Creative coding tasks are often exploratory in nature. When producing digital artwork, artists usually begin with a high-level semantic construct such as a “stained glass filter” and programmatically implement it by varying code parameters such as shape, color, lines, and opacity to produce visually appealing results. Based on interviews with artists, it can be effortful to translate semantic constructs to program syntax, and current programming tools don’t lend well to rapid creative exploration. To address these challenges, we introduce Spellburst, a large language model (LLM) powered creative-coding environment. Spellburst provides (1) a node-based interface that allows artists to create generative art and explore variations through branching and merging operations, (2) expressive prompt-based interactions to engage in semantic programming, and (3) dynamic prompt-driven interfaces and direct code editing to seamlessly switch between semantic and syntactic exploration. Our evaluation with artists demonstrates Spellburst’s potential to enhance creative coding practices and inform the design of computational creativity tools that bridge semantic and syntactic spaces.

Computational thinking (CT) education reaches only a fraction of young children, in part because CT learning tools often require expensive hardware or fluent literacy. Informed by needfinding interviews, we developed a voice-guided smartphone application leveraging storytelling as a creative activity by which to teach CT concepts to 5- to 8-year-old children. The app includes two storytelling games where users create and listen to stories as well as four CT games where users then modify those stories to learn about sequences, loops, events, and variables. We improved upon the app design through wizard-of-oz testing (N = 28) and iterative design testing (N = 22) before conducting an evaluation study (N = 22). Children were successfully able to navigate the app, effectively learn about the target computing concepts, and, after using the app, children demonstrated above-chance performance on a near transfer CT concept recognition task.

As the importance of computational devices grows in today's technology-driven society, tools for teaching computational literacy are becoming more necessary. While microcontrollers have been shown to be an effective way to develop computational literacy in young learners, microcontrollers' accessibility is limited due to their cost. We present domino, a mobile platform that turns the phone into a microcontroller using its inbuilt sensors and actuators. Learners can create their own cause-and-effect apps with the phone's sensors as inputs and existing applications as outputs. In this paper, we reflect on the design aspects of domino that enable learners to use their phones to problem-solve in everyday life, as well as the app's implications for future work in the area of computational literacy.