Post on 05-Jan-2016
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Les trois générations de tuteurRoger Nkambou
3 Générations de tuteurs
1ère Génération – Sur le marché Technologie sous-jacente : Hypertexte & Behaviorisme Pédagogie: Feedback didactique sur les réponses de l’apprenant.
2ème Génération – Emergent sur le marché Technologie : Intelligence Artificielle & Psychologie Cognitive Pédagogie : Assistance sur les étapes de résolution d’un problème
(et non seulement sur une réponse finale)
3ème Génération – Emergent dans les labos Technologie : Traitement du langage naturelle, plannification
réactive, évaluation du continue de la pédagogie et du contenu Pédagogie : Dialogues permettant la construction des
connaissances
La 1ère génération:EAO (Enseignement Assisté par Ordinateur) (CAI – Computer-Based Instruction)
Exemple
Solve 2+2x=12 Multiplication has ahigher precedencethan addition, so 2+2xis the same as 2+(2x),not (2+2)x. Try again.x=7
x=3
x=5
OK
OK
Excellent!
La 1ère génération (suite)
Exemple 2:
La boucle fonctionnelle des EAO
Pour chaque chapitre du curriculum Lire le chapitrePour chaque exercice Boucle
Prendre la réponse Donner la rétroaction et les conseils sur la réponse Sortir si bonne réponse Essayez de nouveau
Fin boucle
FinPourPasser un test sur le chapitre
FinPour
2ème génération:Systèmes Tutoriels Intelligents ClassiquesTechnologie sous-jacente: IA et Psycho. Cogn.Pédagogie: Assistance sur les étapes d’un problèmeExemple:
Tutor: Solve 2+2x=12 Student: <enters 4x=12> Tutor: Not quite. Try again. Student: <clicks on “hint” button> Tutor: Think about operator
precedence. Student: <enters 2x=12-2> Tutor: Good!
2 + 2x = 12 4x = 122x = 12 - 2
Student’s workspace:
Tutor:
Good!
Hint
La boucle fonctionnelle des STI classiques
Pour chaque chapitre du curriculum Lire le chapitrePour chaque exercice Boucle
Pour chaque étape de l’exercice Boucle
Prendre la réponse Donner la rétroaction et les conseils sur la réponse Sortir si bonne réponse Essayez de nouveau
Fin boucle FinPour
FinPourPasser un test sur le chapitre
FinPour
Technologie: Planification réactive & Traitement du langage naturelPedagogie: Dialogues visant la construction des connaissances Exemple:
Tutor: Solve 2+2x=12 Student: 4x=12 Tutor: Should this equation have the
same solution as the first one? Student: Yes. Tutor: The solution to 4x=12 is 3,
so let’s check for an error by trying x=3 in 2+2x=12.
Student: 2+2*3=2+6=8 oops! Tutor: Right! Now look at the
arithmetic steps you did …
3ème génération
2+2x=124x=12
Student’s workspace:
Dialog:
S: 2+2*3=2+6=8 oops!T: Right! Now look...
Hint
Exempe: Algebra Cognitive Tutor
Boucle fonctionnelle des tuteurs de 3ème génération
Pour chaque chapitre du curriculum Lire le chapitrePour chaque exercice
Boucle Pour chaque étape de l’exercice
Boucle Prendre la réponse Sortir si bonne réponse Pour chaque inférence en relation avec le bon raisonnement - Eliciter cette inférence chez l’apprenant - Conseiller, ‘prompter’ - Sortir si l’étudiant complète l’étape FinPour
Fin Boucle FinPour
FinPourPasser un test sur le chapitre
FinPour
Limites des tuteurs de 2ème génération
Beaucoup moins bons que les tuteurs humains!
Ne permettent pas toujours une compréhension profonde de la matière Les symptômes d’un apprentissage
superficiel: Peu de transfert de K dans de nouvelles
situation de résolution de problèmes Peu d’habilité à expliquer (via une conversation
abstraite cohérente sur le domaine)
Les tuteurs de 3e génération
Dialogues pour la construction de connaissances“there is something about conversational dialog that plays
an important role in learning”.
Meilleure théorie sur la stratégie tutorielle visant à promouvoir l’apprentissage :“Good tutors tell less and ask more.” Ils guident les étudiants au fil de leur processus de
construction de nouvelles connaissances. Ils les aide à faire des abstractions Ils les aide à créer des connections qui aide au transfert.
L’orientation des recherches sur les T3G
Sur le plan empirique Déterminer QUAND et POURQUOI le dialogue
tutorielle est éfficace et utile.
Sur le plan technique Développer des systèmes qui supportent les
apprenants dans la construction de connaissances à travers le dialogue tutoriel
Evaluater l’efficacité de ces systèmes
Le but est de rivaliser ou ‘surpasser’ l’efficacité des tuteurs humains
Exemples de T3G Andes/Atlas: Dialogue plutôt que ConseilWhy/Atlas: Dialogues critiques CIRCSIM: Dialogue dans le but de corriger les erreurs dans les prédictions des étudiants sur la causalité physiologique AutoTutor: Dialogue sur le domaine des ordiGeometry Explanation Tutor : Dialogue pour la résolution de problème en géométrie.Ms. Lindquist: Dialogue concernant les méthodes pour l’analyse des mots algébriques
Andes/Atlas: Le dialogue remplace les séquences de conseils
Andes: If you are moving in a straight line and accelerate in the same direction, does your velocity increase or decrease?
You: increase
Andes: You’ve drawn the acceleration of the elevator in the same direction as the velocity. Is the velocity of the elevator increasing?
Why/Atlas
CIRCSIMMartha Evens, Reva Freedman, Michael Glass, Yujian Zou, et al., Illinois Institute of Technology
Domaine: physiologie (contrôle de la pression sanguine)Emphase: dialogue dans le but de corriger les erreurs de prédictions des étudiants sur la cautsalité physiologique Questions à réponses courtes, stratégies de conseil
CIRCSIM-Tutor (Interface usager)
Problem: Pacemaker malfunctions, increasing to 120 beats/min.
T> What variable is affected by HR?S> Cardiac Output.T> But you predicted that HR increases and CO decreases.S>
DR RR SSCentral Venous Pressure -Inotropic State 0Stroke Volume -Heart Rate +Cardiac Output -Total Peripheral Resistance 0Mean Arterial Pressure +
MeanArterial
Pressure
TotalPeripheralResistance
ArteriolarResistance
ArteriolarMuscleTone
ArteriolarDiameter
StrokeVolume
CentralVenous
Pressure
InotropicState
Alpha-Blocker(drug)
Pacemaker Rate Up(or Down)
IntracellularCa++
Concentration
Beta-Blocker(drug)
Transfusion(or Hemorrhage)
Blood VolumeCentral Blood
Volume
CardiacOutput
HeartRate
Sino-AtrialNodeRate
NervousSystem
Response
BaroreceptorPressure
Modèle causaldans CIRCSIM
Famille de dialogues possible dans CIRCSIM
I haveno idea
TPR isneurally
controlled
Sympatheticvasoconstriction
Nervoussystem
Radius ofarterioles
Right
Right.TPR isneural.
And whatcontrols
that?
Nervoussystem
Right
(3) So what must be the value of TPR?
(1) Can you tell me what controls TPR?
(2) Remember that we’re in DR now.
<wrong>
POP
AutoTutorArt Graesser, Derek Harter, Peter Wiemer-Hastings, Natalie Person, et al., University of Memphis
Domaine: Architecture des ordinateursEmphase: Simuler le tuteur humain moyen Dialogue à initiative mixte comportant des questions
permettant le raisonnement profond Interface: Face parlante avec gestures et intonation
Flot du dialogue Prompt, Conseil, Assertion
Rétroaction Back channeling Feedback pédagogique (évaluation des réponses) Feedback correctif (remédiatif)
Répond aux initiatives de l’étudiant
AutoTutor avec la tête parlante Marco
Un exemple de dialogue tutoriel dans AutoTutorTUTOR-1: Alright, let's go on. You want to take photos and send them over the Internet. Consider this problem. What hardware do you need to take photos and send them over the Internet?
STUDENT-1: First of all you need to have access to the internet
TUTOR-2: What else?STUDENT-2: a cameraTUTOR-3: Yeah. For what type of connection do you need a network card?
STUDENT-3: network cardTUTOR-4: Okay. Now, if you have access to the Internet through a network card, then your connection is …
STUDENT-4: I don't know.TUTOR-5: Is direct. Okay. A network card is needed if you have a direct connection to the Internet. Okay. How does the user get hooked up to the internet?
STUDENT-5: by a plug.
TUTOR-6: Once again, a network card is needed if you have a direct connection to the Internet. Okay, what does a modem do?
STUDENT-6: connects network card and internet
TUTOR-7: Okay. Try this. A modem is required when there is …
STUDENT-7: a connectionTUTOR-8: a dial up connection. ...TUTOR-30: Let’s review. To send your photos on the Internet, you need either a digital camera or a regular camera to take the photos. If you use a regular camera, you need a scanner to scan them onto a computer disk. If you have a direct connection to the Internet, then you need a network card. A modem is needed if you have a dial up connection.
But: Aider les étudiants à apprendre via un tutorat par explication
Allant de : l’aprentissage par la pratique A: l’apprentissage par la pratique et l’explication
Motivé par les recherches en Sciences Cognitives sur le “Self-Explanation Effect”Comment permettre aux tuteurs de mieux supporter l’Auto-Explication ? Les étudiants expliquent-ils avec leurs propres
mots ? Est-il nécessaire de donner une rétroaction sur
les explications ?
Geometry Explanation Tutor
Étude 1: Explication ‘par référence’
Le feedback du tuteur indique si l’explication est correcte.
Étude 2:Et l’auto-explication sans rétroaction du tuetur sur les explications de l’étudiant?
Les étudiants produisent très peu de bonnes explications...
Hypothèse: Les étudiants apprennent mieux lorsqu’ils expliquent dans leurs propres mots et le tuteur les aide à rafiner leurs explications par le doalogue.
Un dialogue tutoriel pour supporter l’auto-explication dans GeometryExplanationTutor
Exemple de dialogue dans GeometryExplanationTutor
Student: angles are equalTutor: Are any two angles congruent? What tells
you that there are two congruent angles here?Student: angles in a triangle are equalTutor: That is a bit imprecise. Are ALL angles in
ALL triangles congruent?Student: angles in an isosceles triangle are equalTutor: Correct, except for one thing: are all three
angles in an isosceles triangle congruent?Student: base angles in an isosceles triangle are
equalTutor: CORRECT
INTERFACE USAGER
LCFLEX PARSER
FEATURE STRUCTURE
UNIFIER
LOGIC SYSTEM (Loom)
PRODUCTION ENGINE
COGNITIVE MODEL
SEMANTIC REPRESENTATION
of Explanation
FEATURE STRUCTURES
KNOWLEDGE BASE —Ontology
& Explanation Hierarchy
GRAMMAR & LEXICON
TUTEUR COGNIF
MODULE DE COMPRÉHENSION
LA LNSTATISTICAL CLASSIFIER
Student Explanation
Feedback or Help Message
Detailed Classification of
Explanation
Ballpark Classification of
Explanation
(Numerical)Answer or
Hint Request
STUDENT MODEL
Architecture de GeometryExplanationTutor
Connaissances pédagogiques: Hiérarchie d’explication
Exemple d’hiérarchie partielle pour l’explication du théorème des triangles isocèles
UNKNOWN
CONGR-ANGLES“The angles are congruent.”BASE-ANGLES
“These are base angles.”
BASE-ANGLES-CONG“Base angles are
congruent.”
CONGR-ANGLES-IN-TRI“Angles in a triangle are
congruent.”
TRI-BASE-ANGLES“Base angles in a triangle
are congruent.”
CONGR-ANGLES-IN-ISOS-TRI
“Angles of an isosceles triangle are congruent.”
ISOS-TRI-BASE-ANGLES“Base angles in an isosceles
triangle are congruent.”
ANGLES-OPP-SIDES“Angles opposite the sides are
congruent.”
ANGLES-OPP-CONGR-SIDES“Angles opposite congruent
sides are congruent.”
ISOS-TRIANGLE“The angles opposite congruent sides in
an isosceles triangle are congruent.”
OPPOSITE-ANGLES“Opposite angles are
congruent.”
L’auto-explication en langage naturel améliore l’apprentissage car :
“There is something about NL dialog that is right ...” Le langage naturel est naturel pour l’apprenant
Il est bien pour les étudiants d’expliquer en leurs propres mots… Pouquoi donc ?
L’explication en LN nécessite la rétention (le rappel) plutôt que la reconnaissance (CONT. CHI)L’articulation force l’attention sur les facteurs pertinents L’usage du verbal et du visuel crée une dualité en mémoire. Le LN permet une flexibilité dans l’expression des connaissances partielles
Les étudiants peuvent montrer ce qu’ils savent Le tuteur peut les aider à construire ce qu’ils ne savent pas
L’aide peut être incrémentale Le tuteur peut supporter plusieurs chemins de construction de connaissances
Un autre cas : DIALOGUE INTERACTIF POUR DES FINS DE REFLEXION
Le dialogue interactif dans ce contexte dépend de : (1) The goal of the diagnosis (deeper understanding (includes justified correction of an
error), knowledge construction) (2) The nature of the skill (Concept, Principle, Law, etc./Basic, non Basic)
(1) Generic Model of IDP based on the goal
(1.1) The goal is deeper understanding? Articulate the features of the problem
which elicit the skills (Implicit reflection) (2) The goal is knowledge construction?
Instantiate the 5 stages of explicit reflective thinking as defined by Dewey (Dewey 1933) in the context of the nature of the skill
Example of IDP for the principle related to a variable that is bound to a constant in the domain of Prolog Programming
Skill: Principle
If an element E is a Prolog Variable & this element is associated with a constant value V
Then E can only be associated with a
value equivalent to V in the same context (same Prolog command)
Start
Tutor presents a problem
Student Gives final answer/ performs next action, Asks for help
Is the answer correct ?
Tutor sends a positive evidence to the learner model, for the skill associated with that interaction
Tutor gives negative feedback
Tutor Triggers the NEXT interaction in the CURRENT diagnosis plan
Types of remediation targeted through interactive
diagnosis
-General comprehension
-Deep comprehension
-Knowledge construction
Tutor explains the skill associated with the interaction
NOYES
NO
Is the learner’s answers during the interaction correct?
Tutor sends a negative evidence to the learner model, for the skill associated with that interaction
YES
Done
Tutor takes the INTERACTIVE-DIAGNOSIS PLAN for the skill associated with the problem
There are no more interactions
Hypothesis (1)
Hypothesis (2)
Interactive diagnosis from which a general comprehension of the skills
associated with a problem is expected trough implicit reflective thinking
((Flavell 1979, Hartman 2001)
Research Background & RationaleGoalsGeneric Models & ChallengesImplementationRelated WorkEvaluation & Future Work
Plan de dialogue 1
Start
Tutor presents a problem
Student Gives final answer/ performs next action, Asks for help
Is the answer correct ?
Tutor takes the INTERACTIVE-DIAGNOSIS PLAN for the skill associated with the problem
Tutor sends a positive evidence to the learner model, for Sk(i)
Tutor gives negative feedback
Tutor triggers the NEXT interaction with the learner in the CURRENT diagnosis PLAN
Hypothesis (1) and Hypothesis (3)
Tutor articulates Sk(i)
NOYES
NO
Are the learner’s answers during an interaction correct? The Skill associated with the interaction is Sk(i)
Tutor sends a negative evidence to the learner model, for Sk(i)
Hypothesis (2)
Interactive diagnosis from which a deep comprehension of the skills
associated with a problem is expected through implicit reflective
thinking (Flavell 1979, Hartman 2001)
Tutor takes an INTERACTIVE-Diagnosis Plan for Sk(i)
Is Sk(i) a Basic Skill (does not necessitate the ellicitation of another intellectual skill)
Types of remediation targeted through interactive
diagnosis
-General comprehension
-Deep comprehension
-Knowledge construction
NOYES
YES Generate an Interactive Diagnosis PLAN to verify comprehension
Hypothesis (1,2,3)
Done + Show Skills tracing
There are no more interactions
Plan de dialogue 2
Start
Tutor Challenges the student with two (or more) situations that are contradictory and asks the
learner to make an appropriate inference
Tutor takes the INTERACTIVE-DIAGNOSIS PLAN for the skills associated with the target
Inference
Tutor sends a positive evidence to the learner model, for Sk(i)
Student Proposes an inference
Tutor triggers the NEXT interaction with the learner in the CURRENT diagnosis PLAN: Asks the learner to link an observation with a principle or the contradiction of a
principle, rules, law: Sk(i)(Depending of the inference that he drew)
Hypothesis (1)
NOYES
Has the student made a correct link?
Tutor sends a negative evidence to the learner model, for Sk(i)
Hypothesis (2)
Interactive diagnosis from which knowledge construction is expected
through explicit reflective thinking as in Dewey (Dewey, 1933)
Tutor explains Sk(i) by outlining its use in 2 conflicting situations (Dewey, 1933)
Types of remediation targeted through interactive
diagnosis
-General comprehension
-Deep comprehension
-Knowledge construction
There are no more interactions
To implement Hypothesis (3): Challenges the learner in that specific
skill
Done + Show Skills tracing
Plan de dialogue 3
Exemple de dialogue…
?- X= 37, Y= Z, Z=10, X=Y[T1] What is the result of this command?[L2] Success[T3] Hummmm, no not really
IDP for deeper understanding (non basic skill) Tutor tries to outline the conditions of the principle in this
particular context Tutor brings thelearner to a contradiction of the principle
[T4] What are the variables in this command?[S5] X,Y,Z
[Diagnosis: Students knows <identify a Variable>]
[T6] Right. Is there a constant value associated with X (If yes, give it)[S7] 37[T8] What are the other elements of the command associated with X?[S9] Y.....
?- X= 37, Y= Z, Z=10, X=Y[T1] This command will provide the result “Fail” in Prolog while[?- X= 37, Y= Z, X=Ywill result in “Success”
IDP for deeper understanding (non basic skill) Tutor tries to outline a situation where a conflict occurs Tutor fosters the learner towards the induction of a principle, fact,
procedure
[T4] What are the variables in this command?[S5] X,Y,Z
[Diagnosis: Students knows <identify a Variable>]
[T6] Which variables are associated to constants in the first command?[S7] X,Z[T8] Hummm, not really, which variable is associated with Z?
[Diagnosis: Students knows <apply transitive binding of Variables>]
[S9] Y.....
Implémentation dans Prolog-Tutor
Prolog-Tutor: Logic Programming Concepts
Skills of the domain in this context
Correctly identify and Use of basic structures (variabgles, constant, compound terms, facts, Prolog-rules, etc.)
Understand and apply the principle related to binding a Variable (Understand and perform Unification(1))
Understand Unification (Concept); Perform unification (Procedure)
Understand Resolution (Concept). Perform resolution (procedure)
Learner model = Skills
Domain Knowledge Elements
Implementation (2)
Prolog-Tutor: Logic Programming Concepts
Teaching: an example with RESOLUTION as a procedure (the learner has to perform it)
Dialogue initial plan: All the steps of the procedure Dialogue utterances:
Tutor question: What the learner should do at that step?
[Expected reflection: recall, organize, test the skills necessary at each step: Principles to apply, Concepts and Facts which define the conditions of the problem state and which will be used to test a principle]
[Expected remedial state: deeper understanding, correction]
Dialogue management: (see the paper of this workshop “Elaborating …”)
The initial dialogue plan may be adapted, when the learner model used The discourse may be accommodated or elaborated when the adapted
dialogue reflects some irregularities
Explanation after failure to answer to a question during an
interaction
Application of Hypothesis (2)
Diagnosis in Background: if the learner is unable to answer the question “What is the goal to prove”, the Tutor diagnoses the skill
“Understand the meaning of a GOAL in resolution”
Interactions: Tutor: Asks question to the learner in each step of the procedure after that he has failed to answer to a question
Application of Hypothesis(1)
Expectation of reflection when the tutor asks: “ What is the GOAL to prove in this problem”:
Recall: What is the purpose of a RESOLUTION? What is a GOAL in a resolution? What is the role
of Knowledge Base?
Interactive Diagnosis in Prolog-Tutor (Scenario of Slide 10)
Reflection Elicited: Implicit reflection through the articulation of a procedure
Enhanced or remedial cognitive state expected: General understanding of the skill (Apply a Resolution or Procedure of Resolution) (Slide 10)
Learner model: Skills of the domain with associated probabilities (Simulated)
Skills Traced by the tutor (at the end of all scenarios)
Reflection Elicited: Implicit reflection through showing to the learner his cognitive state as viewed by the system in terms of skills (we should add the interaction which justifies the inference of that cognitive state)
Enhanced or remedial cognitive state expected: General understanding of the elements of the domain
Skills Tracing allows the tutor to generate an exercise for a specific skill, when the learner
request it
ConclusionLes 3 générations de tuteurs diffèrent par Leur technologie sous-jacente Leur pédagogie Et les approches pour leur développement
Un apprentissage superficiel (non profond) peut survenir lorsque l’étudiant n’a pas encoder les aspects pertinents de la tâche CIRSIM, AutoTutor, Ms. Lindquist, et Geometry Explanation Tutor sont des exemples de T3G (Tuteurs cognitifs), Prolog-Tutor aussi.Intuitivement, le dialogue en langage naturel parraît très efficace et utile dans l’apprentissage mais il reste à déterminer (par la recherche) le QUAND et le COMMENT.