T HEME 2: L EARNING OBJECTS D ESIGN AND A GGREGATION EFPC/CSPS Resource Modeling Resource Modeling Task Modeling Task Modeling User, Knowledge/ Competency.

THEME 2: LEARNING OBJECTS DESIGN AND AGGREGATION

EFPC/CSPSResourceModelingResourceModeling

TaskModeling

TaskModeling

User,Knowledge/Competency

Modeling

User,Knowledge/Competency

Modeling

AssistanceModeling

AssistanceModeling

Aggregation/OrchestrationAggregation/Orchestration

2.1, 2.4 2.2

2.3, 2.4

2.4, 2,3

2.5

PROJECT 2.1: MULTI-ACTOR LEARNFLOW DESIGN AND AGGREGATION

Project leader: Olga Marino, PI: Gilbert Paquette

Researchers: Karin Lundgen-Cayrol, Michel Leonard,

Ph.D. Students: Dario Correal

Ms. Student: Alandre Magloire

Collaboration: Anis Masmoudi

2.1 A - Study of Workflow Control Cases and Condition

Objects

Based on a subset of BPMN

26 control patterns Taking into account

workflow patterns Taking into account

main ressource patterns

=» projection of model elements into IMS-LD

Pattern Synchronizing Merge Description “A point in the workflow process where multiple paths converge into one

single thread. If more than one path is taken, synchronization of the active threads needs to take place. If only one path is taken, the alternative branches should converge without synchronization. It is an assumption of this pattern that a branch that has already been activated, cannot be activated again while the merge is still waiting for other branches to complete.”[2]

Diagram

Use Based on control data one or multiple branches could be executed in parallel but it is necessary to synchronize all the concurrent activities before continue with the next activity.

IMS-LD Example

At some point in an IMS-LD course some role-parts are executed. Before continue with the next act it is necessary to synchronize the end of the role-parts.

Priority High[ ] Medium-High [ ] Medium-Low[ ] Low[ ]

2.1 B- Contribution to the Specification of the TELOS Scenario Editor

Reinterpreting BPMN symbols in MOT terms

Defining type and sub-types

Defining object properties

Linking to TELOS technical ontology

2.1C- Adaptation and translation of Scenario Models to the IMS-LD format

Making graphic EML more natural: 2 options

1. Emulate Year 3 MOT+LD graphic editor

2. Translate general TELOS scenario to IMS-LD

MOT+LD Symbols

TELOS Scenario IMS-LD Manifest

Parser

2.1 D Specification of the MOT+IMS-LD editor for levels B&C

Properties : TELOS Input resources (variables) to functions, activities, operation

Conditions: TELOS Event-based conditions, split, merge

Monitoring, notification: TELOS Operations

2.1 E – Definition and execution of multiple viewpoints in workflow processes

General Objective Provide a flexible mechanism to define,

weave and execute viewpoints in workflow without modifications on the processes.

Viewpoints Used to express crosscutting concerns in

processes, in a modular and independent way,

Strategy Proposed To provide a formal language to define

viewpoints at a model level using the AOM (Aspect Object Modeling) principles

To provide a mechanism to weave viewpoints and processes

To provide a mechanism to execute viewpoints and processes

PROJECT 2.2: Service Aggregation and Control of Learning Objects

Project leader : Hamadou Saliah-Hassane

Associate Researchers: Djamal Benslimane (IUT Lyon)Maarouf Saad (ÉTS Montréal)

Graduate students : Mohamed Mhamdi (PhD); Joe Sfeir (M.Sc.A)

2.2 Prototypes, Components and Web Services

Prototype of a Spectrum Analyser Multi-User Interface allowing remote access to the real device

Laboratory User Manager Web Service Component

Laboratory Web Session Notification Component

BPEL Module integrated to the Online Laboratory Environment

Data Base Component Compliant with the Laboratory User Manager Web Service Component and the Laboratory Web Session Notification Component

Real Time Intelligent Robot Control for Education

BPEL Processes are used to put laboratories on-line, to reserve sessions for participants and to execute the interaction with the users.

The GU2005 Client queries BPEL processes to retrieve information of a laboratory session for tutor or trainer supervision.

2.2 Use of BPEL Processes

BPEL Processes invoke Remote and Local Web Services

2.2 Use of BPEL Processes

Pedagogical scenario

Content model

Learningstrategy model

Media model

Delivery model

Knowledge&

Competencies

Activities (processes)performed by actors

Form of resources

Management&

services

RemoteWeb services

LocalWeb services

InvokeBPEL

Translate

Activities (processes)performed by actors

2.2 TELOS Integration

ConnecteursTELOS

Components integration into TELOS can be achieved through Web Service of JAVA Connectors

2.2 A Lab Instrument Web Service

Spectrum Analyser Server(Service Web)

Agilent Spectrum Analyser E4411B

VISA-COM, IntuiLink & Other

SocketShared

VariablesSOAP

Network Interfaces to access to the instrument Server

Dynamic interaction with the instrument

APIs Access to the Instrument

Real Device

Internet Protocol

Spectrum Analyser Clients(Java Applets Java hosted in web page, Scripts de

Web Server Scripts, Standard Windows Applications, Applications for PDA)

TELOS Connector

User Interfaces

2.2 Top Down & Bottom Up Senarios, Real Devices & Software Components Aggregation

R

ServiceVisibility

R

ServiceParameter

R

R

ServiceTypes

hasServiceType

R

1

hasServiceVisibility

RR

11

RR

RR

LibraryLocationLibraryName

hasLibraryLocationhasLibraryName

R

1

R

R

RequiredLibraryhasRequiredLibraries

R

1

R

R

hasInvocationMode

InvocationMode

R

R

1R

R

ServiceVersion

hasServiceVersion

R

R

RR

ComponentServices

1

R

hasServiceName

ServiceName

R

R

R

1

hasServiceReturnedTypehasServiceParameter

SeviceReturnedType

R

1

RServiceAnnotationhasAnnotation

Online laboratory Senario= {Activities}

R

R

hasComponent

TheoryR

R

R

R

Roles

Environments

Components

R

R

R

R

LD

R

Learning-objectives

R

1

R

Method

hasObjective

hasPrerequisitehasMethod

prerequisites Equi

R

R

hasRole

hasActivity

hasEnvironment

Activities

R

Instructional scenario

ComeFromTheory

R

XML Mapping

Documents

BPEL Model

BPEL Files (or WSDL)

Laboratory Real Devices

Pioneer P3ATAll Terrain Robot

Differential Steering

Sensors and Actuators•Sonar•Laser Range Finder•GPS•Gyroscope•PTZ camera•5 d.o.f. armComputers and Network Infrastructure•PC-104 onboard computer•Wi-Fi

ContributionObjective parameter computation•New potential functions•Elimination of the oscillations

IntroductionBehavior-based method•Gradient descent•No prior knowledge of the environment

ApplicationsRemote control•Exploration•Security•Transportation•TeachingMethod

1- Parameter computation

Environment taken without obstacles: Quadratic system

),,(),,( pn Tf

2- Potential field components computation

2

22

2

2

)()(22

1 0

0

22

)()(

1

)()(2

1

R

yyxx

bbet

n

i

iR

D

o

mo

bbb

tt

ob

eyyxxk

de

n

yyxx

3- Force and desired velocity computation

gradF

VmVF

Simulation Results

0 5 10 15 20 25 300

5

10

15

20

25

30

x (m)

y (

m)

Robot trajectory, obstacles and iso-potential lines

Robot

Target

Obstacles

051015202530

0

10

20

30

0

1

2

3

4

x 104

Artificial potential field and robot "sliding"

x (m)y (m)

0 5 10 15 20 25 300

5

10

15

20

25

30

x (m)

y (

m)

Robot trajectory, obstacles and iso-potential lines

Robot

Target

Obstacles

05

1015

2025

30

0

5

10

15

20

25

30

0

0.5

1

1.5

2

x 104

x (m)

Artificial potential field and robot "sliding"

y (m)

tob

2.2 Simulation Method

Get acquainted with basic ideas of mobile robotics

Understand and design a scientific experiment

Study and modify a C++ program

•Perception / Sensors•Sonar•Laser Range Finder

•Movement / Actuators•Translation•Rotation

•Measure robot’s velocity

•Compute acceleration by differentiation

•Filter the resulting signal

•Plot the graphs

0 2 4 6 8 10 12 14 16 18 20-0.5

0

0.5Vitesse - Lecture directe

Temps en secondes

Vitesse e

n m

/s

0 2 4 6 8 10 12 14 16 18 20-0.5

0

0.5Acceleration - Derivation numerique de la vitesse

Temps en secondes

Accele

ration e

n m

/s2

0 2 4 6 8 10 12 14 16 18 20-0.5

0

0.5Acceleration - Derivation numerique de la vitesse

Temps en secondes

Accele

ration e

n m

/s2

•Look up and identify classes related to the robot

•Develop classes relevant to the particular application

•Compile, test and finalize

Behavioral functions•Tele-operation•Emergency stop•Autonomous navigation

Ready made behaviors•Wander•Reading Sonar Data•Reading LRF Data•Distance traveling

2.2 Interactive Learning Scenarios

PROJECT 2.3: Actor and Knowledge Models for Semantic Aggregation

Project leader : G. PaquettePI(s) : R. Hotte, O.MarinoAssociate Researchers : K. Lundgren-

Cayrol, Diane Ruelland, Michel LéonardGraduate Students: J. Contamines, L.

Moulet, D. Rogozan , A. Brisebois, M. Héon

2.3A - MOT+ OWL Graphic Editor

2.3B Conceptual Specification of a Ontology Based Competency Editor

2.3C Competency Management Process and Tools

2.3D Ontology Evolution and Referencing (D. Rogozan)

Validation of SAM utility 6 subjects in LORIT laboratory Positive for an advisor system

due to the rich semantic that is embedded in resource referencing

Perspectives → reengineering of SAM based on a Change Ontology

combined with an inference reasoner

Analyses Change Effects on resources referencing

SAM – Component 1

Identifies Changes applied to ontology version VN to obtain VN+1

SAM – Component 2

Modifies Semantic Referencing to preserve - access to resources- consistent interpretation via VN+1 ontology version

Changes in ontology may have side-effects on resources referencing loss of access to resources, modification of resources interpretation

Our contribution managing the inter-linkage between resources and evolving ontology

with the SemanticAnnotationModifier (SAM) SemanticAnnotationModifier (SAM) plug-in for ontology editors

2.3E Evolving and Multi-viewpoints Learner Model (L. Moulet)

Learner model containing: Personal and professional

information Domain and core

competencies ePortfolio (learner's

productions)

Model evolving with the learning

Interactions with learning systems managed by contracts

Multi-viewpoint model: A viewpoint for each role or

each actor involved with the learner (peers, professor, tutor, administrative staff…)

Learner ModelPersonal and professional information

Core competencies

Domain competencies ePortfolio

Context

2.3F Competency Equilibrium (J. Contamines)

Problem statement Competency Equilibrium of scenarios during design and runtime

Motivations During design : help to produce pedagogically consistent scenarios

Verifying the coherence of the resources selected by the designer according to target goal of the scenario

During runtime : help tutors to give efficient support and learners to accomplish learning activities

Examples - according to learners’ competencies, allow: Modification of the scenario by the tutor Automatic suggestion of new resources for learners

Contributions A formalism to express competency equilibriums and a reasoner to

analyze them Both using the semantic referencing of resources (knowledge and competencies)

A tool to visualize equilibrium’s evolution and to provide advices

Self-manage (10)

Evaluate (9)

Synthesize (8)

Repair (7)

Analyze (6)

Apply (5)

Transpose (4)

Interpret (3)

Identify (2)

Memorize (1)

Pay attention (0)

.

Multimedia Production Method

Skills

Performance Aware Familiarized Productive Expert

Peter M8.4

Video Y.

6.9

Book X9.7

8.6

2.3G Transformation of MOT+ Models to Ontology Representation (M. Héon)

PROJECT 2.4: Adaptive Assistance Models and Tools

Project leader : Aude Dufresne

Graduate Students : Mohamed Rouatbi - UdeM - École PolytechniquePatrick Fulgence Ngoudio-Ako – LICEFFethi Guerdelli - DIC – UQAMEmmanuelle Villiot-Leclercq - CLIPS IMAG,

Grenoble

2.4A Prototypes, software components, Web services

ODIS system : a framework to use ontologically based data integration.

We have implemented the integration between the Concept@ system and Explor@Graph function editor, using SESAME to exchange structures of activities which are aligned to a generic structure.

Explor@GraphNet interface that reads the ontological structure in the SESAME database and display it for WEB navigation

We are developing Export and Import of the structures of activities from the TELOS Scenario editor and from Explor@Graph to define support.

Reconnection of the Explor@Graph system with the new LORNET resource manager.

2.4B Integration and ontology alignment using SESAME

2.4C Integration and support using shared ontological structure

ODIS

Import and export using queries

Use Explor@Graph Editor and Ontologies to define supportUse Classes and transitive relations to

Highlight all prerequisite tasksUpdate user models on structure of concepts or tasks

Select all nodes with a prerequisite relation to a node

Select DISTINCT X from{Edge} ns10:Target_node_uid_eg {"2068"^^xsd:long},{Edge} ns10:Src_node_uid_eg {X},{Edge} ns10:EdgeType {ns10:Prerequis},{Node} ns10:NodeID {X}using namespace owl = <http://www.w3.org/2002/07/owl#>, ns10= <http://www.owl-ontologies.com/unnamed.owl#>, xsd = <http://www.w3.org/2001/XMLSchema#>

2.4D Generic framework for adaptive assistance

ODIS makes it possible to display as a graphic browser structures of concepts, resources or activities extracted from different applications

Explor@Graph may import those structures to define support rules on them.

Generic Advisor can display help in different applications.

PhD thesis experimenting a supportive environment to reuse scenarios - Villiot-Leclerc, 2007

On going research on the development of an evaluation and adaptation framework for adaptive and support functions (Guerdelli FQRSC)

PROJECT 2.5: Global scenario and Orchestration of Theme 2 Components

PIs : Gilbert Paquette, Aude Dufresne,

Olga Marino, Hamadou Saliah

Graduate Students : Anis Masmoudi Mohamed Rouatbi Patrick Dumont-Burnett Dario Correal

o Integrate software components from the other projects in theme 2

o Test TELOS central services by building aggregates using theme 2 components

o Explore new aggregation possibilities

o Put the aggregates to functional tests

o Specify needed improvements for TELOS

2.5 Global Integration Scenario (Components)

ResourceModelingResourceModeling

TaskModeling

TaskModeling

Knowledge/Competency

Modeling

Knowledge/Competency

Modeling

AssistanceModeling

AssistanceModeling

Aggregation/OrchestrationAggregation/Orchestration

• Generic Framework for adaptive assist.• Explor@ Graph• Generic Advisor• Learner Model using Multiple Viewpoint

• Remote Virtual Laboratory (RVL) • Instruments models• Scenario Models• Mobile Robot Models

• PALOMA Res. Man.• SOCOM Comp. Man.• Semantic Annotator

• MOT + OWL• Competency Editor• Competency +• ODIS/Sesame for Ontology Alignment

• Evolving Ontology Ress. Referencing• Competency Annotator• Model Transformation

• Multiple Viewpoint Workflows • Explor@ Activity Editor Web Services

• Scenario Editor• MOT+ LD• IMS-LD Export

2.5 Virtual Lab Application aggregation

2.5 Platform Aggregation

2.5 Converters and TELOS Operations

SCORM format to TELOS scenario editor format

Scenario Editor format to OWL format

OWL format to the Scenario Editor format

OWL Scenario Editor format to OWL Explor@Graph Net format and conversely (aligning ontologies using ODIS/SESAME)

2.5 On-going Work

Graphic aggregation Ontology referencing and

alignment Interchangeability of activity

editors Multi-actor scenarios (IMS-LD) Multi-Technology integration Seemless interfacing Test of the basic TELOS

aggregation mechanisms

THEME 2: LEARNING OBJECTS DESIGN AND AGGREGATION