dc.contributor.author | Goštautaitė, Daiva | |
dc.contributor.author | Kurilov, Jevgenij | |
dc.date.accessioned | 2023-09-18T20:15:45Z | |
dc.date.available | 2023-09-18T20:15:45Z | |
dc.date.issued | 2021 | |
dc.identifier.issn | 2076-3417 | |
dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/148336 | |
dc.description.abstract | A lot of computational models recently are undergoing rapid development. However, there is a conceptual and analytical gap in understanding the driving forces behind them. This paper fo-cuses on the integration between computer science and social science (namely, education) for strengthening the visibility, recognition, and understanding the problems of simulation and modelling in social (educational) decision processes. The objective of the paper covers topics and streams on social-behavioural modelling and computational intelligence applications in educa-tion. To obtain the benefits of real, factual data for modeling student learning styles, this paper investigates exemplar-based approaches and possibilities to combine them with case-based rea-soning methods for automatically predicting student learning styles in virtual learning envi-ronments. A comparative analysis of approaches combining exemplar-based modelling and case-based reasoning leads to the choice of the Bayesian Case model for diagnosing a student’s learning style based on the data about the student’s behavioral activities performed in an e-learning environment | eng |
dc.format | PDF | |
dc.format.extent | p. 1-24 | |
dc.format.medium | tekstas / txt | |
dc.language.iso | eng | |
dc.relation.isreferencedby | Science Citation Index Expanded (Web of Science) | |
dc.relation.isreferencedby | Social Sciences Citation Index (Web of Science) | |
dc.relation.isreferencedby | Scopus | |
dc.relation.isreferencedby | DOAJ | |
dc.rights | Laisvai prieinamas internete | |
dc.source.uri | https://www.mdpi.com/2076-3417/11/15/7083#cite | |
dc.source.uri | https://talpykla.elaba.lt/elaba-fedora/objects/elaba:43982621/datastreams/MAIN/content | |
dc.source.uri | https://talpykla.elaba.lt/elaba-fedora/objects/elaba:43982621/datastreams/ATTACHMENT_101412741/content | |
dc.source.uri | https://talpykla.elaba.lt/elaba-fedora/objects/elaba:43982621/datastreams/ATTACHMENT_101412742/content | |
dc.source.uri | https://talpykla.elaba.lt/elaba-fedora/objects/elaba:43982621/datastreams/ATTACHMENT_101412743/content | |
dc.title | Comparative analysis of exemplar-based approaches for students’ learning style diagnosis purposes | |
dc.type | Straipsnis Web of Science DB / Article in Web of Science DB | |
dcterms.accessRights | This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). | |
dcterms.license | Creative Commons – Attribution – 4.0 International | |
dcterms.references | 68 | |
dc.type.pubtype | S1 - Straipsnis Web of Science DB / Web of Science DB article | |
dc.contributor.institution | Vilniaus Gedimino technikos universitetas | |
dc.contributor.faculty | Fundamentinių mokslų fakultetas / Faculty of Fundamental Sciences | |
dc.subject.researchfield | N 009 - Informatika / Computer science | |
dc.subject.researchfield | S 007 - Edukologija / Educology | |
dc.subject.researchfield | T 007 - Informatikos inžinerija / Informatics engineering | |
dc.subject.studydirection | B01 - Informatika / Informatics | |
dc.subject.vgtuprioritizedfields | IK0303 - Dirbtinio intelekto ir sprendimų priėmimo sistemos / Artificial intelligence and decision support systems | |
dc.subject.ltspecializations | L106 - Transportas, logistika ir informacinės ir ryšių technologijos (IRT) / Transport, logistic and information and communication technologies | |
dc.subject.en | exemplar-based model | |
dc.subject.en | case-based reasoning | |
dc.subject.en | nearest neighbors | |
dc.subject.en | learning style | |
dc.subject.en | Bayes network, similarity | |
dcterms.sourcetitle | Applied sciences | |
dc.description.issue | iss. 15 | |
dc.description.volume | vol. 11 | |
dc.publisher.name | MDPI | |
dc.publisher.city | Basel | |
dc.identifier.doi | 000681806200001 | |
dc.identifier.doi | 10.3390/app11157083 | |
dc.identifier.elaba | 43982621 | |