• Title/Summary/Keyword: Big Data Education

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A Meta-analysis of the Effect of Simulation Based Education - Korean Nurses and Nursing Students - (시뮬레이션 기반 교육 효과에 대한 메타분석 - 국내 간호사와 간호대학생을 중심으로 -)

  • Kim, SinHayng;Ham, younsuk
    • The Journal of Korean Academic Society of Nursing Education
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    • v.21 no.3
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    • pp.308-319
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    • 2015
  • Purpose: The purpose of this study was to identify the effects size of simulation education targeting korean nurses and nursing students. Methods: Meta-analysis was conducted with 48 papers in domestic master and doctorate degree dissertations and academic journals from 2000 to 2014. Results: The entire effect size in simulation education was relevant to big effect size. Regarding the effect size of individual variables, nurse was identified to have biggest effect size in study subject, standardized patient was identified to have biggest effect size in simulation methods and pediatric nursing was identified to have biggest effect size in study subjects. Effect size in each effect variable was highest in psychomotor domain. Conclusion: This study identified the effect size of simulation education and provided the basic data to contribute to the quality improvement of simulation education which is based on the reasons.

News Big Data Analysis of 'Tap Water Larvae' Using Topic Modeling Analysis (토픽 모델링을 활용한 '수돗물 유충' 뉴스 빅데이터 분석)

  • Lee, Su Yeon;Kim, Tae-Jong
    • The Journal of the Korea Contents Association
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    • v.20 no.11
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    • pp.28-37
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    • 2020
  • This study was conducted to propose measures to improve crisis response to environmental issues by analyzing the news big data on the 'tap water larvae' situation and identifying related major keywords and topics. To accomplish this, 1,975 cases of 'tap water larvae' reported between July 13 to August 31, 2020 were divided into three periods and analyzed using topical modeling techniques. The analysis output 15 topics for each period. According to the result, the 'tap water larvae' incident, as reported in the media, is divided into the occurrence, diffusion, and rectification stages. The government's response and civilian risk consciousness and reaction could also be seen. Based on the result, the following measures to respond to environment risk is proposed. First, it is necessary to explore the various intertwined context with the 'tap water larvae' incident at its core and develop responsiveness to environmental problems through education which forms integrated views. Second, a role to monitor the environment must be implemented and civilian-participated environmental information must be shared through the application of internet communities. Third, the cultivation and deployment of environmental communicators who provide and communicate fast and accurate environment information is required. This study, as the first in Korea to use the topic modeling analysis method based on big data related to 'tap water larvae', has academic significance in that it has empirically and systematically analyzed environmental issues which appear as unstructured data. It also political significance as it suggests ways to improve environmental education and communication.

Development and Application of Middle School STEAM Program Using Big Data of World Wide Telescope (WWT 빅데이터를 활용한 중학교 STEAM 프로그램 개발 및 적용)

  • You, Samgmi;Kim, Hyoungbum;Kim, Yonggi;Kim, Heoungtae
    • Journal of the Korean Society of Earth Science Education
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    • v.14 no.1
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    • pp.33-47
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    • 2021
  • This study developed a big data-based STEAM (Science, Technology, Engineering, Art & Mathematics) program using WWT (World Wide Telescope), focusing on content elements of 'solar system', 'star and universe' in the 2015 revised science curriculum, and in order to find out the effectiveness of the STEAM program, analyzed creative problem solving, STEAM attitude, and STEAM satisfaction by applying it to one middle school 176 students simple random sampled. The results of this study are as follows. First, we developed a program to encourage students to actively and voluntarily participating, utilizing the astronomical data platform WWT. Second, in the paired t-test based on the difference between the pre- and post-scores of the creative problem solving measurement test, significant statistical test results were shown in 'idea adaptation', 'imaging', 'analogy', 'idea production' and 'elaboration' sub-factors except 'attention task' sub-factor (p < .05). Third, in the paired t-test based on the difference between the pre- and post-scores of the STEAM attitude test, significant statistical test results were shown in 'interest', 'communication', 'self-concept', 'self-efficacy' and 'science and engineering career choice' sub-factors except 'consideration' and 'usefulness / value recognition' sub-factors (p < .05). Fourth, in the STEAM satisfaction test conducted after class application, the average values of sub-factors were 3.16~3.90. The results indicated that students' understanding and interest in the science subject improved significantly through the big data-based STEAM program using the WWT.

Sentimental Analysis of SW Education News Data (SW 교육 뉴스데이터의 감성분석)

  • Park, SunJu
    • Journal of The Korean Association of Information Education
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    • v.21 no.1
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    • pp.89-96
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    • 2017
  • Recently, a number of researches actively focus on the contents and sensitivity of information distributed through SNS as smartphones and SNS gained its popularity. In this paper, we collected online news data about SW education, extracted words after morphological analysis, and analyzed emotions of collected news data by calculating sentimental score of each news datum. Also, the accuracy of the calculated sentimental score was examined. As a result, the number of news related to 'SW education' in the collection period was about 189 per month, and the average of sentimental score was 0.7, which signifies the news related to 'SW education' was emotionally positive. We were positive about the importance of SW education and the policy implementation, but there were negative views on the specific method for the realization. That is, a lack of SW education environment and its education method, a problem related to improvement of SW developers and improvement of their labor conditions, and increase of private education in coding were the factors for the negative viewers.

Parental Participation and Parenting Stress According to the Big Five Personality Types of Fathers With Young Children (유아기 자녀를 둔 아버지의 Big5성격유형에 따른 양육참여 및 양육스트레스)

  • JongSeung, Yun
    • Korean Journal of Childcare and Education
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    • v.18 no.6
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    • pp.145-162
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    • 2022
  • Objective: The purpose of this study was to examine the differences in parental involvement and parenting stress according to the father's personality type. Methods: The subjects of this study were 302 fathers with children aged three to five living in Seoul, and a survey was conducted on their Big Five personality types, parental involvement, and parenting stress.The collected data were analyzed using K-means cluster analysis and covariance analysis. Results: In this study, fathers' personality types were classified into four types: 'sincerity, friendship, openness'(21.5%), 'neuroticism'(27.8%), 'sincerity'(29.4%), and 'low sincerity'(21.1%). These are the exact same Fathers in the 'sincere, friendly, open' group showed higher parental involvement and lower parental stress, while fathers in the 'neurotic' group showed lower parenting involvement and higher parenting stress. Conclusion/Implications: There was a difference in parental involvement and parenting stress according to the father's personality type.Based on these results, it is expected that the understanding of the father's personality will be come clearer and the foundation for constructing a program related to parenting which considers personality types will be established.

Research on Personalized Course Recommendation Algorithm Based on Att-CIN-DNN under Online Education Cloud Platform

  • Xiaoqiang Liu;Feng Hou
    • Journal of Information Processing Systems
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    • v.20 no.3
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    • pp.360-374
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    • 2024
  • A personalized course recommendation algorithm based on deep learning in an online education cloud platform is proposed to address the challenges associated with effective information extraction and insufficient feature extraction. First, the user potential preferences are obtained through the course summary, course review information, user course history, and other data. Second, by embedding, the word vector is turned into a low-dimensional and dense real-valued vector, which is then fed into the compressed interaction network-deep neural network model. Finally, considering that learners and different interactive courses play different roles in the final recommendation and prediction results, an attention mechanism is introduced. The accuracy, recall rate, and F1 value of the proposed method are 0.851, 0.856, and 0.853, respectively, when the length of the recommendation list K is 35. Consequently, the proposed strategy outperforms the comparison model in terms of recommending customized course resources.

A Comparison Study on the Risk and Accident Characteristics of Personal Mobility (개인이동형 교통수단(PM) 유형별 사고특성 및 위험도 비교연구)

  • Lee, Soo Il;Kim, Seung Hyun;Kim, Tae Ho
    • Journal of the Korean Society of Safety
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    • v.32 no.3
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    • pp.151-159
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    • 2017
  • This study deals with characteristics and risk of a PM based on user survey result, road driving test and data analysis of PM accident. Text mining method is applied to extract PM accident data from Big Data, which are claim data of private insurance company. Road driving test and survey on safety, convenience, noise, overtake ability, steering ability, and climbing ability of PM are performed to evaluate user's safety and convenience considering domestic road condition. As the result of claim data analysis, annual average increase rate of PM accident is 47.4% and average compensation of personal mobility is higher than that of bicycle by maximum 1.5 times. 79.8% of PM accident is self-caused accident due to unskilled driving and age-specific diagnosis rate of driver over 60 is higher than that of under 60. Diagnosis rate of over 60 at lower limb, foot, rib and spine is especially higher than that of under 60. As the result of road driving test and user survey, satisfaction level on safety and convenience of PM is evaluated as close to that of bicycle and satisfaction level of PM is increased after boarding. Overtake ability, steering ability, and climbing ability of PM are evaluated as same or better than that of bicycle but warning equipment to pedestrian or bike such as horn is required because noise level of PM during driving is too low. Finally, user survey result shows that bicycle road is suitable for PM and safety standard, advance-education and insurance are required for PM. It is suggested that drivers' license for PM can be replaced by advance-education. Results of this study can be used to prepare safety measures and legal basis for PM operation.

Big Data Visualization Analysis of Education Occupations with High Employment Rates by Age and Educational Background for Career-Interrupted Women (경력단절여성을 위한 연령 및 학력별 취업률이 높은 교육직종 빅 데이터 시각화 분석)

  • Lee, Jeongwon;Lee, Choong Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.8
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    • pp.1019-1025
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    • 2021
  • Support policies such as education and training for re-employment of career-interrupted women are being implemented, but they are not being effectively employed. In addition, it is difficult for women with high educational background to re-enter, such as having to revise their previous careers or plan a new career for re-employment. In the previous studies, there was insufficient research to solve fundamental problems for re-employment, such as promising jobs with high employment opportunities. Therefore, when developing a curriculum for women with career interruptions, it was felt the need to select educational occupations that would be helpful in finding employment by age and educational background of the trainees. In this study, data on vocational training education of women with career interruptions were used to analyze the educational occupations with the highest employment rate by age and educational background.

Analysis on the Current Status of the Fourth Industrial Revolution-Oriented Curriculum of the Computer and Software-Related Majors Based on the Standard Classification (표준분류에 기준한 컴퓨터 및 소프트웨어 관련 전공의 제4차 산업혁명중심 교육과정 운영 현황 분석)

  • Choi, Jin-Il;Choi, Chul-Jae
    • The Journal of the Korea institute of electronic communication sciences
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    • v.15 no.3
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    • pp.587-592
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    • 2020
  • This paper analyzed the curriculum of computer and software-related majors educating the core IT-related skills needed for the 4th Industrial Revolution. The analysis was conducted on 158 majors classified as applied software, computer science and computer engineering according to the standard classification of university education units by the Standard Classification Committee of the Korean Council of University Education. The current status of introduction of curricular divided into the fields of Internet of Things(IoT) & mobile, cloud & big data, artificial intelligence(AI), and information security was analyzed among the contents of education in the relevant departments. According to the analysis, an average of 81.6% of the majors for each group of curricular organized related subjects into the curriculum. The Curriculum Response Index for the 4th industrial revolution(CRI4th) by major, calculated by weighting track operations by education sector, averaged 27.5 point out of 100 point. And the IoT & mobile sector had the highest score of 42.3 points.

Improvement of Accessibility to Dental Care due to Expansion of National Health Insurance Coverage for Scaling in South Korea (치석제거 요양급여 확대 정책으로 인한 치과의료 접근성 향상)

  • Huh, Jisun;Nam, SooHyun;Lee, Bora;Hu, Kyung-Seok;Jung, Il-Young;Choi, Seong-Ho;Lee, Jue Yeon
    • The Journal of the Korean dental association
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    • v.57 no.11
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    • pp.644-653
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    • 2019
  • Since 2013, adults aged over 20 can receive national health insurance scaling once a year in South Korea. In this study, we analyzed the usage status of national health insurance care service for periodontal disease in 2010-2018 by using Healthcare big data of the Health Insurance Review and Assessment Service. The increase rate of the dental care users was very high at 7.8 and 11.2% in 2013 and 2014, respectively. These are higher than the increase rate of all medical institution users, which is between -1.7 and 3.7%. In 2017, the rate of dental use was 44.4%, which has increased more than 10% compared to 2012. Percent receiver of national health insurance scaling was 19.5% in 2017. The 20s had the highest rate of 23.2%. The rate decreased with age. Based on these results, it can be evaluated that the expansion of national health insurance coverage for scaling improves accessibility to dental care. A more long-term assessment of the effect of periodic dental examination and scaling on reducing the prevalence of periodontal disease is needed. National health insurance coverage should be extended to oral hygiene education and supportive periodontal therapy in order to prevent periodontal disease.

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