Abstract:

The macro design phase of learning paths starts with the content analysis. Unfortunately this activity involves some weak points related to the process management and the loss of information risk. Therefore in the last years concept maps have become a useful tool in order to tackle this issue: as formal representation of knowledge system of courses they’re also an output of the content analysis. On the other hand our experience shows how a concept map is often a closed tool exclusively used to make knowledge systems more explicit. Rarely, in fact, the map is an aid to supply contents or assess learning activities.
In the last years a new content analysis approach has been developed: the study of a concept starting from its main categorizations in order to identify its “basic structure”. In such context, the formal representation of contents in a semantic way can’t be just defined by concept maps but needs more complex and sophisticated tools, the “ontologies”.
The present paper develops the hypothesis OWL ontologies can be used in the instructional design process, as content analysis and formal representation tool. In particular it wants to show how and at which point ontologies can be alternative or complementary to concept maps.
According to our hypothesis, “ontologies” could support the macro design phase by solving some conceptual gaps, in particular the transition from the Formal representation of contents of a conceptual map and the definition of the learning objectives tree hierarchic structure. Moreover they can be used in the micro design and assessment phase and also can be useful to design a new course. That will imply new ways to define the Semantic Density, a fundamental parameter to identify the lesson structure and flow and define learning time. With a dynamic and linear vision of the course knowledge domain, they could allow defining learning objectives structures as flowcharts.
In this sense, we present a research method articulated in 7 activities:
1. Identification of the content to analyze.
2. Concept map definition (with Cmap Tools).
3. Ontology definition (with Altova Semanticworks).
4. Work methodology definition to allow instructional designers creating ontologies through Semanticworks.
5. Comparison between map and ontology to identify differences, similarities, advantages and disadvantages.
6. Theoretical model implementation to define a content semantic density (related to a learning objective) depending on its ontological analysis (hierarchies and categorizations check).
7. Identification of a possible integration between ontologies in the learning design standardized process.

Finally, in order to concretely evaluate the opportunities ontologies entail, we defined from the same content (a math concept from Wikipedia) a map and an ontology. Then we compared the tools in three ways: (a) methodological, by underlining the relative semantic analysis functions and possibilities; (b) applicative, by defining how they can be useful in all the process phases and in which specific domains (for instance content analysis, semi-structured tests measurement, customized learning paths); (c) managerial, by defining how these tools can be part of the design process.
The research output was a guideline to define ontologies with didactic objectives, a document being part of a more extended methodology to manage any sort of content.

Keywords:

Ontology, content analysis, semantics analysis, formal representation, conceptual map, semantic density, objectives tree.