Cargando…
Computational Thinking to Learn Environmental Sustainability: A Learning Progression
Current environmental problems are the primary focus for environmental science students and researchers. Sustainable environmental solutions require interdisciplinary thought processes, which pose difficulty to both students and the public. Computational thinking is an emerging term emphasized by pr...
Autor principal: | |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9684985/ https://www.ncbi.nlm.nih.gov/pubmed/36467441 http://dx.doi.org/10.1007/s10956-022-10004-1 |
_version_ | 1784835406052720640 |
---|---|
author | Christensen, Dana |
author_facet | Christensen, Dana |
author_sort | Christensen, Dana |
collection | PubMed |
description | Current environmental problems are the primary focus for environmental science students and researchers. Sustainable environmental solutions require interdisciplinary thought processes, which pose difficulty to both students and the public. Computational thinking is an emerging term emphasized by progressive science curricula. Computational thinking and environmental science are both interdisciplinary by nature. Learning about sustainable environmental solutions requires students to partake in computational thinking. These ideas lend toward an expansive learning progression that encourages scaffolded and differentiated student progress in both computational knowledge and environmental knowledge. The learning progression, which emerges from the conceptual framework, emphasizes the spheres of sustainability, research, education, and economic perspectives to support environmental science learning through computational thinking. Computational thinking emphasized by the computational components (input, integration, output, and feedback) support learning about environmental solutions within the learning progression. The learning progression promotes application and implications for educators, students, researchers, and environmental scientists. |
format | Online Article Text |
id | pubmed-9684985 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-96849852022-11-28 Computational Thinking to Learn Environmental Sustainability: A Learning Progression Christensen, Dana J Sci Educ Technol Article Current environmental problems are the primary focus for environmental science students and researchers. Sustainable environmental solutions require interdisciplinary thought processes, which pose difficulty to both students and the public. Computational thinking is an emerging term emphasized by progressive science curricula. Computational thinking and environmental science are both interdisciplinary by nature. Learning about sustainable environmental solutions requires students to partake in computational thinking. These ideas lend toward an expansive learning progression that encourages scaffolded and differentiated student progress in both computational knowledge and environmental knowledge. The learning progression, which emerges from the conceptual framework, emphasizes the spheres of sustainability, research, education, and economic perspectives to support environmental science learning through computational thinking. Computational thinking emphasized by the computational components (input, integration, output, and feedback) support learning about environmental solutions within the learning progression. The learning progression promotes application and implications for educators, students, researchers, and environmental scientists. Springer Netherlands 2022-11-22 2023 /pmc/articles/PMC9684985/ /pubmed/36467441 http://dx.doi.org/10.1007/s10956-022-10004-1 Text en © The Author(s), under exclusive licence to Springer Nature B.V. 2022, Springer Nature or its licensor (e.g. a society or other partner) 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 Christensen, Dana Computational Thinking to Learn Environmental Sustainability: A Learning Progression |
title | Computational Thinking to Learn Environmental Sustainability: A Learning Progression |
title_full | Computational Thinking to Learn Environmental Sustainability: A Learning Progression |
title_fullStr | Computational Thinking to Learn Environmental Sustainability: A Learning Progression |
title_full_unstemmed | Computational Thinking to Learn Environmental Sustainability: A Learning Progression |
title_short | Computational Thinking to Learn Environmental Sustainability: A Learning Progression |
title_sort | computational thinking to learn environmental sustainability: a learning progression |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9684985/ https://www.ncbi.nlm.nih.gov/pubmed/36467441 http://dx.doi.org/10.1007/s10956-022-10004-1 |
work_keys_str_mv | AT christensendana computationalthinkingtolearnenvironmentalsustainabilityalearningprogression |