Meta learning
From Wikipedia, the free encyclopedia
Meta learning is the process whereby a system (person, group or organization) manages to dissolve limiting dynamics such as point attractors and limit cycles that impede effective action and evolve complex attractors that have trajectories in phase space that never repeat themselves. These trajectories have a fractal nature, hence their complex order which leads to innovation and creativity (see complexor). High performance teams are able to "meta learn" (Losada, 1999; Losada & Heaphy, 2004; Fredrickson & Losada, 2005).
The meta learning model comprises three state variables and one control parameter. The control parameter is connectivity; the three state variables are: inquiry-advocacy, positivity/negativity, and other-self (external-internal orientation). The state variables are linked by a set of nonlinear differential equations (Losada, 1999; Fredrickson & Losada, 2005; for a graphical representation of the meta learning model see Losada & Heaphy, 2004). When connectiviy is low, there is preponderance of advocacy and self orientation and more negativity than positivity. When connectivity is high there is a dynamical equilibrium between inquiry and advocacy as well as internal and external orientation and the ratio of positivity-to-negativity is at least 2.9 (this ratio is known as the Losada line).
[edit] References
- Losada, M. (1999). The complex dynamics of high performance teams. Mathematical and Computer Modelling, 30 (9-10), pp. 179-192.[1]
- Losada, M. & Heaphy, E. (2004). The role of positivity and connectivity in the performance of business teams: A nonlinear dynamics model. American Behavioral Scientist, 47 (6), pp. 740-765.[2]
- Fredrickson, B. L. & Losada, M. (2005). Positive affect and the complex dynamics of human flourishing. American Psychologist, 60 (7) 678-686.[3]
