• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.219-239
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• 2019

As the importance of providing customized services to individuals becomes important, researches on personalized recommendation systems are constantly being carried out. Collaborative filtering is one of the most popular systems in academia and industry. However, there exists limitation in a sense that recommendations were mostly based on quantitative information such as users' ratings, which made the accuracy be lowered. To solve these problems, many studies have been actively attempted to improve the performance of the recommendation system by using other information besides the quantitative information. Good examples are the usages of the sentiment analysis on customer review text data. Nevertheless, the existing research has not directly combined the results of the sentiment analysis and quantitative rating scores in the recommendation system. Therefore, this study aims to reflect the sentiments shown in the reviews into the rating scores. In other words, we propose a new algorithm that can directly convert the user 's own review into the empirically quantitative information and reflect it directly to the recommendation system. To do this, we needed to quantify users' reviews, which were originally qualitative information. In this study, sentiment score was calculated through sentiment analysis technique of text mining. The data was targeted for movie review. Based on the data, a domain specific sentiment dictionary is constructed for the movie reviews. Regression analysis was used as a method to construct sentiment dictionary. Each positive / negative dictionary was constructed using Lasso regression, Ridge regression, and ElasticNet methods. Based on this constructed sentiment dictionary, the accuracy was verified through confusion matrix. The accuracy of the Lasso based dictionary was 70%, the accuracy of the Ridge based dictionary was 79%, and that of the ElasticNet (${\alpha}=0.3$) was 83%. Therefore, in this study, the sentiment score of the review is calculated based on the dictionary of the ElasticNet method. It was combined with a rating to create a new rating. In this paper, we show that the collaborative filtering that reflects sentiment scores of user review is superior to the traditional method that only considers the existing rating. In order to show that the proposed algorithm is based on memory-based user collaboration filtering, item-based collaborative filtering and model based matrix factorization SVD, and SVD ++. Based on the above algorithm, the mean absolute error (MAE) and the root mean square error (RMSE) are calculated to evaluate the recommendation system with a score that combines sentiment scores with a system that only considers scores. When the evaluation index was MAE, it was improved by 0.059 for UBCF, 0.0862 for IBCF, 0.1012 for SVD and 0.188 for SVD ++. When the evaluation index is RMSE, UBCF is 0.0431, IBCF is 0.0882, SVD is 0.1103, and SVD ++ is 0.1756. As a result, it can be seen that the prediction performance of the evaluation point reflecting the sentiment score proposed in this paper is superior to that of the conventional evaluation method. In other words, in this paper, it is confirmed that the collaborative filtering that reflects the sentiment score of the user review shows superior accuracy as compared with the conventional type of collaborative filtering that only considers the quantitative score. We then attempted paired t-test validation to ensure that the proposed model was a better approach and concluded that the proposed model is better. In this study, to overcome limitations of previous researches that judge user's sentiment only by quantitative rating score, the review was numerically calculated and a user's opinion was more refined and considered into the recommendation system to improve the accuracy. The findings of this study have managerial implications to recommendation system developers who need to consider both quantitative information and qualitative information it is expect. The way of constructing the combined system in this paper might be directly used by the developers.

• The Journal of Society for e-Business Studies
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• v.21 no.2
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• pp.23-46
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• 2016

With the increasing socio-economic value of an open collaboration over the Internet, it has become significantly important to successfully manage open source software development program. Most of the previous research have focused on various factors that influence the performance of the project, but studies on how the project owners recognized as "leader" affect the outcome of the project are very limited. This research investigates how individual and governance characteristics of an owner influences the performance of project based on impression formation and social capital theory. For a data set, we collect 611 Repositories and the owner's data from the open source development platform Github, and we form knowledge sharing network of an each repository by using social network analysis. We use hierarchical regression analysis, and our results show that a leader, who exposes a lot of one's personal information or who has actively followed and showed interests to communicate with other developers, affects positive impacts on project performance. A leader who has a high centrality in knowledge sharing network also positively affects on project performance. On the other hand, if a leader was highly willing to accept external knowledge or is recognized as an expert in the community with large numbers of followers, the result show negative impacts on project performance. The research may serve as a useful guideline not only for the future open source software projects but also for the effective management of different types of open collaboration.

• Journal of Engineering Education Research
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• v.10 no.2
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• pp.44-61
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• 2007

The present investigation is concerned chiefly with new curriculum development at the Department of Mechanical System & Design Engineering at Hongik University with the aim of enhancing creativity, team working and communication capability which modern engineering education is emphasizing on. 'Mechanical System & Design Engineering' department equipped with new curriculum emphasizing engineering design is new name for mechanical engineering department in Hongik University. To meet radically changing environment and demands of industries toward engineering education, the department has shifted its focus from analog-based and machine-centered hard approach to digital-based and human-centered soft approach. Three new programs of Introduction to Mechanical System & Design Engineering, Creative Engineering Design and Product Design emphasize hands-on experiences through project-based team working. Sketch model and prototype making process is strongly emphasized and cardboard, poly styrene foam and foam core plate are provided as working material instead of traditional hard engineering material such as metals material because these three programs focus more on creative idea generation and dynamic communication among team members rather than the end results. With generative, visual and concrete experiences that can compensate existing engineering classes with traditional focus on analytic, mathematical and reasoning, hands-on experiences can play a significant role for engineering students to develop creative thinking and engineering sense needed to face ill-defined real-world design problems they are expected to encounter upon graduation.

• Journal of The Korean Association For Science Education
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• v.37 no.6
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• pp.993-1003
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• 2017

Teachers expect team-based project learning to help students develop collaborative and real-world problem solving skills. In practice, however, students tend to solve problems with simple division of labor, and there is a tendency that learning transfer does not occur in solving problems. The purpose of this study is to develop a collaborative learning model based on the transactive memory system (TMS) and to verify its effectiveness. The collaborative learning model based on the TMS is composed of three stages. The first stage is developing TMS. In this stage, the students learn physics concepts and make knowledge about the expertise of group members through peer instruction. The second stage, activating TMS, is building trust through solving well-defined problems for developing near-transfer. And in the third stage, applying TMS, the students solve an ill-defined problem based on real-world context for practicing far-transfer. Based on this model, a 15-week program including two projects on geometric optics and sound waves was developed and applied to 60 college students. The data for five weeks of one project were collected and analyzed. As a result, the TMS of the experimental group with the TMS-based collaborative learning model improved stepwise. Whereas, the difference between the first week and the last week was statistically significant, while the TMS change of the comparison group using the general project learning model was not significant. Also, the experimental group showed that the learning transfer occurred better in the project than the comparison group. A collaborative learning model based on TMS can be used to learn how students gain synergy through collaboration and how students collaboratively transfer the learned concepts in problem solving.

• Journal of the Korea Institute of Building Construction
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• v.14 no.6
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• pp.561-569
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• 2014

In construction site, BIM is used in part of construct-ability review and design mistake checking. However, in a current domestic construction site, except public order project, most of work in private order project has been processing based on 2D work. As an expert resists to certain point in introduction of new technique, it may be shown in the introduction of BIM. For this, We need to analysis construct-ability of introducing BIM, work field of introducing and operational capability about present domestic construction engineers. Therefore, this study solves the problem of existing construct-ability analysis, and it visualizes the various information and objects for an effective job performance. Furthermore, construct-ability analysis by BIM that can use an intergrated management is theoretically examined and practical field-application priority among conclusions is proposed through a survey targeting on the hand-on worker. Therefore, this study suggests a factor supplying for a business-centric introduction plan and support condition.

• Science of Emotion and Sensibility
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• v.26 no.3
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• pp.69-82
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• 2023

High-tech sensibility textile and fashion, in which consumers' emotions and various textile and fashion technologies are converged, is an important industrial group. It is important to develop the ability to apply in practice by gathering the creative by understanding other fields and exchanging ideas through interdisciplinary collaboration in the field of emotional engineering. Through interdisciplinary research and collaboration, talent must be nurtured of individuals who would lead the era of the 4^th Industrial Revolution with the ability to empathize with others as well as the creative convergence-type intellectual ability necessary for the rapidly changing society. To determine content-creation methods, basic research is conducted. Additionally, this study investigates on the current status and educational process of the emotional textile-fashion industry worldwide. To nurture talents in the textile and fashion sensibility science, the basic contents are created to manage the knowledge that delivers sensibility science and the ICT related to this field, as well as in the intensive, PB-style conceptual design based on sensibility. The process from derivation of consumer emotion analysis and product development can be experienced through smart kit practice. Moreover, various methods are developed to set up intellectual property rights generated while developing ICT convergence products as start-ups. The study also covers new knowledge rights to develop emotional textile fashion.

• 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 Journal of the Convergence on Culture Technology
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• v.10 no.5
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• pp.397-406
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• 2024

Today, in the field of contemporary fashion design, AI is being actively utilized as a new design tool, leading to a new paradigm of collaboration between designers and AI. This study is about a method for developing integrated fashion design through collaboration between human designers and AI. The purpose of this study is to analyze the visual and formative characteristics and changes of fashion design images generated using the AI generation program Midjourney, thereby expanding the understanding and utilization methods of AI image generation programs in fashion design development. The results of this study are as follows. First, Midjourney has the characteristic of relying more on the characteristics of the existing image used rather than the command when creating the image. It also creates new images by distributing and applying the design through an eclectic interaction between the costume and the image background. By excluding the names of fashion items from the commands, you can generate images that can give you more diverse ideas. Second, Midjourney initially expressed clothing colors using colors used in fashion schematics in color creation, and gradually expanded to various color series. Third, there is a kind of compromise between color and design when Midjourney creates an image, and accordingly, by specifying and limiting the image background and clothing colors, more diverse and advanced fashion design images can be created.

• Journal of The Korean Association For Science Education
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• v.38 no.3
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• pp.343-354
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• 2018

In this study, the first experience of the whole research process of a novice scientist (student A) who participated in the Undergraduate Research Program (URP) was analyzed. The data were collected through observation, interviews, and document analysis with the cultural historical activity theory being used as a theoretical lens. At the beginning of novice's research, the mentor guided him in setting a research goal and provided mediating artifacts. Student A formed a research team based on the vertical relationship without a shared mental model. Two major contradictions occurred and they were the sources of changes of student A's activity system. The first contradiction was between the mentor's educational philosophy and the mentee's educational needs, which was resolved in a way that student A asked and used the mentor's network to obtain his needs about task-specific details. The second contradiction arose because the team members wanted horizontal relationship while student A wanted to stick to the vertical relationship. After student A accepted the opinions of the team members, they cooperatively changed the division of labor in the activity system. Student A decided to become a scientist and not a physics teacher, even if his major is physics education after finishing his URP research process. His URP experience also created and expanded his network in the academic field, and his negative attitude toward collaboration changed positively. Through the analysis of the structure and changes in the activity system of URP research, implications for instructional method and support system of the apprenticeship can be obtained.

• Journal of Digital Convergence
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• v.15 no.10
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• pp.429-436
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• 2017

A design thinking-based collaborative workshop in which various stakeholders in the milk processing industry circulation ecosystem participated shows a new problem innovation paradigm that encourages the spread of practical prototyping culture. in the expression of empathy and collective intelligence among members on facing issues, the conversion of collaboration and communication methods, the business handling of the organization based on the design work method as 'creativity mechanism'. In this workshop, which was promoted in three stages of 'approach to problems', 're-definition of problems', and 'experience-based future vision design', participants themselves redefine real problems in terms of the accuracy of feed orders between feed suppliers and livestock farmers, ordering of feeds on time, cost reduction of feed supply and present new alternatives and expanded business areas. The results suggested in this workshop suggest the usefulness of design thinking in business innovation in that they presented how to approach the problem and a creative thinking system to find its solution to direct and indirect stakeholders of the industry as well as the improvement of supply and demand rate of livestock feed and quality.