Ontology of Learning Object Content
Structure
Jelena JOVANOVIû, Dragan GAŠEVIû
FON – School of Business Administration, University of Belgrade
Jove Ilica 154, 11000 Belgrade, Serbia & Montenegro
Katrien VERBERT, Erik DUVAL
Dept. Computerwetenschappen, Katholieke Universiteit Leuven
Celestijnenlaan 200A, B-3001 Leuven, Belgium
Abstract. This paper proposes an ontology that enables a formal definition of
Learning Object (LO) content structure. The ontology extends the Abstract Learning
Object Content Model (ALOCoM) with concepts from information architectures. It
defines a number of concepts that represent different types of content units and it
specifies their structure. Formalising structural aspects of LOs, the ontology facilitates
re-purposing of LOs at different levels of content granularity, i.e. LOs in their entirety
and their components. Furthermore, being a generic LO content model, the ontology
serves as an integration point of heterogeneous LO content models.
Introduction
There is an increasing interest in the learning technology community for repurposing
learning objects (LOs) [1]. Presently, authors of learning materials employ a cut & paste
approach when composing new LOs out of components of existing ones. Nonetheless, such an
approach is non-scalable in terms of maintenance, since each time you copy a content unit, you
create a new place that needs to be maintained [2]. Additionally, the process tends to be error-
prone, and due to its inherent monotony, easily becomes both bothering and time consuming.
The authors are in a much better position if access to the components of LOs and their
composition into meaningful units is made, at least partially, automatic. A possible solution
employs a more reusability prone format of LOs that makes their structure explicit and thus
enables reusability of LO components as well. This can be accomplished through provision
of a flexible model of LO content structure. An explicit content structure allows the
disaggregation of a LO into its constituent components. Those components, enriched with fine-
grained descriptions (metadata), increase the findability of relevant content units.
Ontologies and Semantic Web technologies can be a solid basis for solving the
aforementioned problem, as an ontology gives a formal specification of the shared
conceptualization of a certain domain. For the domain of e-learning, we found a classification
of ontologies suggested in [3] relevant. The classification differentiates between: a) content
(domain) ontologies describing the subject domain of a content unit, b) context (didactic)
ontologies formally specifying the educational/pedagogical role of a content unit, c) structure
ontologies providing a shared conceptualization of how content units can be assembled
together to form a coherent learning whole.
High level of LO re-purposing can be achieved if learning materials are broken down
into small content units that can be easily handled. Accordingly, concepts from the structure
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ontology are especially useful. If we have LO repositories with learning content disaggregated
to content units of the lowest level of granularity (e.g. a single image, text fragment or
audio/video clip) and presented in a structure ontology-aware format, we will be able to make
the process of composing new learning materials out of components of existing LOs (partially)
automatic. Furthermore, this structure related information would also be of great importance to
a dynamic assembly engine of an Adaptive Learning System when combining content units
into a meaningful and well structured learner tailored presentation.
In this paper, we present an ontology that we propose for the formal specification of LO
content structure. The ontology extends the Abstract Learning Object Content Model
(ALOCoM) that defines a framework for LOs and their components [4], with concepts from
the Darwin Information Typing Architecture (DITA) – an XML-based architecture for
authoring, producing, and delivering technical information that is easy to reuse [2].
The paper is organized as follows: in the next section we give a concise overview of the
conceptual origins of the ALOCoM ontology and we briefly describe the ontology
architecture. In the second section we explain the ontology implementation in detail. Section 3
explains the enabling role that the ontology has in achieving interoperability among different
content models and Section 4 concludes the paper.
1. Conceptual Solution
This section explains the conceptual origins of the ontology, thus enabling easier
comprehension of the ontology architecture and design.
The Ontology Origins
As we stated in the introduction, the proposed ontology is a generic content model that
defines a framework for LOs and their components [4]. As Figure 1 suggests, the model
differentiates between Content Fragments (CF), Content Objects (CO), and Learning Objects (LO).
Figure 1. A sketch of Abstract Learning Object Content Model
CFs are content units in their most basic form, like text, audio and video. Basically, CFs
are raw digital resources. They can be further specialized into discrete (graphic, text, image)
and continuous (audio, video, simulation and animation) elements. COs aggregate CFs and add
navigation. Navigation elements enable proper structuring of CFs within a CO. Besides CFs, a
CO can include other COs as well. At the next aggregation level, a LO is defined as a
collection of COs with an associated learning objective.
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