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Development of the Statistical Reasoning in Biology Concept Inventory (SRBCI)
We followed established best practices in concept inventory design and developed a 12-item inventory to assess student ability in statistical reasoning in biology (Statistical Reasoning in Biology Concept Inventory [SRBCI]). It is important to assess student thinking in this conceptual area, because...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society for Cell Biology
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4803094/ https://www.ncbi.nlm.nih.gov/pubmed/26903497 http://dx.doi.org/10.1187/cbe.15-06-0131 |
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author | Deane, Thomas Nomme, Kathy Jeffery, Erica Pollock, Carol Birol, Gülnur |
author_facet | Deane, Thomas Nomme, Kathy Jeffery, Erica Pollock, Carol Birol, Gülnur |
author_sort | Deane, Thomas |
collection | PubMed |
description | We followed established best practices in concept inventory design and developed a 12-item inventory to assess student ability in statistical reasoning in biology (Statistical Reasoning in Biology Concept Inventory [SRBCI]). It is important to assess student thinking in this conceptual area, because it is a fundamental requirement of being statistically literate and associated skills are needed in almost all walks of life. Despite this, previous work shows that non–expert-like thinking in statistical reasoning is common, even after instruction. As science educators, our goal should be to move students along a novice-to-expert spectrum, which could be achieved with growing experience in statistical reasoning. We used item response theory analyses (the one-parameter Rasch model and associated analyses) to assess responses gathered from biology students in two populations at a large research university in Canada in order to test SRBCI’s robustness and sensitivity in capturing useful data relating to the students’ conceptual ability in statistical reasoning. Our analyses indicated that SRBCI is a unidimensional construct, with items that vary widely in difficulty and provide useful information about such student ability. SRBCI should be useful as a diagnostic tool in a variety of biology settings and as a means of measuring the success of teaching interventions designed to improve statistical reasoning skills. |
format | Online Article Text |
id | pubmed-4803094 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | American Society for Cell Biology |
record_format | MEDLINE/PubMed |
spelling | pubmed-48030942016-03-29 Development of the Statistical Reasoning in Biology Concept Inventory (SRBCI) Deane, Thomas Nomme, Kathy Jeffery, Erica Pollock, Carol Birol, Gülnur CBE Life Sci Educ Article We followed established best practices in concept inventory design and developed a 12-item inventory to assess student ability in statistical reasoning in biology (Statistical Reasoning in Biology Concept Inventory [SRBCI]). It is important to assess student thinking in this conceptual area, because it is a fundamental requirement of being statistically literate and associated skills are needed in almost all walks of life. Despite this, previous work shows that non–expert-like thinking in statistical reasoning is common, even after instruction. As science educators, our goal should be to move students along a novice-to-expert spectrum, which could be achieved with growing experience in statistical reasoning. We used item response theory analyses (the one-parameter Rasch model and associated analyses) to assess responses gathered from biology students in two populations at a large research university in Canada in order to test SRBCI’s robustness and sensitivity in capturing useful data relating to the students’ conceptual ability in statistical reasoning. Our analyses indicated that SRBCI is a unidimensional construct, with items that vary widely in difficulty and provide useful information about such student ability. SRBCI should be useful as a diagnostic tool in a variety of biology settings and as a means of measuring the success of teaching interventions designed to improve statistical reasoning skills. American Society for Cell Biology 2016 /pmc/articles/PMC4803094/ /pubmed/26903497 http://dx.doi.org/10.1187/cbe.15-06-0131 Text en © 2016 T. Deane et al.CBE—Life Sciences Education © 2016 The American Society for Cell Biology. 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 (http://creativecommons.org/licenses/by-nc-sa/3.0). “ASCB®”and “The American Society for Cell Biology®” are registered trademarks of The American Society for Cell Biology. |
spellingShingle | Article Deane, Thomas Nomme, Kathy Jeffery, Erica Pollock, Carol Birol, Gülnur Development of the Statistical Reasoning in Biology Concept Inventory (SRBCI) |
title | Development of the Statistical Reasoning in Biology Concept Inventory (SRBCI) |
title_full | Development of the Statistical Reasoning in Biology Concept Inventory (SRBCI) |
title_fullStr | Development of the Statistical Reasoning in Biology Concept Inventory (SRBCI) |
title_full_unstemmed | Development of the Statistical Reasoning in Biology Concept Inventory (SRBCI) |
title_short | Development of the Statistical Reasoning in Biology Concept Inventory (SRBCI) |
title_sort | development of the statistical reasoning in biology concept inventory (srbci) |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4803094/ https://www.ncbi.nlm.nih.gov/pubmed/26903497 http://dx.doi.org/10.1187/cbe.15-06-0131 |
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