• Journal of Convergence for Information Technology
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• v.9 no.4
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• pp.78-87
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• 2019

The study examined how job satisfaction and pay level can affect on old salary workers over time using longitudinal data and longitudinal data analysis. The KLoSA 6-period panel data was used which contains alternate year from 2006 to 2016. In addition, Gender and Age is also considered as moderating variables. As result, the initial value and the slope of pay level influenced the initial value and the slope of job satisfaction, vice versa. It implicates the two factors of pay level and job satisfaction are interrelated. Based on the results of this study, limitations and suggestions were discussed for further research.

• The Mathematical Education
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• v.61 no.1
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• pp.127-156
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• 2022

This study used the data of students from the 6th grade to the 3rd grade of middle schoolin the Korean Educational Longitudinal Study 2013 and classified them into subgroups with similar longitudinal changes in math academic achievement. In addition, the influence of longitudinal changes in the group's academic self-concept and teachers and parents academic support on the longitudinal changes in math academic achievement were analyzed, either directly or indirectly. As a result of the analysis, it was found that the academic self-concept of each group had a positive influence on the academic achievement in mathematics. In addition, the academic support of teachers and parents was found to have a positive influence on the academic achievement in mathematics through the mediating of the academic self-concept. In terms of direct and indirect influence on academic self-concept and math vertical scale scores, it was found that teachers' academic support had more influence than parents' academic support. The educational implications of these points were discussed.

• The Mathematical Education
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• v.63 no.1
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• pp.19-33
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• 2024

This study investigates longitudinal patterns in middle school students' mathematics interest and achievement using panel data from the 4th to 6th year of the Gyeonggi Education Panel Study. Results from the multivariate growth mixture model confirmed the existence of heterogeneous characteristics in the longitudinal trajectory of students' mathematics interest and achievement. Students were classified into four latent classes: a low-level class with weak interest and achievement, a high-level class with strong interest and achievement, a middlelevel-increasing class where interest and achievement rise with grade, and a middle-level-decreasing class where interest and achievement decline with grade. Each class exhibited distinct patterns in the change of interest and achievement. Moreover, an examination of the correlation between intercepts and slopes in the multivariate growth mixture model reveals a positive association between interest and achievement with respect to their initial values and growth rates. We further explore predictive variables influencing latent class assignment. The results indicated that students' educational ambition and time spent on private education positively affect mathematics interest and achievement, and the influence of prior learning varies based on its intensity. The perceived instruction method significantly impacts latent class assignment: teacher-centered instruction increases the likelihood of belonging to higher-level classes, while learner-centered instruction increases the likelihood of belonging to lower-level classes. This study has significant implications as it presents a new method for analyzing the longitudinal patterns of students' characteristics in mathematics education through the application of the multivariate growth mixture model.

• The Journal of Bigdata
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• v.5 no.1
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• pp.11-27
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• 2020

In this paper, we developed a big data platform to store, process, and analyze effectively on such education longitudinal study data. And it was applied to the Seoul Education Longitudinal Study(SELS) to confirm its usefulness. The developed platform consists of data preprocessing unit and data analysis unit. The data preprocessing unit 1) masking, 2) converts each item into a factor 3) normalizes / creates dummy variables 4) data derivation, and 5) data warehousing. The data analysis unit consists of OLAP and data mining(DM). In the multidimensional analysis, OLAP is performed after selecting a measure and designing a schema. The DM process involves variable selection, research model selection, data modification, parameter tuning, model training, model evaluation, and interpretation of the results. The data warehouse created through the preprocessing process on this platform can be shared by various researchers, and the continuous accumulation of data sets makes further analysis easier for subsequent researchers. In addition, policy-makers can access the SELS data warehouse directly and analyze it online through multi-dimensional analysis, enabling scientific decision making. To prove the usefulness of the developed platform, SELS data was built on the platform and OLAP and DM were performed by selecting the mathematics academic achievement as a measure, and various factors affecting the measurements were analyzed using DM techniques. This enabled us to quickly and effectively derive implications for data-based education policies.

• Journal of Digital Convergence
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• v.18 no.11
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• pp.31-41
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• 2020

This study analyzed parents' school satisfaction longitudinally using data from the 1st, 3rd, and 5th wave data of the Korea Education Longitudinal Study(KELS)2013. The subjects of analysis are parents who responded without dropping out in the first, third and fifth panel of the KELS2013, and 4,227 cases that had no missing values in the variables were selected for the sample to input for analysis of the latent growth modeling(LGM). As a result, it is confirmed that the parents' education, educational support, and children's academic achievement have a positive effect on the parents' school satisfaction. But the parents' educational view and education cost have a negative effect on that. The results of this study are expected to be important information to help enhance the primary function of the school.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1409-1419
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• 2013

We analyzed the data from KYPS using the latent growth model which has been widely studied as an analysis method of longitudinal data. In this study, we applied repeated measures ANOVA to unconditional model in order for faster decision of the unconditional model of the latent growth model. Also, we compared the six-type models, the quadratic model and the model of which repeated measures ANOVA is applied.

• Journal of KIISE:Information Networking
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• v.35 no.5
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• pp.415-424
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• 2008

In this paper, we compare the QoS performance enhancement schemes according to the network architecture of mobile WiMAX system in order to improve the end-to-end QoS performance and propose QoS parameter mapping method and IP packet scheduling algorithm. To evaluate the end-to-end QoS performance, we implemented an end-to-end simulator of mobile WiMAX system using OPNET. Simulation results show that the proposed QoS parameter mapping scheme reduces the average delay of VoIP packet and improves uplink resource efficiency. And also, when the proposed IP packet scheduling algorithm is applied to the system, the end-to-end packet transmission delay of VoIP service can be reduced by 44-67 percent compared to FIFO and WRR scheduler.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.891-897
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• 2020

A flight termination system, which consists of ground and vehicle systems, forcibly terminates flight if it is deemed dangerous. In order to accomplish this, the system should maintain the link reliability above a certain level throughout the whole flight. However, the national proving ground for guided missiles could not fully meet that condition because of the gradually improving performance criteria. In this paper, we have analyzed the link budget for the flight termination system. Furthermore, we have designed and developed an emergency destruction command transmitter system, which is a ground system of the flight termination system, to provide the necessary link margin. Afterwards, we measured the received signal strength at the vehicle system and compared it with that of the existing transmitter system. We hereby confirmed that the link reliability of the flight termination system improved.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.10
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• pp.35-42
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• 2003

In this paper, we classified the wavelength reservation mechanisms of optical burst switching (OBS), and investigated the path length priority effect of the offset time/delayed reservation (OT/DR)-based scheme like the just-enough-time (JET) protocol. And, we showed that the fiber delay line (FDL)-based scheme can avoid the path length priority effect in multiple hop network environments. Also, we proposed a novel FDL/DR with hop-by-hop priority increasing (HPI) scheme which can improve the end-to-end throughput by increasing the priority of bursts hop-by-hop using the input FDLs at each node. The simulation results showed that the proposed FDL/DR with HPI scheme could avoid the path length priority effect and enhance the end-to-end throughput in multiple hop network environments.

• Survey Research
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• v.18 no.4
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• pp.25-59
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• 2017

The current study investigated how elderly husbands and wives' marital satisfaction and depression change over time and examined how changes in marital satisfaction account for changes in depression between and within the dyads. The longitudinal dyadic data from the first wave(2006) to the fifth wave(2014) of the Korean Longitudinal Study of Aging(KLoSA), collected by the Korea Employment Information Service, were used for the analyses. Because husbands and wives are interdependent within couples, we applied statistical models for dyadic data. The dyadic growth model(DGM) was used to model the trajectories of marital satisfaction and depressive symptoms. In order to analyze the association of these growth factors, we proposed the dyadic growth actor-partner interdependence model(DG-APIM) and applied the model to the data. The results showed that on average the husbands' marital satisfaction was higher but decreased faster over the course of the study than the wives'. It also showed that the average depression of the husbands was lower than that of the wives but the husbands' depression increased faster than the wives' over the course of the study. The variance of the averages of husbands' (wives's) depression was accounted for by that of wives'(husbands') marital satisfaction, showing a partner effect. The variance of the slopes of husbands'(wives') depression was accounted for by that of marital satisfaction of themselves, showing an actor effect. The results showed that there is a longitudinal interdependence between husbands and wives' marital satisfaction and depression and supported the marital discord model of depression.