ICALT-06, Kerkhade, The Netherlands,July 5-7, 2006

Knowledge, Competency and Educational Modeling for

Lifelong Learning

Gilbert Paquette

LORNET and CICE DirectorLICEF Research Center, Télé-université

www.licef.teluq.uquebec.ca/gp

1- The Global Context

L3: Lifelong LearningL3: Lifelong Learning

Knowledge Management: Enhancing Knowledge Management: Enhancing Human CompetencyHuman Competency

Access to huge ressource/knowledge Access to huge ressource/knowledge repositoriesrepositories

Personalization contextPersonalization context

Towards the (more) Intelligent WebTowards the (more) Intelligent Web

Knowledge Management:Enhancing Human Competency

More than « glorified » document management

At the knowledge level

The goal: knowledge and competency sharing in an organization

Competency implies higher level knowledge

Central role for competency-based Instructional engineering.

Information Knowledge

CognitiveEngineering

InstructionalEngineering

SharedKnowledge andCompetencies

Huge Ressource / Knowledge Repositories on the Web

(Not that available)

MERLOT

EDNA

ARIADNELORNET NIME

Towards a More Intelligent Web

First wave: First wave: STATIC TEXT / DATA EXCHANGESTATIC TEXT / DATA EXCHANGE

Second wave: Second wave: DYNAMIC / MULTIMEDIADYNAMIC / MULTIMEDIA

Third wave: Third wave: SEMANTIC SEMANTIC

PROGRAMMABLEPROGRAMMABLE

PERSONALIZABLEPERSONALIZABLE

Ontology

Semantic annotations to resources enable “intelligent processing”: search, matching, guiding,…

1. Inter-operability

2. Multi-actor

Design

5. Advance

dMultimed

ia 4. KnowledgeExtraction

3. Adaptive

Resources

6. TELOS

LORNET Project - TELOS

Pan-canadian Research Network6 Universities, 4 Research Chairs, 15 entreprises5 years, 7.5 M $, 120 investigators

Develop tools and

methods to build

personalized access

to learning object

repositories

through the Semantic Web

for learning and Knowledge

Management

Personalizing Learning(TELOS Main Use Cases)

<Engineer>

Extend TELOSCore

<Technologist>

Use Core toProduce LKMS

(Platforms)

<Learner> <Administrator>

Support Generation Operations

<Facilitator>

<Designer>

Use LKMS to Produce LKMA(Environments)

Use LKMA to Produce LKMP

(Products)

TELOS Core

LKMAManager

(ApplicationAggregation)

LKMS Manager

(Platform Aggregation)

TELOS CoreModifier

LKMS LKMA

Resource Libraries

LKMS Library

LKMA Library

Tertiary Resource Libraries

LKMP

LKMP Library

LKMPManager

(ePortfolioAggregation)

TELOS High-Level View

Distributed

Service oriented

Ontology-Driven

Component Aggregation

2- Knowledge Extraction: Processes and Tools

The MOT Modeling LanguageThe MOT Modeling LanguageTypology of Knowledge ModelsTypology of Knowledge ModelsMethods: Methods:

Co-Modeling, Co-Modeling, Knowledge Engineering, Knowledge Engineering, Loose and Formal ModelingLoose and Formal Modeling

MOT+ SpecializationsMOT+ SpecializationsMulti-actor workflowsMulti-actor workflowsOntologiesOntologies

Information Knowledge

CognitiveEngineering

MOT Modeling Language

CONCEPTS PROCEDURES PRINCIPLES

C

S

P

I/P

R

I

LINKS

A S

imp

le P

roce

ss M

od

el

User Technician

R

RR

R

R R

An OWL-DL Model

C

ChemicalFertilizers

S

RiceProductionProcesses

I

I

I

RR Produce

RR Produce

CarbonDioxyde

S

Gases

S

R

Fertilizers

R

R

R

NitricOxyde

HasInputs

MethaneHas

Outputs

I

RR

RR

HasOutputs

HasInputs

SS

TraditionalRice

Production

AgriculturalPractices

GreenhouseGases

THINGS

3- Knowledge Dissemination: Processes and Tools

Resources repositories: Resources repositories: content, tools, process content, tools, process (LD)(LD)MOT+LD: a graphic IMS-MOT+LD: a graphic IMS-LD Modeling EditorLD Modeling EditorIDLD: a Repository of IDLD: a Repository of Learning DesignsLearning DesignsA Reuse and Expand A Reuse and Expand ProcessProcessLD “Primitive” Template: LD “Primitive” Template: an Educational Genomean Educational GenomeSemantic AnnotationSemantic Annotation

Information

InstructionalEngineering

SharedKnowledge andCompetencies

Learning Design as Composed Objects

BasicResources

ToolsDocuments

MediaElements

Actors

Units ofLearning

OperationsScenarios Processes

An IMS-LD Model

An OWL-DL Model

Semantic Referencing of Learning Objects

Semantic Referential for LDs

Design

A Library of LD Resourcewww.idld.org

Reusability Process

Modeling a Course and Modeling a Course and Generalizing to a Pattern Generalizing to a Pattern (Instructional Strategy Level)(Instructional Strategy Level)Decomposing into Primitive LD Decomposing into Primitive LD or Direct Creation (Instructional or Direct Creation (Instructional Tactic Level) Tactic Level) Aggregating a Course Pattern Aggregating a Course Pattern from primitive LD (New from primitive LD (New Strategy)Strategy)Specification of Course Pattern Specification of Course Pattern to one or more Course to one or more Course ExamplarExamplar

4- What’s in a Competency?

Competency Use: Competency Use: Human resource managementHuman resource management

Guide knowledge modeling Guide knowledge modeling

Define dcenarios, learning designs, coursesDefine dcenarios, learning designs, courses

Guide tutoring and learning resource self-Guide tutoring and learning resource self-management management

Select information resources, etc.Select information resources, etc.

Many projects, interesting process, little useMany projects, interesting process, little use

Structured CompetencyStructured Competency

Examples Examples

Research on Competency EquilibriumResearch on Competency Equilibrium

Structured Competencies To say that somebody needs to acquire a certain

knowledge is insufficient. What should he be able to do with it ?

Competency referentials address that problem by using natural language statements involving actions on knowledge

Competency statements are most of the time ambiguous and difficult to use

Need to structure competencies: knowledge, skills/attitude, performance/context of use.

A generic skills’ taxonomy combining viewpoints : instructional objectives, generic tasks/processes, meta-knowledge

Comparing Generic Skills’ Taxonomies

Active meta-knowledge

(Pitrat

Generic problems (KADS)

Cognitive objectives (Bloom)

Skills cycle (Romiszowski)

Attention

Memorize Perceptual acuteness and discrimination

Knowledge Search and Storage

Understand Interpretation

Knowledge Use, pression

Apply

Procedure Recall Schema Recall

Prediction, Supervision, Classification, Diagnosis

Analyze Analysis

Repair

Knowledge

discovery

Planning, Design,

Modeling

Synthesize

Synthesis

Knowledge cquisition

Evaluate Evaluation

Initiation, Continuation, Control

Generic Skills Taxonomy Layers

1 2 3

1. Pay Attention

Rec

eive

2. Integrate 2.1 Identify

2.2 Memorize

3. Instantiate / Specify

3.1 Illustrate

3.2 Discriminate 3.3 Explicitate

4. Transpose/ Translate

Rep

rod

uc e

5. Apply 5.1 Use

5.2 Simulate Ex

6. Analyze 6.1 Deduce

6.2 Classify

6.3 Predict

6.4 Diagnose

7. Repair

Cre

ate

8. Synthesize 8.1 Induce

8.2 Plan

8.3 Model/ Construct

9. Evaluate A

Re-

inve

st

10. Self- manage

10.1 Influence

10.2 Self-control

CRITERIA

Performance / Application Context

Frequency

Scope

Autonomy

Complexity

Context

Familiarity2.5 – 5.0

Always

Partial

Withassistance

Weak

Familiar

Expertise7.5 - 10

Always

Total

WithouthelpHigh

Unfamiliar

PERFORMANCE LEVELSAwareness0.0 – 2.5

Sometimes

Partial

Withassistance

Weak

Familiar

Mastery5.0 – 7.5

Always

Partial

WithouthelpMiddle

Familiar

Backbone of an LD Repository

Competency-based Semantic Annotation

Compare planets by mass autonomously and totally

Compare planets by mass autonomously and totally

Compare planets by orbital period autonomously and toally

Compare planets by orbital period autonomously and toally

Analyze, deduce properties of objects (here Planet name and

orbital duration)

Analyze, deduce properties of objects (here Planet name and

orbital duration)

Competency Association to Activities and Resources in Explor@-II

Knowledgeand Competency

Editor

I/P

EntryCompetency

TargetCompetency

DESIGNER

R

DesignI/P I/P

S S

Competency Gap Analysis

ActualCompetency

TUTOR

R

I/E

AssessNearmoment

RR

I/P

EvaluationTool

S

ActualCompetency

LEARNER

I/E

DefineC

I/P

Self-diagnosisTool

S

R

Associate

COMPETENCY

1. Knowledge 2. Generic Skill3. Performance Context

C CC

Select in a domain ontology

I/P

Select in a Skill’s taxonomy

CombinePerformance/ context

criteria

I/P I/PScale position

C C

Reduce Quitting Risk

Learner

Tutor

Designer

System

LEGENDL

T

S

D

Trace eachlearner and tutor

evaluation

Competency,Affective,Social,metacognitivedata (from tools)

L T S

RRR

Calculate

GroupIndicators(Ex: actual Competencyvs target)

CompareDiagnose

Build the LDand the envirn’t

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

S

S

R

Individual /groupdiagnosis

CommunicateDiagnosis toA, T, D and S

R

DiagnosisInterface

D

EC TCL2CG2CT2C

L1CG1CT1C

Id Competency Table Priority

Init Gap

A1 (6) Analyze applicable law texts, without help, to new situations with middle or high complexity .

1 (2) 4

A2 (6) Analyze applicable jurisprudence with some help in complex situations.

1 (2) 4

A3 (3) State applicable rules of law in any situation 2 (1) 2

A4 (5) Apply appropriate civil rights elements without help in famliar situation and middle complexity.

1 (2) 3

…

Constructing a Professional Program (Bar Professional School)

Gap Competencies Course 1

Course 2

Course 3

Course 4

1-3 A3, A4, A5, A6, A7, A8, B4, C2, C6

x

4-5 A1, A2, A9, A10, B1, B3, C1, C3, C5, D2, D5, D6, E1, E2, E3, E8

x x

6-7 C4, D1, D3, D4, E9 x x x

8 B2, E4, E5, E6, E7 x x x x

Generic Skill : a Blueprint for a LD

Selecting Resources for a UserSelf-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 X

9.7

Competency Equilibrium

CC

C

C

Act 5

P

P

P

Activity 5.4

Activitiy 5.1

Activity 5.2

IP

IP

Productresource

InputResourc

eA

InputResource

B

Activity 5.3

R

TrainerLearner

IP

R

Components of a Components of a LD reach LD reach competence competence equilibrium when equilibrium when learning succeeds learning succeeds

Components of a Components of a LD reach LD reach competence competence equilibrium when equilibrium when learning succeeds learning succeeds

7.4

TC:7.4

TC: TC:7.4

EC:6.4

TC:7.4

TC:5.2

EC:5.2

Conclusion

Competency is Competency is a knowledge management / education goala knowledge management / education goalan instructional engineering method toolan instructional engineering method toola way to personalize learning during deliverya way to personalize learning during deliverya way to improve learning environments after deliverya way to improve learning environments after deliverya central piece for ePortfolios and User modelsa central piece for ePortfolios and User models

New generation tools are needed to support New generation tools are needed to support competency-based engineering, learning and tutoringcompetency-based engineering, learning and tutoringNew specification for competencies (Extend IMS-LD ?)New specification for competencies (Extend IMS-LD ?)Shared ontology for semantic annotatation learning Shared ontology for semantic annotatation learning designsdesigns

ICALT-06, Kerkhade, The Netherlands,July 5-7, 2006

MERCI!

Gilbert Paquette

LORNET and CICE DirectorLICEF Research Center, Télé-université

www.licef.teluq.uquebec.ca/gp