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Original article

Describing online learning content to facilitate resource discovery and sharing:the development of the RU LOM Core G. E. Krull, B. J. Mallinson & D. A. Sewry Rhodes University, Grahamstown, South Africa

Abstract

The development of Internet technologies has the ability to provide a new era of easily accessible and personalised learning, facilitated through the flexible deployment of small, reusable pieces of digital learning content over networks. Higher education institutions can share and reuse digital learning resources in order to improve their educational offerings. Descriptive language (known as metadata) is required to facilitate the search and retrieval of learning content. Various research offerings have been proposed to promote interoperable educational metadata. However, current metadata standards cannot accommodate the requirements of every community of users. This paper describes the development of an educational metadata application profile for describing learning resources within a South African higher education context.

Keywords

application profiles, higher education, knowledge based, learning objects, metadata, qualitative.

Introduction

E-learning can be used by higher education institutions to increase access to students and enhance teaching effectiveness. E-learning makes use of information and communication technologies (ICT), such as the Internet, to make connections between students, educators and educational materials. It enables increased accessibility to multiple and diverse learning resources and instructional activities (Mashile & Pretorius 2003). Learning technologies and e-learning enable education to be customised and individualised (McGreal & Roberts 2001). Interoperable descriptive metadata, consistently and systematically implemented, are critical to achieving the vision of easy access to shared and reusable learning resources (Friesen et al. 2002b). This paper examines the complexities of describing learning resources and creating metadata conformant with current learning resource metadata standards. An application profile is developed that can Accepted: 20 February 2006 Correspondence: G.E. Krull, P.O. Box 1982, Cramerview 2060, South Africa. Email: [email protected]

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be used to describe learning content within digital repositories and learning management systems for South African higher education institutions. Firstly, an introduction to ‘learning objects’ and metadata is provided followed by an analysis of the widely known IEEE learning object metadata (LOM) standard. Application profiles are investigated and applied to the implementation of LOM. An application profile for the South African higher education context, known as the RU LOM Core, is then proposed and evaluated. LOM

A common, worldwide system is needed for labelling and describing not just e-learning courses, but individual ‘chunks’ of learning content. These small, granular ‘chunks’ could then easily be located and reused by other educational developers. These e-learning resources or ‘learning objects’ are the smallest element of digital stand-alone information required for an individual to achieve an enabling objective or outcome (Wagner 2002). The widespread use of learning objects has the potential to create a

& 2006 The Authors. Journal compilation & 2006 Blackwell Publishing Ltd Journal of Computer Assisted Learning 22, pp172–181

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learning object economy that will enable the sharing and reuse of digital learning materials for teaching and learning (Currier & Barton 2003). The descriptive language for learning objects (similar to the information in a library’s card catalogue) is metadata. Often simply defined as ‘data about data’, metadata refer to the systematic description of learning objects to facilitate searching and administration (Friesen et al. 2002a). In order to be accessible and reusable, learning objects must be tagged with metadata that provide the important and descriptive information about the object (Hamel & Ryan-Jones 2002). Metadata provide the means to describe and identify every piece of e-learning content so that content developers can efficiently find, select, retrieve, combine, use/reuse and target it for appropriate use (eLearning Consortium 2003). Metadata tagging refers to the creation of the metadata file that is to be placed within a repository (collection of learning objects). The main goal of the standardisation process within e-learning is interoperability among authoring content, tools and management systems. At the forefront of elearning standardisation is the development of metadata specifications. Metadata specifications describe the information used to accurately define educational resources, enabling potential learners and educators to find the content they need (Horton & Horton 2003). The aim is to solve the problem for learners, who cannot find the learning material they require, and course developers, who struggle to combine content and tools from different vendors due to interoperability deficiencies (Horton & Horton 2003). The IEEE Learning Technology Standards Committee LOM 1484.12.1 data model became the first educational metadata accredited standard in 2002 (IEEE 2004). This standard is a conceptual data model or metadata schema that specifies the data elements of which a metadata instance for a learning object is composed (Duval 2001). Most other educational metadata specifications are based on the LOM, or endeavour to be compatible with it (Anido et al. 2002). The LOM standard identifies 77 data elements, covering a wide variety of characteristics attributable to learning objects, and places these elements in interrelationships that are both hierarchical and iterative. At the top of the hierarchy of LOM elements are nine broad categories: General, Lifecycle, Meta-metadata, Technical, Educational, Rights, Relation, Annotation & 2006 The Authors. Journal compilation & 2006 Blackwell Publishing Ltd

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and Classification (IEEE 2004). The LOM elements, listed vertically, can be found in Fig 1. Included in the broad standard is the LOM XML Binding (1484.12.3), which provides machine-readable descriptions to ensure semantic interoperability. This part of the LOM standard describes an XML binding to enable the exchange of LOM instances between conforming systems that implement the 1484.12.1 data model (IEEE 2005). Effective metadata implementation requires a consistent interpretation of each element’s purpose and use. There are several factors limiting the wide scale use of the LOM standard. The number and variety of elements in LOM has created widely recognised difficulties for implementers, being notably resource intensive. Friesen and Nirhamo (2003) found the LOM implementers only use a small number of the LOM elements. Many of the available LOM elements are not populated when creating metadata. Additionally, few of the element iterations and field lengths are put to use. The LOM documentation provides, in some cases, brief and confusing descriptions and abstract complex vocabularies leading to difficulties in implementation (Friesen et al. 2002b). When adopting LOM, many implementers frequently make use of local vocabularies in order to increase community interoperability, sometimes in conjunction with LOM vocabularies. Additionally, there are several metadata elements that are used often, perhaps supporting the need for mandatory elements (elements that are always required in metadata records). More ‘concrete’ elements that describe intellectual content o1.2 Keywords4 and resource characteristics o5.2 Learning Resource Type4are far more frequently used than ‘abstract’ elements, such as o5.4 Semantic Density4. Friesen and Nirhamo (2003) propose that fewer and better-defined elements are more effective in metadata creation rather than the choice and interpretative possibilities currently in LOM. In a similar study, Godby (2004) proposes that the best prospects for interoperability are local application profiles and notes that interoperability decreases as institutional, linguistic and cultural boundaries are crossed. Application profiles

An organisation developing and managing learning objects can adopt the LOM standard or it may prefer to develop its own metadata scheme based on the stan-

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Fig 1 Application profile LOM elements.

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dard, known as an ‘application profile’. Practically, communities find it necessary to implement the LOM standard in ways that meet their specific applications, as no single metadata element set will accommodate the functional requirements of all applications. LOM is a general all-encompassing standard that has been created for use in as many communities as possible. An application profile seeks to be of use for a specific community. An application profile represents a ‘customisation’ of a standard for the specific needs of ‘particular communities of implementers with common application requirements’ (Friesen et al. 2002b). The intent of an application profile is to adapt or combine existing schemas into a package tailored to the functional requirements of a particular organisation, while retaining interoperability with the original base schemas. They facilitate the process of metadata creation because their element set and value spaces are less abstract (Duval et al. 2002). An application profile is more easily accessible as it is adapted to the needs of the specific user group. The community-based metadata have greater meaning within a community and enables better location and management of common resources. This enables implementers to declare how they are using standards. The metadata creation process can be an onerous one. The main reasons developers are not using learning objects is that they lack the technical knowledge to interpret and apply the technical guidelines in practice. Standards adoption has been low due to their complexity (Wagner 2002). Application profiles provide a simple mechanism to implement the standard. An application profile increases the semantic interoperability within a community of users, while preserving compatibility with the general standard user group (Duval et al. 2002). The development of application profiles has come about due to opposing forces. Few institutions have the capacity to undertake the development and promotion of an interoperable metadata standard. Yet there is also the pressure to innovate in an environment where a relatively new metadata standard is still being tested and may only partially address the issues in learning object management (Godby 2004). Building an application profile

There is diverse practice in defining and implementing application profiles (IMS 2004). In order to develop an & 2006 The Authors. Journal compilation & 2006 Blackwell Publishing Ltd

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application profile, it is important to understand the requirements of the profile and to define the purpose of the profile. The first step in the development of an application profile is thus to define its purpose and requirements. Secondly, it is essential to ensure that adequate resources are available for the creation and maintenance of the profile. The third step is to review the relevant standards, specifications and application profiles. This enables the developers to understand what is currently available and also follow existing recommendations for extensions, bindings and vocabularies. An existing profile may be used if it meets the requirements of the community. Fourthly, it is useful to determine the other application profiles with which the profile needs to interoperate (IMS 2004). Once the general framework of the application profile has been established, the detail of the profile is built. The task of adapting an abstract standard to meet the specific needs of local stakeholders requires interpretation, elaboration, extension and, in certain cases, simplification of their syntax and semantics (Friesen et al. 2002a). The policies and culture of the community and project also influence adaptation and interpretation. Defining an application profile generally encompasses several techniques (Duval et al. 2002). The first technique is cardinality enforcement. This is where the status of an element is constrained as either ‘mandatory’ or ‘optional’. The second technique is value space restriction. This occurs when standard definitions are refined and more prescriptive vocabularies are introduced. The third technique involves exclusion of some elements. Elements are excluded to provide a simpler sub-set of the original specification. The fourth technique involves specifying relationships and dependencies. For example, the presence of one data element may mandate that another element is present. Part of the adaptation is the elaboration of local metadata elements that have importance within the community, but which are not expected to have importance within a wider context. These communityspecific modules can be merged to form more complex metadata structures (Duval et al. 2002). It is noted that application profiles may not be required in every case. As all elements in LOM are optional, implementers can choose to implement all, some or none of the elements. In situations where metadata are created infrequently or limited metadata are required, the adoption of LOM is sufficient to meet

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the needs of these implementers. It is also noted that, where practical, applications should endeavour to implement the entire LOM conceptual data schema, even if many elements remain hidden from the end user. This will help ensure interoperability with other application profiles. Current application profiles

Numerous national and international initiatives have been established to investigate ways to develop, share and reuse learning objects with the vision of creating a learning object economy (Littlejohn 2003). The process of educational metadata standardisation is an ongoing process that has been instigated and sustained by the desire for interoperable descriptions of learning resources that allow for the sharing and reuse of learning content. Several metadata specifications have been developed in order to address the need for interoperability, all with links to the LOM standard. The Dublin Core Metadata Element Set (DCMES) is a notable specification and is the only accredited educational metadata standard, other than IEEE LOM. The DCMES is a general-purpose and widely adopted metadata specification targeted to resource location, developed by the Dublin Core Metadata Initiative. The DCMES consists of 15 core metadata elements that map directly to data elements defined in the LOM Standard (Dublin Core 2004). The DCMES is compact and the result of wide consensus and has become the foundation for many other initiatives. The simplicity of DCMES provides the benefits of lowering the cost of creating metadata and promoting interoperability. DCMES increases the accessibility of resources in cross-community domains. However, it does lack the semantic and functional richness of other specifications (Dublin Core 2004). The IMS has contributed throughout the evolution of the LOM standard, starting with the initial joint proposal with the Alliance of Remote Instructional Authoring and Distributed Networks for Europe (ARIADNE). IMS uses the LOM as a basis for its metadata specification – the IMS Learning Resource Metadata Information Model. IMS has also contributed to LOM by introducing best practice guides for metadata implementers and an XML binding specification. The current IMS specification consists of all 76 LOM elements (IMS 2004). The IMS has benefited its

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users by providing a best practice guide, an XML binding specification and an explicated version of LOM. The Advanced Distributed Learning (ADL) initiative’s Sharable Content Object Reference Model (SCORM) maps metadata elements into a hierarchy of three learning content elements: asset metadata, sharable content object metadata and content aggregation metadata. SCORM differs from other metadata specifications as it describes how to apply metadata to specific systems. SCORM has adopted the set of metadata elements described by the IMS Learning Resource Metadata Information Model (Anido et al. 2002). SCORM is widely used in the military and corporate training environments. SCORM provides the framework and detailed implementation reference that enables content, technology and systems using SCORM to interact with each other, thus ensuring interoperability, reusability and manageability. The maturation and broad adoption of SCORM can be seen in the interoperability of many applications and systems that are SCORM conformant (e-Learning Consortium 2003). The aim of ARIADNE is to promote the sharing and reuse of electronic pedagogical material. ARIADNE has developed the Knowledge Pool System for this purpose. One of the features of this system is the metadata specification. The metadata system uses LOM as its basis and works in a multilingual and multicultural environment (Anido et al. 2002). It takes into account the specific needs and requirements of a multilingual and multicultural European community. The Canadian Core (CanCore) initiative has been developed through the support of several Canadian educational institutions and projects (Friesen et al. 2002b). CanCore has been developed as a distributed national repository and has interpreted and refined the LOM standard for the needs of public education in Canada (Friesen et al. 2002b). CanCore aims to provide pragmatic solutions to facilitate adoption of metadata for application, thus providing direction and assistance to those making decisions about educational metadata (Friesen et al. 2002b). CanCore reduces the complexity and ambiguity of the LOM specification, by providing 15 ‘placeholder’ elements and 36 ‘active’ elements, all of which are optional. CanCore has also developed a set of comprehensive guidelines that facilitate the metadata creation process and enable the interoperability of the profile (Friesen et al. 2002b). & 2006 The Authors. Journal compilation & 2006 Blackwell Publishing Ltd

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This application profile has simplified the process of metadata creation for its users and created a means for exchanging resources and has a large market share in Canada. The development of UK LOM Core stems from the formation of a community of practitioners to identify common UK practice in the use of metadata in packaged e-learning content. From this identification, a set of guidelines has been developed to inform UK practitioners on the implementation of a minimum core of elements and associated vocabularies (UK LOM 2004). UK LOM Core has been heavily influenced by the work of CanCore. Elements have the status of mandatory or optional (UK LOM 2004). UK LOM Core has benefited its community through specifying common practice and ensuring interoperability in metadata implementation in the UK. The development of each of these application profiles has resulted in benefits for their respective communities of users. One resulting benefit is that it is easier and simpler to create metadata and also find learning content through the use of common metadata. Additionally, as each application profile is based on or compatible with LOM, the created metadata are still more widely interoperable. A comparison of these specifications has revealed a general consistency in the use of metadata elements. Figure 1 lists the LOM elements vertically, and the application profiles that include, exclude or otherwise qualify their use are listed horizontally. ‘M’ indicates mandatory elements, while ‘O’ indicates elements that are optional. This overview provides an indication of the consistency and divergence of the elements in each application profile. Each application profile has adopted a unique set of LOM elements. However, there are several elements that are common in all, for example, o1.2 Title4 and o1.3 Language4. The importance of these common elements in ensuring interoperability is thus underscored. There are several shortcomings of current metadata specifications that need to be addressed before the widespread use of educational metadata is embraced. These issues include reducing the complexity and resources required for metadata creation and adequate mechanisms to evaluate qualitative information (Friesen et al. 2002a). Additionally, there is no current application profile that meets the particular needs of the South African higher education environment. & 2006 The Authors. Journal compilation & 2006 Blackwell Publishing Ltd

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RU LOM core Context

The development of a local application profile is important in order to meet local needs, such as linguistic and cultural diversity, a lack of access to technology and high technological illiteracy, as well as educational policies. Diversity requires the promotion of linguistic and cultural neutrality and adaptability. The development of a local application profile is also anticipated to be of great benefit for the development of a national learning object repository for higher education learning content. The South African Higher Education environment is characterised by a limited technical infrastructure and rapid change. The use of e-learning technologies in South African higher education is constrained by issues inherent in a developing country, such as the digital divide. South Africa is a developing nation with linguistic (11 official languages) and great cultural diversity. South African higher education has undergone numerous transformations and restructuring processes in the past few years in order to redress social and structural inequalities, effectively utilise limited resources and address globalisation issues (S.A. Education Department 2002). E-learning programmes can provide increased access to informational resources and embrace transformation. However, e-learning projects are hampered by the lack of technical infrastructure, high operational costs, the lack of educator skills and low bandwidth (Mashile & Pretorius 2003). These and other issues call for the implementation of technically efficient and streamlined technologies and projects for increased adoption. Additionally, e-learning possibilities are affected by the curriculum transmitted and the context in which it is received. Most course material is designed and developed in other countries and does not always match the needs of South African educational policies. For example, educators have been required to adapt to South Africa’s revised educational policies, such as an Outcomes-Based Curriculum. Content developed elsewhere may be unsuitable to the social and cultural traditions in this country (Lelliott et al. 2000). Relevant South African educational policies include the recently gazetted National Qualifications Framework (NQF) and Unit Standards policies. The NQF is a quality assurance system within the educational sector that categorises qualifications into a hierarchy of

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levels. Similarly, vocation oriented qualifications are based on Unit Standards that are registered on the NQF (S.A. Council of Higher Education 2001). The NQF is an important framework for recognising the quality of learning content. These considerations need to be taken into account when developing a descriptive system (or metadata set) for learning content within the South African higher education context. Development of RU LOM core

RU LOM core was developed through the application of recommendations and guidelines of LOM and other application profiles as well as practical experiences in metadata implementation. The application profile was built by following the guidelines set out in IMS (2004) and Duval et al. (2002). The purpose of RU LOM core is to support the access, search, selection, use and management of learning objects within South African higher education. The requirements of the profile are that it is to be compatible with other LOM application profiles, facilitate the process of learning content discovery in a pragmatic way, meet the needs of educators and learners looking for quality learning content and do so within an environment that promotes sharing and reuse. Before the development of the application profile, it was determined that adequate resources were available for the creation of the profile. Existing relevant standards, specifications and application profiles were reviewed and applied. This included practical implementations and making use of recommendations for extensions, bindings and vocabularies. Specifically, the recommendations and guidelines of the UK LOM Core and CanCore were used in the development of RU LOM Core. It was determined that although a number of well-defined LOM application profiles exist, none of those surveyed sufficiently meet the requirements of the South African Higher Education community. Thus, the decision was taken to develop the RU LOM Core. RU LOM Core was developed through the exclusion of certain LOM elements, the restriction of vocabularies, cardinality enforcement and restriction of the order of multiple records. Elements were chosen based on likely utility of interoperation within a national repository. This research proposes a LOM application profile, together with a set of guidelines for its use in South African higher education. RU LOM Core takes

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into account the considerations of the South African higher education context, notably educational policies, linguistic diversity, limited technology and lack of educator skills. RU LOM Core is an application profile of the IEEE LOM standard that has been optimised for use within the context of higher education in South Africa. The development of RU LOM took place, in part, through implementing metadata using the guidelines provided by the LOM and several application profiles. The experiences gained during the metadata implementation process were incorporated into the development of the new application profile. The experiences of implementing metadata were found to be in accordance with those reported within the literature, such as Friesen and Nirhamo (2003). It was initially found to be difficult to create metadata, in the case where the metadata creators are not also the authors of the content. For example, it was difficult to know the author’s original intended learning outcomes when describing the content. This would support the view of collaborative metadata creation (Currier & Barton 2003). Some metadata elements were found to be very subjective and difficult to quantify, for example, o5.8 Difficulty4. However, it is this subjective metadata that can be more valuable than objective metadata for identifying relevant learning objects. This led to the view of their continued inclusion in RU LOM Core. RU LOM Core was developed in response to the diversity in technical infrastructure and educator technological skills in local higher education ICT. In order to ensure technical simplicity and widespread use, LOM elements were excluded from this application profile based on their exclusion in other LOM application profiles and difficulties presented in their implementation. For example, the technical aggregate element o4.4 Requirement4 was excluded because of the difficulty in establishing and maintaining vocabulary values and indicating optimal software. Furthermore, it is excluded from CanCore and its usage is not recommended in UK LOM Core. Another instance is the Educational element o5.1 Interactivity Type4, which was also excluded as the vocabulary space (‘active’, ‘expositive’, ‘mixed’) is not well understood (CanCore 2004; UK LOM 2004) and the descriptive characteristics can be described by other elements, such as o5.3 Interactivity Level4 and o4.1 Type4. A notable change in restricting a value space was the common use of South African English (‘en-ZA’), & 2006 The Authors. Journal compilation & 2006 Blackwell Publishing Ltd

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while allowing the use of a number of other languages, such as Zulu, for the element o1.3 Language4. Although this is supported in LOM, this element highlights the availability of tagging learning objects of different languages during implementation. This is also typical of application profiles that support multilingual societies, such as CanCore and ARIADNE. The value space of o1.6 Coverage4 was restricted to refer to the cultural context of the object. Thus, an object can be identified as being suitable to the social or cultural traditions of a particular society or notes the cultural and linguistic dominance of the content origin. Additional vocabulary restrictions have been made to focus on the higher education context. For example, the vocabulary of o5.2 Learning Resource Type4 includes tutorials, lecture presentations and assessments, while the o5.6 Context4 vocabulary includes undergraduate and postgraduate university levels. These additions have been based on the UK LOM Core value spaces and practical experiences in implementation. Certain elements were given mandatory status to ensure their inclusion in all metadata records, for example o1.2 Title4. This is to ensure greater interoperability between users of the RU LOM Core. Based on the implementation experiences, the Classification category recommends the use of the Dewey Decimal Classification (DDC) system, while additional relevant curricula guidelines may also be used. The application of these techniques ensures greater interoperability within the South African higher education community while retaining flexibility with the LOM standard and wider community. A comparison of application profile LOM elements, including RU LOM Core, can be found in Fig 1. For each LOM element, the application profile specifies the LOM element number, name, explanation, size, order, value space, data type, cardinality (‘M’ or ‘O’), an example, and finally, implementation guidelines. This specification is based on the LOM standard and the UK LOM Core. Evaluation of RU LOM Core

Once RU LOM Core was developed, sample metadata were implemented in order to evaluate the profile. Various computer-based tools have been developed to support and simplify the process of learning object & 2006 The Authors. Journal compilation & 2006 Blackwell Publishing Ltd

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creation. One such tool is a metadata editor. The evaluation made use of the RELOAD Editor (RELOAD 2004) for implementation. The RU LOM Core implementation guidelines were used in order to test their applicability and usefulness. RU LOM Core was tested in terms of suitability by describing a variety of learning objects created within the higher education context. A team of implementers created metadata for several learning objects at an undergraduate level within the disciplines of Accounting, Computer Science and Information Systems. These objects consisted mainly of interactive tutorials, assessments, lectures and readings. RU LOM Core conformant metadata were generated with the use of the RELOAD Editor. The creation of a unique metadata record for each learning object proved to be time consuming, and thus a ‘template’ metadata XML file was created that could be imported into other metadata records. This vastly improved the efficiency of the implementation process. The outcomes of this process revealed that all RU LOM Core mandatory elements were used in the metadata creation process. Additionally, the previous experience of metadata implementation assisted in quantifying subjective elements. The element definitions and guidelines of the profile were found to be sufficient for implementation, although minor revisions were made to improve clarity. Certain metadata elements were not used during the implementation process due to difficulties in their definition or the availability of other elements with similar characteristic descriptions. These included o4.4.1.4 Maximum Version4 (maximum version of required software), o5.1 Interactivity Type4 (predominant mode of learning), and o5.4 Semantic Density4. These elements have been removed from RU LOM Core. Additionally, the recommended usage of the DDC system for the Classification category was found to have somewhat limited usefulness. Thus, in addition to the DDC, relevant discipline classification guidelines, such as the international Information Systems Curricula Guidelines (IS2002 2002), were used to classify the learning objects in a more detailed manner. However, not all disciplines may be governed by similar guidelines and such additional classification may not be feasible. An electronic survey was conducted with the purpose of identifying the need for and awareness of

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metadata elements for describing learning content in South African higher education. The survey was also used as an evaluation mechanism for RU LOM Core. The metadata survey was conducted electronically, via the Web, and respondents consisted of South African educators working or interested in the field of educational technology. The survey consisted of a questionnaire categorised into three sections: respondents’ demographics, awareness and use of metadata; and RU LOM Core metadata elements. The survey made use of a five-point Likert scale (ranging from ‘very important’ to ‘no importance’) to rate the importance of the RU LOM Core metadata elements when faced with the situation of searching for and identifying relevant digital learning content. A pilot study was performed, before the survey was published on the Web, with members of the Departments of Computer Science, Education and Information Systems at the university. As a result of this pilot, questions were reformulated in order to improve their clarity. The administration of the survey was facilitated through the use of Questionmark Perception and was conducted electronically. Respondents had to click on a hyperlink to access and complete the survey online. A call for participation was sent to the members of the Computer Assisted Teaching and Training Society (CATTS). This is a society of students, graduates and affiliated members of the computer-assisted education faculty at the University of Pretoria, many of whom work in the computer-assisted education environment in South Africa. Although the response yielded a low rate of 17 respondents, these respondents are fairly representative of the potential community of users of the profile. This is due to the respondents working in the field of educational technology, most of whom are in the higher education environment. The survey may have been premature, since awareness of metadata is low in South Africa, with only six respondents working in projects where the need for metadata had been identified. Many respondents were also not aware of current metadata specifications, with less than half of respondents indicating an awareness of SCORM and IEEE LOM. However, the key results of the metadata survey indicated that the most useful elements for learning object description were perceived to be o1.5 Keyword4, o6.1 Cost4, o4.2 Size4, o4.1 Format4 and o1.4 Description4. The importance of these elements has thus been confirmed in RU LOM

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Core, where all of these elements have a mandatory status. This highlights a possible factor in promoting the interoperability of RU LOM Core. Another result was that more easily quantifiable elements, such aso5.2 Learning Resource Type4, were considered to be more useful than ‘abstract’ elements, such as o5.8 Difficulty4. This enhances the view of ensuring that metadata elements, particularly in RU LOM Core, are easily quantifiable. Respondents also indicated that due to limited bandwidth and technological skills, learning objects will be required in different delivery modes. For example, video can be presented as still images with audio transcripts. Based on these findings, RU LOM Core proposes the use of an additional element o4.8 Alternate Delivery Format4 as a mechanism to describe different delivery formats. The use of this element will be tested in further implementations. Several respondents noted that South African educational policies, such as NQF levels, needed to be taken into account more visibly when searching for relevant learning content. RU LOM Core has been enhanced in order to include these important considerations. Thus, learning objects can be classified in the o9 Classification4 category in RU LOM Core within the DDC system as well as within the NQF level framework. Conclusions and future work

The standardisation process for metadata specifications is a continuously evolving yet necessary process for the complete description of learning objects and their use. This process is particularly important in a developing country, where educational technology can help to bridge the digital and educational divides. This paper investigated learning object metadata and analysed several application profiles. Good progress has been made in the ability to create interoperable metadata in order to aid resource selection through the development of IEEE LOM and other specifications. However, there are still shortcomings with current metadata specifications. The RU LOM Core application profile was developed in order to meet the needs of learning content description in South African higher education. It allows for linguistic and cultural diversity and takes into account the educational policies and the lack of technological literacy within this environment. RU LOM Core was evaluated through a & 2006 The Authors. Journal compilation & 2006 Blackwell Publishing Ltd

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metadata survey and practical implementations. It serves as a starting point for learning object description in South African higher education and will be refined with further use. Further research will be devoted to testing the developed application profile in various systems and testing the interoperability of RU LOM Core with other application profiles. This will enable the refinement of the vocabularies and guidelines and ensure the relevance of the application profile. The development of this profile could be of great benefit in the creation of a learning object repository for learning content in the South African higher education community. References Anido L.E., Fernandez M.J., Caeiro M., Santos J.M., Rodriguez J.S. & Llamas M. 2002 Educational metadata and brokerage for learning resources. Computers and Education 38, 351–374. CanCore. 2004 The Canadian Learning Object Metadata Application Profile (CanCore) Guidelines v2.0. Retrieved 18/10/2004. Available at: http://www.cancore.ca Currier S. & Barton J. 2003 Quality assurance for digital learning object repositories: how should metadata be created? In Communities of practice, ALT-C 2003 research proceedings (eds J. Cook & D. McConnell), pp. 130–142. Association for Learning Technology, Sheffield. Dublin Core. 2004 Dublin Core metadata initiative home page. Retrieved 18/11/2004. Available at: http://dublincore.org Duval E. 2001 Metadata standards: what, who and why. Journal of Universal Computer Science 7, 591–601. Duval E., Hodgins W., Sutton S. & Weibel S. 2002 Metadata principles and practicalities. D-Lib Magazine 8, Available at: http://www.dlib.org/dlib/april02/weibel/04weibel.html e-Learning Consortium. 2003 Making sense of learning specifications and standards: a decision maker’s guide to their adoption. Retrieved 05/04/2004. Available at: http:// www.masie.com/standards/s3_2nd_edition.pdf Friesen N. & Nirhamo L. 2003 Survey of LOM implementations: preliminary report. Retrieved 11/06/2004. Available at: http://mdlet.jtc1sc36.org/doc/N0051-N0100.html. Friesen N., Mason J. & Ward N. 2002a Building educational metadata application profiles. In Proceedings of the International Conference on Dublin Core and Metadata for e-Communities (DC-2002), pp. 63–69. Firenze University Press, Firenze, 13–17 October, Florence, Italy. Friesen N., Roberts A. & Fisher S. 2002b CanCore: learning object metadata. Canadian Journal of Learning and Technology 28. Available at: http://www.cjlt.ca/content/ vol28.3

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