Human learning versus machine learning: Analogies that can be used to approach Cognitive Neuroscience in Continuing Education for Basic Education teachers

• DOI: https://doi.org/10.22533/at.ed.5585525260215

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• Abstract:

  Teacher training must be geared towards a better understanding of the multiplicity of factors that interfere with learning, in order to enhance the educational process.  Understanding the factors that govern learning requires an understanding of the development of cognitive neuroscience.  From a neuroscientific perspective, the argument about the effectiveness of the learning process can take place as follows: when we learn, what changes occur in the brain so that we can later recall a piece of knowledge or perform a rehearsed behavior? The answer to this question involves knowledge related to the process of acquiring information. 
  Cognitive neuroscience studies how information is processed in the brain. In order to facilitate understanding of the learning process in the human brain, analogies can be drawn with the learning process developed in machines. The aim of this paper is to relate some concepts from the field of computing and the development of machine learning to the learning process in the human brain. Nowadays, people have more and more knowledge about computer science concepts and analogies with neuroscience concepts can facilitate the dissemination of essential neuroscience concepts in the educational sphere.
  In some examples it is appropriate to use analogies to compare the learning process in artificial and human systems. Many brain processes, such as the process of acquiring information, are similar to computer processes and the use of analogies can facilitate understanding. However, there are factors that greatly differentiate these learning processes, so these analogies must be used carefully.