• Journal of Christian Education in Korea
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• v.61
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• pp.81-107
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• 2020

This study reviews Bandura's vicarious reinforcement in observational learning process and implies this concept into Christian education in terms of spiritual role modeling. The first part of this study answers three questions: "what is vicarious reinforcement?" "how does vicarious reinforcement take place in observational learning?" and "how does vicarious reinforcement affect observer's behavior change?" Bandura conceptualizes the learning process with observational learning and imitative or non-imitative performance. Based on this concept, Bandura define the roles of vicarious reinforcement in the four steps of observational learning process: attention, retention, motor reproduction, and motivational process. Also, the three effects of vicarious reinforcements are explained in the following categories: the observational learning effect, inhibitory or disinhibitory effects, and eliciting effect. Adapting the structure of observational learning theory in terms of the effect of vicarious reinforcement and the function of role models, the second part of this study examines the biblical concept of imitation of Christ and the modeling strategy of discipleship. Especially Paul's spiritual role model serves as positive vicarious reinforcement for the Christian believers to perform the desired behaviors. Also, Paul's condemnation serves as explicit negative vicarious reinforcement. Then, the last part of this study covers the implication of these findings from observational learning and empirical studies in terms of spiritual role modeling to Christian education.

• Journal of Korean Elementary Science Education
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• v.21 no.1
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• pp.135-142
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• 2002

This paper aims to compare the effects of two teaching methods, the discovery-observational(DO) and the expository-observational(EO) instructions, on students learning interest in the life cycle of fruit fly. The subjects, 463 third-graders from two elementary schools in Changwon City, were divided into two groups, the DO group and the EO group. After the instruction on the life of the flies in two different teaching ways, a questionnaire with 13 items was devised regarding the students' interest, and the subjects were asked to respond to it. The results reveal that the general mean score of the DO group is higher than that of the EO group. Also, the DO group obtains the higher mean score in each item, except two items about knowledge learning. The differences of the mean scores of the two types, general as well as item-individual, between the two groups are statistically significant. This suggests that the class about the life cycle of living creatures easily getatable and observable, such as fruit flies, should be student-centered investigatory one, where students themselves collect them and observe the process of their growth and whole cycle.

• Journal of the Korean earth science society
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• v.39 no.4
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• pp.349-360
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• 2018

This study analyzed variations of learning stress by comparing the salivary cortisol levels of students who participated in Earth Science inquiry activities. The cortisol concentrations between the pre- and post-inquiries of the sample of 34 university students, who had taken the course of 'Basic Earth Science and Experiments', were analyzed. The Earth Science inquiries consisted of geology and astronomy activities. The observational geology activities consisted of a session of 'structure contours and map patterns' and the cognitive astronomy activities consisted of a session of 'representations of horizontal and equatorial coordinates'. These Earth Science inquiry activities were found to cause students to have anxiety, and the thought processes that these activities involved were found to cause learning stress. The variations in cortisol concentrations of students increased by $1.6{\pm}5.9ng\;mL^{-1}$ after conducting observational activities in geology compared with $2.1{\pm}6.2ng\;mL^{-1}$ after doing cognitive activities in astronomy. The analysis of the observational activities in the geology inquiry activities indicated that they were consistent with low levels of learning stress. Conversely, the analysis of the cognitive activities in the astronomy inquiry activities showed significant individual variations in cortisol concentrations. Furthermore, individual differences in cognitive ability were reflected in the astronomy inquiry activities. While students, who received high scores, exhibited low levels of stress in the geology inquiry activities, they showed high levels of stress in the astronomy inquiry activities. It was concluded that, in the case of students with high scores in the study, the level of learning stress increased due to the raised anxiety in cognitive inquiry activities. In contrast, students, who received low scores in the study, exhibited high levels of stress in the geology inquiry activities, and low levels of stress in the astronomy inquiry activities.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.175-187
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• 2011

Since insects play important roles in existence of plants and other animals in the natural environment, they are considered as necessary biological resources from the perspectives of those biodiversity conservation and national utilization strategy. For the conservation and utilization of insect species, an observational learning environment is needed for non-experts such as citizens and students to take interest in insects in the natural ecosystem. The insect identification is a main factor for the observational learning. A current time-consuming search method by insect classification is inefficient because it needs much time for the non-experts who lack insect knowledge to identify insect species. To solve this problem, we proposed an smart phone-based insect identification inference system that helps the non-experts identify insect species from observational characteristics in the natural environment. This system is based on the similarity between the observational information by an observer and the biological insect characteristics. For this system, we classified the observational characteristics of insects into 27 elements according to order, family, and species, and proposed similarity indexes to search similar insects. In addition, we developed an insect identification inference prototype system to show this study's viability and performed comparison experimentation between our system and a general insect classification search method. As the results, we showed that our system is more effective in identifying insect species and it can be more efficient in search time.

• Communications for Statistical Applications and Methods
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• v.29 no.2
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• pp.177-191
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• 2022

This paper addresses the use of machine learning methods for causal estimation of treatment effects from observational data. Even though conducting randomized experimental trials is a gold standard to reveal potential causal relationships, observational study is another rich source for investigation of exposure effects, for example, in the research of comparative effectiveness and safety of treatments, where the causal effect can be identified if covariates contain all confounding variables. In this context, statistical regression models for the expected outcome and the probability of treatment are often imposed, which can be combined in a clever way to yield more efficient and robust causal estimators. Recently, targeted maximum likelihood estimation and causal random forest is proposed and extensively studied for the use of data-adaptive regression in estimation of causal inference parameters. Machine learning methods are a natural choice in these settings to improve the quality of the final estimate of the treatment effect. We explore how we can adapt the design and training of several machine learning algorithms for causal inference and study their finite-sample performance through simulation experiments under various scenarios. Application to the percutaneous coronary intervention (PCI) data shows that these adaptations can improve simple linear regression-based methods.

• Journal of the Korea Convergence Society
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• v.9 no.9
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• pp.293-297
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• 2018

The purpose of this study was to determine the influence of video modeling observational learning intervention on the learning and performance of a bowling skill in adolescents with intellectual disabilities. Thirty special middle school students whose ages ranged from 14 to 16 years were recruited from Daegu, Korea. Intellectual disabilities of the participants were assessed by Korean version of the Wechsler intelligence scale for adolescent and a social maturity scale. During the experiment, participants repeatedly watched the one-minute action observation film for three minutes before beginning each frame and played 60 frames. Statistical comparisons were performed using a 2 (groups) ${\times}$ 6 (trials) ANOVA, with repeated measures on the last factor of the acquisition stage (p<0.05). Factors of the retention stage scores were analyzed by one-way ANOVA. The sources of any significant main effects were tested using a Tukey's HSD (honest significant difference) approach. SPSS 21.0 was used for statistical analyses. The performance scores of the action observation group were significantly higher than those of the control group. The findings showed that observational learning in the form video modeling has the potential to enhance acquisition and learning of a bowling sport skill in intellectual disability individuals; however, these findings are limited to adolescents with moderate intellectual disabilities.

• Korean Medical Education Review
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• v.22 no.2
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• pp.67-76
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• 2020

The structures and processes of medical education have changed little since the publication of Flexner's report, which stressed the scientific orientation of medical education and the curricular structure of 2 years of formal knowledge education and 2 years of clinical experience. However, the previous perspectives on medical education are facing challenges, and these call for new pedagogy and theories on which to base medical education practice. Considering that social dimensions of learning have been emphasized in practice, perspectives that integrate these aspects are needed. Among the various learning theories, social cognitive theory refers to the theoretical framework which contends that learning occurs within interactions with others and environments. From a social cognitive standpoint, learning through observation is a critical component in human functioning. Indeed, observational learning has particular significance in medical education in that it provides the context for which the importance and meaning of role models can be understood. In addition, as theoretical constructs such as self-efficacy and outcome expectations allow us to establish an effective learning environment, exploring the concepts of the theory could be beneficial to medical education practice. In this context, the present review article aims to provide a glimpse of the fundamental assumptions and theoretical concepts of social cognitive theory and discusses the implications the theory has on teaching and learning. Further, a review of previous studies could help explain how the theory has informed medical education practice. Finally, the author will conclude with the implications and limitations of applying social cognitive theory in medical education.

• Journal of the Korean earth science society
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• v.35 no.3
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• pp.180-191
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• 2014

In this study, a geological field trip learning program using 3 Dpanorama virtual reality (PVR) techniques is developed to learn about the Chaeseokgang area located in a national park near Byeonsan-bando, Jeonbuk, Korea. The developed $360^{\circ}{\times}180^{\circ}$ PVR program can show every face of observational points and interact as zoom-in, zoom-out and image rotation. For the educational effects of the materials, it is provided with a compass, a protractor for measuring the dip of strata and observation of specimen of observational points. It also assists students to learn by providing enlarged images, pop-up windows, and expert explanation main observational points. The program is applied to the class of 35 gifted students in middle school to investigate the effectiveness of the program. The results showed that positive responses of the students were 85% or more. It is suggests that this program be used as indirect situated learning material and a solution to geological field trip problems like cost, safety, distance, and so on geological learning of middle school science.

• Journal of Advanced Navigation Technology
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• v.28 no.3
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• pp.262-271
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• 2024

In this paper, by applying deep learning, one of the A.I. techniques, through angle information, which is optical observation data generated when observing satellites at observatories, distance information from observatories is learned to predict range data, thereby increasing the precision of satellite's orbit determination. To this end, we generated observational data from GMAT, reduced the learning data error of deep learning through preprocessing of the generated observational data, and conducted deep learning through MATLAB. Based on the predicted distance information from learning, trajectory determination was performed using an extended Kalman filter, one of the filtering techniques for trajectory determination, through GMAT. The reliability of the model was verified by comparing and analyzing the orbital determination with angular information without distance information and the orbital determination result with predicted distance information from the model.

• Journal of KIBIM
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• v.6 no.4
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• pp.35-41
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• 2016

Learning effect is an observation that the more times a task is performed, the less time is required to produce the same amount of outcomes. The construction industry heavily relies on repeated tasks where the learning effect is an important measure to be used. However, most construction durations are calculated and applied in real projects without considering the learning effects in each of the repeated activities. This paper applied the learning effect to the repeated activities in a small sized apartment construction project. The result showed that there was about 10 percent of difference in duration (one approach of the total duration with learning effects in 41 days while the other without learning effect in 36.5 days). To make the comparison between the two approaches, a large number of BIM based computer simulations were generated and useful patterns were recognized using machine learning algorithm named Decision Tree (See5). Machine learning is a data-driven approach for pattern recognition based on observational evidence.