Explores how creative practitioners intentionally manage their creative process, for example by developing strategies to break out of ruts or stay motivated through uncertainty. Understanding the way experts engage with and manage creativity-relevant processes represents a rich source of foundational knowledge for designers of creativity support tools. We identify four strategies for managing process and discuss implications for the design of process-focused creativity support tools.

Explores how creative practitioners use version control tools and history information in creative process, and introduces four key considerations for version control in creative work: using versions as a palette of materials, providing confidence and freedom to explore, leveraging low-fidelity version capture, and reflecting on and reusing versions across long time scales. We discuss how the themes present across this wide range of mediums and domains can provide insight into future designs and uses of version control systems to support creative process.

Presents Kaleidoscope, a novel tool for documenting and interacting with design history in studio HCI courses. We deployed this tool in an upper-level HCI course during the COVID-19 pandemic to support student learning through feedback, reflection, and interactions with project histories.

In our era of rapid technological advancements, the research landscape for writing assistants has become increasingly fragmented across various research communities. We seek to address the challenge by proposing a design space as a structured way to examine and explore the multidimensional space of intelligent and interactive writing assistants. Through community collaboration, we explore five aspects of writing assistants: task, user, technology, interaction, and ecosystem. Within each aspect, we define dimensions and codes by systematically reviewing 120 papers while leveraging the expertise of researchers in various disciplines. Our design space aims to offer researchers and designers a practical tool to navigate, comprehend, and compare the various possibilities of writing assistants, and aid in the design of new writing assistants.

Presents a computational technique to surface style in written text. We collect a dataset of crowdsourced human judgments of style, derive a model of style by training a neural net on this data, and present novel applications for visualizing and browsing style across broad bodies of literature, as well as an interactive text editor with real-time style feedback. We study these interactive style applications with users and discuss implications for enabling this novel approach to style.