• 제목/요약/키워드: learning related factors

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Using Machine Learning Techniques to Predict Health-Related Quality of Life Factors in Patients with Hypertension (머신러닝 기법을 활용한 고혈압 환자의 건강 관련 삶의 질 요인 예측)

  • Jae-Hyeok Jeong;Sung-Hyoun Cho
    • Journal of The Korean Society of Integrative Medicine
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    • v.12 no.3
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    • pp.11-24
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    • 2024
  • Purpose : This study aims to identify the factors influencing health-related quality of life through machine learning of the general characteristics of patients with hypertension and to provide a basis for related research on patients, such as intervention strategies and management guidelines in the field of physical therapy for health promotion. Methods : Annual data from the second Korean Health Panel (Version 2.0) from 2019 to 2020, conducted jointly by the Korea Health and Social Research Institute and the National Health Insurance Service, were analyzed (Korea Health Panel, 2024). The data used in this study was collected from January to July 2020, and the data was collected using computer-assisted face-to-face interviews. Of the 13,530 household members surveyed, 1,368 were selected as the final study participants after removing missing values from 3,448 individuals diagnosed with hypertension by a doctor. Results : The results showed that walking (P2) was the most significant factor affecting health-related quality of life in random forest, followed by perceived stress (HS1), body mass index (BMIc), total household income (TOTc), subjective health status (SRHc), marital status (Marr), and education level (Edu). Conclusion :To prevent and manage chronic diseases such as hypertension, as well as to provide customized interventions for patients in advanced stages of the disease, research should be conducted in the field of physical therapy to identify influencing factors using machine learning. Based on the findings of this study, we believe that there is a need for additional content that can be utilized in the field of physical therapy to improve the health-related quality of life of patients with hypertension, such as diagnostic assessment and intervention management guidelines for hypertension, and education on perceived stress and subjective health status.

A Hierarchical Evaluation for Success Factors of the Mobile-Assisted Language Learning Using AHP

  • Kim, Gyoo-mi;Lee, Sang-jun
    • International Journal of Contents
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    • v.13 no.3
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    • pp.25-31
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    • 2017
  • With tremendous advancement of information and communication technologies, mobile learning systems have been widely adopted in language learning contexts, and several frameworks have been developed for identifying and categorizing different factors of mobile-assisted language learning (MALL). However, pre-existing frameworks have limitations when evaluating the importance level of criteria. The purpose of this study is to develop a comprehensive hierarchical framework for identifying and categorizing success factors of MALL and prioritizing them according to the importance level. To do that, AHP method is used to quantitatively estimate weight values of MALL criteria. Results reveal that the priority of MALL criteria is ordered as follows: content, system, learner, language learning. Local weights of each criterion are also analyzed; for example, usefulness, accuracy, and authenticity are critical factors for improving MALL contents. Ease of use and mobility of MALL systems are also considered more critical than other systematic factors. In addition, availability of immediate feedback and self-directness has the highest weight values of importance. The findings of the study are discussed regarding hierarchical orders of MALL criteria and conclude that successful MALL implementation may be achieved if related elements are diversely measured and evaluated. Pedagogical implications and suggestions for further research are also presented.

Risk Factors for Sarcopenia, Sarcopenic Obesity, and Sarcopenia Without Obesity in Older Adults

  • Kim, Seo-hyun;Yi, Chung-hwi;Lim, Jin-seok
    • Physical Therapy Korea
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    • v.28 no.3
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    • pp.177-185
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    • 2021
  • Background: Muscle undergoes change continuously with aging. Sarcopenia, in which muscle mass decrease with aging, is associated with various diseases, the risk of falling, and the deterioration of quality of life. Obesity and sarcopenia also have a synergy effect on the disease of the older adults. Objects: This study examined the risk factors for sarcopenia, sarcopenic obesity, and sarcopenia without obesity and developed prediction models. Methods: This machine-learning study used the 2008-2011 Korea National Health and Nutrition Examination Surveys in the analysis. After data curation, 5,563 older participants were selected, of whom 1,169 had sarcopenia, 538 had sarcopenic obesity, and 631 had sarcopenia without obesity; the remaining 4,394 were normal. Decision tree and random forest models were used to identify risk factors. Results: The risk factors for sarcopenia chosen by both methods were body mass index (BMI) and duration of moderate physical activity; those for sarcopenic obesity were sex, BMI, and duration of moderate physical activity; and those for sarcopenia without obesity were BMI and sex. The areas under the receiver operating characteristic curves of all prediction models exceeded 0.75. BMI could predict sarcopenia-related disease. Conclusion: Risk factors for sarcopenia-related diseases should be identified and programs for sarcopenia-related disease prevention should be developed. Data-mining research using population data should be conducted to enhance the effectiveness of early treatment for people with sarcopenia-related diseases through predictive models.

Factors related to satisfaction with non-face-to-face classes of health science students due to COVID-19 pandemic (COVID-19으로 인한 보건계열 대학생의 비대면 수업 만족도 관련 요인)

  • Yoon, Hae-Soo;Lee, Hyun-Jeong;Moon, Soo-Jin;Lee, Kyeong-Hee;Lim, Je-Hyeok;Jang, Jong-Hwa
    • Journal of Korean society of Dental Hygiene
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    • v.21 no.6
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    • pp.805-812
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    • 2021
  • Objectives: To investigate the perceived quality of classes, academic emotions, and learning achievement levels associated with the non-face-to-face classes of health science students, and to analyze the factors related to class satisfaction. Methods: Using a questionnaire, 238 health science students were surveyed regarding the quality of classes, academic emotions, and learning achievement levels. Factors related to calss satisfaction were analyzed using stepwise multiple regression. Results: Lecture types that the students were most satisfied with were 'video lectures using PPT' and 'recorded lectures provided by LMS', while 'real-time video lectures' were scored the lowest (p=0.005). Factors affecting non-face-to-face class satisfaction were perceived achievement (β=0.425, p<0.001), learning content (β=0.265, p<0.001), learning emotion (β=0.171, p<0.001), and learning environment (β=0.137, p=0.012). The adjusted explanatory power for this model was 63.9%. Conclusions: To increase the satisfaction of health science students with non-face-to-face classes, it is necessary to prepare an institutional foundation and to develop an educational program that can increase perceived achievement.

Adult hippocampal neurogenesis and related neurotrophic factors

  • Lee, Eu-Gene;Son, Hyeon
    • BMB Reports
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    • v.42 no.5
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    • pp.239-244
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    • 2009
  • New neurons are continually generated in the subgranular zone of the dentate gyrus and in the subventricular zone of the lateral ventricles of the adult brain. These neurons proliferate, differentiate, and become integrated into neuronal circuits, but how they are involved in brain function remains unknown. A deficit of adult hippocampal neurogenesis leads to defective spatial learning and memory, and the hippocampi in neuropsychiatric diseases show altered neurogenic patterns. Adult hippocampal neurogenesis is not only affected by external stimuli but also regulated by internal growth factors including BDNF, VEGF and IGF-1. These factors are implicated in a broad spectrum of pathophysiological changes in the human brain. Elucidation of the roles of such neurotropic factors should provide insight into how adult hippocampal neurogenesis is related to psychiatric disease and synaptic plasticity.

A Study on the Learner's factors affecting the Satisfaction of BL in Universities (대학 수업에서의 블렌디드 러닝 만족에 영향을 미치는 학습자 변인 연구)

  • Jun, Byoungho
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.13 no.3
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    • pp.105-113
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    • 2017
  • Considered as the "new normal" mode of learning, BL has become popular in recent years especially in University education. BL is defined as a learning approach that combines e-learning and face-to-face classroom learning. BL allows for more interactive and reflective learning environment resulting in enhancing learner-directed learning. The adoption of BL in university has made it significant to probe the crucial determinants that would entice instructors and learners to use BL and enhance learning satisfaction. The primary purpose of this study is to investigate the affecting factors of the satisfaction of BL in universities in terms of leaner's aspects. Learner's role is very important in BL, because learner should self-directed study for effective performance and satisfaction in BL environment. Based on prior studies motivation, self-efficacy, and educational expectancy were identified as affecting factors of satisfaction in BL. According to the result of multiple regression, all factors(motivation, self-efficacy, and educational expectancy) were found to be significantly related to the learner's satisfaction in BL. It can provide practical guideline on effective operation strategy for BL in universities.

The Effects of Early Cumulative Risk Factors on Children's Development at Age 3 - The Mediation of Home Learning Environment - (유아기 발달에 대한 생애 초기 가족 누적위험요인의 영향 - 가정학습환경을 매개로 -)

  • Chang, Young Eun
    • Journal of the Korean Society of Child Welfare
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    • no.54
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    • pp.79-111
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    • 2016
  • The purpose of this study was to examine the structural models in which early cumulative risk factors affect children's language(indicated by expressive vocabularies) and social development(indicated by peer competence) at age 3 thorough their effects on the home learning environment. To examine the hypothesized models, the data of 1,725 families from the second and the fourth waves of the Panel Study of Korean Children was used. Correlation analysis and structural equation modeling were conducted to test the models. First, the cumulative risk factors at age 1 and 3 were highly correlated, implying the stability of the risk factors over time. The more cumulative risk factors at age 1 predicted the lower level of the home learning environment at age 3, which, in turn, was significantly related to both language and social development at age 3. However, the early cumulative risk factors did not directly influence later developmental outcomes. Moreover, the cumulative risk factors at age 3 were directly related to the child's language development, but neither social development northe home learning environment. In addition, the mediational role of the home learning environment (i.e., cumulative risk factors at age 1${\rightarrow}$home learning environment${\rightarrow}$language and social development) was statistically supported. In conclusion, the early cumulative risk factors in infancy indirectly predicted children's development at age 3 through the home learning environment. The practical implications for the early intervention and support for the families with infants who are experiencing multiple risk factors were discussed.

Factors related to the undergraduate nursing students' metacognition (간호대학생의 메타인지 영향요인분석)

  • Suh, Yu-Jin;Bae, Ju-Yoen;Lee, Ju Hee
    • Journal of the Korea Convergence Society
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    • v.10 no.11
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    • pp.523-532
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    • 2019
  • Metacognition is a core element for nurses' clinical competency as a result of the learner's development and evaluate goals and plans for problem solving. The study aimed to analyze factors related to metacognition among undergraduate nursing students. The 205 nursing students participated from August 15 to October 19, 2017 to measure metacognition, self-directed learning, grit, learning environment and learning style. Data were analyzed using descriptive statistics, t-test, ANOVA, Pearson correlation coefficient, and multiple regression with the SPSS/Win 22.0 program. Metacognition represented a positive correlation with self-directed learning, grit, learning environment. The self-directed learning and grit were significant factors on undergraduate nursing students' metacognition. As a result of this study, it is necessary to develop curriculum that can improve metacognition level by increasing self-directed learning ability and grit of undergraduate nursing student.

A Study on Impact of Deep Learning on Korean Economic Growth Factor

  • Dong Hwa Kim;Dae Sung Seo
    • International Journal of Internet, Broadcasting and Communication
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    • v.15 no.4
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    • pp.90-99
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    • 2023
  • This paper deals with studying strategy about impact of deep learning (DL) on the factor of Korean economic growth. To study classification of impact factors of Korean economic growth, we suggest dynamic equation of microeconomy and study methods on economic growth impact of deep learning. Next step is to suggest DL model to dynamic equation with Korean economy data with growth related factors to classify what factor is import and dominant factors to build policy and education. DL gives an influence in many areas because it can be implemented with ease as just normal editing works and speak including code development by using huge data. Currently, young generations will take a big impact on their job selection because generative AI can do well as much as humans can do it everywhere. Therefore, policy and education methods should be rearranged as new paradigm. However, government and officers do not understand well how it is serious in policy and education. This paper provides method of policy and education for AI education including generative AI through analysing many papers and reports, and experience.

A Structural Equation Modeling of the Process of Science Related Career Choice (과학 관련 진로 선택 과정의 구조 방정식 모형)

  • Yoon, Jin;Pak, Sung-Jae
    • Journal of The Korean Association For Science Education
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    • v.23 no.5
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    • pp.517-530
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    • 2003
  • The purpose of this study is to find out a model to explain the process of students' science-related career choice by identifying the causal relationships between science career choice and related factors. Important factors of science-related career choice were identified through factor analysis. 'Perception about career related to science', 'preference for science learning' and 'participation in science related activity' were three main factors of science-related career choice. A questionnaire was developed to know the factors of students' science-related career choice, and so as to make it possible to be analysed by structural equation modeling. The subject were 947 grade 6, 9, and 11 students in Seoul. Numbers of boys and girls in each grade was almost same. According to the structural equation modeling, 4 corrected models were obtained. In all 4 corrected models, 'perception about career related to science' had direct influence, and 'preference for science learning' and 'participation in science related activity' had indirect influence on science-related career choice. In the most fitting model. 'perception about career related to science' had an effect on science-related career choice with standardized total effect coefficient 1.03(direct effect 0.82, indirect effect 0.21). 'Preference for science learning', which influence 'participation in science related activity', had an effect on science-related career choice with standardized indirect effect coefficient 0.65. 'Participation in science related activity', which influence 'perception about career related to science'. had an effect on science-related career choice with standardized indirect effect coefficient 0.79. The implication to school science education is that it is most effective to raise the 'perception about career related to science' in order to make more students choose science related career. It is also effective to have more students participate in science related activity and enhance the preference for science learning. To explain the process of science related career choice more fully, it is necessary to build a more comprehensive model containing more factors influencing science-related career choice. It is necessary to test and complement the structural equation model by enlarging the subject to science high school students and science related college students.