Data Stories in the Classroom
Spotlight on teachers across NC who are enriching their content and their students’ education with data.
Are you, or someone you know, working to build early foundational data skills among your students by using data to enrich student learning? The DSA would like to highlight teachers across North Carolina who are finding small ways to bring data and data science skills into their classrooms.
Whether you are helping young learners recognize patterns and trends in the weather or temperature, collecting and analyzing data in your science class, or exploring different and interesting ways to visualize data in art, we would love to spotlight you in our quarterly newsletter!
Stories and Lessons Submitted by Teachers
Learning with Data – PFAS Water Contamination
Grade(s): 8th – 12th
Subject(s): Science, Social Studies, Math
This lesson is designed to walk students through the data-wrangling process. Students learn how to clean up raw datasets to get them ready for analysis. It is designed as a case study approach to encourage students to decide how they may want to analyze the data. The case study focuses on PFAS levels at various water collection sites along the Cape Fear River. It is a simple dataset with only 3 variables and introduces students to the CODAP platform for low- entry analysis. The Teacher Guide offers suggestions for group activities and ideas about their possible datasets that students can use to look for correlations and to build a data story.
How did it go?:
This lesson was presented to 8th grade – high school science teachers during a professional development workshop. The teachers appreciated the community-based relevance of the data and the ease of use of the CODAP platform. They found the data cleaning process easy to follow but did struggle during some parts of the analysis, particularly with making decisions about how to analyze the data.
Learning with Data – NC Survey on Human Health and the Environment
Grade(s): 8th – 12th
Subject(s): Science, Social Studies, Math
This lesson is designed to walk students through the data-wrangling process. Students learn how to clean up raw datasets to get them ready for analysis. It is designed as a case study approach to encourage students to decide how they may want to analyze the data. The case study focuses on the results from the 2021 and 2022 NC Surveys on Human Health and the Environment. These datasets are more complex using Likert Scale data and a large number of variables (100+). The lesson introduces students to the CODAP platform for low-entry analysis. The Teacher Guide offers suggestions for group activities and ideas about other possible datasets that students can use to look for correlations and to build a data story.
How did it go?:
This lesson was presented to 8th grade – high school science teachers during a professional development workshop. The teachers appreciated the community-based relevance of the data and the ease of use of the CODAP platform. They found the data cleaning process easy to follow but did struggle during some parts of the analysis, particularly with making decisions about how to analyze the data.
Data Stories in the Classroom Submission
Real Teachers using real data in their classroom. Using this form, share how you are using data science and AI to enhance your curriculum. We also encourage you to share steps and resources for others who might want to implement your ideas in their own classrooms! Please submit your story via PDF or Word Document. You can also attach photos as needed in a PNG or JPG file (Any photos of students must be non-identifiable). Up to 5 attachments can be included with your submission. If you have questions, please email Taryn Shelton (tshelto3@ncsu.edu).
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