What else can be learned when coding? A configurative literature review of learning opportunities through computational thinking
dc.contributor.author | Melro, A | |
dc.contributor.author | Tarling, G | |
dc.contributor.author | Fujita, T | |
dc.contributor.author | Kleine Staarman, J | |
dc.date.accessioned | 2023-03-01T10:13:55Z | |
dc.date.issued | 2023-01-23 | |
dc.date.updated | 2023-03-01T09:46:58Z | |
dc.description.abstract | Underpinning the teaching of coding with Computational Thinking has proved relevant for diverse learners, particularly given the increasing demand in upskilling for today’s labour market. While literature on computing education is vast, it remains unexplored how existing CT conceptualisations relate to the learning opportunities needed for a meaningful application of coding in non-Computer Scientists’ lives and careers. In order to identify and organise the learning opportunities in the literature about CT, we conducted a configurative literature review of studies published on Web of Science, between 2006 and 2021. Our sample gathers 34 papers and was analysed on NVivo to find key themes. We were able to organise framings of CT and related learning opportunities into three dimensions: functional, collaborative, and critical and creative. These dimensions make visible learning opportunities that range from individual cognitive development to interdisciplinary working with others, and to active participation in a technologically evolving society. By comparing and contrasting frameworks, we identify and explain different perspectives on skills. Furthermore, the three-dimensional model can guide pedagogical design and practice in coding courses. | en_GB |
dc.description.sponsorship | HEFCE - Higher Education Funding Council for England | en_GB |
dc.description.sponsorship | Institute of Coding | en_GB |
dc.format.extent | 073563312211338- | |
dc.identifier.citation | Published online 23 January 2023 | en_GB |
dc.identifier.doi | https://doi.org/10.1177/07356331221133822 | |
dc.identifier.uri | http://hdl.handle.net/10871/132584 | |
dc.identifier | ORCID: 0000-0002-3547-456X (Fujita, Taro) | |
dc.language.iso | en | en_GB |
dc.publisher | SAGE Publications | en_GB |
dc.rights | © The Author(s) 2023. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). | en_GB |
dc.subject | learning opportunities | en_GB |
dc.subject | computational thinking | en_GB |
dc.subject | coding | en_GB |
dc.subject | non-CS education | en_GB |
dc.subject | literature review | en_GB |
dc.title | What else can be learned when coding? A configurative literature review of learning opportunities through computational thinking | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2023-03-01T10:13:55Z | |
dc.identifier.issn | 0735-6331 | |
dc.description | This is the final version. Available from SAGE Publications via the DOI in this record. | en_GB |
dc.identifier.eissn | 1541-4140 | |
dc.identifier.journal | Journal of Educational Computing Research | en_GB |
dc.relation.ispartof | Journal of Educational Computing Research | |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2023 | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2023-01-23 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2023-03-01T10:10:15Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2023-03-01T10:14:01Z | |
refterms.panel | C | en_GB |
refterms.dateFirstOnline | 2023-01-23 |
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Except where otherwise noted, this item's licence is described as © The Author(s) 2023. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).