• Journal of The Korean Association For Science Education
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• v.39 no.6
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• pp.777-790
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• 2019

The purpose of this study is to investigate the experience of teachers who apply Smart-technology in elementary school STEAM class and the reasons, difficulties when applying the technology and required support. Semi-structured in-depth interviews were conducted with six elementary school teachers with specialized knowledge in STEAM education who have experienced STEAM lessons several times before. The research findings are as follows: First, research participants utilized a variety of Smart-technology in STEAM class, most of which were experiential or interactive technology. Among the STEAM learning criteria, the Smart-technology in 'Creative Design' course was most often applied. Second, they adopted Smart Technology in STEAM class to encourage students to feel interested, actively participate in the class, enjoy indirect experience, and nurture interest in state-of-the-art technology. They used it to prepare for future societies and organize classes that are suitable for STEAM learning criteria. They also used Smart-technology because it was easy to use. Third, they found it difficult to find, secure, and use suitable Smart-technology when applying Smart-technology in the STEAM class. They also had trouble restructuring the curriculum. In addition, there were difficulties in using Smart-technology in the class such as lack of class hours, increased level of activity, insufficient physical environment and unexpected malfunction of Smart-technology, thus interrupted the class. After the class, it was hard to manage Smart-technology and also, there were difficulties in assessment, record, and negative awareness of surrounding people. Fourth, they mentioned that's suggesting education guidelines, develop, and distribute educational materials are required to enable 'Creative Design,' reduce educational content, provide training, secure Smart-technology equipment and provide Wi-Fi, support teacher's club and communities and create an atmosphere to emotionally support teachers in order to activate using Smart-technology in STEAM class.

• Journal of The Korean Association For Science Education
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• v.35 no.2
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• pp.247-258
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• 2015

Students are engaged in classroom learning, and classroom learning occurs not only through conversation but also through nonverbal behavior. In science classrooms especially, there are meaningful nonverbal behaviors such as practical activities like observation and measurement. But these behaviors have not been properly investigated by existing instruments that try to measure students' engagement. This study aims to develop a new instrument for analyzing students' behavioral engagement especially in science classrooms. The method of developing the instrument was structured along three steps. First, student behaviors have been classified into fourteen categories through literature review and a series of observation of elementary science classroom. Second, based on these, a framework for analyzing student behavioral engagement has been developed. With the framework, every student moment could be labeled as Participatory Speech or Participatory Silence or Non-Participatory Speech or Non-Participatory Silence. Third, an instrument to which the framework is applied has been developed by using Microsoft Excel. As a trial, two fourth-grade students in elementary science class were analyzed with this instrument. The results of the trial analysis shows that the longest period of a science lesson was occupied by Participatory Silence (63% and 72%). Among the participatory silence, 'listening' was the most common (51% and 42% of the trial lesson) and 'observing' which is a specific behavior to science was the fourth position (17% and 17% of the trial lesson). It is expected that the developed instrument could be used in improving our understanding of the patterns of student engagement in science classrooms.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.1-13
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• 2015

As opinion mining in big data applications has been highlighted, a lot of research on unstructured data has made. Lots of social media on the Internet generate unstructured or semi-structured data every second and they are often made by natural or human languages we use in daily life. Many words in human languages have multiple meanings or senses. In this result, it is very difficult for computers to extract useful information from these datasets. Traditional web search engines are usually based on keyword search, resulting in incorrect search results which are far from users' intentions. Even though a lot of progress in enhancing the performance of search engines has made over the last years in order to provide users with appropriate results, there is still so much to improve it. Word sense disambiguation can play a very important role in dealing with natural language processing and is considered as one of the most difficult problems in this area. Major approaches to word sense disambiguation can be classified as knowledge-base, supervised corpus-based, and unsupervised corpus-based approaches. This paper presents a method which automatically generates a corpus for word sense disambiguation by taking advantage of examples in existing dictionaries and avoids expensive sense tagging processes. It experiments the effectiveness of the method based on Naïve Bayes Model, which is one of supervised learning algorithms, by using Korean standard unabridged dictionary and Sejong Corpus. Korean standard unabridged dictionary has approximately 57,000 sentences. Sejong Corpus has about 790,000 sentences tagged with part-of-speech and senses all together. For the experiment of this study, Korean standard unabridged dictionary and Sejong Corpus were experimented as a combination and separate entities using cross validation. Only nouns, target subjects in word sense disambiguation, were selected. 93,522 word senses among 265,655 nouns and 56,914 sentences from related proverbs and examples were additionally combined in the corpus. Sejong Corpus was easily merged with Korean standard unabridged dictionary because Sejong Corpus was tagged based on sense indices defined by Korean standard unabridged dictionary. Sense vectors were formed after the merged corpus was created. Terms used in creating sense vectors were added in the named entity dictionary of Korean morphological analyzer. By using the extended named entity dictionary, term vectors were extracted from the input sentences and then term vectors for the sentences were created. Given the extracted term vector and the sense vector model made during the pre-processing stage, the sense-tagged terms were determined by the vector space model based word sense disambiguation. In addition, this study shows the effectiveness of merged corpus from examples in Korean standard unabridged dictionary and Sejong Corpus. The experiment shows the better results in precision and recall are found with the merged corpus. This study suggests it can practically enhance the performance of internet search engines and help us to understand more accurate meaning of a sentence in natural language processing pertinent to search engines, opinion mining, and text mining. Naïve Bayes classifier used in this study represents a supervised learning algorithm and uses Bayes theorem. Naïve Bayes classifier has an assumption that all senses are independent. Even though the assumption of Naïve Bayes classifier is not realistic and ignores the correlation between attributes, Naïve Bayes classifier is widely used because of its simplicity and in practice it is known to be very effective in many applications such as text classification and medical diagnosis. However, further research need to be carried out to consider all possible combinations and/or partial combinations of all senses in a sentence. Also, the effectiveness of word sense disambiguation may be improved if rhetorical structures or morphological dependencies between words are analyzed through syntactic analysis.

• Journal of The Korean Association For Science Education
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• v.15 no.2
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• pp.173-184
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• 1995

The purpose of this study was to analyse the problems of 'Science Inquiry Experiment Contest(SIEC)' which was one of 8 programs of 'The 2nd Student Science Inquiry Olympic Meet(SSIOM)'. The results and conclusions of this study were as follows: 1. It needs to reconsider the role of practical work within science experiment because practical work skills form one of the mainstays in current science. But the assessment of students' laboratory skills in the contest was made little account of. It is necessary to remind of what it means to be 'good at science'. There are two aspects: knowing and doing. Both are important and, in certain respects, quite distinct. Doing science is more of a craft activity, relying more on craft skill and tacit knowledge than on the conscious application of explicit knowledge. Doing science is also divided into two aspects, 'process' and 'skill' by many science educators. 2. The report's and checklist's assessment items were overlapped. Therefore it was suggested that the checklist assessment items were set limit to the students' acts which can't be found in reports. It is important to identify those activities which produce a permanent assessable product, and those which do not. Skills connected with recording and reporting are likely to produce permanent evidence which can be evaluated after the experiment. Those connected with manipulative skills involving processes are more ephemeral and need to be assessed as they occur. The division of student's experimental skills will contribute to the accurate assess of student's scientific inquiry experimental ability. 3. There was a wide difference among the scores of one participant recorded by three evaluators. This means that there was no concrete discussion among the evaluators before the contest. Despite the items of the checklists were set by preparers of the contest experiments, the concrete discussions before the contest were necessary because students' experimental acts were very diverse. There is a variety of scientific skills. So it is necessary to assess the performance of individual students in a range of skills. But the most of the difficulties in the assessment of skills arise from the interaction between measurement and the use. To overcome the difficulties, not only must the mark needed for each skill be recorded, something which all examination groups obviously need, but also a description of the work that the student did when the skill was assessed must also be given, and not all groups need this. Fuller details must also be available for the purposes of moderation. This is a requirement for all students that there must be provision for samples of any end-product or other tangible form of evidence of candidates' work to be submitted for inspection. This is rather important if one is to be as fair as possible to students because, not only can this work be made available to moderators if necessary, but also it can be used to help in arriving at common standards among several evaluators, and in ensuring consistent standards from one evaluator over the assessment period. This need arises because there are problems associated with assessing different students on the same skill in different activities. 4. Most of the students' reports were assessed intuitively by the evaluators despite the assessment items were established concretely by preparers of the experiment. This result means that the evaluators were new to grasp the essence of the established assessment items of the experiment report and that the students' assessment scores were short of objectivity. Lastly, there are suggestions from the results and the conclusions. The students' experimental acts which were difficult to observe because they occur in a flash and which can be easily imitated should be excluded from the assessment items. Evaluators are likely to miss the time to observe the acts, and the students who are assessed later have more opportunity to practise the skill which is being assessed. It is necessary to be aware of these problems and try to reduce their influence or remove them. The skills and processes analysis has made a very useful checklist for scientific inquiry experiment assessment. But in itself it is of little value. It must be seen alongside the other vital attributes needed in the making of a good scientist, the affective aspects of commitment and confidence, the personal insights which come both through formal and informal learning, and the tacit knowledge that comes through experience, both structured and acquired in play. These four aspects must be continually interacting, in a flexible and individualistic way, throughout the scientific education of students. An increasing ability to be good at science, to be good at doing investigational practical work, will be gained through continually, successively, but often unpredictably, developing more experience, developing more insights, developing more skills, and producing more confidence and commitment.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.9 no.1
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• pp.98-104
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• 1998

A 12-year-old girl with a 6 year history of childhood-onset schizophrenia required 2 hospitalizations and long-term clozapine trial due to inadequate responses to combinations of typical neuroleptics and traditional treatments of schizophrenic disorder. On admission, she had continuous auditory and visual hallucinations, persecutory delusion, emotional instability, regression of behaviors including temper tantrums as well as specific developmental delays in learning, language, and motor coordination. The clozapine trial significantly reduced most of the positive symptoms, and facilitated in successful discharge from the hospital. During the 4 year clozapine treatment, no significant adverse reactions were noted, and she returned to a structured school setting with minimal degrees of schizophrenic symptoms. From this clinical experience, we suggest that clozapine might be safe and effective in treating treatment-refractory schizophrenic children.

• Journal of Science Education
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• v.38 no.3
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• pp.718-736
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• 2014

This study was intended to determine PCK of the middle school science teachers on Mendelian genetics and factors influenced to form their PCKs. Two science teachers with biology major with a teaching experience over 5 years were chosen as the subject. Data were collected by class observation, semi-structured interview, teacher questionnaire survey, Content Representation and Pedagogical and Professional-experience Repertoire. The collected data were analyzed based on Magnusson's PCK for science teaching consisting of five components: (a) the orientation toward teaching science, (b) the knowledge of science curriculum, (c) the knowledge of students' understanding, (d) the knowledge of assessment, and (e) the knowledge and belief in the instructional strategies to teach science. Teachers could have the orientation toward teaching science served as an assisting role to support students' abilities. Both subject teachers seemed to focus on giving lectures. Their efforts to improve students' exploration methods and abilities were not expressed enough in their real classes and they found that students struggled to understand Mendelian genetics. Therefore, they should have explained them in an easier way and worked harder to make their students understood accurately and applied basic and advanced concepts of Mendelian genetics. They found students' preconception and misconception regarding Mendelian genetics and wished to enhance their learning effects by various teaching strategies such as correcting misconception, adding the history of science and simply assessing students' affirmative domains. It was also found that factors influenced to form PCK regarding Mendelian genetics by both teachers were as follows: teacher's personality and endeavor, textbooks and guidance books, schools and their circumstances, teaching experience, experience as a learner, interaction with their colleagues, and university curriculum. Both teachers said that it was important for teachers to make every efforts to give better classes.

• The Journal of Korean Philosophical History
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• no.52
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• pp.9-35
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• 2017

This article is to study the life and philosophy of Jonjae Gidaeseung, who was at strife with his days and did not negotiate with himself, with focus on two concepts of buron(不穩, unrest) and 'sympathy'. It is the fact that to study the traditional philosopher is likely to be enlightening. In order to prevent the risk, we need to define first the concept of unrest as including anxiety to critical resistance. Also, I would like to propose the concept of sympathy in order to grasp the function of his mind which judges whether his feelings and actions are valid from an emotional horizon of unrest. Methodologically this article is to adopt a transversal and correlative thinking by combining an east Asian Confucian traditional concept unrest with a modern one space. It is because this research is to show a significant meaning when we study highlighted and hidden layers of our life and politics in 'now-here' and the 'between space' even though this transversal and correlative study shows the horizon of his life. This article is to investigate how a case is structured by occurrences and divergences and reinterpret a meaning from an emotional horizon. This process is done centering on two terms Guchatuan(pursuing ease ignobly), and Suwolbingho(moon reflected in the water and ice in a bottle), which is the source of Bingwoldang. The two terms were used by Jonjae himself. The latter shows an opposite meaning from the first and is accordingly a way by which we can look into his life and days. My research of Jonjae's life and politics from the emotional-philosophical level is original in that it reveals emotional traces beyond his philosophical ideas which previous studies did not show. In this article, I showed that Gobong was ambitious and resolute, and definite in his judgment and therefore was not good at controlling his uprightness. Also he was too straightforward to purify a language. His unrest characters made him conflict with old ministers and high ranking officials and therefore they avoided him even thought he was excellent in writing and learning and talented. He was oriented toward living by goodness and right Ways, which is summed up as Gisesa(vague movement, situational advantage, and death).

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.37-51
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• 2015

Due to the development of internet technology and the rapid increase of internet data, various studies are actively conducted on how to use and analyze internet data for various purposes. In particular, in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of the current application of structured data. Especially, there are various studies on sentimental analysis to score opinions based on the distribution of polarity such as positivity or negativity of vocabularies or sentences of the texts in documents. As a part of such studies, this study tries to predict ups and downs of stock prices of companies by performing sentimental analysis on news contexts of the particular companies in the Internet. A variety of news on companies is produced online by different economic agents, and it is diffused quickly and accessed easily in the Internet. So, based on inefficient market hypothesis, we can expect that news information of an individual company can be used to predict the fluctuations of stock prices of the company if we apply proper data analysis techniques. However, as the areas of corporate management activity are different, an analysis considering characteristics of each company is required in the analysis of text data based on machine-learning. In addition, since the news including positive or negative information on certain companies have various impacts on other companies or industry fields, an analysis for the prediction of the stock price of each company is necessary. Therefore, this study attempted to predict changes in the stock prices of the individual companies that applied a sentimental analysis of the online news data. Accordingly, this study chose top company in KOSPI 200 as the subjects of the analysis, and collected and analyzed online news data by each company produced for two years on a representative domestic search portal service, Naver. In addition, considering the differences in the meanings of vocabularies for each of the certain economic subjects, it aims to improve performance by building up a lexicon for each individual company and applying that to an analysis. As a result of the analysis, the accuracy of the prediction by each company are different, and the prediction accurate rate turned out to be 56% on average. Comparing the accuracy of the prediction of stock prices on industry sectors, 'energy/chemical', 'consumer goods for living' and 'consumer discretionary' showed a relatively higher accuracy of the prediction of stock prices than other industries, while it was found that the sectors such as 'information technology' and 'shipbuilding/transportation' industry had lower accuracy of prediction. The number of the representative companies in each industry collected was five each, so it is somewhat difficult to generalize, but it could be confirmed that there was a difference in the accuracy of the prediction of stock prices depending on industry sectors. In addition, at the individual company level, the companies such as 'Kangwon Land', 'KT & G' and 'SK Innovation' showed a relatively higher prediction accuracy as compared to other companies, while it showed that the companies such as 'Young Poong', 'LG', 'Samsung Life Insurance', and 'Doosan' had a low prediction accuracy of less than 50%. In this paper, we performed an analysis of the share price performance relative to the prediction of individual companies through the vocabulary of pre-built company to take advantage of the online news information. In this paper, we aim to improve performance of the stock prices prediction, applying online news information, through the stock price prediction of individual companies. Based on this, in the future, it will be possible to find ways to increase the stock price prediction accuracy by complementing the problem of unnecessary words that are added to the sentiment dictionary.