Modeling the Spread of K-12 Computer Science in Wisconsin

Title: Understanding and Modeling the Spread of K-12 Computer Science in Wisconsin

Mentor: Dr. Dennis Brylow

Approach: Using both quantitative data (public school teacher licensing database, statewide course enrollment reporting, school report cards, census tract socioeconomic information,) and qualitative data (textual interview data with dozens of computer science teachers), we will extract salient factors that contribute to the successful creation of new CS programs in schools.

Summary: Fewer than one in four Wisconsin schools has identified CS courses at the middle school and high school grade levels. Despite an existing CS teacher licensure requirement and recently adopted CS academic standards for the state, most Wisconsin school children will not have access to any CS coursework in their K-12 career. The PUMP-CS Project has provided professional development to hundreds of new high school and middle school CS teachers, as well as several thousand elementary school teachers in the past five years. More than 60 of Wisconsin’s 424 independent school districts have worked to add new CS teachers and courses, and the number of active high school CS teachers has been more than doubled. In some localities, CS courses take root and thrive; enrollments rise, more teachers are recruited, and entire CS pathways are formed. Yet in other localities, interventions produce short-lived changes. Courses enroll too few students, new CS teachers are overwhelmed by conflicting demands, administrators move on to other efforts. This project aims to develop a deeper understanding of the factors that cause CS courses to thrive and spread in some locations, or whither and die in others. This will drive better policy decisions, more precise targeting of limited intervention resources, and more robust support for new partners.

Student Research Activities: The REU fellows will perform the following major tasks:

• Perform systematic review of publicly-available data sets related to K-12 Computer Science education.
• Analyze quantitative data such as public-school licensing database and school report cards.
• Analyze qualitative data from textual interview of data from dozens of computer science teachers.
• Identify key factors related to CS courses thriving in public schools using association rules.

Student Background: Students need basic programming skills and a passion for educational equity.