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dc.creatorTsaganou, G.en
dc.creatorGrigoriadou, M.en
dc.creatorCavoura, T.en
dc.creatorKoutra, D.en
dc.date.accessioned2015-11-23T10:50:31Z
dc.date.available2015-11-23T10:50:31Z
dc.date.issued2003
dc.identifier10.1016/s0957-4174(03)00090-3
dc.identifier.issn0957-4174
dc.identifier.urihttp://hdl.handle.net/11615/33742
dc.description.abstractThis work aims to present and evaluate a Fuzzy-Case Based Reasoning Diagnosis system of Historical Text Comprehension. The synergism of fuzzy logic and case based reasoning techniques handles the uncertainty in the acquisition of human expert's knowledge regarding learner's observable behaviour and integrates the right balance between expert's knowledge described in the form of fuzzy sets and previous experiences documented in the form of cases. The formative evaluation focused on the comparison of the system's performance to the performance of human experts concerning the diagnosis accuracy. The system was also evaluated for its behaviour when using two different historical texts. Empirical evaluation conducted with human experts and real students indicated the need for revision of the diagnosis model. The evaluation results are encouraging for the system's educational impact on learners and for future work concerning an intelligent educational system for individualized learning. (C) 2003 Elsevier Ltd. All rights reserved.en
dc.source.uri<Go to ISI>://WOS:000185243400002
dc.subjectfuzzy-case based reasoningen
dc.subjecthistorical text comprehensionen
dc.subjectdiagnosisen
dc.subjectevaluationen
dc.subjectlearner modelen
dc.subjectComputer Science, Artificial Intelligenceen
dc.subjectEngineering, Electrical &en
dc.subjectElectronicen
dc.subjectOperations Research & Management Scienceen
dc.titleEvaluating an intelligent diagnosis system of historical text comprehensionen
dc.typejournalArticleen


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Εμφάνιση απλής εγγραφής