dc.contributor.author | Goštautaitė, Daiva | |
dc.date.accessioned | 2023-09-18T19:33:19Z | |
dc.date.available | 2023-09-18T19:33:19Z | |
dc.date.issued | 2019 | |
dc.identifier.issn | 2340-1117 | |
dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/140656 | |
dc.description.abstract | The purpose of spreading, deploying and using information and communication technologies in virtual learning environments and providing digital tools for classrooms is to make learning process easier, more comfortable for students and more personalized, thus helping learners to reach his or her learning objectives. As taxonomies of learning provide incredibly useful tools for defining the types of work that learners should do for reaching their learning purpose, learning environments are designed or constructed on the basis of these taxonomies. The taxonomies function as powerful heuristics, helping analyze learning objectives and to design assignments. Applying taxonomies, the point is to suggest the learner assignments aligned with assessments and current learning objectives, also providing personalized learning environment using advanced information and communication technologies. Here a problem with how to apply taxonomies as the basis for development and/or construction of learning environment arises, bringing up a question how to choose the right and optimal set of taxonomy elements helping the particular group of learners to reach their learning goals and eliminating “noisy”, i.e. non-significant elements. Novel methodology using principal component analysis alongside the techniques for extraction of most important information and communication technology features and elimination the other features is proposed in the paper. Experiment using digital Bloom’s taxonomy activities was conducted to develop the proposed methodology – experimental results are described in the paper. | eng |
dc.format.extent | p. 2910-2920 | |
dc.format.medium | tekstas / txt | |
dc.language.iso | eng | |
dc.relation.isreferencedby | Conference Proceedings Citation Index - Social Science & Humanities (Web of Science) | |
dc.relation.isreferencedby | IATED digital library | |
dc.source.uri | https://library.iated.org/view/GOSTAUTAITE2019PRI | |
dc.source.uri | https://iated.org/edulearn/ | |
dc.title | Principal component analysis and Bloom taxonomy to personalise learning | |
dc.type | Straipsnis konferencijos darbų leidinyje Web of Science DB / Paper in conference publication in Web of Science DB | |
dcterms.references | 35 | |
dc.type.pubtype | P1a - Straipsnis konferencijos darbų leidinyje Web of Science DB / Article in conference proceedings Web of Science DB | |
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 | S 006 - Psichologija / Psychology | |
dc.subject.vgtuprioritizedfields | IK0303 - Dirbtinio intelekto ir sprendimų priėmimo sistemos / Artificial intelligence and decision support systems | |
dc.subject.ltspecializations | L103 - Įtrauki ir kūrybinga visuomenė / Inclusive and creative society | |
dc.subject.en | virtual learning environment | |
dc.subject.en | learning taxonomy | |
dc.subject.en | principal component analysis | |
dc.subject.en | personalisation | |
dc.subject.en | digital Bloom’s taxonomy | |
dcterms.sourcetitle | EDULEARN19 proceedings. 11th International conference on Education and New Learning Technologies, July 1st-3rd, 2019, Palma, Mallorca, Spain : conference proceedings / edited by L. Gómez Chova, A. López Martínez, I. Candel Torres | |
dc.publisher.name | IATED | |
dc.identifier.doi | 000551093103002 | |
dc.identifier.elaba | 37356598 | |