European Schoolnet

Interoperability & Standardsin Learning Technology

2003-01-26

Frans Van Assche

Strategy Manager European Schoolnet

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More AboutStandards

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Excerpt from the LOM doc• Metadata is information about an object, be it

physical or digital.• As the number of objects grows exponentially and

our needs for learning expand equally dramatically, the lack of information or metadata about objects places a critical and fundamental constraint on our ability to discover, manage, and use objects.

• This Standard addresses this problem by defining a structure for interoperable descriptions of learning objects.

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Scope

• Standardized description of learning objects– ‘Any entity, digital or non-digital, that may be used for

learning, education or training’

– ‘Conceptual data schema’

– Linguistic diversity of LO’s and metadata

– Any granularity: from picture to curriculum

• First piece of puzzle for large-scale reuse• Only finished standard in this field

– And CWA on language capabilities

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Scope: Not

• Not– General standard (HTTP, HTML, TCP/IP, JPEG, etc.)

– Learning standard (typically national or regional)

– Binding (XML, RDF, ISO11404, etc.)

– Software, Tool

• Not:– Audiovisual (MPEG-7)– GIS (ISO19115)– bibliography (MARC)– …

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LOM Schema• general: title, language, summary...

• life cycle: author, publisher, version...

• metametadata: scheme, language, author...

• technical: format, size, requirements...

• educational: learning time, difficulty level, interactivity level, pedagogical context...

• rights: price, copyright...

• relation, annotation, external classification

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LOM Schema

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LOM basics• Hierarchical structure

– Base Schema: 9 categories– Category: Group of data elements– Data element: may contain subelements– Only leafs have ‘values’

• Datatypes– LangString, DateTime, Duration, Vocabulary, CharacterString

• Value spaces– Allowed values

• All data elements are optional– Though presence of component implies composite to

which it belongs

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Lists

• Ordered– Authors: most important first– Classification: from general to more specific

• Unordered– Explanatory text in several languages

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Vocabularies“Recommended list of appropriate values”• Increase semantic interoperability

– More likely to be understood

• Value is (source,value) pair– (“LOMv1.0”, “questionnaire”)

• Preferred if adequate

– (“http://www.vocabularies.org/Type”, “Motivating-Example”)

• More flexible

• State: no order (exercise, simulation, …)• Enumerated: order (low, medium, high)

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Smallest permitted maximum

• Aggregate data elements– Maximum number of entries processed cannot

be lower

• CharacterString– Maximum number of characters cannot be

lower

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Conformance

• Strictly conforming LOM instance– Consists solely of LOM data elements

• Conforming LOM instance– May contain extended LOM data elements

• Maximise semantic interoperability– Extended LOM elements should not replace

LOM data elements.

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LOM: LangString

• Language: LangCode[-SubCode]– ISO639, ISO3166

– “en-GB”, “fr-CA”, ...

• String: ISO10646-1• Example:

• {(“it”,”La Gioconda”), (“it”,”Mona Lisa”)}

• {(“en”,”A picture of the Mona Lisa”), (“du”,”Een foto van de Mona Lisa”), (“fr”,”Une photo de la Gioconde”)}

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FAQ

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FAQ: different types of use

repeat categories and data elements!

Example: 5:Educational1. 5.6:Context="higher education”

5.8:Difficulty="medium”

2. 5.6:Context="training" 5.8:Difficulty="difficult"

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FAQ: Subjective metadata

That’s ok!

• We don’t need to develop strict metrics for difficulty, etc.

• Is more general than that– Subject is quite subject-ive…– Even author or title can be subjective!

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FAQ: Learning Style

• Examples– Autonomous learning– Guided learning– Teaching support

• 5.5:IntendedEndUserRole helps• 5.10:Description helps• 9:Classification for interchangeable

learning style description

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FAQ: Educational Objective

• 9:Classification

• 9.1:Classification.Purpose=(“LOMv1.0”,” educational

objective“)

• Often pseudo-hierarchically structured

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FAQ: Extensions

• Structural– Add new elements anywhere in hierarchy of

categories and data elements– Example:

• 5.12:LearningStyle (Vocabulary)

• Extending value space– Retain the data type– Extend value space of vocabulary

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FAQ: Granularity

• Should I describe– Image, “page”, “web”, “course”, …?

• Describe what is reusable– All can be described– Relationships go into 7: relation– Metadata should be inherited up- and downwards?

• Larger– More added value– Less reusable

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FAQ: tokens• Out of scope for the LOM conceptual schema. To

be addressed in binding documents.• Conventions exist for generating tokens from the

LOM element names.• In an XML context, namespaces can be used to

make sure that LOM tokens do not clash with tokens from another context.

• Extreme example, binding to a technology that requires that all names start with upper case should not imply a change to the LOM conceptual schema.

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Too many?

European

SchoolnetCedefop

CanCore

Edna

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European

SchoolnetCedefop

CanCore

Edna

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IEEE LTSC• General:

– architecture, glossary

• Content:– interchange, sequencing, packaging

• Learner:– learner model, student id’s, competency def’s

• (Meta)data:– LOM bindings into XML, RDF, ISO 11404– localisation, bindings, protocols

• Management– Computer-Managed Instruction– tool-agent comm., profiles

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ISSS LTWS

• encourage appropriate standards– Diversity of cultures and languages– Participation in global initiatives,

to ensure that Europeanrequirements are addressed

• Create specifications, agreements, guidelines or recommendations where appropriate:– when no initiative addressing the identified

requirements is in place yet– when global solutions developed elsewhere need to be

localized to the European requirements

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ISSS LTWS

• LOM:– Internationalisation– Translation of LOM document– Availability of alternative

language versions– Repository of vocabularies and taxonomies

• Also:– Language capabilities– Quality assurance– Educational modeling languages– Educational copyright license

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ISO IEC JTC1 SC36

• Since Nov. 1999• ‘Information Technology for Learning,

Education, and Training’• Working groups:

– Vocabulary– collaborative technology– learner information

• Invited LOM to submit for ‘fast tracking’

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IMS & ADL SCORM

• Currently frozen on LOM D6.1• IMS

– Work on defining set of core elements

• SCORM– Different sets for different granularities

• Will both “re-synch” with LOMv1.0– Once bindings are finalized.

• XML Schema

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http://www.cancore.org/

• “synthesize efforts”

• Guidelines for selected elements

• Refinements of definitions

• Examples

• Technical implementation notes

• Vocabulary recommendations

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Issues

• Educating the community– Including expectation management

• What needs to be standardized? Order?– And: political, legal, pedagogical, best practice, …?

• Design for reuse, interoperability?– Look and feel: uniform? adaptable?

• What will effect be:flexibility? collaboration? commercialization?

• Will industry respect the rules? Academia?(‘neo-industrialization’)

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More Examples

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TU Darmstadt

• DTD based

• Output is XML file

• LOMv4.1

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ImseVimse • Java

application

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P2P Tools

• LOMster

• Splash

• Edutella

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LOM basedRepositories

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http://thelearningmatrix.enc.org/

•Simple and complex searches•150 LO’s (?)

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http://www.smete.org/

• federated search protocol

• Cataloging tool

• User profile

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http://www.merlot.org/

Can export to LOM in XML format.

Includes peer review (content, teaching value, ease of use)

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And

• LearnAlberta Portal: http://www.learnalberta.ca/ • BELLE/CAREO: http://careo.netera.ca • COLIS: http://www.edna.edu.au/go/browse/0 • Lydia: http://www.lydialearn.com/ • Heal: http://www.healcentral.org/index.htm • iLumina: http://turing.csc.uncwil.edu/ilumina/

homePage.xml • SeSDL: http://www.sesdl.scotcit.ac.uk 

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Dublin CoreBased Repositories

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DC-Education Consortia

• EDNA:

• EUN:– European Learning Resource

• GEM• Also: projects, commercial products, …

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Application Profiles

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Application Profile

• Fully compatible• Instantiation for a community:

– Some elements mandatory– Some value spaces more specific– Some interrelationships between elements– Some additional elements

• Result:– More semantic interoperability– Higher ‘quality’

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Hierarchy of Application Profiles

LOM

Generic Appl. Prof.

Appl. Prof. 1 Appl. Prof. 2 Appl. Prof. 3

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Multilinguality

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Elements

• Nature of the information– Volatility: Forum messages (high), FAQ (low)– Volume: Harvesting (high), Newsletter (low)

• Quality of the translation

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Translation options

LowerQuality

HighQuality

Low Volume and Low Volatility

High Volume or High Volatility

Manual translations using Translation Workflow Mgt

Tools

Fully Automatic Translation

Not possiblein the next 5 years

Not Interesting

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Fully Automatic Translation

• Using– Character tables for the different languages

– Fixed-text tables

– Multilingual Thesaurus and Vocabulary

– Off-the-shelf proze machine translators (MT) that can be plugged in

– Dynamic Web pages

• Highly structured information (such as the metadata) gives better results

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VocabulariesControlled Vocabularies for Learning Object Metadata.

Typology, impact analysis, guidelines and a web based Vocabularies

Registry.

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Chapter 2Vocabularies and LOM• Value lists, classifications, taxonomies, thesauri,

glossaries, dictionaries, ontologies, natural language

• What do they have in common• Where do they differ• Three properties:

– Unstructured vs. structured (lists, trees, networks)– Purpose (describing, indexing, defining)– Controlled vs. not controlled

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StructureLinguistic tools to support

reuse and interoperability oflearning objects

StructuredTools

UnstructuredTools

NetworksLists Trees

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PurposeLinguistic tools to support

reuse and interoperability oflearning objects

Indexing andSearching tools

DescriptiveTools

DefinitionTools

Subject Indexingand Searching

tools

Property Indexingand Searching

tools

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Simple vocabularies and value lists

1. Structure Simple structure: alphabetic or hierarchical list of terms.

2. Purpose Property indexing and searching tool.

3. Control Highly controlled, as the number of entries is limited to a specific field of application.

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Classifications and taxonomies

1. Structure Quite elaborate structure: alphabetic or hierarchical list organised in broad classes.

2. Purpose Subject indexing and searching tool.

3. Control Controlled vocabularies, where each term is located regarding the main semantic class.

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Thesauri

1. Structure Highly elaborate structure, using different types of relations.

2. Purpose Subject indexing and searching tool.

3. Control Controlled vocabulary which aims at eliminating much of the ambiguity of natural language;

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Glossaries, dictionaries

1. Structure Very simple structure: alphabetic list of terms.

2. Purpose Definition tool.

3. Control Not controlled as they aim to collect an exhaustive set of terms.

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Ontologies

1. Structure Network structure, the relationships may be defined in domain specific predicates.

2. Purpose Definition tool.

3. Control Not controlled, as they aim to collect an exhaustive set of terms.

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Natural Language

1. Structure No structure a priori.

2. Purpose Linguistic tool (for description purpose only).

3. Control Not controlled.

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Describing Learning Objects• Value lists• Classifications• Taxonomies• Thesauri• Glossaries• Dictionaries• Ontologies• natural language

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Guidelines

• Building Multilingual Vocabularies• Semantic Mappings• Structuring and Updating Thesauri• Use of Learning Object Metadata for Describing

Vocabularies• Vocabulary Bindings• Vocabularies and Learning Object Metadata• Use of Natural Language to Describe Learning

Object Metadata Elements

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Semantic Mappings

• Exact equivalence

• Inexact equivalence

• Partial equivalence

• Single-to-multiple equivalence

• Non-equivalence

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Guidelines for structuring and updating thesauri

General

Learning

Application

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Findings, research and examples

• The ISO-2788 standard for monolingual thesauri

• The ISO-5964 standard for multilingual thesauri

• Mapping metadata models

• XML binding for Vocabularies

• Alternative Vocabularies

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Vocabulary Repositoryhttp://www.cenorm.be/isss/LT-vocabulary/vocrep.html

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Brokerage Systems

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Issues• Architecture: central repository or federated• Messaging:

– Transfer protocols: FTP, http, https, NNTP– Envelope protocol: e.g. SOAP– Exchange language: e.g. XML– Messaging models: publish/subscribe, P2P, sync,

aSync, store & forward

• Structure of the information which is exchanged– Model– Vocabularies

• Client/Server communication application (e.g. using XSL)

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The EUN Knowledge Model

Resources

Learning

ManagementLearning

Communities

School

Admin

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Learning Objects• Resource• Learning resource• Multimedia asset• Learning Object• Learning Object Component• Course• Module• Atomic Learning Object• Learning Object Collections• Curriculum

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Learning Mgt & Learning Content Mgt

• Role: Student, Staff• Student Progress• Assessment• Learning Activity• Activity Report• Activity Flow• Outcome

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Learning Community

• Events (such as workshops, conferences, chats)

• Users• User groups• Schools• Special interest groups• Networks• News• Projects• Bulletin boards

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School Management

• Transportation• Libraries• Student attendance• Meals• Gradebooks• Human resources• Financial

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Polyhierarchy of brokerage systems

• Home

• School

• Area

• Region

• Country

• Europe

• Global

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Polyhierarchy of brokerage systems

• On each of those levels– Quality– Digital rights– Decision to publish– Decision to make available

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IMSLEARNING DESIGN

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Based on EML OUNL

• started 1997, research into pedagogies in use

• no description per pedagogy, but

• one meta-language to describe them all: Educational Modelling Language (EML), published in December 2000

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EML: simple yet powerful

• People engage in Activities, for which they use Resources– People: one or many, learner or staff roles– Activities: description, structured– Resources: learning objects & services (chat, etc.)

• Many roles, activities and resources need co-ordination in a workflow: learning flow

• An instructional design/pedagogy/learning design essentially is a learning flow.

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play

Act 1 Act 2 Act 3 Act 4 Act 5

Role-part 1

Role-part 2

Role-part 4

Role-part 5

Role Activity Environment

Learning objects

Learning services

Activity-Description

method

components

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LD: XML - top level

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LD: XML - method

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LD: XML - components

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Content Packaging: schematic

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Current status

• Draft accepted (Oct. 2002) c.f. IMS website• Delivery Final draft 18 December 2002• Voting first months of 2003

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Application example introRelation with a number of spec’s

Pedagogical perspective

Ignorant

Restricted - - -

Expressive ___

ProcessComplete process

description

SequencingPrerequisites, dependencies,

ContentLearning Objects,

metadata

PALO

IMS

CP

IMS

SS

SCORM

OUNL-EML

IMS-LD

Metadata

LOM

IMS QTI

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Digital RightsManagement

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DREL Standardization

• IEEE LTSC DREL SG

• Digital Rights Expression Language Study Group

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DREL Standardization Landscape

• Existing Languages:– ODRL– XrML– DOI– OeB– XML Security Standards

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DREL Standardization Landscape

• Digital Rights Standardization Initiatives– MPEG-21– OASIS– CEN/ISSS WS-LT– IMS Global Learning Consortium– The Open Knowledge Initiative– Indecs2rdd Rights Description Dictionary– ONIX Metadata Specification

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Example ODRL

• The display permission is constrained to a particular CPU.

• The print permission is limited to printing up to five times.

• The play permission is limited to a recurring period of seven days which itself can only occur up to ten times.

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Example<display>

<constraint>

<cpu/>

</constraint>

</display>

<print>

<constraint>

<count>5</count>

</constraint>

</print>

<play>

<constraint>

<interval>P7D</interval>

<constraint>

<count>10 </count>

</constraint>

</constraint>

</play>

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Design Guidelines For Reusable Learning Objects

• Find

• Evaluate

• Acquire

• Adapt

• Integrate

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Thank You