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The CSforALL movement to bring computational thinking to K-12 has been a boon for practitioners and language developers. This panel features three educators passionate about a particular lan- guage that has been successful with K-12 audiences. Each will demonstrate their language, describe what makes it unique, and share some of the fun and engaging projects students have created.

Polyglot programming, the use of multiple programming languages during the development process, is common practice in modern software development. This study investigates this practice through a randomized controlled trial conducted under the context of database programming. Participants in the study were given coding tasks written in Java and one of three SQL-like embedded languages. One was plain SQL in strings, one was in Java only, and the third was a hybrid embedded language that was closer to the host language. We recorded 109 valid data points. Results showed significant differences in how developers of different experience levels code using polyglot techniques. Notably, less experienced programmers wrote correct programs faster in the hybrid condition (frequent, but less severe, switches), while more experienced developers that already knew both languages performed better in traditional SQL (less frequent, but more complete, switches). The results indicate that the productivity impact of polyglot programming is complex and experience level dependent.

Approximately 10% of computer science and engineering majors have a disability. Students with disabilities face a variety of challenges including those related to stigma around disability, inaccessible tools and instruction, disability disclosure, and a lack of mentors. This BOF will bring together individuals who are interested in increasing the representation of students with disabilities in computing and improving their success. Participants will share strategies to help each other do a better job of including these students in our classes and research projects. Resources related to accessible tools and instruction, universal design of learning, opportunities for students, and more will be shared.

The College Board's AP Computer Science Principles (CSP) content has become a major new course for introducing K-12 students to the discipline. The course was designed for many reasons, but one major goal was to broaden participation. While significant work has been completed toward equity by many research groups, we know of no systematic analysis of CSP content created by major vendors in relation to accessibility for students with disabilities, especially those who are blind or visually impaired. In this experience report, we discuss two major actions by our team to make CSP more accessible. First, with the help of accessibility experts and teachers, we modified the entire Code.org CSP course to make it accessible. Second, we conducted a one-week professional development workshop in the summer of 2018 for teachers of blind or visually impaired students in order to help them prepare to teach CSP or support those who do. We report here on lessons learned that are useful to teachers who have blind or visually impaired students in their classes, to AP CSP curriculum providers, and to the College Board.

Scientific computing has become an area of growing importance. Across fields such as biology, education, physics, or others, people are increasingly using scientific computing to model and understand the world around them. Despite the clear need, almost no systematic analysis has been conducted on how students in fields outside of computer science learn to program in the context of scientific computing. Given that many fields do not explicitly teach much programming to their students, they may have to learn this important skill on their own. To help, using rigorous quantitative and qualitative methods, we looked at the process 154 students followed in the context of a randomized controlled trial on alternative styles of programming that can be used in R. Our results suggest that the barriers students face in scientific computing are non-trivial and this work has two core implications: 1) students learning scientific computing on their own struggle significantly in many different ways, even if they have had prior programming training, and 2) the design of the current generation of scientific computing feels like the wild-wild west and the designs can be improved in ways we will enumerate.