A Linked Knowledge Base for Simulation Learning

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Simulation Learning is a frequent practice to conduct near-real, immersive and engaging training sessions. AI Planning and Scheduling systems are used to automatically create and supervise learning …

Simulation Learning is a frequent practice to conduct near-real, immersive and engaging training sessions. AI Planning and Scheduling systems are used to automatically create and supervise learning sessions; to this end, they need to manage a large amount of knowledge about the simulated situation, the learning objectives, the participants’ behaviour, etc.
In this paper, we explain how Linked Data and Semantic Web technologies can help the creation and management of knowledge bases for Simulation Learning. We also present our experience in building such a knowledge base in the context of Crisis Management Training.

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  • 1. A Linked Knowledge Base for Simulation Learning Irene Celino and Daniele Dell’Aglio CEFRIEL, ICT Institute, Politecnico di Milano http://swa.cefriel.it, http://iricelino.org http://www.pandoraproject.eu Linked Learning Workshop at ESWC 2011 – Heraklion, Greece – May 29th 2011
  • 2. Simulation LearningCharacteristics and aims Improve Soft Skills, especially Decision-Making Effective and Engaging Learning Re-create a near-real environment Cheaper than on-the-field training More effective than table-top trainingPANDORA project scenario: Crisis Management Training Trainees are "Gold Commanders": strategic roles in the decision- making process who monitor a crisis situation and takes decision to be dispatched to tactical agents ("Silver Commanders")A Linked Knowledge Base for Simulation Learning 2 Linked Learning Workshop at ESWC 2011
  • 3. Knowledge in Simulation LearningRequirements in terms of Knowledge Management Scenario descriptions Events and stimuli for the trainees Storyboards for the learning sessions Multimedia assets Supporting documents and guidelines Trainees description and behaviour/decisions Learning session monitoringRole of the Exercise Director (Trainer) in traditional SL Define the exercise storyboard and ensure its planned execution Feed information to the trainees and let them make informed decisions Inputs at pre-set intervals, regardless of the previous responses; or By timing the inputs on the basis of the trainer judgment and experience Facilitate rather than orchestrate the exercise Minimal trainer intervention to let trainees recognise and correct problems Decide how much advice to traineesA Linked Knowledge Base for Simulation Learning 3 Linked Learning Workshop at ESWC 2011
  • 4. The need for a smarter solution...An automated way to "play" the storyboard Planning and Scheduling technology to support feeding the stimuli to traineesA consistent way to interlink and maintain knowledge Linked Data and Semantic Web technologies to model and maintain the knowledge for the simulation storyboards and the training sessions recordingA Linked Knowledge Base for Simulation Learning 4 Linked Learning Workshop at ESWC 2011
  • 5. Simulation Learning Architecture Simulation Trainer PLANNING Behaviour Simulation Learning SENSING DELIVERY Learning Simulation Learning Environment TraineesA Linked Knowledge Base for Simulation Learning 5 Linked Learning Workshop at ESWC 2011
  • 6. Modelling Behaviour Learning SENSING DELIVERYTrainee profile Asset modelling Registry data Scenario description Psychological data Audio and video assets Before the training NPC (Non-Player session (questionnaire) Characters) During the training session (self- assessment) Physiological data (this part of the modelling is more Holter monitoring similar to "usual" learning objects (heartbeat) modelling)A Linked Knowledge Base for Simulation Learning 6 Linked Learning Workshop at ESWC 2011
  • 7. Planning Knowledge Simulation PLANNINGSimulation Events Different communication media (email, video news, phone calls, ...) Trainees DecisionsCausality Timeline-based Planning "Synchronizations" (or Planning Rules) On the basis of a happened event, what other events can be triggered on what conditions and in which timeframe tpl:Event tpl:hasPlanningRule tpl:hasValue (isReferenceOf) tpl:hasRuleRelation tpl:hasTarget tpl:PlanningRule tpl:RuleTarget tpl:RuleRelation (Synchronization)A Linked Knowledge Base for Simulation Learning 7 Linked Learning Workshop at ESWC 2011
  • 8. Provenance Tracking for Planning Learning Session wasGeneratedBy(R) used(R) A1 P A2Event or Decision Event or Decision wasControlledBy(R) Completion and Inference rules of the OPM Consistency checking of the Ag simulation modelling (at design time) Trainees or NPC Analysis of average trainee decisions to discover common behaviours (after learning sessions) A Linked Knowledge Base for Simulation Learning 8 Linked Learning Workshop at ESWC 2011
  • 9. A Linked Knowledge Base Simulation Learning Environment other system components Training GUI Simulation SimulationTrainees Planner Web of Linked Data Trainer Knowledge GUI Trainer Base A Linked Knowledge Base for Simulation Learning 9 Linked Learning Workshop at ESWC 2011
  • 10. Some notes on the deployment Pandora Environment Pandora Environment Local Installation 1 Local Installation 2 Pandora Box Pandora Box Local Local KB Global KB KB Web of Linked Data LAN boundary LAN boundaryDistinction between local ald global uner two perspectives: Private vs. public (preserve confidentiality and privacy) Commercial vs. non commercial (scenario description is a business asset for learning organizations!)A Linked Knowledge Base for Simulation Learning 10 Linked Learning Workshop at ESWC 2011
  • 11. Lessons learnedKnowledge technologies are crucial for simulation learningLinked Data technologies can be exploited to Reuse and link to pre-existing knowledge Share simulation modelling between different systemsSemantic Web technologies are useful "A little semantics goes a long way" Some reasoning can be used for consistency checking (Open Provenance Modelling)A Linked Knowledge Base for Simulation Learning 11 Linked Learning Workshop at ESWC 2011
  • 12. Thanks for your attention! Any question? A Linked Knowledge Base for Simulation Learning Paper Authors: Irene Celino, Daniele DellAglio Contact: Irene Celino – Semantic Web Practice CEFRIEL – ICT Institute, Politecnico di Milano email: irene.celino@cefriel.it – web: http://swa.cefriel.it personal website: http://iricelino.org phone: +39-02-23954266 – fax: +39-02-23954466 slides available at: http://www.slideshare.net/iricelino Linked Learning Workshop at ESWC 2011 – Heraklion, Greece – May 29th 2011