Title
Quantifying Collaboration with a Co-Creative Drawing Agent.
Abstract
This article describes a new technique for quantifying creative collaboration and applies it to the user study evaluation of a co-creative drawing agent. We present a cognitive framework called creative sense-making that provides a new method to visualize and quantify the interaction dynamics of creative collaboration, for example, the rhythm of interaction, style of turn taking, and the manner in which participants are mutually making sense of a situation. The creative sense-making framework includes a qualitative coding technique, interaction coding software, an analysis method, and the cognitive theory behind these applications. This framework and analysis method are applied to empirical studies of the Drawing Apprentice collaborative sketching system to compare human collaboration with a co-creative AI agent vs. a Wizard of Oz setup. The analysis demonstrates how the proposed technique can be used to analyze interaction data using continuous functions (e.g., integrations and moving averages) to measure and evaluate how collaborations unfold through time.
Year
DOI
Venue
2017
10.1145/3009981
TiiS
Keywords
Field
DocType
Creativity, collaboration, creative agents, drawing, evaluation methods, interaction dynamics, qualitative coding
Apprenticeship,Turn-taking,Computer science,Coding (social sciences),Human–computer interaction,Software,Creativity,Cognition,Moving average,Empirical research,Distributed computing
Journal
Volume
Issue
ISSN
7
4
2160-6455
Citations 
PageRank 
References 
1
0.40
13
Authors
5
Name
Order
Citations
PageRank
Nicholas Davis1283.60
Chih-Pin Hsiao2204.74
Kunwar Yashraj Singh3193.00
Brenda Lin420.76
Brian Magerko547963.12