• The Mathematical Education
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• v.57 no.2
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• pp.75-92
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• 2018

Based on Perceptions about Mathematics Teachers (PMT) perceived by high school students, measured by 2189 students from Seoul Educational Longitudinal Study 2014 (SELS 2014), latent profile analysis (LPA) identified five distinct types of student groups (positive, partial positive, middle, negative, extreme negative). These student of positive, middle, and negative groups are positive, moderate and negative perceptions about math teachers. Partial positive group generally had a positive perception about mathematics teachers, extremely negative group was very negative about mathematics teachers. Both of these groups had peculiarly inconsistent trends and several anomalies. The Multinomial logistic regression analyses also indicated that individual factors (gender, major, self-concept, resilience, self-assessment, career maturity), school factors (friendship, relationship with school teachers) and parental factors (academic-relationship, emotional-relationship) were significant predictors of PMT profile groups. The Analysis of variance also indicated that mathematics class (attitude, satisfaction and atmosphere), Mathematics achievement were significant predictors of PMT profile groups. The profiling of perceptions about mathematics teachers resulted in enhanced understanding of the complex range of processes students employed. During mathematics class, implementation of smooth interactions and communications between students and teachers added in the teaching and learning of mathematics.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.9
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• pp.1590-1595
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• 2006

This paper proposes a technique of user oriented document ranking using user refile to provide more satisfied results which reflect preference of specific users. User profile is constructed to represent his or her preference. User pfofile consists of 'term array' and 'preference vector' according to the interest field of one. And the User profile for a particular person is updated by 'user access', 'latent relaeon', 'User Profile' proposed in this paper. The latent structures of documents in same domain are analysed by singular value decomposition(SVD). Then, the rank of documents is determined by comparison of user profile with analyzed document on the basis of relevance.

• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.533-545
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• 2021

This study aimed to examine the differences in gender equality consciousness between latent profiles based on corporate workers' organizational culture types. To achieve the study's purpose, descriptive statistics, correlation analysis, and latent profile analysis (LPA) were conducted using 253 Korean corporate workers' data. As a result of the analysis, the latent profiles of organizational culture recognized by corporate workers were classified into 5 profiles. We named each profile as high compete-low create culture, high compete-low collaborate culture, collaborate culture, high create culture, and high control culture based on each profile's organizational culture perception. The ANOVA test found statistically significant differences between the groups in the gender equality consciousness. This study is meaningful in that it reveals the relationship between the organization culture perception and the gender equality consciousness and suggested implications for the organizational-level intervention to improve the gender equality consciousness. It will provide basic data for your research.

• Journal of the Korean Institute of Educational Facilities
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• v.26 no.5
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• pp.3-10
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• 2019

This study has a purpose to profile local sectors into meaningful groups by using facilities rates of Social Overhead Capital(SOC) for daily life. Comparing SOC for daily life among the meaningful groups, the profiling and comparison results bring the comprehensive understanding about the educational facilities in local sectors. For the research purpose, this study utilized Latent Profile Analysis(LPA) by using variables such as population, road information, SOC for daily life, usage of land, possession of land, and appraised value of land from the 2018 Geographic Information System(GIS) dataset of Gwangjin-gu, where is one of the administrative district of Seoul City. Results showed that there are four latent groups of sectors among 904 local sectors(100 squared-meters sector per each) in Gwangjin-gu. By comparing the four latent groups by using LPA, the results diagnose each sector's status and help to improve the policy about educational facilities. Specifically, by using dataset for SOC of daily life, there are four groups of local sectors and each group has different features. Based on the different features of local sector groups, there can be improved management of educational facilities matching with each group's features.

• Survey Research
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• v.18 no.2
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• pp.67-98
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• 2017

The purposes of this study are to identify the latent classes of school violence depending on bullying and victimized experience by type and the influences of individual-level and school-level variables on determining these latent profiles. For these research goals, the present study utilized data from the Seoul Education Longitudinal Study(SELS) 5th wave, containing data from 2,195 middle school students who experienced school violences more than once. Multilevel latent profile models were applied to examine school violence among students. Our results indicated that there were four latent classes; high-level bullying and victimized group (1.7%), mainly bullying group(2.1%), mainly victimized group(3.7%), verbal bullying and victimized group(92.5%). Gender, resilience, self-control, peer relationship, parental relationship were significant determinants of the latent profiles at student level. Teacher-student relationships, school violence prevention, gender ratio of school were significant determinants of the latent profiles at school level. The present study contributed to extending theoretical discussions by classifying students into groups based on frequency and different forms of bullying and victimization. Moreover, this study examined determinants of student and school level simultaneously by dealing with multilevel data.

• Communications for Statistical Applications and Methods
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• v.23 no.2
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• pp.131-146
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• 2016

In research on behavioral studies, significant attention has been paid to the stage-sequential process for longitudinal data. Latent class profile analysis (LCPA) is an useful method to study sequential patterns of the behavioral development by the two-step identification process: identifying a small number of latent classes at each measurement occasion and two or more homogeneous subgroups in which individuals exhibit a similar sequence of latent class membership over time. Maximum likelihood (ML) estimates for LCPA are easily obtained by expectation-maximization (EM) algorithm, and Bayesian inference can be implemented via Markov chain Monte Carlo (MCMC). However, unusual properties in the likelihood of LCPA can cause difficulties in ML and Bayesian inference as well as estimation in small samples. This article describes and addresses erratic problems that involve conventional ML and Bayesian estimates for LCPA with small samples. We argue that these problems can be alleviated with a small amount of prior input. This study evaluates the performance of likelihood and MCMC-based estimates with the proposed prior in drawing inference over repeated sampling. Our simulation shows that estimates from the proposed methods perform better than those from the conventional ML and Bayesian method.

• Korean Journal of School Psychology
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• v.11 no.1
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• pp.253-274
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• 2014

The present study classified groups based on latent profile of self-determination motivation(amotivation, external motivation, intrinsic motivation), and examined the determinants for each group. The data was collected through panel data of Korea Education Longitudinal Study(KELS), total 5,459 participants who answered questionnaires of self-determination motivation of two times both second grade of middle school and second grade of high school. To identify the change motivational type, standardized residual was conducted using SPSS 17.0., and the latent classes for the change of motivational type was investigated using M-Plus in the frame work of Latent Profile Analysis(LPA). The results indicated that five groups(increase of self-determination, self-determination maintenance, self-determination developmental delay, elf-determination confusion, decrease of self-determination group) were classified based on latent profile. In addition, parental control, academic self-concept, teacher-student relationship, test anxiety, avoidance orientation, gender, father's education, and income were significantly related to each group. Lastly, the implications for directions of the adolescent counseling, limitations and future research are discussed.

• The Journal of the Korea Contents Association
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• v.20 no.9
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• pp.365-379
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• 2020

The purpose of this study identifies the patterns of students' learning motivation profiles on entrepreneurial educational motivation among a sample of university students from one of the Korean national university(n=614). This study also examines the relationship between students' learning motivation profiles and entrepreneurial intention and types of entrepreneurship. In order to explore the types of leaning motivation profiles, a latent profile analysis was employed. Result from LPA revealed five distinct types of learning motivation profiles fit the data best, and these five profiles are compared with students' entrepreneurial intentions and types of entrepreneurship. Results showed that Profiles (profile 5 and 4-high goal orientation) are associated with the higher level of entrepreneurial intention. Regarding the type of entrepreneurship, the majority of all students are interested in individual and co-entrepreneurship with friend regardless of the patterns of profiles.

• Korean Journal of Childcare and Education
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• v.17 no.3
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• pp.65-87
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• 2021

Objective: This study aimed to examine the effects of maternal monitoring, shared activities with children, maternal education-oriented behavior, and allowing children to own smart-phones on smart media usage patterns based on smart-phone usage time and purposes among elementary school children. Methods: The participants were 1,315 second-grade elementary school children from the 9th wave of PSKC. Latent profile analysis and the three-step estimation approach were used to examine the determinants of the latent profile and the effects of maternal parenting on the profile. Results: Four latent profiles were identified: 'High-level usage & Entertaining oriented,' 'Moderate-level usage & Social/entertaining oriented,' 'Moderate-level usage & Learning oriented,' and 'Low-level usage.' Additionally, results showed that each profile can be predicted by maternal monitoring, education-oriented behavior, and permitting children to own smart-phones. Conclusion/Implications: Our outcomes suggested that it would be necessary to understand the smart media usage patterns of elementary school children, considering both the amount of time spent with smart media and purposes of uses. Further, it is helpful for mothers to monitor children's daily activities, support their educational activities, and take the role of gatekeeper for smart media as a way of appropriate guidance for their children's use of smart media.

• Korean Medical Education Review
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• v.23 no.2
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• pp.118-127
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• 2021

Due to the coronavirus disease 2019 pandemic, the new norm of online learning has been recognized as core to medical institutions for academic continuity, and students are expected to be motivated and engaged in learning while maintaining distance from other peers and educators. To facilitate students' and educators' newly defined roles in online medical education settings, it is crucial to understand how students are actively motivated and engaged in learning. Hence, this study explored medical students' motivational regulation profiles and examined the effects of motivational regulation strategies (MRS) on cognitive learning and learning engagement for online learning. Data were collected after the end of the first semester in 2020 from a sample of 334 medical students enrolled at a public university school of medicine. Latent profile analysis indicated three subgroups with different motivational regulation profiles: the low-profile, medium-profile, and high-profile groups. Regarding different MRS patterns in the high-profile group, mastery self-talk, performance approach self-talk, and the self-consequating strategy appeared to be most applicable for regulating learners' motivation. Analysis of variance showed that the profile groups with higher levels of MRS use were connected to a higher willingness to use cognitive learning strategies and a higher degree of engagement in online learning. The findings of this study emphasize the use of specific sets of MRS to support learning motivation and the need to design effective self-regulated learning environments in online medical education settings.