• Title/Summary/Keyword: 교육 데이터 모델

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Factors Influencing Character of Nursing Students (간호대학생의 인성에 영향을 미치는 요인)

  • Nam, Soung-Mi;Park, Jeong-Sook;Shin, Eun-Jung
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.8
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    • pp.56-65
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    • 2019
  • The purpose of this study was to identify factors associated with character of nursing students using ecological theory. A descriptive cross-sectional study was conducted with 296 nursing students. Collected data from self report questionnaires were analyzed using descriptive statistics, t-test, ANOVA and multiple regression with SPSS WIN 21.0. The Results of this study were as follows. A total of 2 models were examined according to individual, microsystem in ecological system theory. In the first model including individual factors, positive emotion, communication ability were significant factors explain character of nursing students. In the second model adding micro system factors family strength and major satisfaction found to be significant factors. The prediction factors of nursing student' character were communication ability (${\beta}=.431$, p<.001), major satisfaction (${\beta}=.310$, p<.001) and family strength (${\beta}=.176$, p<.001). The explanation power was 55.6%. These results showed that factors affecting character of nursing students are communication ability, major satisfaction, and family strength. Therefore, we suggest to develop various character education programs considering these factors.

Accuracy Analysis for Slope Movement Characterization by comparing the Data from Real-time Measurement Device and 3D Model Value with Drone based Photogrammetry (도로비탈면 상시계측 실측치와 드론 사진측량에 의한 3D 모델값의 정확도 비교분석)

  • CHO, Han-Kwang;CHANG, Ki-Tae;HONG, Seong-Jin;HONG, Goo-Pyo;KIM, Sang-Hwan;KWON, Se-Ho
    • Journal of the Korean Association of Geographic Information Studies
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    • v.23 no.4
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    • pp.234-252
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    • 2020
  • This paper is to verify the effectiveness of 'Hybrid Disaster Management Strategy' that integrates 'RTM(Real-time Monitoring) based On-line' and 'UAV based Off-line' system. For landslide prone area where sensors were installed, the conventional way of risk management so far has entirely relied on RTM data collected from the field through the instrumentation devices. But it's not enough due to the limitation of'Pin-point sensor'which tend to provide with only the localized information where sensors have stayed fixed. It lacks, therefore, the whole picture to be grasped. In this paper, utilizing 'Digital Photogrammetry Software Pix4D', the possibility of inference for the deformation of ungauged area has been reviewed. For this purpose, actual measurement data from RTM were compared with the estimated value from 3D point cloud outcome by UAV, and the consequent results has shown very accurate in terms of RMSE.

Longitudinal Mediated Effects of Informal Labeling on the Relationship between Adolescent Abuse and Academic Achievement: Application of Labeling Theory with Autoregressive Cross-Lagged Modeling (청소년의 피학대경험이 학업성취에 미치는 영향에 대한 비공식낙인의 종단적 매개효과 검증: 낙인이론과 자기회귀교차지연 모델을 적용하여)

  • Taekho Lee ;Yoonsun Han
    • Korean Journal of Culture and Social Issue
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    • v.22 no.4
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    • pp.567-593
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    • 2016
  • This study examined longitudinal mediated effects of informal labeling on the relationship between adolescent abuse and academic achievement using autoregressive cross-lagged modeling. Data were obtained from the second, third, and fourth waves of the middle school student cohort (N=3,168) of the Korean Youth Panel Survey. The major longitudinal findings of this study are as follows: First, adolescent abuse was found to have a positive association with future informal labeling. Second, informal labeling was found to have a negative association with future academic achievement. Finally, the longitudinal relationship between adolescent abuse and academic achievement was partially mediated by informal labeling. Based on these results, this study suggests directions for adolescent abuse prevention. The need for education and prevention of informal labeling was discussed, as well as the direction of intervention programs for adolescents with experience of informal labeling. Furthermore, this study may provide empirical evidence for labeling theory and contribute to increasing awareness on the longitudinal influence of adolescent abuse and informal labeling.

Factors Affecting Female College Students' Reproductive Health Information Seeking Behaviors on the Internet (여대생의 인터넷 생식건강정보 탐색에 영향을 미치는 요인 연구)

  • Hyunsoo Yoon;Sanghee Oh;Yeongmi Lee
    • Journal of the Korean Society for information Management
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    • v.41 no.1
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    • pp.389-409
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    • 2024
  • The purpose of this study is to identify the factors affecting female college students' behaviors in seeking reproductive health information on the Internet and to explore the relationships among these factors. Based on the Health Belief Model(HBM) and the Theory of Planned Behavior(TPB), perceived sensitivity, perceived severity, perceived benefit, perceived barriers, subjective norms, perceived behavioral control, and affective evaluation were defined as key factors, and the study was designed accordingly. An online survey was distributed to female college students in Seoul through the university student's online community, 'Everytime.' The results showed that the intention of female college students to seek reproductive health information via the Internet was associated with higher perceived sensitivity, perceived benefit, and subjective norms, and lower perceived barriers. There were statistically significant differences between groups in terms of sexual experiences, experience with reproductive system disorders, and the level of health interest. We believe that this research outcome will contribute to assessing the level of awareness regarding reproductive health among female college students, thereby aiding in the development of online health information literacy education or related service programs by university libraries, health institutions, and similar entities targeting female college students.

Verification the Systems Thinking Factor Structure and Comparison of Systems Thinking Based on Preferred Subjects about Elementary School Students' (초등학생의 시스템 사고 요인 구조 검증과 선호 과목에 따른 시스템 사고 비교)

  • Lee, Hyonyong;Jeon, Jaedon;Lee, Hyundong
    • Journal of The Korean Association For Science Education
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    • v.39 no.2
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    • pp.161-171
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    • 2019
  • The purposes of this study are: 1) to verify the systems thinking factor structure of elementary school students and 2) to compare systems thinking according to their preferred subjects in order to get implications for following research. For the study, pre-tests analyze data from 732 elementary school students using the STMI (Systems Thinking Measuring Instrument) developed by Lee et al. (2013). And exploratory factor analysis was conducted to identify the factor structure of the students. Based on the results of the pre-test, the expert group council revised the STMI so that elementary school students could respond to the 5-factor structure that STMI intended. In the post-test, 503 data were analyzed by modified STMI and exploratory factor analysis was performed. The results of the study are as follows: First, in the pre-test, elementary school students responded to the STMI with a test paper consisting of two factors (personal internal factors and personal external factors). The total reliability of the instrument was .932 and the reliability of each factor was analyzed as .857 and .894. Second, for modified STMI, elementary school students responded a 4-factor instrument. Team learning, Shared Vision, and Personal Mastery were derived independent factors, and mental model and systems analysis were derived 1-factor. The total reliability of the instrument was .886 and the reliability of each factor was analyzed as .686 to .864. Finally, a comparison of systems thinking according to preferred subjects showed a significant difference between students who selected science (engineering) group and art (music and physical education). In conclusion, it was confirmed that statistically meaningful results could be obtained using STMI modified by term and sentence structure appropriate for elementary school students, and it is a necessary to study the relation of systems thinking with various student variables such as the preferred subjects.

Probability-based Pre-fetching Method for Multi-level Abstracted Data in Web GIS (웹 지리정보시스템에서 다단계 추상화 데이터의 확률기반 프리페칭 기법)

  • 황병연;박연원;김유성
    • Spatial Information Research
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    • v.11 no.3
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    • pp.261-274
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    • 2003
  • The effective probability-based tile pre-fetching algorithm and the collaborative cache replacement algorithm are able to reduce the response time for user's requests by transferring tiles which will be used in advance and determining tiles which should be removed from the restrictive cache space of a client based on the future access probabilities in Web GISs(Geographical Information Systems). The Web GISs have multi-level abstracted data for the quick response time when zoom-in and zoom-out queries are requested. But, the previous pre-fetching algorithm is applied on only two-dimensional pre-fetching space, and doesn't consider expanded pre-fetching space for multi-level abstracted data in Web GISs. In this thesis, a probability-based pre-fetching algorithm for multi-level abstracted in Web GISs was proposed. This algorithm expanded the previous two-dimensional pre-fetching space into three-dimensional one for pre-fetching tiles of the upper levels or lower levels. Moreover, we evaluated the effect of the proposed pre-fetching algorithm by using a simulation method. Through the experimental results, the response time for user requests was improved 1.8%∼21.6% on the average. Consequently, in Web GISs with multi-level abstracted data, the proposed pre-fetching algorithm and the collaborative cache replacement algorithm can reduce the response time for user requests substantially.

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A Study on the Medical Application and Personal Information Protection of Generative AI (생성형 AI의 의료적 활용과 개인정보보호)

  • Lee, Sookyoung
    • The Korean Society of Law and Medicine
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    • v.24 no.4
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    • pp.67-101
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    • 2023
  • The utilization of generative AI in the medical field is also being rapidly researched. Access to vast data sets reduces the time and energy spent in selecting information. However, as the effort put into content creation decreases, there is a greater likelihood of associated issues arising. For example, with generative AI, users must discern the accuracy of results themselves, as these AIs learn from data within a set period and generate outcomes. While the answers may appear plausible, their sources are often unclear, making it challenging to determine their veracity. Additionally, the possibility of presenting results from a biased or distorted perspective cannot be discounted at present on ethical grounds. Despite these concerns, the field of generative AI is continually advancing, with an increasing number of users leveraging it in various sectors, including biomedical and life sciences. This raises important legal considerations regarding who bears responsibility and to what extent for any damages caused by these high-performance AI algorithms. A general overview of issues with generative AI includes those discussed above, but another perspective arises from its fundamental nature as a large-scale language model ('LLM') AI. There is a civil law concern regarding "the memorization of training data within artificial neural networks and its subsequent reproduction". Medical data, by nature, often reflects personal characteristics of patients, potentially leading to issues such as the regeneration of personal information. The extensive application of generative AI in scenarios beyond traditional AI brings forth the possibility of legal challenges that cannot be ignored. Upon examining the technical characteristics of generative AI and focusing on legal issues, especially concerning the protection of personal information, it's evident that current laws regarding personal information protection, particularly in the context of health and medical data utilization, are inadequate. These laws provide processes for anonymizing and de-identification, specific personal information but fall short when generative AI is applied as software in medical devices. To address the functionalities of generative AI in clinical software, a reevaluation and adjustment of existing laws for the protection of personal information are imperative.

Re-validation of the Revised Systems Thinking Measuring Instrument for Vietnamese High School Students and Comparison of Latent Means between Korean and Vietnamese High School Students (베트남 고등학생을 대상으로 한 개정 시스템 사고 검사 도구 재타당화 및 한국과 베트남 고등학생의 잠재 평균 비교)

  • Hyonyong Lee;Nguyen Thi Thuy;Byung-Yeol Park;Jaedon Jeon;Hyundong Lee
    • Journal of the Korean earth science society
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    • v.45 no.2
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    • pp.157-171
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    • 2024
  • The purposes of this study were: (1) to revalidate the revised Systems Thinking Measuring Instrument (Re_STMI) reported by Lee et al. (2024) among Vietnamese high school students and (2) to investigate the differences in systems thinking abilities between Korean and Vietnamese high school students. To achieve this, data from 234 Vietnamese high school students who responded to translated Re_STMI consisting of 20 items and an Scale consisting of 20 items were used. Validity analysis was conducted through item response analysis (Item Reliability, Item Map, Infit and Outfit MNSQ, DIF between male and female) and exploratory factor analysis (principal axis factor analysis using Promax). Furthermore, structural equation modeling was employed with data from 475 Korean high school students to verify the latent mean analysis. The results were as follows: First, in the item response analysis of the 20 translated Re_STMI items in Vietnamese, the Item Reliability was .97, and the Infit MNSQ ranged from .67 to 1.38. The results from the Item Map and DIF analysis align with previous findings. In the exploratory factor analysis, all items were loaded onto intended sub-factors, with sub-factor reliabilities ranging from .662 to .833 and total reliability at .876. Confirmatory factor analysis for latent mean analysis between Korean and Vietnamese students yielded acceptable model fit indices (χ2/df: 2.830, CFI: .931, TLI: .918, SRMR: .043, RMSEA: .051). Lastly, the latent mean analysis between Korean and Vietnamese students revealed a small effect size in systems analysis, mental models, team learning, and shared vision factors, whereas a medium effect size was observed in personal mastery factors, with Vietnamese high school students showing significantly higher results in systems thinking. This study confirmed the reliability and validity of the Re_STMI items. Furthermore, international comparative studies on systems thinking using Re_STMI translated into Vietnamese, English, and other languages are warranted in the context of students' systems thinking analysis.

Exploring Pre-Service Earth Science Teachers' Understandings of Computational Thinking (지구과학 예비교사들의 컴퓨팅 사고에 대한 인식 탐색)

  • Young Shin Park;Ki Rak Park
    • Journal of the Korean earth science society
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    • v.45 no.3
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    • pp.260-276
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    • 2024
  • The purpose of this study is to explore whether pre-service teachers majoring in earth science improve their perception of computational thinking through STEAM classes focused on engineering-based wave power plants. The STEAM class involved designing the most efficient wave power plant model. The survey on computational thinking practices, developed from previous research, was administered to 15 Earth science pre-service teachers to gauge their understanding of computational thinking. Each group developed an efficient wave power plant model based on the scientific principal of turbine operation using waves. The activities included problem recognition (problem solving), coding (coding and programming), creating a wave power plant model using a 3D printer (design and create model), and evaluating the output to correct errors (debugging). The pre-service teachers showed a high level of recognition of computational thinking practices, particularly in "logical thinking," with the top five practices out of 14 averaging five points each. However, participants lacked a clear understanding of certain computational thinking practices such as abstraction, problem decomposition, and using bid data, with their comprehension of these decreasing after the STEAM lesson. Although there was a significant reduction in the misconception that computational thinking is "playing online games" (from 4.06 to 0.86), some participants still equated it with "thinking like a computer" and "using a computer to do calculations". The study found slight improvements in "problem solving" (3.73 to 4.33), "pattern recognition" (3.53 to 3.66), and "best tool selection" (4.26 to 4.66). To enhance computational thinking skills, a practice-oriented curriculum should be offered. Additional STEAM classes on diverse topics could lead to a significant improvement in computational thinking practices. Therefore, establishing an educational curriculum for multisituational learning is essential.

An Empirical Study on the Effects of Personal Characteristics and Drama Characteristics on Entrepreneurial Intention : Focusing on the Moderating Effect of Social Support (개인 특성과 드라마 특성이 창업의지에 미치는 영향에 관한 실증 연구 : 사회적 지지의 조절효과 중심으로)

  • Chang, Soo-jin
    • Journal of Venture Innovation
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    • v.5 no.4
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    • pp.135-156
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    • 2022
  • This study attempted to identify the factors affecting entrepreneurial intention and to confirm the moderating effect of social support that plays a positive role in increasing entrepreneurial intention. The subjects of the study were 419 ordinary people, and data were obtained online and analyzed. The analysis method of this study was based on the SPSS statistical program Ver. 24, and a hierarchical regression analysis method was conducted to analyze the moderating effect. The results of hypothesis verification analysis in this study are as follows. First, innovativeness, risk-taking, self-fulfillment, economic motivation, immersion in a drama, drama role model, and indirect experience, all had a significant positive(+) effect on entrepreneurial intention. Second, among the factors affecting entrepreneurial intention, self-fulfillment was found to have the greatest influence. Third, it was confirmed that the moderating effect of social support between various variables and entrepreneurial intention had a significant effect on innovativeness, self-fulfillment, drama role model, and indirect experience, and entrepreneurial intention. The academic value of this study is to confirm the effect of drama characteristic variables on entrepreneurial intention. In addition, it was possible to confirm the moderating effect of social support, which is the total of individual external support. The implication of this study is that the desire for achievement had the greatest influence on entrepreneurial intention. Therefore, it is necessary to develop a desire to achieve in start-up support policies and start-up education. In addition, in light of the ripple effect of TV dramas, drama role model and indirect experience increase entrepreneurial intention, so it was possible to predict its influence on changes in perception of start-ups and entrepreneurs.