dc.contributor.author | Kurilov, Jevgenij | |
dc.contributor.author | Kurilova, Julija | |
dc.contributor.author | Kurilova, Ieva | |
dc.contributor.author | Meleško, Jaroslav | |
dc.date.accessioned | 2023-09-18T16:43:38Z | |
dc.date.available | 2023-09-18T16:43:38Z | |
dc.date.issued | 2016 | |
dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/116372 | |
dc.description.abstract | The paper aims to present a methodology to personalise learning and a model of personalised intelligent learning system based on students’ learning styles, cognitive traits and another personal characteristics and needs. First of all, the authors performed systematic review on learning personalisation topic. After that, they have analysed students’ preferences to certain learning styles according to Felder and Silverman Learning Styles Model. This analysis is necessary to further creating individual (personalised) learning packages optimised for particular learners in conformity with their learning styles. These learning packages should consist of suitable learning components (learning objects, learning activities, and learning environments) optimal for particular students. Scientific methodology to creating optimised learning packages for particular learners proposed in the paper is based on expert evaluation method and application of intelligent (smart) technologies – ontologies, recommender systems, and intelligent software agents. The results of Lithuanian case study on identifying students’ learning styles are presented in the paper. The model of personalised intelligent learning system based on application of the aforementioned intelligent technologies is presented in more detail. The main success factors of this approach are the application of pedagogically sound vocabularies of the learning components used to create personalised learning packages, and the experts’ collective intelligence. | eng |
dc.format | PDF | |
dc.format.extent | p. 6976-6986 | |
dc.format.medium | tekstas / txt | |
dc.language.iso | eng | |
dc.relation.ispartofseries | ICERI Proceedings 2340-1095 | |
dc.relation.isreferencedby | Conference Proceedings Citation Index - Social Science & Humanities (Web of Science) | |
dc.relation.isreferencedby | IATED digital library | |
dc.subject | IK01 - Informacinės technologijos, ontologinės ir telematikos sistemos / Information technologies, ontological and telematic systems | |
dc.title | Personalised learning system based on students’ learning styles and application of intelligent technologies | |
dc.type | Straipsnis konferencijos darbų leidinyje Web of Science DB / Paper in conference publication in Web of Science DB | |
dcterms.references | 30 | |
dc.type.pubtype | P1a - Straipsnis konferencijos darbų leidinyje Web of Science DB / Article in conference proceedings Web of Science DB | |
dc.contributor.institution | Vilniaus universitetas Vilniaus Gedimino technikos universitetas | |
dc.contributor.institution | Vilniaus universitetas | |
dc.contributor.institution | The Netherlands Cancer Institute – Antoni van Leeuwenhoek Hospital | |
dc.contributor.institution | Vilniaus Gedimino technikos universitetas | |
dc.contributor.faculty | Fundamentinių mokslų fakultetas / Faculty of Fundamental Sciences | |
dc.subject.researchfield | T 007 - Informatikos inžinerija / Informatics engineering | |
dc.subject.ltspecializations | L106 - Transportas, logistika ir informacinės ir ryšių technologijos (IRT) / Transport, logistic and information and communication technologies | |
dc.subject.en | Personalised learning | |
dc.subject.en | learning styles | |
dc.subject.en | learning packages | |
dc.subject.en | intelligent technologies | |
dc.subject.en | intelligent learning system | |
dcterms.sourcetitle | ICERI 2016 : 9th annual international conference of education, research and innovation, Seville, 14th-16th of November, 2016 : conference proceedings. | |
dc.publisher.name | IATED Academy | |
dc.publisher.city | Valencia | |
dc.identifier.doi | 000417330207004 | |
dc.identifier.doi | 10.21125/iceri.2016.0595 | |
dc.identifier.elaba | 19609099 | |