National Survey of Geoscience Teaching Practices 2016: Current Trends in Geoscience Instruction of Scientific Modeling and Systems Thinking
Thursday 2:45pm Ritchie Hall: 366
Oral Session Part of Thursday A: Professional Development: Faculty, graduate students and teachers
Diane Lally, University of Nebraska at Lincoln
Cory Forbes, University of Nebraska at Lincoln
karen mcneal, Auburn University Main Campus
Nationwide, there is a growing emphasis on effective undergraduate geoscience education. A central element of geoscience teaching and learning involves scientific modeling and systems thinking (SMST). While studies of individual courses or instructional interventions may provide empirical insights into SMST in geoscience education, few efforts have attempted to document where, when, why, and how undergraduate geoscience courses emphasize SMST elements, as well as factors that can help explain and/or predict these trends. Data for this study is from the National Survey of Geoscience Teaching Practices produced for the National Association of Geoscience Teachers by the NSF-funded professional development program, Cutting Edge, for post-secondary geoscience faculty. First administered in 2004, administration of the survey occurred four times over the past 14 years. The present study reviews results from the most recent (2016) administration of the survey (n=2056). We investigated instructor- and course-related variables as they related to a set of nine survey items that serve as the measure for SMST. Reported individual SMST practices varied significantly, with frequencies varying from <20% to >75%. Total reported SMST course elements varied significantly by faculty sub-discipline, use of innovative pedagogical practices (i.e., active learning), recent changes to both the content and teaching of courses, and overall engagement in instructional improvement. Both geoscience research and education-oriented faculty reported similar emphases on SMST course elements that were significantly higher than non-tenure line, teaching faculty respondents. A linear regression model contained predictor variables identified in the analyses. This model was able to account for 17% of the variance in reported SMST course elements, F(9, 2010) = 21.12, p < .001, R2 = .17, 95% CI [.69, 2.3]. These findings have important implications for the design of undergraduate geoscience courses to foster student learning through SMST.