Art educators are on the front lines of designing a rising generation’s relationship with creativity and media. While public access to generative AI tools has sparked new discussions and practices in creative communities, industries, and higher academia, secondary education art teachers often lack the digital literacy and resources to align emergent technology trends with classroom goals. We interviewed 19 art educators across the United States, surfacing 1) constraints around technological access, guidance, and agency; 2) five core values for art education; and 3) the social-emotional labour educators perform to create classroom communities. Lensed by educator needs and the sociotechnical contexts they teach within, we call for researchers to critically consider how art education technology can motivate creative thinking, enable peer teaching among students, complement analogue art-making, and prioritise joy over results to better attend to classroom needs.

Playwrights use writing support tools to craft scripts for the stage. However, these tools are not attuned to the challenges of creating live performance and navigating theater ecosystems, instead complicating and constraining playwrights’ processes. Through thematic analysis of focus groups with 13 playwrights, we explored how playwrights’ creative needs and communities inform their tool use, and how playwrights adapt to tools that fail to meet their needs. We found three themes in playwriting processes: scaffolding communities of practice, incorporating voice and body into writing processes, and managing script elasticity across the theater lifecycle. We discuss lenses of embodied practice and non-normative time through which researchers can better understand creative writers’ overlooked writing behaviors and processes. To guide the development of playwriting support tools, we offer design considerations around enabling speech, visualizing performers, and contextualizing version management. By spotlighting playwrights, we illuminate how performance can inform creative writing support research.

Procedural content generation (PCG), the process of algorithmically creating game components instead of manually, has been a common tool of game development for decades. Recent advances in large language models (LLMs) enable the generation of game behaviors based on player input at runtime. Such code generation brings with it the possibility of entirely new gameplay interactions that may be difficult to integrate with typical game development workflows. We explore these implications through GROMIT, a novel LLM-based runtime behavior generation system for Unity. When triggered by a player action, GROMIT generates a relevant behavior which is compiled without developer intervention and incorporated into the game. We create three demonstration scenarios with GROMIT to investigate how such a technology might be used in game development. In a system evaluation we find that our implementation is able to produce behaviors that result in significant downstream impacts to gameplay. We then conduct an interview study with n=13 game developers using GROMIT as a probe to elicit their current opinion on runtime behavior generation tools, and enumerate the specific themes curtailing the wider use of such tools. We find that the main themes of concern are quality considerations, community expectations, and fit with developer workflows, and that several of the subthemes are unique to runtime behavior generation specifically. We outline a future work agenda to address these concerns, including the need for additional guardrail systems for behavior generation.

Reconstruction of 3D scenes from 2D images is a technical challenge that impacts domains from Earth and planetary sciences and space exploration to augmented and virtual reality. Typically, reconstruction algorithms first identify common features across images and then minimize reconstruction errors after estimating the shape of the terrain. This bundle adjustment (BA) step optimizes around a single, simplifying scalar value that obfuscates many possible causes of reconstruction errors (e.g., initial estimate of the position and orientation of the camera, lighting conditions, ease of feature detection in the terrain). Reconstruction errors can lead to inaccurate scientific inferences or endanger a spacecraft exploring a remote environment. To address this challenge, we present VECTOR, a visual analysis tool that improves error inspection for stereo reconstruction BA. VECTOR provides analysts with previously unavailable visibility into feature locations, camera pose, and computed 3D points. VECTOR was developed in partnership with the Perseverance Mars Rover and Ingenuity Mars Helicopter terrain reconstruction team at the NASA Jet Propulsion Laboratory. We report on how this tool was used to debug and improve terrain reconstruction for the Mars 2020 mission.