• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.2
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• pp.631-638
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• 2017

In the age of the Fourth Industrial Revolution, lifestyle and industrial structures are faced with evolution from IT-based automation to the intelligent stage, demanding talents with software capabilities in various fields. Reflecting these demands, the government has enhanced basic software education for non-majors in elementary and secondary schools as well as universities. In this study, the software convergence education of Non-Majors is proposed to improve the general problem solving ability based on computational thinking and the software convergence ability in the field of their own by developing robot activity. The subjects of this study were 91 students, who were composed of various majors. The class was designed with computing thinking, convergence elements, and creative robot activity. The study was conducted for 13 weeks. To examine the effects of software convergence education through the creative robot activity, this study observed changes in the students' learning outcomes, satisfaction with creative robot activities, and perceptions of other disciplines after class based on pre-diagnosis surveys. The survey asked 12 questions including an understanding of the learning contents, overall satisfaction with multidisciplinary collaborative learning, understanding of other disciplines, and self-evaluation of problem solving ability through creative robot activities, which were compared with that before the class. They answered that their ability was improved.

• 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 Fisheries and Marine Sciences Education
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• v.24 no.4
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• pp.528-542
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• 2012

In this study, we designed and applied the learning program of various algorithms about computer science, which were based on computational thinking, to prospective elementary school teachers who were non-majors of this field. While they were learning, they could understand two fundamental functions of computational thinking: abstraction and automation. This learning program made them change their perceptions about computer science positively. They had been interested in learning algorithms and computer science itself, and they felt confident about teaching it.

• Journal of Practical Engineering Education
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• v.12 no.2
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• pp.265-273
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• 2020

In this paper, to design a basic data science practice curriculum as a liberal arts subject for non-majors, we proposed an educational method using an Excel(spreadsheet) data analysis tool. Tools for data collection, data processing, and data analysis include Excel, R, Python, and Structured Query Language (SQL). When it comes to practicing data science, R, Python and SQL need to understand programming languages and data structures together. On the other hand, the Excel tool is a data analysis tool familiar to the general public, and it does not have the burden of learning a programming language. And if you practice basic data science practice with Excel, you have the advantage of being able to concentrate on acquiring data science content. In this paper, a basic data science practice curriculum for one semester and weekly Excel practice contents were proposed. And, to demonstrate the substance of the educational content, examples of Linear Regression Analysis were presented using Excel data analysis tools.

• Proceedings of The KACE
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• 2017.08a
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• pp.161-164
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• 2017

컴퓨터 사고를 이해하고 컴퓨터와 소통하는 것을 목적으로 한다. 본 연구의 목적은 컴퓨터 비전공자 대상으로 하는 강의의 목적성과 실효성을 규명하고, 나아가 학생과 강의자가 수업의 목표점의 접점을 찾아 나가는데 있다. 강의 대상은 컴퓨터 비전공자 학생 중 인문, 미술, 음악, 자연 계열의 학생들로서 그들이 현시점에서 이수한 교과과목 중 수학의 비중이 상대적으로 낮은 군에 속한다. 따라서 그들이 현실적으로 컴퓨터와 소통하기 위해 어떤 교육의 패러다임을 적용해야 하는가가 중요하다. 본 연구에서는 텍스트 코딩이 가능한 파이썬을 컴퓨터 비전공생에게 학습시키는 이유와 목적에 대해 밝히고 학습의 실효성에 대해 논의한다.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.213-222
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• 2020

Recently, as awareness of the need for software education has spread worldwide, the government of Korea has led compulsory software education also. Basic software education in universities has been stabilized through various trials and efforts. However, due to software classes are mandatory, students not only could not have motivation for learning but also have treated programming course as a difficult subject. In this paper, two programming classes, which were designed and managed as a problem-oriented programming class for the purpose of cultivating computational thinking for the non-computer science students, are compared using the lecture assessment results. As a result, in the case of expanding the use of the problem as a grammatical explanation aid and expanding the ratio of major-friendly problems, the student's responses were concentrated on higher scores and the response average improved by about 7%. It means that the level of difficulty experienced by learners is lowered.

• Proceedings of The KACE
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• 2017.08a
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• pp.235-239
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• 2017

학습자는 교육의 3요소인 교육자, 학습자, 교육내용의 하나로 학습자 특성과 이가 학업성취에 미치는 영향을 이해하는 것이 중요하다. 컴퓨터 비전공자를 대상으로 하는 컴퓨팅 교육이 점점 활발해지고 있다. 비전공자 컴퓨팅 교육이라는 맥락에서 학습자 특성과 학업성취의 관계를 이해할 필요가 있다. 본 연구는 비전공자 컴퓨팅 교육에서 학습자 특성과 학업성취의 관계를 실증적으로 이해하기 위해 실행되었다. 학습자 특성을 이전경험/사전지식, 인지적 요인, 심리적 요인의 3가지로 분류하였고, 연구대상을 3그룹으로 설정, 다양한 하위 요소 데이터를 수집하였다. 그 결과, 대상 1의 경우 학습스타일(순차적: 부적상관, 통합적: 정적상관), 대상 2는 자기 효능감(사후), 대상 3은 수학 사전지식, 컴퓨팅과 전공의 연계성 인식, 정보적 사고에 대한 인식이 학업성취와 유의미한 상관관계가 있었다. 하지만 상관성이 모두 0.5이하로 크지 않고, 자기 효능감과 전공 연계성 인식의 경우 대상에 따라 결과가 상이하였다. 향후 연구에서 다루지 않은 변수에 대한 연구와 상관관계가 밝혀진 변수만을 대상으로 인과성을 확인하는 연구가 필요하다. 또한 현상학적 관점으로 학습자 특성을 고찰할 필요가 있다.

• Journal of the Korea Convergence Society
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• v.9 no.3
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• pp.73-78
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• 2018

Modern society has evolved to such an extent that computing technology has become an integral part of various fields, creating new and superior value to society. Education on computer literacy, including the ability to design and build software, is now becoming a universal education that must be acquired by everyone, regardless of the field of study. Many universities are imparting software education to students to improve their problem-solving ability, including to students who are not majoring in computers. However, software education contains courses that are meant for computer majors and many students encounter difficulty in learning the grammar of programming language. To solve this problem, this paper analyzes the research outcomes of the existing software education model and proposes a Python-based software education model for students who are not majoring in computer science. Along with a Python-based software education model, this paper proposed a curriculum that can be applied during one semester, including learning procedures, and teaching strategies. This curriculum was applied to a liberal arts class and a meaningful result was derived. If the proposed software education model is applied, the students will be interested in the computer literacy class and improve their computational thinking and problem-solving ability.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.393-400
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• 2021

Data science is a scientific discipline that defines problems while finding meaningful information from collected data to solve problems. Along with artificial intelligence technology, the field of data utilization is gradually expanding, and awareness of the importance of data science education is also increasing. Despite the rapid growth of the domestic data industry market, it has recently been predicted that the shortfall of data experts will reach 31.4% within the next 5 years according to an analysis of the current status of the data industry by the Korea Data Agency. In the field of elementary education, various studies have been conducted to introduce data science in order to improve students' computational thinking and creativity. This paper proposed the contents of data science lectures developed for the purpose of educating elementary school teachers, who are mostly non-majors in the computer field. The developed contents were applied to a group of elementary school teachers attending graduate school for artificial intelligence convergence education. Points for improvement were derived by identifying the contents that were difficult for learners to understand and analyzing the causes of difficulty.

• Journal of The Korean Association of Information Education
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• v.25 no.6
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• pp.899-906
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• 2021

Data science is a discipline comprised of the academic fields of statistics, computer science, information technology, and domain knowledge. It analyzes data and derives meaningful results using complex technologies. Data science, along with artificial intelligence, is a core technology of the 4th industrial revolution; consequently, universities and companies worldwide are actively developing programs to develop data scientists who require high levels of expertise. In line with this undertaking, the field of elementary education has recognized the importance of data science education and so various studies have been conducted to develop curricula designed to help students understand how to use data. This paper proposes a curriculum for the purpose of educating elementary school teachers who are mostly non-majors in the computer field about data science. Satisfaction analysis was conducted based on questionnaires collected from students to analyze the effectiveness of the data science education proposed in this paper.