Complete metadata records in learning object repositories: some evidence and requirements

Abstract

A learning object can be considered as a unit of instructional content for which a metadata record describing its characteristics and intended educational usage is provided. Metadata records can be used to develop effective search and location of learning objects, and also to develop automated or semi-automated selection and composition tools. In consequence, the quality of metadata records is a critical point for applications, especially if consistent and standardized software tools are desired. Completeness is one of the essential facets of metadata quality, which can be defined in terms of the metadata elements required for each functionality or usage. The eventual emergence of a global space for learning object-based education requires the creation of learning object repositories providing large collections of contents in a form accessible to standardized software. These repositories are called to play a central role in automated approaches to e-learning, since they provide the required support for learning object access and search facilities, oriented not only to humans but to software agents or systems. In consequence, completeness of metadata records becomes a key requirement for learning object repositories. Nonetheless, metadata creation is a time-consuming and laborious process, and current basic standards for learning object metadata allow for a large degree of flexibility in metadata edition. These two factors combined may eventually result in incomplete and poorly structured metadata. In this paper, the completeness of learning object metadata of samples obtained from the MERLOT and CAREO repositories are analyzed from that viewpoint, using the IEEE LOM standard as a reference framework. The paper concludes with a proposal for the specification of completeness levels as compliancy requirements for learning-related services or processes.Keywords: Learning objects, metadata, learning object evaluation, learning object repositories. Biographical Notes:Miguel A. Sicilia obtained a university degree in Computer Science from the Pontifical University of Salamanca, Madrid, Spain, in 1996 and a Ph.D. degree from the Carlos III University in 1999. From 1997 to 1999 he worked as an assistant professor and later on as a part-time lecturer at the Computer Science Department of the same university. He also worked as a software architect in e-commerce consulting firms. From 2002 to 2003 he worked as a fulltime lecturer at the Carlos III University, after which he joined the University of Alcalá. His research interests are primarily in the areas of adaptive hypermedia, learning technology, and human-computer interaction, with a special focus on the role of uncertainty and imprecision handling techniques in those fields. Starting from 2001, she is associate professor at Computer Science Department of the University of Alcalá and she is a member of the Information System Engineering group of this University. Her research interests mainly focus on topics related to human-computer interaction and knowledge r...

Generating metadata for cyberlearning resources through information retrieval and meta‐search

“…Sampson () proposed competence‐based metadata for educational resources rooted in the IEEE LOM (Learning Object Metadata) metadata schema along with a real‐world case study, e‐Access2Learn system, which aims to provide tools and services for the development and sharing of accessible eTraining Resources. Similarly, Sicilia, Garcia, Pages, and Martinez (), Retalis (), Neven and Duval () qualitatively compared different metadata characterization methods for learning object repository and e‐Learning, which assumed an existing high‐quality resource repository was available. Balatsoukas, Morris, and O'Brien () compared different approaches and different levels of content aggregation for learning objects, which is important for merging different types metadata into a unique explicit machine‐readable metadata schema.…”

Metadata Quality Evaluation of a Repository Based on a Sample Technique

“…M.A. Sicilia et al 'consider machine-understandability as a mandatory requirement for completeness of metadata records' [8].…”

Metadata for semantic and social applications<br />DC- 2008 Berlin

“…The application profile plays the role of the judge by selecting certain metadata fields to be accounted as mandatory or optional. A remarkable study on the completeness of a metadata record, focusing on educational resources (learning objects), is included in (Sicilia et al, 2005).…”