This paper reports on the design and evaluation of a cocreative drawing partner called the Drawing Apprentice, which was designed to improvise and collaborate on abstract sketches with users in real time. The system qualifies as a new genre of creative technologies termed "casual creators" that are meant to creatively engage users and provide enjoyable creative experiences rather than necessarily helping users make a higher quality creative product. We introduce the conceptual framework of participatory sense-making and describe how it can help model and understand open-ended collaboration. We report the results of a user study comparing human-human collaboration to human-computer collaboration using the Drawing Apprentice system. Based on insights from the user study, we present a set of design recommendations for co-creative agents.
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.
This paper describes a co-creative web-based drawing application called the Drawing Apprentice. This system collaborates with users in real time abstract drawing. We describe the theory, interaction design, and user experience of the Drawing Apprentice system. We evaluate the system with formative user studies and expert evaluations from a juried art competition in which a Drawing Apprentice submission won the code-based art category.
This paper describes a new technique for quantifying interaction dynamics during open-ended co-creation, such as collaborative drawing or playing pretend. We present a cognitive framework called creative sense-making. This framework synthesizes existing cognitive science theories and empirical investigations into open-ended improvisation to develop a method of quantifying cognitive states and types of interactions through time. We apply this framework to empirical studies of human collaboration (in the domain of pretend play) and AI-based systems (in the domain of collaborative drawing) to establish its validity through cross-domain application and inter-rater reliability within each domain. The creative sense-making framework described includes a qualitative coding technique, interaction coding software, and the cognitive theory behind their application.
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