• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.141-148
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• 2021

The mainstream tool for software education for elementary students is Educational Programming Language. It is essential for upper graders to advance from EPL to text based programming language. However, many students experience difficulty in adopting to this change since Python is run in English. Python is an actively used TPL. This study focuses on developing an education program to facilitate learning Python for Korean speaking students. We have extracted the necessary reserved words needed for data analysis in Python. Then we replaced the extracted words into Korean terms that could be understood in elementary level. The replaced terms were matched on one-to-one correspondence with reserved words used in Python. This devised program would assist students in experiencing data analysis with Python. We expect that this education program will be applied effectively as a basic resource to learn TPL.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.247-253
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• 2021

There are various programming errors that occur in the course of programming practice for beginners in computer programming. At this time, since it is difficult for learners to recognize errors by themselves, they correct program errors through the instructor's feedback. However, as students learn programming techniques in an online learning environment due to the COVID-19 pandemic, there is a limit to interaction between the students and the instructor in comparison with offline classes, so it is necessary for learners to develop their own ability to solve programming errors by themselves. Therefore, in this study, error cases in online programming classes using the Python language are analyzed and an online programming education method that can improve learners' ability to correct programming errors is proposed based on the analysis results.

• 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.

• Journal of Practical Engineering Education
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• v.14 no.1
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• pp.75-83
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• 2022

Most of the courses that teach the Python programming language are liberal arts courses that all students in general universities must complete. Through this, non-major students who have learned the basic programming process based on computational thinking are strengthening their convergence capabilities to apply SW in various major fields. In the previous research results, various evaluation methods for understanding the concept of computational thinking and writing code were suggested. However, there are no examples of evaluation problems, so it is difficult to apply them in actual course operation. Accordingly, in this paper, a Python basic programming curriculum that can be applied as a liberal arts subject for non-majors is proposed according to the ADDIE model. In addition, the case of evaluation problems for each Python element according to the proposed detailed curriculum was divided into 1st and 2nd phases and suggested. Finally, the validity of the proposed evaluation problem was analyzed based on the evaluation scores of non-major students calculated in the course to which this evaluation problem case was applied. It was confirmed that the proposed evaluation problem case was applied as a real-time online non-face-to-face evaluation method to effectively evaluate the programming competency of non-major students.

• International Journal of Contents
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• v.5 no.2
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• pp.6-15
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• 2009

Recently many different programming languages have emerged for the development of bioinformatics applications. In addition to the traditional languages, languages from open source projects such as BioPerl, BioPython, and BioJava have become popular because they provide special tools for biological data processing and are easy to use. However, it is not well-studied which of these programming languages will be most suitable for a given bioinformatics task and which factors should be considered in choosing a language for a project. Like many other application projects, bioinformatics projects also require various types of tasks. Accordingly, it will be a challenge to characterize all the aspects of a project in order to choose a language. However, most projects require some common and primitive tasks such as file I/O, text processing, and basic computation for counting, translation, statistics, etc. This paper presents the benchmarking results of six popular languages, Perl, BioPerl, Python, BioPython, Java, and BioJava, for several common and simple bioinformatics tasks. The experimental results of each language are compared through quantitative evaluation metrics such as execution time, memory usage, and size of the source code. Other qualitative factors, including writeability, readability, portability, scalability, and maintainability, that affect the success of a project are also discussed. The results of this research can be useful for developers in choosing an appropriate language for the development of bioinformatics applications.

• Journal of The Korean Association of Information Education
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• v.24 no.1
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• pp.117-129
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• 2020

The purpose of this paper is to explore ways to assess computational thinking from a formative perspective and to design a process for assessing programming learning using Python. Therefore, this study explored the computational thinking domain and analyzed research related to assessment design. Also, this study identified the areas of Python programming learning that beginners learn and the areas of computational thinking ability that can be obtained through Python learning. Through this, we designed an assessment method that provides feedback by analyzing syntax corresponding to computational thinking ability. Besides, self-assessment is possible through reflective thinking by using the flow-chart and pseudo-code to express ideas, and peer feedback is designed through code sharing and communication using community.

• The Pure and Applied Mathematics
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• v.29 no.1
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• pp.93-102
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• 2022

The impact of programming languages in the research sector has helped lot of researchers to broaden their view and extend their work without any limitation. More importantly, even the complex problems can be solved in no matter of time while converting them into a programming language. This convenience provides upper hand for the researchers as it places them in a comfort zone where they can work without much stress. With this context, we have converted the research problems in Topology into programming language with the help of Python. In this paper, we have developed a Python program to find the weaker form of closed sets namely alpha closed set, semi closed set, pre closed set, beta closed set and regular closed set.

• Journal of The Korean Association of Information Education
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• v.25 no.4
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• pp.603-610
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• 2021

As part of recent SW education methods, entry sites have been used in all practical textbooks in elementary schools. However, they are all learning block-type programming languages, making it difficult to produce programs that can be used in everyday life. This study is a study on the effects of learning programming using entry python on logical thinking ability and programming interest in elementary school students. Logical thinking ability and programming interest tests were conducted before and after the 8th class. Before and after classes, logical thinking ability score rose from an average of 6.6 to 9.4 and programming interests score also rose from an average of 46.7 to 59.1. This results in programming learning using Entry Python is significant for enhancing the logical thinking ability and programming interest of elementary school students.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.336-344
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• 2019

The Ministry of Education (2015) announced the "2015 Revised Curriculum for Elementary and Secondary Schools" and announced that SW (Software) training for elementary and junior high school students to develop Computational Thinking will be gradually introduced from 2018. In addition, 'problem solving' and 'programming' have become important areas. Furthermore, the ability to analyze and utilize big data is becoming more emphasized. We developed and applied the statistical - Python programming convergence curriculum based on the idea that convergence education combining information and mathematics, programming and statistical literacy is needed according to current trends. Before and after the experiment, problem solving ability test and programming / mathematical interest test were conducted and compared with the corresponding sample t-test. According to the analysis results, there were significant differences in the pre- and post-test on problem solving ability, programming interest and mathematical interest at the significance level of 0.05.

• Journal of Korea Multimedia Society
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• v.23 no.2
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• pp.241-246
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• 2020

Hadoop is a framework to process large data sets in a distributed way across clusters of nodes. It has been a popular platform to process big data, but in recent years, other platforms became competitive ones depending on the characteristics of the application. Spark is one of distributed platforms to enable real-time data processing and improve overall processing performance over Hadoop by introducing in-memory processing instead of disk I/O. Whereas Hadoop is designed to work on Java and data analysis is processed using Java API, Spark provides a variety of APIs with Scala, Python, Java and R. In this paper, the goal is to find out whether the APIs of different programming languages af ect the performances in Spark. We chose two popular APIs: Python and Scala. Python is easy to learn and is used in AI domain in a wide range. Scala is a programming language with advantages of parallelism. Our experiment shows much faster processing with Scala API than Python API. For the performance issues on AI-based analysis, further study is needed.