• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.309-323
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• 2023

As the role of online reviews has become increasingly crucial, numerous studies have been conducted to utilize helpful reviews. Helpful reviews, perceived by customers, have been verified in various research studies to be influenced by factors such as ratings, review length, review content, and so on. The determination of a review's helpfulness is generally based on the number of 'helpful' votes from consumers, with more 'helpful' votes considered to have a more significant impact on consumers' purchasing decisions. However, recently written reviews that have not been exposed to many customers may have relatively few 'helpful' votes and may lack 'helpful' votes altogether due to a lack of participation. Therefore, rather than relying on the number of 'helpful' votes to assess the helpfulness of reviews, we aim to classify them based on review content. In addition, the text of the review emerges as the most influential factor in review helpfulness. This study employs text mining techniques, including topic modeling and sentiment analysis, to analyze the diverse impacts of content and emotions embedded in the review text. In this study, we propose a review helpfulness prediction model based on review content, utilizing movie reviews from IMDb, a global movie information site. We construct a review helpfulness prediction model by using an explainable Graph Neural Network (GNN), while addressing the interpretability limitations of the machine learning model. The explainable graph neural network is expected to provide more reliable information about helpful or non-helpful reviews as it can identify connections between reviews.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.273-285
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• 2024

With the active utilization of Online Judge (OJ) systems in the field of education, various studies utilizing learner data have emerged. This research proposes a problem recommendation based on a user-based collaborative filtering approach with learner data to support learners in their problem selection. Assistance in learners' problem selection within the OJ system is crucial for enhancing the effectiveness of education as it impacts the learning path. To achieve this, this system identifies learners with similar problem-solving tendencies and utilizes their problem-solving history. The proposed technique has been implemented on an OJ site in the fields of algorithms and programming, operated by the Chungbuk Education Research and Information Institute. The technique's service utility and usability were assessed through expert reviews using the Delphi technique. Additionally, it was piloted with site users, and an analysis of the ratio of correctness revealed approximately a 16% higher submission rate for recommended problems compared to the overall submissions. A survey targeting users who used the recommended problems yielded a 78% response rate, with the majority indicating that the feature was helpful. However, low selection rates of recommended problems and low response rates within the subset of users who used recommended problems highlight the need for future research focusing on improving accessibility, enhancing user feedback collection, and diversifying learner data analysis.

• The Mathematical Education
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• v.63 no.1
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• pp.19-33
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• 2024

This study investigates longitudinal patterns in middle school students' mathematics interest and achievement using panel data from the 4th to 6th year of the Gyeonggi Education Panel Study. Results from the multivariate growth mixture model confirmed the existence of heterogeneous characteristics in the longitudinal trajectory of students' mathematics interest and achievement. Students were classified into four latent classes: a low-level class with weak interest and achievement, a high-level class with strong interest and achievement, a middlelevel-increasing class where interest and achievement rise with grade, and a middle-level-decreasing class where interest and achievement decline with grade. Each class exhibited distinct patterns in the change of interest and achievement. Moreover, an examination of the correlation between intercepts and slopes in the multivariate growth mixture model reveals a positive association between interest and achievement with respect to their initial values and growth rates. We further explore predictive variables influencing latent class assignment. The results indicated that students' educational ambition and time spent on private education positively affect mathematics interest and achievement, and the influence of prior learning varies based on its intensity. The perceived instruction method significantly impacts latent class assignment: teacher-centered instruction increases the likelihood of belonging to higher-level classes, while learner-centered instruction increases the likelihood of belonging to lower-level classes. This study has significant implications as it presents a new method for analyzing the longitudinal patterns of students' characteristics in mathematics education through the application of the multivariate growth mixture model.

• Journal of Science Education
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• v.48 no.2
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• pp.75-90
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• 2024

Contemporary society faces increasingly diverse risks with expanding impacts. In response, the importance of science education has become more prominent. This study aims to analyze the characteristics of existing research on science-related risk education and derives implications for such education. Using detailed bibliometric analysis, we collected citation data from 83 international scholarly journals (SSCI) in the field of education indexed in the Web of Science with the keywords 'Scientific Risk.' Subsequently, using the bibliometrix package in R-Studio, we conducted a bibliometric analysis. The findings are as follows. Firstly, research on risk education covers topics such as risk literacy, the structure of risks addressed in science education, and the application and effectiveness of incorporating risk cases into educational practices. Secondly, a significant portion of research on risks related to science education has been conducted within the framework of socioscientific issues (SSI) education. Thirdly, it was observed that research on risks related to science education primarily focuses on the transmission of scientific knowledge, with many studies examining formal education settings such as curricula and school learning environments. These findings imply several key points. Firstly, to effectively address risks in contemporary society, the scope of risk education should extend beyond topics such as nuclear energy and climate change to encompass broader issues like environmental pollution, AI, and various aspects of daily life. Secondly, there is a need to reexamine and further research topics explored in the context of SSI education within the framework of risk education. Thirdly, it is necessary to analyze not only risk perception but also risk assessment and risk management. Lastly, there is a need for research on implementing risk education practices in informal educational settings, such as science museums and media.

• Journal of Internet Computing and Services
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• v.18 no.1
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• pp.77-88
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• 2017

Recently, with the advent of knowledge based society where information and knowledge make values, patents which are the representative form of intellectual property have become important, and the number of the patents follows growing trends. Thus, it needs to classify the patents depending on the technological topic of the invention appropriately in order to use a vast amount of the patent information effectively. IPC (International Patent Classification) is widely used for this situation. Researches about IPC automatic classification have been studied using data mining and machine learning algorithms to improve current IPC classification task which categorizes patent documents by hand. However, most of the previous researches have focused on applying various existing machine learning methods to the patent documents rather than considering on the characteristics of the data or the structure of patent documents. In this paper, therefore, we propose to use two structural fields, technical field and background, considered as having impacts on the patent classification, where the two field are selected by applying of the characteristics of patent documents and the role of the structural fields. We also construct multi-label classification model to reflect what a patent document could have multiple IPCs. Furthermore, we propose a method to classify patent documents at the IPC subclass level comprised of 630 categories so that we investigate the possibility of applying the IPC multi-label classification model into the real field. The effect of structural fields of patent documents are examined using 564,793 registered patents in Korea, and 87.2% precision is obtained in the case of using title, abstract, claims, technical field and background. From this sequence, we verify that the technical field and background have an important role in improving the precision of IPC multi-label classification in IPC subclass level.

• Journal of the Korean earth science society
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• v.42 no.3
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• pp.311-324
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• 2021

Recently, ten geosites have been considered in Hwaseong for endorsement as national geoparks, including the Jebudo, Gojeongri Dinosaur Egg Fossils, and Ueumdo geosites. The Jebudo geosite in the southern part of the Seoul metropolitan area has great potential for development as a new geoscience educational site because it has geological, geographical (landscape), and ecological significance. In this study, we described the geological characteristics through field surveys in the Jebudo geosite. We evaluated its potential as a geo-education site based on comparative analysis with other geosites in Hwaseong Geopark. In addition, we reviewed the practical effect of field education at geosites on the essential concepts and critical competence-oriented education emphasized in the current 2015 revised science curriculum. The Jebudo Geosite is geologically diverse, with various metamorphic rocks belonging to the Precambrian Seosan Group, such as quartzite, schist, and phyllite. Various geological structures, such as clastic dikes, faults, joints, foliation, and schistosity have also been recorded. Moreover, coastal geological features have been observed, including depositional landforms (gravel and sand beaches, dunes, and mudflats), sedimentary structures (ripples), erosional landforms (sea cliffs, sea caves, and sea stacks), and sea parting. The Jebudo geosite has considerable value as a new geo-education site with geological and geomorphological distinction from the Gojeongri Dinosaur Egg Fossils and Ueumdo geosites. The Jebudo geosite also has opportunities for geo-education and geo-tourism, such as mudflat experiences and infrastructures, such as coastal trails and viewing points. This geosite can help develop diverse geo-education programs that improve key competencies in the science curriculum, such as critical thinking, inquiry, and problem-solving. Furthermore, by conducting optimized geo-education focused on the characteristics of each geosite, the following can be established: (1) the expansion of learning space from school to geopark, (2) the improvement of understanding of specific content elements and linkage between essential concepts, and (3) the extension of the education scope throughout the earth system. There will be positive impacts on communication, participation, and lifelong learning skills through geopark education.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.481-493
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• 2023

In high-density urban areas, the urban heat island effect increases urban temperatures, leading to negative impacts such as worsened air pollution, increased cooling energy consumption, and increased greenhouse gas emissions. In urban environments where it is difficult to secure additional green spaces, rooftop greening is an efficient greenhouse gas reduction strategy. In this study, we not only analyzed the current status of the urban heat island effect but also utilized high-resolution satellite data and spatial information to estimate the available rooftop greening area within the study area. We evaluated the mitigation effect of the urban heat island phenomenon and carbon sequestration capacity through temperature predictions resulting from rooftop greening. To achieve this, we utilized WorldView-2 satellite data to classify land cover in the urban heat island areas of Busan city. We developed a prediction model for temperature changes before and after rooftop greening using machine learning techniques. To assess the degree of urban heat island mitigation due to changes in rooftop greening areas, we constructed a temperature change prediction model with temperature as the dependent variable using the random forest technique. In this process, we built a multiple regression model to derive high-resolution land surface temperatures for training data using Google Earth Engine, combining Landsat-8 and Sentinel-2 satellite data. Additionally, we evaluated carbon sequestration based on rooftop greening areas using a carbon absorption capacity per plant. The results of this study suggest that the developed satellite-based urban heat island assessment and temperature change prediction technology using Random Forest models can be applied to urban heat island-vulnerable areas with potential for expansion.

• Journal of Technology Innovation
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• v.20 no.2
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• pp.75-107
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• 2012

Previous researches on technological innovation have several limitations such as lack of general mechanism for technological innovation(inputs, throughputs and outputs of technological innovation), large company oriented studies, and ignoring importance of technology management capabilities. So, this study suggested a new model using resource-based theory and system theory, and empirically applied that to SMEs. Structural equation model analysis by using 223 SMEs in Daegu region provided a support for most of hypotheses. Research results showed that all of factors on technological innovation were significantly and positively related with each other: inputs(R&D leadership, innovation strategy, R&D investment, R&D human resource management, external network), throughputs(portfolio management, project management, technology commercialization) and output(technological innovation). In case of technological innovation inputs, R&D leadership influenced on innovation strategy positively and significantly. And R&D leadership and innovation strategy had positive and significant effects on R&D investment, R&D human resource management and external network. R&D human resource management and external network exerted positive and significant influences on technological innovation throughputs such as portfolio management and project management. But R&D investment did not significant impacts on technological innovation throughputs. Among technological innovation throughputs, both portfolio management and project management had positive and significant effect on technology commercialization. In addition, technology commercialization acted positively and significantly technological innovation output. This study suggests necessary of efforts to implement innovation strategy and manage R&D human resource effectively based on CEO's innovativeness and entrepreneurship. Also, if SMEs want to develop technology and commercialize it, they have to cooperate with external technology resources and informations. Research results revealed that proper level of R&D investment, internal and external communication, information sharing, and learning and cooperative culture were very important for improvement of technological innovation performance in SMEs. Especially, this research suggested that if SMEs manage technological innovation process effectively based on resource-based and system approaches, then they can overcome their resource limitations and gain high technological innovation performance. Also, useful policy support for technological innovation of central or regional government by this research model is important factor for SMEs' technological innovation performance.

• Asia Marketing Journal
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• v.7 no.3
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• pp.53-76
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• 2005

With rapid technological and market change, new product development (NPD) complexity is a significant issue that organizations continually face in their development projects. There are numerous factors, which cause development projects to become increasingly costly & complex. A product is more likely to be successfully developed and marketed when the complexity inherent in NPD projects is clearly understood and carefully managed. Based upon the previous studies, this study examines the nature and importance of complexity in developing new products and then identifies several issues in managing complexity. Issues considered include: definition of complexity : consequences of complexity; and methods for managing complexity in NPD projects. To achieve high performance in managing complexity in development projects, these issues need to be addressed, for example: A. Complexity inherent in NPD projects is multi-faceted and multidimensional. What factors need to be considered in defining and/or measuring complexity in a development project? For example, is it sufficient if complexity is defined only from a technological perspective, or is it more desirable to consider the entire array of complexity sources which NPD teams with different functions (e.g., marketing, R&D, manufacturing, etc.) face in the development process? Moreover, is it sufficient if complexity is measured only once during a development project, or is it more effective and useful to trace complexity changes over the entire development life cycle? B. Complexity inherent in a project can have negative as well as positive influences on NPD performance. Thus, which complexity impacts are usually considered negative and which are positive? Project complexity also can affect the entire organization. Any complexity could be better assessed in broader and longer perspective. What are some ways in which the long-term impact of complexity on an organization can be assessed and managed? C. Based upon previous studies, several approaches for managing complexity are derived. What are the weaknesses & strengths of each approach? Is there a desirable hierarchy or order among these approaches when more than one approach is used? Are there differences in the outcomes according to industry and product types (incremental or radical)? Answers to these and other questions can help organizations effectively manage the complexity inherent in most development projects. Complexity is worthy of additional attention from researchers and practitioners alike. Large-scale empirical investigations, jointly conducted by researchers and practitioners, will help gain useful insights into understanding and managing complexity. Those organizations that can accurately identify, assess, and manage the complexity inherent in projects are likely to gain important competitive advantages.

• Journal of Christian Education in Korea
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• v.77
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• pp.63-84
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• 2024

Research Objective : The study aimed to investigate the satisfaction with the operation of theological university curricula from the perspective of learners experiencing the theological education curriculum in the field. The goal is to provide a basis for reflective introspection on the current theological education curriculum and for restructuring it to have influential impacts within the church and society. Content and Methodology : A survey was conducted with 80 learners currently enrolled in undergraduate, graduate, master's, and doctoral programs at a theological university to analyze satisfaction with current theological education programs. To interpret the survey results progressively, in-depth interviews were conducted with a randomly selected group of 6 participants. Survey Results : First, the satisfaction with the current theological education programs was found to be 60%, indicating a high level of satisfaction. Second, while 77.5% recognized the need for practical pastoral education, only 45.5% reported that practical pastoral education is currently provided in theological education programs, indicating a lower percentage than the perceived need. Third, 73.7% responded negatively regarding whether the current theological education programs can enhance pastoral competence for future society. Lastly, the areas identified as urgently requiring change for the restructuring of theological education programs were theological education content, methodology, and objectives, in that order. Conclusion and Recommendations : In an era of great transformation, our society is changing rapidly. In the face of this wave of change, the theological education curriculum also requires adaptation to suit the new era. Traditional theological education courses have primarily focused on imparting theory-centered knowledge. However, theological education in the new era necessitates a curriculum that enhances the pastoral capacity of churches and pastors to dynamically navigate through this era of significant transition. To achieve this, it is imperative to restructure the curriculum to one that is more closely related to the pastoral field. This involves offering a variety of constructivist-based, learner-centered teaching and learning methods within a theory-centered curriculum and methodology. Additionally, it entails establishing a practice-oriented theological school that can actively address the evolving pastoral landscape in this era of great transition. Restructuring of the process is essential to meet these goals.