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Nonlinear Pedagogy: Learning Design for Self-organizing Neurobiological Systems

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I am going to summarize the article on nonlinear pedagogy. The focus of this article is how learning designs can be changed by the ideas of self-organization, meta-stability and self-organized criticality in difficult neurobiological systems. Throughout this article they have shown how an interplay of constraints in the learning environment can cause behavior changes in the neurobiological systems. By manipulating key constraints such as the environment and personal constraints, a learner can be driven to the meta-stable state such as the environment and personal constraints, a learner can be channeled to the meta-stable state of learning where they can explore and creatively use various behaviors. The inclusion of noise, in particular ‘colored’ noise in the learning process can benefits individuals and help them to gain a wide understanding of the learning designs. Different constraints can channel earners towards the SOC region where they can stand on a performance transition. Recently trainers have adapted their training methods to use different methods of interacting task constraints such as various equipment, space and sources of information. This new approach has been found to be more successful than the traditional prescriptive stance as it will aid more dynamic learning for a performer/student. Neurobiological systems show the development of cognitive learning, and how these systems help improve the process of acquiring knowledge and understanding it properly through experience, thought and senses. Because of indeterminate interactions between learners and the environment, the proves of how individuals gain knowledge takes place. Newel’s Model (1986) shows that the motor coordination emerges from the interplay between the organism, the task and the environment. A human’s performance is adapted to the goal in which an individual wants to meet. In order for learners to find solutions to which will aid them to achieve their goal, educators should act as facilitators to guide learners. In nonlinear dynamics it has been proven that complex neurobiological systems constantly change between stability and instability in order to adapt to various changes in constrains within the environment. As an individual aspires to achieve a certain goal, different patterns of behaviour appear, this shows that neurobiological systems are important.

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There are many differences between nonlinear and linear systems. Within linear systems, one cause will only result in one singular change in behavior or effects. However, within non-linear systems one cause can result in one change or many different changes in behavior or effects. This is very significant for performers as one small change in their training or equipment can result in a huge change in learning and performance. Linear systems are known as mono-stable, whereas non-linear systems are known as multi-stable. Another aspect of linear/non-linear systems which differ is noise. Noise can play a functionable role in non-linear systems, where as it can be detrimental in linear systems.

There are many different constraints that can cause different actions and behaviours within an individual. Examples include, task constraints (e.g. rules of the game), environmental constraints (e.g. temperature, light, gravity) and personal constraints (e. g psychological characteristics). Learners must satisfy different constraints in order to reach their goal. The interaction between the different key constraints causes each individual to lead a different path of learning and to succeed in different ways. It is important for trainers to know this so that each individual doesn’t have to adhere to the same training methods. Noise is one variable which was studied a lot. Studies show that the addition of noise can challenge people to perform in different ways. A study on birds can prove that people adapt in different ways to constraints in order to reach their goals. It is shown that it is better to guide individuals and let them think of their own performance solutions rather than giving corrective instructions and repeating the same tasks.

Relative co-ordination patterns allow individuals to re-organise their components into stable patterns allowing them to have good co-ordination. In task performance games, if a coach varies small constraints in the game, the game re-organises itself producing different constraints varying from simple to very hard. This allows the performer to gage their own learning and see their self-improvements. It is important that all learning strategies are directed towards critical state in which they can vary to allow transitions in behaviour when needed. In team games, small changes usually cause small results however, when abrupt changes are successfully the team normally reaches one of their goals. Also, in team games most of the structural changes are caused as a result of bad events. Team games are normally stable and this is balances with short burst of abrupt movement and activity. This makes the games competitive. By aiming to reach critical point, this provides a platform for team games to allow creativity and vary constraints. If a team can manipulate these constraints they increase their chances of reaching their goal and over-coming the other team.

By manipulating constraints, the learner can reach an optimal level and increase his/her performance. This will also lead them towards the SOC region. It is very important in training groups to direct learners towards the SOC region where transitions can occur. In these regions, individuals seek to adapt to changing environmental constraints which occur during performance. During this, there may be a need to adapt individual constraints if the learners is not adapting to the environmental constraints. The coach then needs to create a task to manipulate the constraints, for example – changing equipment.

A previously highlighted, the role of noise in the learning environment can channel learners towards a state where solutions to movement are there to be explored. This is also known as a meta-stable state. A high noise content can lead to lots of movement solutions and variability while in the meta-stable state. Noise can be designed by trainers and educators to benefit the learner and open up their exploration paths in which they can seek their own solutions and reach their goals. Coloured noise is a lot more beneficial that white noise.

In conclusion, this article highlights the importance of guiding learners to seek their own solutions by manipulating various task constraints which will open up the learner’s exploration and function ability paths leading to greater success.

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