Tuesday, May 12, 2015

Outflow obstruction can occur in feedback loop

Feedback process is initiated by instructor and learner tries to target algorithmic functions and threads in a Feedback framework. The Digestion process in brain implies to mechanism mode, which Feedback Threads capture successfully.  Threads Reference boosts, synchronizes, and saves in Domain Registration. Eventually, it returns signal ( ) function to Brain Controller in order to call threads which is associated with Presence Conceptual Knowledge. When Instance Threads of Presence Conceptual Knowledge identify in Brain then start Adjustment Process Mode. Compare old threads with new Feedback threads in terms of maximizing common threads synchronization. Sensor mode implies to learner who wants to control Feedback Threads through knowledge examination.  Output threads can be controlled by external or internal entities.  Open-loop feedback Mode (critical feedback undermine learning) can inspire learner to contact with instructor again and provide specific feedback. Closed-loop feedback Mode indicates that threads in Feedback solve complexity in relevant data structures. (Fig 1& Fig 2)
In a number of ways, Feedback fails to respond and learner might be frustrated according to following risk factors.
1- Instructor cannot use pedagogical content knowledge in order to keep track of communication threads; therefore, response to question would be irrelevant.
2- A question response has not pedagogical principles and parameters theory in learning styles.
3- Feedback Threads have inconsistent map; therefore, Digestion process encounter with complexity in Brain.
4- Digestion process does not register in the Brain. Learner has not plan to review Feedback threads.
5- Brain cannot adjust Feedback Threads with Presence of Conceptual Knowledge.
Feedback threads can be reviewed by Brain or external entities (examination). Open-loop feedback (inconsistent feedback threads) needs to be recovered by instructor (controller).
Brain is a sort of Black Box, which internal abstract model and genetic algorithm frameworks can be read, interpreted, and concretized through the way Brain Mechanisms work.




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