Film director James Cameron once said that young filmmakers should adopt the motto “Failure is an option. Fear is not.” His point was that in order for new artistry to emerge in his field, filmmakers have to take risks and explore the potential of their medium without worrying about whether the product is successful or marketable. This struck me as a good motto for classrooms as well. To provide an optimal learning environment for students, teachers must create an intellectually safe space, where risk-taking is celebrated as much as getting the right answer. This type of learning space needs to be deliberately set up at the beginning of the school year and reinforced throughout the year, just as much as classroom layout and other rules and routines. So in getting ready to go back to school, here are some ideas to consider for constructing a space that supports possibilities rather than perfection.
The current view of motor learning suggests that when we revisit a task, the brain recalls the motor commands it previously learned. In this view, motor memory is a memory of motor commands, acquired through trial-and-error and reinforcement. Here we show that the brain controls how much it is willing to learn from the current error through a principled mechanism that depends on the history of past errors. This suggests that the brain stores a previously unknown form of memory, a memory of errors. A mathematical formulation of this idea provides insights into a host of puzzling experimental data, including savings and meta-learning, demonstrating that when we are better at a motor task, it is partly because the brain recognizes the errors it experienced before.
Complexity Institute's insight:
The learning process is a co-generative modality between the being
and the environment, and try-and-learn modality is the only way to build a coherent meaning from the environment to stay alive.
The human brain is puzzling -- it is curiously large given the size of our bodies, uses a tremendous amount of energy for its weight and has a bizarrely dense cerebral cortex. But: why? Neuroscientist Suzana Herculano-Houzel puts on her detective's cap and leads us through this mystery. By making "brain soup," she arrives at a startling conclusion.
We can be healthier, live longer, and make the world a better place by exploring our potential for compassionate behavior, according to neurosurgeon James Doty, founder and director of the Center for Compassion and Altruism Research and Education,...
Dans de nombreuses industries, l’intelligence collective est aujourd’hui au cœur du succès d’une entreprise, car elle est non seulement le meilleur moyen de générer des solutions aux problèmes complexes grâce, elle permet aussi d’embarquer un grand...
During consensus decision making, individuals in groups balance personal information (based on their own past experiences) with social information (based on the behavior of other individuals), allowing the group to reach a single collective choice. Previous studies of consensus decision making processes have focused on the informational aspects of behavioral choice, assuming that individuals make choices based solely on their likelihood of being beneficial (e.g., rewarded). However, decisions by both humans and nonhuman animals systematically violate such expectations. Furthermore, the typical experimental paradigm of assessing binary decisions, those between two mutually exclusive options, confounds two aspects common to most group decisions: minimizing uncertainty (through the use of personal and social information) and maintaining group cohesion (for example, to reduce predation risk). Here we experimentally disassociate cohesion-based decisions from information-based decisions using a three-choice paradigm and demonstrate that both factors are crucial to understanding the collective decision making of schooling fish.
Both information and social cohesion determine collective decisions in animal groups Noam Miller, Simon Garnier, Andrew T. Hartnett, and Iain D. Couzin
Gnawing on his left index finger with his chipped old British teeth, temporal veins bulging and brow pensively squinched beneath the day-before-yesterday’s hair, the mathematician John Horton Conway unapologetically whiles away his hours tinkering and thinkering — which is to say he’s ruminating, although he will insist he’s doing nothing, being lazy, playing games.
Based at Princeton University, though he found fame at Cambridge (as a student and professor from 1957 to 1987), Conway, 77, claims never to have worked a day in his life. Instead, he purports to have frittered away reams and reams of time playing. Yet he is Princeton’s John von Neumann Professor in Applied and Computational Mathematics (now emeritus). He’s a fellow of the Royal Society. And he is roundly praised as a genius. “The word ‘genius’ gets misused an awful lot,” said Persi Diaconis, a mathematician at Stanford University. “John Conway is a genius. And the thing about John is he’ll think about anything.… He has a real sense of whimsy. You can’t put him in a mathematical box.”
The hoity-toity Princeton bubble seems like an incongruously grand home base for someone so gamesome. The campus buildings are Gothic and festooned with ivy. It’s a milieu where the well-groomed preppy aesthetic never seems passé. By contrast, Conway is rumpled, with an otherworldly mien, somewhere between The Hobbit’s Bilbo Baggins and Gandalf. Conway can usually be found loitering in the mathematics department’s third-floor common room. The department is housed in the 13-story Fine Hall, the tallest tower in Princeton, with Sprint and AT&T cell towers on the rooftop. Inside, the professor-to-undergrad ratio is nearly 1-to-1. With a querying student often at his side, Conway settles either on a cluster of couches in the main room or a window alcove just outside the fray in the hallway, furnished with two armchairs facing a blackboard — a very edifying nook. From there Conway, borrowing some Shakespeare, addresses a familiar visitor with his Liverpudlian lilt:
Two great trends are evident in the evolution of life on Earth: towards increasing diversification and towards increasing integration. Diversification has spread living processes across the planet, progressively increasing the range of environments and free energy sources exploited by life. Integration has proceeded through a stepwise process in which living entities at one level are integrated into cooperative groups that become larger-scale entities at the next level, and so on, producing cooperative organizations of increasing scale (for example, cooperative groups of simple cells gave rise to the more complex eukaryote cells, groups of these gave rise to multi-cellular organisms, and cooperative groups of these organisms produced animal societies). The trend towards increasing integration has continued during human evolution with the progressive increase in the scale of human groups and societies. The trends towards increasing diversification and integration are both driven by selection. An understanding of the trajectory and causal drivers of the trends suggests that they are likely to culminate in the emergence of a global entity. This entity would emerge from the integration of the living processes, matter, energy and technology of the planet into a global cooperative organization. Such an integration of the results of previous diversifications would enable the global entity to exploit the widest possible range of resources across the varied circumstances of the planet. This paper demonstrates that it's case for directionality meets the tests and criticisms that have proven fatal to previous claims for directionality in evolution.
The direction of evolution: The rise of cooperative organization John E. Stewart
This week, at the 23rd annual Systems Thinking in Action conference, leaders of organizations around the world are gathering to learn how to make sense of complexity, shift an organization's culture, and create meaningful ...
Working together requires information. Going from information to action is at the center of any good knowledge management process. Too often, however, operationalizing collaboration concentrates on what could be measured. In this case its sharing and knowledge management.
Digital data stem from our own personal and social cognitive processes and thus express them in one way or another. But we still don’t have any scientific tools to make sense of the data flows produced by online creative conversations at the scale of the digital medium as a whole.
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