July 2007 Volume 10 Number 3 - Educational Technology & Society

Accordingly, TANGRAM provides students with quick access to a particular type of content about a topic of
interest, e.g. access to examples of RDF documents or definitions of the Semantic Web (both topics belong to the
domain of Intelligent Information Systems).
To enable formal representation of learning content TANGRAM makes use of the aforementioned ALOCoM CS
ontology and ALOCoM CT ontology (see Section 3.1). Additionally, TANGRAM uses the domain ontology to
semantically annotate content units with appropriate domain concepts. We used an OWL binding of the SKOS Core
specification (Miles & Brickley, 2005) to formally represent a sub-domain of intelligent information systems.
However, note that TANGRAM is actually domain independent – to support any other subject domain it suffices to
provide TANGRAM with a SKOS-Core-compliant ontology of that domain. To perform its personalization task
TANGRAM heavily relies on its user model ontology. The system contains a repository of user models represented
in accordance with this ontology.
TANGRAM also makes use of a Learning Paths ontology that defines learning trajectories through the domain’s
topics. This ontology relates instances of the domain ontology through an additional set of relationships reflecting a
specific instructional approach to teaching/learning intelligent information systems. Hence, it can be regarded as a
simplistic form of a learning design ontology. Whenever a student requests a certain topic (i.e. domain concept) to
learn about, TANGRAM performs a sort of comparative analysis of data stored in the student’s model and in the
learning paths ontology in order to determine the student’s knowledge about the domain concepts required for
successful comprehension of the chosen topic. Information resulting from this analysis is used to provide adaptive
guidance and direct the student towards the most appropriate learning content for him/her at that moment (Figure 3).
Figure 3. A screenshot of TANGRAM
TANGRAM also enables a content author to upload a new LO into the repository of LOs with the idea of later being
able to reuse its components. The uploaded LO is decomposed into its components and its structure is explicitely
represented according to the ALOCoM CS ontology. Additionally, the author can easily attach semantic markup to
the uploaded LO, whereas TANGRAM automatically annotates the learning object’s components using its own IEEE
LOM profile (in RDF format).
As the previous discussion suggests, TANGRAM generally fits into the proposed framework: it decomposes LOs in
accordance with a content structure ontology (ALOCOM CS) and enables direct access to (and hence reuse of)
content units of diverse granularity levels; it annotates content units with concepts of an ontology of instructional
roles (ALOCOM CT); it annotates content units with concepts of the domain ontology structured in accordance with
the SKOS Core ontology; it keeps track of its users through the concepts and properties of its user model ontology.
Besides, the architecture of TANGRAM (Jovanović et al, 2006b) closely resembles the one presented on Figure 2.
The only part of the framework that TANGRAM currently does not support is the learning design. In particular, it
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