• Journal of Korean Society for Quality Management
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• v.39 no.2
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• pp.256-270
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• 2011

The study attempts to propose and test a causal research model using SEM (Structural Equation Model) to determine whether there is a relationship between six sigma champion's transformational leadership and belts' creativity based on the mediated effects of intrinsic motivation and project's learning and growth. The subjects of the study composed of 134 belts from manufacturing and service firms implemented six sigma. Empirical results show that transformational leadership is positively related to intrinsic motivation and project learning and growth. In addition, intrinsic motivation and project learning and growth are positively related to creativity. The results of the study imply that creativity of six sigma belts would be enhanced by implementation of six sigma projects and utilizing six sigma tools and methods.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.90-99
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• 2023

This paper deals with studying strategy about impact of deep learning (DL) on the factor of Korean economic growth. To study classification of impact factors of Korean economic growth, we suggest dynamic equation of microeconomy and study methods on economic growth impact of deep learning. Next step is to suggest DL model to dynamic equation with Korean economy data with growth related factors to classify what factor is import and dominant factors to build policy and education. DL gives an influence in many areas because it can be implemented with ease as just normal editing works and speak including code development by using huge data. Currently, young generations will take a big impact on their job selection because generative AI can do well as much as humans can do it everywhere. Therefore, policy and education methods should be rearranged as new paradigm. However, government and officers do not understand well how it is serious in policy and education. This paper provides method of policy and education for AI education including generative AI through analysing many papers and reports, and experience.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.197-200
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• 1996

This paper considers feedback error learning neural networks for robot manipulator control. Feedback error learning proposed by Kawato [2,3,5] is a useful learning control scheme, if nonlinear subsystems (or basis functions) consisting of the robot dynamic equation are known exactly. However, in practice, unmodeled uncertainties and disturbances deteriorate the control performance. Hence, we presents a robust feedback error learning scheme which add robustifying control signal to overcome such effects. After the learning rule is derived, the stability is analyzed using Lyapunov method.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.269-277
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• 2021

The purpose of the study is to explore the effect of university's managing and system support in online classes on learning participation mediated by learning presence and to examine the structural relationship between the factors. In order to achieve the purpose of the study, 135 students who take online "College English 2" classes were analyzed for the fitness of the research model and the path and structural analysis through a confirmative factor of the structural equation model. As a result of the study, first, the university's managing support for online class showed a positive effect to learning presence. Second, the university's managing support for online classes completely mediated learning presence and had a positive effect on learning participation. This study can clarify the structural relationship between environmental factors which are online class support and learners' characteristics in university online class, learning presence, and learning participation and can broaden the understanding of learning participation in online classes. It gives the implications that should be considered in teaching and learning design.

• Journal of Korean Society for Quality Management
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• v.37 no.3
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• pp.54-64
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• 2009

This study conducts an empirical analysis of how the suggestion activity, most widely used in quality control activities, interacts with the dimensions of learning organizations. The study also attempts to analyze the results of Six Sigma based on sub-dimensions of learning organizations, which are infrastructure, culture and system. In order for learning and innovation to take place in implementing a Six Sigma program, the organizational infrastructure and culture are created and sustained and then, a learning organization system would become effective. In this study, a empirical model is used to demonstrate such an association. The sample consists of 134 organizations who have implemented a Six Sigma program for more than three years. Using the version 16.0 of AMOS for structural equation modeling, the study estimates the structural equation model that has a Six Sigma organization's infrastructure, culture and system as independent constructs, the suggestion system as a mediator, and the performance of Six Sigma projects as a dependent construct.

• Journal of The Korean Association For Science Education
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• v.36 no.1
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• pp.125-134
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• 2016

The purpose of this study is to explore the relationship between motivational belief about learning science, self-directed learning ability and conceptual understanding of matter change with a quantitative method, assuming that motivational belief and self-directed learning ability might affect conceptual understanding. To do this, the authors investigated middle school students' motivational belief about learning science, self-directed learning ability, and conceptual understanding of matter change using measurement tools based on previous studies, and then analysed the casual relationship between three variables using PLS structural equation model. As a result, three latent variables in this study could be evaluated as appropriated in reliability and validity. And also, self-directed learning ability could affect both the motivational belief and conceptual understanding, while motivational belief could affect only self-directed learning ability but not conceptual understanding. Through this study the authors confirmed that in the context of science learning self-directed learning ability can directly affect conceptual understanding but motivational belief can affect indirectly. This study is significant in that the causal relationship between different variables in science learning could be confirmed in a quantitate manner, and also in that it can suggest PLS structural equation method as a new research methodology in science education research area.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.281-286
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• 2000

This paper describes a lateral guidance system of an unmanned vehicle, using a neural network model of magneto-resistive sensor and magnetic fields. The model equation was compared with experimental sensing data. We found that the experimental result has a negligible difference from the modeling equation result. We verified that the modeling equation can be used in the unmanned vehicle simulations. As the neural network controller acquires magnetic field values(B$\_$x/, B$\_$y/, B$\_$z/) from the three-axis, the controller outputs a steering angle. The controller uses the back-propagation algorithms of neural network. The learning pattern acquisition was obtained using computer simulation, which is more exact than human driving. The simulation program was developed in order to verify the acquisition of the learning pattern, learning itself, and the adequacy of the design controller. A computer simulation of the vehicle (including vehicle dynamics and steering) was used to verify the steering performance of the vehicle controller using the neural network. Good results were obtained. Also, the real unmanned electrical vehicle using neural network controller verified good results.

• Journal of Digital Contents Society
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• v.9 no.4
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• pp.735-749
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• 2008

The purpose of this study was to examine the influence of the digital textbook attribute factors on the learning interest and learning satisfaction using the structural equation model. In order to accomplish the purpose, the research was carried out with 325 students of digital textbook research school. Attribute factors of digital textbook are divided into self-concept of subjects and attribute factors of subjects. Self-concept of subjects is consist of superiority feeling and confidence. Attribute factors of subjects is interest, a sense of purpose, accomplishment motive. The results of this study can be summarized that the digital textbook attribute factors on the learning interest are signified confidence, interest, a sense of purpose, accomplishment motive. And the digital textbook attribute factors on the learning interest are signified learning satisfaction.

• The Journal of the Korea Contents Association
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• v.7 no.1
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• pp.161-168
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• 2007

In this study, we investigated the effectiveness of e-Learning, and attempted to identify factors affecting educational results. Based on survey data from 712 distance learning participants, we selected and verified factors affecting educational results through a correlation analysis and confidential test. Participants' scores were standardized and considered as a dependent variable representing educational effectiveness. Through several tests using the program AMOS, we suggest the most appropriate structural equation that can verify the causal relation of factors affecting the effectiveness of e-Learning. In result, the most important factor affecting score which is our measurement for educational effectiveness is job-possession. The fidelity has slightly direct influence to the score and the satisfaction has least indirect influence to the score.

• Educational Technology International
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• v.21 no.1
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• pp.1-29
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• 2020

Despite the existing body of literature focusing on the effects of one-to-one mobile technology integration in teaching and learning, research discussed that the determinants of mobile technology acceptance and use in secondary school settings are still unclear. Hence, this study examined the extent to which determinants influence high school students' behavioral intention to use one-to-one mobile technology for learning. The newly proposed model incorporated three additional constructs beyond those in the unified theory of acceptance and use of technology (UTAUT) model, including computer self-efficacy, attitude toward using technology and computer anxiety, as suggested by recent literature. Data were collected from 247 U.S. Midwestern high school students who participated in an online survey. Using a structural equation modeling approach, this study established construct validity for the nine-construct extended UTAUT model to assess high school students' intention to use mobile technology. The results of structural relations in the proposed model showed that their behavioral intention to use mobile technology was significantly predicted by social influence and attitude toward using technology. Also, their strong behavioral intention and facilitating conditions were associated with frequent use of mobile technology in learning. Discussion, implications, and conclusion were addressed in this study.