• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.167-174
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• 2023

Electronic educational environments in the conditions of quarantine restrictions of COVID-19 have become a common phenomenon for the organization of distance educational activities. Under the conditions of Russian aggression, Ukrainian proof of their use is unique. The purpose of the article is to analyze the role of electronic educational environments in the process of training applicants for higher education in Ukraine in the realities of a large-scale war. General scientific methods (analysis, synthesis, deduction, and induction) and special pedagogical prognostic methods, modeling, and SWOT analysis methods were used. In the results, the general properties of the Internet educational platforms common in Ukraine, the peculiarities of using the Moodle and Prometheus platforms, and an approximate model of the electronic learning environment were discussed. The reasons for the popularity of Moodle among Ukrainian universities are analyzed, but vulnerable elements related to security are emphasized. It was also determined that the high cost of Prometheus software and less functionality made this learning environment less relevant. The conclusions state that the military actions drew the attention of universities in Ukraine to the formation of their own educational platforms. This is especially relevant for technical and military institutions of higher education.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1293-1293
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• 2024

Virtual reality (VR) is increasingly utilized in the construction industry for diverse applications. Immersive virtual reality (IVR) offers practical experiences and educational opportunities for workers, enhancing productivity and safety. Efforts to optimize IVR involve analyzing biometric responses to monitor concentration, assess learning efficiency, and deliver personalized content. However, IVR faces challenges such as high production costs and prolonged production periods. Additionally, integrating biometric response recording into IVR experiences requires separate modules, further extending production timelines. To address these challenges, an integrated platform is necessary to streamline IVR production, user experience, and biometric response setup and recording. This study introduces such a platform designed to enhance the efficacy of IVR experiences through real-time biometric response analysis. The proposed platform comprises three main processes: (i) IVR content production using Unity; (ii) biometric response definition; and (iii) IVR content experience accompanied by generated logs for biometric responses. Firstly, IVR content production using Unity involves the development of IVR environments and scenarios. The platform incorporates diverse 3D models, including urban landscapes, building elements, and furniture, as the basis for IVR environments. Scenarios are constructed by integrating events into these environments, triggered by conditions such as reaching specific locations, the passage of time, or user interactions. Upon event activation, participants are presented with description UIs, quiz UIs, or route guidance, facilitating engagement and progression through interaction. Secondly, biometric responses encompass eye tracking and EEG. Eye tracking captures pupil diameter and fixation status on Areas of Interest (AOI), defined during IVR content production. EEG recording options include signals from each channel by default, as well as frequency-specific signals and EEG metrics such as attention, stress, fatigue, valence, and arousal. The platform supports the addition of new EEG metrics, enhancing customization and recording capabilities. Lastly, IVR content can be experienced alongside generated logs for biometric responses. The dataset enables monitoring and evaluation of participants' learning performance during IVR experiences, with the potential to enhance worker safety and productivity through immersive practical training and education.

• The Mathematical Education
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• v.59 no.2
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• pp.147-166
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• 2020

Textbooks are important resources in support of teaching and learning mathematics competencies which are emphasized in the most recently revised mathematics curriculum. This study analyzed how six mathematics competencies and their sub-elements are implemented in the mathematics textbooks for the fifth and sixth grades. A total of 465 activities or items in the targeted textbooks were analyzed. The findings of this study showed that both the communication competence and the reasoning competence were the most frequent competencies, followed by the problem solving competence. In contrast, the other three competences (i.e., creativity and integration, attitude and practice, and information processing) were less popular. Detailed analyses of sub-elements according to each competence revealed that one or two specific sub-elements were emphasized within a competence. Whereas "expressing one's idea" was the most prevalent sub-element in the communication competence, both "analyzing mathematical facts" and "observation and conjecture" were the most frequent in the reasoning practice. Specific sub-elements were jointly implemented within or across competences. "External connections of mathematics and integration" in the creativity and integration competence was carried out in relation to "recognition of values" in the attitude and practice competence. This paper also included some examples of activities or items showing how specific sub-elements of each competence were reflected on. This study is expected to provide implications on how to implement mathematics competencies throughout the textbooks.

• Journal of Science Education
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• v.35 no.2
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• pp.250-261
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• 2011

The purpose of this study is to analyze how the content elements of the environment education are displayed between related subjects in elementary school curriculum and find a desirable direction of the environment education. Major subjects that handle the components of the environment education include science, physical education, social studies, ethics, and practical arts. Among these subjects, science aims for the ecological perspective, social studies aims for rational decision making and practical behaviors, and ethics aims for the correct formation of environmental ethics and values. In the component ratio of the environment education, the domains of the natural environment, environmental ethics, environmental pollution, environmental protection and measure were higher. In the formation of content elements according to grades, the connectivity of the environment curriculum has been relatively well secured in the order of the learning about the environmental components, awareness on environmental problems and the measures and efforts to overcome environmental problems. Based on the findings above, the followings are proposed for future environment curriculum in elementary school. First, it is necessary to increase the ratio of the ecological perspective based on science and coordinate the period to suggest this contents. Second, it is necessary to complement the contents of social studies regarding green growth and sustainable development which have become global issues in the environment education. Third, Pan-curriculum and integrated discussions to prepare multi-academic and interdisciplinary environment curriculum have to be preceded and through this process it is necessary to set the target of environment education and select the content elements of the curriculum.

• Journal of Korean Home Economics Education Association
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• v.23 no.2
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• pp.109-130
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• 2011

The purpose of this study was to examine the elements of green life education reflected in the Korean and Japanese secondary school Home Economics curricula. Although sustainable living at home has been emphasized as one of the main issues of Home Economics since the first curriculum period, green growth education has more reinforced in recent revised Home Economics Curricula of both countries. Thus the 2007 revised secondary school Home Economics Curriculum of Korea and 2008 revised middle school and 2009 revised high school Home Economics Curriculum of Japan were analyzed. The content analyses were done to examine the elements of green life education reflected in 'Characteristics and Objectives', 'Contents', and 'Teaching learning/Contents dealing Strategies' parts of the curriculum through two checking steps. The elements of green life education were included in all parts of the Home Economics Curricula of both countries except the 'Characteristics and Objectives' part of Japanese Curriculum. In both the Korean and Japanese Curricula, the element of green life was the most frequently and concretely reflected in the 'Contents' part, contrary to the 'Characteristics and Objectives' part where the element was the most rarely and abstractly reflected. The practical aspects of the green life education were more emphasized than the theoretical ones in both countries' curricula. The green life educational elements need to be included in all parts of Home Economics curriculum with concrete manner to ensure these elements to be reflected in Home Economics textbooks and to be actively implemented in classroom.

• Journal of The Korean Association For Science Education
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• v.37 no.5
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• pp.799-812
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• 2017

Energy as a powerful and unifying concept to understand natural world has been regarded as one of the key concepts of the science curricula in many countries. However, concerning learning and teaching of energy, various difficulties have been reported widely. This study aimed at analyzing and comparing science curricula of Korea, the U.S., England, and Singapore regarding energy to identify the potential issues for energy curriculum in the future. 2015 revised Korean science curriculum, Next Generation Science Standards of the U.S., Science programmes of study of England, and the Science syllabus of Singapore were compared based on six basic elements of the concept of energy: energy form, energy resource, energy transfer, energy transformation, energy conservation, and energy dissipation. Achievement criteria that include energy were extracted from all curricula and categorized into the six elements. The frequency and distribution of the six elements in the four curricula were compared in terms of school levels and disciplinary areas. Contents of six energy elements were also compared. Though all curricula emphasized energy as a key science concept, we found many differences in the degree of emphasis of basic ideas and specific contents and approaches. Korean curriculum is characterized by 1) high frequency concerning energy form among the elements of the concept of energy, 2) introducing energy forms of unclear meaning, which are not linked with other physical quantities, 3) emphasis on energy conversion in comparison of energy transfer, 4) focusing on mechanical energy conservation instead of more general energy conservation, and 5) absence of the concept of 'system' concerning energy. Issues for energy curriculum development were discussed.

• Journal of Christian Education in Korea
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• v.72
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• pp.245-271
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• 2022

The purpose of this study is to develop a nursing clinical practice education model that applies case-based learning and co-teaching to nursing students, and to secure the validity of the developed model. To verify the validity of the nursing clinical practice education model, it was applied to the subject of 'Health Response and Nursing VI (Perception/ Cognition) Practice' in the 2nd semester of 2021 at J University in Jeonju, and the instructor's response to the model was evaluated. Surveys and focus group interviews were conducted on confidence in clinical practice and teaching and learning models. After deriving the case-based learning stage and co-teaching elements through a review of precedent literature and case studies, an initial model was devised after expert review, and the devised model was reviewed for internal validity by nursing education experts, and then modified and supplemented. As a result of the learner response evaluation conducted after applying the model to the clinical practice subject for external validation verification, the confidence in clinical performance was 4.22 points and the satisfaction with the teaching-learning model was 4.68 points. Summarizing the results of the focus group interview, the importance of prior learning and the learning of selected cases based on actual cases, learning terminology and professional knowledge, eliminated fear of the practice field, felt familiar, and learned various cases. He said that he was able to think critically through the time to organize the knowledge learned in the practice field. In addition, through co-teaching, it was found that field leaders and advisors taught the theoretical and practical aspects at the same time through examples, thereby experiencing practical education closer to practice. It is expected that the nursing clinical practice education model developed through this study, applying case-based learning and co-teaching, will be an effective teaching and learning model that can reduce the gap between theory and practice and improve the clinical performance of nursing students.

• Journal of Korea Water Resources Association
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• v.57 no.1
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• pp.35-44
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• 2024

Research in dam inflow prediction has actively explored the utilization of data-driven machine learning and deep learning (ML&DL) tools across diverse domains. Enhancing not just the inherent model performance but also accounting for model characteristics and preprocessing data are crucial elements for precise dam inflow prediction. Particularly, existing rainfall data, derived from snowfall amounts through heating facilities, introduces distortions in the correlation between snow accumulation and rainfall, especially in dam basins influenced by snow accumulation, such as Soyang Dam. This study focuses on the preprocessing of rainfall data essential for the application of ML&DL models in predicting dam inflow in basins affected by snow accumulation. This is vital to address phenomena like reduced outflow during winter due to low snowfall and increased outflow during spring despite minimal or no rain, both of which are physical occurrences. Three machine learning models (SVM, RF, LGBM) and two deep learning models (LSTM, TCN) were built by combining rainfall and inflow series. With optimal hyperparameter tuning, the appropriate model was selected, resulting in a high level of predictive performance with NSE ranging from 0.842 to 0.894. Moreover, to generate rainfall correction data considering snow accumulation, a simulated snow accumulation algorithm was developed. Applying this correction to machine learning and deep learning models yielded NSE values ranging from 0.841 to 0.896, indicating a similarly high level of predictive performance compared to the pre-snow accumulation application. Notably, during the snow accumulation period, adjusting rainfall during the training phase was observed to lead to a more accurate simulation of observed inflow when predicted. This underscores the importance of thoughtful data preprocessing, taking into account physical factors such as snowfall and snowmelt, in constructing data models.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.79-104
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• 2020

Recently, as deep learning has attracted attention, the use of deep learning is being considered as a method for solving problems in various fields. In particular, deep learning is known to have excellent performance when applied to applying unstructured data such as text, sound and images, and many studies have proven its effectiveness. Owing to the remarkable development of text and image deep learning technology, interests in image captioning technology and its application is rapidly increasing. Image captioning is a technique that automatically generates relevant captions for a given image by handling both image comprehension and text generation simultaneously. In spite of the high entry barrier of image captioning that analysts should be able to process both image and text data, image captioning has established itself as one of the key fields in the A.I. research owing to its various applicability. In addition, many researches have been conducted to improve the performance of image captioning in various aspects. Recent researches attempt to create advanced captions that can not only describe an image accurately, but also convey the information contained in the image more sophisticatedly. Despite many recent efforts to improve the performance of image captioning, it is difficult to find any researches to interpret images from the perspective of domain experts in each field not from the perspective of the general public. Even for the same image, the part of interests may differ according to the professional field of the person who has encountered the image. Moreover, the way of interpreting and expressing the image also differs according to the level of expertise. The public tends to recognize the image from a holistic and general perspective, that is, from the perspective of identifying the image's constituent objects and their relationships. On the contrary, the domain experts tend to recognize the image by focusing on some specific elements necessary to interpret the given image based on their expertise. It implies that meaningful parts of an image are mutually different depending on viewers' perspective even for the same image. So, image captioning needs to implement this phenomenon. Therefore, in this study, we propose a method to generate captions specialized in each domain for the image by utilizing the expertise of experts in the corresponding domain. Specifically, after performing pre-training on a large amount of general data, the expertise in the field is transplanted through transfer-learning with a small amount of expertise data. However, simple adaption of transfer learning using expertise data may invoke another type of problems. Simultaneous learning with captions of various characteristics may invoke so-called 'inter-observation interference' problem, which make it difficult to perform pure learning of each characteristic point of view. For learning with vast amount of data, most of this interference is self-purified and has little impact on learning results. On the contrary, in the case of fine-tuning where learning is performed on a small amount of data, the impact of such interference on learning can be relatively large. To solve this problem, therefore, we propose a novel 'Character-Independent Transfer-learning' that performs transfer learning independently for each character. In order to confirm the feasibility of the proposed methodology, we performed experiments utilizing the results of pre-training on MSCOCO dataset which is comprised of 120,000 images and about 600,000 general captions. Additionally, according to the advice of an art therapist, about 300 pairs of 'image / expertise captions' were created, and the data was used for the experiments of expertise transplantation. As a result of the experiment, it was confirmed that the caption generated according to the proposed methodology generates captions from the perspective of implanted expertise whereas the caption generated through learning on general data contains a number of contents irrelevant to expertise interpretation. In this paper, we propose a novel approach of specialized image interpretation. To achieve this goal, we present a method to use transfer learning and generate captions specialized in the specific domain. In the future, by applying the proposed methodology to expertise transplant in various fields, we expected that many researches will be actively conducted to solve the problem of lack of expertise data and to improve performance of image captioning.

• Journal of the Korean earth science society
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• v.29 no.2
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• pp.151-162
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• 2008

This study quantitatively investigated the actual situations and perceptions of gifted students and their teachers during small group inquiry activities in Korea. Some 1,670 gifted math students and 1,732 gifted science students as well as 614 of their teachers were selected through random sampling to participate in this study. Data were collected by means of a survey developed by the researchers of this study, based on reviews of literature related to inquiry and small group cooperative learning. The results were as follows: (1) In Korean gifted education, small group inquiry activities were frequently used as teaching and learning strategies, and both the students and teachers perceived its effects to be very positive in terms of cognition and affection. (2) Gifted education teachers emphasized the development of students' procedural inquiry skills as well as logical thinking skills, whereas they were indifferent to the essential elements of small group cooperative learning and therefore the lessons did not surpass the level of traditional group activities. (3) The fact that the actual small group inquiry activities did not reflect the characteristics of well-organized small group activities is due to a lack of knowledge on the teacher's part as to effective teaching strategies concerning cooperative learning. This study implies that gifted education teachers require the opportunity to reflect on and develop their knowledge and understanding of small group inquiry activities through professionally developed programs in order to maximize the effectiveness of small group inquiry activities in gifted education.