• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.25-34
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• 2022

Today, further education of adults in the UK is one of the developing areas of continuing education. The Open University with distance learning, in the process of which innovative forms and methods based on computer and telecommunication technologies are used, is particularly successful in the organization of additional education of the adult population. The advantages of distance learning, multimedia - the latest information technologies, which provide the combination of graphic images, video, sound with the help of modern computer tools, are noted. The basic principles and forms underlying the technologies and forms of work with the elderly are defined. The international experience of implementing "Universities of the Third Age" is summarized. The most widespread approach in adult education in Great Britain is informational. The use of computer technologies motivates a new paradigm in educational methods and strategies, which requires new approaches, forms of learning, and innovative ways of delivering educational materials to adult learners. Information technologies have gained great popularity in such activities as distance learning, online learning, assistance in the education management system, development of programs and virtual textbooks in various subjects, online search for information for the educational process, computer testing of students' knowledge, creation of electronic libraries, formation of a single scientific electronic environment, publication of virtual magazines and newspapers on pedagogical topics, teleconferences, expansion of international cooperation in the field of Internet education. The information technology of synchronous distance learning "online" has gained considerable popularity in the educational process today. A promising direction is the use of multimedia technologies in educational activities to create a design of a virtual computer environment by decoding audiovisual information.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.2
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• pp.93-114
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• 2023

In accordance with the educational paradigm that values self-directed creative education, school libraries and public libraries emphasize self-directed learning support through curriculum-linked programs as their main tasks. For self-directed learning, it is essential to provide learner-centered educational knowledge information, and there should be abundant textbook-linked references that can deepen and expand the curriculum reflected in textbooks. This study established KDC-linked information related to unit and cross-curricular learning topics through the analysis of elementary school textbooks and curriculum-linked books, restructured KDC system based on major subjects in the elementary school curriculum, and established a curriculum-linked subject information. Libraries can strengthen support for self-directed creative learning for elementary school students in an online environment by linking library content targeted for each user with elementary school education content focusing on learning topics in the curriculum.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.20 no.2
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• pp.109-128
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• 2009

In the 21st century, Korean society has continually changed into information society, knowledge society, and recently ubiquitous society. Therefore, 'ubituious' has become one of the most popular terms, and in many sectors of our society the ubiquitous environment has become more and more realities. And, universities are facing the need for changes in teaching and learning as well as library services. In this research, to enhance and vitalize the ubiquitous learning and academic library services, the following topics are discussed: First, the concept of 'ubiquitous' is defined and its major elements are examined. Second, the trend of establishing the information environment in higher education and developing the ubiquitous learning are investigated. Third, the present situation of ubiquitous campus and libraries are reviewed. Fourth, proposed are the strategies of developing those ubiquitous learning and library services in universities in Korea.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.35 no.2
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• pp.135-156
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• 2024

Librarians facing the new information environment need to actively cope with knowledge and skills, but librarians in outsourced public libraries are burdened with participation in external education due to concerns about work gaps or inadequate institutional support, making it difficult to continue their education. Therefore, in this study, in order to create an environment in which librarians can grow together, the current status of the activities of the learning community was checked and the effects were identified. An online survey was conducted from May 20 to 22, 2023, targeting librarians who had participated in learning community activities among librarians belonging to the Gangnam-gu Library, and 101 copies were distributed to collect 81 copies and use them as analysis data. As a result of the study, it was confirmed that librarians are satisfied with the activities of the learning community and have a high level of understanding and empathy for their necessity. Therefore, as a way to revitalize the learning community, we propose to form a culture that promotes collaboration among members, share visions and values for learning community activities, and provide institutional support.

• Journal of Korean Academy of Nursing
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• v.46 no.1
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• pp.90-99
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• 2016

Purpose: This study was conducted to examine effects of a learning portfolio by identifying the learning of nursing students taking a learning portfolio-utilized nursing management class. Methods: A non-equivalent control group pretest-posttest design was used. Participants were 83 senior students taking the nursing management course in one of the Departments of Nursing at 2 Universities. Experimental group (n=42) received a learning portfolio-utilized nursing management class 15 times over 15 weeks (3 hours weekly). Self-directed learning abilities, approaches to learning and learning flow of the participants were examined with self-report structured questionnaires. Data were collected between September 2 and December 16, 2014, and were analyzed using chi-square test, Fisher's exact test, independent t-test and ANCOVA with SPSS/PC version 21.0. Results: After the intervention the experimental group showed significant increases in self-directed learning abilities, deep approaches to learning and learning flow compared to the control group. However, no significant difference was found between groups for surface approaches to learning. Conclusion: Learning activities using the learning portfolios could be effective in cultivating the learning competency for growth of knowledge, technology and professionalism by increasing personal concentration and organization ability of the nursing students so that they can react to the rapidly changing environment.

• Journal of Korean Clinical Health Science
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• v.4 no.2
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• pp.571-581
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• 2016

Purpose. This study was to identify the relationship between self-directed learning and nursing student's satisfaction of clinical practice. Methods. This study was designed to measure the level of satisfaction according to the contents, guidance, environment, time, and the evaluation of clinical practice. Two hundred thirty-one nursing student from baccalaureate program in H-gun was sampled. A scale consisting of 75 questions, developed by the researcher, was used to gather data from September 14 through 27, 2012. The data was analyzed by descriptive statistics, paired t-test, pearson correlation, and multiple linear regression using the SPSS WIN 18.0 program. Results. The results were summarized : Self-directed learning didn't show a significant different by grade(t=0.83, p=.934). Nursing student's satisfaction of clinical practice didn't show a significant different by grade(t=0.26, p=.798). The relationship between self-directed learning correlated with the degree of nursing student's satisfaction in clinical practice(r=.44, p<.001). The factors of self-directed learning described nursing student's satisfaction of clinical practice as $R^2$=.215(F=9.858, p<.001). Conclusions. It was found that a higher degree of satisfaction in clinical practice depends on a higher degree of self-directed learning. Therefore, nursing faculty should plan intervention to improve satisfaction level of clinical practice by fostering self-directed learning.

• Journal of dental hygiene science
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• v.17 no.5
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• pp.383-397
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• 2017

We attempted to develop a problem-based learning (PBL) module for integrated education in dental hygiene with the aim of helping students gain clinical competencies necessary for dental hygienist work. To develop the PBL Module for Clinical Dentistry in Dental Hygiene course, the researchers identified literature related to not only educational technology, but also medical science, nursing, dentistry, and dental hygiene. During the design phase of the PBL module, problem scenarios and a plan for the teaching and learning process were developed. Developing problem scenarios involved describing a problematic situation and three questions related with that situation. To cultivate competencies required in dental clinics, each question was related to the diagnosis of a dental disease, dental treatment, and dental hygiene procedures for care. Teaching-learning process plan included the designs of operating environment, operational strategies, learning resources, facilitation of problem-solving process, and evaluation. It is necessary to evaluate the PBL module for integrated education in dental hygiene to confirm its effectiveness.

• Journal of Korea Multimedia Society
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• v.21 no.5
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• pp.571-582
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• 2018

Recently, development of deep learning has shown better image classification result than human. According to recent research, a hidden layer of deep learning is deeper, and a preservation of extracted features shows good results. However, in the case of general images, the extracted features are clear and easy to sort. This study aims to classify plant leaf images. This plant leaf image has high similarity in each image. Since plant leaf images have high similarity not only between images of different species but also within the same species, classification accuracy is not increased by simply extending the hidden layer or connecting the layers. Therefore, in this paper, we tried to improve the hidden layer of the algorithm called DenseNet which shows the recent excellent classification results, and compare the results of several different modified layers. The proposed method makes it possible to classify plant leaf images collected in a natural environment more easily and accurately than conventional methods. This results in good classification of plant leaf image data including unnecessary noise obtained in a natural environment.

• Journal of The Korean Association of Information Education
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• v.9 no.1
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• pp.79-86
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• 2005

With the rapid advance of computer and communication technology, the amount of data transferred is also increasing more than ever. The recent trend of education systems is connecting related information semantically in different systems in order to improve the utilization of computerized information Therefore, Web-based teaching-learning is developing in the ubiquitous learning direction that learners select and organize the contents, time and order of learning by themselves. That is, it is evolving to provide teaching-learning environment adaptive to individual learners' characteristics (their level of knowledge, pattern of study, areas of interest). This paper proposes the efficient evaluation method of learning contents in a mediator for the integration of heterogeneous information resources. This means that the autonomy of a remote server can be preserved to the highest degree. In addition, this paper proposes the adaptive optimization of learning contents such that available storage in a mediator can be highly utilized at any time. In order to differentiate the recent usage of a learning content from the past, the accumulated usage frequency of a learning content decays as time goes by.

• Geomechanics and Engineering
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• v.25 no.1
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• pp.1-16
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• 2021

Machine learning models have been widely used for landslide susceptibility assessment (LSA) in recent years. The large number of inputs or conditioning factors for these models, however, can reduce the computation efficiency and increase the difficulty in collecting data. Feature selection is a good tool to address this problem by selecting the most important features among all factors to reduce the size of the input variables. However, two important questions need to be solved: (1) how do feature selection methods affect the performance of machine learning models? and (2) which feature selection method is the most suitable for a given machine learning model? This paper aims to address these two questions by comparing the predictive performance of 13 feature selection-based machine learning (FS-ML) models and 5 ordinary machine learning models on LSA. First, five commonly used machine learning models (i.e., logistic regression, support vector machine, artificial neural network, Gaussian process and random forest) and six typical feature selection methods in the literature are adopted to constitute the proposed models. Then, fifteen conditioning factors are chosen as input variables and 1,017 landslides are used as recorded data. Next, feature selection methods are used to obtain the importance of the conditioning factors to create feature subsets, based on which 13 FS-ML models are constructed. For each of the machine learning models, a best optimized FS-ML model is selected according to the area under curve value. Finally, five optimal FS-ML models are obtained and applied to the LSA of the studied area. The predictive abilities of the FS-ML models on LSA are verified and compared through the receive operating characteristic curve and statistical indicators such as sensitivity, specificity and accuracy. The results showed that different feature selection methods have different effects on the performance of LSA machine learning models. FS-ML models generally outperform the ordinary machine learning models. The best FS-ML model is the recursive feature elimination (RFE) optimized RF, and RFE is an optimal method for feature selection.