GSA Connects 2022 meeting in Denver, Colorado

Paper No. 59-3
Presentation Time: 2:00 PM-6:00 PM

THE FOOD-ENERGY-WATER NEXUS: USING HYDROVIZ TO SUPPORT UNDERGRADUATE STUDENTS' LEARNING ABOUT COMPLEX SOCIO-HYDROLOGIC ISSUES


MOSTACEDO MARASOVIC, Silvia Jessica, Department of Earth and Environmental Sciences, University of Texas at Arlington, Arlington, TX 76019, WHITE, Holly, School of Biology and Ecology, University of Maine, Orono, ME 04469 and FORBES, Cory, Department of Curriculum and Instruction & Department of Earth and Environmental Sciences, University of Texas at Arlington, Arlington, TX 76019

The Food-Energy-Water (FEW) Nexus is a framework that foregrounds food, energy, and water security, while responding to increasing human and natural pressures brought about by population growth and economic development, as well as climate change. Decision-making around the FEW-Nexus occurs at varying levels, engaging multiple stakeholders from different disciplines. Students, particularly in undergraduate education, should learn about and develop skills to understand, analyze, and make effective, science-informed decisions about complex, real-world challenges in the FEW-Nexus. Within this context we developed, implemented, and analyzed the results of a comprehensive curriculum and its instructional resources to engage undergraduate students in case-based decision-making about the FEW Nexus using a data visualization tool called Hydroviz. The purpose of this study is to evaluate i) to what extent is a decision-making task supporting students’ problem-solving outcomes about a FEW Nexus issue? and ii) what areas in the decision-making process were students able to engage in most-effectively? The study is based on a mixed-methods approach, where we analyzed the results from a four-part data analysis and structured decision-making task; pre-tests related to conceptual knowledge of water, the FEW Nexus, and decision making; and students’ interviews from (N = 99) students. We used a non-parametric Friedman test to compare between each component of the decision-making task. To evaluate students’ overall decision-making outcome, we used: i) ANOVA and t-tests to evaluate differences between academic years, programs, and gender, and ii) correlations with the pre-tests. Overall, results suggest that students may need additional support to frame the decision-making problem. Qualitative results indicate that students with higher scores were better able to contextualize using their results from the data analysis when defining the problem identification.