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Developing an Analytical Framework to Characterize Student Reasoning about Complex Processes
Real-world processes are complex and require ideas from multiple disciplines to be explained. However, many science courses offer limited opportunities for students to synthesize scientific ideas into coherent explanations. In this study, we investigated how students constructed causal explanations...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society for Cell Biology
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6234831/ https://www.ncbi.nlm.nih.gov/pubmed/30183566 http://dx.doi.org/10.1187/cbe.17-10-0225 |
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author | Scott, Emily E. Anderson, Charles W. Mashood, K. K. Matz, Rebecca L. Underwood, Sonia M. Sawtelle, Vashti |
author_facet | Scott, Emily E. Anderson, Charles W. Mashood, K. K. Matz, Rebecca L. Underwood, Sonia M. Sawtelle, Vashti |
author_sort | Scott, Emily E. |
collection | PubMed |
description | Real-world processes are complex and require ideas from multiple disciplines to be explained. However, many science courses offer limited opportunities for students to synthesize scientific ideas into coherent explanations. In this study, we investigated how students constructed causal explanations of complex phenomena to better understand the ways they approach this practice. We interviewed 12 undergraduate science majors and asked them to explain real-world phenomena. From these interviews, we developed a characterization framework that described the reasoning patterns we found. In this framework, we identified three explanatory frames that differentiated the kinds of explanations students provided: a colloquial frame, wherein participants activated conceptual resources based on personal experience using everyday language; an emerging mechanistic frame, wherein participants used scientific concepts in semicoherent ways; and a causal mechanistic frame, wherein participants cohesively drew upon scientific conceptual resources to construct mechanistic explanations. Overall, the causal mechanistic frame was the least prevalent frame invoked by students. Instead, many drew on an emerging mechanistic frame and struggled to identify and apply scientific concepts to real-world scenarios. We advocate for incorporating opportunities to reason about real-world phenomena into undergraduate science curricula to provide students with experience integrating scientific concepts to explain real-world phenomena. |
format | Online Article Text |
id | pubmed-6234831 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | American Society for Cell Biology |
record_format | MEDLINE/PubMed |
spelling | pubmed-62348312018-11-16 Developing an Analytical Framework to Characterize Student Reasoning about Complex Processes Scott, Emily E. Anderson, Charles W. Mashood, K. K. Matz, Rebecca L. Underwood, Sonia M. Sawtelle, Vashti CBE Life Sci Educ Article Real-world processes are complex and require ideas from multiple disciplines to be explained. However, many science courses offer limited opportunities for students to synthesize scientific ideas into coherent explanations. In this study, we investigated how students constructed causal explanations of complex phenomena to better understand the ways they approach this practice. We interviewed 12 undergraduate science majors and asked them to explain real-world phenomena. From these interviews, we developed a characterization framework that described the reasoning patterns we found. In this framework, we identified three explanatory frames that differentiated the kinds of explanations students provided: a colloquial frame, wherein participants activated conceptual resources based on personal experience using everyday language; an emerging mechanistic frame, wherein participants used scientific concepts in semicoherent ways; and a causal mechanistic frame, wherein participants cohesively drew upon scientific conceptual resources to construct mechanistic explanations. Overall, the causal mechanistic frame was the least prevalent frame invoked by students. Instead, many drew on an emerging mechanistic frame and struggled to identify and apply scientific concepts to real-world scenarios. We advocate for incorporating opportunities to reason about real-world phenomena into undergraduate science curricula to provide students with experience integrating scientific concepts to explain real-world phenomena. American Society for Cell Biology 2018 /pmc/articles/PMC6234831/ /pubmed/30183566 http://dx.doi.org/10.1187/cbe.17-10-0225 Text en © 2018 E. E. Scott et al. CBE—Life Sciences Education © 2018 The American Society for Cell Biology. “ASCB®” and “The American Society for Cell Biology®” are registered trademarks of The American Society for Cell Biology. http://creativecommons.org/licenses/by-nc-sa/3.0 This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License. |
spellingShingle | Article Scott, Emily E. Anderson, Charles W. Mashood, K. K. Matz, Rebecca L. Underwood, Sonia M. Sawtelle, Vashti Developing an Analytical Framework to Characterize Student Reasoning about Complex Processes |
title | Developing an Analytical Framework to Characterize Student Reasoning about Complex Processes |
title_full | Developing an Analytical Framework to Characterize Student Reasoning about Complex Processes |
title_fullStr | Developing an Analytical Framework to Characterize Student Reasoning about Complex Processes |
title_full_unstemmed | Developing an Analytical Framework to Characterize Student Reasoning about Complex Processes |
title_short | Developing an Analytical Framework to Characterize Student Reasoning about Complex Processes |
title_sort | developing an analytical framework to characterize student reasoning about complex processes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6234831/ https://www.ncbi.nlm.nih.gov/pubmed/30183566 http://dx.doi.org/10.1187/cbe.17-10-0225 |
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