A SYSTEM TO SUPPORT TUTORS IN ADAPTING DISTANCE

LEARNING SITUATIONS TO STUDENTS

Élise Garrot, Sébastien George, Patrick Prévôt

ICTT Laboratory, INSA Lyon, France

Keywords: Computer based environments for human learning, tutors’ role and instrumentation, ontology, expert

system.

Abstract: Currently, tutor’s roles in distance learning are not clearly defined and few tools support him/her in his/her

functions. Some tools help tutors to monitor learners and interact with them, but no tools assist them in the

setting-up of learning sessions. Activities are created by instructional designers who envisage standard

scenarios without knowing the learners. Thus, the aim of our research project is to create a system to help

tutors to adapt learning situations to learners’ needs and characteristics. The first phase of our work consists

in determine tutor’s roles in collaborative distance learning, in order to identify his/her needs. Then, we

implement an assistance system based on an ontology containing learners’ characteristics and parameters of

learning situations. An inference engine creates links between these characteristics by reasoning on the

ontology. Finally, some rules deduce relations between ontology elements in order to give the tutor advice.

1 INTRODUCTION

Over the last thirty years, distance learning moved

from postal to an on-line teaching in which

information and communication technologies (ICT)

play a prominent part. In particular, it involved a

new definition of teacher roles, even if up to now

these are rather badly defined and vary from one

educational institution to the other.

Our research is in the area of the computer-based

environments for human learning, using partnership

between man and machine, particularly through ICT.

Internet generalization makes this dimension

currently central.

On the one hand, we identify tutor’s roles,

especially in collaborative learning situations; on the

other hand, we design a system aiming at helping the

tutor to take up all roles which are assigned to him.

More particularly, this tool assists tutor in the

setting-up of learning sessions adapted to learners’

needs and characteristics.

In this paper, we first determine distance learning

functions of tutors, compared with traditional

teacher roles. The next section explains why we

supply an assistance tool to the tutor. The following

sections show system design with an example of

implementation in the form of rules which advice

the tutor. The final section presents an overview of

our work in progress.

2 TEACHER’S ROLES: FROM

PRESENCE TO DISTANCE

Our work is based on a literature survey on teacher’s

roles in traditional education and distance learning.

We first want to determine the effects of distance on

teachers’ roles and the differences on the actors’

interactions and relations due to distance,

specifically in collaborative learning. The aim of this

study is to determine the roles of the different actors

of the course, especially the role of “tutor”.

Houssaye (1988) represents relations between

learner, teacher and knowledge, under the shape of

the "educational triangle". This triangle brings out

three educational styles (Faerber, 2002). The

teacher-knowledge relation corresponds to the

traditional education with transmission of

knowledge, the teacher-learner relation defines the

emotional and psychological relation between these

two actors and learner-knowledge relation represents

the appropriation phase of knowledge by the learner.

In traditional education, teacher often has a role

of "transmitter of knowledge" and learners absorb a

261

Garrot É., George S. and Prévôt P. (2006).

A SYSTEM TO SUPPORT TUTORS IN ADAPTING DISTANCE LEARNING SITUATIONS TO STUDENTS.

In Proceedings of WEBIST 2006 - Second International Conference on Web Information Systems and Technologies - Society, e-Business and

e-Government / e-Learning, pages 261-267

DOI: 10.5220/0001248702610267

 SciTePress

quantity of information, among which little will be

transformed into knowledge. School has still an

approach to education which tends to inculcate a set

of knowledge and capacities which will not be

reusable in another context than the one in which

they were learnt (Perrenoud, 2000).

Perrenoud (2000) suggests setting learners in true

situations, steps of project, open problems, and

incites teachers to offer learners activities in which

they will be the actors of their learning. It joins to it

the constructivist theories (Doise et al., 1984) which

consider learning as a personal experience towards

knowledge, influenced by the social context in

which it takes place.

According to the socio-constructivist approach,

interactions between learners play a dynamic role in

individual learning. In this way, collaborative

learning activities are more and more used in

distance education. This kind of activity, as project-

based learning (George et al., 2001), business game,

case solving, has already proved to be useful

When we transpose the “educational triangle” to

collaborative and distance learning, other poles and

relations appear. In a specific collaborative learning,

another element appears: learning group (Faerber,

2002). By introducing this new element, we take

into account interactions and relations between

learner, teacher and learning group, each learner

being a member of a group. These relations and

interactions are more complex in the context of our

study due to distance. So it is very important to

consider the learning group in order to identify

teachers’ roles and to help the different actors to

interact in a positive way.

In distance learning, the function of teacher is

then divided into two distinct roles: the instructional

designer of courses supports and contents, and the

tutor who helps learners to build knowledge and

competencies and assess them. A one single person

can play both roles, but each role does not intervene

in the same moment of the course.

Figure 2 represents new relations between that

appear between the learning elements. The relations

between items have to be defined: both between the

pedagogical team (instructional designer and tutor)

and other elements (group, learner and knowledge),

and between instructional designer and tutor. Are

these both in relation with knowledge? Are they

both in relation with learners? A lot of questions

appear and our research tends to answer them.

Figure 2: Relations between actors of learning and

knowledge

We want to determine relations between learner,

learning group and pedagogical team and with the

knowledge to be acquired by the learner. With this

in mind, we consider the tutor as the centre of the

learning and try to identify his/her role in specific

collaborative distance learning.

3 TUTOR’S ROLES

In literature, distance tutors are named differently,

according to the functions that one assigns to them:

moderator, facilitator, online tutor, online moderator,

e-moderator, coach, distance education tutor, e-

tutor… Reviewing the literature on the tutor’s role in

distance learning, we were surprised by all the roles

that are assigned to only one person and the

differences according to distance courses.

Tutors’ roles are generally classified into four

parts: pedagogical, organisational, relational and

technical. Denis et al. (2004), inside the Learn-Nett

project, assign seven different roles to the tutor. For

them, the tutor is a content, metacognition and

process facilitator, an advisor/counsellor, an

assessor, a technologist and a resource provider.

According to Lentell (2003, p. 74), “They [tutors]

have to be effective listeners and communicators, to

be a coach, facilitator, mentor, supporter and

resource. They have to listen, to shape, to give

feedback, to motivate, to direct, to appreciate –

broadly to be developmental and problem solving.”

According to Dillenbourg (1999), the tutor is a

“facilitator” because he/she has to assure a minimal

educational intervention to guide the learning group

in a productive way or to follow which members are

except the interaction.

We based our view of tutors’ roles on those who

are assigned to them by the platform ACOLAD

Learner Tutor

Designer

Learning

Group

Knowledge

Pedagogical

team

WEBIST 2006 - E-LEARNING

262

(Faerber, 2003) and on the view of Daele et al.

(2002). Tutors, in the ACOLAD environment,

decide which learning situations to propose to

learners, in order to adapt them to their needs. For a

given situation, tutors can bring documents and

personal references. We agree with this view of

tutors’ roles because we think that it is very

important for them to have the possibility to adapt

the activities to learners’ needs and characteristics.

It is necessary to differentiate the activities and

the interactions so that each learner is in his/her

proximal zone of development (Vygotsky, 1986), so

that he/she is constantly or at least very often

confronted with the most fertile didactics situations

for him/her. Tutors, thanks to their psychological

and emotional role, are the ones who are best placed

to choose the activities which are appropriated to

learners and the resources which they need.

Daele et al. (2002) are interested in collaborative

distance learning based on a pedagogical model

centred on the learner and on interactions. In this

context, they distinguish two levels of intervention:

with the learning group and with the learner. Tutors

help the group to define a common project, to find

adapted resources, to organize and regulate

exchanges, to respect the instructions and deadlines,

and to structure itself. They help the learner to

express his/her personal project, to articulate it to the

project of the group, to think about his/her own

approach of learning and collaboration at distance.

We also think it is essential to distinguish these two

levels of intervention in order not to lose the learner

into the learning group.

Dillenbourg (1999) gives four means to try to

develop interactions. These means are the following:

to carefully set up the situation of learning (group

size, selection of group members, suited tasks…), to

specify the “contract of collaboration” with a

scenario based on roles (to give different viewpoint

to subjects, asking subjects to play a specific role in

an argumentation,…), to specify interaction rules for

the computer-mediated interactions in collaboration,

to monitor and regulate the interactions. This advice

corresponds with many roles tutors have to perform

in collaborative learning.

In order to be able to play all their roles, tutors

must have experience and competencies to base on,

so as to be credible towards learners. The tutor may

have experience as a teacher or in a local point of

expertise in the field of the contents. It is necessary

that the tutor has a minimum of competencies in

these two fields (pedagogy and in the subject area),

so as to have capacities to build himself/herself as an

expert. He/she is a witness of his/her personal

experience; he/she must be able to bring out the

sense of the contents to learners, for example by

giving them anecdotes and personal references.

Regarding the works previously described, we

synthesize tutors’ roles. For the learning group, the

tutor is:

¾ A group assessor: he/she assess the learning

group’s productions and activities.

¾ A resource provider: for a given learning

situation, he/she can provide documents or

advise adapted resources in order to guide

learners in a good way.

¾ A moderator: he/she has to set up the

dynamic of the group and to develop

interactions within all possible means

(Dillenbourg, 1999).

¾ A pedagogical architect (George, 2004):

he/she has degrees of freedom to adapt the

learning situations created by the instructional

designer to learners’ needs and

characteristics, provided that the designer

foresaw that one needs to furnish the training

(Faerber, 2003).

Tutors also have different roles to help the

learner. For a learner in particular, the tutor is:

¾ A learner assessor: he/she evaluates the

knowledge and competencies that the learner

has acquired during the course.

¾ A psychological and emotional support:

he/she is a human mediator to motivate the

learner, to encourage, stimulate and boost him

(Lentell, 2003).

¾ A regulator: he/she has to regulate the

learning, to adapt learning situation

difficulties for each learner, and to give

him/her feedback on the assessment.

¾ A guide and facilitator so that the learner

acquires the competencies necessary to

autonomy in a specific context of distance

and collaborative learning (George, 2004).

He/she helps the learner to take part to the

learning group interactions and activities.

4 AN ASSISTANCE TOOL FOR

THE TUTOR

As Dufresne et al. (2003) emphasize, the

instrumentation of tutors’ activity in distance

learning environments is still little developed.

Research was rather centred on the characterization

and the standardization of learning activities in order

to assist authors in the designing of scenarios, and

also centred on tutors to support them to monitor

A SYSTEM TO SUPPORT TUTORS IN ADAPTING DISTANCE LEARNING SITUATIONS TO STUDENTS

263

learner’s activities and interact to solve difficulties

(Després, 2003).

As we assert in the previous section, tutors have

several roles which do not only consist in

monitoring and interacting with learners. We want

tutors to be resource providers and pedagogical

architects, to set-up the dynamic of the group, to

regulate the learning and to adapt situations to

learning groups and to each learner in particular. We

think that it is impossible for tutors to assume all

these roles without a tool to assist them. As

suggested by Bennett et al. (2002) tutors are being

asked “to run before they can walk”.

Generally, the instructional designer prepares

scenarios without knowing learners. We prefer the

concept of “learning situation” to “scenario”. A

scenario anticipates a learning process and

interactions during learning sessions (Faerber,

2004). It generally defines a progress through

contents, resources, and it anticipates behaviour,

tasks sequencing. But is it possible to provide a

scenario for all possible cases? We prefer the term

“learning situation” which is more general and

shows all the possibilities offered to the tutor to

adapt learning sessions during the course, according

to learners’ needs and progress, not defined a priori.

The system we developed assists tutors in the

instantiation of generic learning situations provided

by instructional designers. Learning situations

consist of a set of activities carried-out by a learners

group engaged in a same objective. Project, case

study, problems resolution… are examples of

learning situations. The designer defines parameters

for each situation, in order to give degrees of

freedom to the tutor to adapt them to learners. The

system assists and advises tutors in the setting-up of

learning sessions, by creating links between

learners’ characteristics and the parameters of

activities.

Figure 3 highlights the role of the assistance

system for tutors to help them to set-up learning

sessions. In this configuration, the instructional

designer has to envisage a variety of activities and

possible situations of learning with parameters

(number of students, group size…). Then the tutor

can prepare specific learning situations from existing

generic situations.

Figure 3: The functioning and the place of our assistance

tool to help tutors.

5 DESIGN OF THE ASSISTANCE

TOOL

5.1 Development Choices

The assistance system must be able to adapt to

learning situations which vary according to the type

of online courses and the tutoring model applied.

That’s why we chose to separate knowledge and

reasoning. The system is based on an ontology

which represents the different concepts (like actors

or activities), their properties and the relations

existing between them. Ontology has the advantage

to make explicit what is regarded as implicit in the

field (Kasai et al., 2004), to use a vocabulary

comprehensible by all actors, to re-use and make this

vocabulary evolve.

Concerning the implementation, we chose the

software Protege2000

, a tool for modelling and

knowledge acquisition developed by the University

of Stanford, in the United States. The plug-in

JessTab

, integrated into Protege2000, makes it

possible to introduce the knowledge stored by

Protege2000 into a data base, in order to be inferred

by some rules written in the inference engine Jess

an expert system independent of Protege2000.

http://protege.stanford.edu/

http://www.ida.liu.se/~her/JessTab/

http://herzberg.ca.sandia.gov/jess/

WEBIST 2006 - E-LEARNING

264

5.2 Ontological Model

The developed ontology identifies and describes

several concepts: the actors of the learning (learner,

tutor, designer…), learning situations (project, case-

study…), resources, knowledge, behaviour and an

historic of the learning.

For example, we created two different concepts:

Actor and Actors’ characteristics. These two

concepts correspond to classes which each contains

subclasses (figure 4). The class Actor has for

subclasses Learner, Tutor, Instructional Designer

and Computer Designer. To each subclass of the

class Actors’-characteristics correspond general

characteristics (like identity) and the subclass

Learner has specific characteristics. For the moment,

we have especially developed learner characteristics

but tutor characteristics can be added later. Both

concepts are connected by properties of the class

Actor which are instances of the class Actors’-

characteristics.

For the learner, we identified five general

characteristics: learner’s knowledge and behaviour,

his/her experience, identity profile (curriculum-

vitae, cultural origins, interests and habits), needs

and objectives, and cognitive capacities (figure 4).

Figure 4: Properties associating to learners characteristics

in Protege2000.

To give a structure and describe learning

situations, we referred to the granularity levels of the

standard IMS-LD (IMS Learning Design)

. This

model, based on the EML standard (Koper, 2001),

describes a formal way to represent the structure of a

Unit of Learning and the concept of a pedagogical

method specifying roles and activities that learners

and support persons can play using learning objects.

In the ontology, activities are decomposed in the

following way: Course -> Learning situation ->

Activity -> Resources and communication tool ->

Media (figure 5). The course corresponds to a unit of

learning described in IMS-LD and, as we said in the

previous section, the concept of “learning situation”

is preferred to “scenario”.

http://www.imsglobal.org/learningdesign/index.html

We consider that learners carry out a set of

activities within a same learning situation. In a case

study-based learning, an activity can be the problem

formalization, searching for causes or solutions.

Some resources (documents…) and means of

communication (chat, forum, e-mail…) are offered

to actors before and during learning sessions. They

represent the learning environment. A resource is

composed of media (picture, video, sound…).

We have brought out two important concepts:

knowledge and behaviour (Paquette, 2002), because

these two concepts are linked to other concepts of

the ontology: activity, learning situation and learner.

On the one hand, activities and learning situations

have properties which define pre-required

knowledge and behaviours, and knowledge and

behaviours to be acquired. On the other hand,

learners have initial behaviours and knowledge, and

some to acquire during the course.

Figure 5: Activities description in Protege2000.

It is important for the tutor to have the possibility

to note and to have access to data concerning

learners. We give tutor the possibility to keep for

each learner and learning group a chronological

record of learning. With this chronological record

tutors can indicate learners’ achievements,

interactions and carried-out activities. Tutors can

also note their perceptions about learners, on their

level of initiative, motivation, stress, autonomy or

interactions, at some point of the course.

6 IMPLEMENTATION OF RULES

TO ADVICE THE TUTOR

The implementation of the system consists in writing

different types of inference rules. These types are the

following ones:

A SYSTEM TO SUPPORT TUTORS IN ADAPTING DISTANCE LEARNING SITUATIONS TO STUDENTS

265

¾ Rules which create links between learners’

characteristics.

¾ Rules which deduct advice to give to the tutor

concerning the type of pedagogy to be applied

for each learner, according to some of his/her

characteristics.

¾ Rules which create links between activities’

parameters and learners’ characteristics by

advising the tutor an activity to attribute to a

learner according to some variables.

Rules can help tutors to play all the roles we

assigned in a previous section. For example, tutors

are moderators who have to develop interactions. To

play this role, Dillenbourg (1999) gives

recommendations: set up the situation, specify

interaction rules and roles inside the learning group.

These recommendations can be implemented in the

system in the form of rules, which infer advice to

tutors, according to the characteristics of a given

activity defined in the ontology, in the form of an

instance of the class Activity.

For example, let us consider a learner who has

just validated an activity. We have developed a rule

which advises the tutor an activity to attribute to the

learner and the modality associated (individual or

collective), according to the need for autonomy

declared by this learner. The rule so created looks

for activities which need the pre-required activities

validated by the learner. Then, in the case of an

activity which can be indifferently done in an

individual or collective way, we look at the need in

autonomy declared by the learner and we advise an

activity with the associated modality. We present a

part of the code which enables this rule to be

followed:

(if (and (eq ?pre_required_activities

?validated_activities_object)

(eq (slot-get ?activity

modality) individual-or-collaborative))

then (foreach ?need (slot-get ?learner

has-as-needs-and-objectives)

(if (eq (slot-get ?need

autonomy) TRUE)

then (printout t "Propose to

learner "?name" to do the actvity

"?activity_name "individually."crlf))

The rules have no ambition to be totally

educationally valid at this time of the project; they

only show the feasibility of the system. To validate

the rules, we will work with specialists of education

sciences.

We also want to give the possibility to tutors to

modify and create the instructional rules themselves,

so as to ensure a good appropriation of the tool by

tutors. We do not want either to replace the tutor by

a system, or to automate its work. We want to assist

him/her in his/her functions with a system which

gives advice. This research is based on the

partnership between man and machine.

7 WORK IN PROGRESS

In the next weeks, we will validate our view of

tutors’ roles and needs by interviewing some of

them. We are in relation with several tutors of

various backgrounds who are interested in working

in collaboration on this subject. We will present to

tutors a model of our assistance tool, so as to make

its functionalities progress.

We developed a system to assist the tutor before

learning sessions in the setting-up of learning

situations. Tutors also monitor and manage learning

sessions. Beyond the learners monitoring necessary

in a pedagogical way, we are more particularly

interested in recovering information about learners’

activities and interactions which will guide tutors in

the setting-up of sessions to come. This iterative

functioning is the heart of our future research work

(figure 7).

Figure 7: Iterative functioning of the system.

The aim is to develop specific monitoring tools

in order to trace learner activities to determine or get

more precise learners’ characteristics. The

monitoring tools will have to be configurable by the

tutor.

WEBIST 2006 - E-LEARNING

266

8 CONCLUSION AND FUTURE

DIRECTION

A result of this research concerns tutors’ roles in

collaborative distance learning. We assigned four

roles in regard to the learning group and four roles in

regard to each learner individually. This work led to

the implementation of a system to help tutors to

adapt learning sessions to learners, taking into

account their characteristics and needs during the

course.

The system is based on an ontology which

integrates all the learning concepts (actors, learning

situations, activities, resources) by specifying their

properties and relations. Finally, the development of

the system containing rules, which apply on the

classes instances of the ontology, showed the

feasibility of our assistance system to set-up learning

situations. Moreover, the diversity of rules shows the

flexibility of the system and the many prospects

offered.

Future research will be directed towards two

axes: the validation of our view of tutors’ roles and

needs and the complete implementation of the

system. We are in relation with several tutors of

various specialities who are interested in working in

collaboration on this subject. It will be as many

possible grounds for our future experiments.

Concerning the tutor’s assistance system to

configure learning activities, we want to conceive

various interfaces for learning actors, in order to

guide them to insert data in the ontology. In

addition, it will be interesting to give the tutor the

possibility to modify and create learning rules

himself, thus ensuring a feed-back on uses and a

good appropriation of the tool. We also have in

prospect to associate an interactions analysis agent

to automatically feed the system with data

concerning interactions between learners.

REFERENCES

Bennett, S., Marsh, D. (2002). Are We Expecting Online

Tutors to Run Before They Can Walk? In Innovations

in Education and Teaching International, Vol. 39, n°1,

p. 14-20.

Daele, A., Docq, F. (2002). Le tuteur en ligne, quelles

conditions d'efficacité dans un dispositif

d'apprentissage collaboratif à distance ? In 19ème

colloque de l'AIPU (Association Internationale de

Pédagogie Universitaire), Louvain-la-Neuve.

Denis, B., Watland, P., Pirotte, S. Verday, N. (2004).

Roles and Competencies of the e-Tutor (Learn Nett

project). In Networked Learning Conference, England.

Després, C. (2003). Synchronous Tutoring in Distance

Learning. In AIED conference, Sydney, Australie, p.

271-278.

Dillenbourg, P. (1999). What do you mean by

'collaborative learning'? Collaborative-learning:

Cognitive and Computational Approaches. E. P.

Dillenbourg, Oxford, Elsevier, p. 1-19.

Doise, W., Mugny, G. (1984). The Social Development of

the Intellect. Pergamon Press, New York.

Dufresne, A., Basque, J., Paquette, G., Léonard, M.,

Lundgren-Cayrol, K., Prom Tep, S. (2003). Vers un

modèle générique d'assistance aux acteurs du

téléapprentissage. Revue STICEF, Vol. 10, p. 57-88.

Faerber, R. (2002). Le groupe d'apprentissage en

formation à distance : ses caractéristiques dans un

environnement virtuel. La place des TICE en

formation initiale et continue à l'enseignement : Bilan

et perspectives, E. L. F. K. T. Sherbrooke, p 99-128.

Faerber, R. (2003). Groupements, processus pédagogiques

et quelques contraintes liés à un environnement virtuel

d'apprentissage. In Environnements Informatiques

pour l'Apprentissage Humain, Strasbourg, France.

Faerber, R. (2004). Caractérisation des situations

d'apprentissage en groupe. Revue STICEF numéro

spécial Ontologies pour les EIAH, Vol. 11, p. 297-

331.

George, S., Leroux, P. (2001). Project-Based Learning as a

Basis for a CSCL Environment: An Example in

Educational Robotics. In First European Conference

on Computer-Supported Collaborative Learning

(Euro-CSCL 2001). Maastricht, The Netherlands.

George, S., Prévôt, P., Amghar, Y., Pierson, J-M. (2004).

Complexité des situations pédagogiques e-learning

dans un contexte multi-culturel, collaboratif et

synchrone. In Conférence TICE Méditerranée, Nice.

Houssaye J. (1988). Théorie et pratiques de l’éducation

scolaire (Tome 1– Le triangle pédagogique), Berne :

Peter Lang.

Kasai, T., Yamaguchi, H., Nagano, K., Mizoguchi, R.

(2005). Goal Transition Model and Its Application for

Supporting Teachers based on Ontologies. In 12th

Artificial Intelligence in Education (AIED2005),

Amsterdam, The Netherlands, p. 330-337.

Koper, R. (2001). Modeling Units of study from a

pedagogical perspective - The pedagogical meta-

model behind EML. Open University of the

Netherlands.

Lentell, H. (2003). The Importance of the Tutor in Open

and Distance Learning. In A. Tait & R. Mills (Eds.),

Rethinking Learner Support In Distance Education,

London: RoutledgeFalmer, p. 64-76.

Paquette, G. (2002).

Modélisation des connaissances et

des compétences. Presse de l’Université du Québec,

2002

Perrenoud, P. (2000). L'approche par compétences, une

réponse à l'échec scolaire ? In Colloque de

l'association de pédagogie collégiale, Montréal.

Vygotsky, Lev (1986). Thought and Language,

Cambridge, Massachusetts: The MIT Press.

A SYSTEM TO SUPPORT TUTORS IN ADAPTING DISTANCE LEARNING SITUATIONS TO STUDENTS

267