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
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2- Potential field components computation
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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
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