• The Journal of Korean Association of Computer Education
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• v.6 no.2
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• pp.137-146
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• 2003

The Web programming techniques like CGI and server-sided script languages such as ASP, PHP and JSP have been used for developing on-line Web-based learning systems on SQL. But, the systems developed by using those techniques are dependent on the platforms on which the target DBMS's are located. Therefore, they can be hardly reused and maintained. In addition, it is not easy for them to provide a learner with the feedback information on processing his/her query and to give a teacher an opportunity of monitoring and guiding learner's learning process. In this paper, we propose an SQL learning system on the Web by using Java Applet and JDBC, which is independent on the target DBMS's. Moreover, it gives feedback information on learner's queries so that a teacher can monitor the learning process and teach them efficiently.

• Journal of Korean Society for Quality Management
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• v.48 no.3
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• pp.511-520
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• 2020

Purpose: The purpose of this study was to devise an accurate machine learning model for predicting silica concentrations following the addition of impurities, through time series analysis of mining data. Methods: The mining data were preprocessed and subjected to time series analysis using the machine learning model. Through correlation analysis, valid variables were selected and meaningless variables were excluded. To reflect changes over time, dependent variables at baseline were treated as independent variables at later time points. The relationship between independent variables and the dependent variable after n point was subjected to Pearson correlation analysis. Results: The correlation (R2) was strongest after 3 hours, which was adopted as a dependent variable. According to root mean square error (RMSE) data, the proposed method was superior to the other machine learning methods. The XGboost algorithm showed the best predictive performance. Conclusion: This study is important given the current lack of machine learning studies pertaining to the domestic mining industry. In addition, using time series analysis in mining data will show further improvement. Before establishing a predictive model for the proposed method, predictions should be made using data with time series characteristics. After doing this work, it should also improve prediction accuracy in other domains.

• Industry Promotion Research
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• v.7 no.1
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• pp.1-8
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• 2022

We investigated various types of machine learning methods that can be applied to censored data. Exploratory data analysis reveals the distribution of each feature, relationships among features. Next, classification problem has been set up where the dependent variable is death_event while the rest of the features are independent variables. After applying various machine learning methods to the data, it has been found that just like many other reports from the artificial intelligence arena random forest performs better than logistic regression. But recently well performed artificial neural network and gradient boost do not perform as expected due to the lack of data. Finally Kaplan-Meier and Cox proportional hazard model have been employed to explore the relationship of the dependent variable (t_i, δ_i) with the independent variables. Also random forest which is used in machine learning has been applied to the survival analysis with censored data.

• Proceedings of the Korea Association of Information Systems Conference
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• 1996.11a
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• pp.217-227
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• 1996

The new field of learning control develops controllers that learn to improve their performance at executing a given task, based on experience performin this specific task. In a previous work［6］, the authors presented a theory of indirect learning control based on use of indirect adaptive control concepts employing simultaneous identification ad control. This paper develops improved indirect learning control algorithms, and studies the use of such controllers in decentralized systems. The original motivation of the learning control field was learning in robots doing repetitive tasks such as on an assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. The basic result of the paper is to show that stability of the indirect learning controllers for all subsystems when the coupling between subsystems is turned off, assures convergence to zero tracking error of the decentralized indirect learning control of the coupled system, provided that the sample time in the digital learning controller is sufficiently short.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.24 no.3
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• pp.181-188
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• 2017

Purpose: Competency in physical assessment is an important component of nursing practice. However, some physical assessment skills are not being utilized within the current teacher-centered, content-heavy curriculum. This study was conducted to identify the effects of student-centered, self-directed learning in the physical assessment class. Methods: An experimental study with a post-test only control group design was used to compare an intervention group that was provided self-directed learning classes and a control group that was provided traditional lecture and practice classes. Competency in physical assessment, academic self-confidence, and learning satisfaction were evaluated. Collected data were analyzed using $x^2$-test (Fisher's exact test) and independent t-test. Results: Competency in physical assessment was significantly higher in the experimental group. However, academic self-confidence and learning satisfaction were not significantly different between the groups. Conclusion: The findings in this study indicate that self-directed learning can improve nursing students competency in physical assessment and that self-directed learning is a good education method to improve nursing students' competency in physical assessment during clinical practice and perform quality patient care by making active use of physical assessment skills.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1996.10a
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• pp.217-227
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• 1996

The new filed of learning control develops controllers that learn to improve their performance at executing a given task , based on experience performing this specific task. In a previous work[6], authors presented a theory of indirect learning control based on use of indirect adaptive control concepts employing simultaneous identification and control. This paper develops improved indirect learning control algorithms, and studies the use of such controller indecentralized systems. The original motivation of the learning control field was learning in robots doing repetitive tasks such as on an asssembly line. This paper starts with decentralized discrete time systems. and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. The resultof the paper is to show that stability of the indirect learning controllers for all subsystems when the coupling between subsystems is turned off, assures convergence to zero tracking error of the decentralized indirect learning control of the coupled system, provided that the sample tie in the digital learning controller is sufficiently short.

• Journal of Digital Convergence
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• v.8 no.4
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• pp.165-176
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• 2010

The aim of this study is to determine the relationship between variables affecting learning effect and flow experience on an e-Learning English program. There are 4 independent variables; English thinking structure, self-efficacy in English and flow. The results are as follows: Firstly, there is statistically significant positive correlation between each variable of English thinking structure, pre English skill, self-efficacy in English, flow and learning effect. Secondly, it appeared that flow was affected by all three variables of English thinking structure, pre-English skill and self-efficacy in English. Also flow experience affected learning improvement. Finally, it is verified that there is a mediating effect of flow experience on the relation of self-efficacy in English and learning effect.

• Child Health Nursing Research
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• v.25 no.4
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• pp.507-517
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• 2019

Purpose: This study was conducted to examine the effects of team-based problem-based learning combined with smart education among nursing students. Methods: A quasi-experimental non-equivalent control group, pre-posttest design was used. The experimental group (n=36) received problem-based learning combined with smart education and lectures 7 times over the course of 7 weeks (100 minutes weekly). Control group (n=34) only received instructor-centered lectures 7 times over the course of 7 weeks (100 minutes weekly). Data were analyzed using the $x^2$ test, the Fisher exact test, and the independent t-test with SPSS for Windows version 21.0. Results: After the intervention, the experimental group reported increased learning motivation (t=2.70, p=.009), problem-solving ability (t=2.25, p=.028), academic self-efficacy (t=4.76, p<.001), self-learning ability (t=2.78, p<.001), and leadership (t=2.78, p=.007) relative to the control group. Conclusion: Team-based problem-based learning combined with smart education and lectures was found to be an effective approach for increasing the learning motivation, problem-solving ability, academic self-efficacy, self-learning ability, and leadership of nursing students.

• Korean Medical Education Review
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• v.14 no.2
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• pp.64-68
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• 2012

Learning in medical school is usually regarded as a very specialized type of learning compared to that of other academic disciplines. Medical students might have general beliefs about their own learning. Beliefs about learning have a critical effect on learning behavior. There are several factors that affect medical students' learning behavior: epistemological beliefs, learning styles, learning strategies, and learning beliefs. Several studies have addressed epistemological beliefs, learning styles, and learning strategies in medical education. There are, however, few studies that have reported on medical students' beliefs about learning. The purpose of this study was to determine what learning beliefs medical students have, what the causes of these beliefs are, and how medical educators teach students who have such beliefs. In this study, the five learning beliefs are assumed and we considered how these beliefs can affect students' learning behaviors. They include: 1) medical students are expected to learn a large amount of information in a short time. 2) memorization is more important than understanding to survive in medical schools. 3) learning is a competition and work is independent, rather than collaborative. 4) reading textbooks is a heavy burden in medical education. 5) the most effective teaching and learning method is the lecture. These learning beliefs might be the results of various hidden curricula, shared experiences of the former and the present students as a group, and personal experience. Some learning beliefs may negatively affect students' learning. In conclusion, the implications of medical students' learning beliefs are significant and indicate that students and educators can benefit from opportunities that make students' beliefs about learning more conscious.

• Journal of the Korea Society of Computer and Information
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• v.23 no.11
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• pp.229-238
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• 2018

The purpose of this study is to investigate the mediating effect of learners' learning flow in the effect of presence on academic achievement in web-based e-learning. For this purpose, this study analyzed the influencing relationship between the each factor based on the structural model with the learning flow as a mediator variable. Based on existing theoretical studies, learning satisfaction and academic achievement, which represent learning outcomes, are set as dependent variables, and teaching presence, cognitive presence, and social presence are set as independent variables. Data collected from a total of 256 e-learning learners were used in the analysis of this study. According to the results of the analysis, teaching presence, cognitive presence, and social presence were found to have a significant effect on academic achievement when a learning flow is a mediator variable. Concretely, teaching presence, cognitive presence, and social presence have a positive effect on the learning flow, while learning flow has a positive effect on learning satisfaction. On the other hand, learning flow has a negative effect on academic achievement. As a result of verifying the mediating effect of learning flow on the relationship between presence, learning satisfaction, and academic achievement, there was meditating effect in the aggregate. This study implies that in order to increase the level of learning satisfaction and academic achievement, it is necessary to make the teaching-learning design in the provision of contents and materials for e-learning so that the learner can feel the presence. The results of this study can be used as a basic data for seeking support and promotion strategies for enhancement of future learning flow and presence.