Environmental Data-Driven Inquiry and Exploration (EDDIE)- Water Focused Modules for interacting with Big Hydrologic Data
Abstract
High-frequency sensor data are driving a shift in the Earth and environmental sciences. The availability of high-frequency data creates an engagement opportunity for undergraduate students in primary research by using large, long-term, and sensor-based, data directly in the scientific curriculum. Project EDDIE (Environmental Data-Driven Inquiry & Exploration) has developed flexible classroom activity modules designed to meet a series of pedagogical goals that include (1) developing skills required to manipulate large datasets at different scales to conduct inquiry-based investigations; (2) developing students' reasoning about statistical variation; and (3) fostering accurate student conceptions about the nature of environmental science. The modules cover a wide range of topics, including lake physics and metabolism, stream discharge, water quality, soil respiration, seismology, and climate change. In this presentation we will focus on a sequence of modules of particular interest to hydrologists - stream discharge, water quality and nutrient loading. Assessment results show that our modules are effective at making students more comfortable analyzing data, improved understanding of statistical concepts, and stronger data analysis capability. This project is funded by an NSF TUES grant (NSF DEB 1245707).
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2016
- Bibcode:
- 2016AGUFMED52A..03M
- Keywords:
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- 0820 Curriculum and laboratory design;
- EDUCATIONDE: 0825 Teaching methods;
- EDUCATIONDE: 0845 Instructional tools;
- EDUCATIONDE: 1899 General or miscellaneous;
- HYDROLOGY