Interoperability issues between learning object
repositories and metadata harvesters

Ricard de la Vega1, Jordi Conesa2, Julià Minguillón2

1 Centre de Supercomputació de Catalunya, Barcelona, Spain,
rdelavega@cesca.cat
2 Universitat Oberta de Catalunya, Barcelona, Spain,
{jconesac, jminguillona}@uoc.edu

Abstract. In this paper we describe an open learning object repository on Statistics
based on DSpace which contains true learning objects, that is, exercises, equations,
data sets, etc. This repository is part of a large project intended to promote the use
of learning object repositories as part of the learning process in virtual learning
environments. This involves the creation of a new user interface that provides users
with additional services such as resource rating, commenting and so. Both aspects
make traditional metadata schemes such as Dublin Core to be inadequate, as there
are resources with no title or author, for instance, as those fields are not used by
learners to browse and search for learning resources in the repository. Therefore,
exporting OAI-PMH compliant records using OAI-DC is not possible, thus limiting
the visibility of the learning objects in the repository outside the institution. We
propose an architecture based on ontologies and the use of extended metadata
records for both storing and refactoring such descriptions.

1. Introduction

Nowadays, most educational institutions use learning content management systems in order to
provide learners with additional support in their learning process. Books have been the traditional
content used in such institutions, but new learning theories more oriented towards competence
acquisition and development rather than content consumption are changing this, promoting the
concept of activity in front of the concept of content. In this sense, learning objects are small
pieces of content that are supposed to help learners to achieve a specific learning goal, as part of
the activities performed during the learning process (Wiley, 2000). Ideally, learning objects are
self-contained, that is, can be taken independently; reusable, that is, context independent; can be
aggregated and are tagged with metadata.

Obviously, digital repositories are a way to organize learning objects (and their parts that can be
processed separately) in collections, although there are several specific issues that must be firstly
addressed. For example, an exercise (which is basically a text defining a problem and, optionally,
its solution, another text which may include references to the use of software or tables with data,
for instance) is a typical learning object. But, differently to classical items in a collection of a
digital repository, exercises may have neither a title nor even an author, the two main fields used
for finding a book. Other typical learning objects can be data sets, mathematical proofs,
equations, simulations, and so. Usually, learners search through these kinds of resources not by
title or author, but by keyword or, even better, using a hierarchical taxonomy specially designed.
Therefore, it becomes necessary to rethink the traditional way of describing learning resources,
using criteria related to the learning process but maintaining a minimum description for archiving
purposes. The use of metadata standards for describing learning objects such as IEEE LOM
(instead of Dublin Core) is also a possibility, although there is not a single solution to be found
superior than the rest. On the contrary, some authors point out that several standards and
specifications will (or should) converge in a near future for improving the description of learning
resources (Currier, 2008).

2. Learning object repository on Statistics

This work is part of a large project that takes place in a higher education institution, the Open
University of Catalonia (UOC), with the aim of promoting the development and acquisition of
competencies through the use of learning object repositories. The UOC is an online distance
university with more than 40,000 students and more than 2,500 staff including instructional
designers, teachers, tutors, academic and technical staff. The UOC uses a virtual campus as an
integrated e-learning environment that allows students to pursue their studies purely online. We
intend to design and develop a learning object repository that is not only useful as a mere
repository but, at the same time, its use becomes an active element of the learning process, so
students using the repository will achieve a set of competences.

As part of a pilot experience, an open learning object repository with resources on Statistics has
been built using DSpace as platform. This repository, named OER, has been designed with the
aim of providing learners with a comprehensive vision of the whole knowledge domain of
Statistics, trying to make of browsing and searching a true learning experience (Ferran et al.,
2009). In order to do so, learning objects in the repository have been tagged according to the
following minimum criteria: every resource is an element part of several taxonomies (one for
describing the Statistics domain of knowledge, another for describing the kind of resource and a
third one for identifying the course or degree the resource was created for), and it is described by
one or more keywords. Therefore, according to their nature, learning objects may have or not
title, author, creation date, etc., so they cannot be accessed by classical retrieval mechanisms used
in digital libraries or repositories. In fact, DSpace had to be customized to change the basic fields
used for searching and browsing, as well as the workflows related to the process of adding new
resources to the repository.

On the other hand, this repository is also used as a starting point for creating a new visual user
interface, so users will be able to browse and search for learning resources without using the
interface provided by DSpace. The main goal of this project is to promote the integration of
learning resources into the learning process, by allowing learners to tag, rate, make comments,
favorite and ask questions on learning objects which they consider useful, thus creating a social
network among learning resources and learners according to their interests (Córcoles et al., 2009).
These services allow learners to use their own words to describe learning objects, creating
folksonomies that need to be further analyzed in order to ensure and improve a certain level of
quality of the metadata (Kim et al., 2010). The main problem here is that current standards and
specifications do not provide full support to the information generated during the use of a given
learning object, although such information can be stored using RDF or any other XML-based
schema.

3. Interoperability with metadata harvesters

On the other hand, in order to give more visibility to these learning objects and encourage its
reuse beyond the university itself, the learning object repository can be exposed to external
metadata harvesters using the Open Archives Initiative Protocol for Metadata Harvesting (OAI-
PMH). Then, learning objects can be integrated by other repositories (or harvesters) with a greater
scope of potential users, such as MDX1 (Learning Materials Online). MDX is a cooperative
repository that contains digital materials and resources resulting from teaching activities carried
out in member universities, which currently are 10 (Huguet et al., 2007). This metadata harvester
also has been built using DSpace as platform and with an Old Dominion University OAI-PMH
plug-in. Currently now, MDX does not harvest metadata from OER, so the latter is virtually
invisible to the whole academic community.


1
http://www.mdx.cat