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Creativity research is a large and varied field in which the subject is characterised on many different levels. The arrival of digital media and computational tools has opened up new possibilities for creative practice. The cutting edge in the digital arts is a highly fertile ground for the investigation of creativity and the role of new technologies. The demands of such work often reveal the limitations of existing technologies and open the door to developing new approaches and techniques. This provides the creativity researcher with opportunities to understand the multi-dimensional characteristics of the creative process. At the same time, it places new demands upon the creators of the technological solutions and pushes forward our understanding of the future requirements of creative technologies. This paper is concerned with the nature of creativity and the design of creativity enhancing computer systems. The research has multi-disciplinary foundations in Human-Computer Interaction and creative practice in Art, Design, Science and Engineering. As a result of a series of studies of creative people and the associated developments in technology, a strategy for practice-based research has evolved in which research and practice are interdependent activities that have mutual benefits as well as distinctive outcomes. This paper charts the development of that co-evolutionary process from the foundation studies to recent outcomes of a major project in art and technology collaboration. The notion of the Studio as a laboratory in the field is introduced and a new methodology for systematic practice-based research is presented. From the results of the investigations that took place, opportunities for the development of technology environments for creative collaboration are propo...

Abstract: One of the challenges being addressed within education, and higher education in particular, is that of providing students with life-long learning skills. The speed with which technology evolves, the multiplicity of its impact on society and the ramifications of that impact mean that more than technical competence with specific tools and techniques is necessary. This is especially true of disciplines where changing technology is one of the raisons d’être. This paper focuses on the background to an approach based at the School of Engineering, Murdoch University to enhance the adaptability skills and knowledge of Software Engineering students by stressing the need for divergent thinking and creativity within a formal course in Requirements Engineering.

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Tools exist for creating practically every type of artistic, creative, or communicative digital artifact, including pictures, music, video, and computer animation. While these tools make it technically feasible to produce creative content, they do not guarantee that the creator will produce work that is valued by a community as possessing quality or meaning. Can an intelligent system augment non-expert creative ability? We present a metaphor for designing intelligent systems that support human creativity: computer-as-audience. We motivative the computer-as-audience metaphor with discussion of support of human creative story authoring.

We present empirical results from a new approach, Aesthetic Computing to customizing model structures for designing models for systems found in mathematics and computer simulation. At the University of Florida, we have taught the methodology of Aesthetic Computing as a separate class, and within the context of a Simulation class. Students in the simulation class were taught the method and then subsequently allowed to construct their own interactive 3D representations of typical simulation model structures such as Petri nets and finite state automata. While using the method, natural issues arise, questioning where aesthetic computing can provide benefit in model representation. To help answer such questions, a student needs to be presented with a body of knowledge that represents the “aesthetic computing technique, ” and then the student applies this knowledge to create the modeling artifacts. We present recent empirical studies from two classes, Aesthetic Computing and Computer Simulation, where aesthetic “methods/techniques” were employed. From the studies, we determined that there were several key results associated with Aesthetic Computing: 1) the ability for the student to be more creative in building their own custom models, and 2) the ability to improve perceived communication of technical topics (e.g., associated with the models) to non-experts.

The paper is concerned with increasing our understanding of creative expertise drawing upon studies of collaboration between technologists and artists. The nature of expertise in collaborative creative work is discussed and the implications for support tools considered. Characteristics of a visual programming environment used to support collaboration in the development of interactive digital works are discussed. Such environments provide facilities for sharing representations between experts from different domains and in this way can be used to enable all parties to the collaboration to participate fully in the decision making process.

Understanding collective creativity is crucial for advancing the general study of human creativity as well as for guiding the design of creativity support tools for small teams and larger collectivities. In this article, a qualitative case study of collective creativity online, derived from an analysis of collaborative interactions of virtual teams of students working in the field of mathematics, is presented. Group creative activity is examined broadly, ranging from the microlevel coconstruction of novel resources for team problem solving to the evolutionary reuse of ideas and solution strategies across teams. The analysis focuses on describing the relationship between the dynamics of creative work present in a single collaborative episode of an online group and their evolution across time and across collectivities. The analysis indicates that the synergy between these two types of interactions and the resulting creative engagement of the teams relies on three fundamental processes: (a) indexical referencing, (b) group remembering, and (c) bridging across discontinuities.

Dr. Ken Perlin, Advisor“If I have said anything to the contrary I was mistaken. If I say anything to the contrary again I shall be mistaken again. Unless I am mistaken now. Into the dossier with it in any case, in support of whatever thesis you fancy.”- Samuel BeckettACKNOWLEDGEMENTS I would like to thank my advisor, Ken Perlin, for his continual support and inspiration over the course of this research. I am also indebted to my committee members, Helen Nissenbaum, Katherine Isbister, Matthew Stone, and Alan Siegal for their ongoing support and generous contributions of time and input at every stage of the project. Additionally I wish to thank John Cayley, Bill Seaman, Braxton Soderman and Linnea Ogden, each of whom provided important contributions to the ideas presented here. While there are too many to mention individually here, I would like to thank my colleagues, collaborators, and friends who have been generous and tolerant enough to put up with me over the past five years. Finally, I would like to thank my parents and brother who have given me their unconditionally support, however misguided or unintelligible my direction, since the beginning.

The facilitated brainstorming session includes a collection of creativity techniques designed to increase the quantity and quality of ideas produced by a group of participants. First, this article introduces a measure to estimate the effectiveness of a creativity technique. Second, this article describes how an evaluative measure–inspired by the concept of quality control charting–can be integrated into the brainstorming session and used within a larger framework for continuous improvement of the brainstorming process. Results captured in a real-world creative environment using self-report survey data (response rate of 92%) provides a statistically significant relationship between 1) the ratings of a technique's effectiveness and the quantity of ideas produced by the creativity technique (r = 0.30, p<.022) and 2) between the combined effectiveness of multiple creativity techniques used in a day long session and the number of new product and service concepts developed from the larger set of ideas (r = 0.61, p<.01). These results point to the ability to do two salient interventions. First, one can monitor the effectiveness of a brainstorming session and make needed changes while the ideas are being created. Second, the results point to the ability to improve future brainstorming sessions as