Valentina Dagienė

Prof. Dr. Valentina Dagienė

Institute of Data Science and Digital Technologies, Vilnius University, Vilnius 01513, Lithuania
orcid

Research Focus & Metrics

Academic Career Length

21Years (2006-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2017 in Informatica
Verified
Journal Article
Closed access
Valentina DagienėValentina Dagienė
Valentina Dagienė
SSSue Sentance
Sue Sentance
Gabrielė StupurienėGabrielė Stupurienė
Gabrielė Stupurienė

1 January 2018 in Informatics in Education
Verified
Journal Article
Open access
AJAnita Juškevičienė
Anita Juškevičienė
Valentina DagienėValentina Dagienė
Valentina Dagienė

26 August 2020 in Computer Applications in Engineering Education
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Journal Article
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PDF file
AJAnita Juškevičienė
Anita Juškevičienė
Valentina DagienėValentina Dagienė
Valentina Dagienė
VDVladimiras Dolgopolovas
Vladimiras Dolgopolovas

6 January 2021 in Computer Applications in Engineering Education
Verified
Journal Article
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VDVladimiras Dolgopolovas
Vladimiras Dolgopolovas
Valentina DagienėValentina Dagienė
Valentina Dagienė

26 August 2021 in Informatica
Verified
Journal Article
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PDF file
Tatjana JevsikovaTatjana Jevsikova
Tatjana Jevsikova
Gabrielė StupurienėGabrielė Stupurienė
Gabrielė Stupurienė
DSDovilė Stumbrienė
Dovilė Stumbrienė
AJAnita Juškevičienė
Anita Juškevičienė
Valentina DagienėValentina Dagienė
Valentina Dagienė
State of emergency affects many areas of our life, including education. Due to school closure during COVID-19 pandemic as a case of a long-term emergency, education has been moved into a remote mode. In order to determine the factors driving the acceptance of distance learning technologies and ensuring sustainable education, a model based on the Unified Theory of Acceptance and Use of Technology has been proposed and empirically validated with data collected from 550 in-service primary school teachers in Lithuania. Structural equation modelling technique with multi-group analysis was utilized to analyse the data. The results show that performance expectancy, social influence, technology anxiety, effort expectancy, work engagement, and trust are factors that significantly affect teachers’ behavioural intention to use distance learning technologies. The relationships in the model are moderated by pandemic anxiety and age of teachers. The results of this study provide important implications for education institutions, policy makers and designers: the predictors of intention to use distance learning technologies observed during the emergency period may serve as factors that should be strengthened in teachers’ professional development, and the applicability of the findings is expanded beyond the pandemic isolation period.

1 January 2022 in Computer Science and Information Systems
Verified
Journal Article
Open access
PDF file
Valentina DagienėValentina Dagienė
Valentina Dagienė
Tatjana JevsikovaTatjana Jevsikova
Tatjana Jevsikova
Gabrielė StupurienėGabrielė Stupurienė
Gabrielė Stupurienė
AJAnita Juškevičienė
Anita Juškevičienė
Computational thinking (CT) as one of the 21st century skills enters early years education. This paper aims to study the worldwide tendencies of teaching CT through computing in primary education and primary school teachers? understanding of CT. A survey of 52 countries has been performed and complemented by a qualitative study of 15 countries. In order to identify teachers? understanding-level of CT and its integration approach in the class activities, a case study of 110 in-service teachers from 6 countries has been performed. The implications of the research results may be useful for primary school educators, educational initiatives, government authorities, policy makers, e-learning system and content developers dealing with support for teachers aiming to improve their CT professional development qualification.