• Journal of Korean Society of Industrial and Systems Engineering
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• 제38권1호
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• pp.74-82
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• 2015

Two key challenges in statistical relational learning are uncertainty and complexity. Standard frameworks for handling uncertainty are probability and first-order logic respectively. A Markov logic network (MLN) is a first-order knowledge base with weights attached to each formula and is suitable for classification of dataset which have variables correlated with each other. But we need domain knowledge to construct first-order logics and a computational complexity problem arises when calculating weights of first-order logics. To overcome these problems we suggest a method to generate first-order logics and learn weights using association analysis in this study.

• Communications for Statistical Applications and Methods
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• 제31권3호
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• pp.279-289
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• 2024

Familial searching is a useful technique in a forensic investigation. Using genetic information, it is possible to identify individuals, determine familial relationships, and obtain racial/ethnic information. The total number of shared alleles (TNSA) and likelihood ratio (LR) methods have traditionally been used, and novel data-mining classification methods have recently been applied here as well. However, it is difficult to apply these methods to identify familial relationships above the third degree (e.g., uncle-nephew and first cousins). Therefore, we propose to apply a stacking ensemble machine learning algorithm to improve the accuracy of familial relationship identification. Using real data analysis, we obtain superior relationship identification results when applying meta-classifiers with a stacking algorithm rather than applying traditional TNSA or LR methods and data mining techniques.

• Journal of the Korean School Mathematics Society
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• 제22권4호
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• pp.501-520
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• 2019

This study compared and analyzed Korean, American, Singaporean, and Japanese middle school mathematics curriculum standards and the learning contents in statistics. Through a comparative analysis of the curriculums of these four countries, I found several overall features and differences between the curriculums. First, all four countries emphasized statistical education in a real-life context. Second, all four countries emphasized the use of technological tools. Third, there is a middle school grade in which only Korea does not deal with statistical domains. Fourth, the statistical areas of the United States, Singapore, and Japan focused on identifying trends or variability in data distribution. Fifth, I have found some contents that only Korea does not deal with. Based on this, the following recommendations were developed for the development of the next curriculum and new textbooks in Korea. First, the statistics curriculum should be changed from one that focuses on understanding statistical concepts to one that focuses on statistical activity that utilizes these concepts. Second, in terms of middle school statistical curriculum contents, the addition of interquartile range (IQR) and box plots as learning contents should be considered. IQR and box plots are simple and practical techniques for the comparison of multiple sets of data that can be easily learned and drawn by middle school level students and applied to real-life-related statistical data to expand statistical literacy. Through this study, it is suggested that IQR and box plots need to be included in the statistical curriculum of middle schools in Korea.

• Research in Community and Public Health Nursing
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• 제33권3호
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• pp.312-320
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• 2022

Purpose: This study was performed to explore the effect of the delivery format on teaching presence, learning presence, and learning outcomes in distance learning of nursing students. Methods: A descriptive survey was conducted to understand teaching presence, learning presence, and learning outcomes depending on the delivery format of distance learning. Quota sampling methodology was used to recruit 295 nursing students from all over the country, and data collection was done from July 27 to September 10, 2020. The first delivery format for distance learning was synchronous learning in which communication between the instructor and students occurred simultaneously. The second delivery format was asynchronous learning in which prerecorded videos were provided and communication did not occur simultaneously. Results: In synchronous learning, teaching presence (especially direct facilitation) and learning presence (especially emotional expression) had a statistical significance that was higher than in asynchronous learning. However, in learning outcomes, there was no statistically significant difference. There were significant positive correlations between teaching presence, learning presence, and learning outcomes, and there were significant positive correlations. Conclusion: It can be suggested that learning outcomes can be improved if presence is improved in the distance learning environment based on the results of this study. It is necessary to add contact with nursing students and instructors to improve teaching presence in the asynchronous learning, and it is necessary to help students express their emotions to improve learning presence.

• Korean Journal of Childcare and Education
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• 제10권1호
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• pp.5-26
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• 2014

This study examined the effects of web-based learning experiences, learning style, and Internet self-efficacy that influence beginning child care teachers belief about web-based learning. The participants were 215 beginning child care teachers who work in child care centers. Data were analyzed by means of frequency analysis, correlation, and multiple regression for SPSS windows. The results were as follows: First, significant statistical differences were detected in web-based learning experiences and beliefs about web-based learning. Online teacher learning community use and frequency were significant gaps in beliefs about web-based learning. Second, there were statistical differences in learning styles and beliefs about web-based learning. And teachers with assimilator learning style showed high difficulty beliefs about web-based learning. Third, teachers' belief about web-based learning was significantly related to Internet self-efficacy. It means that teachers that have high Internet self-efficacy show high belief about web-based learning. Forth, among the teachers' personal variables, a higher level of online teacher learning community use and Internet self-efficacy predicted higher beliefs about web-based learning. Thus, this study suggested the importance of web-based learning experiences and Internet self-efficacy to beliefs about web-based learning. And it implicated ways to improve positive beliefs about web-based learning of beginning child care teachers.

• Journal of Engineering Education Research
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• 제17권6호
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• pp.20-29
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• 2014

The purpose of this study is to analyze the traits on the cognitive and affective learning style of university students. CALSIU(The Cognitive & Affective Learning Style Inventory for University School Students) by Kim, E. J. was modified for applying to university students and performed with 399 university students from three universities in Daejeon and Chungnam. Statistical analysis done in this study were ANOVA and Scheffe's test. Findings of the study are as follows : First, the students with high academic achievements have intuitive perception type, whole processing type, and deep storage & recall type. Secondly, the students with low academic achievement have strong non-academic learning type. Third, interaction attitude of affective learning styles is the important element to determine their academic achievement. The students with independent type get high academic achievements. Therefore, instructor should consider the learning styles of students, and it should be used to improve their teaching & learning strategy for better academic achievements of university students.

• Journal of Technologic Dentistry
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• 제44권3호
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• pp.97-103
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• 2022

Purpose: This study sought to identify the factors influencing learning motivation and demotivation in online dental technology students. Methods: A survey was conducted from October 1 to 30, 2021, on 188 dental technology students. The collected data were processed using the IBM SPSS IBM SPSS Statistics ver. 22.0 statistical program (IBM), and frequency, factor, and one-way ANOVA analyses were performed, for which the significance was set at 0.05. Results: It was found that the main online learning motivation factors were the usefulness of the learning content, interest, and confidence in the activities, the relationships with the teachers and friends, the feedback, and learning satisfaction. The factors that reduced the students' online learning motivation were interaction difficulties, maladaptation to the self-directed learning environment, the inadequate number of learning activities, and activity difficulty. Conclusion: Based on the identified online class motivation and demotivation factors, better systematic management and increased research are needed to improve the quality of non-face-to-face classes.

• Journal of Practical Engineering Education
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• 제15권2호
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• pp.419-427
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• 2023

In this study, optimal adhesion conditions to alleviate defects caused by heat shrinkage with FDM type 3D printers with machine learning are researched. Machine learning is one of the "statistical methods of extracting the law from data" and can be classified as supervised learning, unsupervised learning and reinforcement learning. Among them, a function model for adhesion between the bed and the output is presented using supervised learning specialized for optimization, which can be expected to reduce output defects with FDM type 3D printers by deriving conditions for optimum adhesion between the bed and the output. Machine learning codes prepared using Python generate a function model that predicts the effect of operating variables on adhesion using data obtained through adhesion testing. The adhesion prediction data and verification data have been shown to be very consistent, and the potential of this method is explained by conclusions.

• The Korean Journal of Applied Statistics
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• 제34권4호
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• pp.633-658
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• 2021

Statistical engineering contains design of experiments, quality control/ management, and reliability engineering. Python is a free software environment for machine learning, data science, and graphics. Python package has many functions and libraries for statistical engineering. We can use Python package as a useful tool for statistical engineering. This paper shows applications of Python package for statistical engineering and suggests a total Python projects for statistical engineering.

• Journal of Technologic Dentistry
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• 제39권3호
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• pp.171-177
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• 2017

Purpose: The purpose of the study is to analyze the effects that Flipped Learning Method has on a college student's self directed learning ability, critical thinking disposition, learning motivation, and learning satisfaction, and determine its effectiveness as a new pedagogical approach. Methods: The survey was conducted on dental technology students. The collected data was analyzed by the statistical program SPSS 21.0. The results were analyzed by reliability, frequency, t-test. To test for significance on each item, p<0.05 has been decided as a standard. Results: According to the analysis, the student who attended a class that utilized Flipped Learning Method was found to have higher levels of self directed learning ability, critical thinking disposition, learning motivation, and learning satisfaction than a student who attended a class that did not utilize such a method. Conclusion: The study results show that, in order to enhance students' self directed learning ability, critical thinking disposition, learning motivation, and learning satisfaction and to improve the quality of class instruction, it may be necessary that Flipped Learning Method be adopted more widely and recommended more strongly. Such changes will promote a long term improvement in educational environments and play a major role in strengthening students' abilities.