• Title/Summary/Keyword: Programming Learning

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Needs of Improving the Curriculum of National University of Education for Strengthening SW Education (SW교육 강화를 위한 교육대학교의 교육과정 개선 요구 분석)

  • Kim, Chul
    • Journal of The Korean Association of Information Education
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    • v.23 no.1
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    • pp.1-8
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    • 2019
  • In order to provide basic data necessary for developing a curriculum to enhance SW education for elementary school teacher students, a questionnaire survey was conducted on 1,260 students at G National University of Education. The results are summarized as follows. First, it is necessary to improve class time of SW education for the college students and revise the SW curriculum to improve SW education capacity for teacher students. Second, in the liberal arts course, it is necessary to develop the teaching and learning materials and the textbooks using various software. Third, in the major course, the Subject Pedagogy programs should be expanded rather than the subject content programs. Fourth, in the specialization course, the programming language education focusing on the Entry and EPL should be strengthened so that it can be linked with the elementary school curriculum. In addition, it is necessary to expand the choice of subjects for the students by reducing the number of required courses and increasing the number of elective courses.

A Study on the Instructional System and Curriculum Design to Evolve the Software Education in Elementary School (초등학교 소프트웨어교육의 교육과정 개선을 위한 내용체계 및 교과 편성의 설계에 대한 연구)

  • Park, Phanwoo;Shin, Seungki
    • Journal of The Korean Association of Information Education
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    • v.23 no.3
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    • pp.273-282
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    • 2019
  • In this study, we have look through the national progress of computer science education in South Korea and analyzed the main subjects and contents of each period. We suggests the ways to evolve the current computer science education in terms of class hours for computer science education, hierarchical instructions, and the limitation of current national curriculum. In South Korea, it has been leaded the computer science education in the world since the it was promoted in earnest since 1995. Based on the recently revised national curriculum, South Korean government are taking efforts to nurture a leader through computer science education in terms of the students' future skills. However, it should be promoted to strengthen the ability of not only problem-solving ability through programming education, but also balanced computing and digital literacy through enhancing the ICT skills. In order to improve the curriculum of computer science education in elementary school of South Korea, a sufficient class hours of computer science education should be secured first.

The Meta-Analysis on Effects of Python Education for Adolescents (청소년 대상 파이썬(Python) 활용 교육의 효과에 대한 메타분석)

  • Jang, Bong Seok;Yoon, So Hee
    • Journal of Practical Engineering Education
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    • v.12 no.2
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    • pp.363-369
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    • 2020
  • This study intends to examine effects of python education for adolescents. 6 primary studies were chosen through careful search process and investigated through meta-analysis. Research findings were as follows. The total effect size was 0.684. Second, the effect sizes of dependent variables were academic achievement 0.871, cognitive domain 0.625, and affective domain 0.428 in order. Third, for cognitive domain, the effect sizes were self-efficacy 0.833, problem-solving 0.283, computing thinking 0.276, and coding competency 0.251 in order. Fourth, for affective domain, the effect sizes were learning interest 0.560 and programming interest 0.417 in order. Fifth, regarding school level, the effect sizes were middle school 0.851, high school 0.585, and college 0.435 in order. Finally, for subject areas, the effect sizes were mathematics 1.057, design 0.595, information 0.585, and software 0.28 in order.

An Analysis Study of SW·AI elements of Primary Textbooks based on the 2015 Revised National Curriculum (2015 개정교육과정에 따른 초등학교 교과서의 SW·AI 요소 분석 연구)

  • Park, SunJu
    • Journal of The Korean Association of Information Education
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    • v.25 no.2
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    • pp.317-325
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    • 2021
  • In this paper, the degree of reflection of SW·AI elements and CT elements was investigated and analyzed for a total of 44 textbooks of Korean, social, moral, mathematics and science textbooks based on the 2015 revised curriculum. As a result of the analysis, most of the activities of data collection, data analysis, and data presentation, which are ICT elements, were not reflected, and algorithm and programming elements were not reflected among SW·AI content elements, and there were no abstraction, automation, and generalization elements among CT elements. Therefore, in order to effectively implement SW·AI convergence education in elementary school subjects, we will expand ICT utilization activities to SW·AI utilization activities. Training on the understanding of SW·AI convergence education and improvement of teaching and learning methods using SW·AI is needed for teachers. In addition, it is necessary to establish an information curriculum and secure separate class hours for substantial SW·AI education.

A Method of Detection of Deepfake Using Bidirectional Convolutional LSTM (Bidirectional Convolutional LSTM을 이용한 Deepfake 탐지 방법)

  • Lee, Dae-hyeon;Moon, Jong-sub
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.30 no.6
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    • pp.1053-1065
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    • 2020
  • With the recent development of hardware performance and artificial intelligence technology, sophisticated fake videos that are difficult to distinguish with the human's eye are increasing. Face synthesis technology using artificial intelligence is called Deepfake, and anyone with a little programming skill and deep learning knowledge can produce sophisticated fake videos using Deepfake. A number of indiscriminate fake videos has been increased significantly, which may lead to problems such as privacy violations, fake news and fraud. Therefore, it is necessary to detect fake video clips that cannot be discriminated by a human eyes. Thus, in this paper, we propose a deep-fake detection model applied with Bidirectional Convolution LSTM and Attention Module. Unlike LSTM, which considers only the forward sequential procedure, the model proposed in this paper uses the reverse order procedure. The Attention Module is used with a Convolutional neural network model to use the characteristics of each frame for extraction. Experiments have shown that the model proposed has 93.5% accuracy and AUC is up to 50% higher than the results of pre-existing studies.

A Study on Development and Application of Artificial Intelligence Education Program using Robot (로봇 활용 인공지능 교육 프로그램 개발과 적용에 관한 연구)

  • Yoo, Inhwan;Bae, Youngkwon;Park, Daeryoon;Ahn, Joongmin;Kim, Wooyeol
    • Journal of The Korean Association of Information Education
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    • v.24 no.5
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    • pp.443-451
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    • 2020
  • In elementary school software education, a programming process is experienced through a simple problem solving process. And even this experience emphasizes that the problem-solving process is a CS Unplugged activity. However, CS Unplugged has a disadvantage in that it only learns the principles of computing, and the learner cannot experience real problem solving. In this study, a learning program using artificial intelligence robots was developed with the goal of cultivating the ability to solve problems encountered in the real life of elementary school students. Students could solve complex problems in real life from the point of view of artificial intelligence through the developed program, and increase their interest and understanding of artificial intelligence education through robot control.

Analysis of the Current Status of the AI Major Curriculum at Universities Based on Standard of AI Curriculum

  • Kim, Han Sung;Kim, Doohyun;Kim, Sang Il;Lee, Won Joo
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.3
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    • pp.25-31
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    • 2022
  • The purpose of this study is to explore the implications for the systematic operation of the AI curriculum by analyzing the current status of the AI major curriculum in universities. To this end, This study analyzed the relevant curriculum of domestic universities(a total of 51 schools) and overseas QS Top 10 universities based on the industry demand-based standard of AI major curriculum developed through prior research. The main research results are as follows. First, in the case of domestic universities, Python-centered programming subjects were lacking. Second, there were few subjects for advanced learning such as AI application and convergence. Third, the subjects required to perform the AI developer job were insufficient. Fourth, in the case of colleges, the ratio of AI mathematics-related subjects was low. Based on these results, this study presented implications for the systematic operation of the AI major education.

A Case Study of Educational Effectiveness by Software Subjects for Humanities College Students

  • Seo, Joo-Young;Shin, Seung-Hun
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.9
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    • pp.267-277
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    • 2022
  • Recently, the topics of SW liberal-arts education are diversifying, from 'Computational Thinking(CT)' to 'Programming, Data Analysis and Artificial Intelligence(AI)' in universities. We expect that the diversification of SW liberal-arts subjects does not just mean that the learning contents are different, but also differentiates the educational goals and educational effects of each subject. In this paper, we conducted a case study to analyze the educational effect according to the educational goals of two SW liberal-arts subjects, CT and Data Analysis Fundamentals(DA), for humanities college students. We confirmed that the educational effect of 'CT Efficacy' increased significantly in accordance with the common educational goal of 'Improving CT-based SW convergence competency' in both subjects. However, we also analyzed the difference in the educational effects of 'CT(the goal of basic SW education)' and 'DA(the goal of major-friendly SW education)', which have different subject goals. 'CT' mainly showed an educational effect on how to solve general daily problems, and 'DA' showed confidence in how to solve major problems along with general problems.

Case study of extended reality education and field application of pre-service elementary teachers (예비 초등교사의 확장현실 교육 및 현장 적용 사례 연구)

  • Junghee Jo;Gapju Hong
    • Journal of The Korean Association of Information Education
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    • v.26 no.5
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    • pp.307-315
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    • 2022
  • The purpose of this study was to design a training program for pre-service elementary teachers, incorporating the concepts of extended reality technologies. This program contained the basic skills necessary for them to utilize in their future classrooms. To accomplish this, 12 undergraduate students of various majors enrolled in one of Korea's national universities of education were selected as research subjects. For a total of 6 times over 6 weeks, they participated in a training program learning the basic concepts of virtual, augmented, and mixed reality, as well as creating their own education software to use in simulated classes. To improve the quality of future research efforts, this study found it would be beneficial to: 1) expand the relevant support equipment, 2) provide students with preliminary, background knowledge of text-based programming, 3) introduce short-term, more intensive training, and 4) improve the survey methods for this research.

Crack detection in folded plates with back-propagated artificial neural network

  • Oguzhan Das;Can Gonenli;Duygu Bagci Das
    • Steel and Composite Structures
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    • v.46 no.3
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    • pp.319-334
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    • 2023
  • Localizing damages is an essential task to monitor the health of the structures since they may not be able to operate anymore. Among the damage detection techniques, non-destructive methods are considerably more preferred than destructive methods since damage can be located without affecting the structural integrity. However, these methods have several drawbacks in terms of detecting abilities, time consumption, cost, and hardware or software requirements. Employing artificial intelligence techniques could overcome such issues and could provide a powerful damage detection model if the technique is utilized correctly. In this study, the crack localization in flat and folded plate structures has been conducted by employing a Backpropagated Artificial Neural Network (BPANN). For this purpose, cracks with 18 different dimensions in thin, flat, and folded structures having 150, 300, 450, and 600 folding angle have been modeled and subjected to free vibration analysis by employing the Classical Plate Theory with Finite Element Method. A Four-nodded quadrilateral element having six degrees of freedom has been considered to represent those structures mathematically. The first ten natural frequencies have been obtained regarding healthy and cracked structures. To localize the crack, the ratios of the frequencies of the cracked flat and folded structures to those of healthy ones have been taken into account. Those ratios have been given to BPANN as the input variables, while the crack locations have been considered as the output variables. A total of 500 crack locations have been regarded within the dataset obtained from the results of the free vibration analysis. To build the best intelligent model, a feature search has been conducted for BAPNN regarding activation function, the number of hidden layers, and the number of hidden neurons. Regarding the analysis results, it is concluded that the BPANN is able to localize the cracks with an average accuracy of 95.12%.