Computational “Accompaniment” of the Introduction of New Mathematical Concepts

IF 1.9 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Andrey Lavrenov, Elena Tolkacheva, Sergei Pozdniakov
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引用次数: 0

Abstract

The computational capabilities of computer tools expand the student’s search capabilities. Conducting computational experiments in the classroom is no longer an organizational problem. This raises the “black box” problem, when the student perceives the computational module as a magician’s box and loses conceptual control over the computational process. This article analyses the use of various computer tools, both existing and specially created for “key” computational experiments, that aim at revealing the essential aspects of the introduced concepts using specific examples. This article deals with a number of topics of algebra and calculus that are transitional from school to university, and it shows how computational experiments in the form of a “transparent” box can be used.
新数学概念引入的计算“伴奏”
计算机工具的计算能力扩展了学生的搜索能力。在课堂上进行计算实验不再是一个组织问题。这就提出了“黑盒子”问题,当学生将计算模块视为魔术师的盒子,并失去对计算过程的概念控制时。本文分析了各种计算机工具的使用,既有现有的,也有专门为“关键”计算实验创建的,旨在通过具体的例子揭示所介绍概念的基本方面。本文讨论了从中学过渡到大学的代数和微积分的一些主题,并展示了如何使用“透明”框形式的计算实验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Computation
Computation Mathematics-Applied Mathematics
CiteScore
3.50
自引率
4.50%
发文量
201
审稿时长
8 weeks
期刊介绍: Computation a journal of computational science and engineering. Topics: computational biology, including, but not limited to: bioinformatics mathematical modeling, simulation and prediction of nucleic acid (DNA/RNA) and protein sequences, structure and functions mathematical modeling of pathways and genetic interactions neuroscience computation including neural modeling, brain theory and neural networks computational chemistry, including, but not limited to: new theories and methodology including their applications in molecular dynamics computation of electronic structure density functional theory designing and characterization of materials with computation method computation in engineering, including, but not limited to: new theories, methodology and the application of computational fluid dynamics (CFD) optimisation techniques and/or application of optimisation to multidisciplinary systems system identification and reduced order modelling of engineering systems parallel algorithms and high performance computing in engineering.
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