The Complexity Leadership Theory (CLT) starts with the notion of Complex Adaptive Systems (CAS), which are a basic unit of analysis in complexity science. CAS are neural-like networks of interactin...
Jim Price's insight:
'Complex Leadership Theory' is something that I have been teaching for over 10 years at postgraduate level for medical, health and social care students at the University of Brighton, UK.
I am so pleased there is a growing literature base about complex leadership, because, intuitively, I have always known it to be the best context in which to teach this slippery subject. This has been evidenced by feedback from my students, much of which has indicated career-changing transformative experiences.
Roger Martin recently diagnosed a kind of complexity that is manufactured by us and largely unaddressed: inter-domain complexity.
Jim Price's insight:
What a great phrase - perfect in so many ways. This 'inter-domain' complexity is an interesting concept and adds to the fragmentation/ wholism dynamic in systems thinking. Suffice it to say that I have often been made to feel that I 'should' be embarrassed, by espousing a 'complexity' worldview, but in truth I have never been embarrassed by preferring this lens to life - it helps me more than any other I've come across - except perhaps Buddhism.
Collaboration may be understood as the execution of coordinated tasks (in the most general sense) by groups of users, who cooperate for achieving a common goal. Collaboration is a fundamental assumption and requirement for the correct operation of many communication systems. The main challenge when creating collaborative systems in a decentralized manner is dealing with the fact that users may behave in selfish ways, trying to obtain the benefits of the tasks but without participating in their execution. In this context, Game Theory has been instrumental to model collaborative systems and the task allocation problem, and to design mechanisms for optimal allocation of tasks. In this paper, we revise the classical assumptions of these models and propose a new approach to this problem. First, we establish a system model based on heterogenous nodes (users, players), and propose a basic distributed mechanism so that, when a new task appears, it is assigned to the most suitable node. The classical technique for compensating a node that executes a task is the use of payments (which in most networks are hard or impossible to implement). Instead, we propose a distributed mechanism for the optimal allocation of tasks without payments. We prove this mechanism to be robust evenevent in the presence of independent selfish or rationally limited players. Additionally, our model is based on very weak assumptions, which makes the proposed mechanisms susceptible to be implemented in networked systems (e.g., the Internet).
PubMed comprises more than 22 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.
Networks of interconnected nodes have long played a key role in cognitive science, from artificial neural networks to spreading activation models of semantic memory. Recently, however, a new Network Science has been developed, providing insights into the emergence of global, system-scale properties in contexts as diverse as the Internet, metabolic reactions or collaborations among scientists. Today, the inclusion of network theory into cognitive sciences, and the expansion of complex systems science, promises to significantly change the way in which the organization and dynamics of cognitive and behavioral processes are understood. In this paper, we review recent contributions of network theory at different levels and domains within the cognitive sciences.
Networks in Cognitive Science
Andrea Baronchelli, Ramon Ferrer-i-Cancho, Romualdo Pastor-Satorras, Nick Chater, Morten H. Christiansen
A reminder that complex systems theory is all about scalability (fractals for instance) and that the ways of working of the brain in cognitive science can offer clincial teachers lessons about how we teach in other contexts - both the classroom & workplace. Just 'think' about it...!
Just as the industrial age produced the laws of thermodynamics, we need universal laws of complexity to solve our seemingly intractable problems
Jim Price's insight:
Big data are the by-productof our myriad interconnections - and complexity & network theories do help us with frameworks with which to deal with the data generated, but what might superficially be perceived as 'chaos'. Big data and complex systems demand new ways of researching things.
What we need are some agreed 'terms of engagement' with research, and to assert independence from, albeit with acknowledged synergy with, the more traditional paradigms of research, traditional 'ways of doing' AND assessment. We need new and complementary ways to conduct research and assessment in this new, data-sated, complex educational ecosystem.
Editor’s note: Steve Wishman is a presentation designer at Prezi. Known for creating rich cinematic presentations for TED presenters and Silicon Valley leaders, engineers, startups, and more, Steve comes to Prezi with a lofty but simple goal: to create breathtaking visual stories that help change the world.
Helpful advice - but no mentiuon of Prezi which at least allows a sidgeon of non-linearity to one's presentions. vertigo-inducing perhaps, but useful if non-linear presenting is waht you want. Does anyone know of other non-linear applications like Prezi?
According to a 2011 report by the Pew Research Center's Internet & American Life Project, of the 74% of American adults using the Internet, 34% have read someone else's commentary or experience about health or medical issues on an online news group, website or blog. Meanwhile, about 13% of patients blog about their diagnosis or experience.
Dr Hannah Fry, according to her website, is a “Dr. of Fluid Dynamics, researcher of Complexity Theory and all round bad-ass.” If you take a look at her PhD Thesis, it's 200 pages of graduate level mathematics that pretty well ...
Jim Price's insight:
Useful summary in the conclusion - again from someone unrelated to medicine or education, but the lessons are there. I've read Duhigg's book and agree that it is worth a read, as is Jeremy Dean's ' making habits, breaking habits'.
James Glattfelder studies complexity: how an interconnected system -- say, a swarm of birds -- is more than the sum of its parts. And complexity theory, it turns out, can reveal a lot about how the economy works.
Jim Price's insight:
A good 14 minute introduction to systems and complexity - using finance as the prime example - but relevent in every sphere, including medical education. It's all about 'understanding' and 'sense making'...
These are my top tips try to address different aspects of effective explanations – the what and the how of explanations – the content and the delivery. What is reassuring is that really effective explanations can be deconstructed and be based upon evidence of how memory works, rather than being simply attributed to the power of personality. Great explanations, like all aspects of great teaching, can be repeatedly honed and improved."
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