Artificial neural network for learning personalisation

The paper aims to suggest a method of using artificial neural for learning personalisation. Learning personalisation consists form learning style identification then linking it to learning activities and objects which correspond to learning style. But the problem is that learning style identified by...

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Main Authors: Andrius Berniukevičius, Eugenijus Kurilovas
Format: Article
Language:English
Published: Vilnius University Press 2017-12-01
Series:Lietuvos Matematikos Rinkinys
Subjects:
Online Access:https://www.journals.vu.lt/LMR/article/view/17755
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author Andrius Berniukevičius
Eugenijus Kurilovas
author_facet Andrius Berniukevičius
Eugenijus Kurilovas
author_sort Andrius Berniukevičius
collection DOAJ
description The paper aims to suggest a method of using artificial neural for learning personalisation. Learning personalisation consists form learning style identification then linking it to learning activities and objects which correspond to learning style. But the problem is that learning style identified by questionnaire cannot guarantee adequacy and objectivity. In order to overcome this issue we can use artificial neural network which could analyse learner in learning activities and interaction with learning objects and correct learning style and scenarios characteristics according to collected information.
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spelling doaj.art-125307a7c77740839c32f4f57380d3ff2022-12-21T23:19:40ZengVilnius University PressLietuvos Matematikos Rinkinys0132-28182335-898X2017-12-0158B10.15388/LMR.B.2017.04Artificial neural network for learning personalisationAndrius Berniukevičius0Eugenijus Kurilovas1Vilniaus universitetasVilniaus Gedimino technikos universitetasThe paper aims to suggest a method of using artificial neural for learning personalisation. Learning personalisation consists form learning style identification then linking it to learning activities and objects which correspond to learning style. But the problem is that learning style identified by questionnaire cannot guarantee adequacy and objectivity. In order to overcome this issue we can use artificial neural network which could analyse learner in learning activities and interaction with learning objects and correct learning style and scenarios characteristics according to collected information.https://www.journals.vu.lt/LMR/article/view/17755personalisationartificial neural networklearning style
spellingShingle Andrius Berniukevičius
Eugenijus Kurilovas
Artificial neural network for learning personalisation
Lietuvos Matematikos Rinkinys
personalisation
artificial neural network
learning style
title Artificial neural network for learning personalisation
title_full Artificial neural network for learning personalisation
title_fullStr Artificial neural network for learning personalisation
title_full_unstemmed Artificial neural network for learning personalisation
title_short Artificial neural network for learning personalisation
title_sort artificial neural network for learning personalisation
topic personalisation
artificial neural network
learning style
url https://www.journals.vu.lt/LMR/article/view/17755
work_keys_str_mv AT andriusberniukevicius artificialneuralnetworkforlearningpersonalisation
AT eugenijuskurilovas artificialneuralnetworkforlearningpersonalisation