In attempting to understand the interactions between formal and informal communities, Cynthia Kurtz and Dave Snowden’s sense-making model the Cynefin framework challenges three key assumptions currently held within organizational theory: 1) ‘Order’ – that human interactions and markets possess fundamental cause and effect relationships; 2) ‘Rational choice’ – that rational decision making based on minimizing pain or maximizing pleasure (Skinner’s ‘operant conditioning’) can be manipulated through education and thus determine possible outcomes; and 3) ‘Intent’ – that individuals or communities acquiring capabilities show an intention to use that capability. While the above assumptions may be true in some cases, Snowden’s sense-making approach contends they are not true universally, despite the fact that the methods commonly used assume that they are. Data is frequently skewed by the fact that people not only have multiple identities of which they are often blind, but they do not follow rules or act on local patterns.

Snowden, D., & Kurtz, C. F. (2003). The new dynamics of strategy: Sense-Making in a complex and complicated world. IBM Systems Journal, 42(3), 35-45.

‘Chaos, Trends and/or Rhythms Constituting Structures in Time’ by Franz Halberg (2001)

While recent studies by Stanford’s Martin Fischer highlight the benefits of employing 4D modeling in construction (improved communications for planning and production) the most common reasons for lack of adoption into practice is the steep learning curve, lack of analytical support and cost. Despite Fischer’s methodology ‘generating 4D models from 3d product models’ I would argue that valuable criteria remains missing from the project.

Currently, all 4D design systems are 3D platforms with procurement and scheduling plug-ins – essentially post-conceptual, thus limiting collaborative influence in the early stages of design. Without the ability to conceptualize ‘time’ as a critical dimension beyond the other 3, all environment design is fatally flawed from the earliest point of creative ideation. This is not however the fault of the architect – digital modeling platforms enforce a ‘bounded projection’ in how designers think and structure projects from a user-centred perspective. 4D models may be more easily understood by stakeholders, yet such benefits mask an critical point – buildings do not function solely as commodified entities, they must also adapt to provide stimulating and healthy environments over time to a broad range of people.

The physiological effects of ’time’ on humans has been known since the C18, with the latest studies linking chronobiological cycles to the human genome (Duboule, 2003). With the arrival of chronomic science (see Halberg‘s diagram above) and growth in evidence supporting the effects of electronic media on neurotransmitters like serotonin, noradrenaline, dopamine and tryptophan (natural psychotropics) an increasing number of researchers are now looking beyond traditional cognitive models to question the chronomic implications of media. My thesis begins with the assumption that chronomic science has the potential to counter traditional ‘closed’ systems of architectural design based on cybernetic homeostasis (the ‘superorganism’) by providing more ‘open’ tangible media frameworks instructed by biological rhythmicity.

The Affective Geography of Silence by Giaccardi & Sabena (2006)

In her 2001 essay ‘Digital Pedagogy’ Professor of Urban Studies at UCLA Dana Cuff raises some key issues regarding the digital media on offer throughout the majority of European and American based architectural schools. As design software ‘both reflects and enables forms of thought, as does language, according to the Whorfian hypothesis‘, Cuff notes ‘there is a decided bias toward surface rather space.’ This may come as no surprise to design tutors of production (AutoCAD, ArchiCAD, CATIA) or visualization software (Maya, FormZ, StudioMax) however as Cuff reveals, ‘most schools tend to prioritize one visualization application in studio, which invites a particular way of thinking about design.’¹ By restricting movement ’between viz-ware and production software, or between digital and material design’, Cuff contends that design environments prioritizing representation over instructional output fail to deliver the primary role of architectural drawing – instruction. While some schools are attempting to bridge the divide between digital and tactile design (e.g. UCLA, SciArc) Cuff’s essay confirms a disturbing trend within practice and research – what Kees Dorst recently referred to as an over-emphasis on process.² 

However, what Cuff and others have failed to develop is why such an over-emphasis should matter. As connectivist learning theorist George Siemens notes, recent changes in social media have irreversibly altered our understanding of learning and idea creation, thus design research internalizing the creative process from within empirically closed systems (e.g. traditional behaviourist or constructivist models) blind themselves to the open dynamics of distributed creativity. Arguably, any future companies wishing to optimize creativity in a conceptual economy (Greenspan, 1997; Pink, 2005) will be ones structured on a collective sharing of media and ideas, a connectivist approach to learning which few design researchers have yet to address, with the exception of Fischer & Giaccardi‘s conceptual framework for metadesign (see below). As Fischer et al. stress, ‘meta-design puts owners of problems in charge of creating open, evolvable systems that address the limitations associated with closed systems.’³

The SER (seeding, evolutionary growth, reseeding) model  by Gerhard Fischer (1995)

1. Deborah Snoonian & Dana Cuff, (2001) Digital Pedagogy: An Essay, Architectural Record, Vol. 189, Issue 9

2. Kees Dorst, (2007) Design research: a revolution-waiting-to-happen, Keynote speech delivered at the Congress of the International Association of Societies of Design Research, Hong Kong Polytechnic University

3. Gerhard Fischer et al., (2004) Meta-Design: A Manifesto for End User Development. Communications of the ACM, Vol. 47, Issue 9, pp 33-37

Investigating the nature of intuition the 1970s, Amos Tversky and Daniel Kahneman identified cognitive bias as heuristic reasoning (cognitive shortcuts) which results in errors of statistical judgment, social attribution and memory. Ubiquitous throughout human cognition, such errors clearly skew the reliability of anecdotal and verbal protocol analysis. Reminiscent of McLuhan’s notion of hot and cool media cognitive biases have also been grouped into either hot or cold states of emotional arousal. E.g., highly attentive and interactive information affording heightened patterns arousal or ‘hot cognition’  bias rapid emotionally-charged decision making without analytical reflection. Conversely, low attentive non-engaging information affording low patterns of arousal or ‘cold cognition’ bias calmer reflective thought processes.¹ The above diagram is taken from a recent visual study of cognitive bias which can be found here.

As Peter Rowe argued, the practice of architectural design is inherently heuristic, exerting ‘a strong and dynamic influence over subsequent sequences of problem interpretation, solution generation, problem representation and solution assessment.’² Based on protocol analyses of architectural designers at work, Rowe identifies five classes of heuristic constraints which shape architectural production: 1) anthropometric analogies, 2) literal analogies, 3) environmental relations, 4) typologies and 5) formal languages. A more extended analysis to the one offered below can be found in his 1991 book Design Thinking.

1. Abelson, R. P. (1963). Computer simulation of “hot cognition”, in S. S. Tomkins & S. Messick (Eds.), Computer simulation of personality (pp. 277-302). New York: Wiley

2. Rowe, P. (1999). A Priori Knowledge and Heuristic Reasoning in Architectural Design. In Classic Readings in Architecture, edited by K. Spreckelmeyer & J. Stein. WCB/McGraw Hill. Originally published in Journal of Architectural Education 36, no.1 (1982) p.18

Connectivism MindMap by George Siemens (2004)

In response to shifts in education media and the limitations of behaviorist, cognitivist and constructivist learning environments, George Siemens and Stephen Downes have developed an alternative model – connectivism. Referred to as “a learning theory for the digital age” it aims to understand the effects of technology on human life, communications and learning:

‘…connectivism is the integration of principles explored by chaos, network, and complexity and self-organization theories. Learning is a process that occurs within nebulous environments of shifting core elements – not entirely under the control of the individual. Learning (defined as actionable knowledge) can reside outside of ourselves (within an organization or a database), is focused on connecting specialized information sets, and the connections that enable us to learn more are more important than our current state of knowing. Connectivism is driven by the understanding that decisions are based on rapidly altering foundations.‘¹

As Siemens himself notes, the idea for connectivism is drawn from earlier texts on distributed congition Hutchins, media theory McLuhan and social development Vygotsky. In this respect it seems difficult to claim the theory as revolutionary, indeed as a review of the epistemology of design highlights, the majority of learning theories have evolved from three fundamental positions – innatism, empiricalism and constructivism. However, despite recent critics who claim it can not be defined as a theory (Verhagen, 2006), Siemens argument for revising the fundamental precepts of learning from ‘skill acquisition’ to ‘actionable knowledge’ seems well justified on many levels, not least of which is the growing evidence base supporting educational software.

Contrary to assumptions that networks ‘haven’t changed learning so much that we need to throw away all of the established learning theories and replace them with a new one’ (Kerr, 2006), distributed co-creation radically confronts the inadequacies of traditional learning models (Kolb, Riding, Gregorc, Myers-Brigg, Entwistle) which are predominantly based on inadequately validated concepts of genetic inheritance, archetypal psychology and instrinsic motivation. Many of Siemens’ critics fail to grasp this salient point – connectivism does not transfer cognitive power from the individual to the smartmob (digital Maoism) as proposed by media moralists like Jaron Lanier.

Rather, it responds to the urgent need for educational professionals to begin sharing and building a knowledge base to address fundamental change, instead of wasting time agressively defending opposing theoretical positions which bear little or no relevance to how digital natives (screenagers) acquire knowledge in the C21.

1. George Siemens, (2005) Connectivism: A Learning Theory for the Digital Age, Retrieved 17/01/11 http://www.itdl.org/journal/jan_05/article01.htm