Sharing an ontology in Education: Lessons learnt from the OURAL project

Grandbastien, Monique; Azouaou, Faiçal; Desmoulins, Cyrille; Faerber, Richard; Leclet, Dominique; Quénu-Joiron, Céline

doi:10.1109/icalt.2007.227

Cited by 11 publications

(11 citation statements)

References 4 publications

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“…There are several ontology development tools that implement concept model ontology in different languages. Our ontology experts utilize Protégé [9] to transform the conceptual map produced by the course tutors into a formal model by using the formal OWL language [10]. Figure 2 shows an OWL/XML/RDF syntax of relations between two classes and Figure 3 shows a part of Frame Systems concept map in Protégé.…”

Section: A a Methodology For Building Ontologiesmentioning

confidence: 99%

Ontological Modelling for Intelligent E-learning

Aggelopoulou

Pierrakeas

Artikis

et al. 2014

2014 IEEE 14th International Conference on Advanced Learning Technologies

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The evolution of scientific research as well as the development of the relevant technologies and methodologies in the area of distance learning fall within the scope of the objectives the Hellenic Open University whose mission is to provide distance education at both undergraduate and postgraduate level. To develop intelligent e-learning applications, we capture the semantics of the Computer Science module concepts with the use of ontologies, by following a specific methodology to build domain knowledge ontologies. We illustrate our approach by presenting the construction of the ontologies of the Artificial Intelligence & Expert Systems module.)

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Section: A a Methodology For Building Ontologiesmentioning

confidence: 99%

Ontological Modelling for Intelligent E-learning

Aggelopoulou

Pierrakeas

Artikis

et al. 2014

2014 IEEE 14th International Conference on Advanced Learning Technologies

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“…To elaborate, the OMNIBUS ontology provides a detailed modeling of learning instruction, instructional design and the concrete phenomena of education [21]. The Ontology of Instructional Items catalogs the "instructional semantics" of learning resources terminology [22], while the Ontoural, facilitates ontology-based learning environments by mapping the main actors and contexts of the learning process [23]. The AIISO ontology (Academic Institution Internal Structure Ontology) is more focused on the internal organization of academic institutions [24].…”

Section: Modeling Academic Activitymentioning

confidence: 99%

Creating the Context for Exploiting Linked Open Data in Multidimensional Academic Ranking

Triperina

Sgouropoulou

Xydas

et al. 2015

Int. J. Recent Contrib. Eng. Sci. IT

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Abstract-Academia is a complex socio-technical system with multiple aspects and constituents that involve various stakeholders. In order to address stakeholders' needs and to assist the institutional accountability, this complexity should be considered during the development of academic services. We have designed a dynamic multidimensional ranking approach, easily modifiable to address user requirements, so as to assess and compare the university performance with a clear view to the support of effective institutional strategic planning and policy making. Our approach comprises the following components: the AcademIS ontology to model the academic domain and its multiple dimensions, the AcademIS Information System to manage and display the academic information, published in Linked Open Data format and the visual-aided Multiple Criteria Decision Making component, to evaluate and rank the performance of the academic units. The data are aggregated from several sources, in different formats, LODified by our system, and presented to the user by the interface to ultimately assist the decision making process.

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“…Ontologies for the Use of digital learning Resources and semantic Annotations on Line (OURAL) is presented in Grandbastien et al (2007), the project includes people from several disciplines (educational science, computer science, and cognitive psychology) building e-learning services. The authors present the extracted class using Natural-language processing (NLP) techniques in unstructured texts about learning situation.…”

Section: Class Extractionmentioning

confidence: 99%

A Class Validation Proposal of a Pedagogic Domain Ontology based on Clustering Analysis

Alemán¹,

Somodevilla²,

Vilariño³

2018

CIS

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The knowledge bases of the Web are fundamentally organized in ontologies in order to answer queries based on semantics. The ontologies learning process comprises three fundamental steps: creation of classes and relationships, population and evaluation. In this paper the focus includes the classes creation, by introducing a class validation proposal using clustering analysis. As case of study was selected a pedagogical domain, where a corpus was semi-automatically built, from articles written in Spanish published in Social Sciences. Moreover, a dictionary containing classes, concepts and synonyms was included in the experiments. Clustering analysis allowed to verify the concepts that the experts considered as the most important for the domain. For the case of study selected, the cluster analysis step reports clusters with the same instances that the clusters defined by the experts.

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Sharing an ontology in Education: Lessons learnt from the OURAL project

Cited by 11 publications

References 4 publications

Ontological Modelling for Intelligent E-learning

Ontological Modelling for Intelligent E-learning

Creating the Context for Exploiting Linked Open Data in Multidimensional Academic Ranking

A Class Validation Proposal of a Pedagogic Domain Ontology based on Clustering Analysis

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