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The LD Research Team

Learning Design based on Graphical Knowledge-Modeling LICEF-CIRTA, Télé-Université _________________________________ Michel Léonard UNFOLD Workshop Valkenburg, sept, 21-22, 2005. The LD Research Team. Gilbert Paquette, Scientific Director and ID Specialist

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The LD Research Team

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  1. Learning Design based on Graphical Knowledge-ModelingLICEF-CIRTA, Télé-Université _________________________________Michel LéonardUNFOLD WorkshopValkenburg, sept, 21-22, 2005

  2. The LD Research Team • Gilbert Paquette, Scientific Director and ID Specialist • Stefan Mihaila, Denis Gareau, System Designer • Ileana de la Teja, I.D. Specialist and Competency Models • Karin Lundgren-Cayrol, I.D. Specialist and Collaborative Learning • Michel Leonard, Knowledge Modeling Expert and System Design

  3. Subjects: • M.O.T. Modeling language using Object Type • MOTPlus Graphic editor use to produce ‘Unit of Learning’ models and XML-LD manifest compliant with the IMS-LD specification • MISA: Instructional Engineering Method adapted to support IMS-LD • Structured competencies

  4. R & D- Implementation - Revision • 1987 - Research on knowledge based systems • 92/98 - Design & dev. of a pedagogical design course • 95-98 - Development of MISA-1, 2, 3 and MOT softw. • 1999 - Development of MOTPlus standard model • 2000 - ADISA(MISA4and MOT): Web Workbench • 04-05 - MISA4/MOTPlus : • Standard model • Flowchart model by actor • IMS-Learning Design model + XML-LD • Ontology model + XML-OWL

  5. Plan • LD Editor Graphic Representation • MOTPlus - LD Graphic vocabulary • Misa – LD Engineering process • Knowledge/Competency Referencing • Conclusion

  6. WHAT? Conceptual K HOW? Procedural K WHEN? WHY? Conditional K MOTPlus : Type of knowledge units Concrete facts Abstract knowledge Concepts Examples Procedures Traces Principles Statements

  7. Objects • Documents, tools • Dates • Definitions Concepts • Actions • Tasks, activities • Instructions, algorithms • Steps in a scenario Procedures • Conditions, constraints • Rules, heuristics • Laws, theories • Decisional actors Principles Example: concrete object representing a concept Trace: concrete object representing a procedure Statement: concrete object representing a principle Facts Examples of different type of knowledge

  8. L I N K S CONCEPTS PRINCIPLES PROCEDURES C S P I/P R I MOT Graphic Language

  9. Example of Knowledge Model

  10. Set of Examples S Set of Traces S S Set of Taxonomies and Statements Typologies S Component Systems S S Hybrid Conceptual Series Systems Procedures S Parallel S Ontologies Procedures S Definitions, Iterative Norms and Procedures Constraints S Laws and Theories S S Decision Trees S Processes Control Rules S Methods S S LD Collaborative Systems ModelTaxonomy(Categories) Factual Models Conceptual S Models S Knowledge Procedural S Model Models S Prescriptive Models S Processes and Methods

  11. Desired Properties of a MOT GraphicRepresentation Formalism • Simplicity and User Friendliness (win spec, only few type) • Generality (structured overview of the domain) • Completeness (process, resources and rules in the same model) • Has easily Interpretable graphic objects (only few type) • Facilitates communication (same semantic for each model) • Allows building meta-knowledge models : Generic Skills and Competencies • Makes explicit the relationship between knowledge/competency and LD • Translates to machine (XML) format

  12. Plan • LD Editor Graphic Representation • MOTPlus - LD Graphic vocabulary • Misa – LD Engineering process • Knowledge/Competency Referencing • Conclusion

  13. MOTPlus - LD Graphic Objects

  14. MOT+ LD Links

  15. Graphic Representation of a LD

  16. DISPLAYS RESULTS Send Results RETURNED TO THE LO C RECORDER Returned results Versailles ACT1: VERSAILLES Expérience ACT8: REFLECT ON OVERVIEW TREATY IP C OUTCOMES C C P C Send Results Send Results Read Posted IP P to Recorder Env Results Play ACT2: C C C C INTRODUCTION TO ACT7: REVIEW France PREPARATORY MAIN PHASE Negotiation NEGOTIATION DAY Day C Main Main C C C Negotiation IP Negotiating P USA-France Forum Chamber P US-France C IP Side-room Forum C ACT3: C C C BACKGROUND C STUDY - OFFLINE GB-France GB-France ACT6: THE MAIN IP ACTIVITIES France-Serbia France-Serbia Side-room Forum NEGOTIATIONS IP Forum Side-room Poland-France P P Side-room France-Italy France-Serbia Side-room C ACT5: ACT4: SIX NATION I Side-room INTRODUCTION TO P ONLINE STRATEGY MAIN NEGOTIATION IP PREPARATION DAY IP FRANCE-Serbia IP Confer Poland-France FRANCE-SERBIA France-Italy Forum France-Serbia Negotiate AD res Forum Forum I I-France Serbia Confer SO Collaboration (Versailles Scenario)

  17. Referencing LDs with an Ontology

  18. Plan • LD Editor Graphic Representation • MOTPlus - LD Graphic vocabulary • Misa – LD Engineering process • Knowledge/Competency Referencing • Conclusion

  19. The basis Cognitive Science Education Science MISA Software Engineering

  20. ? $ Strategy Structure Comparing MISA with the ID model ADDIE MISA Project definition Preliminary solution Architectural design Instructional materials design Materials’ development & validation Infrastructure planning Analysis Design Development Implementation Evaluation

  21. Documentation Elements 35 textual and graphical templates • Modular structure • Allows a flexible approach for the designers and for the administrators • Facilitate location, updates and re-use of the LS constituents in new projects. MISA: Description 6 Phases Contents 4 Axes Phases 2 - 6 are structured according to specialized AXES Strategy Materials Delivery

  22. Problem definition 100 Training system 102 Training objectives 104 Target Learners 106 Actual situation 108 Reference documents Instructional Modeling Knowledge Modeling 210 Knowledge modeling principles 212 Knowledge model 214 Target competencies 310 Learning units content 410 Learning instruments content 610 Knowledge and competency management 220 Instructional principles 222 Learning events network 224 Learning units properties 320 Instructional scenarios 322 Learning activities properties 420 Learning instruments properties 620 Actors and group management Delivery Modeling Materials Modeling 240 Delivery principles 242 Cost-benefit analysis 340 Delivery planning 440 Delivery models 442 Actors and user’s materials 444 Tools and telecommunication 446 Services and delivery locations 540 Assessment planning 640 Maintenance / quality management 230 Media principles 330 Development infrastructure 430 Learning materials list 432 Learning materials models 434 Media elements 436 Source documents 630 Learning system / resource management MISA 4.0 Method

  23. MISA - Instructional Engineering Method

  24. Plan • LD Editor Graphic Representation • MOTPlus - LD Graphic vocabulary • Misa – LD Engineering process • Knowledge/Competency Referencing • Conclusion

  25. Structured Competencies • To say that somebody needs to acquire a certain knowledge is insufficient • What kind of generic skill and performance? • Explain or Use or Analyse or Communicatethe Knowledge • In a simple or complex situation, with or withouthelp • The generic skills’ taxonomy is based on different viewpoints : instructional objectives, generic tasks/processes, meta-knowledge • Competency = Meta-process (skill) applied to a knowledge at a certain performance level • Permits to situate knowledge acquisition goals on a competency/performance scale (to be measured or observed)

  26. Frameworks

  27. A Generic Skills (Meta-process) Taxonomy Exerce a skill S S Self- Receive manage S 1-Show S S awareness S S 10-Self- S manage 2-Internalize S Reproduce Create S Identify Initiate/ S Influence S 9-Evaluate S S Memorize 3-Instantiate S Adapt/ S S /Detail S control Generic skill Inputs Products 8-Synthesize S Simulate A Process and its sub-procedures, inputs, products and control principles Trace of the procedure: set of facts obtained through the application of the procedure in a particular case Illustrate 4-Transpose S S 6-Analyze 5-Apply 7-Repair S Construct S S S S S Discriminate Deduce S S S Diagnose Plan Construct Definition constraints to be satisfied such as target inputs, products or steps…. A model of the process: its inputs, products, sub-procedures each with their own inputs, products and control principles Simulate Induce Explicitate Classify Predict Utilize

  28. Simulation: generic and scenario models

  29. Plan • LD Editor Graphic Representation • MOTPlus - LD Graphic vocabulary • Misa – LD Engineering process • Knowledge/Competency Referencing • Conclusion

  30. Conclusion • Generic Skill’s Meta-process could be used and reused as a basis for Learning Scenarios • Target competencies with its hierarchic skill structure contribute to build effective and efficient instructional scenarios • In a Learning Object Repository, the skill taxonomy provides a way to classify UoLs scenarios • by their association to the generic graphic knowledge based models • Through the Learning Design templates’ metadata using the main target skill and the related knowledge type

  31. Learning Design based on Graphical Knowledge-ModelingIEEE ET&S journal Presented by Michel Léonard, mleonard@licef.teluq.uquebec.ca UNFOLD /ProLearn meeting ,Valkenburg, sept, 21-22, 2005 Address: LICEF Reaches Center http://www.licef.teluq.uquebec.ca/eng/index.htm MOTPlus LD Resources to download : (software, presentations and examples) http://206.167.88.22:90/cice/motplus_IMSLD/

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