Journal of The Korean Association For Science Education
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v.39
no.6
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pp.707-715
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2019
The self-directed inquiry to improve students' core scientific competency is an important teaching method. Students experience a variety of difficulties in carrying out their inquiry tasks, sometimes fail to produce the desired results, or fail to perform a meaningless inquiry. This study was conducted to identify the causes of difficulties and failures in students' self-directed scientific inquiry. The study involved 16 high school students with experience in science research at science high schools and science-focused high schools. The data collection consisted of in-depth interviews centered on semi-structured open questions. Qualitative data analysis was imputed by finding paragraphs from the interview material that might reveal the difficulties and failures experienced by participants and the reasons for them. The study found that most of the causes of failure were lack of ability, incomplete procedures, and selection of complicated tasks. A variety of cognitive biases, such as overconfidence, planning fallacy, and groupthink, were also analyzed as causes. Based on the results of the study, it is necessary to develop an educational strategy that students can be fully prepared to reduce their trials and errors in a self-directed inquiry maximally.
Journal of The Korean Association For Science Education
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v.35
no.6
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pp.949-959
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2015
In this case study, we analyzed the STEAM lessons conducted by secondary science teachers in the perspective of the CHAT. Two science teachers at high schools in Seoul participated in this study. All of the teaching-learning materials were collected before lessons, and their lessons were observed and videotaped. We also observed the atmospheres in both school offices and classrooms. Semi-structured interviews were conducted before and after their lessons. All the data collected were categorized according to the elements of the activity system and analyzed by using the constant comparative method. The analyses of the results revealed that both teachers did not consider the student-centered self-directed activities in their STEAM lessons, but that they differed in the subject element such as teacher's professionalism on STEAM. Various elements of the activity system such as environmental characteristics of the school and policies about the STEAM influenced the performance of their STEAM lessons. Contradictions in the elements of the activity system brought about various changes. Successful experiences of the STEAM lessons by complex effects of the elements positively influenced their performances on their STEAM lessons. Based on these results, we have made some suggestions for the establishment of the STEAM in secondary schools.
Journal of The Korean Association For Science Education
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v.32
no.4
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pp.717-728
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2012
The purpose of this study is to analyze the argumentation of gifted students in the perspective of rebuttal. Rebuttal is a significant indicator of argumentation quality; it is also an essential component for science learning through interaction. However, most previous research point out insufficient use of rebuttal in student's argumentation. The argumentation of 37 8th grade students, enrolled in institutes for the scientifically gifted in Seoul, are observed and recorded for 4 hours. The argumentation topic is about how to measure the brightness of the sun. Based on Verheij's (2005) five types of rebuttal patterns, the features of rebuttal are analyzed. It is found that students' argumentation include all of the five rebuttal types: rebuttal of the data, the claim, the warrant, warrant's applicability, and connection between data and claim. It is also found that these five types can be categorized in two groups. The first group consists of first three types and is characterized by the disagreement with the validity of what has been said. The second group consists of the last two types and is characterized by the suggestion or additional information for missing links in argumentation.
Korean Journal of Construction Engineering and Management
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v.14
no.3
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pp.78-87
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2013
The modern society has been drastically changed from the industrial economic society to the knowledge based society, to catch up with the knowledge and the change of technology required for the modern people, the people can not live in the modern society without the continued study or education. In case of architectural design firm, it is concentrating on the productivity of enterprise by cultivating the working level through the self education focused on the improvement of inner capacity. In connection with this, the efficiency of enterprises are analyzed by carrying out the Data Envelopment Analysis(DEA) utilizing the financial ratio index in the various field of industries recently, the analysis study for the efficiency utilizing DEA is increased in the construction industries as well. However, in case of construction industries, the study focused on the efficiency of administration only has been progressed, it is the real situation that the approach for the analysis of education efficiency of each enterprise is very insufficient. Therefore, this study analyzed the education efficiency of architectural design firm after the selection of input and output variables by utilizing the DEA model and utilizing the AHP analysis technique by deducting the variables through the preceding study in relation to the education efficiency and the interview with the specialists.
KSCE Journal of Civil and Environmental Engineering Research
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v.38
no.6
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pp.839-850
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2018
The flood damage in urban areas due to torrential rain is increasing with urbanization. For this reason, accurate and rapid flooding forecasting and expected inundation maps are needed. Predicting the extent of flooding for certain rainfalls is a very important issue in preparing flood in advance. Recently, government agencies are trying to provide expected inundation maps to the public. However, there is a lack of quantifying the extent of inundation caused by a particular rainfall scenario and the real-time prediction method for flood extent within a short time. Therefore the real-time prediction of flood extent is needed based on rainfall-runoff-inundation analysis. One/two dimensional model are continued to analyize drainage network, manhole overflow and inundation propagation by rainfall condition. By applying the various rainfall scenarios considering rainfall duration/distribution and return periods, the inundation volume and depth can be estimated and stored on a database. The Rainfall-Duration-Flooding Quantity (RDF) relationship curve based on the hydraulic analysis results and the Self-Organizing Map (SOM) that conducts unsupervised learning are applied to predict flooded area with particular rainfall condition. The validity of the proposed methodology was examined by comparing the results of the expected flood map with the 2-dimensional hydraulic model. Based on the result of the study, it is judged that this methodology will be useful to provide an unknown flood map according to medium-sized rainfall or frequency scenario. Furthermore, it will be used as a fundamental data for flood forecast by establishing the RDF curve which the relationship of rainfall-outflow-flood is considered and the database of expected inundation maps.
Journal of the Korea Academia-Industrial cooperation Society
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v.20
no.5
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pp.231-240
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2019
The purpose of this study is to understand of flipped learning of vocational high school teachers and to provide basic data of teacher training program development that can support flipped learning classes of vocational high school. We conducted surveys and focus group interviews to solve these research problems. The focus group interview is conducted on four flipped learning teachers who participated in the questionnaire. The results of this study are as follows. First, vocational high school teachers only heard the term 'flipped learning', but they did not have much experience in class. Second, it is necessary to learn contents and pre-learning for basic understanding of flipped learning, method of making learning contents of learning materials that focused on students' motivation and interest in the classroom. Also, we needed a method to induce participation in classroom activities, and a compensation method and evaluation method to maintain it. In addition, they requested specific flipped learning instruction procedures and various learning materials at each stage in accordance with the vocational high school situation. Third, I requested training contents and practice - centered training method that can induce interest and motivation as the training management method for the vocational high school teachers' flipped learning classes. In addition, it required step - by - step training according to the understanding level of flipped learning of high school teacher.
The purpose of this study was to be used as basic data for the development of future-type curriculum in health. The awareness and preparation of the forth industrial revolution were surveyed on 280 college students in health departments preparing medical technicians. A self-written structured questionnaire was used for data collection, and the recognition of the forth industry revolution was 2.74, 3D printing (3.59) was high, and neural network machine learning(2.33) was the lowest. Students majoring in Physiotherapy (3.00) had the highest perception, and those majored in Dental engineering(2.37) had the lowest perception, and there was a difference in the degree of perception of IoT by major (p=0.024). For the forth industrial revolution, 54.5% of students are preparing, and lack of interest (42.9%) is the most difficult reason to prepare, and 50.6% of educational experience and 60.9% of VR&AR game experience have experience. In the era of the forth industrial revolution, job loss (38.7%) was high, and the required competency was creative capacity (50.6%). Therefore, it is necessary to develop a curriculum related to the fourth industrial revolution and apply teaching methods that can increase the awareness and preparation of health college students in the era of the fourth industrial revolution.
Journal of Korean Library and Information Science Society
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v.54
no.2
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pp.43-65
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2023
The purpose of all public libraries is to provide knowledge and information services for the intellectual and reading activities of local residents, program services that provide opportunities for cultural enjoyment and lifelong learning, and third-party spaces and facilities that contribute to the development of the community. To this end, social needs must be reflected in a timely manner with the establishment of a sound infrastructure as a prerequisite. This study analyzed the current status centered on key indicators of the public libraries in Daegu City and presented policy issues that need to be improved through a survey. The key indicators in Daegu City, compared to the national average, were not only significantly weak for the 3rd largest city but also showed considerable variation among local governments. While Daegu citizens valued public libraries in their daily lives, the dissatisfaction rate was high in the order of transportation inconvenience, lack of necessary materials and desired programs, and various regulations. Therefore, Daegu City should focus on increasing the acquisition budget, strengthening the development of new book collections, expanding the number of librarians, expanding the construction of public libraries to address service disparities among local governments, improving accessibility, and addressing factors that hinder usage. In addition, with the establishment and operation of the Daegu Library in 2024, efforts should be made to establish an operational system for public libraries, expand the scope through collaborative partnerships with other knowledge and cultural institutions, and enhance knowledge and cultural services for the Daegu citizen.
Park, Mi Jeong;Lim, Yunjin;Kwon, Yoojin;Lee, Kwangjae
Journal of Korean Home Economics Education Association
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v.32
no.1
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pp.15-34
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2020
The purpose of this study was to examine the secondary school technology and home economics teachers' perception of the school curriculum organization and high school credit system. For this purpose, the questionnaire data of 345 secondary technology and home economics teachers nationwide were analyzed through descriptive statistics, t-test, and F-test with SPSS 24. The research results were as follows. First, technology and home economics teachers recognized that current schools lacked the time to organize technology and home economics curriculum (61.1%) and the number of teachers (53%). Most of them have participated (62.0%) and were very willing to participate in the school curriculum organization (4.47, 89.9%). Second, technology and home economics teachers were aware of the high school credit system more than the average (3.34), and more negative (52.8%) than positive (37.7%). As a positive influence, students recognized career choices (3.88) and deepened professional content in their major fields (3.81). On the other hand, the negative impact was the decrease in choice due to non-entry subjects (3.90) and the difficulty in moving teachers to school (3.57). Third, in order to stably respond to the introduction of high school credit system, technology and home economics teachers recognized the importance of coordinating career elective courses (4.51), developing and disseminating teaching and learning materials for elective courses (4.46), separating technology and home economics (4.45), and providing training on evaluation methods and applications (4.44). This study would be useful to provide the basic information and data for the future development of technology and home economics curriculum at the national level based on high school credit system.
Park, Jun Sang;Seo, Yun Am;Kim, Kyu Rang;Ha, Jong-Chul
Korean Journal of Agricultural and Forest Meteorology
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v.20
no.3
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pp.262-276
/
2018
Models to predict Leaf Wetness Duration (LWD) were evaluated using the observed meteorological and dew data at the 11 citrus orchards in Jeju, South Korea from 2016 to 2017. The sensitivity and the prediction accuracy were evaluated with four models (i.e., Number of Hours of Relative Humidity (NHRH), Classification And Regression Tree/Stepwise Linear Discriminant (CART/SLD), Penman-Monteith (PM), Deep-learning Neural Network (DNN)). The sensitivity of models was evaluated with rainfall and seasonal changes. When the data in rainy days were excluded from the whole data set, the LWD models had smaller average error (Root Mean Square Error (RMSE) about 1.5hours). The seasonal error of the DNN model had the similar magnitude (RMSE about 3 hours) among all seasons excluding winter. The other models had the greatest error in summer (RMSE about 9.6 hours) and the lowest error in winter (RMSE about 3.3 hours). These models were also evaluated by the statistical error analysis method and the regression analysis method of mean squared deviation. The DNN model had the best performance by statistical error whereas the CART/SLD model had the worst prediction accuracy. The Mean Square Deviation (MSD) is a method of analyzing the linearity of a model with three components: squared bias (SB), nonunity slope (NU), and lack of correlation (LC). Better model performance was determined by lower SB and LC and higher NU. The results of MSD analysis indicated that the DNN model would provide the best performance and followed by the PM, the NHRH and the CART/SLD in order. This result suggested that the machine learning model would be useful to improve the accuracy of agricultural information using meteorological data.
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