A Fuzzy Knowledge Representation Model for Student Performance Assessment

Knowledge representation models based on Fuzzy Description Logics (DLs) can provide a foundation for reasoning in intelligent learning environments. While basic DLs are suitable for expressing crisp concepts and binary relationships, Fuzzy DLs are capable of processing degrees of truth/completeness...

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Bibliographic Details
Published in2014 IEEE 14th International Conference on Advanced Learning Technologies pp. 539 - 540
Main Authors Badie, Farshad, Soru, Tommaso, Lehmann, Jens
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2014
Subjects
Cognition
Data models
E-Learning
Fuzzy Description Logic
Fuzzy logic
Fuzzy sets
Intelligent Educational System
Knowledge Representation
Ontologies
OWL2 Ontologies
Semantic Web
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Summary:Knowledge representation models based on Fuzzy Description Logics (DLs) can provide a foundation for reasoning in intelligent learning environments. While basic DLs are suitable for expressing crisp concepts and binary relationships, Fuzzy DLs are capable of processing degrees of truth/completeness about vague or imprecise information. This paper tackles the issue of representing fuzzy classes using OWL2 in a dataset describing Performance Assessment Results of Students (PARS).
ISSN:2161-3761
2161-377X
DOI:10.1109/ICALT.2014.157