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Conditionally Accepted to ACM CREATIVITY & COGNITION 2024

Drawcto

Investigate the impact of embodiment on creative experiences in collaborative non-representational art drawing

Interaction Design, Human Centred AI, Experience Design

Roles

  • UX Researcher

Methods

  • Co-Creation Hands on
  • Interviews
  • Video Coding
  • Thematic Analysis
  • Quantitative Analysis

Time

  • 6 months

Collaborators

Manoj Deshpande, Jisu Park

1. What is Drawcto?

Drawcto is a multi-agent AI that incorporates elements of the human visual perception theory capable of co-creating non-representational art with a human collaborator on the web.
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2. What are we investigating?

Investigate the impact of embodiment on creative experiences in collaborative non-representational art drawing.


3. Research Question

"How does embodied interaction in the context of drawing within Human-Computer Interaction (HCI) impact user engagement, perception, and the collaborative experience, particularly in the creative domain of non-representational art?"

4. Study Design

Design Type

Within-subject study design
(A within-subject design involves having all participants exposed to the exact same treatments.)

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Collaboration Types Compared

  1. Human - Human Collaboration
  2. Human - Robot Collaboration
  3. Human - Software Collaboration

Control of Variables

  1. Chosen to control extraneous variables like individual differences.

Mitigation Carryover Effects

  1. Balanced the order of conditions to address potential carryover effects, to prevent the order in which participants experience different conditions from affecting the results

Data Anaysis Approach

  1. Mixed-method approach
  2. Combination of statistical and qualitative methods

    Quantitative Methods
    3. These measures were specifically designed to evaluate the OCSM (Outcome, Collaboration, Sense-Making) curve. The OCSM curve likely represents a way to quantify aspects of the collaborative drawing experience, though the exact parameters and methods for this assessment are not detailed in the excerpt..

    Qualitative Methods

    Alongside the quantitative measures, qualitative data was collected from structured interviews. These interviews provided deeper insights into the subjects' perspectives and experiences of the collaboration.
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3. Focused on evaluating the collaborative experience with the Drawcto System

Focus

  1. Participant Demographics: A total of 22 participants, including both females and males, with an unspecified average age (M=xx, SD=xx). The exact numbers of female and male participants were not provided in the excerpt.
  2. Background of Participants: The participants were students from various majors. They were categorized as novice designers based on their average years of design experience.

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