Data Science Standards Crosswalk
The Data Paths project has created a Data Science Standards Crosswalk that identifies important data practices that are aligned with common K-12 standards in mathematics, science, and computer science. If you are an educator in these disciplines, this resource is meant to help you consider how you might integrate important data practices into your existing teaching.
Sample of the Crosswalk
We have organized the Crosswalk in two ways:
Matrix
The matrix allows educators to look up important data practices to see where and when they may be integrated into mathematics, science, and computer science classes in grades K-12. In this matrix, individual data practices are listed in the first column. Abbreviations for common mathematics, science, and computer science standards that we have judged to be aligned with each data practice are identified in adjacent cells, organized by grade level.
Subject Guide
Our subject guides allow educators to look up individual K-12 mathematics, science, and computer science standards to see which important data practices may be aligned with them. These subject guides contain the same information as in the matrix, but the guides lead with the disciplinary standards rather than with the data practices. They also include the full text for each disciplinary standard, not simply the abbreviation.
To create the Crosswalk, we took the following steps.
- We considered important data practices to be the concepts and skills described in the report Pre-K-12 Guidelines for Assessment and Instruction in Statistics Education II, or GAISE II, written by leading statistics educators (Bargagliotti et al., 2020).
- We examined individual K-12 standards in the Common Core State Standards for Mathematics (CCSSM), the Next Generation Science Standards (NGSS), the Computer Science Teachers Association or CSTA K-12 Standards, and the Massachusetts Digital Literacy and Computer Science or MA DLCS Standards.
- We asked: If a teacher was leading a lesson to help students meet this standard, is there a data practice that the teacher could integrate from GAISE II with relative ease to deepen both data and disciplinary learning among students? (We defined “relative ease” as requiring only one or two small steps during instruction to integrate the data practice.)
- If the answer was yes, we included the disciplinary standard in our matrix.
- We went through an iterative process to determine whether data practices and disciplinary standards are aligned. Project team members made Initial judgments of alignment, followed by reviews by external subject matter experts, followed by further team review and discussion to arrive at consensus decisions.
We consider the crosswalk, in both matrix and subject guide formats, as version 1.0.
In the future, we hope to make these resources even more useful by incorporating discussion of how data practices may be connected to individual disciplinary standards in the classroom. We also hope to provide examples of possible classroom activities to illustrate these connections.