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Interdisciplinary Approach in Physics Education Using Modeling of Physical Processes

EasyChair Preprint no. 4240

5 pagesDate: September 22, 2020

Abstract

For a long time, many people have been having difficulties with effective learning and deep understanding of various sciences, especially such fundamental ones as physics. This is a big problem as it directly affects the ability of humanity to progress, make serious life decisions, improve livelihood, etc. This issue was regarded multiple times throughout the history of humankind, but it all was of little productivity. The reason is that education is a neurobiological process and should be treated respectively. Any investigations that were not using and mentioning neuroscience could not provide precise problem description and solution. The purpose of this article is to suggest a neuroscientifically explained way to make studying and understanding of different matters easier for learners of any age by combining multiple spheres of experience (disciplines) and propose an ICT application – modeling of physical processes – based on the example of physics education. The method, overall, helps the brain improve memory, structurization and merging processes; collect more basic ideas, methods, approaches, real and abstract experience. All of these are the core of creativity, flexibility, inventiveness, problem-solving and deep comprehension, not only in physics, but also in many other fields of human life. Modeling of physical processes might greatly increase the effectiveness of the method and facilitate the learning process.

Keyphrases: cognitive science, episodic memory, ICT in education, interdisciplinary approach, Modeling of physical processes, physics education, semantic memory

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:4240,
  author = {Mykola Stretovych},
  title = {Interdisciplinary Approach in Physics Education Using Modeling of Physical Processes},
  howpublished = {EasyChair Preprint no. 4240},

  year = {EasyChair, 2020}}
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