A new approach for searching and selecting user-relevant MOOCs courses fitting the level of students' education and based on the semantic representation of the user's knowledge of the subject area is presented. This approach supports the search for relevant knowledge by the students during the active learning process of the course. The effectivity of the present ontology based technique is based on the fact that it is aimed on users with different levels of knowledge that can be represented as ontologies and thesauri.

http://ieeexplore.ieee.org/iel7/7387214/7397173/07397219.pdf

Semantic Web and ontologies for personalisation of learning in MOOCs

Об основаниях математики и физики

Mereological approach is an important instrument of ontological analysis that deals with the different aspects of the fundamental relations between the ontology's concepts “is a part” All mistakes of this phase result to the great problems on the understanding of the subject domain and student skills examining in the learning process We propose to classify the subtypes of all mereological relations of domain ontology for their more correct development

Use of Mereological Approach for Ontological Constructing in Education Tasks

It is complex to assess multi-level hierarchical teams, because the solution needs to organize their rapid dynamic adaptation to perform operational tasks, and train team members without sufficient competencies, skills and experience. Assessment also reveals the strengths and weaknesses of the whole team and each team member, which provides opportunities for their further growth in the future. Assessment of the work of teams needs external knowledge and processing methods. Therefore, this study proposed to use ontological approach to improve the assessment of multi-level hierarchical teams, because ontology integrated domain knowledge with relevant competencies of positions and levels in the hierarchical teams. Information on competencies of applicants was acquired in the portfolio analysis. After subdividing the hierarchical teams, appropriate ontologies and Web-services were used to obtain assessment results and competence improvement recommendations for the teams at various sublevels. The step-by-step team assessment method was described, which used elements of semantic similarity between different information objects to match applicants and equipment with team positions. This method could be used as a component of integrated multi-criteria decision-making and was targeted at specific cases of user tasks. The set of assessment criteria was pre-determined by tasks, and built based on domain knowledge. However, particular criterion were dynamic, and changed along with environmental at different time points. 

/pdf/hierarchical-aggregate-assessment-of-multi-level-teams-using-pnuxo6np.pdf

Hierarchical Aggregate Assessment of Multi-Level Teams Using Competency Ontologies

It is complex to assess multi-level hierarchical teams, because the solution needs to organize their rapid dynamic adaptation to perform operational tasks, and train team members without sufficient competencies, skills and experience. Assessment also reveals the strengths and weaknesses of the whole team and each team member, which provides opportunities for their further growth in the future. Assessment of the work of teams needs external knowledge and processing methods. Therefore, this study proposed to use ontological approach to improve the assessment of multi-level hierarchical teams, because ontology integrated domain knowledge with relevant competencies of positions and levels in the hierarchical teams. Information on competencies of applicants was acquired in the portfolio analysis. After subdividing the hierarchical teams, appropriate ontologies and Web-services were used to obtain assessment results and competence improvement recommendations for the teams at various sublevels. The step-by-step team assessment method was described, which used elements of semantic similarity between different information objects to match applicants and equipment with team positions. This method could be used as a component of integrated multi-criteria decision-making and was targeted at specific cases of user tasks. The set of assessment criteria was pre-determined by tasks, and built based on domain knowledge. However, particular criterion were dynamic, and changed along with environmental at different time points.

Acadlore Transactions on AI and Machine Learning

We consider actual trends in use of semantic technologies for development of the Web-oriented advisory software. Requirements and expressiveness of knowledge representation in this domain cause use of ontological knowledge model, and the Semantic Web standards and tools provide the technological foundation for creation of intelligent advisory applications that use external ontologies as sources of domain knowledge. Personification of advisory services needs in analysis of learning outcomes of informal and non-formal learning, and therefore we propose method of their formalization with use of background knowledge about with classifications of professions and qualifications in agricultural domain. This method is based on matching of semantic properties of information objects with different structure represented by atomic competencies. Services provided by advisory system are considered from the point of view of semantic technologies. Proposed approach is used for development of applied advisory system AdvisOnt aimed to combine the market of educational services with the labor market. AdvisOnt characteristics satisfy requirements to distributed semantic application.

Semantization of The Web-Oriented Advisory Software: Models, Methods And Technologies

Complex Information Objects Repository as a Component of the Semantic Analitic-Information Web-Oriented Systems Development

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