• Journal of vocational education research
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• v.29 no.3
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• pp.23-40
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• 2010

Career guidance refers to services intended to assist students to make educational and occupational choices and to manage their careers. Young students, specially enrolled in vocational high schools, need programs to help them make transitions to the working world and to re-engage with further learning, and career guidance needs to be part of such programs. Teachers assume the critical roles in planning and organizing the career guidance programs in vocational high schools. The program includes career information provision, assessment and self-assessment tools, career counseling, work search, etc. In this study, we developed a research model based upon TRA(theory of reasoned action) developed by Ajzen and Fishbein to investigate the factors influencing the intention to provide career guidance services to students in vocational high schools. Based on 155 survey responses from vocational high school teachers, we show that attitude and subjective norm motivate teachers to provide career guidance services, and that attitude toward career guidance is directly influenced by self-efficacy for career guidance and burden from extra work. It was also confirmed that facilitating condition is the antecedent of self-efficacy. But contrary to our expectation, self-efficacy for career guidance has no significant effect on the intention for providing career guidance services at 5% significance level. In light of these findings, implications for theory and practice are discussed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.310-318
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• 2018

Recently, the importance of big data analysis is increasing as a large amount of data is generated by various devices connected to the Internet with the advent of Internet of Things (IoT). Especially, it is necessary to analyze various large-scale IoT streaming sensor data generated in real time and provide various services through new meaningful prediction. This paper proposes a real-time indoor PM10 concentration prediction LSTM model based on streaming data generated from IoT sensor using AWS. We also construct a real-time indoor PM10 concentration prediction service based on the proposed model. Data used in the paper is streaming data collected from the PM10 IoT sensor for 24 hours. This time series data is converted into sequence data consisting of 30 consecutive values from time series data for use as input data of LSTM. The LSTM model is learned through a sliding window process of moving to the immediately adjacent dataset. In order to improve the performance of the model, incremental learning method is applied to the streaming data collected every 24 hours. The linear regression and recurrent neural networks (RNN) models are compared to evaluate the performance of LSTM model. Experimental results show that the proposed LSTM prediction model has 700% improvement over linear regression and 140% improvement over RNN model for its performance level.

• Journal of The Korean Association For Science Education
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• v.39 no.3
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• pp.337-348
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• 2019

The purpose of this study is to examine epistemic thinking in middle school students in an argument-based inquiry science class. Participants of the study were 93 9th grade students from four classes of a middle school in a metropolitan city. Observations were made over one semester during which argument-based inquiry lessons on five subjects were conducted. Data was collected from argument-based inquiry activity worksheets and student questionnaires. After analysis of epistemic thinking in the written reflections, students were found to have the highest frequency of epistemic metacognitive skills, followed by epistemic cognition, epistemic metacognitive experience, and epistemic metacognitive knowledge. While investigating the effects of an argument-based inquiry science class on student epistemic thinking and after analysis of the reflections written for the first ABI activity and the fifth ABI activity, we found that all of the sub-elements of epistemic thinking have increased. The rate of growth for epistemic cognition is greatest, followed by epistemic metacognitive knowledge and epistemic metacognitive skills. Assessed for epistemic thinking, the level of epistemic thinking improved over the course of the argument-based inquiry science class. The results of the survey show that students actively participating and being recognized for their active participation in the argument-based inquiry science class are helpful in understanding scientific knowledge. Therefore, an argument-based inquiry science class is a teaching and learning program that allows students to understand and experience the epistemic nature of scientific knowledge and its construction through collaboration and agreement.

• Journal of the Korean earth science society
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• v.40 no.2
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• pp.188-199
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• 2019

The purpose of this study was to investigate the tendency of inquiry of earth science content presented in North Korean textbooks of the 2013 National curriculum using Romey's method, and to help use as basic data for better understanding earth science education in North Korea. The content of earth science in the text, figure, question, and activity index of textbooks of Natural Science 1 and 2, Chosun Geography 2 of elementary junior high school, and of Geography 1 of advanced junior high school were all analyzed using Romey's method. The results of this study were as follows: First, the atmospheric science question and the astronomy text showed the tendency of inquiry type. Second, the proportion of oceanography was relatively small. Third, there were many non-inquiry questions or excessive inquiry questions, and both types of questions needed to be balanced. Fourth, there were a tendency that did not emphasize inquiry learning. Finally, the quantitative and qualitative level of inquiry tendency should be improved. In this paper, we propose to use a qualitative method when analyzing earth science content in North Korean textbooks, and suggested that we should further study the comparative analysis of inquiry tendency of earth science content using South and North Korean textbooks.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.65-70
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• 2019

The purpose of this study is to understand the college students' needs for software curriculum which based on surveys from educational satisfaction of the software lecture evaluation, as well as to find out the improvement plan by applying the text content analysis method. The research method used the text content analysis program to calculate the frequency of words occurrence, key words selection, co-occurrence frequency of key words, and analyzed the text center and network analysis by using the network analysis program. As a result of this research, the decent points of the software education network are mentioned with 'lecturer' is the most frequently occurrence after then with 'kindness', 'student', 'explanation', 'coding'. The network analysis of the shortage points has been the most mention of 'lecture', 'wish to', 'student', 'lecturer', 'assignment', 'coding', 'difficult', and 'announcement' which are mentioned together. The comprehensive network analysis of both good and shortage points has compared among key words, we can figure out difference among the key words: for example, 'group activity or task', 'assignment', 'difficulty on level of lecture', and 'thinking about lecturer'. Also, from this difference, we can provide that the lack of proper role of individual staff at group activities, difficult and excessive tasks, awareness of the difficulty and necessity of software education, lack of instructor's teaching method and feedback. Therefore, it is necessary to examine not only how the grouping of software education (activities) and giving assignments (or tasks), but also how carried out group activities and tasks and monitored about the contents of lectures, teaching methods, the ratio of practice and design thinking.

• Korean Journal of Remote Sensing
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• v.35 no.2
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• pp.299-316
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• 2019

The purpose of this study was to analyze landslide susceptibility in the Pyeongchang area using Weight of Evidence (WOE) and Evidential Belief Function (EBF) as probability models and Artificial Neural Networks (ANN) as a machine learning model in a geographic information system (GIS). This study examined the widespread shallow landslides triggered by heavy rainfall during Typhoon Ewiniar in 2006, which caused serious property damage and significant loss of life. For the landslide susceptibility mapping, 3,955 landslide occurrences were detected using aerial photographs, and environmental spatial data such as terrain, geology, soil, forest, and land use were collected and constructed in a spatial database. Seventeen factors that could affect landsliding were extracted from the spatial database. All landslides were randomly separated into two datasets, a training set (50%) and validation set (50%), to establish and validate the EBF, WOE, and ANN models. According to the validation results of the area under the curve (AUC) method, the accuracy was 74.73%, 75.03%, and 70.87% for WOE, EBF, and ANN, respectively. The EBF model had the highest accuracy. However, all models had predictive accuracy exceeding 70%, the level that is effective for landslide susceptibility mapping. These models can be applied to predict landslide susceptibility in an area where landslides have not occurred previously based on the relationships between landslide and environmental factors. This susceptibility map can help reduce landslide risk, provide guidance for policy and land use development, and save time and expense for landslide hazard prevention. In the future, more generalized models should be developed by applying landslide susceptibility mapping in various areas.

• Journal of Science Education
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• v.42 no.3
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• pp.334-351
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• 2018

Teacher's gaze empathy for students in science class is considered to be effective in enhancing the learning effect. Thus, studies on gaze empathy have been conducted, but most of the studies are just to reveal the characteristics of gaze. Therefore, it is necessary to deal with a research to raise the level of science teacher's gaze empathy. The purpose of this study is to develop an instruction consulting strategy based on eye tracking for improving science teachers' gaze empathy. In this study, we selected and analyzed relevant literature on teacher's gaze empathy. We also designed a consulting strategy and then revised the design through expert reviews on validity and reliability. The developed consulting strategy was aimed to improve science teacher's gaze empathy and set quantitative goal based on eye tracking. The consulting strategy consisted of six steps: preparation for consulting, measurement and analysis of teacher's gaze empathy, instruction and feedback of gaze empathy, training for improving gaze empathy, evaluation of consulting result, and completion of the consulting. In addition, the consultation was completed or repeated again through the measurement and evaluation of gaze empathy using eye tracking. The developed consulting strategy has a value in that it provides an alternative with quantitative diagnosis and prescription for improving gaze empathy. The strategy can contribute to enhance teacher professional competency through the analysis of teaching behavior.

• Journal of the Korean Society of Radiology
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• v.13 no.4
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• pp.629-635
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• 2019

In term of the factors affecting psychosocial adjustment of breast cancer patients, their quality of life after surgical operation, radiation, and chemotherapy were systematically meta-analyzed. As a result, their qualities of life of the patients that had radiation therapy was the lowest right after the therapy, and gradually increased after the end of the therapy. However, after six months, their quality of life failed to reach the same level before the therapy. They had depression and side effects the most right after the therapy, and somewhat reduced them after the end of the therapy. In case of surgical operation, the more they were educated, the more they had psychosocial adjustment, and the more they had a medical examination and took out an insurance policy, the more they had psychosocial adjustment. In case of chemotherapy, their cognitive function is influenced so that they have impairments in memory, learning, and thinking stages. Since subjective cognitive impairment has a relationship with depression, it is necessary to monitor depression of chemotherapy patients. Given the results of this systematic meta-analysis, when three types of therapies (surgical operation, radiation therapy, and chemotherapy) are applied to patients with breast cancer, it is necessary to recognize their psychosocial adjustment, depression, anxiety, and quality of life in the nursing and radiation therapy fields and thereby to introduce an intervention program for a holistic approach.

• Journal of the Korean Society of Earth Science Education
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• v.12 no.2
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• pp.119-130
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• 2019

The TIMSS assessment is conducted every four years, and Korean fourth grade cohort in TIMSS 2011 participated in TIMSS 2015 again as eighth graders, which produced the first achievement data of the cohort group of elementary and middle schools. In this study, in order to investigate the causes of the decline in Korean students' science achievement with grade changes from the fourth to the eighth grade, we analyzed educational context variables such as characteristics of students, teachers, and classroom instructions of the top 5 achievement countries participated in both TIMSS 2011 and TIMSS 2015. According to the results, students' sense of school belonging increased, whereas students' positive attitudes toward science teaching decreased with the grade change from the fourth to the eighth. As for the teacher characteristics, the teacher's professional development activity increased, and the teacher's confidence in science teaching showed similar tendency to the international average. Regarding classroom instruction characteristics, the frequency of inquiry-related science activities was highest at the fourth grade, and lower than the international average at the eighth grade. Based the results, we suggested implications for science teaching and learning as well as further studies including development of differentiated strategy by the school level to improve students' achievement, the necessity of converting into more student-engaging science classes, and the necessity of in-depth study on the teacher related educational contextual variables.

• Journal of Digital Convergence
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• v.17 no.9
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• pp.135-145
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• 2019

Prolonged recession has caused the youth unemployment rate in Korea to remain at a high level of approximately 10% for years. Recently, the number of unemployed Koreans in their 30s and 40s has shown an upward trend. To expand the government's employment promotion and unemployment benefits from youth-centered policies to diverse age groups, including people in their 30s and 40s, prediction models for different age groups are required. Thus, we aimed to develop unemployment prediction models for specific age groups (30s and 40s) using available unemployment rates provided by Statistics Korea and Google search queries related to them. We first estimated multiple linear regressions (Model 1) using seasonal autoregressive integrated moving average approach with relevant unemployment rates. Then, we introduced Google search queries to obtain improved models (Model 2). For both groups, consequently, Model 2 additionally using web queries outperformed Model 1 during training and predictive periods. This result indicates that a web search query is still significant to improve the unemployment predictive models for Koreans. For practical application, this study needs to be furthered but will contribute to obtaining age-wise unemployment predictions.