Around the United States, educators are teaching new computer science (CS) education standards, including in Tennessee, which announced its first K-8 CS standards in 2018. In Tennessee, the standards are now the official guidelines for CS education at the K-8 level, what barriers prevent CS teaching and learning to become a reality, especially for elementary and middle grades teachers, are unknown. We developed and administered a needs survey for K-8 teachers regarding CS education as a part of a broader community-engaged project. From 251 K-8 teachers' responses, we found that CS is important to them, but there are barriers to meeting the standards. Qualitative items about needs and barriers related to CS education teachers revealed a demand for professional development and training opportunities for teachers to learn about both the technical aspects of computing education and embedding computing ideas across the K-8 curriculum. We will discuss the implications of these findings and will describe how these results will enable our efforts to provide professional learning opportunities for educators.

While computer science (CS) education researchers have frequently examined what happens in courses, programs of study, or occupations in general, they have less frequently addressed finer-grained experiences that spark students' interest in CS. One excellent way to study these types of student experiences is the Experience Sampling Method (ESM). ESM involves collecting data on individuals' experiences at much more frequent intervals than traditional survey research. This aspect of ESM makes it well-suited to examine time-specific aspects of students' experiences, as well as changes due to the disruptive effects of COVID-19.

This poster explores a new context and design to learn to visualize data, the social media-based #tidytuesday weekly challenge. We use a novel data source for understanding learning —tweets from participation individuals over more than one year—and a combination of qualitative and computational research methods. The content individuals shared explained, qualified, or highlighted the substance of the visualizations they created, and participation over time (and longer code) was related to being recognized more by others.