• Title/Summary/Keyword: non-computer majors

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A study on basic software education applying a step-by-step blinded programming practice (단계적 블라인드 프로그래밍 실습과정을 적용한 소프트웨어 기초교육에 관한 연구)

  • Jung, Hye-Wuk
    • Journal of Digital Convergence
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    • v.17 no.3
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    • pp.25-33
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    • 2019
  • Recently, universities have been strengthening software basic education to be active in the era of the fourth industrial revolution. Non-majored students need a variety of teaching methods because they have low knowledge of programming or a lack of connectivity with major courses. Therefore, in this paper, a learning model applying the step-by-step blind programming practice based on the Demonstration Modeling Making model was designed and applied to the actual lecture. As a result of analyzing the problem solving ability of the learner, it was confirmed that the learner's self - solving ratio increased as parking progressed. In the following study, it is necessary to analyze the learner's learning results in various aspects and to study effective teaching methods according to the difficulty of the learning contents.

Development of Convolutional Neural Network Basic Practice Cases (합성곱 신경망 기초 실습 사례 개발)

  • Hur, Kyeong
    • Journal of Practical Engineering Education
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    • v.14 no.2
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    • pp.279-285
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    • 2022
  • In this paper, as a liberal arts course for non-majors, we developed a basic practice case for convolutional neural networks, which is essential for designing a basic convolutional neural network course curriculum. The developed practice case focuses on understanding the working principle of the convolutional neural network and uses a spreadsheet to check the entire visualized process. The developed practice case consisted of generating supervised learning method image training data, implementing the input layer, convolution layer (convolutional layer), pooling layer, and output layer sequentially, and testing the performance of the convolutional neural network on new data. By extending the practice cases developed in this paper, the number of images to be recognized can be expanded, or basic practice cases can be made to create a convolutional neural network that increases the compression rate for high-quality images. Therefore, it can be said that the utility of this convolutional neural network basic practice case is high.

Gradient Descent Training Method for Optimizing Data Prediction Models (데이터 예측 모델 최적화를 위한 경사하강법 교육 방법)

  • Hur, Kyeong
    • Journal of Practical Engineering Education
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    • v.14 no.2
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    • pp.305-312
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    • 2022
  • In this paper, we focused on training to create and optimize a basic data prediction model. And we proposed a gradient descent training method of machine learning that is widely used to optimize data prediction models. It visually shows the entire operation process of gradient descent used in the process of optimizing parameter values required for data prediction models by applying the differential method and teaches the effective use of mathematical differentiation in machine learning. In order to visually explain the entire operation process of gradient descent, we implement gradient descent SW in a spreadsheet. In this paper, first, a two-variable gradient descent training method is presented, and the accuracy of the two-variable data prediction model is verified by comparison with the error least squares method. Second, a three-variable gradient descent training method is presented and the accuracy of a three-variable data prediction model is verified. Afterwards, the direction of the optimization practice for gradient descent was presented, and the educational effect of the proposed gradient descent method was analyzed through the results of satisfaction with education for non-majors.

A Case Study of the Curriculum of Data Science for Elementary School Teachers (초등교사 대상의 기초 데이터 과학 교육의 사례 연구)

  • Jo, Junghee
    • 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.

A Study on Development of Basic Data Science Education Contents for Artificial Intelligence Capability (인공지능 기반의 기초 데이터 과학 교육에 관한 연구)

  • Jo, Junghee
    • 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.

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Factors Affecting College Students' Teeth Whitening Preference

  • Seon-Rye Kim
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.10
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    • pp.179-186
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    • 2023
  • This study investigated tooth whitening preferences among college students, evaluating their knowledge, satisfaction, aesthetic criteria, and preferences, while identifying influencing factors. Using a 28-item questionnaire covering general, tooth whitening knowledge, satisfaction, aesthetic criteria, and preference questions, 175 participants surveyed from June 7th to 10th, 2022, underwent analysis. Descriptive statistics, t-tests, analysis of variance, and regression analysis were applied. Results showed tooth whitening knowledge scored 2.90 out of 5 points, satisfaction 2.97, aesthetic criteria 3.59, and preferences 3.28. Tooth whitening knowledge was higher among female and health-related major students, while satisfaction was greater among males, non-health-related majors, and those without cosmetic procedures. Aesthetic criteria were stronger in participants with higher allowances and cosmetic procedures experience. No significant tooth whitening preference differences were found based on general characteristics. Regression analysis revealed significant impact of aesthetic criteria on tooth whitening preferences (β=0.252).

A Study on Coding Education of Non-Computer Majors for IT Convergence Education (IT 융합교육을 위한 비전공자 코딩교육의 발전방안)

  • Pi, Su-Young
    • Journal of Digital Convergence
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    • v.14 no.10
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    • pp.1-8
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    • 2016
  • Coding education is an effective convergence type educational tool. While solving problems and designing programs, students can enhance problem solving ability, logical reasoning ability and creative thinking. Researches on coding education are done primarily for elementary school and middle school students. However, researches on college students are lacking. Today, educating college students about coding is in dire need. Although there are efforts to promote the importance of coding education and make it requirements. People find it difficult to find ways to provide training. There is a need for researches on coding as universal education. Therefore, this research proposed educational training using app inventor based on flipped running in order to effectively promote coding education. This study conducted the survey and the personal interview to measure the effectiveness of coding education. It is hoped that, through coding education, students who do not major in coding could combined their knowledge of their major with coding to improve their problem solving ability to solve various problems based on computing knowledge and approach.

A Study on Customized Software Education method using Flipped Learning in the Digital Age (디지털시대에 플립드 러닝을 활용한 학습자 맞춤형 소프트웨어 교육 방안 연구)

  • Kim, Kyungmi;Kim, Hyunsook
    • Journal of Digital Convergence
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    • v.15 no.7
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    • pp.55-64
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    • 2017
  • The purpose of this study is to identify the difficulties of learners who started programming after entering college and to search an effective software education method as university liber arts for non-science major students. In order to do this, we analyzed the difficulties of learners in Python programming classes composed of students from various majors at H University through questioning and taught them using flipped class model with pre-questions. The questions that students submit are collected online before class every time, the data on the degree of the difficulty of feeling and the understanding of feeling were obtained through the questionnaire. As a result, for learners who are new to programming, the learners should allocate the process of making the problem into a logical abstraction at the beginning of the curriculum before learning the basic concept of computer language, each lesson should be practiced through the bottom-up problems enough to provide a logical understanding before actual coding. In addition, detailed curriculum should be developed according to characteristics of learner's major, contents and conducting level.

A Study on the Verification of Computational Thinking Effectiveness of Understanding-Oriented SW Basic Education Program (이해중심 SW기초교육 프로그램의 컴퓨팅사고 효과성 검증 연구)

  • Oh, Kyung-Sun;Kwon, Jung-In
    • Journal of Digital Convergence
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    • v.17 no.10
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    • pp.23-35
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    • 2019
  • In order to cultivate talented people who have problem solving ability due to computational thinking according to the trend of the fourth industrial revolution, each university is actively promoting software education. This study suggests that understanding-oriented SW curriculum is needed for non-majors students to improve computational thinking. In order to achieve the purpose of the study, this study designed the basic education program based on the understanding of the SW with the backward design model. The SW Basic Education Program was applied to 15 weeks of instruction and conducted three surveys. The positive effects of the understanding-oriented SW basic education on the computational thinking efficacy and the computer perception were verified. In addition, it was found that the understanding-oriented computational thinking and programming education are effective when they are linked to one process. It is expected that understanding-based SW based education, which uses the backward design model, can be applied as one of the efficient ways to improve computational thinking in the education field.

Analysis and Orange Utilization of Training Data and Basic Artificial Neural Network Development Results of Non-majors (비전공자 학부생의 훈련데이터와 기초 인공신경망 개발 결과 분석 및 Orange 활용)

  • Kyeong Hur
    • Journal of Practical Engineering Education
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    • v.15 no.2
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    • pp.381-388
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    • 2023
  • Through artificial neural network education using spreadsheets, non-major undergraduate students can understand the operation principle of artificial neural networks and develop their own artificial neural network software. Here, training of the operation principle of artificial neural networks starts with the generation of training data and the assignment of correct answer labels. Then, the output value calculated from the firing and activation function of the artificial neuron, the parameters of the input layer, hidden layer, and output layer is learned. Finally, learning the process of calculating the error between the correct label of each initially defined training data and the output value calculated by the artificial neural network, and learning the process of calculating the parameters of the input layer, hidden layer, and output layer that minimize the total sum of squared errors. Training on the operation principles of artificial neural networks using a spreadsheet was conducted for undergraduate non-major students. And image training data and basic artificial neural network development results were collected. In this paper, we analyzed the results of collecting two types of training data and the corresponding artificial neural network SW with small 12-pixel images, and presented methods and execution results of using the collected training data for Orange machine learning model learning and analysis tools.