Sarah Sterman

EECS Department, University of California, Berkeley

Technical Report No. UCB/EECS-2022-207

August 12, 2022

http://www2.eecs.berkeley.edu/Pubs/TechRpts/2022/EECS-2022-207.pdf

Technology is deeply entwined with creativity. In creative work today, computational tools provide unique capabilities, new materials, and shape how we perform tasks. Yet many modern computer systems have roots in productivity and industrial contexts, the needs and values of which do not always align with those of creative work. In this dissertation, I seek to understand the values of creative process, and how these values can inform the design of creativity support tools that embrace the messy, complicated, and human aspects of creative work.

This dissertation contributes two concepts for organizing our approach to creative process. Value inversions define moments when the values in creative process seem at odds with traditional computational values; these inversions reveal opportunities for changing our expectations of the role of tools in our work and perceptions about effective workflows. Process-sensitive creativity support tools embrace the values of creative process, foregrounding the actions and mindsets necessary to creative work rather than solely focusing on output. To develop these concepts, this dissertation combines qualitative research on professional creative practice with the design and evaluation of novel computational tools in the areas of creative writing, documentation tools, and design education.

As we integrate existing tools into our workflows and develop novel creativity support tools, it is important to consider how these tools are shaping our process and workflows. The expectations and values embedded in our tools have concrete effects on how we work, how we evaluate success, and how we learn and grow as creative practitioners.

Advisors: Eric Paulos

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BibTeX citation:

@phdthesis{Sterman:EECS-2022-207,
    Author= {Sterman, Sarah},
    Title= {Process-Sensitive Creativity Support Tools},
    School= {EECS Department, University of California, Berkeley},
    Year= {2022},
    Month= {Aug},
    Url= {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2022/EECS-2022-207.html},
    Number= {UCB/EECS-2022-207},
    Abstract= {Technology is deeply entwined with creativity. In creative work today, computational tools provide unique capabilities, new materials, and shape how we perform tasks. Yet many modern computer systems have roots in productivity and industrial contexts, the needs and values of which do not always align with those of creative work. In this dissertation, I seek to understand the values of creative process, and how these values can inform the design of creativity support tools that embrace the messy, complicated, and human aspects of creative work.

This dissertation contributes two concepts for organizing our approach to creative process. Value inversions define moments when the values in creative process seem at odds with traditional computational values; these inversions reveal opportunities for changing our expectations of the role of tools in our work and perceptions about effective workflows. Process-sensitive creativity support tools embrace the values of creative process, foregrounding the actions and mindsets necessary to creative work rather than solely focusing on output. To develop these concepts, this dissertation combines qualitative research on professional creative practice with the design and evaluation of novel computational tools in the areas of creative writing, documentation tools, and design education.

As we integrate existing tools into our workflows and develop novel creativity support tools, it is important to consider how these tools are shaping our process and workflows. The expectations and values embedded in our tools have concrete effects on how we work, how we evaluate success, and how we learn and grow as creative practitioners.},
}

EndNote citation:

%0 Thesis
%A Sterman, Sarah 
%T Process-Sensitive Creativity Support Tools
%I EECS Department, University of California, Berkeley
%D 2022
%8 August 12
%@ UCB/EECS-2022-207
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2022/EECS-2022-207.html
%F Sterman:EECS-2022-207