dc.creator | Costa, Patricia | es |
dc.creator | Castaño Muñoz, Jonatan | es |
dc.creator | Kampylis, Panagiotis | es |
dc.date.accessioned | 2022-09-07T08:30:18Z | |
dc.date.available | 2022-09-07T08:30:18Z | |
dc.date.issued | 2020-11-28 | |
dc.identifier.citation | Costa, P., Castaño Muñoz, J. y Kampylis, P. (2020). Capturing schools’ digital capacity: Psychometric analyses of the SELFIE self-reflection tool. Computers & Education, 162, 1-15. | |
dc.identifier.issn | 0360-1315 | es |
dc.identifier.issn | 1873-782X | es |
dc.identifier.uri | https://hdl.handle.net/11441/136835 | |
dc.description.abstract | Results from self-reflection tools for schools’ digital capacity can lead to evidence-based decisions
within the school community and/or the development of an action plan for a better integration of
digital technologies. Thus, it is important that the information derived from self-reflection tools is
complete, accurate, and relevant. However, usually self-reflection tools do not show evidence of
the quality of the information provided. In this paper, we focus on SELFIE, a new, comprehensive,
and customisable self-reflection tool for schools’ digital capacity, and we analyse the quality of
the information that it provides. In particular, we look at discrimination and difficulty item parameters (using item response theory), we analyse the reliability (using Cronbach’s alpha and
Omega) and the construct validity (using confirmatory factor analysis) of its core items. We find
support for the tool quality and conclude that schools using SELFIE are provided with accurate
information on their digital capacity. Additionally, we discuss ideas for further improving the tool
and future research work. The innovative design of the SELFIE tool and the psychometric analyses
of its core items are a novelty in the field of schools’ digital capacity and can provide insights for
the development of self-reflection tools for school communities. | es |
dc.format | application/pdf | es |
dc.format.extent | 15 p. | es |
dc.language.iso | eng | es |
dc.publisher | Pergamon-Elsevier Science Ltd | es |
dc.relation.ispartof | Computers & Education, 162, 1-15. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Data science applications in education | es |
dc.subject | Information literacy | es |
dc.subject | Teaching/learning strategies | es |
dc.subject | Elementary education | es |
dc.subject | Secondary education | es |
dc.title | Capturing schools’ digital capacity: Psychometric analyses of the SELFIE self-reflection tool | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Didáctica y Organización Educativa | es |
dc.relation.publisherversion | http://doi.org/10.1016/j.compedu.2020.104080 | es |
dc.identifier.doi | 10.1016/j.compedu.2020.104080 | es |
dc.journaltitle | Computers & Education | es |
dc.publication.volumen | 162 | es |
dc.publication.initialPage | 1 | es |
dc.publication.endPage | 15 | es |