• Hwankyungkyoyuk
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• v.14 no.2
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• pp.40-50
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• 2001

To meet the objectives of environmental education, teachers especially have to perceive the importance of environmental education, comprehend various characteristics of teaching/learning methods, and be able to conduct classes by choosing proper teaching/leaming methods in accordance with a specific purpose and educational focus about environmental education. Therefore, it Bs necessary to investigate the current status of Korean environmental education and provide teachers with appropriate environmental teaching/leaming methods. To this end this study aims to examine Korean science teachers'perceptions'on environmental education and the kind of teaching/learning methods which can be utilized in environmental education. Teachers who completed the survey were 135 science teachers from middle and high schools in Seoul, and 126 social science teachers from Kyoungki province. The majors of the science teachers were in physics, chemistry, biology, geology, and earth science. Also, there was one teacher who majored in special education. For social science teachers two majors were common, geography and general sociology. After analysis of the data from the surveys the results are as follows. First, science and social science teachers in middle and high school recognized the necessity of environmental education in school education. Second, most teachers had applied environment related topics to their subject of study occasionally, but they mostly concurred that environment related contents should be included in their textbooks. Third, science teachers agreed that field trip, discussion, and the STS approach were the most proper methods for environmental education, and social science teachers agreed that field trips, inquiry, and discussion were the most appropriate methods for a teaching environment. They realized that they should decide good teaching-learning methods appropriate to the objectives and content needed for effective environmental education as they selected different teaching-learning methods according to detailed environmental objectives and contents in their textbooks.

• Journal of Korean Elementary Science Education
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• v.23 no.4
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• pp.305-317
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• 2004

The learning materials in elementary school science textbooks should include all kinds of materials being used by both teachers and students in the science teaching. The major purpose of this research is to analysis textbooks and teacher's guidebooks prepared for the science teaching of 3-6 grade students. To clarify this research, we listed whole of the learning materials of science teaching for each grade and counted numbers being used for whole of the lessons of science. And according to the characteristics and the methods of its preparation of materials, the types of learning materials can be divided into 10 categories such as teaching equipments for science, test materials, consumables, audio-visual aids, teaching equipments in general, collecting' recycling materials, field studies' collected data, breeding' cultivation materials, manufacture materials, and etc. At the result of this research, the 7th national science curriculum needs total 844 items of learning materials for science education. They could be separated into ten types of categories such as 159 items of teaching equipments for science, 65 items of test materials, 116 items of consumables, 198 items of audio-visual aids, 64 items teaching equipments in general, 31 items of collecting' recycling materials, 38 items of field studies (collecting) materials, 17 items of breeding-cultivation materials, 58 items of manufacturing materials, 105 items of other materials. And we found out that there were 332 items of materials for the 3rd grade, 303 items for the 4th grade, 324 items for the 5th grade, and 254 items for the 6th grade. The result of this research could be useful for classroom activities for science teaching.

• Journal of Internet Computing and Services
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• v.15 no.1
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• pp.143-156
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• 2014

The smart education has the goal of enhancing the capability of learners in the 21st century and especially address the improvement of the problem solving capability. This smart education based on the growth of smart devices and the effect of dramatical spread requires the ability of problem solving using the smart technology in accordance with time change. As the problem solving learning is a model used mainly for improving the capability of problem solving, this study develops the problem solving learning model focusing on the teaching-learning activity using the smart devices and also applies this model to the school field. As a result, the favorable response that using the smart devices is effective to the problem solving can be obtained. This study can contribute to achieve the goal of the smart education, and later can be effective to the successful smart education in the school field.

• Journal of the Korean Institute of Landscape Architecture
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• v.29 no.6
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• pp.50-61
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• 2002

As recognition and polices for plans to preserve natural resources and to develop environment-friendly space in school education is developed, not only organization of curriculums related to these is required but also facilities for the education are indispensable. Therefore, this study tries to suggest several standards on matters including kinds and scale of facilities and the introduction of species by facilities required for outdoor teaming spaces for environmental education in the elementary school system. The methods of this study include researching various records related to environmental education in elementary school, researching the present condition of outdoor learning space installed and operating in the existing schools by making an on-the-spot survey, and analyzing appearance frequencies of plants and animals displayed in the text. In addition, the actual conditions of the facility use and management were investigate through a questionnaire, We chose and diagrammed a model of the installed facilities by putting the results together. For analyses the investigated eight schools, were categorized as ‘facilities-arranged type’or ‘connection type with ecological park’. The first type distributed and arranged facilities, including meteorological observatory, rocky park, experience-learning area, ecological pond, animal-breeding farm and field-leaning area into appropriate locations according to the site conditions of the school while the second type created a natural learning place by integrating several facilities and arranging areas such as an animal-breeding farm and experience-learning area into appropriate sites. In this study, essential facilities for outdoor learning are classified into ecological park, experience-loaming area, field loaming area, and for natural learning, meteorological observatory, animal-breeding farm, and greenhouse.

• Journal of Engineering Education Research
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• v.12 no.3
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• pp.118-128
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• 2009

The purpose of this study is to develop a teaching and learning model for the field of engineering to nurture innovative thinking and competency in engineering elites of the next generation. We have reviewed the literature to find out the necessary thinking and capabilities required for the next-generation engineers, and analyzing domestic and international case studies. As a result, we have created Scientific Inquiry and Creative Activity with Technology (SICAT) as a teaching and learning model applicable for the Fusion Materials field. SICAT model is classified ARDA, CoCD, ReSh type to apply directly in class according to teaching and learning objective. And we developed SICAT teaching and learning model guidebook for teachers. In near future, It should be consolidated the validity of the model and improved succeedingly in engineering education through applying and analyzing effectiveness in classes.

• Journal of the Korea Institute of Building Construction
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• v.19 no.5
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• pp.457-465
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• 2019

Technology and society have undergone continued progress and improvement. Thus, constant changes are required for university education, which then directs social development. This study analyzed the current status of educational innovations in the field of building construction at domestic universities in South Korea. The major findings of this study are as follows. Lectures on educational innovations have been introduced in the field of building construction at domestic universities. Five out of 50 universities were found to offer lectures on innovation. Notable innovative teaching methods being introduced were team-based learning and flipped learning. The biggest difference between innovative and traditional teaching methods was whether to encourage students to perform self-directed learning. In this manner, there were also differences in evaluation methods, weekly lecture schedules and learning support tools. Thus it is determined that continuous research and efforts for innovation in university education are necessary to respond to the ever-present changes in society.

• Journal of the Korean Society of Radiology
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• v.15 no.1
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• pp.15-20
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• 2021

CT is important role in the medical field, such as disease diagnosis, but the number of examination and CT images are increasing. Recently, deep learning has been actively used in the medical field, and it has been used to diagnose auxiliary disease through object detection during deep learning using medical images. The purpose of study to evaluate accuracy by detecting kidney and vertebrae during abdominal CT using object detection deep learning in YOLOv3. As a results of the study, the detection accuracy of the kidney and vertebrae was 83.00%, 82.45%, and can be used as basic data for the object detection of medical images using deep learning.

• Geophysics and Geophysical Exploration
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• v.25 no.2
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• pp.71-84
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• 2022

When acquiring seismic data, various types of simultaneously recorded seismic noise hinder accurate interpretation. Therefore, it is essential to attenuate this noise during the processing of seismic data and research on seismic noise attenuation. For this purpose, machine learning is extensively used. This study attempts to attenuate noise in prestack seismic data using unsupervised machine learning. Three unsupervised machine learning models, N2NUNET, PATCHUNET, and DDUL, are trained and applied to synthetic and field prestack seismic data to attenuate the noise and leave clean seismic data. The results are qualitatively and quantitatively analyzed and demonstrated that all three unsupervised learning models succeeded in removing seismic noise from both synthetic and field data. Of the three, the N2NUNET model performed the worst, and the PATCHUNET and DDUL models produced almost identical results, although the DDUL model performed slightly better.

• Journal of Korean Society of Water and Wastewater
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• v.36 no.4
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• pp.239-248
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• 2022

The prediction of algal bloom is an important field of study in algal bloom management, and chlorophyll-a concentration(Chl-a) is commonly used to represent the status of algal bloom. In, recent years advanced machine learning algorithms are increasingly used for the prediction of algal bloom. In this study, XGBoost(XGB), an ensemble machine learning algorithm, was used to develop a model to predict Chl-a in a reservoir. The daily observation of water quality data and climate data was used for the training and testing of the model. In the first step of the study, the input variables were clustered into two groups(low and high value groups) based on the observed value of water temperature(TEMP), total organic carbon concentration(TOC), total nitrogen concentration(TN) and total phosphorus concentration(TP). For each of the four water quality items, two XGB models were developed using only the data in each clustered group(Model 1). The results were compared to the prediction of an XGB model developed by using the entire data before clustering(Model 2). The model performance was evaluated using three indices including root mean squared error-observation standard deviation ratio(RSR). The model performance was improved using Model 1 for TEMP, TN, TP as the RSR of each model was 0.503, 0.477 and 0.493, respectively, while the RSR of Model 2 was 0.521. On the other hand, Model 2 shows better performance than Model 1 for TOC, where the RSR was 0.532. Explainable artificial intelligence(XAI) is an ongoing field of research in machine learning study. Shapley value analysis, a novel XAI algorithm, was also used for the quantitative interpretation of the XGB model performance developed in this study.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.131-135
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• 2024

Baseball attracts the largest audience among professional sports in Korea. In particular, attendance is the primary source of income in baseball. Previous studies have limitations in reflecting the characteristics of individual stadium. For instance, the KIA Tigers exhibit the highest away game revenue among domestic teams, but they show lower home game earnings. Therefore, we aim to predict the daily attendance at the Gwangju-KIA Champions Field of the KIA Tigers using deep learning. We collected and preprocessed daily attendance, dates, weather, and team-related variables for Gwangju-KIA Champions Field from 2018 to 2023. We propose a deep learning-based linear regression model to predict the daily attendance. We expect that the proposed deep learning model will be used as basic information to increase the club's revenue.