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 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

Subjects: M.O.T. MOTPlus MISA: Structured competencies 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

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 (MISA4 and MOT): Web Workbench 04-05 - MISA4/MOTPlus : Standard model Flowchart model by actor IMS-Learning Design model + XML-LD Ontology model + XML-OWL Validated in 9 organisations Several projects that are interlinked: AGD - Learning Systems Engineering Workbench MOT - tool for knowledge structuring

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

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

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

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

Example of Knowledge Model

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

Desired Properties of a MOT Graphic Representation 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

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

MOTPlus - LD Graphic Objects

MOT+ LD Links

Graphic Representation of a LD

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

Referencing LDs with an Ontology

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

The basis Cognitive Education Science Science Software Engineering MISA 4 categories: facts, concepts, procedures and principles Concept of schema LS components, and interelations can be represented by a model Software Engineering

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

Phases 2 - 6 are structured according to specialized AXES MISA: Description 6 Phases Phases 2 - 6 are structured according to specialized AXES 4 Axes Contents Strategy Materials Documentation Elements 35 textual and graphical templates Delivery 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.

Instructional Modeling MISA 4.0 Method Problem definition 100 Training system 102 Training objectives 104 Target Learners 106 Actual situation 108 Reference documents 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 Instructional Modeling 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 Materials Modeling 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 Delivery 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

MISA - Instructional Engineering Method First version of the method developed between 1992 and 1994, embedded in a AGD computerized support system.

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

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 Communicate the Knowledge In a simple or complex situation, with or without help 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)

Frameworks

A Generic Skills (Meta-process) Taxonomy Exerce a skill Receive Reproduce Create Self- manage 1-Show awareness 9-Evaluate 4-Transpose 7-Repair 2-Internalize 3-Instantiate /Detail 5-Apply 6-Analyze 8-Synthesize 10-Self- Generic skill Inputs Products 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 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 S Identify Illustrate Memorize Utilize Classify Construct Initiate/ Influence Adapt/ control Discriminate Explicitate Simulate Deduce Predict Diagnose Induce Plan

Simulation: generic and scenario models

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

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

Learning Design based on Graphical Knowledge-Modeling IEEE 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/