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Research

Faculty self-reported use of quantitative and data analysis skills in undergraduate geoscience courses

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Pages 373-386 | Received 15 Jul 2019, Accepted 01 Dec 2019, Published online: 19 Dec 2019
 

Abstract

Quantitative literacy is a foundational component of success in STEM disciplines and in life. Quantitative concepts and data-rich activities in undergraduate geoscience courses can strengthen geoscience majors’ understanding of geologic phenomena and prepare them for future careers and graduate school, and provide real-world context to apply quantitative thinking for non-STEM students. We use self-reported teaching practices from the 2016 National Geoscience Faculty Survey to document the extent to which undergraduate geoscience instructors emphasize quantitative skills (algebra, statistics, and calculus) and data analysis skills in introductory (n = 1096) and majors (n = 1066) courses. Respondents who spent more than 20% of class time on student activities, questions, and discussions, taught small classes, or engaged more with the geoscience community through research or improving teaching incorporated statistical analyses and data analyses more frequently in their courses. Respondents from baccalaureate institutions reported use of a wider variety of data analysis skills in all courses compared with respondents from other types of institutions. Additionally, respondents who reported using more data analysis skills in their courses also used a broader array of strategies to prepare students for the geoscience workforce. These correlations suggest that targeted professional development could increase instructors’ use of quantitative and data analysis skills to meet the needs of their students in context.

Acknowledgments

Experts from Professional Data Analysts, Inc., including Becky Lien, worked on development and analysis of the 2016 survey. Lija Greenseid, Greenseid Consulting Group, LLC facilitated survey design and implementation and contributed to interpretation of data analysis. On the Cutting Edge PIs are R. Heather Macdonald, Cathryn A. Manduca, David W. Mogk, Barbara J. Tewksbury, Rachel Beane, David McConnell, Katryn Wiese, and Michael Wysession.

Additional information

Funding

This work was supported by the National Science Foundation Division of Undergraduate Education under grants DUE-1022844, DUE-1125331, and DUE-1525593. Any opinions, findings, conclusions or recommendations expressed in this work are those of the authors and do not necessarily reflect the views of the National Science Foundation.

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