• Communications of Mathematical Education
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• v.38 no.2
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• pp.93-120
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• 2024

On-line education in mathematics education changed in various aspects before and after COVID-19. This study conducted a systematic literature review of 98 academic papers on on-line education published from 2017 to 2023 in the field of mathematics education before and after COVID19. In particular, this study conducted content analysis to organize on the definitions of various similar terms related to online education. In addition, this study explored research trends on year, research subject, research method, on-line education type, and research topic by the pre-COVID-19, COVID-19, and post-COVID-19 era. Also, a comparative analysis was conducted on literatures on the effects of online education. As a result, first, it was confirmed that there is a need to organize the definitions of terms similar to online education. Also, the implications of identifying the differences and hierarchies between each term can be found. Second, it was confirmed that teachers' expertise for on-line mathematics education was emphasized based on the result of the rapid increase in the number of on-line education studies on teachers since COVID-19. Third, it was confirmed that the number of studies on blended and flipped learning was high in pre-COVID-19, but decreased in the COVID-19 era. Instead, in the COVID-19 era, studies on real-time interactive classes were rapidly active, and even in the post-COVID-19 era, studies on real-time interactive classes still occupied a large proportion. Finally, it was confirmed that the effectiveness of on-line education varies depending on the research background and model. Accordingly, the need to be cautious in interpreting the results of each study on the effectiveness of on-line education was confirmed. Based on these findings, this study presented implications for future research on on-line education in mathematics education.

• Journal of Korea Water Resources Association
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• v.49 no.6
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• pp.551-563
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• 2016

According to the 4th and 5th assessment of the Intergovernmental Panel on Climate Change (IPCC), global climate has been rapidly changing because of the human activities since Industrial Revolution. The perceived changes were appeared strongly in temperature and concentration of carbon dioxide ($CO_2$). Global average temperature has increased about $0.74^{\circ}C$ over last 100 years (IPCC, 2007) and concentration of $CO_2$ is unprecedented in at least the last 800,000 years (IPCC, 2014). These phenomena influence precipitation, evapotranspiration and soil moisture which have an important role in hydrology, and that is the reason why there is a necessity to study climate change. In this study, Asia region was selected to simulate primary energy index from 1951 to 2100. To predict future climate change effect, Common Land Model (CLM) which is used for various fields across the world was employed. The forcing data was Representative Concentration Pathway (RCP) data which is the newest greenhouse gas emission scenario published in IPCC 5th assessment. Validation of net radiation ($R_n$), sensible heat flux (H), latent heat flux (LE) for historical period was performed with 5 flux tower site-data in the region of AsiaFlux and the monthly trends of simulation results were almost equaled to observation data. The simulation results for 2006-2100 showed almost stable net radiation, slightly decreasing sensible heat flux and quite increasing latent heat flux. Especially the uptrend for RCP 8.5 has been about doubled compared to RCP 4.5 and since late 2060s, variations of net radiation and sensible heat flux would be significantly risen becoming an extreme climate condition. In a follow-up study, a simulation for energy index and hydrological index under the detailed condition will be conducted with various scenario established from this study.

• Korean Journal of Environment and Ecology
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• v.34 no.5
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• pp.358-371
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• 2020

As climate change is expected to lead to a severe reduction of biodiversity, studies to investigate the reasons for habitat loss, growth decline, and death of Korean fir (Abies koreana Wilson), endangered alpine/subalpine species in Korea, have been conducted for years but found no clear answer yet. This study reviewed previous studies on Korean fir published in the journals in the past 40 years, 1980 through 2020, into 10-year units, examined the study trend by period, region, and subject with a focus on ecological studies, and analyzed the study results. The ecological studies were categorized into evolutionary ecology, physiological ecology, population ecology, and landscape ecology. Based on the results, we suggested the required research fields in the future. We found a total of 73 papers published in the past 40 years and 48 (65.8%) of them published in the past 10 years. In terms of region, Mt. Halla accounted for the most as 41 papers were on it. In terms of ecological subjects, the physiological ecology accounted for the most with 38, and the evolutionary ecology accounted for the least with 10. The review of the study results showed that many studies identified water stress caused by the water resource imbalance due to temperature increase and spring precipitation reduction following climate change as the main reason for the decline and habitat loss of Korean fir. However, recent studies suggested other factors, such as soil environment, disturbing organisms, and climatic events. The cause of the decline and death of the Korean fir not yet being clearly identified is that most of the studies dealt with the basic content, were carried out intermittently, and were concentrated in some regions. Therefore, we need long-term studies with advanced technology in each study subject at a local scale to find the cause of Korean fir decline and present sustainable management and conservation. Moreover, it is necessary to extend our study subjects to ecosystem ecology and systems ecology to integrate the results from various study subjects for a comprehensive understanding of the reason for Korean fir declines. The results of comprehensive studies could provide clearer answers for Korean fir's declines and the alternatives of conservation management and practices.

• Journal of Environmental Policy
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• v.14 no.2
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• pp.149-170
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• 2015

The purpose of this paper is to figure out the research direction and information regarding Mt. Baekdu in Korea through analyses of the research field and trends. Firstly, we made inventory of journal papers, conference proceedings, and research reports published related to Mt. Baekdu. A total of 255 data, spanning the 34 years from the 1980s to the middle of 2014, were acquired and classified into categories according to the year, field, contents and study area. Results show that research on Mt. Baekdu has been performed more than twice since 2010 and study regarding prediction has been carried out in 54.7% cases. In addition, the importance of geo-spatial information is expected to increase in order to study Mt. Baekdu. Secondly, we made and analyzed a geospatial information using inventory of 234 detailed research contents in research reports by Korea Meteorological Administration (KMA) and National Institute of Meteorological Research (NIMR). Statistics on categories show that research regarding prediction accounted for 81.6% of cases and the study of geo-spatial information utilization accounted for 54.7% of cases. However, the focus on studying the Mt. Baekdu region accounted for only 20.1% of cases. Thus, this indicates that it is necessary to do research at Mt. Bakdu itself. If the directly available geo-spatial information system is developed related to Mt. Baekdu, it will save research costs and analysis time. This study can be used to manage information about the research field of Mt. Baekdu by analysing inventory of research references and geospatial information using inventories when the Mt. Baekdu area is the focus of future research.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.207-228
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• 2007

Measuring Information Technology(IT) organizations' activities have been limited to mainly measure financial indicators for a long time. However, according to the multifarious functions of Information System, a number of researches have been done for the new trends on measurement methodologies that come with financial measurement as well as new measurement methods. Especially, the researches on IT Balanced Scorecard(BSC), concept from BSC measuring IT activities have been done as well in recent years. BSC provides more advantages than only integration of non-financial measures in a performance measurement system. The core of BSC rests on the cause-and-effect relationships between measures to allow prediction of value chain performance measures to allow prediction of value chain performance measures, communication, and realization of the corporate strategy and incentive controlled actions. More recently, BSC proponents have focused on the need to tie measures together into a causal chain of performance, and to test the validity of these hypothesized effects to guide the development of strategy. Kaplan and Norton[2001] argue that one of the primary benefits of the balanced scorecard is its use in gauging the success of strategy. Norreklit[2000] insist that the cause-and-effect chain is central to the balanced scorecard. The cause-and-effect chain is also central to the IT BSC. However, prior researches on relationship between information system and enterprise strategies as well as connection between various IT performance measurement indicators are not so much studied. Ittner et al.[2003] report that 77% of all surveyed companies with an implemented BSC place no or only little interest on soundly modeled cause-and-effect relationships despite of the importance of cause-and-effect chains as an integral part of BSC. This shortcoming can be explained with one theoretical and one practical reason[Blumenberg and Hinz, 2006]. From a theoretical point of view, causalities within the BSC method and their application are only vaguely described by Kaplan and Norton. From a practical consideration, modeling corporate causalities is a complex task due to tedious data acquisition and following reliability maintenance. However, cause-and effect relationships are an essential part of BSCs because they differentiate performance measurement systems like BSCs from simple key performance indicator(KPI) lists. KPI lists present an ad-hoc collection of measures to managers but do not allow for a comprehensive view on corporate performance. Instead, performance measurement system like BSCs tries to model the relationships of the underlying value chain in cause-and-effect relationships. Therefore, to overcome the deficiencies of causal modeling in IT BSC, sound and robust causal modeling approaches are required in theory as well as in practice for offering a solution. The propose of this study is to suggest critical success factors(CSFs) and KPIs for measuring performance for IT organizations and empirically validate the casual relationships between those CSFs. For this purpose, we define four perspectives of BSC for IT organizations according to Van Grembergen's study[2000] as follows. The Future Orientation perspective represents the human and technology resources needed by IT to deliver its services. The Operational Excellence perspective represents the IT processes employed to develop and deliver the applications. The User Orientation perspective represents the user evaluation of IT. The Business Contribution perspective captures the business value of the IT investments. Each of these perspectives has to be translated into corresponding metrics and measures that assess the current situations. This study suggests 12 CSFs for IT BSC based on the previous IT BSC's studies and COBIT 4.1. These CSFs consist of 51 KPIs. We defines the cause-and-effect relationships among BSC CSFs for IT Organizations as follows. The Future Orientation perspective will have positive effects on the Operational Excellence perspective. Then the Operational Excellence perspective will have positive effects on the User Orientation perspective. Finally, the User Orientation perspective will have positive effects on the Business Contribution perspective. This research tests the validity of these hypothesized casual effects and the sub-hypothesized causal relationships. For the purpose, we used the Partial Least Squares approach to Structural Equation Modeling(or PLS Path Modeling) for analyzing multiple IT BSC CSFs. The PLS path modeling has special abilities that make it more appropriate than other techniques, such as multiple regression and LISREL, when analyzing small sample sizes. Recently the use of PLS path modeling has been gaining interests and use among IS researchers in recent years because of its ability to model latent constructs under conditions of nonormality and with small to medium sample sizes(Chin et al., 2003). The empirical results of our study using PLS path modeling show that the casual effects in IT BSC significantly exist partially in our hypotheses.

• Korean Journal of Remote Sensing
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• v.36 no.2_1
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• pp.121-137
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• 2020

Data from the Ozone Monitoring Instrument (OMI) satellite and national emission inventories were used in this study to analyze air quality in East Asia and estimate the impact of domestic and foreign emissions on South Korea's air quality, based on which future emissions were predicted. The concentration trends of nitrogen dioxide (NO₂) and sulfur dioxide (SO₂) in East Asia from 2005 to 2015 showed that both substances were highest in North East China (NEC), followed by South East China (SEC) and Seoul Metropolitan Area (SMA). The average SO₂ concentration was 1.63 times higher in NEC than in SMA. Analysis on the ratios of NO₂/SO₂ and NO_x/SO_x provides an indirect picture of the effect of transboundary air pollutants on atmospheric composition in Korea. The concentration ratio of NO₂/SO₂ in all study areas peaked in 2013 and SMA's emission ratio of NO_x/SO_x increased in 2015 by over 22% from 2013. Despite the reduction in domestic emissions, the concentration-to-emission ratios (NO₂/NO_x, SO₂/SO_x) rose gradually, which implies that other factors besides domestic emissions (e.g., foreign sources, lifetime, etc.) influence air quality in SMA. We estimated future emissions of NO_x and SO_x in SMA to be 296.2 and 39.0 ktons in 2025 and 284.4 and 33.8 ktons in 2035, respectively. Application of the inter-comparison techniques of this study to the data from the Geostationary Environment Monitoring Instrument (GEMS) is expected to provide concrete information which can be used to improve national emission inventories and figure out factors and sources that affect domestic air quality.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.554-564
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• 2017

The purpose of this study is to assist farmers in determining the optimal time for the shipment of stored apples by investigating the market trends, storage status and release dates of low-temperature stored apples. We surveyed 300 apple cultivation farms in Daegu, Gyeongbuk Province, which is the main producer of apples, and examined the cultivars, cultivation areas, storage conditions, and shipment status of apples. The main results are as follows: the proportion of apples cultivatedat different ripening times was surveyed. According to the results, the proportions of early, middle and late varieties were 78.3%, 63.7% and 96.0%, respectively. Also, 48.7% of the farm households surveyed had cold storage facilities. The average storage cost per apple box(15kg) was 978.3 won for self-storage and 1,771.8 won for consignment storage. For the six(6) months between November and April, the proportion of shipped apples was 91.6% of the total stored apples. The (average total?)annual apple shipment, including apples stored in general storage warehouses, was 744.4 boxes. The (average total?) annual shipment of cold storage apples was 616 boxes. The stored apples were mainly shipped to 'wholesale markets', which have the highest sales share, followed by 'production site collectors' and then 'supermarkets'. The most common shipping method of the apples was by general trucks, followed by low-temperature trucks, and finally by delivery services. The analysis of the factors influencing the decision to release apples by period showed that it was affected by the storage cost, loss rate, and customary shipping in the off-season(from May to August). On the other hand, in the general release season(from November to April), the statistically significant decision factors for the release of apples were the future expected price, storage cost and decision of the leading farmer groups. For farmers with a high share of general shipment, the deciding factors for the release of apples were the future expected price, storage cost, high income expectation, and decision by leading farmers.

• Journal of Distribution Science
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• v.10 no.2
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• pp.53-62
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• 2012

Well-being is a reflection of current sociocultural trends that focus on the quality of life based on economic growth. Furthermore, organic food is believed to help people maintain good health and therefore leads to increased consumption of organic foods. Therefore, consumer interest in organic food is increasing, causing its market to grow, and this trend will be maintained in the future. The abuse of agricultural pesticides, gene manipulation, and bovine spongiform encephalopathy has caused consumers to worry about food safety. The well-being trend has also contributed to consumers' growing interest inorganic food and organic agricultural products. A consumer's choice offood is a complex processes affected by various factors. In particular, organic food is considered an individualistic merit good, considering the consumers' preferences related to certification policies. Therefore, various factors such as personal characteristics and sense of value could affect consumers' decisions. This research focused on an analysis of the factors influencing consumers' purchasing intention for organic food on the basis of an increase in organic food consumption. The research method was based on the theory of planned behavior (TPB). Factors such as consumer characteristics regarding food consumption, purchasing frequency, and other factors affecting purchasing intention were presented. The hypothesis was set using advanced research and stated that it is easier to forecast purchasing intentions by combining the theory of planned behavior and personal characteristics of consumer. The results show that two dimensions, attitude and perceived behavioral control, have statistically significant influence on the purchasing intention. It can be said that a positive attitude toward organic foods in particular increases the possibility of purchasing intention. In addition, consumers who consume more organic food products are more likely to have positive attitudes, and, in the past, purchasing frequency has positively influenced purchasing intention of organic foods. Consumers' negative feelings about the non-purchase of organic foods also showed a negative influence on purchasing intentions. In other words, even though consumers feel uncomfortable when not consuming organic food products, they do not try to purchase such products because of this feeling of discomfort. Furthermore, the subjective norm and the behavioral control of food-related involvement do not have a statistically significant influence on the purchasing intention or attitudes. This research verified the influence of factors related to purchasing intention. This study has several limitations: (1) even though consumers' responses can change based on the type of food, the types of food were not classified in this study; (2) future studies are necessary to analyze the attitudes of consumers on the basis of their purchasing experiences with organic foods.

• The Mathematical Education
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• v.30 no.1
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• pp.1-19
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• 1991

This study intends to provide some desirable suggestions for the development of application oriented mathematics curriculum. More specific objects of this study is: 1. To identify the meaning of application and modelling in mathematics curriculm. 2. To illuminate the historical background of and trends in application and modelling in the mathematics curricula. 3. To consider the reasons for including application and modelling in the mathematics curriculum. 4. To find out some implication for developing application oriented mathematics curriculum. The meaning of application and modelling is clarified as follows: If an arbitrary area of extra-mathematical reality is submitted to any kind of treatment which invovles mathematical concepts, methods, results, topics, we shall speak of the process of applying mathemtaics to that area. For the result of the process we shall use the term an application of mathematics. Certain objects, relations between them, and structures belonging to the area under consideration are selected and translated into mathemtaical objects, relation and structures, which are said to represent the original ones. Now, the concept of mathematical model is defined as the collection of mathematical objcets, . relations, structures, and so on, irrespective of what area is being represented by the model and how. And the full process of constructing a mathematical model of a given area is called as modelling, or model-building. During the last few decades an enormous extension of the use of mathemtaics in other disciplines has occurred. Nowadays the concept of a mathematical model is often used and interest has turned to the dynamic interaction between the real world and mathematics, to the process translating a real situation into a mathematical model and vice versa. The continued growing importance of mathematics in everyday practice has not been reflected to the same extent in the teaching and learning of mathematics in school. In particular the world-wide 'New Maths Movement' of the 19608 actually caused a reduction of the importance of application and modelling in mathematics teaching. Eventually, in the 1970s, there was a reaction to the excessive formallism of 'New Maths', and a return in many countries to the importance of application and connections to the reality in mathematics teaching. However, the main emphasis was put on mathematical models. Applicaton and modelling should be part of the mathematics curriculum in order to: 1. Convince students, who lacks visible relevance to their present and future lives, that mathematical activities are worthwhile, and motivate their studies. 2. Assist the acqusition and understanding of mathematical ideas, concepts, methods, theories and provide illustrations and interpretations of them. 3. Prepare students for being able to practice application and modelling as private individuals or as citizens, at present or in the future. 4. Foster in students the ability to utilise mathematics in complex situations. Of these four reasons the first is rather defensive, serving to protect or strengthen the position of mathematics, whereas the last three imply a positive interest in application and modelling for their own sake or for their capacity to improve mathematics teaching. Suggestions, recomendations and implications for developing application oriented mathematics curriculum were made as follows: 1. Many applications and modelling case studies suitable for various levels should be investigated and published for the teacher. 2. Mathematics education both for general and vocational students should encompass application and modelling activities, of a constructive as well as analytical and critical nature. 3. Application and modelling activities should. be introduced in mathematics curriculum through the interdisciplinary integrated approach. 4. What are the central ideas of, and what are less-important topics of application-oriented curriculum should be studied and selected. 5. For any mathematics teacher, application and modelling should form part of pre- and in-service education.