• Title/Summary/Keyword: Computer Liberal Arts

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Some Results of Non-Central Wishart Distribution

  • Chul Kang;Jong Tae Park
    • Communications for Statistical Applications and Methods
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    • v.5 no.2
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    • pp.531-538
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    • 1998
  • This paper first examines the skewness of Wishart distribution, using Tracy and Sultan(1993)'s results. Second, it investigates the variance-covariance matrix of random matrix $S_Y=YY'$ which has a non-central Wishart distribution. Third, it proposes the exact form of the third moment of the random matrix with non-central Wishart distribution.

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Empirical Bayes Estimation of the Binomial and Normal Parameters

  • Hong, Jee-Chang;Inha Jung
    • Communications for Statistical Applications and Methods
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    • v.8 no.1
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    • pp.87-96
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    • 2001
  • We consider the empirical Bayes estimation problems with the binomial and normal components when the prior distributions are unknown but are assumed to be in certain families. There may be the families of all distributions on the parameter space or subfamilies such as the parametric families of conjugate priors. We treat both cases and establish the asymptotic optimality for the corresponding decision procedures.

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A CHANGE OF SCALE FORMULA FOR GENERALIZED WIENER INTEGRALS II

  • Kim, Byoung Soo;Song, Teuk Seob;Yoo, Il
    • Journal of the Chungcheong Mathematical Society
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    • v.26 no.1
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    • pp.111-123
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    • 2013
  • Cameron and Storvick discovered change of scale formulas for Wiener integrals on classical Wiener space. Yoo and Skoug extended this result to an abstract Wiener space. In this paper, we investigate a change of scale formula for generalized Wiener integrals of various functions using the generalized Fourier-Feynman transform.

Application and Effect Analysis of ARCS Model to Improve Learner's Learning Motivation in Liberal Computational Thinking Subjects (교양 컴퓨팅 사고력 과목의 학습자 학습동기 향상을 위한 ARCS 모델의 적용 및 효과 분석)

  • Jun, Soo-jin;Shin, ChwaCheol
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.2
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    • pp.259-267
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    • 2020
  • The purpose of this study is to analyze the effects of computational thinking class using ARCS model to increase students' learning motivation. Then, this study designed the detailed instruction strategy according to each motivation factor(Attention, Relevance, Confidence, Satisfaction) of ARCS through the previous study on computational thinking education and ARCS model. The results of the ARCS test were compared between the experimental group to which the ARCS model was applied and the control group to which the general class was conducted. As a result, students in the experimental group showed significantly higher motivation for learning about computational thinking. In particular, the learning motivation of computer-related majors was significantly higher than that of the control group. In addition, majors were found to have high relevance(R) and non-majors had high satisfaction(S). Therefore, based on these findings, this study suggests an improvement for effective computational thinking class in liberal arts education.

The Evaluation Tool and Process for Effective Education Outcomes Measurement and Analysis of Computer Education

  • Kim, Young-Tak;Sim, Gab-Sig
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.9
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    • pp.149-156
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    • 2016
  • This paper is concerned with education courses operating practices for basic computer literacy training. In this study, we propose an example for students to effectively measure and evaluate the achievement of defined ability in the performance measurement and analysis, learning objectives and learning outcomes set in operation throughout the course. Through research and development use case presents the tools for teaching method and effective and objective measurement of the related subjects. And based on the results, we propose the possibility of utilizing NCS-based course operation and education certification. In this study, the measurement process is based on the association with the objective of the development and operation, and measurement tools, measuring tools for measuring learning outcomes associated with the curriculum design methods for the measurement and evaluation of the case of the operation of the course units of learning outcomes and the method proposed.

Study on the Walk Navigation App using Augmented Reality (증강현실을 이용한 도보 길찾기 앱에 관한 연구)

  • Lee, Myung-suk;Kim, Joo-Hwan;Lee, Ho-Jun;Jeon, Cho-Hui
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2016.01a
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    • pp.197-199
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    • 2016
  • 일반적으로 네비게이션은 차를 이용하는 것으로 발전한 것이 대부분이며, 지형이나 지도 또는 정보를 저장했다가 사용하는 로드뷰를 이용하여 개발되고 있다. 본 연구에서는 증강현실 기술과, 스마트폰의 카메라, 센서 등을 이용하여 실제의 길과 주변 환경을 스마트폰에 보여주고, 실제 길 위에 찾고자 하는 목적지까지 길을 안내해주며 다양한 부가 정보를 제공하는 도보 길찾기 앱을 개발하고자 한다. 기존의 앱과 다른 점은 증강현실 기술을 활용하는 것이다. 기존 네이게이션에서 2D나 3D로 그래픽 처리되어 있는 것을 실제 화면을 적용하여 직관적으로 길을 찾을 수 있고, 부가적으로 주변의 정보들을 실시간으로 표현할 수 있는 이점이 있다.

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Understanding the Internet of Things: Education and Experience

  • Yun, Jaeseok
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.12
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    • pp.137-144
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    • 2018
  • In this paper, we propose an well-organized lecture note for giving a better understanding on the Internet of Things (IoT) to people including non-computer majors without computing and communication knowledge. In recent years, the term 'IoT' has been popularized, and IoT will make a huge impact on our industries, societies, and environments. Although there are large amount of literature on presenting IoT from technological perspectives, few are published that are organized for teaching students having non-computer-related majors. Based on research and education experiences on IoT, we tried to make a lecture note focusing on the process of collecting data from everyday objects, transmitting and sharing data, and utilizing data to create new values for us. The proposed lecture note was employed in teaching a liberal arts class, and it was shown that students could have an understanding of what IoT really means and how IoT could change our world.

Design of Learning Process with Code Reconstruction Principle for Non-computer Majors

  • Hye-Wuk, Jung
    • International Journal of Advanced Culture Technology
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    • v.10 no.4
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    • pp.175-180
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    • 2022
  • To develop computational thinking skills, university students are learning how to solve problems with algorithms, program commands and grammar, and program writing. Because non-computer majors have difficulty with computer programming-related content, they need a learning method to acquire coding knowledge from the process of understanding, interpreting, changing, and improving source codes by themselves. This study explored clone coding, refactoring coding, and coding methods using reconstruction tools, which are practical and effective learning methods for improving coding skills for students who are accustomed to coding. A coding learning process with the code reconstruction principle was designed to help non-computer majors use it to understand coding technology and develop their problem-solving ability and applied the coding technology learning method used in programmer education.

A Study on Coding Education for Non-Computer Majors Using Programming Error List

  • Jung, Hye-Wuk
    • International Journal of Advanced Culture Technology
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    • v.9 no.1
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    • pp.203-209
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    • 2021
  • When carrying out computer programming, the process of checking and correcting errors in the source code is essential work for the completion of the program. Non-computer majors who are learning programming for the first time receive feedback from instructors to correct errors that occur when writing the source code. However, in a learning environment where the time for the learner to practice alone is long, such as an online learning environment, the learner starts to feel many difficulties in solving program errors by himself/herself. Therefore, training on how to check and correct errors after writing the program source code is necessary. In this paper, various types of errors that can occur in a Python program were described, the errors were classified into simple errors and complex errors according to the characteristics of the errors, and the distributions of errors by Python grammar category were analyzed. In addition, a coding learning process to refer error lists was designed to present a coding learning method that enables learners to solve program errors by themselves.