dc.contributor.author | Kaklauskas, Artūras | |
dc.contributor.author | Binkytė-Vėlienė, Arūnė | |
dc.contributor.author | Vetlovienė, Ingrida | |
dc.contributor.author | Skirmantas, Darius | |
dc.contributor.author | Kuzminskė, Agnė | |
dc.date.accessioned | 2023-09-18T20:31:40Z | |
dc.date.available | 2023-09-18T20:31:40Z | |
dc.date.issued | 2020 | |
dc.identifier.issn | 2340-1117 | |
dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/150708 | |
dc.description.abstract | Much of the worldwide researches conducted seek to establish the determinants of study results. The idea has been to prove that interest, arousal, valence and learning productivity have a great deal of influence on the results learners are able to achieve. Noteworthy from such researches is the rather close relationship between the interests, arousal, valence and learning productivity with the academic achievements by students. A subject for learning seemingly requires constant adaptation, as experts in the field have noticed, relevant to situational and individual interests. This is needed to stimulate interest, increase learning productivity and sustain a rational level of stress among students. Thereby the authors of the article undertook the development of a highly suitable tool to accomplish such a goal, the Affective, Intelligent, Tutoring System for Passive House Neuromarketing (with the acronym ATHENA). Integration of the self-assessment and self-esteem measurements of students with multimodal biometric and intelligent methodologies and technologies is an ATHENA innovation. This new System custom makes a rational learning process for some specific student. This can be accomplished with biometric technologies by considering the level of interest in some study, its difficulty and the stress level the study course generates. An automatic function, which this System includes, assembles an optimized set of personalized materials aimed at some specific student relevant to a topic of a study module. The partial demonstration of this newly-developed System appears as a case study in this article. | eng |
dc.format | PDF | |
dc.format.extent | p. 946-954 | |
dc.format.medium | tekstas / txt | |
dc.language.iso | eng | |
dc.relation.isreferencedby | IATED digital library | |
dc.source.uri | https://library.iated.org/publications/EDULEARN20 | |
dc.title | An affective, intelligent, tutoring system for passive house neuromarketing | |
dc.type | Straipsnis konferencijos darbų leidinyje kitoje DB / Paper in conference publication in other DB | |
dcterms.references | 40 | |
dc.type.pubtype | P1c - Straipsnis konferencijos darbų leidinyje kitoje DB / Article in conference proceedings in other DB | |
dc.contributor.institution | Vilniaus Gedimino technikos universitetas | |
dc.contributor.institution | VšĮ Lietuvos verslo paramos agentūra | |
dc.contributor.faculty | Statybos fakultetas / Faculty of Civil Engineering | |
dc.contributor.department | Tvariosios statybos institutas / Institute of Sustainable Construction | |
dc.subject.researchfield | T 002 - Statybos inžinerija / Construction and engineering | |
dc.subject.researchfield | S 003 - Vadyba / Management | |
dc.subject.vgtuprioritizedfields | SD0404 - Statinių skaitmeninis modeliavimas ir tvarus gyvavimo ciklas / BIM and Sustainable lifecycle of the structures | |
dc.subject.ltspecializations | L102 - Energetika ir tvari aplinka / Energy and a sustainable environment | |
dc.subject.en | artificial intelligence | |
dc.subject.en | smart technology | |
dc.subject.en | affective tutoring systems | |
dc.subject.en | student behaviour | |
dc.subject.en | academic performances and achievements, interest in studies, emotion | |
dcterms.sourcetitle | EDULEARN 20: 12th international conference on education and new learning technologies online conference, 6-7 July 2020, Palma, Spain | |
dc.publisher.name | IATED | |
dc.publisher.city | Valencia | |
dc.identifier.doi | 10.21125/edulearn.2020.0334 | |
dc.identifier.elaba | 69287351 | |