What Can 10k State CS Standards Reveal about Learning? A New Dataset for Investigation

In the United States, state learning standards guide curriculum, assessment, teacher certification, and other key drivers of the student learning experience. Investigating standards allows us to answer a lot of big questions about the field of K-12 computer science (CS) education. Our team has created a dataset of state-level K-12 CS standards for all US states that currently have such standards (n = 42). This dataset was created by CS subject matter experts, who - for each of the approximately 10,000 state CS standards - manually tagged its assigned grade level/band, category/topic, and, if applicable, which CSTA standard it is identical or similar to. We also determined the standards' cognitive complexity using Bloom's Revised Taxonomy. Using the dataset, we were able to analyze each state's CS standards using a variety of metrics and approaches. To our knowledge, this is the first comprehensive, publicly available dataset of state CS standards that includes the factors mentioned previously. We believe that this dataset will be useful to other CS education researchers, including those who want to better understand the state and national landscape of K-12 CS education in the US, the characteristics of CS learning standards, the coverage of particular CS topics (e.g., cybersecurity, AI), and many other topics. In this lightning talk, we will introduce the dataset's features as well as some tools that we have developed (e.g., to determine a standard's Bloom's level) that may be useful to others who use the dataset.