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Using Standards in e-Learning

Using Standards in e-Learning. Claude Moulin UMR CNRS 6599 Heudiasyc University of Compiègne (France). Some e-learning features. Definitions of e-Learning usually emphasize on network utilization (''e'' in e-learning) and on Information Technology. Added requirements

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Using Standards in e-Learning

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  1. Using Standards in e-Learning Claude Moulin UMR CNRS 6599 Heudiasyc University of Compiègne (France)

  2. Some e-learning features • Definitions of e-Learning usually emphasize on network utilization (''e'' in e-learning) and on Information Technology. • Added requirements • two domains: training domain, application domain • reflection on content • Objectives of training session, • Competences acquired by learners, etc. • Concepts of the application domain and the relations between these concepts • construction of new resources taking into account possibilities offered by Information Technology: • digitalization of old resources is generally not enough, • redefinition of actors roles according to situations • teachers, learners, tutors.

  3. E-Learning applications • Learning Content Management Systems • Creation of resources • (distributed) Repositories of resources • Portfolios, Pedagogical Web sites • Learning Organizational Memories • Modeling of the domain and indexing of resources on domain concepts • Learning Management Systems • Organization of content in pedagogical units (activities) • Scheduling of P.U. • Student Assessment

  4. Instructional Design Semantic Web E-Learning Two influences – integration?

  5. Language Levels • Conceptualization • Pedagogical scenarios • Meta data - Ontology - Knowledge Base • Operationalization • Operational languages • Composition of pedagogical units • rules for Sequencing activities • Functional languages used in knowledge base engines • Rule languages • Query languages

  6. Conceptual level

  7. XML Schema for metadata: LOM File name, browser type Narrative Text, learning time test

  8. OWL: Web Ontology Language • Ontology • Definition Concepts (classes) and relations (properties) between concepts • Axioms on concepts and relations • Restrictions on relations • Different level of ontology • Knowledge base • Adding extensions (set of individuals) to concepts • Axioms on individuals • Requires management systems for making inferences • True, inferred true, false, inferred false, unknown • Limitations • OWL does not allow to represent all ontology features (points of view, attenuated transitivity)

  9. XTM: ML for Topic Maps • Ontology • Definitions of classes and subclasses of topics • Relations (association) on classes of topics • Axioms on classes of topics • Knowledge Base • Topics as instances of classes of topics • Axioms on topics • Features • Occurrence: for linking topics and resources to classes of topics • Scope: associations between topics can be considered inside a scope

  10. Use of ontologies in e-Learning • Currently • Indexing of resources • Modeling of training domain and application domains • Future?? • describing e-Learning Services?

  11. Pedagogical Scenarios • Pedagogical Unit: composed of Pedagogical Scenarios • A complete training course, a lesson, etc. • Pedagogical Scenario: composed of sequence of Pedagogical Acts • Bricks for building a learning process • a problem solving activity, an experiment • Pedagogical Act: An atomic task • Read a text, write a document, do a synthesis, etc.

  12. IMS-LD • Origin • EML – Educational Modeling Language • meta-language for describing pedagogical models from concepts involved in the learning process • Open University of Netherlands IMS-LD • Language defined by an XML Schema • The conceptual model • Make easier specifications and implementations • Three levels of representation • Static: the sequencing of activities is the same for all • Dynamic: the sequencing may depend on properties (tests) • Events: activities based on notifications (messages)

  13. Operational Level

  14. Learning Management Systems • SCORM: suite of technical standards that enable web-based learning systems to find, import, share, reuse, and export learning content in a standardized way.  • Content Aggregation Model (CAM) • Run-Time Environment (RTE) • Sequencing and Navigation (SN)

  15. SCORM - CAM • It describes the components used for structuring the content. • Asset : atomic pedagogical content. any resource which can be displayed in a browser. • SCO (Sharable Content Object) : Composed by assets capable to communicate with a LMS. • CO (Content Organization) : structure describing the composition of assets and SCOs in activities • SCOs are described using the LOM model

  16. Functional languages • Semantic Web Management Frameworks require functional languages: • Rule languages for reasoners • Ex: HP Jena Framework [rule1: (?a tg:rel ?b), (?b tg:trans ?c) -> (?a tg:rel ?c)] • Other languages: ruleML, SWRL • Query languages • RDQL (query language for RDF) SELECT ?x WHERE (?x, <tg:is_situated_in>, <tg:france>) USING tg FOR <http://terregov#>

  17. Conclusion • Will the Semantic Web Change Education? • Services for e-Learning? • Which model for services? • How is it possible to integrate instructional design and semantic web features when designing e-learning sessions?

  18. References • EML • http://eml.ou.nl/ • Rob Koper papers, from 1998 to 2003 • SCORM • http://www.adlnet.org/ • HP Semantic Web Programme • http://www.hpl.hp.com/semweb/ • KAON • http://kaon.semanticweb.org • Journal of Interactive Media in Education • DIG Group • http://dl-web.man.ac.uk/dig

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