Teaching Tips

• Little preparation time is required for educators in a programming class that utilizes R. It would require more time if the teacher wanted to transfer the code to a different language, or help prepare students for the activity by doing some intro programming activities first.
• Educators may want to complete the activity ahead of time themselves to understand the activity since there are few instructions for teachers provided.
• It would be most helpful to allow multiple class periods for students to go through the data analysis activities as well, so this could be done as a week-long activity where students go through each of the linked data analysis activities.
• Encouraging students to further their data analysis beyond what is shown in the step-by-step activities would provide students with an opportunity to practice inquiry. Having students present their data analysis could be a great way for students to practice science communication.
• Educators may want to connect this activity to climate change explicitly, and prompt students with follow-up questions for critical thinking.
• The tutorial is part of the Data Activities that can be used with the Quantifying The Drivers and Impacts of Natural Disturbance Events Teaching Module, which can be found here: https://www.neonscience.org/resources/learning-hub/teaching-modules/quantifying-drivers-and-impacts-natural-disturbance-events

About the Content

• In this activity, students explore and visualize the stream discharge data collected during the 2013 Colorado Floods.
• Students will learn how data can be used to understand the impacts of natural disturbance events through the analysis of data from the 2013 Colorado Floods, as well as why collecting and analyzing quantitative data is important in the understanding, prediction, and recovery from natural disturbance effects.
• This activity is heavily data-focused, including a rigorous coding activity. Students will be analyzing data from USGS and plotting precipitation data using the open-source software R.
• The data used in this activity are from a reliable, government-funded dataset.
• Comments from expert scientist: very straightforward instructions to reading in data file and make a plot in R. Description of the scatter plot on annual peak discharge needs to be clearer. The caption for the figure showing annual peak streamflow can be more specific on the datapoint you're trying to get the audience to focus on.

About the Pedagogy

• This lesson has videos, readings, questions, and optional data analysis activities in the coding language "R". The questions and data analysis can be done individually or in groups.
• Knowledge of R or another coding language would be helpful, though this may be taught as part of an intro programming class where the students and teacher go through the activities together.
• There is not a comprehensive teaching guide included, however there are suggestions for lesson presentation here: https://www.neonscience.org/resources/learning-hub/teaching-modules/quantifying-drivers-and-impacts-natural-disturbance-events
• There are multiple modes of presentation (videos, reading, data analysis, visuals) that could be helpful to reach diverse learners and diverse learning styles.
• This is an engaging activity, especially if the optional data analysis activities are done and reading questions are answered.
• Educators could have students go through the website-based activity in groups. From here, each group can present their findings to the rest of the class so that they can all learn from the activities without taking class time for each student to complete every activity. The students can then be encouraged to do the coding activities they did not complete in class as homework or optional extra practice.
• After this activity, students will know how to download stream gauge data from USGS's National Water Information System, plot precipitation data in R, and publish & share an interactive plot of the data using Plotly.

• This resource engages students in using scientific data.
  See other data-rich activities

Technical Details/Ease of Use

• The most current version of R, RStudio to write code, and R Libraries that are listed at the start of each coding activity are required for this activity.
• Students will use tools such as ggplot2 and Plotly.
• This activity assumes that you have set your working directory to the location of the downloaded and unzipped data subsets.