• Journal of The Korean Association of Information Education
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• v.22 no.3
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• pp.357-366
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• 2018

The Code Block Based Educational Programming Language(EPL) is the mainstream tool for software education for elementary students. However, Code Block Based EPL has limitations in scalability, even though there are many advantages as an introductory tool for software education. In this study, we searched the approach of SW education using Python, which is a text-based programming language actively used in real industrial field. We developed a learning program and model using Python and applied it to the sixth grade elementary school students for 10 hours. As a result, we found that the robot-based Python learning model had a significant effect on improving students' thinking skills and confirmed the applicability of text-based programming language to elementary school students.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.07a
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• pp.287-288
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• 2013

본 논문에서는 스마트폰의 확산으로 각광받고 있는 안드로이드 앱을 구현하기 위해 앱 인벤터라는 비주얼 프로그래밍 툴을 활용하는 법을 제안한다. 스마트폰 앱을 만드는 과정에서 컴퓨터 전공 초보 학생들이 느끼는 프로그래밍 언어 문법의 어려움을 최대한 덜어주고 문제해결능력과 논리 교육을 우선시함으로써 프로그래밍에 대한 재미와 흥미를 느끼게 해준다. 이로 인해 학생들의 중도탈락을 예방하고 전공 취업률을 높이는 효과를 기대할 수가 있다. 본 논문에서는 앱 인벤터를 통해 학생들이 구현한 간단한 예제를 살펴보고 교육적 효과와 활용 방안을 제안한다.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.777-782
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• 2020

As the demand for the talented with computing thinking and programming skills increases the importance of coding education is increasing. Although various coding instructor training programs have been implemented nationwide, little research has been conducted analyzing the current status and contents of coding instructor training programs. Therefore, this thesis presents the design, development process and managing strategies of the 'Coding Instructor Training Courses for 4C Talent Development'. The training program consists of introductory courses and practical coding courses. In the introductory courses, learners acquires the basic knowledge required of coding instructors, and then proceeds to the practical courses to systematically learn the pedagogical knowledge and skills required to educate learners from kindergarten through high school. The case study introduced in this paper is expected to provide useful information to the educators planning and managing the coding instructor training program in the future.

• Journal of Internet Computing and Services
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• v.11 no.4
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• pp.159-173
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• 2010

It is difficult for us to teach the introduction course of programming to beginners just starting their college life. What is particularly hard to do is to provide them with learning motivation so that the freshmen can be easily and rapidly adapted to programming work and to enhance their will to learn. In this paper, we suggest a method to apply LEGO Mindstorms robot to the introduction course of programming in purpose to allow programming beginners to be motivated and have higher will to learn so that they can receive programming education easily and joyfully. This paper attempts to find reasonable methods for improvement which can help programming beginners to be motivated and encouraged to learn in the course of C programming education and can facilitate learning effects as well, and conducts education using LEGO Mindstorms robot as a way to solve problems like students' low interest or will to learn. According to the result of providing the freshmen with the introduction course of C programming to which the suggested method was applied, it was found that their academic achievement in programming education enhanced through their increased motivation and will to learn programming. This result shows that students' interest, motivation, and will to learn the subject are statistically significant improvement through the course that employs LEGO Mindstorms robot.

• 대한공업교육학회지
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• v.33 no.2
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• pp.120-136
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• 2008

Using the tangible programming tools, which combines physical objects (e.g. robot) and educational programming language, may help to encourage learners' creative thinking as well as to enhance problem solving ability. That is, learners can have opportunities to simulate problem solving processes through the physical objects, such as robots. Therefore, they can minimize an fixation about problem solving process. These experience is effective to induce creative thinking that is useful to find new solutions and change environment actively. Therefore, we developed a robot based programming teaching and learning curriculum and implemented it in college level introductory programming courses. The result shows that the robot based programming learning has a positive effect in all three factors of learners' creative problem solving potential, especially in a cognitive factor. The cognitive factor includes general problem solving abilities as well as factors that explain creativity, such as divergent thinking, problem recognition, problem representation. These result means that the developed robot based programming teaching and learning curriculum give positive effect to creative problem solving abilities.

• Journal of KIISE
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• v.44 no.9
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• pp.986-991
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• 2017

In this paper, we present a method for synthesizing imperative programs from input-output examples. Given (1) a set of input-output examples, (2) an incomplete program, and (3) variables and integer constants to be used, the synthesizer outputs a complete program that satisfies all of the given examples. The basic synthesis algorithm enumerates all possible candidate programs until the solution program is found (enumerative search). However, it is too slow for practical use due to the huge search space. To accelerate the search speed, our approach uses code optimization and avoids unnecessary search for the programs that are syntactically different but semantically equivalent. We have evaluated our synthesis algorithm on 20 introductory programming problems, and the results show that our method improves the speed of the basic algorithm by 10x on average.

• Asia Marketing Journal
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• v.16 no.1
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• pp.35-69
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• 2014

The impact of competition on pricing has been studied in the context of counterfactual merger analyses where expected optimal prices in a hypothetical monopoly are compared with observed prices in an oligopolistic market. Such analyses would typically assume static decision making by consumers and firms and thus have been applied mostly to data obtained from consumer packed goods such as cereal and soft drinks. However such static modeling approach is not suitable when decision makers are forward looking. When it comes to the markets for durable products with indirect network effects, consumer purchase decisions and firm pricing decisions are inherently dynamic as they take into account future states when making purchase and pricing decisions. Researchers need to take into account the dynamic aspects of decision making both in the consumer side and in the supplier side for such markets. Firms in a two-sided market typically subsidize one side of the market to exploit the indirect network effect. Such pricing behaviors would be more prevalent in competitive markets where firms would try to win over the battle for standard. While such qualitative expectation on the relationship between pricing behaviors and competitive structures could be easily formed, little empirical studies have measured the extent to which the distinct pricing structure in two-sided markets depends on the competitive structure of the market. This paper develops an empirical model to measure the impact of competition on optimal pricing of durable products under indirect network effects. In order to measure the impact of exogenously determined competition among firms on pricing, we compare the equilibrium prices in the observed oligopoly market to those in a hypothetical monopoly market. In computing the equilibrium prices, we account for the forward looking behaviors of consumers and supplier. We first estimate a demand function that accounts for consumers' forward-looking behaviors and indirect network effects. And then, for the supply side, the pricing equation is obtained as an outcome of the Markov Perfect Nash Equilibrium in pricing. In doing so, we utilize numerical dynamic programming techniques. We apply our model to a data set obtained from the U.S. video game console market. The video game console market is considered a prototypical case of two-sided markets in which the platform typically subsidizes one side of market to expand the installed base anticipating larger revenues in the other side of market resulting from the expanded installed base. The data consist of monthly observations of price, hardware unit sales and the number of compatible software titles for Sony PlayStation and Nintendo 64 from September 1996 to August 2002. Sony PlayStation was released to the market a year before Nintendo 64 was launched. We compute the expected equilibrium price path for Nintendo 64 and Playstation for both oligopoly and for monopoly. Our analysis reveals that the price level differs significantly between two competition structures. The merged monopoly is expected to set prices higher by 14.8% for Sony PlayStation and 21.8% for Nintendo 64 on average than the independent firms in an oligopoly would do. And such removal of competition would result in a reduction in consumer value by 43.1%. Higher prices are expected for the hypothetical monopoly because the merged firm does not need to engage in the battle for industry standard. This result is attributed to the distinct property of a two-sided market that competing firms tend to set low prices particularly at the initial period to attract consumers at the introductory stage and to reinforce their own networks and eventually finally to dominate the market.