Evaluation of suitability, acceptance and use of personalised learning scenarios

The paper aims to present a methodology (i.e. model and method) to evaluate suitability, acceptance and use of personalised learning scenarios. High-quality learning scenarios should consist of the learning components (i.e. learning objects, learning activities, and learning environment) optimised...

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Main Authors: Julija Kurilova, Eugenijus Kurilovas, Saulius Minkevičius
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/17759
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spelling doaj-48c73414e377476fb6ca8951e951faba2020-11-25T02:58:12ZengVilnius University PressLietuvos Matematikos Rinkinys0132-28182335-898X2017-12-0158B10.15388/LMR.B.2017.08Evaluation of suitability, acceptance and use of personalised learning scenariosJulija Kurilova0Eugenijus Kurilovas1Saulius Minkevičius2Vilniaus universitetasVilniaus Gedimino technikos universitetasVilniaus universitetas The paper aims to present a methodology (i.e. model and method) to evaluate suitability, acceptance and use of personalised learning scenarios. High-quality learning scenarios should consist of the learning components (i.e. learning objects, learning activities, and learning environment) optimised to particular students according to their personal needs, e.g. learning styles. In the paper, optimised learning scenarios mean learning scenarios composed of the components having the highest probabilistic suitability indexes to particular students according to Felder–Silverman learning styles model. Personalised learning scenarios evaluation methodology presented in the paper is based on (1) probabilistic suitability indexes to identify learning components suitability to particular students needs according to their learning styles, and (2) Educational Technology Acceptance & Satisfaction Model (ETAS-M) based on well-known Unified Theory on Acceptance and Use of Technology (UTAUT) model. https://www.journals.vu.lt/LMR/article/view/17759personalised learning scenariosevaluationprobabilistic suitability indexesacceptance and useUTAUT modellearning components
collection DOAJ
language English
format Article
sources DOAJ
author Julija Kurilova
Eugenijus Kurilovas
Saulius Minkevičius
spellingShingle Julija Kurilova
Eugenijus Kurilovas
Saulius Minkevičius
Evaluation of suitability, acceptance and use of personalised learning scenarios
Lietuvos Matematikos Rinkinys
personalised learning scenarios
evaluation
probabilistic suitability indexes
acceptance and use
UTAUT model
learning components
author_facet Julija Kurilova
Eugenijus Kurilovas
Saulius Minkevičius
author_sort Julija Kurilova
title Evaluation of suitability, acceptance and use of personalised learning scenarios
title_short Evaluation of suitability, acceptance and use of personalised learning scenarios
title_full Evaluation of suitability, acceptance and use of personalised learning scenarios
title_fullStr Evaluation of suitability, acceptance and use of personalised learning scenarios
title_full_unstemmed Evaluation of suitability, acceptance and use of personalised learning scenarios
title_sort evaluation of suitability, acceptance and use of personalised learning scenarios
publisher Vilnius University Press
series Lietuvos Matematikos Rinkinys
issn 0132-2818
2335-898X
publishDate 2017-12-01
description The paper aims to present a methodology (i.e. model and method) to evaluate suitability, acceptance and use of personalised learning scenarios. High-quality learning scenarios should consist of the learning components (i.e. learning objects, learning activities, and learning environment) optimised to particular students according to their personal needs, e.g. learning styles. In the paper, optimised learning scenarios mean learning scenarios composed of the components having the highest probabilistic suitability indexes to particular students according to Felder–Silverman learning styles model. Personalised learning scenarios evaluation methodology presented in the paper is based on (1) probabilistic suitability indexes to identify learning components suitability to particular students needs according to their learning styles, and (2) Educational Technology Acceptance & Satisfaction Model (ETAS-M) based on well-known Unified Theory on Acceptance and Use of Technology (UTAUT) model.
topic personalised learning scenarios
evaluation
probabilistic suitability indexes
acceptance and use
UTAUT model
learning components
url https://www.journals.vu.lt/LMR/article/view/17759
work_keys_str_mv AT julijakurilova evaluationofsuitabilityacceptanceanduseofpersonalisedlearningscenarios
AT eugenijuskurilovas evaluationofsuitabilityacceptanceanduseofpersonalisedlearningscenarios
AT sauliusminkevicius evaluationofsuitabilityacceptanceanduseofpersonalisedlearningscenarios
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