• Journal of The Korean Association For Science Education
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• v.37 no.2
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• pp.359-370
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• 2017

The purpose of this study is to explore the changes caused by using smart technology in school science inquiry. For this, we investigated 12 elementary school teachers' perceptions by using an open-ended questionnaire, group discussions, classroom discussions, and participant interviews. The results of this study indicate that the introduction of technology into classroom inquiry can open up the various possibilities and can cause additional burdens as well. First, teachers explained that smart technology can expand the opportunities to observe natural phenomena such as constellations and changing phases of the moon. However, some teachers insisted that, sometimes, learning how to use new devices disrupts students' concentration on the inquiry process itself. Second, teachers introduced the way of digital measurement using smart phone sensors in inquiry activities. They said that digital measurement is useful in terms of the reduction of errors and of the simplicity to measure. However, other teachers insisted that using new devices in classroom inquiry can entail additional variables and confuse the students' focus of inquiry. Communication about inquiry process can also be improved by using digital media. However, some teachers emphasized that they always talked about both the purpose of using SNS and online etiquettes with their students before using SNS. Based on these results, we discussed the necessity of additional analysis on the various ways of using digital devices depending on teachers' perceptions, the types of digital competency required in science inquiry using smart technology, and the features of norms shaped in inquiry activities using smart technology.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.12 no.3
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• pp.65-74
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• 2017

There have been questions how entrepreneurs think, act and why individuals become entrepreneurs. The trait-based explanation of entrepreneurial activities has been main stream. However, the trait-based theory has been criticized because it assumes that entrepreneurial traits are inherited, stable and enduring over time. This research accepts the cognitive theory to see how entrepreneurs learn or accept others' values, how entrepreneurial perceptions of opportunity impact entrepreneurial actions and how individuals acquire the social legitimation of the formation of entrepreneurial activities. In order to capture the attitudes, activities and motivations of people who are involved in entrepreneurial activities, the author uses the GEM Korea 2016 data. The data from the Global Entrepreneurship Monitor(GEM) has been well known for the data to capture individuals early-stage entrepreneurial activities. This paper used the sample from the APS(Adult Population Survey) of the GEM which was completed by a representative sample of two thousand adults in Korea by the qualified survey vendor, with strict procedures and oversight by the GEM central data team. The hypotheses are tested with logit regression analysis to estimate the probability of the influence of perceptual variables such as individual perception in social learning, the opportunity recognition in the environment, and social legitimation in the entrepreneurial activities. Based on the results, individuals tend to have high entrepreneurial activities if individuals have high self-efficacy. Also, the existence of role models around the entrepreneurs encourages the individuals involve in entrepreneurial activities more however the perception of opportunity in the environment is not strongly associated with entrepreneurial activities. The media exposure of successful entrepreneurs is more important than others' perception of entrepreneurs on the desirable career option or respect from communities. This paper can contribute to the cognitive processes, particular perception about oneself, as well as perception which is impacted by a community or a society.

• Journal of the Korean Society of Food Culture
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• v.18 no.4
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• pp.333-345
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• 2003

We conducted a survey on Japanese women's consciousness of food culture and their traditional food consumption by self filling-out questionnaire during January, 2000 for the period of a month, For the survey we selected 250 women residing in Kyoto, Japan. For the statistic work we used SAS package system, and t-test, $\cal{X}^2-test$ and Duncan's multiple range test were also used to verify the results significance. The purpose of this survey lies in gathering a basic data on the comparative direction of Korean and Japanese women's food culture in the future 1. Comparing the preferred food purchase place, In case of Korean women, traditional market was comparatively more preferred while Japanese women relatively preferred convenience store (p<0.001). 2. In case of Japanese women, they answered there is no difference from ordinary days on New Year's Day (71%) and Christmas (40%) while 38% answered they prepare food at home. 40% said they prepare food on parents-in-law's birthday, and 41% said no difference from ordinary days. 52% said they prepare food at home on husband's birthday. For their own birthday, 32% said yes to preparing food at home while 45% said no difference and 22.3% said eating out. For children's birthday 65% said preparing at home, 16.3% said no difference and 14.9% said eating out. 3. Comparing the conception on traditional food, Korean women answered 'complicated' (77%) most while 'simple' (5%) least, which indicates their demands for simplified recipes. In case of Japanese women, 'complicated' (44%) was most while 'scientific' (6%) was least which indicates their demands for scientific way of recipes. There were differences shown by age (p<0.001) and the older the more said 'simple' or 'logical' (p<0.01). 4. As the reason for the complicity of traditional food recipes, Koreans said 'too many hand skill' (60%) most while 'too many spices' (8%) least. For Japanese, 'various kind of the recipe' (55%) was most while 'too many hand skill' (7%) was least. There were significant differences shown by academic background (p<0.01) and income(p<0.01), and the lower the academic background, the more said 'too many spices' as the reason for the complicity in making traditional food. Generally, the lesser the income, the more tendency to say 'various kinds of the recipe'. 5. In case of Koreans, 'the recipe is difficult' (56%) was high while 'uninterested' (9%) was low in answer which showed differences by academic background (p<0.05), and in case of Japanese, 'no time to cook' (44%) was high while 'uninterested' (7%) was low. 6. The following is the reasons for choosing traditional food as a snack for children. In case of Koreans, they answered as 'traditional food' (34%), 'made from nutrious and quality materials' (27%), 'for education' (22%) and 'suites their taste' (17%) revealing 'traditional food' is highest. In case of Japanese, it was revealed in the order of 'made from nutrious and quality materials' (36.3%), 'traditional food' (25.2%), 'suites their taste' (22.6%), 'for education' (12.8%) and 7. Comparing the most important thing for the popularization of traditional food in the world, Koreans answered 'taste and nutrition' (45%) most while 'shape and color' (6%) least. In case of Japanese, 'taste and nutrition' (75%) was answered most while 'hygienic packaging' (4%) was least. Both considered 'taste and nutrition' as most important thing for the popularization of traditional food in the world. 8. In case of Koreans, they answered they learn how to make traditional food 'from mother' (47%), 'media' (18%), 'school' (15%), 'from mother-in-law' (14%), 'private cooking school' (4%) and 'close acquaintances' (2%). In case of Japanese, they said mostly learn 'from mother', but it was also shown that the lower the academic background the lesser the tendency of learning 'from mother' but 'from school' (p<0.001). 9. About the consumption of traditional fermented food, Koreans said they make kimchi (90%), pickled vegetables (39%), soy sauce (33%), bean paste (38%), salted fishery (12%) and traditional liquors (14%) at home while 67% for salted fishery and 48% for traditional liquors answered they buy rather than making at home. On the other hand, Japanese answered they mostly buy kimchi (60%), soy sauce (96%), bean paste(91%), natto(92%), salt fermented fish foods (77%) and traditional alcoholic beverage (88%) to eat. This difference was shown very distinct between Korean and Japanese women (p<0.001). 10. About the most important thing in food, Koreans answered in the order of 'liking and satisfaction' (33%), 'for health' (32%), 'for relieve hunger' (18%) and 'convenience' (17%). In case of Japanese, it was revealed in the order of 'for health' (61%), 'liking and satisfaction' (20%), 'to relieve hunger' (16%) and 'convenience' (3%). This shows that Japanese women take comparably more importance to health than Korean women. The conception of food was shown different between Korean and Japanese women (p<0.001), and Koreans showed level 4-5 of food culture while Japanese showed level 5.

• Journal of Korean Home Economics Education Association
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• v.20 no.1
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• pp.137-152
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• 2008

This study examined the organization and operation of home economics curriculum of specialized middle school in the form of regular school among alternative schools and analyzed the perceptions of teachers and students about home economics class. Interviews were conducted with teachers of 6 specialized schools in order to determine the operations and teachers' perceptions of home economics education. Students' perceptions for home economics class were gathered through surveys with students from the 3 (of the original 6) schools that authorized the questionnaire survey. The final analysis utilized 205 student responses. Survey data were analyzed using the SPSS program. The results of the research were as follows: First, home economics education within specialized middle schools was mostly conducted according to the form of the technology-home economics curriculum, which is the national common basic curriculum. Compared to the 7th national curriculum, the class of technology-home economics curriculum in 4 schools occurred 1 hour less each week. Each school incorporated various specialized curricula related to home economics. Second, as for the operation of home economics education in specialized schools, most home economics classes were conducted by teachers who had majored (or minored) in home economics. Moreover, all but 1 school, which used self-made materials, used the national textbook and dealt with the entire content of the textbook. For teaching-learning methods and instructional media, various means were utilized. For evaluation methods, most schools based grades on paper-and-pencil tests(50-60%) and performance tests(40-50%). Third, among teachers' perceptions of home economics education, the meaning of home economics education was focused on practical help and the pursuit of home happiness; the purpose was to realize the happiness of students and their homes by applying these to actual living, and increase students' ability to see the world. In regards to difficulties in educational operations, most pointed out poor conditions of practice rooms. As for differences from general schools, most teachers mentioned the active communication with students. Fourth, through the home economics class, it was found that students perceived the goal of technology-home economics curricula as lower than average. Among students' perceptions about home economics class, most were negative. Perceptions about goal of technology-home economics curricula and home economics class also showed meaningful differences according to each school. Students of the school, which had more home economics class hours and specialized curricula related to home economics, perceived more positively. Also, students who were more satisfied with school and learned from a teacher who majored in home economics tended to perceive home economics class more positively.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.77-92
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• 2014

Recently, numerous documents including unstructured data and text have been created due to the rapid increase in the usage of social media and the Internet. Each document is usually provided with a specific category for the convenience of the users. In the past, the categorization was performed manually. However, in the case of manual categorization, not only can the accuracy of the categorization be not guaranteed but the categorization also requires a large amount of time and huge costs. Many studies have been conducted towards the automatic creation of categories to solve the limitations of manual categorization. Unfortunately, most of these methods cannot be applied to categorizing complex documents with multiple topics because the methods work by assuming that one document can be categorized into one category only. In order to overcome this limitation, some studies have attempted to categorize each document into multiple categories. However, they are also limited in that their learning process involves training using a multi-categorized document set. These methods therefore cannot be applied to multi-categorization of most documents unless multi-categorized training sets are provided. To overcome the limitation of the requirement of a multi-categorized training set by traditional multi-categorization algorithms, we propose a new methodology that can extend a category of a single-categorized document to multiple categorizes by analyzing relationships among categories, topics, and documents. First, we attempt to find the relationship between documents and topics by using the result of topic analysis for single-categorized documents. Second, we construct a correspondence table between topics and categories by investigating the relationship between them. Finally, we calculate the matching scores for each document to multiple categories. The results imply that a document can be classified into a certain category if and only if the matching score is higher than the predefined threshold. For example, we can classify a certain document into three categories that have larger matching scores than the predefined threshold. The main contribution of our study is that our methodology can improve the applicability of traditional multi-category classifiers by generating multi-categorized documents from single-categorized documents. Additionally, we propose a module for verifying the accuracy of the proposed methodology. For performance evaluation, we performed intensive experiments with news articles. News articles are clearly categorized based on the theme, whereas the use of vulgar language and slang is smaller than other usual text document. We collected news articles from July 2012 to June 2013. The articles exhibit large variations in terms of the number of types of categories. This is because readers have different levels of interest in each category. Additionally, the result is also attributed to the differences in the frequency of the events in each category. In order to minimize the distortion of the result from the number of articles in different categories, we extracted 3,000 articles equally from each of the eight categories. Therefore, the total number of articles used in our experiments was 24,000. The eight categories were "IT Science," "Economy," "Society," "Life and Culture," "World," "Sports," "Entertainment," and "Politics." By using the news articles that we collected, we calculated the document/category correspondence scores by utilizing topic/category and document/topics correspondence scores. The document/category correspondence score can be said to indicate the degree of correspondence of each document to a certain category. As a result, we could present two additional categories for each of the 23,089 documents. Precision, recall, and F-score were revealed to be 0.605, 0.629, and 0.617 respectively when only the top 1 predicted category was evaluated, whereas they were revealed to be 0.838, 0.290, and 0.431 when the top 1 - 3 predicted categories were considered. It was very interesting to find a large variation between the scores of the eight categories on precision, recall, and F-score.

• Journal of Science Education
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• v.33 no.1
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• pp.111-121
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• 2009

The purpose of this research is to survey elementary pre-service teachers' in understand the legal Units, focusing on seven basic unit such a 'm', 'm2', 'L', 'kg', 'K', 'cd', 's'. This study specifically investigates whether the students understand the legal units. The subjects were 1096 students from the University of Education in Jinju, Gyeongnam. Data was collected through a questionnaire which was designed by this research and checked by authority, and the frequency and percentage of responses to each question were obtained and analysed. The survey was the legal units on interesting, using the experience of confusing and understanding of elementary pre-service teachers. The Korea Government is regulating using traditional measures such as 'pyeong' or 'don' in commercial transactions change to adopt the metric system for as a subsidiary the first of July, 2007. The interesting of the legal units dose not exceed a positive answer to the question 52.1%. Their were answered that the experience of the confused of 60.1% in the life. How to do efforts for the settle down of the legal units that answered broadcasting>in class>a campaign>study and training by an academic year in oder. Findings show regardless of academic year, gender and from the department of liberal arts or the science department all the students knew very well that 'm' '$m^2$', 'L', 'kg' are included in the legal units, compared to the others low percentage of 'K', 'cd' and 's' the legal units. In case of time(s), women has correct answered 2.7 times than man. In case of academic year, except for the third-year students was not to exceed 50%. In case of from the department of liberal arts or the science department contrary to one's expectations increase of 50% or more correct answer while half the students scored in science. The elementary pre-service teachers are seems to thinking separate the legal units with their in university life. Also elementary pre-service teachers are the lack of interest on society. Their should be for settle down of the legal units through learning to class in university, newspapers, strengthen publicity activities of broadcast media's further more by maintenance efforts of the government.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.119-142
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• 2015

With the explosive growth in the volume of information, Internet users are experiencing considerable difficulties in obtaining necessary information online. Against this backdrop, ever-greater importance is being placed on a recommender system that provides information catered to user preferences and tastes in an attempt to address issues associated with information overload. To this end, a number of techniques have been proposed, including content-based filtering (CBF), demographic filtering (DF) and collaborative filtering (CF). Among them, CBF and DF require external information and thus cannot be applied to a variety of domains. CF, on the other hand, is widely used since it is relatively free from the domain constraint. The CF technique is broadly classified into memory-based CF, model-based CF and hybrid CF. Model-based CF addresses the drawbacks of CF by considering the Bayesian model, clustering model or dependency network model. This filtering technique not only improves the sparsity and scalability issues but also boosts predictive performance. However, it involves expensive model-building and results in a tradeoff between performance and scalability. Such tradeoff is attributed to reduced coverage, which is a type of sparsity issues. In addition, expensive model-building may lead to performance instability since changes in the domain environment cannot be immediately incorporated into the model due to high costs involved. Cumulative changes in the domain environment that have failed to be reflected eventually undermine system performance. This study incorporates the Markov model of transition probabilities and the concept of fuzzy clustering with CBCF to propose predictive clustering-based CF (PCCF) that solves the issues of reduced coverage and of unstable performance. The method improves performance instability by tracking the changes in user preferences and bridging the gap between the static model and dynamic users. Furthermore, the issue of reduced coverage also improves by expanding the coverage based on transition probabilities and clustering probabilities. The proposed method consists of four processes. First, user preferences are normalized in preference clustering. Second, changes in user preferences are detected from review score entries during preference transition detection. Third, user propensities are normalized using patterns of changes (propensities) in user preferences in propensity clustering. Lastly, the preference prediction model is developed to predict user preferences for items during preference prediction. The proposed method has been validated by testing the robustness of performance instability and scalability-performance tradeoff. The initial test compared and analyzed the performance of individual recommender systems each enabled by IBCF, CBCF, ICFEC and PCCF under an environment where data sparsity had been minimized. The following test adjusted the optimal number of clusters in CBCF, ICFEC and PCCF for a comparative analysis of subsequent changes in the system performance. The test results revealed that the suggested method produced insignificant improvement in performance in comparison with the existing techniques. In addition, it failed to achieve significant improvement in the standard deviation that indicates the degree of data fluctuation. Notwithstanding, it resulted in marked improvement over the existing techniques in terms of range that indicates the level of performance fluctuation. The level of performance fluctuation before and after the model generation improved by 51.31% in the initial test. Then in the following test, there has been 36.05% improvement in the level of performance fluctuation driven by the changes in the number of clusters. This signifies that the proposed method, despite the slight performance improvement, clearly offers better performance stability compared to the existing techniques. Further research on this study will be directed toward enhancing the recommendation performance that failed to demonstrate significant improvement over the existing techniques. The future research will consider the introduction of a high-dimensional parameter-free clustering algorithm or deep learning-based model in order to improve performance in recommendations.

• Journal of Nutrition and Health
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• v.55 no.1
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• pp.21-35
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• 2022

The recommended meal composition allows the general people to organize meals using the number of intakes of foods from each of six food groups (grains, meat·fish·eggs·beans, vegetables, fruits, milk·dairy products and oils·sugars) to meet Dietary Reference Intakes for Koreans (KDRIs) without calculating complex nutritional values. Through an integrated analysis of data from the 6th to 7th Korean National Health and Nutrition Examination Surveys (2013-2018), representative foods for each food group were selected, and the amounts of representative foods per person were derived based on energy. Based on the EER by age and gender from the KDRIs, a total of 12 kinds of diets were suggested by differentiating meal compositions by age (aged 1-2, 3-5, 6-11, 12-18, 19-64, 65-74 and ≥ 75 years) and gender. The 2020 Food Balance Wheel included the 6th food group of oils and sugars to raise public awareness and avoid confusion in the practical utilization of the model by industries or individuals in reducing the consistent increasing intakes of oils and sugars. To promote the everyday use of the Food Balance Wheel and recommended meal compositions among the general public, the poster of the Food Balance Wheel was created in five languages (Korean, English, Japanese, Vietnamese and Chinese) along with card news. A survey was conducted to provide a basis for categorizing nutritional problems by life cycles and developing customized web-based messages to the public. Based on survey results two types of card news were produced for the general public and youth. Additionally, the educational program was developed through a series of processes, such as prioritization of educational topics, setting educational goals for each stage, creation of a detailed educational system chart and teaching-learning plans for the development of educational materials and media.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.183-203
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• 2018

News articles are the most suitable medium for examining the events occurring at home and abroad. Especially, as the development of information and communication technology has brought various kinds of online news media, the news about the events occurring in society has increased greatly. So automatically summarizing key events from massive amounts of news data will help users to look at many of the events at a glance. In addition, if we build and provide an event network based on the relevance of events, it will be able to greatly help the reader in understanding the current events. In this study, we propose a method for extracting event networks from large news text data. To this end, we first collected Korean political and social articles from March 2016 to March 2017, and integrated the synonyms by leaving only meaningful words through preprocessing using NPMI and Word2Vec. Latent Dirichlet allocation (LDA) topic modeling was used to calculate the subject distribution by date and to find the peak of the subject distribution and to detect the event. A total of 32 topics were extracted from the topic modeling, and the point of occurrence of the event was deduced by looking at the point at which each subject distribution surged. As a result, a total of 85 events were detected, but the final 16 events were filtered and presented using the Gaussian smoothing technique. We also calculated the relevance score between events detected to construct the event network. Using the cosine coefficient between the co-occurred events, we calculated the relevance between the events and connected the events to construct the event network. Finally, we set up the event network by setting each event to each vertex and the relevance score between events to the vertices connecting the vertices. The event network constructed in our methods helped us to sort out major events in the political and social fields in Korea that occurred in the last one year in chronological order and at the same time identify which events are related to certain events. Our approach differs from existing event detection methods in that LDA topic modeling makes it possible to easily analyze large amounts of data and to identify the relevance of events that were difficult to detect in existing event detection. We applied various text mining techniques and Word2vec technique in the text preprocessing to improve the accuracy of the extraction of proper nouns and synthetic nouns, which have been difficult in analyzing existing Korean texts, can be found. In this study, the detection and network configuration techniques of the event have the following advantages in practical application. First, LDA topic modeling, which is unsupervised learning, can easily analyze subject and topic words and distribution from huge amount of data. Also, by using the date information of the collected news articles, it is possible to express the distribution by topic in a time series. Second, we can find out the connection of events in the form of present and summarized form by calculating relevance score and constructing event network by using simultaneous occurrence of topics that are difficult to grasp in existing event detection. It can be seen from the fact that the inter-event relevance-based event network proposed in this study was actually constructed in order of occurrence time. It is also possible to identify what happened as a starting point for a series of events through the event network. The limitation of this study is that the characteristics of LDA topic modeling have different results according to the initial parameters and the number of subjects, and the subject and event name of the analysis result should be given by the subjective judgment of the researcher. Also, since each topic is assumed to be exclusive and independent, it does not take into account the relevance between themes. Subsequent studies need to calculate the relevance between events that are not covered in this study or those that belong to the same subject.

• Journal of Distribution Research
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• v.15 no.4
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• pp.61-85
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• 2010

Introduction: Diffusion is process by which an innovation is communicated through certain channel overtime among the members of a social system(Rogers 1983). Bass(1969) suggested the Bass model describing diffusion process. The Bass model assumes potential adopters of innovation are influenced by mass-media and word-of-mouth from communication with previous adopters. Various expansions of the Bass model have been conducted. Some of them proposed a third factor affecting diffusion. Others proposed multinational diffusion model and it stressed interactive effect on diffusion among several countries. We add a spatial factor in the Bass model as a third communication factor. Because of situation where we can not control the interaction between markets, we need to consider that diffusion within certain market can be influenced by diffusion in contiguous market. The process that certain type of retail extends is a result that particular market can be described by the retail life cycle. Diffusion of retail has pattern following three phases of spatial diffusion: adoption of innovation happens in near the diffusion center first, spreads to the vicinity of the diffusing center and then adoption of innovation is completed in peripheral areas in saturation stage. So we expect spatial effect to be important to describe diffusion of domestic discount store. We define a spatial diffusion model using multinational diffusion model and apply it to the diffusion of discount store. Modeling: In this paper, we define a spatial diffusion model and apply it to the diffusion of discount store. To define a spatial diffusion model, we expand learning model(Kumar and Krishnan 2002) and separate diffusion process in diffusion center(market A) from diffusion process in the vicinity of the diffusing center(market B). The proposed spatial diffusion model is shown in equation (1a) and (1b). Equation (1a) is the diffusion process in diffusion center and equation (1b) is one in the vicinity of the diffusing center. $$\array{{S_{i,t}=(p_i+q_i{\frac{Y_{i,t-1}}{m_i}})(m_i-Y_{i,t-1})\;i{\in}\{1,{\cdots},I\}\;(1a)}\\{S_{j,t}=(p_j+q_j{\frac{Y_{j,t-1}}{m_i}}+{\sum\limits_{i=1}^I}{\gamma}_{ij}{\frac{Y_{i,t-1}}{m_i}})(m_j-Y_{j,t-1})\;i{\in}\{1,{\cdots},I\},\;j{\in}\{I+1,{\cdots},I+J\}\;(1b)}}$$ We rise two research questions. (1) The proposed spatial diffusion model is more effective than the Bass model to describe the diffusion of discount stores. (2) The more similar retail environment of diffusing center with that of the vicinity of the contiguous market is, the larger spatial effect of diffusing center on diffusion of the vicinity of the contiguous market is. To examine above two questions, we adopt the Bass model to estimate diffusion of discount store first. Next spatial diffusion model where spatial factor is added to the Bass model is used to estimate it. Finally by comparing Bass model with spatial diffusion model, we try to find out which model describes diffusion of discount store better. In addition, we investigate the relationship between similarity of retail environment(conceptual distance) and spatial factor impact with correlation analysis. Result and Implication: We suggest spatial diffusion model to describe diffusion of discount stores. To examine the proposed spatial diffusion model, 347 domestic discount stores are used and we divide nation into 5 districts, Seoul-Gyeongin(SG), Busan-Gyeongnam(BG), Daegu-Gyeongbuk(DG), Gwan- gju-Jeonla(GJ), Daejeon-Chungcheong(DC), and the result is shown