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Biometric and intelligent student progress assessment system

dc.contributor.authorKaklauskas, Artūras
dc.contributor.authorZavadskas, Edmundas Kazimieras
dc.contributor.authorSeniut, Mark
dc.contributor.authorVlasenko, Andrej
dc.contributor.authorKaklauskas, Gintaris
dc.contributor.authorJuozapaitis, Algirdas
dc.contributor.authorKuzminskė, Agnė
dc.contributor.authorKaklauskas, Gabrielius
dc.contributor.authorPečiūrė, Lina
dc.contributor.authorUbartė, Ieva
dc.contributor.authorNaimavičienė, Jurga
dc.contributor.authorČerkauskas, Justas
dc.date.accessioned2023-09-18T19:58:28Z
dc.date.available2023-09-18T19:58:28Z
dc.date.issued2013
dc.identifier.other(BIS)VGT02-000027193
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/145377
dc.description.abstractA number of methodologies (Big Five Factors and Five Factor Model, intelligence quotient tests, self-assessment) and strategies for web-based formative assessment are used in an effort to predict a student's academic motivation, achievements and performance. These methodologies, biometric voice analysis technologies and 13 years of authors' experience in distance learning were used in development of the Biometric and Intelligent Student Progress Assessment System for psychological assessment of student progress. Also the BISPA system was developed in consideration of worldwide research results involving the interrelation between a person's knowledge, self-assessment and voice stress along with instances of available decision support, recommender and intelligent tutoring systems.eng
dc.formatPDF
dc.format.extentp. 59-69
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.ispartofseriesStudies in Computational Intelligence vol. 457 1860-949X
dc.relation.isreferencedbyConference Proceedings Citation Index - Science (Web of Science)
dc.relation.isreferencedbyScopus
dc.relation.isreferencedbyMathSciNet
dc.relation.isreferencedbyZentralblatt MATH (zbMATH)
dc.relation.isreferencedbySpringerLink
dc.source.urihttp://link.springer.com/chapter/10.1007/978-3-642-34300-1_6
dc.titleBiometric and intelligent student progress assessment system
dc.typeStraipsnis konferencijos darbų leidinyje Web of Science DB / Paper in conference publication in Web of Science DB
dcterms.references14
dc.type.pubtypeP1a - Straipsnis konferencijos darbų leidinyje Web of Science DB / Article in conference proceedings Web of Science DB
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.institutionVilniaus Gedimino technikos universitetas Vilniaus universitetas
dc.contributor.institutionVilniaus universitetas
dc.contributor.facultyStatybos fakultetas / Faculty of Civil Engineering
dc.contributor.facultyVilniaus Gedimino technikos universitetas / Vilniaus Gedimino technikos universitetas
dc.subject.researchfieldT 002 - Statybos inžinerija / Construction and engineering
dc.subject.enE-Learning
dc.subject.enVoice Stress Analysis
dc.subject.enIntelligent System
dc.subject.enE-Self-Assessment
dc.subject.enE-Examination
dc.subject.enHistorical Information
dc.subject.enReliability of Results
dcterms.sourcetitleAdvanced methods for computational collective intelligence. 4th International Conference on Computational Collective Intelligence Technologies and Applications (ICCCI 2012), Ho Chi Min City, Vietnam, November 28-30, 2012
dc.publisher.nameSpringer
dc.publisher.cityBerlin Heidelberg
dc.identifier.doiMRU02-000017168
dc.identifier.doi000312877500006
dc.identifier.doi10.1007/978-3-642-34300-1_6
dc.identifier.elaba4042991


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