• 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 Engineering Education Research
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• v.22 no.6
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• pp.21-27
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• 2019

In the last few years, interest in computer science education has increased significantly. The curriculum is being revised to introduce computer science. Although interest has focused on coding as the main subject, in fact the computer science includes much more than coding. It engages people in being creative with technology as well as understanding the fundamental principles of computer science. Therefore, it is important to consider the curriculum to provide a foundation by teaching and learning computer science. The curriculum is required the development of courses to teach computer science for non-majors in general education. To think like a computer scientist on the knowledge of computer science is computational thinking. In order to maximize the effectiveness of teaching and learning for computational thinking, various teaching methods and supplementary learning materials, and activities should be developed and provided.

• 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.

• Journal of Convergence for Information Technology
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• v.11 no.10
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• pp.151-158
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• 2021

The purpose of this paper is to examine the concept of computational thinking in an easy-to-understand way for non-computer majors. First, It is necessary to expand from the problem-solving perspective to the perspective of problem discovery and creation ability, and establish it as a thinking ability that can cultivate human-like thinking, that is, creative thinking. Second, the concept of computational thinking can be viewed not only in the cognitive aspect but also in the emotional motive and attitude aspect. Third, systematic design of teaching methods is needed based on the expansion of the concept to computational thinking that helps learners to improve their reflective ability. It is expected that the results of this study will serve as basic research for various attempts in terms of the purpose and teaching method of computational thinking education in the future.

• 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.

• 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.319-320
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• 2018

4차 산업혁명 시대에 걸맞은 미래 인재양성을 위해 Computational Thinking (CT) 향상을 위한 교육에 대한 관심이 높아지고 있다. 더불어 비전공자 학생들을 대상으로 하는 컴퓨팅 교육이 확산되어 진행되고 있다. 그러나 많은 비전공 학습자들이 CT 교육 학습 과정에 어려움을 느끼고 있다. 이에 본 논문에서는 CT 교육 학습 과정에 도구를 활용한 학습 방법으로 이를 해결하고자 하였다.

• The Journal of the Convergence on Culture Technology
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• v.6 no.1
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• pp.185-190
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• 2020

The programming education of non-computer major undergraduates aims to increase the their problem-solving and coding skills so that the skills can be applied to various fields and motivate them to continuously study computer or programming. However, it difficult for them to recognize the necessity of programming knowledge and to find out how it can be used in their major. Therefore, the professor needs to give students a full explanation of their roles to play. In this paper, we revisit the necessity of programming knowledge for non-computer major undergraduates by looking at the convergence cases of ICT technology and the humanities and social arts fields. And we propose an instruction direction of programming learning for them.

• Journal of Practical Engineering Education
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• v.13 no.2
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• pp.233-242
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• 2021

In this paper, as a liberal arts course for non-majors, we proposed a supervised learning artificial neural network parameter optimization method and a basic education method for activation function to design a basic artificial neural network subject curriculum. For this, a method of finding a parameter optimization solution in a spreadsheet without programming was applied. Through this training method, you can focus on the basic principles of artificial neural network operation and implementation. And, it is possible to increase the interest and educational effect of non-majors through the visualized data of the spreadsheet. The proposed contents consisted of artificial neurons with sigmoid and ReLU activation functions, supervised learning data generation, supervised learning artificial neural network configuration and parameter optimization, supervised learning artificial neural network implementation and performance analysis using spreadsheets, and education satisfaction analysis. In this paper, considering the optimization of negative parameters for the sigmoid neural network and the ReLU neuron artificial neural network, we propose a training method for the four performance analysis results on the parameter optimization of the artificial neural network, and conduct a training satisfaction analysis.

• 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.