Theme 2 - Presentation

Aggregation and Multi-Actor Designs

Theme 2 - Presentation

Aggregation and Multi-Actor Designs

i2LOR-06 Conference, Montreal November8-10

2.1 Workflow models to provide multi-actor interactions (O. Marino)2.2 Active Learning Design for on-line real-time applications (H. Saliah) 2.3 Knowledge representation of actors, events and resources (G.Paquette) 2.4 Actors’ adaptive assistance (A. Dufresne)2.5 Functional aggregation of theme 2 components (G.Paquette)

Aude Dufresne, Olga Marino, Gilbert Paquette and Hamadou Saliah-Hassane

Projects

Project 2.1: Aggregation and Design of Multi-actors Learning Flows

Project 2.1: Aggregation and Design of Multi-actors Learning Flows

Project leader: Olga Marino, PI: Gilbert Paquette

Researchers: Karin Lundgen-Cayrol, Michel Leonard,Ileana de la Teja

Ph.D. Students: Dario Correal

Ms. Student: Alandre Magloire

Collaboration: Anis Masmoudi

2.1 Upgrades to the MOT+LD Editor

RULES(Principles)

EXTENDED SPECIFICOBJECTS

(Facts)

BASIC SPECIFICOBJECTS

(Facts)

ACTORS(Principles)

ACTIONS(Procedures)

RESSOURCES(Concepts)

Index by Typeof Element

Index byElement

Index by Class

Class

Item

Metadata

Prerequisites

Learningobjectives

Oncompletion

#1

Time limit #1

Number toselect #1

Staff role #1

Learner role#1

External unitof learning

SupportActivity

LearningActivity

ActivityStructure

Act

Play

Method

Search by index

Send-Mail

Conference

Learning object oroutcome

EnvironmentC ItemItem

R

Any Action(exceptActivity

Structure andexterna UoL)

R

Any Action(exceptMethod)

R

R

Any Action(except Method,

Play, Act)

R

R Environnement

IP

Any Resource

C

Oncompletion

R ActivityStructure

Number toselect

Time limit

Staff role

Learner role

C

C

Staff role

Learner role

Staff role

Learner role

P

Any Action(except Method

and Play)

Any Action(except Method

and Play)

IP

Any Action(except Method,

Play, Act)

Environnement

C

C

C

C

C

C

C

C

C

External unitof learning

ActivityStructure

Method

SupportActivity

LearningActivity

Act

Play

C

C

C

C

C

Conference

Send-Mail

Environment

Search by index

Learning objector outcome

Environment

IP LINK

P LINK

C LINK

R LINK

Item

I

I

I

Learner role

Activity Structure,Learning and Staff

Activity

Method , learningor staff activity

I

I

Index by typeof element

I

Search by index

Index by Class

Staff role

I

I

Any Ressource(except environmentand index search)

Index byelement

I

Learningobjectives

I LINK

Prerequisites

A

SupportActivity

A

AActivityStructure

LearningActivity

SupportActivity

AA

Learner role Staff role

A

ActivityStructure,

Learning andStaff Activity

A

Any Ressource(except

environment)

A

A

Learning object oroutcome #21

Environment #12

A

Item

A

A

Prerequisites

Learningobjectives

A

AAny Action

(except externalUoL)

Any Ressource

Class

Index byElement

Metadata

A LINK

2.1 MOT+LD Specification for Levels B and C

• Study and comparison of 4 workflow engines: – WFMopen, – BPEL from Oracle,– JBPM on JBOSS, – OMG workflow API

• Comparative study of learnflow and workflow meta-models – IMS-LD – XPDL

Comparison Aspects– static & dynamic domains

– Control flow

– Actor Representation

– Knowledge Referencing

2.1 State of the art in workflow / learnflow models, engines and languages

2.1 Specification of a generic multi-actor function editor

• Based on a subset of BPMN• Taking into account workflow

patterns• Taking into account main

ressource patterns

=» projection of model elements into IMS-LD

Participant An action performer

Group

A group of participants

Role Defines a expected behavior of an actor (s) during the process definition. This element has associated two attributes: Minparticipant : Defines the minimum number of participants that can belong to this role Maxparticipant: Defines the maximum number of participants that can belong to this role

Activity

A process activity

MultiActivity A process activity instantiated multiple times in execution

Product

A product produced by an activity

Tool

A tool used in an activity

Relations Symbol Description Control link

Simple link between two activities. It establishes precedence in time during execution. The target activity will be launched when the source ends.

Product Dependency Link

A link between two activities. The source activity sends a product to the destination activity. The target activity is started when the product is produced (data flow).

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

A student has the option to select one and only one activity among two possible ones. After finishing this learning activity a support activity starts its execution.

IMS-LDExample

Only one incoming path was executedUse

Diagram

“A point in the workflow process where two or more alternative branches come together without synchronization. It is an assumption of this pattern that none of the alternative branches is ever executed in parallel...”[2]

Description

Simple MergePattern 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 Learnflow support using a model driven approach*

Meta-model édition, visualisation and manipulation (for IMS-LD level A) using generic metamodeling (eclipse ecore + GMF)

* Alandre Magloire, Ms I.T

2.1 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

*D.Correal, Ph.D. engineering student, U.los Andes / Teluq

2.1 Process Viewpoints at the model level*

*Paper, D.Correal & O.Marino

Project 2.2: Distributed Aggregation and Control of Learning Objects

Project 2.2: Distributed Aggregation and Control of Learning Objects

Project leader : Hamadou Saliah-Hassane

Associate Researchers: Ileana de la Teja, Djamal Benslimane (IUT Lyon)

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

2.2 Online Laboratories• Practical work online• Active learning in real time • Various types of resources :

learning objects, communication tools

• Integrated into a multi-environment platform: the environments of the learner, the tutor, the administrator and the instructional designer

2.2 Building a Repository for Online Laboratories Learning Scenarios

We present a pedagogical model for online laboratory repositories of learning scenarios based on IMS-LD

Our approach consists of exporting the IMS-LD compliant XML file for learning scenarios built with MOT+LD

Storage procedure for laboratory metadata (LOM, PROLEARN ), instructional scenarios and learning objects.

IHttp://www...

IP

IP R

Trainer

SupportActivity #1

R

Team 3

Observer

I

Http://www...

C

Oscilloscope

CCC

SetupFunctiongenerator

Requestanalysis

C

Confrence#1

IP

IP

IP

Environment #3

Environment #2

Environment #1

RTeam 1

P

CC

P

P

CCC

SendinformationDetermine the

type of set up

Getfeedback

Activity:send signals

ActivityStructure #2

Activity Structure#1

2.2 Storage procedure

2.2 Meta Referencing Components and Applications PALOMA

2.2 Metadata• In distance-laboratories, learning objects are graphic

interfaces and real devices in a remote labs or hooked to a learner’s or tutor’s computer.

• Various metadata required to ensure granular and aggregative learning objects

• LOM (Learning Object Metadata) describe the basic properties of the LOs

• ProLearn metadata supplements the components missing in LOM to describe a distance-laboratory activity.

necessary pre-requisites, configuration required, learners’ roles and tasks, etc.

• Example : Spectrum Analyser with Metadata generated in Prolearn

2.2 Conceptual Model for Future Work Validate the above model using scenarios with

various measuring instruments and actors (users) in remote locations.

Four models used to describe a Learning scenario : content, learning strategy, media, delivery processes

Web services using WSFL or BPEL will be used to link these components.

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

The Virtual Lab Client query BPEL processes to retrieve information of a laboratory session for tutor or trainer supervision.

2.2 – Towards a General Framework

CLIENTS

WEB

SERVER

HOSTING ENVIRONMENT

INTERNET

INTERNET

LAN

Computing resourcesNetwork connectionsDataDevices

MiddlewareJini service

Web ServiceWSDL

Devices

Devices

RTLabQnx real timeSystem

Sun SolarisClustersHPC

InstrumentsInterconnectsPXI, VXI, RS232,TCP/IP

Business Layer

Learning scenariosBPEL

engine

Service BrokerPlanner/Scheduler

Grid container

App Server

LDAPService lookup

Registration mgrGSH/GSR

Service ObjectsWeb Service

engine

HTTPS

Project 2.3: Knowledge and Competency Modeling of Resources and Actors

Project 2.3: Knowledge and Competency Modeling of Resources and Actors

Project leader : G. PaquettePI(s) : R. Hotte, O.MarinoAssociate Researchers : I. de la Teja, K. Lundgren-Cayrol, Diane Ruelland, Michel LéonardGraduate Students: J. Contamines, L. Moulet, V. Psyché, D. Rogozan , A. Brisebois

2.3 - MOT+ OWL Graphic Editor

User-friendly totally graphic editor Compliant with the OWL-DL standard Based on Description Logic Guaranties computability Used for the TELOS technical ontology Used for a Learning Design ontology Export OWL-DL XML files Successful exports to PROTEGE

2.3 Competency-based Semantic Annotation

Compare planets by mass autonomously

Compare planets by orbital period autonomously

Analyze, relations between planet mass and orbital period

2.3 Adding a MetricSelf-manage (10)

Evaluate (9)

Synthesize (8)

Repair (7)

Analyze (6)

Apply (5)

Transpose (4)

Interpret (3)

Identify (2)

Memorize (1)

Pay attention (0)

.

Planet mass and orbital period

Skills Scale

Performance Scale

Aware Familiarized Productive Expert

Peter M6.3

Video Y.

4.9

Book X7.7

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

2.3 Identify Abandon Risk*

Learner

Tutor

Designer

System

LEGENDL

T

S

D

Calculate

GroupIndicators(Ex: actual Competencyvs target)

S

CompareDiagnose

S

Individual /groupdiagnosis

CommunicateDiagnosis toA, T, D and S

DiagnosisInterface

Trace eachlearner and tutor

evaluation

Competency,Affective,Social,metacognitivedata (from tools)

L T S

RRR

Build the LDand the envirn’t

Model ofthe envirn’t,the task (LD)the domainontology andentry/target competency

D

EC TCL2CG2CT2C

L1CG1CT1C

* Anne Brisebois, PhD Work

2.3 Equilibrate Competency in a LD*

Components of a function around activities must

reach competence equilibrium . .

Components of a function around activities must

reach competence equilibrium . .

C CC

C

P

P

P

Act 5

Activity 5.4

Activitiy 5.1

Activity 5.2

Activity 5.3

7.4

TC:

7.4

TC: TC:7.4

EC:6.4

TC:7.4

TC:5.2

EC:5.2

R

IP

IP

Productresource

Inputresource

Inputresource

TrainerLearner

IP

R

* Julien Contamines, PhD Work

2.3 Model Learner for ePortfolio *• Analysis of an existing ePortfolio open source : Open Source

Portfolio (OSP, http://www.osportfolio.org/) • ePortfolio model structure defined : personal information, domain

and transversal competencies, internal links semantic• Analyse of standards:

– IMS: ePortfolio, Learner Information Package, Reusable Definition of Competency or Educational Objective

– CEN: Guidelines for the production of learner information standards and specifications (CWA 14926), Recommendations on a Model for expressing learner competencies (CWA 14927), A European Model for Learner Competencies (CWA 15455),

– IEEE: Public and Private Information for Learners (PAPI Learner, IEEE P1484.2)

• Choice of computer representation of the model and functional specifications

* Lucie Moulet, PhD Work

2.3 – Maintain Referencing Consistency through Ontology Evolution*

OntoAnalyseur

Identify the effects of ontology changes on the semantic referencing of

objects

UKIsModificateur

Modify the reference links of objects to allow them to properly refer to the new

ontology version

A MOT+ Graphic OWL Editor

* Delia Rogozan, PhD Work

Project 2.4: Adaptive Assistance Models and Tools

Project 2.4: Adaptive Assistance Models and Tools

Project leader : Aude Dufresne

Graduate Students : Mohamed Rouatbi - École PolytechniquePatrick Fulgence Goudjo-Ako – LICEFFethi Guerdelli -Doctorat en Informatique Cognitive – UQAMVilliot-Leclercq, Emmanuelle - CLIPS IMAG, Grenoble

2.4 - Actors Adaptive Assistance

Support users in the execution of functions in multiple applications

???

Static or DynamicStatic or DynamicDifferent in their implementationsDifferent in their implementationsEvolvingEvolvingRunning simultaneouslyRunning simultaneously

Explore integration

Communicate structures of information between

applications initially and dynamically

Integrated environment for support

2.4 – Integration of support

Coordinate assesment,

Integrate support

Facilitate help definition

2.4 Integration and ontology alignment using SESAME

Integration Mohamed Rouatbi

2.4 Interaction using the ontology in SESAME

InteractionAssistanceMohamed Rouatbi, Patrick

Fulgence, Goudjo-Ako

An example

EFDAuteur Explor@Graph

Generic Advisor

2.4 - Integration of assistanceusing OWL ontologies

XMLSchema Ontologies fortasks, domains

user modelsapplications

ExploraGraph EditorStructures of concepts

and tasks

An ApplicationA Resource

Generic Advisor

Generic Rule Editor

ExploraGraph Navigator with

Adaptive support

XSD structures and XML instances

XML Structures of objects and rules

Events

AdaptationFeedback

XML instances

EventsAdaptationFeedback

XSDXSD

XML Instances

ELearning applications

Adaptive support applications

Domain applications

RDF Description of objects, rules, user models

owlowl

Owl structures exported using

Protege API

2.4 - Distributed Integration of support

Resource

The integration using the ontology adds a visualization of

the link to a ressource node and the properties of that ressource

Integration with PALOMA Ressource Manager using BPEL

Distributed integration of support

2.4 – Project Results

Prototypes Generic Editor - C* Edition of rules using structures Generic Advisor - Java expert system Rights Manager C* Explor@GraphNet VB.Net version of Explor@Graph navigator In progress: Exportation of Graphs from Expor@Graph Editor Planned: To use Sesame repository to keep User Models and rules from EG; Integration of Generic advisor in EGN and other TELOS application using JCM

Models and applications– Prototype of support in the EXAO environment– Develop the embedding of support to teachers – Case study of a collaborative scenario ICALT’2006– BEST - Case of the Virtual Doctoral School

2.5 Functional Aggregation2.5 Functional Aggregation

• Goals of the project– Integrate software components from the other

project in theme 2– Explore new aggregation possibilities and tools

report to help orient theme 6 work– Put to the test TELOS central services to built

specific aggregates using theme 2 and other components

– Put the aggregates to functional tests– Specify improvements needed to theme 6 and

other themes

2.5 Project Contributions

2.5 Partial Aggregation in project 2.4• Micro-aggregation PALOMA and Explor@GRAPH• Macro aggregation using Sesame, BPEL and the TELOS

Function Editor

2.5 Partial Aggregation in project 2.2• Aggregating PALOMA, Concept@ LCMS and Virtual Lab

Tools using BPEL and TELOS function editor

2.5 Global Integration Scenario(Components)

• Function Editor– Function Editor/Paloma

aggregate• SOCOM (components

Manager)• Knowledge and

Competency Editor Annotator

• Generic Advisor• Explor@Graph

– Explor@Graph/Paloma micro-aggregate

– Explor@Graph Editor– Explor@Graph User

Manager

• Concept@• Remote Virtual Laboratory

(RVL)- RVL micro-aggregate- Spectrum Analyzer Client - Labader User Manager - Spectrum Analyzer Server

• PALOMA• PALOMA Users manager • PALOMA Folder Manager• PALOMA LOM Manager

• Sesame

2.5 Global Integration Scenario(Scenario)

1. Technologist (Actor 1) uses the Function Editor to compose a LKMS composed of the above components enhancing the Concept@ LCMS

2. Designer A (Actor 2) – Use the LKMS to create a VLAS (RLV micro-aggregate)– Use the K&C editor to represent the domain and define target

competencies for the VLAS– Use PALOMA to search for useful LOMS and associate LOs to

VLAS activities– Use the GEN ADVISOR to add advices to activities– Store the VLAS and attachments into SESAME

2.5 Global Integration Scenario(Scenario cont.)

3. Designer B (Actor 3) • Loads the VLAS from SESAME into Explor@Graph to view• Loads the VLAS from SESAME into the Function Editor to

modifiy it to an IMS-LD compliant LD with the same attachments

• Stores it back into SESAME

4. Tutor (Actor 4) – Authenticates in the VLAS through the tutor view– Uses SpectrumAnalyseServer to book a RVL session– Loads reservation information using the RVL micro-aggregate

5. Learners (Actor 5)– Authenticate with the RVL in their own version of the VLAS – Tutor set learners rights in Spectrum Analyzer – Learners use SpectrumAnalyzerClient assisted by tutor– Learner with tutor evaluate actual competencies and receive

advice from GenericAdvisor.

2.5 Principles illustrated in the process

• Graphic aggregation• Ontology referencing• Interchangeability of activity editors• Multi-actor scenarios (LD)• Multi-Technology integration• Seemless interfacing• ………

Theme 2 - Presentation

Aggregation and Multi-Actor Designs

Theme 2 - Presentation

Aggregation and Multi-Actor Designs

i2LOR-06 Conference, Montreal November8-10

Aude Dufresne, Olga Marino, Gilbert Paquette and Hamadou Saliah-Hassane