers in Human Behavior 17 (2001) 465–480

www.elsevier.com/locate/comphumbeh

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

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* Corresponding author. Tel.: +32-4-366-20-72; fax: +32-4-366-29-53.

E-mail address: [email protected] (B. Denis).

1. Introduction

This paper focuses on an activity based on collaborative and problem-basedlearning called ‘‘educational robotics’’. Its instructional design implies the choice ofsome teaching and learning methods, of classroom management parameters, of toolsto be used (e.g. computers, robotics material, reference guides, etc.) to reach deter-mined objectives. The regulation of such activity needs the use of evaluation tools.Here they consist in observation grids that permit coding of social interactionsbetween peers and actions on the didactic materials.

2. Context: the educational robotics framework

Educational robotics (ER) consists in building and programming small robots andconducting them with the help of computer programs that have to be built by thelearners themselves. Different approaches are observed in educational roboticsapplications (Denis, 1993a; Denis & Baron, 1993). They aim to develop somelearners’ competencies such as problem solving strategies, the formalisation ofthought, the socialisation as well as the acquisition of various concepts. In fouremerging trends from the ER use several differences related to their fields of applicationcan be observed (Denis & Baron, 1993):

1. a technocentric approach aimed at the development of technical situationsoften close to the industrial world (Delannoy, 1993; Nicoud, 1993; Tauriac,1993),

2. an approach based on the creation and exploration of microworlds based on thelearner’s project (Denis, 1993; Leroux, 1997; Limbos, 1993; Morato, 1993;Napierala et al., 1993; Sougne, 1993; Vivet, 1993; Papert, 1984),

3. an approach based on the theory of the cognitive spectacles or computer assistedexperimentation, connected to scientific contents (Nonnon, 1986; Cervera &Nonnon, 1993; Girouard & Nonnon, 1997; Hudon & Nonnon, 1993;Macherez, 1993; Marchand, 1993; Nonnon, 1993; Rellier & Sourdillat, 1993),

4. a programming or algorithmic approach (Duchateau, 1993).

Among those approaches, the specific objectives and the methodologies are var-ied, even if the epistemological bases of the activities are all based on an interac-tionist constructivism. The interdisciplinary aspect of this activity has also beenemphasised. In fact, it is difficult to classify educational robotics within one givendiscipline since projects often vary, switching from one kind of approach to anotherone.In addition, the target public is also varied, since ER addresses learners from ele-

mentary school to adult’s training.The approach we have adopted in our study is the second one: exploration and

creation of microworlds. Here, the learners’ task is complex and based on a mean-ingful project shared by the two peers involved in it. This groupwork should con-tribute to the learners’ motivation throughout the learning activity.

466 B. Denis, S. Hubert / Computers in Human Behavior 17 (2001) 465–480

3. Learning objectives and learning/teaching paradigms

Two models, a four level architecture of competencies and the six learning/teachingparadigms help to analyse and characterise the educational robotics activities (Fig. 1).

3.1. The architecture of competencies

Regardless of the approaches (out of the four options), the ER learning objectivesmentioned earlier can also be categorised referring to Leclercq’s (1987) model of thearchitecture of competencies. He suggested that four types of competencies shouldbe considered:

Levels of architecture of competencies E.R. objectivesDynamic

The dynamic competencies are related to (Personal) project.MOTIVATION, i.e. the pleasure a personexperiences in doing things, in learningspecific, demultiplicative or strategiccompetencies. This level is the most vulnerable:it can be easily affected. It is also the most‘‘penetrating’’, i.e. the motor that drives the restwhen facing a new domain which the learnerhas to enter. Those competencies correspond tothe learner’s initiative, will, pleasure anddispleasure, perseverance, rigor, . . .includingone’s own image as a person being able andmotivated to learn.

Meaningful activity.

StrategicThe strategic competencies are concernedwith METACOGNITION, i.e. knowingoneself (as a learner, as an actor, etc.), one’sweaknesses and one’s talents, and developingstrategies to adapt to complex situations (for

Problem solving andformalisation of thought:structuring the problem,definition and test ofhypotheses, conclusions, . . .

Fig. 1. Architecture of competencies (Leclercq, 1987).

B. Denis, S. Hubert / Computers in Human Behavior 17 (2001) 465–480 467

instance to choose which demultiplicativecompetency to use for learning in givencircumstances). They concern planning (e.g.how much time will it take me to master agiven subject, to do a specific work), problemsolving (e.g. analysis and structuring the problem,decision making, . . .), communication andcooperation (how much and when do I needothers? in which respect?) and self estimation ofknowledge (to know one’s degree of expertise ina domain: what do I know? what do I not know?).

Socialisation: collaboration,socio-cognitive conflicts, . . .

DemultiplicativeThe demultiplicative competencies (LEARNINGTOOLS) enable the learner to get information byhim/herself and acquire more specificcompetencies: reading, listening, notes taking,communicating, interviewing, using the computerto consult a database or to produce texts,referring to guides, etc.

Reading, listening, notestaking, consultation ofreference guides, usingthe computer.

SpecificThe specific competencies (ELEMENTS OFCOGNITION skills) deal with specific contents(e.g. geography, history, physics, vocabulary ofa language, . . .) and are hardly transferable.These specific competencies are infinite and ahuman being can (and has to) know only someof them.

Electronics components,types of electric circuits,programming instructions,production procedures,syntax of a givencomputer language, . . .

This four levels architecture of competencies model offers a useful conceptualframework which allows the learner to address important questions related to theobjectives and the methodology to choose: do we want the learners just to acquirespecific competencies or should they acquire strategic level skills?, etc.Several relationships between competencies and educational robotics approaches

have been described in Denis and Hubert (1999). We shall hereafter just focus onstrategic ones since they deal with abilities such as collaborating and interacting witheach other and to some aspects of problem solving.

3.2. Six learning/teaching paradigms

Like other educational situations, educational robotics activities can be describedand analysed referring to the ‘‘six teaching and learning paradigms’’ model (Denis &Leclercq, 1994; Leclercq & Denis, 1998; Fig. 2). These paradigms imply very differ-ent kinds of interactions between trainers and learners and the proportion ofthe learner’s and trainer’s initiatives mostly depends on the chosen paradigms.


Moreover, according to the paradigm, the learner develops some particular compe-tencies (e.g. the paradigm of ‘‘creation’’ will develop more competencies such asdemultiplicative, strategic and dynamic ones than specific ones).Whatever the considered paradigm, we find social interactions between peers and

between the trainer and the learners. Those interactions intervene as ‘‘learning cat-alysts’’. Nevertheless, we may consider that actual collaborative learning situationswill mostly appear in the three paradigms that allows more learner’s self-initiative(creation, experimentation, exploration) than the others.For us, our approach, which is based on ‘‘microworlds’’, will essentially consider

creation, that will also lead the learner to develop behaviours linked to exploration andexperimentation, but always referring to learners’ personal projects. Nevertheless, thatdoes not imply that a trainer will always base the activity only on creation. He/she candecide that the learner will have the initiative to define and realise a project (build therobots and program them), but at some moments provide a synthesis about the newnotions encountered and enrich them with new concepts (transmission/reception).

Learning/teaching paradigms ER objectivesCreation Two facets of creation of an educational robotics

activity are pointed here. One refers to thebuilding of the robot, and, the other, to thewriting of a program.

Programming a computer with a given languagecan always be considered as creation since thelearner can choose the movements the robot willexecute. When the general design is defined by thetrainer (Nicoud, 1993; Vivet, 1993) or by an otherlearner, the creativity relies on the way to buildthe robot and the program, but not in theproject choice.

Fig. 2. Six learning/teaching paradigms (Leclercq & Denis, 1998).


Exploration To do this, the learners can explore some didacticmaterials (e.g. reference guides, help on line, . . .).

We could also consider the elaboration of theoriesby the learners. But it is a common core betweenthe different approaches of the educational roboticssince it is based on constructivism: inside theactivity, the learners have the opportunity toexperiment by trial and error (experimentation) andbuild their process and personal theories about thecurrent topic. How they create those theories andrepresentations are and have to be studied byresearchers (Limbos, 1993).

Experimentation The creation of original robots mainly depends onthe flexibility of the materials. For instance, in the‘‘computer assisted experimentation’’ or ‘‘cognitivespectacles’’ approach, the learner has a standardmaterial that will allow him/her to make his/herown experiments on a specific topic [e.g. build amodel about how a battery functions (Marchand,1993), about refrigeration systems (Hudon &Nonnon, 1993), breathing metabolism (Rellier &Sourdillat, 1993), . . .].

Imitation But, the learners could also build their robot orautomate from their imagination with salvage ofwaste products (of Saldano) or with materialssuch as kits sold by Fischertechnik1, Lego1,Inventa1, . . . even if those societies also providewith their materials some guidelines to build therobots. If those guides are used, it leads to theapplication of paradigms such as imitation(watching a video or observing a model) andtransmission/reception (reading to guidelines).Emerging activities based on virtual robotics alsoappear now; they refer to several approaches(Meurice de Dormale, 1997; Nonnon, 1997).

Reception

4. A collaborative problem based learning

The learning activity proposed here is based upon two main methodologicalprinciples: problem based and collaborative learning.


4.1. Problem based learning

Problem based learning (PBL) is based on a constuctivist approach of learning:the learner is at the centre and builds his/her knowledge. PBL has some commonfeatures with the ‘‘pedagogy of the project’’ (cf. Freinet, Le Grain), even if some-times the project is given by the tutor and not especially a learner’s personal project.PBL deeply implies the learners in the learning/training process since he/she (orthe group) has to define a strategy to solve the proposed problem (cf. Barrows &Tamblyn, 1977; EARLI Instructional design, 1998; Leclercq & Van Der Vleuten,1998).Sometimes, the teacher suggests the project. Defining and managing such problem-

solving situations based on personal project is not very easy for the trainer and thelearners. In fact, those educational practices are not often developed among theteachers and they prefer to adopt a constructivist methodology. With the learnersinvolved in a problem-solving situation, one has mainly to try to adopt teaching andlearning paradigms such as exploration, experimentation and creation (Leclercq &Denis, 1998).Hubert & Denis (1998, p. 33) define a ‘‘problem situation’’ or ‘‘challenge’’ as

follows:

1. a ‘‘desequilibrating’’ situation, an obstacle;2. an enigma (whose solution is not a priori known);3. a problem that answers a need;4. a problem that is significant for the learner;5. a problem whose complexity, duration and length match with the learner’s

capacities and availability;6. a problem that can support various topics (even parallel) in the classroom; and7. the opportunity to seek for information coming from different sources.

This list is not exhaustive. It just helps to determine if a proposed situation is areal problem solving one. All the criteria do not have to be present. Nevertheless,some of them are more fundamental than others. That is the case for the criteria 1– 5.This approach has been used in secondary schools to manage activities linked to

the course of Education par la technologie (Hubert & Denis, 1998) and in a researchon the pedagogical uses of Internet (Hubert, Denis, Detroz, & Demily, 2000).In the present context of ER activities, small groups (two or three students) have

to manage the challenge to realise their personal projects, so they have to solvemeaningful problems.

4.2. Cooperative and collaborative learning

Interactions between peers are an important and well known factor on the cognitivedevelopment, since there are confrontations of points of view (Mugny, 1985; Doise &Mugny, 1981; Perret Clermont, 1979) or exchanges of skills or strategies (Clark &Lampert, 1986) or reflections on one’s practice to help to regulate it (Denis, 1990). Theshare of core knowledge and the interaction between the learners’ proximal zones of


development (Vygostsky, 1962) permit learning by the way of social interactions(Lewis, 1996). The management of educational situations based on PBL and colla-borative learning such as the S.E.R.P (Sequences d’Entraınement a la Resolution deProblemes; Leclercq, 1979) or the LOGO environment (Denis, 1990) helps the learnersto structure their knowledge, but also implies some changes in the teacher’s role.The definitions of collaboration and cooperation are not unanimous. Even if dif-

ferent typologies or taxonomies of collaboration situations exist (Bennett & Dunne,1991; Pepitone, 1985), they finally always deal with the contribution of individualcompetencies to an explicit common objective and on the repartition of the groupmembers’ roles.According to Rogalski (Peeters et al., 1998), we shall retain ‘‘three main form of

cooperation, depending on the relation between the task and the actors of the collec-tive work: (1) collaboration, for the situations where the actors share the same goals allalong the task realisation; (2) distributed cooperation, for the situations where sub-tasks having a common goal are a priori distributed among different actors; andfinally (3) mediatisation, when an actor is in the situation of let other actors executetasks that participate to the realisation of his/her mission defined at a more generallevel’’. To the term mediatisation that generally refers to the notion of media, we pre-fer the expression cooperative delegation that refers more to the activity itself.As we shall see hereafter, in our educational robotics activity, we can talk about

collaboration inside the groups and about distributed cooperation between themsince the learners share and work on a common objective or sometimes since theirproject will be part of a bigger one (e.g. build a city with cars, trains, pedestrianspassages, . . .; Chung, 1991; Lewis, 1996; Peeters et al, 1998; Slavin, 1986).Collaboration can be a learning topic, in a creative activity (here try to answer to a

challenge or realise a project) (of Learn Nett, 1999). In fact, we have observed inanother situation that collaboration or cooperation can be learned and regulated atthe level of the roles or actions of the members of a group (Denis, 1981). It isimportant to structure the collaboration to obtain benefits from it: self-esteem,socialisation, etc.Considered at distance or not, synchronously or not, we consider that collabora-

tive learning:

1. Reduces the gap between teachers and learners: in collaborative learningenvironments, the trainer’s role evolves and becomes that of a facilitator, reg-ulator of the learners’ interactions. When learning is at distance, the tutors’role also deals with the management of learners’ interactions (Charlier, Daele,Cheffert, & Peeters, 1999a; Charlier et al, 1999b; Peeters et al, 1998).

2. Leads to active and creative learning: the learners have goals and problems tosolve together. They create knowledge.

3. Creates a sense of community: considering the evolution of our society to aknowledge and information society, it is very important to accentuate theirsharing and to focus on the development of community of practices and refer-ences among the members of groups or organisations to reinforce their coher-ence and efficiency. ER could help to reach this kind of goals.


5. Evaluation process

Hereafter, the evaluation process will only focus on some aspects of the learningprocess. The observation will not consider the different levels of the educationalsystem, but it will contribute to study and regulate the interactions between peers ina collaborative learning environment.

5.1. The regulation process

We shall situate our ER activity referring to the regulation process described byLeclercq (1995). This author defines six phases in any regulated process (or teaching/learning process) that we have illustrated referring to the ER framework:

1. Needs analysis or problem identification: we consider here that it is the factthat everybody should acquire a technological culture and competencies of thefour levels described earlier (cf. Fig. 1).

2. Project or definition of the general objectives: among several possible projects,we choose to develop ER activities to contribute to answer the needs.

3. Planning or operationalisation: the ER activities are planned in the agenda(e.g. 2 h per week), with specific materials, in a group of three students, withdetailed objectives (a learner’s target profile) and methodology (an animator’sprofile) (Denis, 1993).

4. Action or execution: the activity is organised. The learners and teacher act andinteract.

5. Observation or measure: the observation of the process is possible with ade-quate tools (see later).

6. Decisions of regulations or feedback loops: the results of observations help totake decision to ameliorate the activity.

This process can also be presented in different numbers of phases: in four phases(Hornke & Kluge, 1996; Leroy, 1991), in six (other) phases (Bahr, 1990), in sevenphases (Brien, 1986), in eight phases (Gagne & Briggs, 1986), in 17 phases (Kessels &Smit, 1994). These phases are also observed at several levels, for instance the society,the organisations (e.g. companies, schools, . . .), teachers, learners, . . . (Denis, 1997).The retroaction coming from the results of the evaluation will deal with one (or

several) phase(s) of the regulation process. So the feedback loop can be as shown inFig. 3.

5.2. Evaluation tools

To focus our observation and regulation on the interactions between learners, wehave chosen to develop observation grids (Denis, 1993b; Denis & Villette, 1995). Theanalysis of the verbalisations between the learners and their actions on tools such asthe computers, the robotics materials and reference guides coming from thoseobservations offer the opportunity to study the way the learners are collaboratingand use those tools.


The data collected permits analysis of what has happened during the action phaseand to regulate it (during the next activity—R4) or eventually to regulate the plan-ning phase (R3—e.g. modify the target profile of a learner: having observed somedifficulties related to prerequisites, decide not to focus first on computer skills).There are two grids, one deals with the learners’ behaviours, the other one with

the animator’s ones. To directly code interactions between the learners and theiractions we use the first one (with 25 categories of coding). So the results can becommunicated to the animator and the learners just after the activity and decisionsof regulation can be taken at once.In this grid, some categories focus more on the collaboration between learners.

The interactions between learners can be observed by verbalisations (elicitations,explanations, descriptions and evaluations). But the collaboration can also existconcerning the actions of building of the robots and programming them.

6. Learners’ collaboration in an educational robotics environment

We shall focus here on learners’ collaborative behaviours when they are involvedin an ER activity. What are their roles? How are the tasks distributed?

6.1. ER activity and observations

We shall present, hereafter, some results from the observation of two couples ofstudents of a primary school in Liege (cf. Villette, 1995). They are 10 years old. Thetwo groups have been observed during six periods of 80 min.In this classroom, only one computer is equipped with the ER interface and soft-

ware and there is just a little robotics material. The pupils worked on LOGO for 2years. In the approach that we have adopted, the task is generally complex andbased on a meaningful project. The task of the couple 1 was to build and program arobot or an automate with some LEGO1 material; the second one has to under-stand what was a prebuilt model (a merry go round) and to let it move with thehelp of the computer. Since the creation paradigm appears both in building and

Fig. 3. Combined loops of regulation.


programming for the group 1, we can consider that it will involve the pupils instrong collaboration and the development of dynamic competencies (linked to thedevelopment of their own project). This could be less observed in the second groupthat only has to invent the computing program.

6.2. Hypotheses

Our hypotheses are:

1. The learners collaborate during the definition and the realisation of the ERproject: they use the tools provided in the environment and are task centred.

2. There is a repartition of the tasks (build the robot, program it and verbalise theprocess) between the learners.

3. There is less collaboration behaviours observed in group 2 than in group 1.4. When there is a leader among the group, it is possible to regulate the interac-

tions between the learners in order to let the others act and verbalise more thanobserved.

5. Socio-cognitive conflicts have positive effect on the structuration and the rea-lisation of the learners’ project.

ER activity’s observations allow us to obtain some indicators concerning thesehypotheses.

6.3. Results

Referring to Table 1, that indicates the behaviours of each pupil observed, someof the hypotheses have been tested.

6.3.1. The learners collaborate during the definition and the realisation of the ERproject: they use the tools of the environment and are task centredWe can observe that:

1. During the activity the pupils of each group always work together and com-municate about the task (Nx1=813, Ny1= 602, Nx2= 455, Ny2=481).

2. At least a quarter of their activity concerns the use of the didactic tools (27–34%): they use the robotics materials (4–12%), the computer (5–19%), thereference guides (2–7%) and they take and write personal notes (3–7%).They also elicit many actions on computer, robotics material and documents(20–25%).

3. They announce what they are going to do or have done (16–29%) andask questions about this (13–19%), so they talk about the project and how torealise it.

There is a collaborative learning since the learners are ‘‘(i) more or less at the samelevel and can perform the same action, (ii) have a common goal, and (iii) work


together’’ (cf. Dillembourg, quoted by Gross, 2000). We can also consider that allthe learners are task centred. They do not give up their project and interact about it.Some demultiplicative skills (e.g. consultation of reference guides, note taking)

and strategic ones (e.g. explanations, collaboration,. . .) are observed (Table 1).

Table 1

Repartition of users’ behaviors

Behaviors Group 1 Group 2

X1 Y1 X2 Y2

Actions 218 27% 202 34% 125 27% 145 30%

Action on robotics materials (LEGOS) 95 12% 47 8% 19 4% 21 4%

Action on the computer 41 5% 80 13% 76 17% 91 19%

Action on reference documents 23 3% 45 7% 18 4% 9 2%

Action on notes (keeping/reading) 59 7% 30 5% 12 3% 24 5%

Towards the animator 21 3% 10 2% 19 4% 15 3%

Calls the animator 12 1% 6 1% 9 2% 7 1%

Listens to the animator 9 1% 4 1% 10 2% 8 2%

Verbalisations

Elicitation 314 39% 257 43% 168 37% 170 35%

of actions 20% 25% 22% 22%

Elicits a determined on the computer 29 4% 45 7% 42 9% 39 8%

Elicits an effect to produce on the computer 19 2% 23 4% 29 6% 36 7%

Elicits an action on robotics materials (LEGOS) 75 9% 30 5% 15 3% 24 5%

Elicits an action on documents 39 5% 50 8% 12 3% 9 2%

Of verbalisations 19% 18% 15% 13%

Elicits some information 27 3% 13 2% 8 2% 7 1%

Elicits a feedback, an agreement 25 3% 9 1% 5 1% 3 1%

Elicits an explanation—how? 12 1% 9 1% 6 1% 5 1%

Elicits an explanation—why? 19 2% 15 2% 6 1% 12 2%

Elicits a description—of an action 41 5% 50 8% 39 9% 26 5%

Elicits a description—of a project 28 3% 13 2% 6 1% 9 2%

Descriptions, explanations 158 19% 96 16% 131 29% 126 26%

Announces an action to realise 31 4% 30 5% 13 3% 21 4%

Describes a past action 10 1% 12 2% 6 1% 9 2%

Explains—how? 9 1% 12 2% 6 1% 9 2%

Explains how to structure the project, the action 12 1% 3 0% 6 1% 2 0%

Explains—why? 34 4% 10 2% 2 0% 4 1%

Evaluates 29 4% 12 2% 50 11% 42 9%

Predicts the result of an action 33 4% 17 3% 48 11% 39 8%

Yes/no 102 13% 37 6% 12 3% 25 5%

Agrees 72 9% 25 4% 9 2% 16 3%

Disagrees 30 4% 12 2% 3 1% 9 2%

Total behaviours 813 602 455 481


6.3.2. There is a repartition of the ‘‘tasks’’ (build the robot, program it and verbalisethe process) between the learnersEach pupil contributes to the robot creation (some more than others), especially in

group 1 (X1=12% and X2= 8%).As foreseen, group 2 does not have a lot of action on the robotic materials (4%)

since the model is already built and then they have proportionally more verbalinteractions and behaviours centred on computer and robot programming.Pupils of group 1 are complementary since the one (Y1) who uses the robotics

materials least (N=47 vs. 95 behaviours) programs the computer model (N=80 vs.41). Explanations (how to do, why this consequence is observed, and projectdecomposition) are given by everybody. X1 and Y1 also express evaluations (on thework done) or predictions.

6.3.3. There are less collaboration behaviours in group 2 than in group 1The type of projects (free or forced) seems to influence the quantity of behaviours:

there are more interactions in group 1 than in the second one (respectively, 1415 and936). But this could also be linked to individual differences (Denis, 1993a). In fact,both groups act and interact about the task, even if in the repartition of the beha-viours, we observe few differences (e.g. less descriptions and explanations in group 1).So we cannot conclude that the collaboration is qualitatively lower in group 2

than in group 1.

6.3.4. When there is a leader among the group, it is possible to regulate theinteractions between the learners in order to let the others act and verbalise more thanobservedIn group 1, we observe 813 behaviours of pupil X1 and 602 for the pupil Y1.

Generally and proportionally, X1 acts more on the robotics materials, elicits moreaction on it, explains, evaluates and predicts more actions, elicits information andfeedback and reacts (agrees or disagrees) more than Y1. In the second group, thedifferences between the two pupils are less obvious: they have almost the samenumber of behaviours. We can note that X2 elicits more action on reference docu-ments and description of the action, evaluates and predicts more the result of hisaction than Y2.To regulate the leadership behaviours and help everybody to take part actively in

all the phases of the project, the animator has to play a certain role. For instance,he/she can ask the pupils to use alternatively the computer, to take personal notesor/and share them. He/she has to play the role of moderator until the pupils learn toshare and exchange regularly and autonomously their roles.

6.3.5. Socio-cognitive conflicts have positive effect on the structuration and therealisation of the learners’ projectThe present grid as it has been used does not allow pointing out socio-cognitive

conflicts that appear among the pupils. Nevertheless, if we observe sequentiallythe learners’ actions and verbalisations, it is possible to identify some of them(Denis, 1990).


The sequences of behaviours such as ‘‘explanation of action to be done; action onthe computer, negative feedback—explanations, . . .’’ should indicate the possiblepresence of socio-cognitive conflicts (e.g. an ‘‘explanation A’’ confronted to an‘‘explanation B’’). Nevertheless, this grid in itself does not allow a sequential analy-sis. To do it, it is necessary to use video recording and to code and analyse thebehaviours a posteriori.

7. Conclusions and perspectives

ER environment centred on the learning paradigm of creation offers a greatopportunity to collaborate to a project, even if the teacher has imposed this one first.The pupils have to create at least the program to move the robots. This permitsbuilding of strategic competencies (e.g. explanations skills), demulptiplicative ones(e.g. consultation of reference guides, note taking and specific ones (e.g. computerprogramming).Many interactions focused on the tasks are observed. The learners work together.

They mainly developed strategic competencies such as problem solving and colla-boration. The type of interactions can vary inside a group and from one group toanother. Some leadership can appear in a couple of learners and be detected bythe coding of the activity. So the interpretation of the results can help to take thedecision to regulate the learners’ way to interact.Coding directly the learners’ behaviours with the grid presented here is possible,

but is mainly focused on a cognitive dimensioning (some aspects of problem sol-ving). The use of a more specific grid focused on social dimensions such as the rolescentred on the climate of the group or on the task (e.g. Bales) should permit obser-vation of other types of learner interactions and attitudes.The role of the trainer is also important in the method of animating groups and

reaching the objective of letting them collaborate on a project.

References

Barrows, H. S., & Tamblyn, R. M. (1977). The portable patient pack (P4), a problem-based learning unit.

Journal of Medical Education, 52, 1002–1004.

Bennett, N., & Dunne, E. (1991). The nature and quality of talk in co-operative classroom groups,

Learning and Instruction, vol. 1, 103–118.

Brien, R. (1986). Design Pedagogique. Montreal: Les Editions Saint-Yves, Inc.

Cervera, D., & Nonnon, P. (1993). Demarche de modelisation en simulation assistee par ordinateur pour

l’apprentissage des concepts d’energie des fluides. In B. Denis, & G.L. Baron (Eds.) (pp. 197–195).

Charlier, B., Daele, A., Cheffert, J. L., & Peeters, R. (1999a). Lusalusa, S., learning collaboratively in a

virtual campus: teachers’ experiences. Dublin: ISATT.

Charlier, B., Daele, A., Docq, F., Lebrun, M., Lusalusa, S., Peeters, R., & Deschryver, N. (1999b).

‘‘Tuteurs en ligne’’: quels roles, quelle formation?. Poitiers: Entretiens du CNED.

Chung, J. (1991). Collaborative Learning Strategies: The Design of Instructional Environments for the

Emerging New School, Educational Technology (pp. 15–22).

Delannoy, P. (1993). Decouverte micro-robotique: programmation sous hypercard. In Denis et Baron

(pp. 205–212).


Denis, B. (1990). Vers une auto-regulation des conduites d’animation en milieu LOGO. These de doctorat

non publiee, Universite de Liege.

Denis, B. (1993a). Measuring some cognitive effects of using control technology. In B. Denis (Ed.), Con-

trol technology in elementary education (Vol. 116; NATO ASI series, serie F: Computer and systems

sciences) (pp. 183–213). Berlin: Springer Verlag.

Denis, B. (1993b). Reguler les interventions des formateurs en robotique pedagogique. In B. Denis & G.L.

Baron (Eds)

Denis, B. (1997, March). Evaluation of the implementation of NICT in higher education. In BITE Con-

ference ‘‘Bringing Information into Technology of Education’’ (pp. 366–378). Maestricht.

Denis, B., & Baron, G. L. (Eds.). (1993). Regards sur la robotique pedagogique. Actes du quatrieme colloque

international sur la robotique pedagogique. Paris: INRP, Technologies nouvelles et education.

Denis, B., & Hubert, S. (1999). A conceptual framework of educational robotics. Colloque AI-ED 99, 9th

International conference on Artificial Intelligence in Education, AI-ED 99, Workshop on Educational

Robotics (pp. 45–54). Le Mans.

Denis, B., & Leclercq, D. (1994). The fundamental I.D.’s and their associated problems. In J. Lowyck & J.

Elen (Eds.), Modelling I.D. research, proceedings of the first workshop of the special interest group on

instructional design of EARLI, 17–19 June (pp. 67–83). Leuven.

Doise, W., & Mugny, G. (1981). Le developpement social de l’intelligence. Paris: Inter Editions.

Duchateau, C. (1993). Robotique-informatique: memes ebats, memes debats, memes combats? In B.

Denis, & G.L. Baron (Eds). (pp. 10–33).

EARLI (1998). Instructional design for problem-based learning. Proceedings of the Third Workshop of

the EARLI SIG Instructional design, 26–27 June. University of Maastricht.

Gagne, R.M., Briggs, L. J. (1986). Principles of Instructional Design. New York: Holt, Rinehart &Winston.

Girouard, M., & Nonnon, P. (1997). La ‘‘lunette cognitive’’ pour l’acquisition d’un langage graphique de

codage, son influence sur l’atteinte d’objectifs terminaux des cours de physique a l’education des adultes.

Montreal: Veme colloque de robotique pedagogique.

Gros, B. (2000). Instructional design for computer-supported collaborative learning in primary ans sec-

ondary school. Fourth Workshop of the EARLI SIG Instructional design, 3–4 July, University of

Barcelona.

Hubert, S., Denis, B., Detroz, P., & Demily, F. (2000). Apprentissage et utilisation d’Internet. Comment

utiliser Internet a des fins educatives? Comment evaluer les effets de l’emploi d’Internet sur le developpe-

ment de competences transversales et specifiques chez les eleves de l’enseignement secondaire? Rapport,

Convention 71/99, Communaute francaise de Belgique.

Hudon, R. & Nonnon, P. (1993). Environnement pedagogique informatise pour la ‘‘visualisation’’ de

systemes techno-scientifiques. In B. Denis, & G.L. Baron (Eds.) (pp. 173–178).

Kessels, & Smit. (1994). Opleidings Kunde: Kluwer Bedrijffswetenschappen.

Learn Nett (1999). http://tecfa.unige.ch/proj/learnett/.

Leclercq, D. (1979). La complementarite des approches clinique et experimentale des processus de resolu-

tions de problemes. Liege: Actes de la recontre belgo-suisse de Recherche en Sciences de l’Education.

Leclercq, D. (1987). L’ordinateur et les defis de l’apprentissage. Horizon, 13.

Leclercq, P. (1995). Approche Technologique de l’Education et de la Formation, Universite de Liege.

Leclercq, D., & Denis, B. (1998). Methodes de formation et psychologie de l’apprentissage. Service de

Technologie de l’Education de l’Universite de Liege.

Leclercq, D. & Van Der Vleuten, C. (1998). Apprentissage Par Problemes (APP). In Pour une pedagogie

universitaire de qualite. Liege: Mardaga (pp. 187–205).

Leroux, P. (1997). Roboteach: un assistant pedagogique logiciel dedie a l’alphabetisation en technologie.

Montreal: Veme colloque de robotique pedagogique.

Lewis, R. (1996, June). Working and learning in distributed communities. Universidad Autonoma de

Madrid, seminar, Computer Supported Learning Environments.

Limbos, B. (1993). L’utilisation de representations graphiques en robotique pedagogique. In B. Denis, &

G.L. Baron (Eds.) (pp. 65–84).

Macherez, G. (1993). La robotique pedagogique au College I. Goffin de Mouzon. In Denis et Baron (pp.

155–160).


Marchand, D. (1993). Modelisation et mesures en sciences physiques et robotique pedagogique. In B.

Denis, & G. Baron (Eds.) (pp. 161–172).

Meurice de Dormale, R. (1997). Robotique virtuelle: environnement pour un apprentissage dynamique et

interactif de l’algorithmique. Montreal: Veme colloque de robotique pedagogique.

Morato, P. (1993). L’environnement LOGO et le developpement de la cognition spatiale pour des enfants

atteints de Trisomie 21. In Denis et Baron (pp. 106–116).

Mugny, G. (1985). Psychologie sociale du developpement cognitif. Berne: Peter Lang.

Napierala, D. et al. (1993). La robotique pedagogique au service de la pedagogie du projet. In Denis et

Baron (pp. 94–105).

Nicoud, J. D. (1993). Concours de robots. In B. Denis, & G.L. Baron (Eds.) (pp. 197–204).

Nonnon, P. (1986). Laboratoire d’initiation aux sciences assiste par ordinateur. Universite de Montreal:

Faculte des Sciences de l’Education,.

Nonnon, P. (1993). Proposition d’un modele de recherche developpement technologique en education. In

B. Denis, & G.L. Baron (Eds.) (pp. 147–154).

Nonnon, P. (1997). Radioscopie virtuelle. Montreal: Veme colloque de robotique pedagogique.

Papert, S. (1984). Microworlds: transforming education. Paper presented at the ITT Key Issues Conference

held at the Annenberg School of Communications of the University of Southern California, 14-3.

Pepitone, E. A. (1985). Children in cooperation and competition. In Slavin, et al. (Eds.), Learning to

cooperate, cooperating to learn (pp. 17–65). New York: Plenum Press.

Perret Clermont, A. N. (1979). La construction de l’intelligence dans l’interaction sociale. Berne: Lang.

Petters, R., et al. (1998). Learning collaboratively in a virtual campus. Learn-Nett, WP4.

Rellier, C., & Sourdillat, F. (1993). Evariste et la Lunette Cognitive. In B. Denis, & G.L. Baron (Eds.) (pp.

179–186).

Sougne, J. (1993). Les raisonnements temporels en robotique pedagogique. In Denis et Baron (pp. 85–93).

Tauriac, G. (1993). Du projet pedagogique au produit industriel: Modulix 787/Pgrafcet. In B. Denis, &

G.L. Baron (Eds.) (pp. 256–260).

Villette, A. (1995). Analyse de l’acquisition d’une demarche scientifique au travers d’activites de robotique

pedagogique. Memoire de licence en sciences de l’education non publie, Universite de Liege.

Vivet, M. (1993). La reception des productions des apprenants : une phase essentielle dans la conduite des

projets. In B. Denis, & G.L. Baron (Eds.) (pp. 117–134).
