Garabato - IMS-LD

  • Description of the case study pdf


Garabato is the name of an IMS-LD implementation on top of Cumbia. IMS-LD is a specification for defining workflows in an e-learning context, using components and learning materials conforming to several complementing specifications. In this context, IMS-LD is the central specification that is used to define learnflows, while the other complementing specifications serve to describe the interaction with other applications and the structure and contents of learning materials.

There are several requirements that are specific to the e-learning context and that we had not considered in the previous case studies. For example, in this domain it is fundamental to offer support for dynamic adaptation because instructors should be able to modify the learnflows, at run time, in response to the students’ performance. Another difficulty is the existence not only of activities that every student has to perform independently, but also of activities that require the joint work of several students. Furthermore, the close relation between IMS-LD and other specifications to integrate external services, applications, and learning materials, created some additional restrictions for the implementation.

IMS-LD turned out to be a very useful scenario to test the Cumbia platform. Because of its special characteristics, the platform had to be improved in many ways to accommodate features discovered during the development of the project.

Following the principles of Cumbia, Garabato was developed as the composition of several metamodels, which are shown in the following figure. The central metamodel in Garabato is called CumbiaLD, and it embodies the elements required to describe the structure of the learnflows, at the level A of the IMS-LD specification. CumbiaLD is complemented by the optional metamodel called XLD, which implements levels B and C of the specification.RoleD is the metamodel where IMS-LD users and roles are managed. The LDContents metamodel was defined to describe learning materials, and it supports all the elements required by the IMS-LD and IMS- CP specifications. Finally, Garabato also employed XTM to describe time restrictions over the learnflows.

Garabato Metamodels

The implementation of Garabato included the development of the engines, of a client for participants in the learnflows, of a console for monitoring the learnflows at run time, and an application to convert IMS-LD specifications into model specifications. The following figure shows screenshots of the client application and of the monitoring console.

Other documents (in spanish)

Nadya Calderón and Carlos Vega: Composición y adaptación de modelos ejecutables extensibles para aplicaciones eLearning. Caso IMS-LD pdf