• Journal of the Korea Society of Computer and Information
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• v.17 no.11
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• pp.53-61
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• 2012

Kodu made by MS is a new 3D visual programming language made specifically for creating games. This language is based on creativity, problem-solving methods, and storytelling. So, it is very suitable for game programming education for kids. In this paper, we designed learning method to develop games based on elementary school students' creative thinking. The instruction was given to 27 6-grade elementary school students in 30 hours. And we applied the learning method in class. Also, we analyzed the changes in the learners' creative thinking and the learning effects of game programming.

• Journal of Digital Contents Society
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• v.18 no.7
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• pp.1313-1321
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• 2017

In the future society where ICT-based digital convergence creates new value, collaborative skills among experts in various fields and SW based problem solving ability is more emphasized. Non-SW specialists are required to have SW based communication skills to effectively collaborate with SW experts to solve their problems. Therefore, SW programming curriculum for non-major college students should be different from the existing programming education for SW-majors aiming at a high level of coding ability. It is also known that diagram-based visual representation is helpful for productive communication and collaboration. In this study, we defined the SW education objectives for the non-majors as cultivating the visual programming ability for SW based problem solving. In order to accomplish this, we explored SW programming curriculum and content development model for non-majors focusing on visual representation of SW solutions. The results of this paper will help to provide appropriate SW learning model for non-majors and to cultivate practical SW capabilities.

• The Journal of Korean Association of Computer Education
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• v.15 no.2
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• pp.1-8
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• 2012

General form of the programing education is finding and realizing algorithm to solve problems faster and more efficiently. In other words, it is based on convergent thinking. However, the programming education must have different characteristics to education targets. For elementary school students, it is needed to provide various experience-centered investigation environments. They should learn how to find the most efficient problem solving method by themselves. This study had adopted divergent thinking strategy where divergent thinking and convergent thinking can be repeated at the same time to suit a programming education with great importance of convergent thinking to elementary school leaners, and analyzed its effects. This study was applied to 5th graders, and 12 times of experimental measure classes were conducted by dividing them into the control group that conducted general programming class and the experimental group that conducted a programming class including divergent thinking of CPS model. As a result, CPS model had significant effect on the subordinate elements of creative problem solving skills, self-assurance, independence, and divergent thinking.

• Journal of the Korea Society of Computer and Information
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• v.14 no.2
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• pp.27-35
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• 2009

Integer programming is a very effective technique for searching optimal solution of combinatorial optimization problems. However, its applicability is limited to linear models. In this paper, I propose an effective method for solving a nonlinear optimization problem by integrating the powerful search performance of integer programming and the flexibility of neighborhood search algorithms. In the first phase, integer programming is executed with subproblem which can be represented as a linear form from the given problem. In the second phase, a neighborhood search algorithm is executed with the whole problem by taking the result of the first phase as the initial solution. Through the experimental results using a nonlinear maximal covering problem, I confirmed that such a simple integration method can produce far better solutions than a neighborhood search algorithm alone. It is estimated that the success is primarily due to the powerful performance of integer programming.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.415-422
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• 2014

This paper presents a new approach to solve the multi area unit commitment problem (MAUCP) using an evolutionary programming based particle swarm optimization (EPPSO) method. The objective of this paper is to determine the optimal or near optimal commitment schedule for generating units located in multiple areas that are interconnected via tie lines. The evolutionary programming based particle swarm optimization method is used to solve multi area unit commitment problem, allocated generation for each area and find the operating cost of generation for each hour. Joint operation of generation resources can result in significant operational cost savings. Power transfer between the areas through the tie lines depends upon the operating cost of generation at each hour and tie line transfer limits. Case study of four areas with different load pattern each containing 7 units (NTPS) and 26 units connected via tie lines have been taken for analysis. Numerical results showed comparing the operating cost using evolutionary programming-based particle swarm optimization method with conventional dynamic programming (DP), evolutionary programming (EP), and particle swarm optimization (PSO) method. Experimental results show that the application of this evolutionary programming based particle swarm optimization method has the potential to solve multi area unit commitment problem with lesser computation time.

• 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 Korea Multimedia Society
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• v.23 no.9
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• pp.1191-1200
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• 2020

In this paper, we proposed DEVS based programming education model that based on the cognitive information processing theory, not a grammatical programming education, and studied effectiveness analysis using computer thinking patterns. By creating a small range of patterns in the grammar which underlies the programming language and solving various examples through combinations, this paper shows an education method to develop problem-solving skills based on algorithmic thinking. The purpose of this study is to facilitate non-majors learn programming languages and understand patterned program structures when writing programs by patterning of control statements which the most important in learning programming.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.617-620
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• 2000

In this paper, we show an application of constraint logic programming to the operation scheduling on machines in a job shop. Constraint logic programming is a new genre of programming technique combining the declarative aspect of logic programming with the efficiency of constraint manipulation and solving mechanisms. Due to the latter feature, combinatorial search problems like scheduling may be resolved efficiently. In this study, the jobs that consist of a set of related operations are supposed to be constrained by precedence and resource availability. We also explore how the constraint solving mechanisms can be defined over a scheduling domain. Thus the scheduling approach presented here has two benefits: the flexibility that can be expected from an artificial intelligence tool by simplifying greatly the problem; and the efficiency that stems from the capability of constraint logic programming to manipulate constraints to prune the search space in an a priori manner.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.599-607
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• 2006

We propose a simple new analytic method for solving a fuzzy goal programming (FGP) problem with general membership functions of fuzzy goals and re-examine a previously defined method for dealing with fuzzy weights for each of the goals. Several illustrative examples are given.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.38
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• pp.131-138
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• 1996

In real world, the organization has multiple objects. Inorder to solve the multiple objects, we present the goal programming for solving project selection problem we also developed expert system which is focused on function of analysis. User which doesn't have knowledge of goal programming can solve the project selection problem and get a result of analysis.