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dc.contributor.authorBehera, Amar Kumar
dc.contributor.authorde Sousa, Ricardo Alves
dc.contributor.authorOleksik, Valentin
dc.contributor.authorDong, Jingyan
dc.contributor.authorFritzen, Daniel
dc.date.accessioned2022-03-22T14:50:47Z
dc.date.available2022-03-22T14:50:47Z
dc.identifierhttps://chesterrep.openrepository.com/bitstream/handle/10034/626766/2021%20COVID-19%20Mechanical%20%26%20Industrial%20Engineering%20Education%20Survey%20%28Responses%29%20-%20ReShare.xlsx?sequence=1
dc.identifier.citationBehera, A. K., Alves de Sousa, R., Oleksik, V., Dong, J., & Fritzen, D. (2022). Multi-metric evaluation of the effectiveness of remote learning in mechanical and industrial engineering during the COVID-19 pandemic: Indicators and guidance for future preparedness, 2021. [Data Set]. UK Data Service. 855604. http://doi.org/10.5255/UKDA-SN-855604en_US
dc.identifier.urihttp://hdl.handle.net/10034/626766
dc.description.abstractThis data set is a follow on study from a study on remote learning conducted in 2020 during the first year of the COVID-19 pandemic. It contains data collected from 5 universities in 5 countries about the effectiveness of e-learning during the COVID-19 pandemic in 2021, specifically tailored to mechanical and industrial engineering students. A survey was administered in August 2021 at these universities simultaneously, using Google Forms. The survey had 41 questions, including 24 questions on a 5-point Likert scale. The survey questions gathered data on their program of study, year of study, university of enrolment and mode of accessing their online learning content. The Likert scale questions on the survey gathered data on the effectiveness of digital delivery tools, student preferences for remote learning and the success of the digital delivery tools during the pandemic. All students enrolled in modules taught by the authors of this study were encouraged to fill the survey up. Additionally, remaining students in the departments associated with the authors were also encouraged to fill up the form through emails sent on mailing lists. The survey was also advertised on external websites such as survey circle and facebook. Crucial insights have been obtained after analysing this data set that link the student demographic profile (gender, program of study, year of study, university) to their preferences for remote learning and effectiveness of digital delivery tools. This data set can be used for further comparative studies and was useful to get a snapshot of the evolution of the student preferences and e-learning effectiveness during the COVID-19 pandemic from 2020 to 2021 by comparing with the dataset from 2020.en_US
dc.publisherUK Data Serviceen_US
dc.relation.urlhttps://beta.ukdataservice.ac.uk/datacatalogue/studies/study?id=855604en_US
dc.relation.urlhttps://reshare.ukdataservice.ac.uk/855604/en_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.subjectCOVID-19en_US
dc.subjectremote learningen_US
dc.subjectmechanical engineeringen_US
dc.subjectindustrial engineeringen_US
dc.titleMulti-metric Evaluation of the Effectiveness of Remote Learning in Mechanical and Industrial Engineering During the COVID-19 Pandemic: Indicators and Guidance for Future Preparedness, 2021en_US
dc.typeDataseten_US
dc.contributor.departmentUniversity of Chester; University of Aveiro; Lucian Blaga University of Sibiu; North Carolina State University; SATC College, Criciumaen_US
or.grant.openaccessYesen_US
rioxxterms.funderunfundeden_US
rioxxterms.identifier.projectunfundeden_US
rioxxterms.versionAMen_US
rioxxterms.versionofrecord10.5255/UKDA-SN-855604en_US
dcterms.dateAccepted2022-03-18
rioxxterms.publicationdate2022-03-18
dc.date.deposited2022-03-22en_US


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Attribution-NonCommercial-NoDerivatives 4.0 International
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 International