• The Journal of Korean Association of Computer Education
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• v.21 no.5
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• pp.37-48
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• 2018

The 2015 revised national curriculum includes SW courses to improve computational thinking, and a variety of physical computing tools for learning are on sale for use in education. The purpose of this study is to provide a basis for selecting physical computing tool for learning suitable for learning situations and learning purposes, and to provide a reasonable basis for judging the choice of tools in the field. Delphi survey method was used as a reference method for developing evaluation criteria through 25 expert panels. As a result, the criterion of evaluation of the learning tool composed of 40 essential and 11 selection criteria for 7 domains was presented. In addition, the evaluation results of five kinds of learning tools commercialized through the evaluation criteria of the learning tool were analyzed. The evaluation criteria for the learning tools developed through this study are expected to help teachers select rational learning tools and help learning tool developers develop learning tools.

• Journal of Digital Convergence
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• v.14 no.2
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• pp.245-258
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• 2016

This paper aims to present the way to bring about significant results through performance improvement of learning algorithm in the research applying to machine learning. Research papers showing the results from machine learning methods were collected as data for this case study. In addition, suitable machine learning methods for each field were selected and suggested in this paper. As a result, SVM for engineering, decision-making tree algorithm for medical science, and SVM for other fields showed their efficiency in terms of their frequent use cases and classification/prediction. By analyzing cases of machine learning application, general characterization of application plans is drawn. Machine learning application has three steps: (1) data collection; (2) data learning through algorithm; and (3) significance test on algorithm. Performance is improved in each step by combining algorithm. Ways of performance improvement are classified as multiple machine learning structure modeling, $+{\alpha}$ machine learning structure modeling, and so forth.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.312-320
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• 2023

Recently, there has been an increasing attempt to replace defect detection inspections in the manufacturing industry using deep learning techniques. However, obtaining substantial high-quality labeled data to enhance the performance of deep learning models entails economic and temporal constraints. As a solution for this problem, semi-supervised learning, using a limited amount of labeled data, has been gaining traction. This study assesses the effectiveness of semi-supervised learning in the defect detection process of manufacturing using the MixMatch algorithm. The MixMatch algorithm incorporates three dominant paradigms in the semi-supervised field: Consistency regularization, Entropy minimization, and Generic regularization. The performance of semi-supervised learning based on the MixMatch algorithm was compared with that of supervised learning using defect image data from the metal casting process. For the experiments, the ratio of labeled data was adjusted to 5%, 10%, 25%, and 50% of the total data. At a labeled data ratio of 5%, semi-supervised learning achieved a classification accuracy of 90.19%, outperforming supervised learning by approximately 22%p. At a 10% ratio, it surpassed supervised learning by around 8%p, achieving a 92.89% accuracy. These results demonstrate that semi-supervised learning can achieve significant outcomes even with a very limited amount of labeled data, suggesting its invaluable application in real-world research and industrial settings where labeled data is limited.

• Journal of Korean Elementary Science Education
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• v.27 no.4
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• pp.420-436
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• 2008

The purpose of this study was to investigate and analysis the elementary teachers' and students' views about the difficulties in teaching and learning in geology units of elementary school science. For the purpose of this study, semi-structured interviews were conducted individually with seventeen elementary teachers who have serviced more than three years, and with sixteen elementary students located in Cheongju City. The interview questions were developed through Seidman's step to acquire a reliability in the interview data with triangulation, then in-depth interview questions were modified and completed through pre-interview after constructing the trustworthiness of interviewees. In-depth interviews were performed in applying the analytic induction method and the interviews were recorded. From the interviews, we found that elementary teachers' views about the difficulties in teaching geology units; teachers' inner difficulties, the difficulty of lab activities, the problems of rock samples, the problems of curriculum in geology units, the difficulty of the geological feature, the problems of the cramming education, the lack of the opportunity for the speciality, and so on. And the students have the views about the difficulties in learning geology units; the difficulty of the unit contents understanding, the problems of learning by heart, the lack of the interest, the lack of materials, the problems of rock samples, the difficulty of the field learning, and so on. Based on the results, the study suggested that an interesting lab activities should be included in the geology units and taught in the geological field trip to help elementary school students more fully comprehend contents of the geology units.

• Journal of Convergence for Information Technology
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• v.9 no.5
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• pp.14-20
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• 2019

Energy saving is becoming more and more important issue due to lack of resources and limited nature. However, There is a lack of learning status on energy saving in the school field. In particular, in elementary education on energy saving was not linked to practice, and the educational effect was insufficient. Although various kinds of learning tools are utilized, many successful cases of energy saving game strategy are introduced in overseas industry field, and game design is proposed so that energy related education can be played through games. Because energy conservation can not be effective without practice, learning using games as a tool is expected to be more effective than learning based on knowledge transfer in the classroom. We propose a defense game for energy conservation education by using the mission elements, score acquisition element, time limit element, and character element which are the interesting elements of the game designed in the previous research.

• Animal Bioscience
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• v.36 no.6
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• pp.980-989
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• 2023

Objective: Iris pattern recognition system is well developed and practiced in human, however, there is a scarcity of information on application of iris recognition system in animals at the field conditions where the major challenge is to capture a high-quality iris image from a constantly moving non-cooperative animal even when restrained properly. The aim of the study was to validate and identify Black Bengal goat biometrically to improve animal management in its traceability system. Methods: Forty-nine healthy, disease free, 3 months±6 days old female Black Bengal goats were randomly selected at the farmer's field. Eye images were captured from the left eye of an individual goat at 3, 6, 9, and 12 months of age using a specialized camera made for human iris scanning. iGoat software was used for matching the same individual goats at 3, 6, 9, and 12 months of ages. Resnet152V2 deep learning algorithm was further applied on same image sets to predict matching percentages using only captured eye images without extracting their iris features. Results: The matching threshold computed within and between goats was 55%. The accuracies of template matching of goats at 3, 6, 9, and 12 months of ages were recorded as 81.63%, 90.24%, 44.44%, and 16.66%, respectively. As the accuracies of matching the goats at 9 and 12 months of ages were low and below the minimum threshold matching percentage, this process of iris pattern matching was not acceptable. The validation accuracies of resnet152V2 deep learning model were found 82.49%, 92.68%, 77.17%, and 87.76% for identification of goat at 3, 6, 9, and 12 months of ages, respectively after training the model. Conclusion: This study strongly supported that deep learning method using eye images could be used as a signature for biometric identification of an individual goat.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.21-30
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• 2024

This research aims to design a system capable of generating real web pages based on deep learning and big data, in three stages. First, a classification system was established based on the industry type and functionality of e-commerce websites. Second, the types of components of web pages were systematically categorized. Third, the entire web page auto-generation system, applicable for deep learning, was designed. By re-engineering the deep learning model, which was trained with actual industrial data, to analyze and automatically generate existing websites, a directly usable solution for the field was proposed. This research is expected to contribute technically and policy-wise to the field of generative AI-based complete website creation and industrial sectors.

• Journal of Korean Elementary Science Education
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• v.24 no.5
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• pp.495-503
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• 2005

The purpose of this study was to analyze elementary school students' attitudes through field-experience teaming activities program for the integrated textbook on the environment issues. This study was conducted after implementing the field environmental education for fifth graders with the teaching-teaming plan applied to the field education and was based on the analysis of environment-related education for the fifth graders. A total of 64 elementary students, 32 in the experimental group and 342 in the control group, were involved in this study. The study used the instrument consisting of 36 Likert-type questions on attitudes toward environment. After going over the influences of the field environmental education program on the students, we found out the positive development in the pre-test and post-test, concerning all environmental themes, especially in the field of protection of animals, environmental pollution, and environment in general.

• Journal of the Korean earth science society
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• v.23 no.2
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• pp.166-179
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• 2002

This study investigated preservice teachers' perceived constraints in implementing their ideal pedagogies and the influence of the teacher education program on their pedagogical beliefs changes. Unique features that the university-based coursework and field experiences had on preservice teachers' learning to teach were also explored. This preservice teacher education program employs constructivist aspects of teacher education and generates applications of constructivism to the practice of teaching. Major findings include: preservice teachers' having traditional pedagogy as the default, recovery of prior beliefs, constraints on implementing constructivist pedagogy, and being overly confident in themselves as teachers. With the influence of constructivist epistemology, these preservice teachers' pedagogical beliefs evolved and were refined over time as they incorporated various constructivist ideas. The benefits and influences of the M.Ed. program's theoretical coursework and the field experiences on these teachers' learning-to-teach experiences are addressed with rich data. The implications for teacher educators as well as for the instructional practices of preservice teacher education programs are discussed. Recommendations for future research are also presented.

• Journal of The Korean Association of Information Education
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• v.15 no.4
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• pp.579-587
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• 2011

In this study, we developed the filed-experience learning support application. Because teachers want to use LBS in education area. In order to select fit functions, we carried out survey about functions that teachers want. Then, we analysed the result of survey and implemented the functions. Also, for survey about application's effectiveness, we selected elementary school teachers. Then we demonstrated and explained the application to them. The result of survey about application's effectiveness shows that application have higher utilization in education area.