• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.597-604
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• 2020

This is a narrative research study conducted on the subject in order to understand the relationship between the meta-cognition, learning flow, and problem solving ability of nursing students in online class, and to find out the factors that influence problem solving ability, 88 students enrolled in 2nd and 3rd grade students who participated in online classes at G city universities. The analysis method was analyzed by means, standard deviation, t-test, one-way ANOVA, Pearson correlation, and stepwise multiple regression using SPSS version WIN 23.0. As a result of the study, the difference between learning flow and problem-solving ability according to general characteristics was significantly different depending on the perception of nurses after learning and the motivation for admission to the department of nursing, and the problem-solving ability was positively correlated with metacognition and learning flow. There was a relationship, and metacognition and learning flow were significant variables that influenced problem solving ability. The conclusion of the study is considered to be the basic data for the development of a systematic program that can increase the learning flow and meta-cognition to increase problem solving ability amid the change from nursing education to online classes, and to change the teaching method.

• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.495-509
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• 2020

This study is a theoretical research to explore ways to effectively learn AI in the age of intelligent information driven by artificial intelligence (hereinafter referred to as AI). The emphasis is on presenting a teaching method to make AI education accessible not only to students majoring in mathematics, statistics, or computer science, but also to other majors such as humanities and social sciences and the general public. Given the need for 'Explainable AI(XAI: eXplainable AI)' and 'the importance of storytelling for a sensible and intelligent machine(AI)' by Patrick Winston at the MIT AI Institute [33], we can find the significance of research on AI storytelling learning model. To this end, we discuss the possibility through a pilot study targeting general students of an university in Daegu. First, we introduce the AI storytelling(AI+ST) learning method[30], and review the educational goals, the system of contents, the learning methodology and the use of new AI tools in the method. Then, the results of the learners are compared and analyzed, focusing on research questions: 1) Can the AI+ST learning method complement algorithm-driven or developer-centered learning methods? 2) Whether the AI+ST learning method is effective for students and thus help them to develop their AI comprehension, interest and application skills.

• Journal of the Korean Applied Science and Technology
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• v.38 no.1
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• pp.75-87
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• 2021

The purpose of this investigate the effect of the educational institution service quality f the government-supported beauty-related educational institution on the students' perceived usefulness and career preparation behavior. Participations in the study collected 362 students at a government-funded educational institution located in Seoul and Gyeon-ggi by a convenience sampling method. The collected data was analyzed through descriptive statistics, factor analysis, reliability analysis, correlation analysis and multiple regression analysis using SPSS statistical package version 26.0 version. The results derived through a series of research procedures are as follows: First, educational service quality, perceived usefulness and career preparation behavior showed a statistically significant positive(+) correlation. Second, it was found that educational service quality had a statistically significant positive(+) effect on perceived usefulness. Third, the educational service quality showed a positive(+) influence on the career preparation behavior of information collection activities and job preparation activities. Fourth, the perceived usefulness was found to have a statistically significant positive(+) effect on the career preparation behavior of the information collection activities ad job preparation activities. The results of this research can be used as basic data to increase the efficiency of beauty-related government funding projects by evaluating the quality of education services of state-funded beauty related educational institutions.

• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1711-1720
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• 2020

Particulate matter (PM) that has been artificially generated during the recent of rapid industrialization and urbanization moves and disperses according to weather conditions, and adversely affects the human skin and respiratory systems. The purpose of this study is to predict the PM10 concentration in Seoul using meteorological factors as input dataset for multiple linear regression (MLR), support vector machine (SVM), and random forest (RF) models, and compared and evaluated the performance of the models. First, the PM10 concentration data obtained at 39 air quality monitoring sites (AQMS) in Seoul were divided into training and validation dataset (8:2 ratio). The nine meteorological factors (mean, maximum, and minimum temperature, precipitation, average and maximum wind speed, wind direction, yellow dust, and relative humidity), obtained by the automatic weather system (AWS), were composed to input dataset of models. The coefficients of determination (R2) between the observed PM10 concentration and that predicted by the MLR, SVM, and RF models was 0.260, 0.772, and 0.793, respectively, and the RF model best predicted the PM10 concentration. Among the AQMS used for model validation, Gwanak-gu and Gangnam-daero AQMS are relatively close to AWS, and the SVM and RF models were highly accurate according to the model validations. The Jongno-gu AQMS is relatively far from the AWS, but since PM10 concentration for the two adjacent AQMS were used for model training, both models presented high accuracy. By contrast, Yongsan-gu AQMS was relatively far from AQMS and AWS, both models performed poorly.

• Journal of Wetlands Research
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• v.23 no.1
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• pp.1-6
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• 2021

The average annual rainfall in Busan to increase, and in case of Oncheon-Chen in Busan, frequent flooding occurred frequently. The middle and lower reaches of the Oncheon-Chen are relatively flat and urban areas are developed. Therefore, due to the frequent flooding of rivers and the large flood damage, a method of effectively eliminating the flow rate of Oncheon-Chen in the event of heavy rain is needed. In this study, underground waterway was established in the east of Hoedong-Reservoir as a measure to reduce floods in hot springs and simulated with EPA-SWMM. The information needed to construct the basin was utilized by GIS. In middle part of the Suyeong-Gang, there is a Hoedong-Reservoir and a dam is installed and has better conditions than the Nakdong-Gang. It also analyzed the effect of the Oncheon-Chen flow through the underground waterway on the Suyeong-Gang when it was transferred to the Hoedong-Reservoir. It was analyzed that the flood reduction rate at the flood risk points set up in this study was reduced by 24.64% on average when the underground waterway was installed, and the inflow of the water into the Suyeong-Gang increased by 1% on average when the flow rate was excluded by the Suyeong-Gang.

• Journal of The Korean Association of Information Education
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• v.25 no.2
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• pp.423-436
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• 2021

In the future, artificial intelligence (AI) technology is expected to become a general-purpose technology (GPT), and it is predicted that AI competency will become an essential competency. Several nations around the world are fostering experts in the field of AI to achieve technological proficiency while working to develop the necessary infrastructure and educational environment. In this study, we investigated the status of software education at the liberal arts level at 31 universities in Seoul, along with precedents from domestic and foreign AI education research. Based on this, we concluded that an AI literacy education model is needed to link software education at the liberal arts level with professional AI education. And we classified 20 AI-related lectures released in the KOCW according to the AI literacy competencies required; based on the results of this classification, we propose a model for AI literacy education in the liberal arts for undergraduate students. The proposed AI literacy education model may be considered as AI·SW convergence to experience AI along with literacy in the humanities, deviating from the existing theoretical and computer-science-based approach. We expect that our proposed AI literacy education model can contribute to the proliferation of AI.

• Journal of Korean Library and Information Science Society
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• v.52 no.2
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• pp.145-166
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• 2021

The study was aimed at verifying the effectiveness of Book-Coding reading education as a reader activity of older elementary school children at a time when high-dimensional thinking abilities were formed. To this end, 30 fifth-grade children of N Elementary School in N-si, Gyeonggi-do, comprised of 15 students from a reading education program using Book-Coding, and 15 students from a reading comprehension program, and applied the reading education program over a total of 12 sessions. The main results of the study are summarized as follows. First, when the effects of the convergence reading education program using Book-Coding on the logical thinking ability of the students in the upper grades in the elementary school were analyzed, all the six sub-factors of logical thinking ability, that is, conservation logic, proportional logic, variable controlling logic, probabilistic logic, correlational inference logic, and combinational logic, were proved to have statistically more meaningful difference than the group writing a book report. Second, the analysis result of the influence of the convergence reading education program using Book-Coding on the creativity of the students in the upper grades of the elementary school showed that all the 13 elements of curiosity, persistence, effectiveness, independence, adventurousness, openness, knowledge, imagination, originality, sensitivity, fluency, flexibility, and accuracy were statistically meaningfully different compared to the book report group. Third, when it was analyzed how the convergence reading education program using Book-Coding affected the creative personality of the elementary school students, all the six factors of curiosity, task commitment, independence, awareness of risk, and openness of thinking, and aesthetics were found out to have a statistically more meaningful difference than the group that wrote a book report.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.119-126
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• 2022

The reported risk factors for gallstone disease (GD) are old age, female sex, obesity, metabolic syndrome and migrants. Many younger adults tend to live in Jeju City, where transportations are convenient and commercial activities are active. Whereas, older people tend to live in Seogwipo City, because they engaged in fisheries and agriculture. Rates of migrants and old age could affect the prevalence of GD among residents in two regions. Therefore, the purpose of this study was to compare the GD prevalence and analyze risk factors affecting GD including residencies. A total of 13,050 subjects who visited a single health medical check-up center on Jeju Island between 2012 and 2019 were included. We performed univariate and multivariate analysis to identify risk factors for GD. The prevalence of GD among residents were 5.7% in Jeju City and 5.8% in Seogwipo City, respectively. Multivariate analysis revealed that age (P=0.008), body mass index (P=0.044), high-density lipoprotein cholesterol (P=0.006) and gamma-glutamyl transferase (P=0.013) were independent factors affecting GD. The old age, mean higher body mass index, gamma-glutamyl transferase and mean lower high-density lipoprotein cholesterol were independent risk factors affecting GD. However, residencies did not affect the prevalence of GD.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.834-841
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• 2022

Recently, applying artificial intelligence technologies in various fields of production has drawn an upsurge of research interest due to the increase for smart factory and artificial intelligence technologies. A great deal of effort is being made to introduce artificial intelligence algorithms into the defect detection task. Particularly, detection of defects on the surface of metal has a higher level of research interest compared to other materials (wood, plastics, fibers, etc.). In this paper, we compare and analyze the speed and performance of defect classification by combining machine learning techniques (Support Vector Machine, Softmax Regression, Decision Tree) with dimensionality reduction algorithms (Principal Component Analysis, AutoEncoders) and two convolutional neural networks (proposed method, ResNet). To validate and compare the performance and speed of the algorithms, we have adopted two datasets ((i) public dataset, (ii) actual dataset), and on the basis of the results, the most efficient algorithm is determined.

• Journal of Creative Information Culture
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• v.7 no.4
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• pp.243-255
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• 2021

The purpose of this study is to investigate the effect of software education based on physical computing on the CT ability of elementary school students. To this end, previous studies related to physical computing software education and software education in the 2015 revised curriculum were analyzed. In addition, COBL was selected among many physical computing tools on the market in consideration of the level and characteristics of learners in the school to conduct the study, and 'Professor Lee Jae-ho's AI Maker Coding with COBL' was used as the textbook. This study was conducted for 10 sessions on 135 students in 6 classes in 6th grade of H Elementary School located in Pyeongtaek, Gyeong gi-do. The results of this study are as follows. First, it was confirmed that physical computing software education linked to real life was effective in improving the CT ability of elementary school students. Second, the change in competency of CT ability by sector improved evenly from 8 to 30 points in the pre-score and post-score of computing thinking ability. Third, in this study, it was confirmed that 87% of students were very positive as a result of a survey of satisfaction with classes after real-life physical computing software education. We hope that follow-up studies will help select various regions across cities and rural areas, and prove that real-life physical computing software education for various learner members, including large and small schools, will help elementary school students improve their CT ability.