Rodyti trumpą aprašą

dc.contributor.authorKurilov, Jevgenij
dc.contributor.authorKurilova, Julija
dc.contributor.authorAndruškevič, Tomaš
dc.date.accessioned2023-09-18T16:42:53Z
dc.date.available2023-09-18T16:42:53Z
dc.date.issued2016
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/116265
dc.description.abstractThe aim of the paper is two-fold: first, to perform literature review on scientific methods, techniques, and possible results on application of personalised learning approach in education, and second – to present original research methodology and some results on application of personalised learning approach based on intelligent methods and technologies in Lithuania. In the paper, personalised learning approach is ensured by taking into account students’ learning styles according to different learning styles models. Interrelations of students’ learning styles and their cognitive traits (i.e. working memory capacity, inductive reasoning ability, and associative learning skills) is also analysed in the paper. This preferences analysis is necessary to further creating individual learning paths (scenarios) that should be optimal for particular learners. These learning paths should consist of suitable learning components (learning objects, learning methods, learning activities, learning tools, mobile apps etc.) optimal to particular students according to their personal needs (i.e. learning styles and cognitive traits). Scientific methodology to creating optimal learning paths for particular learners presented in the paper is based on the expert evaluation method and application of intelligent technologies. Intelligent technologies applied in the paper are multiple criteria decision making based expert evaluation, ontologies, recommender systems, intelligent software agents, and personal learning environments to construct learning paths (scenarios) consisting of the learning components that are the most suitable for particular learners. Inquiry-based learning activities are also analysed in the paper in terms of suitability to students’ learning styles. The main success factors of this approach are pedagogically sound vocabularies of learning components used to create personalised learning paths (scenarios), and experts’ collective intelligence. Lithuanian Intelligent Future School project aimed at implementing both learning personalisation and educational intelligence is presented in more detail.eng
dc.formatPDF
dc.format.extentp. 89-98
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyConference Proceedings Citation Index - Science (Web of Science)
dc.relation.isreferencedbyIATED digital library
dc.source.urihttps://library.iated.org/view/KURILOVAS2016ONP
dc.subjectIK01 - Informacinės technologijos, ontologinės ir telematikos sistemos / Information technologies, ontological and telematic systems
dc.titleOn personalised learning approach based on application of intelligent technologies
dc.typeStraipsnis konferencijos darbų leidinyje Web of Science DB / Paper in conference publication in Web of Science DB
dcterms.references40
dc.type.pubtypeP1a - Straipsnis konferencijos darbų leidinyje Web of Science DB / Article in conference proceedings Web of Science DB
dc.contributor.institutionVilniaus universitetas Vilniaus Gedimino technikos universitetas
dc.contributor.institutionVilniaus universitetas
dc.contributor.facultyFundamentinių mokslų fakultetas / Faculty of Fundamental Sciences
dc.subject.researchfieldT 007 - Informatikos inžinerija / Informatics engineering
dc.subject.ltspecializationsL106 - Transportas, logistika ir informacinės ir ryšių technologijos (IRT) / Transport, logistic and information and communication technologies
dc.subject.enPersonalised learning
dc.subject.enlearning styles
dc.subject.enintelligent technologies
dc.subject.enrecommender systems
dc.subject.enTechnology-Enhanced Learning
dcterms.sourcetitleEDULEARN16 : 8th international conference on education and new learning technologies, 4th-6th July 2016, Barcelona, Spain : conference proceedings. Book series: EDULEARN proceedings. ISSN 2340-1117.
dc.publisher.nameIATED Academy
dc.publisher.cityValencia
dc.identifier.doi000402955900011
dc.identifier.doi10.21125/edulearn.2016.1015
dc.identifier.elaba18225921


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Rodyti trumpą aprašą