open-intelligent-effective barbara kieslinger [email protected] centre for social innovation

www.elena-project.org

Creating a Smart Space for Learning

The ELENA Consortium

Information Society Technologies (ist) PROGRAMME


OPEN-INTELLIGENT-EFFECTIVE

Barbara [email protected]

Centre for Social Innovation

www.elena-project.orgwww.elena-project.org

Corporate Learning Management....state of the art

Today‘sKnowledge

Worker

Tool:Web Browser

Publishing House

Magazins,Journals

OnlineBookstore

Books

Intranet

Tutorials

Intranet

Best PracticeStudies

OnlineMarketplace

Courses

OP

EN


Current drawbacks

Lack of transparency of knowledge offerings

Increased search costs

Personalization is site-based (e.g. everything you buy at

Amazon.com) vs. process-based personali-zation (e.g.

gain know-how on “Web Services”)

No decision support

OP

EN


Corporate Learning Management...future

Tommorrow‘sKnowledge

Worker

Tool:Web Browser+ PersonalLearning Assistant

(PLA)

Publishing House

Magazins,Journals

OnlineBookstore

Books

Intranet

Tutorials

Intranet

Best PracticeStudies

OnlineMarketplace

Courses

Sm

art S

pace fo

r Learn

ing

PLA

OP

EN


RequirementsSystem interface framework

ADMINISTRATION LAYER

APPLICATION LAYER

AccessControl

Learning Resource

Management

SystemRegistration

UserAuthentication Inspection

Provision Querying Access & Delivery

ServiceAnnouncement

NEW

PENDINGOP

EN


First Prototype

Arel

Clix

Edutella P2P Network

www.EducaNext.org

Experimental UBP

Edutella OLRProviderTRIPLES

Edutella OLRProviderTRIPLES

UBP

UBPITeachYou

SimpleEdutella

Consumer

Communication andexchange via UBPsystem interfaces

ULIEdutella File-

based ProviderTheory of

Algorithms

Edutella File-based Provider

InternetApplications

Edutella File-based Provider

ArtificialIntelligence

JavaClient

JavaClient

Clix

OP

EN


Issues

Broker[UBP]-centred approach less flexible administrative and performance bottleneck

Adoption of common schema by provider increases implementation costs local mapping instead of enforced schema

Lack of interoperability on schema level mapping of search results required

High implementation effort for plugging in new node sound interface definition required

Performance of Peer-to-Peer Network Identification of performance bottlenecks

OP

EN


Requirements for a query interface

The query interface must be designed to query heterogeneous metadata schemas.

The query interface must not require a specific query language.

The query interface must build upon existing standards of the W3C such as XML, RDF, and SOAP.

The query interface must not require a specific network architecture.

The query interface must be based on a light-weight design, which allows for a fast implementation.

First public draft: http://nm.wu-wien.ac.at/e-learning/interoperability/query.pdf

Submission to CEN/ISSS Standardization Workshop(Work Item on Interoperability of Repositories for Learning

by Erik Duval, Simos Retalis, and Bernd Simon)

OP

EN


Next Milestone

UBP-basedPersonalLearningAssistant

Arel Clix

IteachYouUBP-based

Market-place

Clix

Amazon

Provision Interface

Query Interface

Amazon Interface

Edutella P2P Network

OP

EN


What is a Smart Space?

A Smart Space for Learning is a system, which aims to manage the distribution and consumption of Learning Services via a Personal Learning Assistant.

“Space” depicts a network of educational nodes, designed for the provision of a heterogeneous set of learning services. “Smart” refers to the use AI techniques (e.g. reasoning) and shall ensure an optimized selection of learning services.

INTELLIG

EN

T


Who is smart?

PLA, the personal learning assistant, performs the search for suitable learning services based on the learner's individual profile, processes the selected services and supports the evaluation of the learner.

Learners with different background

Learners with different goals, preferences, aims

Learners with different learning styles

INTELLIG

EN

T


The Situation

Distributed content/services

Distributed standard based metadata descriptions about:

Content/Services

Relationships between the content/services

Learner

Logic Programs

Query

Add restrictions to queries

Enhance metadata

P2P

Content/Service

Relationships

Content/Service Metadata

Logic ProgramsLearner Model

INTELLIG

EN

T


Summary of Personalisation Approach of ELENA

Service/Content metadata seen as some constraints on use for learning services (LS)

Learning service metadata are retrieved according to matching between learner profile and LS metadata

Rules determine how adaptation is performed based on the matching learner profile and LS metadata

Standards: LOM and Dublin Core

INTELLIG

EN

T


Learner Profiling

Why: To be able to customize (adapt) information to specific person

Different user characteristics can support personalization

Current State:

IEEE PAPI:

– IEEE Public and Private Information (PAPI) for learner (IEEE P1484.2/D7, 2000-11-28)

IMS LIP:

– IMS Learner Information Profile (v1.0, 2001-3-9)

Which way to go? (standard analysis, needs analysis)

INTELLIG

EN

T


Resulting Profile

..... after comparison

Study performance

– Performance, portfolio, certification

Identification

Calendar

HRP

– Job, Title, Department

Other user features

– Preference, Goal, Interest

INTELLIG

EN

T


PLA Search InterfaceIN

TELLIG

EN

T


PLA Results InterfaceIN

TELLIG

EN

T


What we need Smart Spaces for?

We want to assist in the process

of making training management

more effective for the

corporate world, by

introducing Smart Spaces for

Learning.

EFFEC

TIV

E


Interviews

Interview procedure -- 2nd

round:

1.Introduction to the study

2.Pre-questionnaire

3.Successful / Failed Cases

4.Scenario validations

combined with

questionnaire

5.Claims analysis for

different artefacts and

features

6.Wrap-up and conclusion

EFFEC

TIV

E


Findings 1/2

Companies spend resources on life-long learning (1-1,5 % of EPIDA)

Older, larger companies still have centralised behaviours, deciding employee training at boards

Employees build perceived trust with customers by getting certified degrees

Employees have annual meeting with HR manager.

Companies assign their training budget on an employee-basis or on a department-basis.

Personnel departments aim to maintain training accounts per employee in order to get the training partly refunded when the employee leaves the company within a specific time period.

EFFEC

TIV

E


Finding 2/2

Companies choose learning services from recognised companies/institutions

Companies allow departmenthead/employees to choose learning services

Employees some times take

'wrong‘ decisions when it

comes to the selection of

learning servicesEFFEC

TIV

E


Reflections on a Smart Space

A corporate demand for a well-managed central market place for learning services does exist. (Google for learning services).

Well-managed means that providers are carefully selected, references to providers do exist, and the portfolio of the learning service offer exceeds a significant size.

Learning service markets are local. Building a single European corporate portal for learning services does not make sense. Language and location are too big barriers. Most effective filtering attributes: period when learning service is intended to be consumed, anguage and location

E-Learning is hardly accepted by the corporations. Sometimes failed projects do exist. Hence, the learning service portfolio also needs to include presential courses.

EFFEC

TIV

E


User centred approach

Involve users e.g. companies with training management

– in design

– trials

– and surveys

EFFEC

TIV

E

Smart Space for

Learning


Thank you!


open-intelligent-effective barbara kieslinger [email protected] centre for social innovation

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