Promoting the Multidimensional Character of Scientific Reasoning
This study reports part of a long-term program to help students improve scientific reasoning using higher order cognitive tasks set in the discipline of cell biology. This skill was assessed using problems requiring the construction of valid conclusions drawn from authentic research data. We report...
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American Society for Microbiology
2017-05-01
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doaj-89a63ddc7a73401ebd97520de20d154c2020-11-25T02:48:41ZengAmerican Society for MicrobiologyJournal of Microbiology & Biology Education1935-78771935-78852017-05-0118110.1128/jmbe.v18i1.1272635Promoting the Multidimensional Character of Scientific ReasoningWilliam S. Bradshaw0Jennifer Nelson1Byron J. Adams2John D. Bell3Department of Microbiology and Molecular Biology Retired Brigham Young University Provo, UT 84602Department of Physiology and Developmental Biology Brigham Young University, Provo, UT 84602Department of Biology Brigham Young University, Provo, UT 84602Department of Physiology and Developmental Biology Brigham Young University, Provo, UT 84602This study reports part of a long-term program to help students improve scientific reasoning using higher order cognitive tasks set in the discipline of cell biology. This skill was assessed using problems requiring the construction of valid conclusions drawn from authentic research data. We report here efforts to confirm the hypothesis that data interpretation is a complex, multifaceted exercise. Confirmation was obtained using a statistical treatment showing that various such problems rank students differently—each contains a unique set of cognitive challenges. Additional analyses of performance results have allowed us to demonstrate that individuals differ in their capacity to navigate five independent generic elements that constitute successful data interpretation: biological context, connection to course concepts, experimental protocols, data inference, and integration of isolated experimental observations into a coherent model. We offer these aspects of scientific thinking as a “data analysis skills inventory,” along with usable sample problems that illustrate each element. Additionally, we show that this kind of reasoning is rigorous in that it is difficult for most novice students, who are unable to intuitively implement strategies for improving these skills. Instructors armed with knowledge of the specific challenges presented by different types of problems can provide specific helpful feedback during formative practice. The use of this instructional model is most likely to require changes in traditional classroom instruction.http://jmbesubmissions.asm.org/index.php/jmbe/article/view/1272undergraduatescientific thinkinghigher order reasoningdata interpretationcell biologyconstructed response assessment |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
William S. Bradshaw Jennifer Nelson Byron J. Adams John D. Bell |
spellingShingle |
William S. Bradshaw Jennifer Nelson Byron J. Adams John D. Bell Promoting the Multidimensional Character of Scientific Reasoning Journal of Microbiology & Biology Education undergraduate scientific thinking higher order reasoning data interpretation cell biology constructed response assessment |
author_facet |
William S. Bradshaw Jennifer Nelson Byron J. Adams John D. Bell |
author_sort |
William S. Bradshaw |
title |
Promoting the Multidimensional Character of Scientific Reasoning |
title_short |
Promoting the Multidimensional Character of Scientific Reasoning |
title_full |
Promoting the Multidimensional Character of Scientific Reasoning |
title_fullStr |
Promoting the Multidimensional Character of Scientific Reasoning |
title_full_unstemmed |
Promoting the Multidimensional Character of Scientific Reasoning |
title_sort |
promoting the multidimensional character of scientific reasoning |
publisher |
American Society for Microbiology |
series |
Journal of Microbiology & Biology Education |
issn |
1935-7877 1935-7885 |
publishDate |
2017-05-01 |
description |
This study reports part of a long-term program to help students improve scientific reasoning using higher order cognitive tasks set in the discipline of cell biology. This skill was assessed using problems requiring the construction of valid conclusions drawn from authentic research data. We report here efforts to confirm the hypothesis that data interpretation is a complex, multifaceted exercise. Confirmation was obtained using a statistical treatment showing that various such problems rank students differently—each contains a unique set of cognitive challenges. Additional analyses of performance results have allowed us to demonstrate that individuals differ in their capacity to navigate five independent generic elements that constitute successful data interpretation: biological context, connection to course concepts, experimental protocols, data inference, and integration of isolated experimental observations into a coherent model. We offer these aspects of scientific thinking as a “data analysis skills inventory,” along with usable sample problems that illustrate each element. Additionally, we show that this kind of reasoning is rigorous in that it is difficult for most novice students, who are unable to intuitively implement strategies for improving these skills. Instructors armed with knowledge of the specific challenges presented by different types of problems can provide specific helpful feedback during formative practice. The use of this instructional model is most likely to require changes in traditional classroom instruction. |
topic |
undergraduate scientific thinking higher order reasoning data interpretation cell biology constructed response assessment |
url |
http://jmbesubmissions.asm.org/index.php/jmbe/article/view/1272 |
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