A semantic approach to expert system for e-Assessment of credentials and competencies

Authors:
Oksana Biletska;Yevgen Biletskiy;Howard Li;Ruslan Vovk
Affiliations:
University of New Brunswick, P.O. Box 4400, 15 Dineen Drive, Fredericton, E3B 6B9 Canada;University of New Brunswick, P.O. Box 4400, 15 Dineen Drive, Fredericton, E3B 6B9 Canada;University of New Brunswick, P.O. Box 4400, 15 Dineen Drive, Fredericton, E3B 6B9 Canada;V.N. Karazin Kharkiv National University, 4 Svoboda Square, Kharkiv 61077, Ukraine
Venue:
Expert Systems with Applications: An International Journal
Year:
2010

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Abstract

The Prior Learning Assessment and Recognition (PLAR) is a labor-intensive process for academic advisors, evaluation services, graduate schools, registrars, learners, and other individuals and organizations responsible for assessment of learner's credentials and competencies with the purpose of continuing (lifelong) learning. The present paper describes an approach to build an expert system for electronic assessment (e-Assessment) of academic credentials and competencies, which is an e-Learning application intended to essentially help assessors to conduct their work more effective and efficient. The proposed approach uses the semantic web technologies, such as RDFS ontologies and POSL rules to convert academic credentials between educational institutions and make correspondences between the learner's competencies and credentials.