IMS Learning Object Discovery and Exchange - Summary
|Although the use of learning platforms is becoming common in most educational organizations, and the number of learning objects available online, for free or by subscription, is huge, most of these learning objects are not globally discoverable, which hampers their potential use and reuse. Improving access to these learning objects would have a significant impact on learning.
Over the last few years, IMS has produced specifications that make it easier to exchange and reuse general-purpose learning objects: QTI, Common Cartridge, Content Packaging, Simple Sequencing, Learning Design. All of these specifications allow specific types of learning objects to be transferred between systems and reused but do not address the issue of how this content can be found. IMS has also produced specifications such as Learning Resource Metadata and VDEX that aid discovery by unifying the descriptions of this content. The missing piece in this collection of specifications is a protocol to support the discovery and exchange of all this interoperable content.
The IMS GLC Learning Object Discovery & Exchange (LODE) specification aims to facilitate the discovery and retrieval of learning objects stored across more than one collection.
LODE is based on the following assumptions:
- Learning objects are described by metadata such as IEEE LOM or Dublin Core.
- Multiple metadata instances might be necessary in order to adequately describe all the aspect of a learning object (i.e., in order to provide the information necessary to support the LODE use cases).
- Metadata can be gathered to create searchable catalogues of learning objects.
- Consulting such metadata catalogues is the main way to obtain the information necessary to search for learning objects, assess their usefulness, and retrieve them.
- Metadata catalogues are stored in repositories.
- Repositories can be searched programmatically using a standard Application Programming Interface (API) such as the Simple Query Interface (SQI) or Search/Retrieve with URL (SRU).
- Large catalogues can be created by harvesting (i.e., mirroring) metadata stored in repositories using protocols such as the Open Archives Initiative – Protocol for Metadata Harvesting (OAI-PMH).
|IMS LODE can be seen as a glue specification that profiles existing general-purpose protocols in order to take into account requirements specific to the educational domain, rather than creating new protocols. It proposes three main data models:
- A LODE Context Set for the Contextual Query Language (CQL): a data model for the attributes of learning objects, which can be used for search by expressing educationally meaningful queries;
- A data model, named Information for Learning Object eXchange (ILOX), that organizes sets of metadata on learning objects to be used in data exchange; and
- A data model, named Learning Object Repository Registry Data Model, for learning object collections, to be used in discovering and configuring access to those collections.
|The diagram illustrates how the IMS LODE specification can be combined with other specifications to permit to a LODE Client (i.e., a system that relies on the IMS LODE specification to discover and access learning objects) to actually obtain such learning objects.
IMS LODE at work
|Learning objects are described by metadata stored in repositories. The latter use different search and/or harvesting protocols (e.g., SQI, SPI, OAI-PMH) to expose metadata. In order to get access to this metadata, the first step is to discover the repositories in which it is stored.
The IMS LODE Registry Data Model provides a consistent way to describe repositories, their collections of learning objects and metadata, and the protocols they support. This enables the registration of repositories in a central registry that can be accessed by LODE clients. When consulting a LODE Registry, a LODE Client obtains repository descriptions that contain all the information needed to automatically connect to the repositories and get access to their metadata collections.
For those repositories that support search protocols such as SQI or SRU, the LODE Context Set for CQL (LODE CQL) enables LODE Clients to express queries in terms of learning object attributes.
Finally, whatever the protocol used by a LODE client to obtain metadata (search or harvesting), using LODE ILOX to organize the different metadata instances returned by this protocol ensures that all the information necessary to get access to learning objects is present and well-organized, without confusing the kinds of learning object described, and can be handled easily.