• Journal of Korean Home Economics Education Association
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• v.33 no.2
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• pp.57-80
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• 2021

The purpose of this research is to develop a Home Economics education curriculum that can promote citizenship through critical literacy. To this end, the 'housing' area in the 2015 revised curriculum of home economics and textbooks were analyzed from a critical literacy perspective. Using Laster(1986)'s critical science curriculum development course and "A Teacher's guideFamily, Food and Society"(Staaland & Storm, 1996), a 'Citizenship raising curriculum of home economics education in the housing area.' was developed. The results of this research are as follows. First, when the the curriculum was examined, the teaching objectives of the overall subject, or the achievement criteria, learning elements, and evluative methods of the housing area consisted of practical problem solving curriculum that can include critical literacy content. In addition, as a result of analyzing the text of the three textbooks' housing areas, it was found that most of them were described as adapting to and coping with the current culture, and few problems or social issues were mentioned that could lead to critical literacy. Second, the housing area curriculum for critical literacy learning was developed, with a total of 13 plan of 7 modules including continuous interests, valued ends, learning contents, and 26 learning materials including reading materials, and video materials. Based on the findings, the next curriculum and textbook should address social issues related to critical literacy and various classes of housing, and teachers' communities and training should be operated to support teachers who can be examplary for practical reasoning and critical thinking.

• Journal of vocational education research
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• v.35 no.4
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• pp.155-176
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• 2016

This study analyzed content of and recognition on occupations shown from Technology Home Economics textbooks of the high school elective subject having a higher connection with the career development capability for the occupational world as shown from a curriculum analysis. Hence, this study selected 3 kinds of high school Technology Home Economics textbooks with a higher share from 6 in the 2007 revised curriculum and analyzed a frequency by characteristic of occupational content and recognition on description of a occupation. Content analyzed by researchers was examined by 2 school teachers to ensure the validity and objectivity of research findings. Research findings show that there is a great deal of frequency difference in occupations suggested by publisher and unit in the Technology Home Economics subject. Also suggestion frequency of the occupational classification by level from Korean standard industrial classification did not correspond to an actual situation of employment. Occupation names suggested from textbooks occupied 3.3% of those by Korean Occupation Dictionary, showing a higher suggestion ratio at occupations preferred by adolescents. In the textbooks, occupations were suggested from reading materials, photos and illustrations more than from texts. Recognition on descriptions of occupations showed for the most part the neutral(82.8%) and the positive16.2%)', and there was no biased intention even from some negative cases(1.0%). Based on research findings, this research has significance in that it suggested things to be considered for teaching career development capability in the high school Technology Home Economics subject and need for cultivating teachers' specialty to understand occupations and instruct career development. It also suggested improvements to be required for a new curriculum textbook.

• Journal of Korean Elementary Science Education
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• v.37 no.4
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• pp.402-415
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• 2018

This study aims to inquire into the U. S. elementary school teachers' storylines for science teaching methods, scientific knowledge and interactions with students. As research subjects, two American elementary school teachers, named Christina and Melissa, were selected. As test tools, this study adopted Storyline Test and semi-structured interviews. Firstly, in regard to the science teaching method, Christina evaluated that she gradually improved her science teaching skills up to positive 6 points, starting from 2 points in the first year of teaching career, while Melissa sustained a stable state with 5 points in the 9th year of teaching career, starting from 1 point in the first year of teaching career. It was found that both the teachers had more confidence in their science teaching methods by participating in various training programs. Secondly, Christina evaluated her scientific knowledge in the first year of teaching career as 4 points, but evaluated her present scientific knowledge as stable as 6 points since she started studying teaching materials actively, discussing with other teachers and having more ability of application through science class integrated with other school subjects, in the 7th year of her teaching career. On the other hand, Melissa evaluated her scientific knowledge in the first year of teaching career as 1 point since she did not exactly know what to teach elementary school students, but in the 6th year of teaching career, she sustained a stable state with points through joint-activities with other teachers. It was found that chances to research with other teachers had important effect on both the teachers' confidence in scientific knowledge. Thirdly, in regard to interactions with students in science class, Christina said that she did not have any interaction with students when instructing inquiry activities in the first year of teaching career, but since the 10th year of her teaching career, she had sustained a stable state with 6 points through active interaction with students, by leading learning projects and science competitive exhibitions, etc. On the other hand, Melissa evaluated her interaction with students in the first year of teaching career as 1 point because her class was reading-oriented, but since the 9th year of teaching career, she had sustained a stable state with 6 points so far, by developing inquiry activity strategies to improve interaction with students. Overall, it was found that inquiry activities played a central role in improving both the teachers' interaction with students.

• Journal of Korean Library and Information Science Society
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• v.52 no.4
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• pp.103-126
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• 2021

This study aims to propose a plan to restructure libraries as a complex space for education and culture for 19 public libraries belonging to the Chungcheongnam-do Office of Education. For the purpose of this, case surveys and user surveys of complex facilities of domestic and foreign public institutions were conducted. Based on the findings, a space restructuring strategy was suggested by dividing the library space into the following ways: a space to learn (a comprehensive data room, a theme data inquiry room, a future classroom, a blended learning center, a STEAM training room, and an online lecture learning room), a space to express (a foyer, a maker room, a digital media creation room and an online lecture production room), a space to share (a club room, a group study room, a well-being complex culture space, a convenient living space, rest area, and a browsing area), and a space to enjoy (a performance-thought playground, infant and child archives, a digital virtual experience room, a specialized alcove room, and an outdoor reading room). In addition, a restructuring model of public libraries belonging to the Office of Education was proposed, such as a leading model, a basic model, a joint model, and a minimum model, in consideration of the size of the building, the size of the library, and the level of service and space.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.1
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• pp.167-188
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• 2023

This study reviewed the current status of low-experienced teacher librarians with less than 5 years and attempted to identify their educational needs through IPA analysis, Borich Priority Formula, and The Locus for Focus Model. A survey was conducted on low-experienced teacher librarians with less than 5 years of experience to analyze their process in the pre-service teacher training and experiences before an appointment and to identify teacher librarians instructional expertise. The results of the analysis of the study are as follows. First, there was a statistically significant difference between the importance and performance in all areas of instructional expertise of low-experienced teacher librarians. Second, 'reading education-practice progress' was recognized as a 'Keep up good work' with high importance and satisfaction, and 'library-based instruction planning, progress evaluation', 'information literacy-curriculum design', and 'digital and media literacy education-progress and evaluation' were recognized as areas of 'Concentrate here' through IPA analysis. Third, In the Borich Priority Formula, 'teaching-learning evaluation', 'teaching-learning progress', and 'teaching-learning plan' in the Library based instruction area showed the highest educational needs. Fourth, the library-based instruction was shown to the high discrepancy/high importancy area as same as the Borich Proity Formula. The results of this study can provide implications for improving the instructional expertise of teacher librarians.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.15-24
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• 2022

The article clarifies the conditions for information, digital and educational accessibility for higher education seekers with disabilities in terms of distance learning caused by quarantine restrictions. It is established that such conditions are regulated by international and Ukrainian legal documents (The Standard Rules on the Equalization of Opportunities for Persons with Disabilities, Convention on the Rights of Persons with Disabilities, Sustainable Development Goals, Law of Ukraine "On Education", Law of Ukraine "On Higher Education", Strategy for the Development of Higher Education in Ukraine 2021-2031, Development Strategy areas of innovation for the period up to 2030, Development strategy of the sphere of innovation activity for the period up to 2030). As a part of information barrierlessness, Higher Education Institutions (HEI) should provide access to information in various formats and using technologies, in particular Braille script, large-type printing, audio description (audio descriptive commenting), sign language interpretation, subtitling, a format suitable for reading by screen access programs, formats of simple speech, easy-to-read formats, means of alternative communication. The experience of Pavlo Tychyna Uman State Pedagogical University is described. In particular, special attention is paid to the study of sign language: in view of this, the initiative group implemented the project "Learning to hear and overcome social isolation together" with the financial support of the British Council in Ukraine. Within the framework of digital accessibility, the official website of the Faculty of Social and Psychological Education has been adapted for the visually impaired in accordance with WCAG 2.0 World Standards. In 2021, Pavlo Tychyna Uman State Pedagogical University implemented the project "Cultural, Recreational and Tourist Cherkasy Region: Inclusive Social 3D Map" funded by the Ukrainian Cultural Foundation; a site with available content for online travel in the region to provide barrier-free access to the historical and cultural heritage of Cherkasy region was created. Educational accessibility is achieved by increasing the number of people with special educational needs, receiving education in inclusive groups; activities of the Center for Social and Educational Integration and Inclusive Rehabilitation Social Tourism "Bez barieriv" ("Without barriers"); implementation of a research topic for financing the Ministry of Education and Science of Ukraine: "Social and psychological rehabilitation of children and youth with special educational needs by means of inclusive tourism"; implementation of the project "Social inclusion of distance educational process"; development of information campaigns to popularize the ideas of accessibility, the need for its implementation, ongoing training programs and competitions, etc.

• Korean Journal of Radiology
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• v.23 no.3
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• pp.343-354
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• 2022

Objective: To develop and evaluate a deep learning-based artificial intelligence (AI) model for detecting skull fractures on plain radiographs in children. Materials and Methods: This retrospective multi-center study consisted of a development dataset acquired from two hospitals (n = 149 and 264) and an external test set (n = 95) from a third hospital. Datasets included children with head trauma who underwent both skull radiography and cranial computed tomography (CT). The development dataset was split into training, tuning, and internal test sets in a ratio of 7:1:2. The reference standard for skull fracture was cranial CT. Two radiology residents, a pediatric radiologist, and two emergency physicians participated in a two-session observer study on an external test set with and without AI assistance. We obtained the area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity along with their 95% confidence intervals (CIs). Results: The AI model showed an AUROC of 0.922 (95% CI, 0.842-0.969) in the internal test set and 0.870 (95% CI, 0.785-0.930) in the external test set. The model had a sensitivity of 81.1% (95% CI, 64.8%-92.0%) and specificity of 91.3% (95% CI, 79.2%-97.6%) for the internal test set and 78.9% (95% CI, 54.4%-93.9%) and 88.2% (95% CI, 78.7%-94.4%), respectively, for the external test set. With the model's assistance, significant AUROC improvement was observed in radiology residents (pooled results) and emergency physicians (pooled results) with the difference from reading without AI assistance of 0.094 (95% CI, 0.020-0.168; p = 0.012) and 0.069 (95% CI, 0.002-0.136; p = 0.043), respectively, but not in the pediatric radiologist with the difference of 0.008 (95% CI, -0.074-0.090; p = 0.850). Conclusion: A deep learning-based AI model improved the performance of inexperienced radiologists and emergency physicians in diagnosing pediatric skull fractures on plain radiographs.

• Journal of the Korean Society of Radiology
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• v.85 no.4
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• pp.714-726
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• 2024

Researchers have developed various algorithms utilizing artificial intelligence (AI) to automatically and objectively diagnose patterns and extent of pulmonary emphysema or interstitial lung diseases on chest CT scans. Studies show that AI-based quantification of emphysema on chest CT scans reveals a connection between an increase in the relative percentage of emphysema and a decline in lung function. Notably, quantifying centrilobular emphysema has proven helpful in predicting clinical symptoms or mortality rates of chronic obstructive pulmonary disease. In the context of interstitial lung diseases, AI can classify the usual interstitial pneumonia pattern on CT scans into categories like normal, ground-glass opacity, reticular opacity, honeycombing, emphysema, and consolidation. This classification accuracy is comparable to chest radiologists (70%-80%). However, the results generated by AI are influenced by factors such as scan parameters, reconstruction algorithms, radiation doses, and the training data used to develop the AI. These limitations currently restrict the widespread adoption of AI for quantifying pulmonary emphysema and interstitial lung diseases in daily clinical practice. This paper will showcase the authors' experience using AI for diagnosing and quantifying emphysema and interstitial lung diseases through case studies. We will primarily focus on the advantages and limitations of AI for these two diseases.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.111-136
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• 2018

In this paper, we propose a methodology to extract answer information about queries from various types of unstructured documents collected from multi-sources existing on web in order to expand knowledge base. The proposed methodology is divided into the following steps. 1) Collect relevant documents from Wikipedia, Naver encyclopedia, and Naver news sources for "subject-predicate" separated queries and classify the proper documents. 2) Determine whether the sentence is suitable for extracting information and derive the confidence. 3) Based on the predicate feature, extract the information in the proper sentence and derive the overall confidence of the information extraction result. In order to evaluate the performance of the information extraction system, we selected 400 queries from the artificial intelligence speaker of SK-Telecom. Compared with the baseline model, it is confirmed that it shows higher performance index than the existing model. The contribution of this study is that we develop a sequence tagging model based on bi-directional LSTM-CRF using the predicate feature of the query, with this we developed a robust model that can maintain high recall performance even in various types of unstructured documents collected from multiple sources. The problem of information extraction for knowledge base extension should take into account heterogeneous characteristics of source-specific document types. The proposed methodology proved to extract information effectively from various types of unstructured documents compared to the baseline model. There is a limitation in previous research that the performance is poor when extracting information about the document type that is different from the training data. In addition, this study can prevent unnecessary information extraction attempts from the documents that do not include the answer information through the process for predicting the suitability of information extraction of documents and sentences before the information extraction step. It is meaningful that we provided a method that precision performance can be maintained even in actual web environment. The information extraction problem for the knowledge base expansion has the characteristic that it can not guarantee whether the document includes the correct answer because it is aimed at the unstructured document existing in the real web. When the question answering is performed on a real web, previous machine reading comprehension studies has a limitation that it shows a low level of precision because it frequently attempts to extract an answer even in a document in which there is no correct answer. The policy that predicts the suitability of document and sentence information extraction is meaningful in that it contributes to maintaining the performance of information extraction even in real web environment. The limitations of this study and future research directions are as follows. First, it is a problem related to data preprocessing. In this study, the unit of knowledge extraction is classified through the morphological analysis based on the open source Konlpy python package, and the information extraction result can be improperly performed because morphological analysis is not performed properly. To enhance the performance of information extraction results, it is necessary to develop an advanced morpheme analyzer. Second, it is a problem of entity ambiguity. The information extraction system of this study can not distinguish the same name that has different intention. If several people with the same name appear in the news, the system may not extract information about the intended query. In future research, it is necessary to take measures to identify the person with the same name. Third, it is a problem of evaluation query data. In this study, we selected 400 of user queries collected from SK Telecom 's interactive artificial intelligent speaker to evaluate the performance of the information extraction system. n this study, we developed evaluation data set using 800 documents (400 questions * 7 articles per question (1 Wikipedia, 3 Naver encyclopedia, 3 Naver news) by judging whether a correct answer is included or not. To ensure the external validity of the study, it is desirable to use more queries to determine the performance of the system. This is a costly activity that must be done manually. Future research needs to evaluate the system for more queries. It is also necessary to develop a Korean benchmark data set of information extraction system for queries from multi-source web documents to build an environment that can evaluate the results more objectively.

• The Korean Journal of Elementary Counseling
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• v.7 no.2
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• pp.101-115
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• 2008

The purposes of this study were to consist an anger control program in order to help children confirm and modify their cognitive errors in peer anger-provoking situations(Lee Mi-gyeong, 2006), that and to examine the effects of this program on anger-provoking experience, anger controllability and peer relationship. The cognitive-behavioral anger control program was consisted of 16 sessions. The focus of the program were placed on perceiving angry feelings, confirming automatic thinking and cognitive errors and acquiring how to correct the cognitive errors(1st-10th sessions), and checking cognitive errors in 13 anger-provoking situations and practicing way to correct the errors(11th-15th sessions). To examine the effects of the program, 10 children who had a lot of anger-provoking experiences, and were poor at anger control and faced difficulties with peer relationship were selected. The cognitive-behavioral anger control program was implemented for eight weeks, twice a week, 40 minutes each. The collected data were analysed by the ANOVA method using the SPSS and Kwakstat(Kwak Ho-wan, 1993). What cognitive errors children made and how they modified the errors during the program were checked. The findings of the study were as follows: The cognitive-behavioral anger control program served to cut down on the anger-provoking experiences, to improve their anger controllability, to boost their peer relationship, and that effect lasted till six weeks later. And the cognitive errors they made during the program were in the order as follows: stating the oughtness of their behavior, followed by naming, seeing everything in black and white, emotional judgment, mind reading, linking the situation to themselves, overgeneralizing, and hasty conclusion. The ways to correct the cognitive errors were in the order as follows: putting oneself in another's place, explaining in a different manner, looking for proof, thinking of it is so difficult to indure, thinging of there is moral to it, and thinking of how angry after passing time.