• The Journal of Industrial Distribution & Business
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• v.10 no.11
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• pp.71-80
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• 2019

Purpose: The purpose of this study is to design the curriculum of Basic College Software Programming to develop creative and logical-thinking. This course is guided by algorithmic thinking and logical thinking that can be solved by computing for problem-solving, and it helps to develop by software through basic programming education. Through the stage of problem analysis, abstraction, algorithm, data structure, and algorithm implementation, the curriculum is designed to help learners experience algorithm problem-solving in various areas to develop diffusion thinking. For Learners aim to achieve the balanced development of divergent and convergent-thinking needed in their creative problem-solving skills. Research design, data and methodology: This study is to design a basic software education for improving algorithm-thinking for non-major. The curriculum designed in this paper is necessary to non-majors students who have completed the 'Creative Thinking and Coding Course' Design Thinking based are targeted. For this, contents were extracted through advanced research analysis at home and abroad, and experts in computer education, computer engineering, SW education, and education were surveyed in the form of quasi-openness. Results: In this study, based on ADD Thinking's algorithm thinking, we divided the unit college majors into five groups so that students of each major could accomplish the goal of "the ability to internalize their own ideas into computing," and extracted and designed different content areas, content elements and sub-components from each group. Through three expert surveys, we established a strategy for characterization by demand analysis and major/textbook category and verified the appropriateness of the design direction to ensure that the subjects and contents of the curriculum are appropriate for each family in order to improve algorithm-thinking. Conclusions: This study helps develop software by enhancing the ability of students who practice various subjects and exercises to explore creative expressions in various areas, such as 'how to think like a computer' that can implement and execute their ideas in computing. And it helps increase the ability to think logical and algorithmic computing based on creative solutions, improving problem-solving ability based on computing thinking and fundamental understanding of computer coding and development of logical thinking ability through programming.

• Journal of The Korean Association of Information Education
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• v.15 no.1
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• pp.119-127
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• 2011

We selected algorithm learning subjects and developed the play-based algorithm learning program for elementary school students. In addition, we analyzed a positive effect of improve on logical thinking by the field application. We found that the developed learning program was helpful in growing logical thinking skills. It means that the play-based algorithm learning program helps learners to improve on logical thinking.

• Journal of The Korean Association of Information Education
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• v.14 no.4
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• pp.555-560
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• 2010

The purpose of this study is to investigate the effect of learning algorithm which uses real-life examples including the concept of algorithm on the logical thinking of elementary school students. For this purpose, the experiment was performed by pre-GALT test, a case selection of algorithm which can be taught in real-life, experiment treatment after completing teaching plan, post-GALT test, and paired sample t-test on the results of pre and post GALT in order. As a result, changes in the degree of logical thinking ability and in five sub-regions(conservative logic, proportional logic, combinatorial logic, probabilistic logic, controlling variables) composing of logical thinking obtained statistically significant results in .05 significance level but changes in the correlational logic couldn't obtain the significant results.

• Journal of The Korean Association of Information Education
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• v.26 no.5
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• pp.295-305
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• 2022

In the modern artificial intelligence society, the goal of education is to cultivate convergent talents who can adapt well to and lead the artificial intelligence society. The core competency required of convergent future talents is to be able to understand and create software well. In this respect, algorithmic education is very important. Therefore, in this study, an algorithm education program was developed to improve convergent thinking ability. The effectiveness was verified through the paired samples t-test by conducting a pre-post test of convergent thinking ability, and it was found that students' convergent thinking ability was significantly improved in the areas of algorithm knowledge and function.

• The Mathematical Education
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• v.58 no.2
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• pp.319-335
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• 2019

In this paper, we examine the effectiveness of calculation according to automation, which is one of Computational Thinking, by coding the conceptual process into Python language, focusing on the concept of divisibility in elementary school textbooks. The educational implications of these considerations are as follows. First, it is possible to make a field of learning that can revise the new mathematical concept through the opportunity to reinterpret the Conceptual Thinking learned in school mathematics from the perspective of Computational Thinking. Second, from the analysis of college students, it can be seen that many students do not have mathematical concepts in terms of efficiency of computation related to the divisibility. This phenomenon is a characteristic of the mathematics curriculum that emphasizes concepts. Therefore, it is necessary to study new mathematical concepts when considering the aspect of utilization. Third, all algorithms related to the concept of divisibility covered in elementary mathematics textbooks can be found to contain the notion of iteration in terms of automation, but little recursive activity can be found. Considering that recursive thinking is frequently used with repetitive thinking in terms of automation (in Computational Thinking), it is necessary to consider low level recursive activities at elementary school. Finally, it is necessary to think about mathematical Conceptual Thinking from the point of view of Computational Thinking, and conversely, to extract mathematical concepts from computer science's Computational Thinking.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.382-395
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• 2017

Learning computational thinking is very important in programming education. Computational thinking refers to the problem solving ability based on the theories of computer science, indicating the importance of algorithm thinking. That is the reason for focusing on promoting creativity and improving the problem solving ability of the students in programming education. This paper commented the elements to consider for teachers when teaching computational thinking to elementary school students with online coding education website 'code.org' that helps beginners have easy programming experiences based on the characteristics of the website, and proposed the appropriate teaching methods.

• Journal of Multimedia Information System
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• v.8 no.3
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• pp.191-196
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• 2021

Computational thinking refers to the process and method of solving everyday problems using computers. When teaching a computational thinking class for computer majors and non-majors at university, the easiest example to deliver the concept of computational thinking is sorting. Sorting is the concept of arranging given data in order. In this work, we have implemented four visualized sorting algorithms that anyone can easily use. In particular, it helps to understand the difference between the algorithms by showing the number of comparisons and exchanges between elements, which are the criteria for evaluating the performance of the sorting algorithm in real time. It was confirmed that the practice of using the sorting visualization app developed in this research contributed to the improvement of students' understanding of computational thinking.

• The Journal of the Korea Contents Association
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• v.14 no.10
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• pp.840-849
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• 2014

The paper shows that algorithm education positively affects algorithmic thinking for elementary students. Experiments are conducted on thirty five sixth graders without prior experience of algorithm. The experimental group is given eleven sessions of lesson for four weeks in which algorithmic solution is sought for graph coloring problems. After four weeks of experiments questionnaires are distributed to the students in order to measure differences in algorithmic interest and algorithmic thinking ability. The following results are obtained: Firstly, it may be observed that algorithm education with graph coloring may be effective in reinforcing students' interest in algorithms. Secondly, the experiment shows that algorithmic thinking ability may be enhanced from participating in graph coloring activities. In conclusion, algorithm education with graph coloring problem helps students develop algorithmic thinking ability as well as cultivate students' interest in algorithmic thinking.

• The Journal of Korean Association of Computer Education
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• v.14 no.2
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• pp.13-22
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• 2011

The importance of algorithm education has been emphasized for creative problem-solving capability. Especially, algorithm teaching materials related with mathematics and science are under development to enhance logical thinking. However, there are not enough teaching-learning models applicable in the field of education. Therefore, this paper proposed a teaching-learning model for effective algorithm education. The teaching-learning model reflects two characteristics : an algorithm learning process is spiral, and algorithm education is based on logical thinking. Furthermore, a survey was conducted for students' satisfaction, and the result was a mixed teaching-learning model with PBL, SDL, and peer tutoring. Based on the proposed model, examples of classes for mathematics and science are suggested to show the feasibility of effective algorithm education.

• Journal of The Korean Association of Information Education
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• v.21 no.3
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• pp.335-342
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• 2017

The artificial intelligence, robot technology, Internet of things, and life sciences that create added value while dramatically transforming human life have been highlighted in the fourth industrial revolution, the next industrial revolution. In order to adapt to the 4th industry, it is necessary to educate students to develop fusion thinking and computing thinking ability. Therefore, in this study, we developed a digital Yut Playing system based on physical computing, reflecting STEAM and decomposition, pattern recognition, abstraction, and algorithm design, which are components of computing thinking. By experiencing the developed system and applying it to education, it raised interest and interest in programming education and improved programming lesson for fusion thinking and computing thinking ability.