Nutrient Loading Module
This module was initially developed by Castendyk, D.N., T. Meixner, and C.A. Gibson. 6 June 2015. Project EDDIE: Nutrient Loading. Project EDDIE Module 7, Version 1. Module development was supported by NSF DEB 1245707.
Estimating nutrient loads is a critical concept for students studying water quality in a variety of environmental settings. Many STEM/Environmental science students will be asked to assess the impacts of a proposed anthropogenic activities on human water resources and/or ecosystems as part of their future careers. This module engages students in exploring factors contributing to the actual loads of nitrogen that are transmitted down streams. Nitrogen is a key water quality contaminant contributing to surface water quality issues in fresh, salt, and estuarine environments. Students will utilize real-time nitrate data from the US Geological Survey to calculate nitrate loads for several locations and investigate the interplay of concentration and discharge that contributes to calculated loads.

Riparian Plant Lab
Julie Stoughton, University of Nevada-Reno
In this field exercise for an introductory environmental science course, students investigate plant cover and type in a riparian area using transects. The final assignment is a lab report that includes a summary data table, a graph of cover types along their transect and an analysis of riparian health.

Modeling Rare Plant Distributions Using ArcGIS
Elizabeth Crook, University of California-Irvine
In this activity, students work with rare plant occurrence data from the Nature Reserve of Orange County, California to create species distribution maps in ArcGIS. Students are given shapefiles of species ...

Assessing the Risk of Invasive Species Using Community Science Data
Matthew Heard, Belmont University
This module introduces students who are already familiar with GIS to doing comparative analyses with large-scale community science (often called citizen science) data sets. Students will explore how we can use ...

Exploring Fish Diversity in Australia's Marine Ecoregions
Andrew Fischer, university of tasmania
This activity accomplishes two tasks. First it teaches students about the concepts of species richness and biodiversity using a global data set of marine fish diversity. Second, it teaches them about application ...

Water Quality Module
This module was initially developed by Castendyk, D. and Gibson, C. 30 June 2015. Project EDDIE: Water Quality. Project EDDIE Module 6, Version 1. cemast.illinoisstate.edu/data-for-students/modules/water-quality.shtml. Module development was supported by NSF DEB 1245707.
Water quality is a critical concept for undergraduate students studying Earth Sciences, Biology, and Environmental Sciences. Many of these students will be asked to assess the impacts of a proposed anthropogenic ...

Dino Doom
Sina Kirk, Arizona State University at the Tempe Campus
This is an online learning experience that transports learners around the world to different locations related to the Cretaceous–Paleogene (K–Pg) extinction event. Students will collect and analyze evidence to ...

Phenology Trends and Climate Change in Minnesota
Pamela Freeman, The College of Saint Scholastica
Seasonal events, for example flowering, fruiting, and the return of migrating birds, happen at particular times of the year. Some of these events happen in relation to climate, while others are dependent on other ...

Plastic Amniote Phylogeny
Rowan Martindale, The University of Texas at Austin
Students use plastic animals to discuss and synthesize their knowledge about the evolutionary relationships between different vertebrates (amniotes). In small groups, students get a bag of animals (e.g., mammals, ...

Analyzing datasets in ecology and evolution to teach the nature and process of science
Rebecca Price, University of Washington-Tacoma Campus
This quarter-long project forms the basis of a third-year course for majors and nonmajors at the University of Washington, Bothell called Science Methods and Practice. Students use databases to identify novel research questions, and extract data to test their hypotheses. They frame the question with primary literature, address the questions with inferential statistics, and discuss the results with more primary literature. The product is a scientific paper; each step of the process is scaffolded and evaluated. Given time limitations, we avoid devoting time to data collection; instead, we sharpen students' ability to make sense of a large body of quantitative data, a situation they may rarely have encountered. We treat statistics with a strictly conceptual, pragmatic, and abbreviated approach; i.e., we ask students to know which basic test to choose to assess a linear relationship vs. a difference between two means. We stress the need for a normal distribution in order to use these tests, and how to interpret the results; we leave the rest for stats courses, and we do not teach the mathematics. This approach proves beneficial even to those who have already had a statistics course, because it is often the first time they make decisions about applying statistics to their own research questions. We incorporate peer review and collaborative work throughout the quarter. We form collaborative groups around the research questions they ask, enabling them to share primary literature they find, and preparing them well to review each other's writing. We encourage them to cite each other's work. They write formal peer reviews of each other's papers, and they submit their final paper with a letter-to-the-editor highlighting how their research has addressed previous feedback. A major advantage of this course is that an instructor can easily modify it to suit any area of expertise. Students have worked with data about how a snail's morphology changes in response to its environment (Price, 2012), how students understand genetic drift (Price et al. 2014), maximum body size in the fossil record (Payne et al. 2008), range shifts (Ettinger et al. 2011), and urban crop pollination (Waters and Clifford 2014).