Research

In computing education, live coding refers to a pedagogical technique where the instructor writes code live in front of students, thinking aloud to explain their process. In this work, we investigate how students can take better notes while watching live coding lectures. Based on interviews with instructors who use live coding, we designed a simple note-taking interface consisting of a rich text editor which allows students to take snapshots of the instructor's code. Through a lab experiment, we found that using our system led to a decreased mental workload and more comprehensive notes.

Live coding is a performance practice where one or more performers continuously run and modify code to create music or visuals. In this project, we seek to better understand how live coding musicians keep track of the evolving state of their programs and how that differs in performance vs. practice. To explore this idea, we developed an IDE extension called SHARP which helps live coders keep track of their program versions as they explore new sounds and new code.

Existing Trigger-Action Programming systems such as IFTTT allow users to define simple if-then programs consisting of a "Trigger" and "Action". For example, a program could be "If it starts to rain (Trigger), then change my smart light bulb color to blue (Action)". In this project, we explore what happens if we keep the convenient triger and action abstractions of TAP systems, but allow connecting them using short snippets of JavaScript code. This affords users the full power of a textual programming language, but still allows them to outsource tricky API integrations to a simple UI.

Octave (Observable Connections between Tables, Algorithms, and Visualization in an EUP) is an end-user programming environment that allows for the visualization and analysis of spatiotemporal trajectory data. It's designed to help construction students understand GPS data gathered from the field. Octave presents data both as a table and as a visualization and provides a small and simple set of simple computational primitives. The views of the data are tightly connected to provide a responsive and intuitive environment. For example, hovering over a table row will highlight the corresponding data point(s) in the visualization.