• Journal of The Korean Association For Science Education
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• v.37 no.1
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• pp.113-123
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• 2017

The purpose of this study is to investigate engineering students' attitude toward convergence and relevance with engineering education accreditation, gender, and academic year and attitude toward convergence. To be specific, fist, we examined whether the instrument for measuring attitudes toward convergence were reliable and valid for engineering students. Second, we compared levels of attitudes toward convergence in terms of engineering education accreditation, gender and academic year. Third, latent classes, which were distinguished in terms of attitudes toward convergence, were identified. Participants were 2076 engineering students. By using factor analysis and Rasch analysis, validity and reliability of instrument measuring attitudes toward convergence were confirmed. The differences in attitude toward convergence in terms of engineering education accreditation experience, gender, and academic year were examined by independent t-test and ANOVA. There were significant differences in attitude towards convergence in terms of engineering education accreditation, gender, and academic year. Students who experience engineering education accreditation program and male and high academic year have higher levels of attitude toward convergence than others. Lastly latent class analysis (LCA) was conducted to identify subgroups underlying engineering students in terms of attitude toward convergence and five latent classes were identified. In addition, the chi-square results showed that there were significant relationships between identified latent classes and engineering education accreditation, gender, and academic year. Based on these results, engineering education considering students' characteristics and diversity in attitude toward convergence were discussed.

• Research in Community and Public Health Nursing
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• v.31 no.2
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• pp.212-221
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• 2020

Purpose: This study aims to identify the types of health-related quality of life (QoL) based on the EuroQoL 5 Dimensions among community older people and predict the factors affecting these types. Methods: This study used data from the 2016 Korea Health Panel Survey, whose participants included 3,848 older people. The data were analyzed using the software jamovi 1.2.17 and Mplus 8.2 for latent class analysis. Results: The subgroups of the older people's health-related QoL were identified as three latent classes: General stable type (43.9%), pain-related low type (35.0%), and general low type (21.1%). The types and characteristics of health-related QoL among the latent classes differed. Comparing the difference between the general low type and general stable type, the subjects showed higher probability of belonging to the general stable type when they were men, younger, higher education level, employment, better subjective health, lower BMI and stress level, and no suicidal ideation. A comparison between the general low type and the pain-related low type showed that the subjects were more likely to be classified as the pain-related low type when they were younger, higher education, employment, and better subjective health. Conclusion: The results showed a significant heterogeneity in the types of health-related QoL among community older people, and the predictors for each type were not the same. These findings present basic data for cultivating nursing interventions that enhance health-related QoL.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.278-291
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• 2021

This study performed a longitudinal research on the causal relationship between multidimensionality of problem drinking and poverty, and multidimensional deprivation meaning the inequality, focusing on gender difference. For this, this study examined the latent group of problem drinking change trajectory through the latent class growth analysis targeting total 3,770 men and 5,632 women by using the 6th-year Korea Welfare Panel Study data from 2013 to 2018, and then conducted the multinominal logistic regression analysis to verify the influence of multidimensional deprivation factors on this latent group. The main results of this study are as follows. First, the latent group of problem drinking change trajectory according to gender was classified into three latent groups in both men and women while the development aspect was different from each other. The male latent group with 'moderate level' or higher showed higher level of problem drinking than women. However, in case of 'drinking group with high level' according to gender, as time passed, the men tended to maintain it while the women tended to increase it. Second, in the results of examining the effects of multidimensional deprivation on the latent group of problem drinking change trajectory, the men with more experiences of social deprivation and the women with more experiences of social security deprivation showed the higher possibility to belong to the 'drinking group with high level' compared to the 'drinking group with low level'. Based on such results above, this study discussed the preventive/intervention measures for problem drinking according to gender.

• Communications of Mathematical Education
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• v.34 no.1
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• pp.17-39
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• 2020

The purpose of this study is to analyze the mathematical beliefs of students and teachers by Latent Class Analysis(LCA). This study surveyed 60 teachers about beliefs of 'nature of mathematics', 'mathematic teaching', 'mathematical ability' and also asked 1850 students about beliefs of 'school mathematics', 'mathematic problem solving', 'mathematic learning' and 'mathematical self-concept'. Also, this study classified each student and teacher into a class that are in a similar response, analyzed the belief systems and built a profile of the classes. As a result, teachers were classified into three types of belief classes about 'nature of mathematics' and two types of belief classes about 'teaching mathematics' and 'mathematical ability' respectively. Also, students were classfied into three types of belief classes about 'self concept' and two types of classes about 'School Mathematics', 'Mathematics Problem Solving' and 'Mathematics Learning' respectively. This study classified the mathematics belief systems in which students were categorized into 9 categories and teachers into 7 categories by LCA. The belief categories analyzed through these inductive observations were found to have statistical validity. The latent class analysis(LCA) used in this study is a new way of inductively categorizing the mathematical beliefs of teachers and students. The belief analysis method(LCA) used in this study may be the basis for statistically analyzing the relationship between teachers' and students' beliefs.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.177-179
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• 2023

본 연구에서는 사회복지시설 종사사의 직무만족도 유형을 살펴보고 유형별 예측변인과의 영향관계를 검증하였다. 이러한 연구목적을 검증하기 위해 보건복지부의 '사회복지시설 실태조사'(2014년) 데이터에서 직무만족도 변인에 모두 응답한 11,660명을 최종 분석하였다. 잠재프로파일 분석결과, 사회복지사의 직무만족도 유형은 4집단으로 나타나 '최상 직무만족도집단', '중상 직무만족도집단', '중간 직무만족도집단', '최하 직무만족도집단'으로 명명하였다. 다항로지스틱 분석결과, CLASS4(최상 직무만족도집단)를 준거집단으로 하여 CLASS1(최하 직무만족도집단)과 비교해 노동강도대비 보수수준 평가, 타직종대비 보수수준 평가, 시설안전도, 인권보장도를 높게 인식할수록 CLASS4(최상 직무만족도집단)에 속할 확률이 높아지는 것으로 나타났다. 다만, 이직의사는 낮을수록 CLASS4(최상 직무만족도집단)에 속할 확률이 높아지는 것으로 나타났다. CLASS4를 준거집단으로 하여 CLASS2집단, CLASS3집단도 비교분석 하였다.

• Journal of Wetlands Research
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• v.15 no.3
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• pp.357-366
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• 2013

This study investigates to explain preference heterogeneity of respondents for economic valuation in washland of Upo wetland using Mixed Logit Model and Latent Class Model. Mixed Logit Model showed respondent heterogeneity in the attributes of wetland area and funds as well as some alternatives violated IIA assumption. 2-class Latent Class Model for respondents were used to explain the sources of the heterogeneity. Class 1 respondents who are located relatively close to Upo wetland had more experience and knowledge of Upo wetland and better understood the information suggested in the questionnaire than class 2 respondents in mostly metropolitan area of Seoul, Incheon.

• Survey Research
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• v.12 no.2
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• pp.113-144
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• 2011

The purposes of the present study were (1) to identify the latent classes depending on youth employees' trajectories in job satisfaction and turnover intention and (2) to test the effects of person-job fit(major fit, education level fit, skill level fit) on job satisfaction and turnover intention using Youth Panel 2001. In order to estimate latent classes of job satisfaction and turnover intention changes simultaneously and study probabilities linking latent class membership in trajectory across the two variables, we applied dual trajectory model, an extension of semi-parametric group-based approach, Results showed that four latent classes were identified for job satisfaction, which were defined, based on the trajectory patterns, as increasing group, decreasing group, medium-level group, and high-level group. And, three latent classes estimated for turnover intention were defined as low-level group, maintaining group, and rapidly decreasing group. To test the effects of person-job fit variables, we added the variables as time-dependant variables to the unconditional latent class model. The effect of education level fit and skill level fit were found significant in the groups which are low in job satisfaction and have high in turnover intention. Findings from this study suggest the need to consider trajectory heterogeneity in the study of youth employees' job satisfaction and turnover intention to capture the dynamic dimension of overlap between the two constructs.

• Journal of Korean Academy of Nursing
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• v.40 no.1
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• pp.88-98
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• 2010

Purpose: The purpose of this study was to identify the social network types of elders and to identify differences among latent classes by social network. Methods: The data of 312 elders used in this study were collected from health, welfare, and other facilities and from elders living in the community. The interviews were conducted from July 16 to September 30, 2007 using a standard, structured questionnaire. Descriptive statistics, one way ANOVA with the SPSS 15.0 program and latent class analysis using Maximum Likelihood Latent Structure Analysis (MLLSA) program were used to analyze the data. Results: Using latent class analysis, social network types among older adults were identified as diverse for 58.0% of the sample, as family for 34.0%, and as isolated for 8.0%. The health status of respondents differed significantly by network type. Elders in diverse networks had significantly higher health status and elders in isolated networks had significantly lower physical health status on average than those in all other networks. Conclusion: The results of this study suggest that these network types have important practical implications for health status of elders. Social service programs should focus on different groups based on social network type and promote social support and social integration.

• Journal of Korean Academy of Nursing
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• v.50 no.6
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• pp.822-836
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• 2020

Purpose: This study aimed to identify latent classes of behavioral problem trajectories in children with allergic diseases and investigate their predictors. Methods: This study used data from the 5th to 7th Panel Study of Korean Children. The participants included 840 children aged 4~6 years with allergic diseases. Statistical analyses were conducted using latent class growth analysis and multinomial logistic regression. Results: The trajectories of both internalizing and externalizing behavioral problems in children with allergic diseases were classified into five groups, that is deteriorative, recovering, changing 1 (decreasing-increasing), changing 2 (increasing-decreasing), and low state persistent group. For the internalizing behavioral problems, predictors were temperament, father's education, family interaction, and disconnection in peer interaction. For the externalizing behavioral problems, predictors child's gender, temperament, marital conflict, parenting stress, family interaction, and parenting environment. Conclusion: Deteriorative group has high-risk behavioral problems in children with allergic diseases. We suggest to provide interventions considering latent problem trajectories based on ecological environments for allergic children.

• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.719-731
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• 2021

This study proposes a two-stage hybrid classification model for crop classification using multi-temporal remote sensing images; the model combines feature embedding by using an autoencoder (AE) with a convolutional neural network (CNN) classifier to fully utilize features including informative temporal and spatial signatures. Long short-term memory (LSTM)-based AE (LAE) is fine-tuned using class label information to extract latent features that contain less noise and useful temporal signatures. The CNN classifier is then applied to effectively account for the spatial characteristics of the extracted latent features. A crop classification experiment with multi-temporal unmanned aerial vehicle images is conducted to illustrate the potential application of the proposed hybrid model. The classification performance of the proposed model is compared with various combinations of conventional deep learning models (CNN, LSTM, and convolutional LSTM) and different inputs (original multi-temporal images and features from stacked AE). From the crop classification experiment, the best classification accuracy was achieved by the proposed model that utilized the latent features by fine-tuned LAE as input for the CNN classifier. The latent features that contain useful temporal signatures and are less noisy could increase the class separability between crops with similar spectral signatures, thereby leading to superior classification accuracy. The experimental results demonstrate the importance of effective feature extraction and the potential of the proposed classification model for crop classification using multi-temporal remote sensing images.