Learning object repositories and their standards

As specified earlier, the new eLearning systems advanced the idea of creating learning object repositories for re-use of learning content (LOs) across different eLearning platforms. Increasingly, open access learning object repositories have gained popularity because the learning objects can be used as part of a lesson, module or course on different eLearning platforms. The popularity of Internet searchable Learning Object Repositories (hereafter LOR) of high quality peer reviewed learning objects, with attributable authors’ copyrights, is accompanied by development of various search capabilities. Approaches depend on whether the learning object repositories offer full content or only the description of learning objects and relevant links to different repositories. McGreal (2008) divided the learning object repositories into three categories of provider offerings:

1. Content of LO and metadata,

2. Metadata with link to LO that are located in different sites,

3. Hybrid repositories from both categories 1 and 2, that host content and link to external learning object.

During their indepth analysis of LORs, Ochoa and Duval (2009) categorized the learning object repositories into six types:

1. Learning object repository, 2. Learning object referratory, 3. Open courseware Initiatives, 4. Learning management system,

6.2 Modeling of knowledge domain and learners 83 5. Institutional repositories,

6. Institutional repositories-University.

The categorization is derived based on whether the LOR is offering the LO as content, content and metadata, only a link of content, or only a link of content and metadata. The following descriptions offer examples of various categories of learning object repositories that are related to the above categorisation of learning objects repositories.

ARIADNE (The Alliance of Remote Instructional Authoring and Distribution Networks for Europe) Educational metadata is compatible with Learning Object Metadata (LOM). It promotes the use of electronical pedagogical material [128]. The repository, which was created for sharing and reusing LOs, is called the Knowledge Pool System. The description of LOs includes data elements which are grouped into six categories: General, Semantics, Pedagogical, Technical, Indexation and Annotations. The transformation of ARIADNE metadata into LOM metadata using XSLT was presented in [129].

MERLOT is a repository program of the California State University, which stands for Multimedia Educational Resources for Learning and Online Teaching. MERLOT is a free and open source learning object repository that provides links and annotations to peer reviewed assignments. It is developed to provide learning materials from different disciplines for teachers and students. This repository is made from contributions from individuals, higher education institutions and other partners with a common goal of improving worldwide education. OpenStax (then Connexions) is hosted by Rice University to provide authors and learners with an open space where they can share and freely adapt educational materials such as courses, books, and reports. The OpenStax CNX content is available in two formats: modules, which are like small "knowledge chunks," and collections, which are groups of modules structured into books or course notes, or for other uses. MIT Opencourseware is a repository initiated in 2001 at Massachusetts Institute of Technology. Since then, more than 2000 university courses have been digitized and published and made open and available for the higher education community worldwide.

The research project CWSpace [130], supported by MIT and the Microsoft Research iCampus program, has investigated and advanced metadata standards and protocols required for archiving the Opencourseware (hereafter OCW) material into the MIT institutional repository DSpace, and making the corpus available for learning management systems around the globe. Besides this, the Cloud eLearning developed in this research study contains learning materials from these repositories but it has a more open approach, by offering space also for those learning materials that are not controlled, but the reputation of each learning

material then is ranked based on the feedback (rating) that is derived from the users as part of their learning experience.

Standardization of Learning Object descriptions

Successfully re-using, sharing and retrieving learning objects for personalised use is only possible if LOs are tagged and described appropriately. This process of describing LOs through tagging can be accomplished manually and/or automatically [34]. Tagging the learning objects through fully automated process requires to investigate a number of research applications, where the process become even more complex when dealing with various formats of learning objects, such as: text, video and audio. Therefore for the scope of this PhD, tagging the learning objects manually or even semi-automatically is simpler when considering the time constrains that we have for this PhD.

International standardization of LO descriptions are essential for sharing and re-using LOs across different platforms. Nowadays, several metadata specification standards have emerged, such as:

• DCMI Dublin Core metadata standard,

• IEEE Learning Object Metadata (LOM) standard, • IMS Learning Resource Metadata Specification,

• SCORM ( sharable content object reference ) metadata specification.

DCMI Dublin Core Metadata This international standard for cross domain digital content description originated in 1995. However, in 2006 DCMI was under the review of terms in Dublin Core Metadata Element Set (DCMES), which resulted with new terms documentation from its usage board. DCMES facilitates the discovery of the web resources through its 15 Dublin Core elements, divided into three classes, as follows [33]:

• Content (title, subject, description, source, language, relation, coverage), • Intellectual Property (creator, publisher, contributor, rights),

• Instantiation (data, type, format, identifier).

Dublin standards have two levels - simple and qualified. There are 15 elements covered in Simple level and 18 elements in so called qualified level, adding: audience, provenance and Rights Holder as new elements.

6.2 Modeling of knowledge domain and learners 85 IEEE Learning Object Metadata (IEEE 1484.12.1) is a LOM standard for creating a well structured description of learning objects. This model specifies how a particular LO should be described and what vocabularies should be used while describing a particular LO. Good vocabulary choices aid classification, avoiding redundant elements and even polysemy words (words with more than one distinct meaning). This standard also guides how to bind LOM data (e.g., how LOM records should be represented using XML, RDF) [1].

Fig. 6.3 Learning Object Metadata hierarchy structure

As shown in Figure 6.3, the LOM consists of 9 particular elements: General, Life cycle, Meta-metadata, Technical, Educational, Rights, Relation, Annotation, and Classification. Each of the elements is divided further into sub elements, and so on. The sub elements derive the context of their parent elements, which differentiate the final sub elements even with the same names.

IMS Learning Resource Metadata Specification is provided by IEEE and is based on early standard specifications which were contributed by the IMS Project and ARIADNE, from the United States and the European Union respectively. The collaborators chose to extend the LOM standard capabilities by introducing the best practices for describing the LO into the IMS learning resource metadata, binding them through XML based data structure and transforming XML instances into IEEE LOM using XSLT.

The ADL (advanced distributed learning) network was established in 1997, and its aim was to provide the highest quality standardized eLearning for the Department of Defense in United States, adapted for individuals’ needs. Instead of achieving its goal, ADL developed and distributed the sharable content object reference model (hereafter SCORM) based on

XML and the ADL Registry, with financial support from the United States Department of Defense. The SCORM metadata elements are categorized into three groups: asset metadata, shareable content object metadata and aggregation metadata[28], which enable a successful sharing of LOs across different LMSs. SCORM metadata builds upon previous standards, such as the AICC (The Aviation Industry CBT Committee), IMS and IEEE, with the aim of creating a unified content model with associated metadata.

Using standardised metadata, most learning object repositories tend to enhance interoper- ability by using the two schemas, the Dublin Core and IEEE LOM. Some LORs provide LOs in content packages according to SCORM and IMS standard specifications, instead of being able to “transfer” the content into different LMS which support those standards.