• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.95-103
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• 2023

This paper proposes an artificial intelligence convergence education program for teaching the main concept and principle of Support Vector Machines(SVM) at elementary schools. The developed program, based on Jeju's natural environment theme, explains the decision boundary and margin of SVM by vertical and parallel from 4th grade mathematics curriculum. As a result of applying the developed program to 3rd and 5th graders, most students intuitively inferred the location of the decision boundary. The overall performance accuracy and rate of reasonable inference of 5th graders were higher. However, in the self-evaluation of understanding, the average value was higher in the 3rd grade, contrary to the actual understanding. This was due to the fact that junior learners had a greater tendency to feel satisfaction and achievement. On the other hand, senior learners presented more meaningful post-class questions based on their motivation for further exploration. We would like to find effective ways for artificial intelligence convergence education for elementary school students.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.97-117
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• 2020

Product evaluation criteria is an indicator describing attributes or values of products, which enable users or manufacturers measure and understand the products. When companies analyze their products or compare them with competitors, appropriate criteria must be selected for objective evaluation. The criteria should show the features of products that consumers considered when they purchased, used and evaluated the products. However, current evaluation criteria do not reflect different consumers' opinion from product to product. Previous studies tried to used online reviews from e-commerce sites that reflect consumer opinions to extract the features and topics of products and use them as evaluation criteria. However, there is still a limit that they produce irrelevant criteria to products due to extracted or improper words are not refined. To overcome this limitation, this research suggests LDA-k-NN model which extracts possible criteria words from online reviews by using LDA and refines them with k-nearest neighbor. Proposed approach starts with preparation phase, which is constructed with 6 steps. At first, it collects review data from e-commerce websites. Most e-commerce websites classify their selling items by high-level, middle-level, and low-level categories. Review data for preparation phase are gathered from each middle-level category and collapsed later, which is to present single high-level category. Next, nouns, adjectives, adverbs, and verbs are extracted from reviews by getting part of speech information using morpheme analysis module. After preprocessing, words per each topic from review are shown with LDA and only nouns in topic words are chosen as potential words for criteria. Then, words are tagged based on possibility of criteria for each middle-level category. Next, every tagged word is vectorized by pre-trained word embedding model. Finally, k-nearest neighbor case-based approach is used to classify each word with tags. After setting up preparation phase, criteria extraction phase is conducted with low-level categories. This phase starts with crawling reviews in the corresponding low-level category. Same preprocessing as preparation phase is conducted using morpheme analysis module and LDA. Possible criteria words are extracted by getting nouns from the data and vectorized by pre-trained word embedding model. Finally, evaluation criteria are extracted by refining possible criteria words using k-nearest neighbor approach and reference proportion of each word in the words set. To evaluate the performance of the proposed model, an experiment was conducted with review on '11st', one of the biggest e-commerce companies in Korea. Review data were from 'Electronics/Digital' section, one of high-level categories in 11st. For performance evaluation of suggested model, three other models were used for comparing with the suggested model; actual criteria of 11st, a model that extracts nouns by morpheme analysis module and refines them according to word frequency, and a model that extracts nouns from LDA topics and refines them by word frequency. The performance evaluation was set to predict evaluation criteria of 10 low-level categories with the suggested model and 3 models above. Criteria words extracted from each model were combined into a single words set and it was used for survey questionnaires. In the survey, respondents chose every item they consider as appropriate criteria for each category. Each model got its score when chosen words were extracted from that model. The suggested model had higher scores than other models in 8 out of 10 low-level categories. By conducting paired t-tests on scores of each model, we confirmed that the suggested model shows better performance in 26 tests out of 30. In addition, the suggested model was the best model in terms of accuracy. This research proposes evaluation criteria extracting method that combines topic extraction using LDA and refinement with k-nearest neighbor approach. This method overcomes the limits of previous dictionary-based models and frequency-based refinement models. This study can contribute to improve review analysis for deriving business insights in e-commerce market.

• Journal of the Korean Society of Radiology
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• v.12 no.3
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• pp.403-407
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• 2018

Currently, the highest cancer death rate in Korea is lung cancer, which is a typical cancer that is difficult to detect early. Low-dose chest CT is being used for early detection, which has a greater lung cancer diagnosis rate of about three times than regular chest x-ray images. However, low-dose chest CT not only significantly reduces image resolution but also has a weak signal and is sensitive to noise. Also, air filled lungs are low-density organs and the presence of noise can significantly affect early diagnosis of cancer. This study used Visual C++ to set a circle inside a large circle with a density of 2.0, with a density of 1.0, which is the density of water, in which five small circle of mathematics have different densities. Gaussian noise was generated by 1%, 2%, 3%, and 4% respectively to determine the effect of noise on the mean value, the standard deviation value, and the relative noise ratio(SNR). In areas where the density difference between the large and small circles was greatest in the event of 1 % noise, the SNR in the area with the greatest variation in noise was 4.669, and in areas with the lowest density difference, the SNR was 1.183. In addition, the SNR values can be seen to be high if the same results are obtained for both positive and negative densities. Quality was also clearly visible when the density difference was large, and if the noise level was increased, the SNR was reduced to significantly affect the noise. Low-density organs or organs in areas of similar density to cancers, will have significant noise effects, and the effects of density differences on the probability of noise will affect diagnosis.

• Proceedings of the Korean Society for the Gifted Conference
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• 1994.08a
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• pp.1.2-37
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• 1994

Currently Korea encourages gifted high schoolers and junior high schoolers to participate in international achievement contests such as International Olympiads. Participants for these contests are selected nationwide among gifted students in areas of mathematics, physics, chemistry, and others. They go through a series of screening tests and programs. One of the screening processes IS Korean Olympiad School, which provides study programs each summer for student-candidates prior to following year's International Olympiads. Approximately 40 students of high schools and junior high schools, in each subject of study, gather at Korean Olympiad Summer School, and they go through intensive study programs during a short period of time. Out of 40 candidates,' less than 10 students are finally selected to participate in International Olympiads. In this study, a psycho-educational program called "Situation Coping Training Program" was developed to enhance ahievement motivation for these student-candidates. This study was to see if this training program actually improved their cognitive, emotive motivation factors, and to see how this training program affected their achievement level. Training was administered for five days. This training program was found effective for participants to increase self-efficacy, internal locus of control, and anxiety copmg. These cognitive and emotive motivation factors, other than intelligence, were found to have positive relationship with achievement level, of which self-efficacy and attribution style of students were found as two best predictors of achievement. This training program was perceived as necessary. by participants, and helpful for recovering self-confidence and self-control as well as coping pressure. Suggestions were made that this kind of training program be administered as a regular curriculum in preparative study programs such as Korean Olympiads, since cognitive, emotive motivation factors are related with achievement, and furthermore, be utilized in all gifted education programs in Korea. in Korea.

• Journal of Gifted/Talented Education
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• v.13 no.4
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• pp.65-94
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• 2003

The purpose of this study is to acquire the information on the current situation of students' selection process in order to renovate the system of picking up the students. As a first step of the study, we examined the validity of the factors of the single-out system such as qualification and the process for the application and the standards and proceeding of the selection. Then we analysed the result of the entrance examination of Hansung Science Highschool in 2002. The analysis was on the correlation between the result of entrance examination and the achievement in the school and the decision of the course after graduation. To know on the achievement of the students, we investigated the records of regular tests and asked the teachers' opinion in math and science classes. As a result, we gained the following points: First, the present single-out system has a danger of excluding students who are much talented in science and math field because it is based on students' achievements in middle schools; Second, the new selection system should consider the character and attitude of the applicants in addition to their knowledge; Third, the continuous observation of the teacher in middle school should be an important factor of the picking up system; Fourth, more questions requiring divergent thinking ability and inquiry skill should be developed as selective examination question. Also examination questions should cover the various contents from mathematics to science, and do not affect pre-learning; Finally, the system of present letting all students stand in one line should be changed into that of letting students in various lines. We can consider using multi-step selection system.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.97-113
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• 2016

Due to the growth of internet data and the rapid development of internet technology, "big data" analysis is actively conducted to analyze enormous data for various purposes. Especially in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of existing structured data analysis. Various studies on sentiment analysis, the part of text mining techniques, are actively studied to score opinions based on the distribution of polarity of words in documents. Usually, the sentiment analysis uses sentiment dictionary contains positivity and negativity of vocabularies. As a part of such studies, this study tries to construct sentiment dictionary which is customized to specific data domain. Using a common sentiment dictionary for sentiment analysis without considering data domain characteristic cannot reflect contextual expression only used in the specific data domain. So, we can expect using a modified sentiment dictionary customized to data domain can lead the improvement of sentiment analysis efficiency. Therefore, this study aims to suggest a way to construct customized dictionary to reflect characteristics of data domain. Especially, in this study, movie review data are divided by genre and construct genre-customized dictionaries. The performance of customized dictionary in sentiment analysis is compared with a common sentiment dictionary. In this study, IMDb data are chosen as the subject of analysis, and movie reviews are categorized by genre. Six genres in IMDb, 'action', 'animation', 'comedy', 'drama', 'horror', and 'sci-fi' are selected. Five highest ranking movies and five lowest ranking movies per genre are selected as training data set and two years' movie data from 2012 September 2012 to June 2014 are collected as test data set. Using SO-PMI (Semantic Orientation from Point-wise Mutual Information) technique, we build customized sentiment dictionary per genre and compare prediction accuracy on review rating. As a result of the analysis, the prediction using customized dictionaries improves prediction accuracy. The performance improvement is 2.82% in overall and is statistical significant. Especially, the customized dictionary on 'sci-fi' leads the highest accuracy improvement among six genres. Even though this study shows the usefulness of customized dictionaries in sentiment analysis, further studies are required to generalize the results. In this study, we only consider adjectives as additional terms in customized sentiment dictionary. Other part of text such as verb and adverb can be considered to improve sentiment analysis performance. Also, we need to apply customized sentiment dictionary to other domain such as product reviews.

• Journal of Science Education
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• v.36 no.2
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• pp.381-393
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• 2012

This study was analyzed that what kind of elements for STEAM, except scientific commonsense, are contained in 2009 revised chemistry textbooks I for high school students. So first, elements of STEAM in textbooks were examined by following three sections; by publishing company, each unit and area of textbook. For reference, new sub-elements of STEAM were set because existing elements of STEAM is incongruent with current textbooks. As a result, most chemistry textbooks included elements of STEAM properly for inter-related learning with the other fields. Every textbook had its unique learning methods for utilizing elements of STEAM and they were unified as one way. Depending on textbooks, learning methods were little bit different from the others. Also, detailed elements of STEAM contained in textbooks were classified just 14 types. And they were even focused on a few elements according to sort of textbook. Thus, it seemed that there was a certain limitation of current education of STEAM in chemistry Field. By the unit, according to the curriculum, contained elements of STEAM were different. Almost all elements of STEAM were located in I section. Consequently, it is difficult to include elements of STEAM if mathematics or history were not existed in curriculum. Lastly, by the area, most of all elements of STEAM were included in reference section. Almost all elements of STEAM were focused on art and culture. Thus, STEAM was used for utilization about chemical knowledge in substance. Otherwise, convergence training for approach method was not enough in chemical knowledge.

• Korean Journal of Cognitive Science
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• v.27 no.2
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• pp.159-219
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• 2016

Mathematical ability is important for academic achievement and technological renovations in the STEM disciplines. This study concentrated on the relationship between neural basis of mathematical cognition and its mechanisms. These cognitive functions include domain specific abilities such as numerical skills and visuospatial abilities, as well as domain general abilities which include language, long term memory, and working memory capacity. Individuals can perform higher cognitive functions such as abstract thinking and reasoning based on these basic cognitive functions. The next topic covered in this study is about individual differences in mathematical abilities. Neural efficiency theory was incorporated in this study to view mathematical talent. According to the theory, a person with mathematical talent uses his or her brain more efficiently than the effortful endeavour of the average human being. Mathematically gifted students show different brain activities when compared to average students. Interhemispheric and intrahemispheric connectivities are enhanced in those students, particularly in the right brain along fronto-parietal longitudinal fasciculus. The third topic deals with growth and development in mathematical capacity. As individuals mature, practice mathematical skills, and gain knowledge, such changes are reflected in cortical activation, which include changes in the activation level, redistribution, and reorganization in the supporting cortex. Among these, reorganization can be related to neural plasticity. Neural plasticity was observed in professional mathematicians and children with mathematical learning disabilities. Last topic is about mathematical creativity viewed from Neural Darwinism. When the brain is faced with a novel problem, it needs to collect all of the necessary concepts(knowledge) from long term memory, make multitudes of connections, and test which ones have the highest probability in helping solve the unusual problem. Having followed the above brain modifying steps, once the brain finally finds the correct response to the novel problem, the final response comes as a form of inspiration. For a novice, the first step of acquisition of knowledge structure is the most important. However, as expertise increases, the latter two stages of making connections and selection become more important.

• Communications of Mathematical Education
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• v.27 no.1
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• pp.63-80
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• 2013

Reflecting the recent trends and needs of gifted education, this study set out to compare and analyze mathematically gifted elementary students and common students in self-efficacy and career attitude maturity, understand the characteristics of the former, and provide assistance for career education for both the groups. The subjects include 237 mathematically gifted elementary students and 221 common students in D Metropolitan City. The research findings were as follows: First, mathematically gifted elementary students turned out to have higher self-efficacy than common students at the significance level of .01 in the three self-efficacy subfactors, namely confidence, self-regulated efficacy, and task difficulty preference. The findings indicate that mathematically gifted elementary students have much confidence in themselves and strong faith in themselves, thus forming a habit of preferring a relatively high-level task by taking self-management and task difficulty into proper consideration. Second, mathematically gifted elementary students showed higher overall career attitude maturity than common students. There was significant difference at the significance level of .01 in decisiveness and preparedness between the two groups and significant difference at the significance level of .05 in assertiveness. However, there was no statistically significant difference in purposefulness and independence between the two groups. Finally, there were positive correlations at the significance level of .01 between all the subfactors of self-efficacy and those of career attitude maturity in all the subjects except for self-regulated efficacy and purposefulness, between which there were positive correlations at the significance level of .05. The mathematically gifted elementary students showed positive correlations between more subfactors of self-efficacy and career attitude maturity than common students. Given those findings, it is necessary to take differences in self-efficacy and career attitude maturity between mathematically gifted elementary students and common students into account when organizing and running a curriculum. The findings confirm the importance of providing students with various experiences fit for them and point to a need for helping mathematically gifted elementary students maintain a high level of self-efficacy and guiding them through career education with more appropriate career attitude maturity improvement programs.

• Journal of the Korean Chemical Society
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• v.59 no.2
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• pp.164-178
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• 2015

The purpose of this study was to design a teaching and learning method conductive to the development of creative thinking skills and investigate its effects. It has been developed integrated mind map with feature of visualizing the divergent thinking to the aspects of Science (S), Technology (T) & Engineering (E), Arts (A), Mathematics (M). Integrated mind map can be divided into four types of STEAM type, STEA type, STEM type, STE type depending on the category of key words in the first branch. And Integrated mind map can be divided into three levels of guided, intermediate, open depending on the teacher's guide degree. And also integrated mind map activities were carried out in the form of group, class share as well as individual. This study was implemented during a semester and students in experiment group experienced individual-integrated mind map activity 10 times, group-integrated mind map activity 10 times, class share-integrated mind map activity 3 times. The results indicated that the experimental group presented statistically meaningful improvement in creative thinking skills (p<.05). And there was a statistically meaningful improvement in fluency, flexibility, originality as a sub-category of creative thinking skills(p <.05). Also creative thinking skills are not affected by the level of cognitive, academic performance, gender (p<.05). In conclusion, it was found that 'integrated mind map activity' improved student's creative thinking skills. There was no interaction effect about creative thinking skills between the teaching strategy and cognitive level, achivement, gender of those students.