• 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.

• Journal of the Korea Convergence Society
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• v.9 no.2
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• pp.7-12
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• 2018

With our society entering the Fourth Industrial Revolution, there has been heightened interest in coding education, which has led to an increased number of coding classes offered in schools. Once catered to degree holders only, coding courses are now being offered as liberal arts courses to even non-majors. As the importance of computing abilities and creativity-oriented education through software learning becomes increasingly pronounced, the need for research on effective coding learning is growing more urgent. The present study sought an effective coding education model that would encourage and enhance learners' participation and interest in coding. The proposed learning model is designed to invoke learner's recognition of various coding grammars and data search in the process of designing and performing their own unique project. Application of the proposed learning model and analysis of such case studies showed improvement in learning outcomes. One can expect improved performance among learners if the proposed learning model is applied to various coding courses.

• Korean Journal of Childcare and Education
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• v.17 no.5
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• pp.25-41
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• 2021

Objective: The purpose of this study was to analyze the effect of a director's support for coding education perceived by childcare teachers on the participation of teachers in the learning community and the intention to implement coding education. Methods: The participants of this study were 312 early childhood teachers working at daycare centers in Seoul, Gyeong-gi, and In-cheon area. The data were collected through the survey questionnaires and analyzed using a structural model to explore the relationship between variables. Results: Verifying the mediating effect of infant teacher participation in the learning community between a director's support and infant teacher's intention to implement coding education positively mediates the director's support and infant teacher's intention to implement coding education. In particular, it was discovered that the intention to participate in coding-related learning communities had the greatest impact on infant teachers' intentions to implement coding education based on total effectiveness. Conclusion/Implications: The above analysis results suggest that in order to enhance the intention of infant teachers to implement coding education, it is necessary to support the learning community related to coding education and encourage participation from infant teachers.

• Journal of Information Processing Systems
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• v.19 no.2
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• pp.232-239
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• 2023

Aiming at the poor compression quality of traditional image compression coding (ICC) algorithm, a multi-description ICC algorithm based on depth learning is put forward in this study. In this study, first an image compression algorithm was designed based on multi-description coding theory. Image compression samples were collected, and the measurement matrix was calculated. Then, it processed the multi-description ICC sample set by using the convolutional self-coding neural system in depth learning. Compressing the wavelet coefficients after coding and synthesizing the multi-description image band sparse matrix obtained the multi-description ICC sequence. Averaging the multi-description image coding data in accordance with the effective single point's position could finally realize the compression coding of multi-description images. According to experimental results, the designed algorithm consumes less time for image compression, and exhibits better image compression quality and better image reconstruction effect.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.2
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• pp.69-78
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• 2018

When it comes to the value of modern education, teachers are required to perform the role of a helper to promote interaction between learners, the role of a manager to facilitate smooth learning, and the role of a guide who has expert knowledge in the learning contents. Therefore, this study investigated what kind of learner-centered teaching methods there are, which require teachers to perform the roles of helper, manager, and guide, and conducted a pedagogical research on coding education to explore class models for self-directed learning. Subsequently, a class model was proposed by applying the flipped learning and havruta learning to a coding class. In this study, the learner-centered education methods of flipped learning and havruta method were applied to constructing a coding class as a university general education course. The feature of this class is that it enables dynamic interaction between teachers and learners as well as active interaction between leaners in a classroom instruction. After applying the proposed method to the actual class and analyzing it, the students taught using suggested method were more positively assessed in learning interest than those taught using a traditional method. And that in academic achievement as well, suggested method was more effective.

• Journal of Practical Engineering Education
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• v.9 no.1
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• pp.23-30
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• 2017

This is a study on a case applying flipped learning to coding classes that is a college liberal arts course. A required coding class for the students who do not major in computers needs a teaching method differentiated from a coding education for training experts. The present study presented a flipped learning teaching model for the coding education of non-major students, and observed its effect and possibility. Flipped learning enables learners to learn with on-line contents anywhere and anytime they want and concentrate on practice education based on what they learned during class. Accordingly, the study sought for the solution to maximize the efficiency of teaching and learning through flipped learning. A pre and post surveys after applying a flipped learning to a practical class confirmed that the students taught using flipped learning were more positively assessed in learning satisfaction than those taught using a traditional method, and that in academic achievement as well, flipped learning was more effective.

• Journal of the Korea Society of Computer and Information
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• v.23 no.1
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• pp.49-55
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• 2018

In this paper, we propose a design and development of instructional cards to understand the grammar of coding, solving the problems and extending the computational thinking in the robot-driven environment. First, we designed the input/output module of the robot to process the coding grammar through the function analysis of the robot. And we designed the module of command card to learn coding grammar using color sensors. We have proven the validity of the designed instruction card by examining the experts to see if it is suitable for coding grammar learning. Designed robot and command card were developed with 28 cards and sensor robot. After applying the developed robot and command card to the elementary school students, the questionnaire showed that students grow the understanding and confidence of coding. In addition, students showed an increased need for programming learning.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.735-743
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• 2020

Secure coding is a technique that detects malicious attack or unexpected errors to make software systems resilient against such circumstances. In many cases secure coding relies on static analysis tools to find vulnerable patterns and contaminated data in advance. However, secure coding has the disadvantage of being dependent on rule-sets, and accurate diagnosis is difficult as the complexity of static analysis tools increases. In order to support secure coding, we apply machine learning techniques, such as DNN, CNN and RNN to investigate into finding major weakness patterns shown in secure development coding guides and present machine learning models and experimental results. We believe that machine learning techniques can support detecting security weakness along with static analysis techniques.

• 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.

• International Journal of Advanced Culture Technology
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• v.8 no.3
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• pp.186-191
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• 2020

Artificial Intelligence (AI) technology is used in a variety of fields because it can make inferences and plans through learning processes. In the field of coding technologies, AI has been introduced as a tool for personalized and customized education to provide new educational environments. Also, it can be used as a virtual assistant in coding operations for easier and more efficient coding. Currently, as coding education becomes mandatory around the world, students' interest in programming is heightened. The purpose of coding education is to develop the ability to solve problems and fuse different academic fields through computational thinking and creative thinking to cultivate talented persons who can adapt well to the Fourth Industrial Revolution era. However, new non-computer science major students who take software-related subjects as compulsory liberal arts subjects at university came to experience many difficulties in these subjects, which they are experiencing for the first time. AI based coding technologies can be used to solve their difficulties and to increase the learning effect of non-computer majors who come across software for the first time. Therefore, this study examines the current state of AI based coding technologies and suggests the direction of future coding education.