1 N. Capuano 1, M. Gaeta 1, R. Iannone 1, F. Orciuoli 2 1 Centro di Ricerca in Matematica Pura ed Applicata, {capuano, gaeta, 2.

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Presentation transcript:

1 N. Capuano 1, M. Gaeta 1, R. Iannone 1, F. Orciuoli 2 1 Centro di Ricerca in Matematica Pura ed Applicata, {capuano, gaeta, 2 MoMA Srl, Learning Design and run-time resource binding in a distributed e-learning environment

2 Introduction  Pedagogies in e-learning systems.  Personalized Learning experience.  Educational e-content repositories and networked infrastructures.

3 Our Goals  Providing an extension of IMS LD to support domain-independent pedagogies.  Building personalized Unit of Learning (UoL) based on didactical domain ontology-based.  Defining a distributed UoL delivery architecture.

4 IMS Learning Design (Brief introduction)  Level A: meta language XML-based  Level B: enhances sequencing by properties and condictions  Level C: notification support

5 IMS Learning Design (Brief introduction)  Step 1: title, learning-objectives, prerequisites

6 IMS Learning Design (Brief introduction)  Step 2: roles, environments, activities

7 IMS Learning Design (Brief introduction)  Step 3: multi-user sequencing

8 IMS Learning Design (Brief introduction)  Level B: properties

9 IMS Learning Design (Brief introduction)  Level B: conditions

10 IMS Learning Design (Brief introduction)  Level C: notification

11 IMS LD drawbacks  Learning design scenarios implement domain-dependent pedagogies.  Learning processes cannot be really adaptive (based on learner profiles).  E-learning scenarios don’t exploit some advantages of distributed infrastructures.

12 Scenario: Building a UoL 1. Pedagogy construction Instructional designer builds a pedagogy using IMS LD language …

13 Scenario: Building a UoL 2. Didactic domain modeling Domain experts model didactic domain through ontologies …

14 Scenario: Building a UoL 3. UoL construction Teacher realize UoL using pedagogy and concepts …

15 Scenario: UoL delivery architecture  UoL Delivery Service  Localization Service  Repositories Is based on three type of distributed services:

16 Scenario: UoL delivery architecture

17 Scenario: UoL delivery architecture UoL Delivery Service that is composed by three tiers:

18 Scenario: UoL delivery architecture An UoL delivery will walk across two phase: startup and run.  Retrieve target concepts  Query Localization Service for repositories  Query repository for LO metadata  Filter LO metadata respect activity parameters  Perform binding between activities and real LO Startup phase:

19 Scenario: UoL delivery architecture An UoL delivery will walk across two phase: startup and run.  Detects the resource identificator and repository URL  Get WSRP mark-up from the repository’s delivery port  Compose the overall GUI of UoL and return complete WSRP mark-up to the client Run phase:

20 Conclusion and …  Extension of IMS LD to meet the need for domain-independent pedagogies.  An ontology-based approach merged with independent pedagogies to obtain personalized units of learning.  A distributed infrastructure for personalized units of learning delivery.

21 … future work  Develop the presented delivery architecture extending the IWT (Intelligent Web Teacher) platform implemented by MoMA.  Enrich the IWT platform with a set of authoring tools to cover all phases of units of learning building process.  Nowadays we are making experience with Coppercore and Reload opensource projects.

22 IWT overwiev  Intelligent Web Teacher is an extensible application framework for building learning solutions  It provides software and technologies building blocks for implementing domain specific learning solutions  It has been designed for supporting the emerging learning scenarios (personalised learning path, knowledge management, any time, any place and any pace access to learning services etc.)  It doesn’t exist a solution that fit all need  It should facilitate Learning Object reuse