• Title/Summary/Keyword: Algorithmic

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A Case Study of Developing Students' Ability to Design Algorithm in LOGO Environment

  • Peng, Aihui
    • Research in Mathematical Education
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    • v.11 no.1
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    • pp.65-74
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    • 2007
  • The algorithmic idea has been a kind of necessary mathematics quality for modern people in this information society. In China the algorithm was represented fully as one of the new mathematics contents in the secondary level for the first time when The Standards of Mathematics Curriculum for the Senior High School was promulgated in 2003, so the research about the teaching algorithm undoubtedly has its practical implications for mathematics education. In this paper, with the conceptual framework of The Mathematics Task Framework as the research tool, an algorithmic teaching case based on LOGO software was introduced in detail, and data by ways of observations, interviews and worksheets were collected, then the case was analyzed. The results showed that the teaching of algorithm is feasible and effective in the LOGO environment. Some beneficial implications about the instructional design of algorithm were also discussed.

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A review of tree-based Bayesian methods

  • Linero, Antonio R.
    • Communications for Statistical Applications and Methods
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    • v.24 no.6
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    • pp.543-559
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    • 2017
  • Tree-based regression and classification ensembles form a standard part of the data-science toolkit. Many commonly used methods take an algorithmic view, proposing greedy methods for constructing decision trees; examples include the classification and regression trees algorithm, boosted decision trees, and random forests. Recent history has seen a surge of interest in Bayesian techniques for constructing decision tree ensembles, with these methods frequently outperforming their algorithmic counterparts. The goal of this article is to survey the landscape surrounding Bayesian decision tree methods, and to discuss recent modeling and computational developments. We provide connections between Bayesian tree-based methods and existing machine learning techniques, and outline several recent theoretical developments establishing frequentist consistency and rates of convergence for the posterior distribution. The methodology we present is applicable for a wide variety of statistical tasks including regression, classification, modeling of count data, and many others. We illustrate the methodology on both simulated and real datasets.

A Computing Method of a Process Coefficient in Prediction Model of Plate Temperature using Neural Network (신경망을 이용한 판온예측모델내 공정상수 설정 방법)

  • Kim, Tae-Eun;Lee, Haiyoung
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.28 no.11
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    • pp.51-57
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    • 2014
  • This paper presents an algorithmic type computing technique of process coefficient in predicting model of temperature for reheating furnace and also suggests a design method of neural network model to find an adequate value of process coefficient for arbitrary operating conditions including test conditons. The proposed neural network use furnace temperature, line speed and slab information as input variables, and process coefficient is output variable. Reasonable process coefficients can be obtained by an algorithmic procedure proposed in this paper using process data gathered at test conditons. Also, neural network model output equal process coefficient under same input conditions. This means that adquate process coefficients can be found by only computing neural network model without additive test even if operating conditions vary.

The Development of Contents in Real Life for Improving Algorithmic Thinking of Elementary Gifted Student in Information (초등 정보영재의 알고리즘적 사고력 향상을 위한 실생활 중심의 컨텐츠 개발)

  • Jeon, Su-Ryun;Nam, Dong-Soo;Lee, Tae-Wuk
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2011.06a
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    • pp.225-228
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    • 2011
  • 창의성이 강조되는 시대에 영재 교육의 중요성은 점차 높아지고 있다. 그러나 정보 영재를 위한 연구는 수학이나 과학 영재에 비해 미미한 수준이며, 특히 초등 정보영재를 위한 프로그래밍 교육은 창의적 알고리즘을 개발하는 능력을 기르는 것보다 학습자의 수준에 맞지 않는 특정 프로그래밍 언어의 사용법이나 문법 위주의 교육에 치중하고 있다는 우려의 목소리가 높았다. 이에 본 논문에서는 초등 정보영재의 알고리즘적 사고력을 향상시키기 위한 실생활 중심의 컨텐츠를 제안하고자 한다. 초등학생의 생활과 밀접하게 연관된 주제를 선정하여 학습 동기를 유발하고, Polya의 문제해결모형을 토대로 스스로 이야기를 만들고 그 안에서 알고리즘을 찾아가는 과정을 통해 알고리즘적 사고력을 향상시킬 수 있도록 컨텐츠를 설계하였다.

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A Fuzzy Logic Based Software Development Cost Estimation Model with improved Accuracy

  • Shrabani Mallick;Dharmender Singh Kushwaha
    • International Journal of Computer Science & Network Security
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    • v.24 no.6
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    • pp.17-22
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    • 2024
  • Software cost and schedule estimation is usually based on the estimated size of the software. Advanced estimation techniques also make use of the diverse factors viz, nature of the project, staff skills available, time constraints, performance constraints, technology required and so on. Usually, estimation is based on an estimation model prepared with the help of experienced project managers. Estimation of software cost is predominantly a crucial activity as it incurs huge economic and strategic investment. However accurate estimation still remains a challenge as the algorithmic models used for Software Project planning and Estimation doesn't address the true dynamic nature of Software Development. This paper presents an efficient approach using the contemporary Constructive Cost Model (COCOMO) augmented with the desirable feature of fuzzy logic to address the uncertainty and flexibility associated with the cost drivers (Effort Multiplier Factor). The approach has been validated and interpreted by project experts and shows convincing results as compared to simple algorithmic models.

The Relationships of Chemistry problem Solving Ability with Cognitive Variables and Affective Variables (화학 문제 해결력과 인지적.정의적 변인 사이의 관계)

  • Noh, Tae-Hee;Han, Jae-Young;Kim, Chang-Min;Jeon, Kyung-Moon
    • Journal of the Korean Chemical Society
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    • v.44 no.1
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    • pp.68-73
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    • 2000
  • In this study, tlhe relationships of high school students' abilities to solve chemistry problems with cognitive variables (logical thinking ability, mental capacity. and learning strategy) and affective variables(self-efficacy, self-concept of ability, learning goal, and attitude toward science) were investigated. The proportion of variance due to the variables for algorithmic and conceptual problem solving ability was studied by a multiple regression analysis. The results indicated that, among the cognitive variables, the logical thinking ability significantly predicted the algorithmic problem solving ability, and the learning strategy was the best predictor of conceptual problem solving ability although not significant. Among the affective variables studied, the self-concept of alility was the significant predictor of both algorithmic and conceptual problem solving abilities. The seif-efficacy was significantly correlated with conceptual problem solving ability, but it had no predictive power.

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A Study on Application of Teaching-Learning Program based on Constructivist Views for Mathematically gifted Students in Primary School (초등 영재 교육에서의 구성주의 교수.학습 모형 적용 연구 - 알고리즘 문제를 중심으로 -)

  • Choi, Keun-Bae;Kim, Hong-Seon
    • Communications of Mathematical Education
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    • v.21 no.2 s.30
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    • pp.153-176
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    • 2007
  • The purpose of this paper is to analyze teaching-learning program which can be applied to mathematically gifted students in primary school, Our program is based on constructivist views on teaching and learning of mathematics. Mainly, we study the algorithmic thinking of mathematically gifted students in primary school in connection with the network problems; Eulerian graph problem, the minimum connector problem, and the shortest path problem, The above 3-subjects are not familiar with primary school mathematics, so that we adapt teaching-learning model based on the social constructivism. To achieve the purpose of this study, seventeen students in primary school participated in the study, and video type(observation) and student's mathematical note were used for collecting data while the students studied. The results of our study were summarized as follows: First, network problems based on teaching-learning model of constructivist views help students learn the algorithmic thinking. Second, the teaching-learning model based on constructivist views gives an opportunity of various mathematical thinking experience. Finally, the teaching-learning model based on constructivist views needs more the ability of teacher's research and the time of teaching for students than an ordinary teaching-learning model.

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Development of Algorithm Design Worksheets using Algorithmic Thinking-based Problem Model in Programming Education for Elementary School Students (초등학생의 프로그래밍 학습을 위한 알고리즘적 사고 문제 모델 기반의 활동지 개발 및 적용)

  • Kim, Yongcheon;Choi, Jiyoung;Kwon, Daiyoung;Lee, Wongyu
    • Journal of The Korean Association of Information Education
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    • v.17 no.3
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    • pp.233-242
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    • 2013
  • "Problem-solving methods and procedures" sections in the 2009 revised informatics curriculum emphasized active use of algorithmic thinking to solve problems. And it is proposed to solve the various problems of real life using programming language for the implementation of the algorithm. Recently, various Educational Programming Language has been developed for elementary programming activity and many researches showed that students' cognitive burden was reduced in learning programming language with Educational Programming Languages. However implementation of the algorithm is difficult for novice programmer. For the reason, effective way is required for elementary students to connect design of the algorithm and implementation of the algorithm. Therefore, in this study propose the algorithm design worksheets that it is possible to create an algorithm to describe the content needed to implementation in programming education. And this study proved the effect of the algorithm design learning tools through experiment.