Structures: such as algorithms, routines, procedures, scripts, checklists, and protocols for conducting instruction
Foreword by David C. Berliner (p.xiv-xvi) 

• The power of routines, scripts, and all kinds of established procedures to guide action in environments that are stable and predictable is not be questioned. But as events become less certain, and the outcomes desired less standardized, adherence to those same routines can be ineffectual, if not dangerous.  
  
• Too much of classroom life has become too routinized: 1) due partly to powerful accountability policies that demand that certain student outcomes be achieved; 2) another reason for this increase in demand for uniformity and routines in schools arises from the increasing dominance of business models models applied to education. (works in business settings but not in teaching)

Gardner, H. (1988). Creativity: An interdisciplinary perspective. Creativity Research Journal, 1(1), 8-26.

Sawyer, R. K., & DeZutter, S. (2009). Distributed creativity: How collective creations emerge from collaboration. Psychology of Aesthetics, Creativity, and the Arts, 3(2), 81-92.

[Abstract] Creativity is often considered to be a mental process that occurs within a person's head. In this article, we analyze a group creative process: One that generates a creative product, but one in which no single participant's contribution determines result. We analyze a series of 5 theater performances that were improvisationally developed in rehearsal by a theater group; over the course of these 5 performances, a collaborative creation emerged from the improvised dialogues of the group. W e argue that in cases of creativity such as this one, it is inaccurate to describe creativity as a purely mental process; rather, this case represents a nonindividualistic creative process that we refer to as distributed creativity. We chose this term by analogy with studies of distributed cognition, which are well established in cognitive science, but have not yet had a substantial impact on creativity research. Our study demonstrates a methodology that can be used to study distributed creative process, provides a theoretical framework to explain these processes, and contributes to our understanding of how collaboration contributes to creativity.

[Notes]
The first wave of research on creativity after Guilford's American Psychological Association Presidential address (Guilfrod, 1950); by the 1980s scholars had begun to realize that a narrow focus on the solitary individual could provide only a partial explanation of creativity, so several researchers began to explore the social and cultural dimensions of creativity (Amabile, 1983; Csikszentmihalyi, 1988), which gained inspiration from a similar shift in cognitive science from focusing on internal mental states and processes, to an analysis of how cognition is distributed across people, tools, and environments (Hutchins, 1995; Salomon, 1993). 

Through the 1900s, a second wave of creativity research pursued the idea that creativity is found in collaboration and group dynamics. In the last few years, this research has resulted in several books that explore collaborative creativity (Farrell, 2001; John-Steiner, 2000; Paulus & Nijstad, 2003; Sawyer, 2003, 2006).
The 2nd wave of research has provided a new perspective that creativity is embedded in social groups, and how creative products emerge from collaborative networks. 

Even studies of individual creators, when researchers focus on the social and cultural origins of their ideas, have revealed a high degree of collaboration behind their ideas (Cskiszentmihalyi, 1996; Farrell, 2001; John-Steiner, 2000).

One potential path forward is for creativity researchers to borrow methodologies and frameworks from cognitive scientists who have contributed to our understanding of distributed cognition. When cognitive processes are distributed across groups, they become visible,  and scientists can observe them by analyzing the verbal and gestural interactions among the participants. Studies of distributed cognition typically use qualitative and observational methods that enable researchers to capture the real-time processes of distributed cognition. Perhaps the dominant methodology is interaction analysis--Videotaping collaborations over time, and documenting the step-by-step emergence of cognition from the contribution of each group member (Jordan & Henderson, 1995).


Goal:

• contribute to our understanding of the interactional mechanisms that occur when creativity is distributed throughout a group;
• to demonstrate the potential power of interaction analysis as a tool that could contribute to our standing of group creativity.

We use the term distributed creativity to refer to situations where collaborating groups of individuals collectively generate a shared creative product. 
We are specifically interested in collaborating groups that are relatively unconstrained, such that unexpected creativity could result. We use the term collaborative emergence to refer to these group processes (Sawyer, 2003). 
Collaborative emergence is more likely to be found as a group becomes more aligned with the following characteristics:

• the activity has an unpredictable outcome, rather than a scripted, known endpoint;
• there is moment-to-moment contingency: each person's action depends on the one just before;
• the interactional effect of any given action can be changed by the subsequent actions of other participants; and
• the process is collaborative, with each participant contributing equally.

Because collaborative emergence results from interactions among participants, it must be analyzed as a discursive, distributed process. The distributed creativity perspective locates creativity in the symbolic social interactions among members of a group.

Improvised narratives are good example of collaborative emergence because they are so obviously created by the collaborative efforts of the entire group. No single speaker creates the narrative; it emerges from the give and take of conversation. 

When groups of individuals work together to generate a collective creative product, the interactions among group members often become a more substantial source of creativity than the inner mental processes of any one participating individual. 

Distributed creativity can occur in single encounters and across multiple encounters. In this paper, we extended the scope of the methodology by applying interaction analysis to repeated rehearsals of an improvised performance. To reveal the mechanisms by which groups are collaboratively creative, group creativity research could incorporate the methods of interaction analysis to closely analyze the processual, turn-by-turn dynamics of collaborative dialogue.

Interaction analysis:
The goal of interaction analysis is to identify recurring patterns in collective behavior, and processes that result in the emergence of these recurring patterns. It roots in ethnography, sociolinguistics, developmental psychology, and conversation analysis. The central focus of an interaction analysis is the collective behaviors of a group of interesting individuals. 

Interaction analysis is particularly valuable when each individual's behaviors display a moment-to-moment dependency on the behaviors of other individuals--a characteristic that we referred to above as ''contingency." In situations of contingency, one person's action at a given moment is highly influenced by the actions of their partners immediately before--such that prediction of a person's action cannot be made successfully independent of the sequence of preceding actions of others. 
In collaborating creative groups, creativity is an ongoing social process, and a full explanation of processes of distributed creativity requires an empirical study of the moment-to-moment processes whereby individual creative actions result in the emergence of a collective creative product.

Standard interaction analysis procedures generally involve six steps

1. Videotape naturally occurring encounters as part of a broader ethnographic study, using participant observation when the researcher is an active participant in the interaction;
2. Once videotapes are made, the first analytic step is to watch through the videos and prepare a content log--each identifiably distinct episode is given a heading and a rough summary of events;
3. Perhaps the most critical stage is the identification of general patterns--sequences of interaction that occur repeatedly and that provide insight into the nature of distributed creativity; (index video data so that instances of similar events can be observed together: 1) key narrative elements of the performance emerged from the collective improvisations of the ensemble, foundational elements of narrative as character, relationship, and plot;  2) within the emergent narrative structure, short segments of dialogue and action emerged collectively and were retained through subsequent performances-bits)
4. Depending on the researcher's interest, some portion of the video dataset is selected for transcription.
5. For many research questions, it can be valuable to quantify video data by coding the data (1) delimit the stream of data into distinct episodes; 2) develop categories, or codes, within which the episodes can be grouped; 3) use two or more researchers to assign codes to each episode, and then calculate intercoder reliability of the coding scheme. Iterative process, once a reliable coding scheme is developed, and the many episodes found in the video data have been coded, quantitative methods can be used to identify generalizable patterns. If we eventually choose to analyze the emergence over time of a single scene, coding was not appropriate. If we eventually choose to conduct similar analyses over a larger number of scenes, then application of a coding scheme would allow for quantitative analyses of similarities and differences in processes of collaborative emergence across scenes, actors, or even ensembles. )
6. Many interaction analysts ask the original participants to watch the videotapes with the research team, with the goal of eliciting the participants' perspectives on what was happening.

This sorts of analysis has the potential to expand our understandings of the step-by-step processes whereby creativity emerges from groups, and of the relationship between the distributed creativity of the group, and the individual creative actions of each member of the group.

[Findings]
After step 1, 2, and 3, identified 2 types of dramatic structure that collaboratively emerged: foundational elements of narrative (character, relationship, and plot); and short segments of dialogue and action, known as bits, emerged collectively and were retained through subsequent performances.
Our findings are consistent with theoretical perspectives that emphasize that collective nature of situated social activity, perspectives that include distributed cognition (Salomon, 1993) and sociocultural theory (Rogoff, 1990, 1998). 

Several prominent creativity researchers, influenced by the onset of sociocultural and distributed approaches to cognition in the 1980s, have begun to analyze the role of collaboration and context in creativity. This second wave of creativity research focuses on how novelty emerges from unstructured and improvised group collaboration. This collaborative turn in creativity research has provided us with a deeper understanding of how new things are created--not only by solitary individuals, but also by collaborative teams and social networks. 

[BF717 B28 2013]

Paulus, P. B., & Nijstad, B. A. (2003). Group creativity: Innovation through collaboration. Oxford: New York.

Glaveanu, V. P. (2014). Distributed creativity: Thinking outside the box of the creative individual. New York: Springer.

Sawyer, K. R. (2013). Zig zag: The surprising path to greater creativity. New York: Jossey-Bass

Sawyer, K. (2007). Group genius: The creative power of collaboration. New York: Basic Books.

Main Library: HD 30.29 S29 2007

John-Stein, V. (1997). Notebooks of the mind: Explorations of thinking. New York: Oxford University Press. BF 408 J5 1997

Gardner, H. (1993). Creating minds. New York: Basic Books.

Csikszentmihalyi, M. (1999). Implications of a systems perspective for the study of creativity. In R.J. Sternberg (Ed.), Handbook of Creativity (pp. 313-335). New York: Cambridge University Press.

Collins, M. A., & Amabile, T. M. (1999). Motivation and creativity. In R. J. Sternberg (Ed.), Handbook of creativity (pp. 297-312). New York: Cambridge University Press.

Boden, M. A. (1999). Computer models of creativity. In R. J. Sternberg (Ed.), Handbook of creativity (pp. 351-372). New York: Cambridge University Press.

Sternberg, R. J. (Ed.). (1999). Handbook of creativity. New York: Cambridge University Press.

Boden, M. A. (1990). The creative mind: Myths and mechanism. New York: Basic Books.

Amabile, T. M. (1998). How to kill creativity. Harvard Business Review, 76 (5), 76-87.

Amabile, T. M. (1996). Creativity in context. Boulder, CO: Westview.

Amabile, T. M. (1983). The social psychology of creativity. New York: Springer-Verlag.

Amabile, T.M. (2001). Beyond talent: John Irving and the passionate craft of creativity. American Psychologist, 56(4), 333-336.

John-Stein, V. (2000). Creative collaboration. New York: Oxford University Press.

Gloor, P. A. (2006). Swarm creativity: Competitive advantage through collaborative innovation networks. New York: Oxford University Press.

By visualizing the flow of knowledge, making it transparent, and optimizing its course, organizations and individuals become more creative, innovative, and responsive to change. This is one of the keys to success in the new century (p 16-17). Organization can successfully promote COINS by giving up central control in favor of self-organization in swarm creativity, developing an ethical code, and setting up a social network connected by hubs of trust (p.17). 
Swarm intelligence in social insects is based on self-organization; no one is in charge, but social insects successfully solve complex tasks (p.20). According to Bonabeau, self-organization has four properties:

• positive feedback reinforces desired behavior;
• negative feedback counterbalances positive feedback;
• amplification of randomness leads to positive reinforcement;
• amplification of interactivity has a positive outcome.

Social insects combine these four properties into predefined patterns, which have evolved over time, to efficiently accomplish a given task. (p.20)
Errors and randomness contribute very strongly to the success of social insects by enabling them to discover, explore, and exploit. Errors feed self-organization, creating flexibility so the colony can adapt to a changing environment with robustness, ensuring that-even when one or more individuals fail-the group can still perform its tasks. Swarm intelligence offers an alternative way of designing "intelligent" systems in which autonomy, emergence, and the ability to distribute tasks replace control, pre-programming, and centralization (p.21).
The obvious advantages in accomplishing complex tasks through swarm intelligence include no central control, errors being okay, flexibility, robustness, and self-repair. It is difficult for conventional managers to accept the idea that solutions are emergent rather than predefined and pre-programmed (p. 21).
People working with the innovator are not working for her or him because they have been ordered to do so, but because they want the innovation to succeed. They all share the same vision and goals (in a sense, the same "genes"); they want to succeed, and they want to see their innovation spread and be accepted by the outside world (p. 22).
If you and I swap a dollar, you and I still each have a dollar. If you can I swap an idea, you and I have two ideas each.

The free flow of ideas and thoughts is essential to the success of creative teams . It is entirely self-organizing and self-selecting. Roles and responsibilities of each member are clear to all, with no need for lengthy coordination meetings (p. 24).

"Creativity is just connecting things. When you ask creative people how they did something, they feel a little guilty because they didn't  really do it, they just saw something. It seemed obvious to them after a while. That's because they were able to connect experiences they have had and synthesize new things." (Interview with Steve Jobs, Wired, Feb, 1996)

Kirby Ferguson: Embrace the remix (TED Video)
URL: http://www.ted.com/talks/kirby_ferguson_embrace_the_remix.html