Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/12897
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dc.contributor.authorYankovskaya A.E.
dc.contributor.authorDementev Y.N.
dc.contributor.authorLyapunov D.Y.
dc.contributor.authorYamshanov A.V.
dc.date.accessioned2021-04-05T03:21:46Z-
dc.date.available2021-04-05T03:21:46Z-
dc.date.issued2018
dc.identifier.issn21945357
dc.identifier.other2-s2.0-85030631624
dc.identifier.urihttps://ir.swu.ac.th/jspui/handle/123456789/12897-
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85030631624&doi=10.1007%2f978-3-319-67843-6_11&partnerID=40&md5=14a2f5c7608ceed588ef31a894df5943
dc.description.abstractIn this paper, we discuss the relevance of students’ learning outcomes evaluation using computer-based testing. The learning process is based on mixed diagnostic tests. For the purpose of evaluation, we use the threshold, fuzzy logic and cognitive graphic tools. The construction of mixed diagnostic tests, representing a compromise between unconditional and conditional components, in order to develop students’ knowledge evaluation is proposed for a number of disciplines. We suggest a technique for optimal mixed diagnostic tests construction based on the expert knowledge of the subjects for effective learning. The developed approach is used for a number of both the humanities and technical disciplines. One of useful outcomes of mixed diagnostic tests application is the learning trajectory design for each individual. We construct students’ learning trajectory using the intelligent learning and testing system and suggest defining their inherent approach to the learning process within the problem area. © 2018, Springer International Publishing AG.
dc.subjectComputer circuits
dc.subjectComputer testing
dc.subjectFuzzy logic
dc.subjectIntelligent systems
dc.subjectLearning systems
dc.subjectLinguistics
dc.subjectPattern recognition
dc.subjectPattern recognition systems
dc.subjectStudents
dc.subjectThreshold logic
dc.subjectTrajectories
dc.subjectCognitive graphic tools
dc.subjectComputer-based testing
dc.subjectEffective learning
dc.subjectIntelligent learning
dc.subjectKnowledge evaluations
dc.subjectLearning trajectories
dc.subjectMixed diagnostic tests
dc.subjectN simplex
dc.subjectEducation
dc.titleLearning outcomes evaluation based on mixed diagnostic tests and cognitive graphic tools
dc.typeConference Paper
dc.rights.holderScopus
dc.identifier.bibliograpycitationAdvances in Intelligent Systems and Computing. Vol 677, (2018), p.81-90
dc.identifier.doi10.1007/978-3-319-67843-6_11
Appears in Collections:Scopus 1983-2021

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