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Predicting behavioural intention among graduate students in emergency remote teaching: evidence from a transition country
Emergency remote teaching (ERT) is a new concept that describes the context in which instructional delivery is switched entirely online due to crisis circumstances. Recent research in such a context has been focused either on exploring the unique learning environment and enabling factors or on instr...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer Berlin Heidelberg
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9441826/ http://dx.doi.org/10.1007/s40692-022-00239-7 |
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author | Dibra, Sidita Gerdoçi, Blendi Sula, Gerda Kurti, Sllavka |
author_facet | Dibra, Sidita Gerdoçi, Blendi Sula, Gerda Kurti, Sllavka |
author_sort | Dibra, Sidita |
collection | PubMed |
description | Emergency remote teaching (ERT) is a new concept that describes the context in which instructional delivery is switched entirely online due to crisis circumstances. Recent research in such a context has been focused either on exploring the unique learning environment and enabling factors or on instructors’ intended behavior, with few studies exploring the students’ perspective. This study aims to contribute to the literature on technology-mediated teaching and learning by deepening the knowledge of the factors determining students’ behavioral intentions (BI) in ERT settings, using a survey of 487 graduate students attending public and non-public universities in Albania conducted during the COVID-19 pandemic lockdown period. The Technology Acceptance Model (TAM) was employed to explore the chain relationship between ease of use (EASYUSE), expected efficiency (EE), attitudes (ATT), and BI. We expand the TAM model and increase its explanatory power by introducing new variables, such as co-presence (CP), and emergent variables, such as lack of learning materials and time constraints. Variance-based partial least squares techniques were used to validate our conceptual model. As hypothesized, EE and EASYUSE have a direct, positive effect on BI and an indirect effect via ATT. CP does not influence the BI directly but only indirectly via ATT and EE. Finally, the lack of learning materials is shown to negatively affect EE. While some of the findings have limited generalizability the specific research setting provides a unique opportunity to investigate the critical role of interactive teaching methods and learning barriers on students’ intentions and ATT. The fresh insights gained from the extended TAM model have important implications concerning the effective and systematic use of online modalities in similar settings. SUPPLEMENTARY INFORMATION: The online version of this article (10.1007/s40692-022-00239-7) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-9441826 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-94418262022-09-06 Predicting behavioural intention among graduate students in emergency remote teaching: evidence from a transition country Dibra, Sidita Gerdoçi, Blendi Sula, Gerda Kurti, Sllavka J. Comput. Educ. Article Emergency remote teaching (ERT) is a new concept that describes the context in which instructional delivery is switched entirely online due to crisis circumstances. Recent research in such a context has been focused either on exploring the unique learning environment and enabling factors or on instructors’ intended behavior, with few studies exploring the students’ perspective. This study aims to contribute to the literature on technology-mediated teaching and learning by deepening the knowledge of the factors determining students’ behavioral intentions (BI) in ERT settings, using a survey of 487 graduate students attending public and non-public universities in Albania conducted during the COVID-19 pandemic lockdown period. The Technology Acceptance Model (TAM) was employed to explore the chain relationship between ease of use (EASYUSE), expected efficiency (EE), attitudes (ATT), and BI. We expand the TAM model and increase its explanatory power by introducing new variables, such as co-presence (CP), and emergent variables, such as lack of learning materials and time constraints. Variance-based partial least squares techniques were used to validate our conceptual model. As hypothesized, EE and EASYUSE have a direct, positive effect on BI and an indirect effect via ATT. CP does not influence the BI directly but only indirectly via ATT and EE. Finally, the lack of learning materials is shown to negatively affect EE. While some of the findings have limited generalizability the specific research setting provides a unique opportunity to investigate the critical role of interactive teaching methods and learning barriers on students’ intentions and ATT. The fresh insights gained from the extended TAM model have important implications concerning the effective and systematic use of online modalities in similar settings. SUPPLEMENTARY INFORMATION: The online version of this article (10.1007/s40692-022-00239-7) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2022-09-05 /pmc/articles/PMC9441826/ http://dx.doi.org/10.1007/s40692-022-00239-7 Text en © Beijing Normal University 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Dibra, Sidita Gerdoçi, Blendi Sula, Gerda Kurti, Sllavka Predicting behavioural intention among graduate students in emergency remote teaching: evidence from a transition country |
title | Predicting behavioural intention among graduate students in emergency remote teaching: evidence from a transition country |
title_full | Predicting behavioural intention among graduate students in emergency remote teaching: evidence from a transition country |
title_fullStr | Predicting behavioural intention among graduate students in emergency remote teaching: evidence from a transition country |
title_full_unstemmed | Predicting behavioural intention among graduate students in emergency remote teaching: evidence from a transition country |
title_short | Predicting behavioural intention among graduate students in emergency remote teaching: evidence from a transition country |
title_sort | predicting behavioural intention among graduate students in emergency remote teaching: evidence from a transition country |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9441826/ http://dx.doi.org/10.1007/s40692-022-00239-7 |
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