Working Group Details
SCORMRENEW - Working Group for Renewing SCORM Standards
|Working Group Chair||
|IEEE Program Manager|
IEEE 1484.12.3-2020 - IEEE Standard for Learning Technology--Extensible Markup Language (XML) Schema Definition Language Binding for Learning Object Metadata
This Standard defines a World Wide Web Consortium (W3C) Extensible Markup Language (XML) Schema definition language binding of the learning object metadata (LOM) data model defined in IEEE Std 1484.12.1TM?2002. The purpose of this Standard is to allow the creation of LOM instances in XML, which allows for interoperability and the exchange of LOM XML instances between various systems. This Standard uses the W3C XML Schema definition language to define the syntax and semantics of the XML encodings.
A conceptual data schema that defines the structure of a metadata instance for a learning object is specified in this standard. For this standard, a learning object is defined as any entity, digital or non-digital, that is used for learning, education, or training; a metadata instance for a learning object describes relevant characteristics of the learning object to which it applies. Such characteristics can be regrouped in general, life cycle, meta-metadata, educational, technical, educational, rights, relation, annotation, and classification categories. The conceptual data schema defined in this standard specifies the data elements of which a metadata instance for a learning object is composed and allows for linguistic diversity of both learning objects and the metadata instances that describe them. It is intended that this standard will be referenced by other standards that will define the implementation descriptions of the data schema, so that a metadata instance for a learning object can be used by a learning technology system to manage, locate, evaluate, or exchange learning objects. The intent of this standard is to specify a base schema, which can be used to build on as practice develops, for instance in order to facilitate automatic, adaptive scheduling of learning objects by software agents.