Corey Ford

HCI researcher with specialisms in creativity support tools, human-AI interaction and audio. My research broadly explores the role of technologies (such as Generative AI) in creative user experiences (such as music composition).

Areas: Creativity Support Tools, Designing for Reflection, Music Technology, User Experience Design, Interaction Design, Computer-Supported Education, Music Composition, Generative Music, Explainable AI, Machine Learning, NIME, P5js & Processing, C++

selected publications

CHI

Towards a Reflection in Creative Experience Questionnaire

Ford, Corey, and Bryan-Kinns, Nick

In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems Apr 2023

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Reflection is underexplored in Creativity Support Tool (CST) research, partly due to its ambiguous nature. We suggest that researchers could benefit from a measure of a CST’s capacity to support reflection. To this end, we detail the first stages of development of the Reflection in Creative Experience Questionnaire (RiCE) – a lightweight questionnaire for differentiating between creative user experiences which exhibit more or less moments of reflection. We develop RiCE through i) an expert review of questionnaire items (n=10) and ii) an exploratory factor analysis (n=300) of the reviewed items. We also present a user study testing RiCE (n=58) across two time points (one week apart) with novel interfaces designed for creative writing and music making. Although we do not confirm validity, we identify four factors for RiCE which we suggest are interpretable in a conceptually meaningful way. Our formative studies contribute towards supporting future explorations on reflection with CSTs.
C&C

Identifying Engagement in Children’s Interaction Whilst Composing Digital Music at Home

Ford, Corey, and Bryan-Kinns, Nick

In Proceedings of the ACM SIGCHI Conference on Creativity and Cognition Jun 2022

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Identifying points of engagement from a person’s interaction with computers could be used to assess their experience and to adapt user interfaces in real-time. However, it is difficult to identify points of engagement unobtrusively; HCI studies typically use retrospective protocols or rely on cumbersome sensors for real-time analysis. We present a case study on how children compose digital music at home in which we remotely identify points of engagement from patterns of interaction with a musical interface. A mixed-methods approach is contributed in which video recordings of children’s interactions whilst composing are labelled for engagement and linked to i) interaction logs from the interface to identify indicators of engagement in interaction, and ii) interview data gathered using a remote video-cued recall technique to understand the experiential qualities of engaging interactions directly from users. We conclude by speculating on how the suggested indicators of engagement inform the design of adaptive music systems.