National Geoscience Faculty Survey 2016: Prevalence of systems thinking and scientific modeling learning opportunities

Abstract

Scientific modeling and systems thinking (SMST) is central to the geosciences, yet few studies have documented how and to what extent undergraduate geoscience courses emphasize SMST, as well as factors that might help explain or predict these trends. Here, we present research based on data (n = 2056) from the most recent (2016) administration of the National Geoscience Faculty Survey, administered to a national sample of postsecondary geoscience instructors in the United States. We investigated instructor- and course-related variables as they relate to a set of 9 survey items that serve as a composite measure for SMST. Significant variation was observed in reported frequencies of individual SMST practices in undergraduate geoscience courses. The highest levels of reported SMST were associated with faculty from atmospheric and environmental sciences, those who emphasized research-based, student-centered pedagogical practices, those who recently made changes to both course content and teaching methods, and those who reported high levels of engagement in instructional improvement activities (workshops, presentations, seminars). Reported SMST practices were similar for faculty identifying as geoscientists and geoscience education researchers, and both were significantly higher than for teaching-focused faculty who do not conduct research. A linear regression model including variables found to be significant in the analyses was able to predict 17% of the overall variance in reported SMST practices. These findings illustrate the importance of instructors’ disciplinary orientation and active engagement in instructional innovation as related to SMST, and provide important points of impact for enhancing SMST in undergraduate geoscience courses through course design and faculty development. However, the relatively modest predictive power of the regression model indicates there are many other factors influencing SMST that warrant future research.

Keywords:

• Geoscience education
• systems thinking
• scientific modeling
• undergraduate

Acknowledgments

The authors conceptualized this study, conducted data analyses, and authored the manuscript. We acknowledge and thank the following individuals for other contributions, which made this study possible: Raymond Y. Chu, Julius Dollison, and Roman Czujko of the Statistical Research Center of the American Institute of Physics helped develop the 2004 and 2009 survey instruments, administer these surveys, and did the initial analysis of the results. Diane Ebert-May and colleagues in biology provided an unpublished copy of a similar survey developed for biology from which the 2004 leadership team benefited. Staff, including Nick Claudy and Christopher Keane, from the American Geological Institute worked through permissions to provide the initial set of geoscience faculty email addresses. John McLaughlin, the On the Cutting Edge external evaluator, made contributions to the development of the 2004 and 2009 survey instruments. Experts from Professional Data Analysts, Inc.—including Michael Luxenberg, Becky Lien, Eric Graalum, and Mao Thao—worked on the analysis of the 2009 survey and development and analysis of the 2012 and 2016 survey. Lija Greenseid, of Greenseid Consulting Group, LLC, facilitated survey design and implementation and contributed to interpretation of data analysis (2012 and 2016). Thank you to On the Cutting Edge PIs: 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’s Division of Undergraduate Education (DUE) under awards 0127310, 0127141, 0127257, 0127018, 0618482, 0618725, 0618533, 1022680, 1022776, 1022844, 1022910, 1125331, 1525593, 1524605, 1524623, 1524800, and 1609598. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.