• Journal of The Korean Association of Information Education
• /
• v.14 no.4
• /
• pp.627-635
• /
• 2010

This study analysed the programming attitude and degree of achievement as the 6 types of learning styles which is suggested by Grasha and Reichmann(1974) after a performance of the programming education using the Diki-3000 which is the teaching tools of the specific manipulative activities, in order to prepare the programming education method according to the characteristics of elementary school learners. As the result of the study, the programming attitude according to the 6 types of the learning styles has indicated more positiveness in the independence type than in the dependence type, in the competition type than in the cooperation type, in the participation type than in the avoidance type. In the side of the degree of the achievement, the independent, competition, and participation types indicated more positive than the other types. Also, as the result of an structured interview with learners, which was conducted for deep understanding, there was an understanding of differences of requests to the programming learning classified by the learning styles, and suggestion of a plan for improvement of the Diki-3000 programming in the aspect of an educational environment, teaching tools, teaching contents, and teaching methods in this study.

• The Journal of the Korea Contents Association
• /
• v.21 no.1
• /
• pp.311-320
• /
• 2021

At present, the secondary school teacher employment examination(SSTEE) is the only gateway to become a national and public secondary teacher in Korea, and after the revision from the 2014 academic year, all the questions of the exam have been converted to supply-type test items, requiring more definitive, accurate, and solid answers. Compared to the selection-type test items that measure recognition memory, the supply-type questions, testing recall memory, require constant memorization and retrieval practices to furnish answers; however, there is not enough learning tools available to support the practices. At this juncture, this study invented a mobile app, called ONE PASS, for the SSTEE. By unpacking the functional mechanisms of the brain, the basis of cognitive processing, this ONE PASS app offers a set of tools that feature brain-based learning principles, such as a personalized study planner, motivation measurement scales, mind mapping, brainstorming, and sample questions from previous tests. This study is expected to contribute to the research on the development of learning contents for applications, and at the same time, it hopes to be of some help for candidates in their exam preparation process.

• Proceedings of the Korea Contents Association Conference
• /
• 2006.11a
• /
• pp.287-291
• /
• 2006

E-learning has increased on importance as people realize that the use of technology can improve the teaming process. Consequently, new learning environments have been developed. However, in general they are oriented to address a specific e-learning functionality. Therefore, in most of the cases, they are not developed to interoperate with other e-learning tools, which makes the creation of a fully functional e-learning environment more difficult. We analyses of total information security infrastructure of school affairs information system for secure ubiquitous campus.

• Journal of Families and Better Life
• /
• v.22 no.2
• /
• pp.59-67
• /
• 2004

As we enter into the 21C, it is important to reassess the knowledge and skills that are necessary for individual consumers and consumer professionals to be able to function efficiently in the rapidly changing society, and also to develop teaching tools fit to enhance the teaming of such knowledge and skills. The Purpose of this study is three-folds: 1) to identify key competencies necessary in the 21C consumer education, especially in higher education institutions, 2) to suggest 'experiential learning' as an ideal pedagogical tool for consumer education in the 21C century, and 3) to provide an example from an undergraduate classroom in the U.S. that applies 'service learning' as a teaching tool in a consumer studies curriculum. Discussions about the potentials for expanding this learning strategy are also provided.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.8 no.2
• /
• pp.1-10
• /
• 2012

In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The finite failure nonhomogeneous Poisson process models presented and the life distribution applied exponential and log shaped type hazard function. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than autonomous errors-detected factor that is generally efficient model could be confirmed. This paper, a failure data analysis of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and coefficient of determination.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.7 no.2
• /
• pp.1-8
• /
• 2011

In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The finite failure non-homogeneous Poisson process models presented and the life distribution applied extreme distribution which used to find the minimum (or the maximum) of a number of samples of various distributions. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than automatic error that is generally efficient model could be confirmed. This paper, a numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error.

• 한국정보컨버전스학회:학술대회논문집
• /
• 2008.06a
• /
• pp.205-208
• /
• 2008

Contents application from contents development of web technical base and with the operation different environment information of the educational resources integration the importance and necessity of the management central chain e-Learning system will be able to operate are raising its head with base. Is the actual condition which develops the development process where but, the education application currently is not standardized in base. Approaches with an educational domain from the present paper consequently, and defines MDA(Model Driven Architecture) coats e-Learning System. Also uses a studying contents standard metadata and about the contents storage space analyzes and plans the core property which uses MDA automatic tools leads and under developing boil e-Learning System will be able to provide the contents which does in actual professor own necessity.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.8 no.3
• /
• pp.196-201
• /
• 2008

Statistical learning theory has three analytical tools which are support vector machine, support vector regression, and support vector clustering for classification, regression, and clustering respectively. In general, their performances are good because they are constructed by convex optimization. But, there are some problems in the methods. One of the problems is the subjective determination of the parameters for kernel function and regularization by the arts of researchers. Also, the results of the learning machines are depended on the selected parameters. In this paper, we propose an efficient method for objective determination of the parameters of support vector clustering which is the clustering method of statistical learning theory. Using evolutionary algorithm and bootstrap method, we select the parameters of kernel function and regularization constant objectively. To verify improved performances of proposed research, we compare our method with established learning algorithms using the data sets form ucr machine learning repository and synthetic data.

• Journal of Engineering Education Research
• /
• v.24 no.4
• /
• pp.41-51
• /
• 2021

This paper is to study whether cooperative learning applying group games becomes a teaching method that can increase interest and participation in class in calculus and the effect of the number of students. To increase interest and participation in class, the researcher conducted cooperative learning by applying smartphones and various game tools to group games. The consequences of the study confirmed that students' interest and participation in the class increased regardless of their mathematics basics. Therefore, it is expected that the calculus which is difficult for students to understand will be more easily approached by cooperative learning applying group games in the future.

• Biomolecules & Therapeutics
• /
• v.30 no.2
• /
• pp.179-183
• /
• 2022

Traditionally, pathologists microscopically examine tissue sections to detect pathological lesions; the many slides that must be evaluated impose severe work burdens. Also, diagnostic accuracy varies by pathologist training and experience; better diagnostic tools are required. Given the rapid development of computer vision, automated deep learning is now used to classify microscopic images, including medical images. Here, we used a Inception-v3 deep learning model to detect mouse lung metastatic tumors via whole slide imaging (WSI); we cropped the images to 151 by 151 pixels. The images were divided into training (53.8%) and test (46.2%) sets (21,017 and 18,016 images, respectively). When images from lung tissue containing tumor tissues were evaluated, the model accuracy was 98.76%. When images from normal lung tissue were evaluated, the model accuracy ("no tumor") was 99.87%. Thus, the deep learning model distinguished metastatic lesions from normal lung tissue. Our approach will allow the rapid and accurate analysis of various tissues.