• Title/Summary/Keyword: computational mathematics

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Improving Computational Thinking Abilities Through the Teaching of Mathematics with Sage ('컴퓨팅 사고력(Computational thinking)' 향상과 Sage 도구를 이용한 수학교육)

  • Park, Kyung-Eun;Lee, Sang-Gu
    • Communications of Mathematical Education
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    • v.29 no.1
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    • pp.19-33
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    • 2015
  • Recently in major industrial areas, there has been a rapidly increasing demand for 'Computational Thinking', which is integrated with a computer's ability to think as a human world. Developed countries in the last 20 years naturally have been improving students' computational thinking as a way to solve math problems with CAS in the areas of mathematical reasoning, problem solving and communication. Also, textbooks reflected in the 2009 curriculum contain the applications of various CAS tools and focus on the improvement of 'Computational Thinking'. In this paper, we analyze the cases of mathematics education based on 'Computational Thinking' and discuss the mathematical content that uses the CAS tools including Sage for improving 'Computational Thinking'. Also, we show examples of programs based on 'Computational Thinking' for teaching Calculus in university.

An Analysis of Teaching and Learning Activities in Elementary Mathematics Based on Computational Thinking (Computational Thinking 기반 초등수학과 교수.학습활동 분석)

  • Nam, Choong-No;Kim, Chong-Woo
    • 한국정보교육학회:학술대회논문집
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    • 2011.01a
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    • pp.47-51
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    • 2011
  • The aim of Information Education is to improve the problem-solving skills based on Computational Thinking. In the current elementary school curriculum, there is no independent information subject. So, it will get used to browse the sub-element being applied implications for Computational Thinking through an analysis of teaching and leaning elementary mathematic scene. In this paper reveal the relationship sub-element of the Computational Thinking for solving problems through teaching and learning scene in elementary mathematics.

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Transforming mathematics education with AI: Innovations, implementations, and insights

  • Sheunghyun Yeo;Jewoong Moon;Dong-Joong Kim
    • The Mathematical Education
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    • v.63 no.2
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    • pp.387-392
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    • 2024
  • The use of artificial intelligence (AI) in mathematics education has advanced as a means for promoting understanding of mathematical concepts, academic achievement, computational thinking, and problem-solving. From a total of 13 studies in this special issue, this editorial reveals threads of potential and future directions to advance mathematics education with the integration of AI. We generated five themes as follows: (1) using ChatGPT for learning mathematical content, (2) automated grading systems, (3) statistical literacy and computational thinking, (4) integration of AI and digital technology into mathematics lessons and resources, and (5) teachers' perceptions of AI education. These themes elaborate on the benefits and opportunities of integrating AI in teaching and learning mathematics. In addition, the themes suggest practical implementations of AI for developing students' computational thinking and teachers' expertise.

PARALLEL COMMUNICATING AUTOMATA SYSTEMS -A SURVEY

  • Carlos Martin-Vide;Victor Mitrana
    • Journal of applied mathematics & informatics
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    • v.7 no.2
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    • pp.357-377
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    • 2000
  • A parallel communicating automata system is an accepting device based on the communications between more automata working in parallel. It consists of several automata corking independently but communicating with each other by request. We survey several variants of parallel communicating automata systems with respect to their computational power. Other aspects like decidability and complexity matters are also briefly discussed. Some open problem sand directions for future research are finally pointed out.

NUMERICAL SIMULATIONS FOR THE CONTRACTION FLOW USING GRID GENERATION

  • Salem, S.A.
    • Journal of applied mathematics & informatics
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    • v.16 no.1_2
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    • pp.383-405
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    • 2004
  • We study the incomprssible Navier Stokes equations for the flow inside contraction geometry. The governing equations are expressed in the vorticity-stream function formulations. A rectangular computational domain is arised by elliptic grid generation technique. The numerical solution is based on a technique of automatic numerical generation of acurvilinear coordinate system by transforming the governing equation into computational plane. The transformed equations are approximated using central differences and solved simultaneously by successive over relaxation iteration. The time dependent of the vorticity equation solved by using explicit marching procedure. We will apply the technique on several irregular-shapes.

SOME PROPERTIES OF SUMMABLE IN MEASURE

  • Kim, Hwa-Joon
    • Journal of applied mathematics & informatics
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    • v.25 no.1_2
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    • pp.525-531
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    • 2007
  • We newly introduce the concept of summable in measure and investigate on some its properties. In addition to this, we consider a size of given series by means of we are giving Lebesgue measure to an associated series.

A SIXTH-ORDER OPTIMAL COLLOCATION METHOD FOR ELLIPTIC PROBLEMS

  • Hong, Bum-Il;Ha, Sung-Nam;Hahm, Nahm-Woo
    • Journal of applied mathematics & informatics
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    • v.6 no.2
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    • pp.513-522
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    • 1999
  • In this paper we present a collocation method based on biquintic splines for a fourth order elliptic problems. To have a better accuracy we formulate the standard collocation method by an appro-priate perturbation on the original differential equations that leads to an optimal approximating scheme. As a result computational results confirm that this method is optimal.

THE CONVERGENCE OF A DUAL ALGORITHM FOR NONLINEAR PROGRAMMING

  • Zhang, Li-Wei;He, Su-Xiang
    • Journal of applied mathematics & informatics
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    • v.7 no.3
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    • pp.719-738
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    • 2000
  • A dual algorithm based on the smooth function proposed by Polyak (1988) is constructed for solving nonlinear programming problems with inequality constraints. It generates a sequence of points converging locally to a Kuhn-Tucker point by solving an unconstrained minimizer of a smooth potential function with a parameter. We study the relationship between eigenvalues of the Hessian of this smooth potential function and the parameter, which is useful for analyzing the effectiveness of the dual algorithm.