Rodyti trumpą aprašą

dc.rights.licenseVisos teisės saugomos / All rights reserveden_US
dc.contributor.authorOvtšarenko, Olga
dc.date.accessioned2025-12-19T11:37:10Z
dc.date.available2025-12-19T11:37:10Z
dc.date.issued2023
dc.identifier.isbn9798350303841en_US
dc.identifier.issn2831-5634en_US
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/159603
dc.description.abstractThe need to automate learning paths is caused by an ever-growing need to personalise the learning process. Each student is an individual and has their learning preferences. In addition, it is required to consider changes in the knowledge and skills of the student during training. The article analyses the known methods of adaptation of e-learning and the learning path generation and presents the idea of developing an electronic course structure using a competency tree to ensure the adaptability of parts of electronic educational material in the student's independent work. Mapping the course taking into account and analysing the relationship between topics and test questions to assess student knowledge, reveals the potential for automating feedback, considering student performance. Adaptive solutions are needed to determine the sequence of choosing educational topics, exercises and test questions, taking into account their complexity and the degree of connection between different concepts in the course and depending on the change in the student's knowledge, which ensures effective and successful individual learning.en_US
dc.description.sponsorshipSimona Ramanauskaitėen_US
dc.format.extent4 p.en_US
dc.format.mediumTekstas / Texten_US
dc.language.isoenen_US
dc.relation.urihttps://etalpykla.vilniustech.lt/handle/123456789/159403en_US
dc.source.urihttps://ieeexplore.ieee.org/document/10134844en_US
dc.subjecte-learningen_US
dc.subjectcompetency treeen_US
dc.subjectpersonalisationen_US
dc.subjectadaptationen_US
dc.subjecte-assessmenten_US
dc.titleOpportunities for Automated E-learning Path Generation in Adaptive E-learning Systemsen_US
dc.typeKonferencijos publikacija / Conference paperen_US
dcterms.accrualMethodRankinis pateikimas / Manual submissionen_US
dcterms.issued2023-05-30
dcterms.references24en_US
dc.description.versionTaip / Yesen_US
dc.contributor.institutionVilniaus Gedimino technikos universitetasen_US
dc.contributor.institutionVilnius Gediminas Technical Universityen_US
dc.contributor.departmentInformacinių technologijų katedra / Department of Information Technologiesen_US
dcterms.sourcetitle2023 IEEE Open Conference of Electrical, Electronic and Information Sciences (eStream), April 27, 2023, Vilnius, Lithuaniaen_US
dc.identifier.eisbn9798350303834en_US
dc.identifier.eissn2690-8506en_US
dc.publisher.nameIEEEen_US
dc.publisher.countryUnited States of Americaen_US
dc.publisher.cityNew Yorken_US
dc.identifier.doihttps://doi.org/10.1109/eStream59056.2023.10134844en_US


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