• Journal of Fashion Business
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• v.24 no.6
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• pp.135-147
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• 2020

This study explored students' online fashion studio class experiences, and investigated the factors affecting their class satisfaction. An online survey of college students who were enrolled in online studio classes within apparel and fashion-related departments during the spring of 2020 was conducted in June 2020. Responses from a total of 213 participants were included in the final data. Respondents rated lecture clips as the most useful, followed by teacher demonstration and feedback, PowerPoint (PPT) supplements, and Q&As. Frequently mentioned areas of improvement were online platform stability and video quality. Many respondents also stated that more streamlined teacher-student communication channels, immediate and meticulous teacher feedback, the adoption of course contents developed specifically for an online environment, and provisions for equipment usage would be desirable. Student satisfaction of an online fashion design studio class was significantly affected by teaching presence, social presence, online learning system stability, perceived usefulness of teacher's demonstration, and affective response toward COVID-19. Students satisfaction of an online garment construction studio class was significantly affected by teaching and social presence, online learning system stability, and perceived usefulness of teacher's demonstration. Based on these findings, we recommend developing teaching contents and methods that allow students to feel included in class and establish an online system with various functions to enhance the sense of social connection that can enable two-way communication.

• Journal of Engineering Education Research
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• v.24 no.1
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• pp.24-33
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• 2021

As online learning continues to be extended, many engineering colleges are engaged in online learning activities. One of the core competencies required of engineering students in a knowledge-convergence society is communication skills. Online discussion activities are frequently used in educational field to improve communication skills. Efforts are being made to provide visual dashboards in online discussion activity systems to more effectively support online discussion activities. However there is less qualitative studies on students' experience in discussion activities. The purpose of this study is to explore the experience of engineering students participating in discussion activities using online discussion systems and visual dashboards. We interviewed 15 students who participated in online discussion activities to achieve their research objectives about their experience in utilizing the online discussion system, their perception of visual dashboards, and their experience in discussion activities. As a result of the study, students' perception of the use of the online discussion activity system, the visual dashboard, and the perception of a sense of social presence were understood. To be more effective in providing tool support, such as discussion activity systems and visual dashboards in online discussion activities, instructors need to understand the nature of learners' online discussion activities.

• Journal of Information Technology Services
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• v.6 no.3
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• pp.195-207
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• 2007

This study describes the design and implementation of web based collaborative learning system to improve interactivity among learners. Based on suggestions from previous studies, the system is composed of three main parts : the community module, the learning module, and the administrative module. The study participants were 254 university students from two different institutions. They were divided into 43 groups and asked to complete an online TOEIC preparation module using the learning system over 4 weeks. Survey data were collected at three points from each participant-before and 3 weeks after the beginning of the online module and at the completion of the module. The result indicates that the usage of this system is positively related to the learners' collaborative learning activities, the level of sense of community, and learner satisfaction both at the individual and group levels.

• The Journal of the Korea Contents Association
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• v.14 no.6
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• pp.513-528
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• 2014

The landscape of Christian higher education is changing. Students once spent most of their time in a traditional classroom with a professor, but now they take online and hybrid courses (face to face and online). Some students complete their entire degree in a fully online program. Nearly every type of college in the United States offers online courses. Online learning has clearly moved from a fad to a fixture, and nowhere is that more apparent than at one of the largest universities in the country. As the demand for online course and programs increase, teachers and administrators in Christian universities and colleges face new challenges. Even though some teachers and administrators still believe online education is inferior to traditional face-to-face learning, we found no statistically significant differences in standard measures of learning outcomes between students in the traditional classes and students in the hybrid-online format classes. In this situation, since online education will develop continuously, Christian universities should utilize it variously through complete understanding and research about it predicting the future of online education style.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.719-730
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• 2013

The English Conversation class as a required course in S university is designed as blended learning to reinforce English education. To identify the influence of this blended learning on its students' achievement, the research about what variables are related with it was conducted. Data analysis indicates that gender, major, military service, overseas stay, face-to-face attendance, quiz, and online attendance have an effect on the student achievement. However, the students' style of online learning--study place, study time, and study frequency--doesn't have any relationship with their achievement. Their satisfaction with the online study was questioned in the three areas such as instructor, contents, and system, among which only the 'system' area has an influence on their achievement.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.285-288
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• 2017

In this paper, we propose a vision-based object detection and tracking system using online learning. The proposed system adopts a feature point-based method for tracking a series of inter-frame movement of a newly detected object, to estimate rapidly and toughness. At the same time, it trains the detector for the object being tracked online. Temporarily using the result of the failure detector to the object, it initializes the tracker back tracks to enable the robust tracking. In particular, it reduced the processing time by improving the method of updating the appearance models of the objects to increase the tracking performance of the system. Using a data set obtained in a variety of settings, we evaluate the performance of the proposed system in terms of processing time.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.179-192
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• 2014

Keeping in line with the recent changes in the information technology environment, the online learning environment that supports multiple users' participation such as MOOC (Massive Open Online Courses) has become important. One of the largest professional associations in Information Technology, IEEE Computer Society, announced that "Supporting New Learning Styles" is a crucial trend in 2014. Popular MOOC services, CourseRa and edX, have continued to build active learning environment with a large number of lectures accessible anywhere using smart devices, and have been used by an increasing number of users. In addition, collaborative web services (e.g., blogs and Wikipedia) also support the creation of various user-uploaded learning materials, resulting in a vast amount of new lectures and learning materials being created every day in the online space. However, it is difficult for an online educational system to keep a learner' motivation as learning occurs remotely, with limited capability to share knowledge among the learners. Thus, it is essential to understand which materials are needed for each learner and how to motivate learners to actively participate in online learning system. To overcome these issues, leveraging the constructivism theory and collective intelligence, we have developed a social bookmarking system called WeStudy, which supports learning material sharing among the users and provides personalized learning material recommendations. Constructivism theory argues that knowledge is being constructed while learners interact with the world. Collective intelligence can be separated into two types: (1) collaborative collective intelligence, which can be built on the basis of direct collaboration among the participants (e.g., Wikipedia), and (2) integrative collective intelligence, which produces new forms of knowledge by combining independent and distributed information through highly advanced technologies and algorithms (e.g., Google PageRank, Recommender systems). Recommender system, one of the examples of integrative collective intelligence, is to utilize online activities of the users and recommend what users may be interested in. Our system included both collaborative collective intelligence functions and integrative collective intelligence functions. We analyzed well-known Web services based on collective intelligence such as Wikipedia, Slideshare, and Videolectures to identify main design factors that support collective intelligence. Based on this analysis, in addition to sharing online resources through social bookmarking, we selected three essential functions for our system: 1) multimodal visualization of learning materials through two forms (e.g., list and graph), 2) personalized recommendation of learning materials, and 3) explicit designation of learners of their interest. After developing web-based WeStudy system, we conducted usability testing through the heuristic evaluation method that included seven heuristic indices: features and functionality, cognitive page, navigation, search and filtering, control and feedback, forms, context and text. We recruited 10 experts who majored in Human Computer Interaction and worked in the same field, and requested both quantitative and qualitative evaluation of the system. The evaluation results show that, relative to the other functions evaluated, the list/graph page produced higher scores on all indices except for contexts & text. In case of contexts & text, learning material page produced the best score, compared with the other functions. In general, the explicit designation of learners of their interests, one of the distinctive functions, received lower scores on all usability indices because of its unfamiliar functionality to the users. In summary, the evaluation results show that our system has achieved high usability with good performance with some minor issues, which need to be fully addressed before the public release of the system to large-scale users. The study findings provide practical guidelines for the design and development of various systems that utilize collective intelligence.

• Journal of Physiology & Pathology in Korean Medicine
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• v.30 no.6
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• pp.412-418
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• 2016

The emergence of systems biology in the 21st century is changing the paradigm of biomedical research. Whereas the reductionist approaches focus on components rather than time or contexts, systems biology focus more on interrelationships, dynamics, and contexts. The key ideas of the systems biology shares much with the philosophy of Korean Medicine(KM) and therefore, the paradigm shift is shedding light on understanding the mechanism of action of KM at system level. In this article, I provide a guide to learning systems biology for KM researchers using online learning resources. Thanks to the recent development of MOOC(massive open online courses) and other online learning platforms, learners can access to plenty of high-quality resources from top-tier universities in the world. I expect this guide help researchers to employ systems biology methods into their KM researches, and will lead to the development of future curricula for training "bi-lingual" experts, KM and computational approaches.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.109-117
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• 2006

E-learning method has many advantages that supplement the shortfalls of offline education. For this reason, today's offline educational institutions adopted the online education technique to improve learning effectiveness. Recently, general universities have partially adopted online learning. As a result, a study is searching for ways to improve the effectiveness of education by copying the merits of the existing offline education onto the online education. Thus a proper evaluation of learners and a feedback provision are considered necessary to improve the effectiveness of online learning. This study aims to suggest a model that will improve learning efficiency by adapting the advantages of offline education to online learning. To evaluate properly, this study conducted Item Response Test to examine the learners and finally ensure them an adequate level of education. Also, this study suggested a way to enhance learning efficiency by finding out each learner's study habits and to address the weaknesses of online learning. It is expected that the suggested method would be helpful in bettering learner's ability to study in school environment.

• The Journal of the Acoustical Society of Korea
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• v.41 no.2
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• pp.199-209
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• 2022

Typical anomaly detection algorithms are trained by using prior data. Thus the batch learning based algorithms cause inevitable performance degradation when characteristics of newly incoming normal data change over time. We propose an online anomaly detection algorithm which can consider the gradual characteristic changes of incoming normal data. The proposed algorithm based on one-class classification model includes both offline and online learning procedures. In offline learning procedure, the algorithm learns the prior data to be close to centroid of the latent space and then updates the centroid of the latent space incrementally by new incoming data. In the online learning, the algorithm continues learning by using the updated centroid. Through experiments using public underwater acoustic data, the proposed online anomaly detection algorithm takes only approximately 2 % additional learning time for the incremental centroid update and learning. Nevertheless, the proposed algorithm shows 19.10 % improvement in Area Under the receiver operating characteristic Curve (AUC) performance compared to the offline learning model when new incoming normal data comes.