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Theme 2: Learning objects Design and Aggregation


EFPC/CSPS THEME 2: LEARNING OBJECTS DESIGN AND AGGREGATION User, Knowledge/ Competency Modeling 2.3, 2.4 2.1, 2.4 2.2 2.5 Task Modeling Aggregation/ Orchestration – PowerPoint PPT presentation

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Title: Theme 2: Learning objects Design and Aggregation

Theme 2 Learning objects Design and Aggregation
User, Knowledge/ Competency Modeling
Resource Modeling
Task Modeling
Aggregation/ Orchestration
Assistance Modeling
Project 2.1 Multi-actor Learnflow design and
  • 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

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
  • Emulate Year 3 MOTLD graphic editor
  • Translate general TELOS scenario to IMS-LD

2.1 D Specification of the MOTIMS-LD editor for
levels BC
  • Properties TELOS Input resources (variables) to
    functions, activities, operation
  • Conditions TELOS Event-based conditions, split,
  • 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
  • To provide a mechanism to execute viewpoints and

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
  • Laboratory User Manager Web Service Component
  • Laboratory Web Session Notification Component
  • BPEL Module integrated to the Online Laboratory
  • 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

2.2 Use of BPEL Processes
  • 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

2.2 TELOS Integration
Components integration into TELOS can be achieved
through Web Service of JAVA Connectors
2.2 A Lab Instrument Web Service
2.2 Top Down Bottom Up Senarios, Real Devices
Software Components Aggregation
2.2 Simulation Method
  • Contribution
  • Objective parameter computation
  • New potential functions
  • Elimination of the oscillations
  • Introduction
  • Behavior-based method
  • Gradient descent
  • No prior knowledge of the environment
  • Applications
  • Remote control
  • Exploration
  • Security
  • Transportation
  • Teaching

1- Parameter computation Environment taken
without obstacles Quadratic system
2- Potential field components computation
  • Pioneer P3AT
  • All Terrain Robot
  • Differential Steering
  • Sensors and Actuators
  • Sonar
  • Laser Range Finder
  • GPS
  • Gyroscope
  • PTZ camera
  • 5 d.o.f. arm
  • Computers and Network Infrastructure
  • PC-104 onboard computer
  • Wi-Fi

3- Force and desired velocity computation
Simulation Results
2.2 Interactive Learning Scenarios
Study and modify a C program
  • Perception / Sensors
  • Sonar
  • Laser Range Finder
  • Movement / Actuators
  • Translation
  • Rotation
  • Measure robots velocity
  • Compute acceleration by differentiation
  • Filter the resulting signal
  • Plot the graphs
  • Look up and identify classes related to the robot
  • Develop classes relevant to the particular
  • Compile, test and finalize

PROJECT 2.3 Actor and Knowledge Models for
Semantic Aggregation
Project leader G. Paquette PI(s) R. Hotte,
O.Marino Associate Researchers  K.
Lundgren-Cayrol, Diane Ruelland, Michel
Léonard Graduate 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.
  • 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) plug-in
    for ontology editors

SAM Component 1
  • 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

Identifies Changes applied to ontology version VN
to obtain VN1
Analyses Change Effects on resources referencing
SAM Component 2
  • Modifies Semantic Referencing to preserve
  • access to resources
  • consistent interpretation via VN1 ontology

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
  • Multi-viewpoint model
  • A viewpoint for each role or each actor involved
    with the learner (peers, professor, tutor,
    administrative staff)

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
  • During runtime help tutors to give efficient
    support and learners to accomplish learning
  • Examples - according to learners competencies,
  • Modification of the scenario by the tutor
  • Automatic suggestion of new resources for
  • 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 equilibriums evolution and
    to provide advices

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
Polytechnique Patrick Fulgence Ngoudio-Ako
LICEF Fethi Guerdelli - DIC UQAM Emmanuelle
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_at_ system and Explor_at_Graph function editor,
    using SESAME to exchange structures of activities
    which are aligned to a generic structure.
  • Explor_at_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_at_Graph to define support.
  • Reconnection of the Explor_at_Graph system with the
    new LORNET resource manager.

2.4B Integration and ontology alignment using
2.4C Integration and support using shared
ontological structure
Select all nodes with a prerequisite relation to
a node Select DISTINCT X from Edge
ns10Target_node_uid_eg "2068"xsdlong, Edge
ns10Src_node_uid_eg X, Edge ns10EdgeType
ns10Prerequis, Node ns10NodeID X using
namespace owl lthttp//
gt, ns10 lthttp//
.owlgt, xsd lthttp//
Import and export using queries
Use Explor_at_Graph Editor and Ontologies to define
support Use Classes and transitive relations to
Highlight all prerequisite tasks Update user
models on structure of concepts or tasks
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_at_Graph may import those structures to
    define support rules on them.
  • Generic Advisor can display help in different
  • 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
  • Integrate software components from the other
    projects in theme 2
  • Test TELOS central services by building
    aggregates using theme 2 components
  • Explore new aggregation possibilities
  • Put the aggregates to functional tests
  • Specify needed improvements for TELOS

PIs Gilbert Paquette, Aude Dufresne,
Olga Marino, Hamadou Saliah Graduate
Students  Anis Masmoudi Mohamed Rouatbi
Patrick Dumont-Burnett Dario Correal
2.5 Global Integration Scenario (Components)
Knowledge/ Competency Modeling
Resource Modeling
Task Modeling
Aggregation/ Orchestration
Assistance Modeling
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_at_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
Questions ?