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Learning Design Engines as Remote Control to Learning Support Environments

Learning Design Engines as Remote Control to Learning Support Environments. Andreas Harrer , Nils Malzahn, Kay Hoeksema, Ulrich Hoppe COLLIDE research group Institut für Informatik und interaktive Systeme, Universität Duisburg-Essen. Outline of the Talk.

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Learning Design Engines as Remote Control to Learning Support Environments

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  1. Learning Design Engines as Remote Control to Learning Support Environments Andreas Harrer, Nils Malzahn,Kay Hoeksema, Ulrich Hoppe COLLIDE research group Institut für Informatik und interaktive Systeme, Universität Duisburg-Essen

  2. Outline of the Talk • Motivation: „Unscripted“ Learning Support Environments and „Scripting“ with Learning Design • The Remote Control Approach • Example Scenario • Implementation Prototype • Further Work

  3. Learning Environments and Learning Flow Models • A wide variety of Collaborative Modelling, Argumentation and Inquiry Learning Environments are already existing • Belvedere (Suthers 1995 passim) • CoLab (de Jong, van Joolingen et al.) • ModellingSpace, Synergo (Avouris et al.) • CoolModes, FreeStyler (Hoppe et al.) • Most of these environments do not explicitly follow or offer a process structure

  4. Using Process Structures for Learning Environments • Introducing explicit Process Models provides • Students a scaffold for their learning • Teachers support in setting up their intended process (e.g. with different group settings, roles and tools) • Researchers opportunities to evaluate efficiency of scripts

  5. Implementation Alternatives • For existing Learning Environments there are two options for introducing the process model • Implementing a (proprietary) process modell within the learning environment, i.e. „Build an own engine“ • Using existing engines as external control to the learning environment, i.e. „Engine as remote controller“ • The first option has to be developed completely separate for each learning environment, the second can be re-used for several

  6. The Engine as Remote Controller (ERC)

  7. An Example Process

  8. Modelling the Scenario in LD • Map each phase to a learning activity • Properties for • Current activity • Voting_demanded • Voting_active • Voting_result • Consensus_achieved • On each state transition a Cool Modes workspace is shown or hidden

  9. The Process within Cool Modes • Communication Primitive „Show workspace for Voting Phase“

  10. „Remote Control Architecture“

  11. First Implementation of the „ERC“ Approach • CopperCore as Learning Design Engine • Cool Modes as Learning (Support) Environment • Creation of events in the engine extension • Remote Control Component encapsulates mapping from LDE events to general communication primitives • uses the Java Message Service (JMS) to publish the primitives to the translators subscribing to the Remote Control • Mapping of primitives to Cool Modes functionality by a “Cool Modes translator” providing the remote interface • „Show workspace for Voting Phase“ ::=„Add Voting Plugin“ „Initialize Workspace“ „Provide Result“

  12. One step further: protoype of ISIS – Integrated Science Inquiry System

  13. CoLab and Cool Modes integrated

  14. Outlook • At the moment we are in the process of generalizing and extending the vocabulary of communication primitives useful for different LSEs • Mapping of primitives to concrete LSEs, like Cool Modes and CoLab. • Abstract direct (low-level) interoperation of LSEs to define mode of interoperation at LD level

  15. Wrapping it up… • Collaborative Learning Environments and Learning Design can and should be used in combination • Model Learning Designs in the Collaborative Tools with different levels of specification (that‘s a different story about LD editors…) • Use the Learning Design and Engines to introduce process support in „non-scripted“ learning environments

  16. Thank you! Please feel free tocomment and ask…

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