“The ability to take data — to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it — that’s going to be a hugely important skill in the next decades.”
– Hal Varian, chief economist at Google
Data is everywhere. K-12 students need to learn it. —Data Science for Everyone
Every field is now computational. Teams in every sector attack complex problems with big data sets and smart tools. As a result, every k-12 students requires a foundation of data literacy in applied problem solving. A big coalition is forming around this idea including Data Science for Everyone. This post includes a few examples of what school districts are doing to incorporate data science into their curriculum.
South Fayette Data Science Initiative
In South Fayette Township School District, the leadership team is working on a data science initiative in partnership with Stanford and Youcubed. The district is using the Youcubed Big Ideas alongside support from Jo Boaler and Cathy Williams.
This work requires upskilling and movement from within thes school community. In order to meet the demand for these skills, South Fayette has involved their K-12 STEAM teachers and also funded two-year Data Science/UDL Coach positions. The purpose of these coaches is to help support Data Science adoption and implementation beyond the STEAM curriculum. The adoption of the PA STEELS science standards creates new opportunities for embedding data science in the classroom.
Dr. Matt Callison, South Fayette’s Director of Innovation and Strategic Parnetships, shares that the experts in the field “have been very impressed with our teacher’s learning, enthusiasm, and creativity throughout this process, and how we have incorporated a wide range of teachers from across K-12 (special education, third grade, high school math, computer science, technology education, STEAM). This fits the interdisciplinary nature of data science and I think is helping teachers see all the different connections and possibilities across disciplines and grade levels.”
In preparation for this new curriculum, all teachers involved were given access to the course: 21st Century Teaching and Learning: Data Science.
Some of the core focus areas of South Fayette’s leadership team are:
- Developing teacher knowledge and capacity around Data Science
- Trying new teacher moves and activities related to Data Science in their own classrooms
- Investigating where teachers might be able to add in a layer of Data Science to existing assignments, activities, and projects
Alongside the development of courses and curriculum, this work will culminate in a common K-12 framework for Data Science specific to South Fayette including a vertical alignment. Because of the quality of the lessons in data science that South Fayette educators are creating, Stanford has committed to sharing these lessons and activities our teachers develop on their Youcubed website.
Kansas City Real World Data Science
In Kansas City, we’ve been supporting their broader Real World Learning initiative for a few years. One great organization that has been supporting this work is PREP-KC, an organization that partners with schools to provide students with opportunities to engage with business professionals and higher education faculty to help young people explore their futures.
During this work, PREP-KC was awarded a grant from the USDOE’s Office of Education Innovation and Research (EIR) to launch and evaluate the impact of a new 8th-grade data science course. Alongside MDRC, a control/evaluation partner, PREP-KC will be measuring the impact of a very hands-on data science 8th-grade elective on students’ career interests and enrollment in HS STEM courses. This work will impact at least 4,500 students and will drive the development of additional HS opportunities for dual credit in data science, industry credentials, and internships.
PREP-KC is also hosting its second annual Data Viz competition, an invitation to teams of high school teachers and students from PREP-KC’s partner urban districts to work together to create compelling data visualizations.
Conclusion
As stated in a post a few years ago, “Put data and its analysis at the center of high school mathematics.” That’s the conclusion of Stanford math professor Jo Boaler and University of Chicago economist Steven Levitt. They recommend that “every high school student should graduate with an understanding of data, spreadsheets, and the difference between correlation and causality.”
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