• Journal of The Korean Association For Science Education
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• v.36 no.4
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• pp.551-561
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• 2016

The purpose of this study is to investigate both theoretically and empirically the roles of models in abductive reasoning for scientific problem solving. The context of the study is design-based research the goal of which is to develop inquiry learning programs in the domain of earth science, and the current article dealt with an early process of redesigning an abductive inquiry activity in geology. In the theoretical study, an extensive review was conducted with the literature addressing abduction and modeling together as research methods characterizing earth science. The result led to a tentative scheme for modeling-based abductive inference, which represented relationships among evidence, resource models, and explanatory models. This scheme was improved by the empirical study in which experts' reasoning for solving a geological problem was analyzed. The new scheme included the roles of critical evidence, critical resource models, and a scientifically sound explanatory model. Pedagogical implications for the support of student reasoning in modeling-based abductive inquiry in earth science was discussed.

• Journal of the Korean Home Economics Association
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• v.34 no.4
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• pp.327-343
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• 1996

The objective of this study were 1) to determine the stages of concern of HE teachers about the practical problem-based curriculum approach, as illustrated by the Ohio's Work and Family Life Curriculum (W&FLC); 2) to determine the relationships between home economics (HE) teacher's stages of concern about W&FLC and personal and professional characteristics of HE teachers; and 3) to determine aspects of interest about the practical problem-based curriculum approach, such as the Ohio W&FLC. Respondents in this study were 225 HE teachers. The data were collected during the in-service teacher training sessions after presentation about W&FLC. Concerns Based Adoption Model (CBAM) was modified to provide a conceptual framework for this study. Frequencies, SD, mean, mode, range were used to determine the stages of concern of HE teachers. To determine the relationships between stages of concerns and personal and professional characteristics of HE teachers, coefficient of Chi-Square contingency tables was used. Content analysis was used to determine aspects of interest about the practical problem-bsed curriculum approach, such as W&FLC. The median of the stages of HE teachers' concerns about W&FLC was Stage 1, Information Stage. About 60% of HE teachers were interested in learning more details about W&FLC. Chi-square revealed no statistically significant relationships between stages of concerns about W&FLC and characteristics of HE teachers. Content analysis was used to determine aspects of interest about W&FLC of HE teachers. Nine categories were found: content, teaching strategies, implementation of the curriculum, philosophical framework, how to adopt W&FLC, resource materials, students' outcomes, in-service teacher training, and HE teacher organization. The majority of HE teachers were interested in relationships with family and others, resource management, family relationships, personal development, communication skill, family life, creating a self-identity, life planning, roles of family members, homemaking management, child care, and parenting.

• Journal of Information Technology Applications and Management
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• v.25 no.3
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• pp.43-54
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• 2018

In recent years, international cooperation has become important not only at the humanitarian level but also at the socio-economic level. As a result, major foreign countries are increasing capital-intensive international cooperation. In this environment, Korea needs to look for differentiated international cooperation plans centered on sustainable talent cultivation and move away from capital-based international cooperation. In this study, we analyzed the case of HRD (Human Resource Development) center in Cambodia as an international cooperation model between industry-academia-college for training software (SW) workforce. The HRD Center in Cambodia is an educational institution that fosters SW talent and can be viewed as an international cooperation model that can influence the ICT industry in Cambodia as an educational platform. In fact, 190 people who have been hired so far have entered various fields. 97% of graduates have been satisfied with HRD center and 90% of them are willing to recommend the center. In particular, as highlighted in the case study, the HRD Center has had a positive effect on not only cultivating self-initiated learning-based SW talent, but also formulating positive image of Korea and Korean companies thereby facilitating entry into the global market. The HRD Center in Cambodia has developed a virtuous cycle of fostering human resources, providing education, advancing industry and building a cooperative network. Korea has transformed into a platform for international cooperation and human resource development and education by providing active support and aid. This case study will be utilized as a new model of international cooperation with SW expert training platform for Korea.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5580-5593
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• 2019

A malicious Uniform Resource Locator (URL) recognition and detection method based on the combination of Attention mechanism with Convolutional Neural Network and Long Short-Term Memory Network (Attention-Based CNN-LSTM), is proposed. Firstly, the WHOIS check method is used to extract and filter features, including the URL texture information, the URL string statistical information of attributes and the WHOIS information, and the features are subsequently encoded and pre-processed followed by inputting them to the constructed Convolutional Neural Network (CNN) convolution layer to extract local features. Secondly, in accordance with the weights from the Attention mechanism, the generated local features are input into the Long-Short Term Memory (LSTM) model, and subsequently pooled to calculate the global features of the URLs. Finally, the URLs are detected and classified by the SoftMax function using global features. The results demonstrate that compared with the existing methods, the Attention-based CNN-LSTM mechanism has higher accuracy for malicious URL detection.

• Journal of Korean Academy of Nursing
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• v.40 no.4
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• pp.463-472
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• 2010

Purpose: This study was done to develop a web-based education program for nurses working in nursing homes. The focus was on the rights of older adults. Methods: The program was designed based on the Network-Based Instructional System Design (NBISD) model and was operated and evaluated between July 2007 and June 2008. Results: Out of nursing records of 40 residents from a nursing home, the final 7 cases were deducted through classification using the Resource Utilization Group (RUG)-III. The data on needs for education was collected from 28 nurses working in 15 nursing homes located in Seoul and Gyeonggi Province, who agreed to complete a self-report questionnaire. A comprehensive review of the literature and two focus groups interviews were used to search for risk factors and guidelines for protection of human rights. The education program was developed based on Kolb's experiential learning model and composed of 5 units, which included content on types of human rights and rights to death with dignity, elder abuse, physical liberty, and self-determination. The program was positively evaluated showing a score of 3.35 (SD=0.37) out of 4. Conclusion: The educational program developed in this study should promote nurses' sensitivity to the rights of elders and improve nurses' behaviors in protecting the rights of elders residing in nursing homes.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1107-1118
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• 2021

Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.

• Information Systems Review
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• v.19 no.2
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• pp.1-19
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• 2017

Original scripts of e-learning lectures for the CEOs of corporation S were analyzed using topic analysis, which is a text mining method. Twenty-two topics were extracted based on the keywords chosen from five-year records that ranged from 2011 to 2015. Research analysis was then conducted on various issues. Promising topics were selected through evaluation and element analysis of the members of each topic. In management and economics, members demonstrated high satisfaction and interest toward topics in marketing strategy, human resource management, and communication. Philosophy, history of war, and history demonstrated high interest and satisfaction in the field of humanities, whereas mind health showed high interest and satisfaction in the field of in lifestyle. Studies were also conducted to identify topics on the proportion of content, but these studies failed to increase member satisfaction. In the field of IT, educational content responds sensitively to change of the times, but it may not increase the interest and satisfaction of members. The present study found that content production for CEOs should draw out deep implications for value innovation through technology application instead of simply ending the technical aspect of information delivery. Previous studies classified contents superficially based on the name of content program when analyzing the status of content operation. However, text mining can derive deep content and subject classification based on the contents of unstructured data script. This approach can examine current shortages and necessary fields if the service contents of the themes are displayed by year. This study was based on data obtained from influential e-learning companies in Korea. Obtaining practical results was difficult because data were not acquired from portal sites or social networking service. The content of e-learning trends of CEOs were analyzed. Data analysis was also conducted on the intellectual interests of CEOs in each field.

• Journal of The Korean Association For Science Education
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• v.38 no.2
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• pp.187-202
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• 2018

This study posits that a more equitable science education is possible through analyzing the sociocultural mechanisms that operate in the participation and marginalization in science learning process, and therefore aims to review research trends in this area of science education. To do so, the study analyzed 85 articles that adopted a sociocultural approach to science learning identity in major international journals. The review was organized into 1) overall trends such as the number of articles by year, country, learner's sociocultural background, research context and research methods, and 2) a more in-depth analysis of the main research problems and conceptual frameworks along with concrete research examples. The study found that the current research works in this area have contributed to broadening the idea of legitimate learners in science education by considering learners' various sociocultural identities as the positive resource for learning based on the premise that science learning occurs as identity formation through participating communities of practice, and critiquing the culture or discourses that oppress such identity formation. The studies in this area also brought up the equity issue in science education in ways which embrace various learners that had been marginalized in the traditional science class and facilitate their agency. Based on these findings, the study made a case for analyzing various sociocultural mechanisms relating to the participation and marginalization in science learning to realize 'science education for all Koreans' and proposed future research direction.

• Journal of Korean Home Economics Education Association
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• v.34 no.1
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• pp.151-165
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• 2022

The aim of this study is to examine the effectiveness of non-face-to-face classes conducted due to the COVID-19 crisis. In order to achieve this goal, a non-face-to-face class with flipped learning was applied in one subject of clothing major held at 'S' University in Cheongju, Korea. In addition, this study tried to analyze the differences between pre- and post-non-face-to-face classes in problem analysis ability, resource/information/technology literacy, convergent thinking ability as core competencies, and overall learning satisfaction. As a result, after participating in the non-face-to-face class in which the flipped learning was applied, the students recognized that their abilities improved in the three problem-solving competency sub-areas, and their overall learning satisfaction also increased. The effectiveness of non-face-to-face classes in the field of clothing and fashion has been mainly measured in fashion design and clothing construction courses. However, based on the results of this study, it can be suggested that non-face-to-face classes in a theory-oriented lecture-type class can be effective methods for improving students' core competencies such as problem-solving skills if teaching-learning methods such as flipped learning are applied. Therefore, the results of this study will be useful data for designing differentiated non-face-to-face class strategies in a theory-oriented lecture-type class to improve the core competencies of college students.

• Journal of the Korean Society for Library and Information Science
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• v.51 no.4
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• pp.227-248
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• 2017

This paper introduces an integrated model for systematically constructing a linguistic resource database that can be used by machine learning-based biomedical information extraction systems. The proposed method suggests an orderly process of collecting and constructing dictionaries and training sets for both named-entity recognition and relation extraction. Multiple heterogeneous structures for the resources which are collected from diverse sources are analyzed to derive essential items and fields for constructing the integrated database. All the collected resources are converted and refined to build an integrated linguistic resource storage. In this paper, we constructed entity dictionaries of gene, protein, disease and drug, which are considered core linguistic elements or core named entities in the biomedical domains and conducted verification tests to measure their acceptability.