• Korean Medical Education Review
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• v.24 no.1
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• pp.56-62
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• 2022

Despite current regulations requiring social distancing due to coronavirus disease 2019, problem-based learning (PBL) requires student interaction to achieve common goals and enhance critical thinking and deep learning abilities. Social presence in the online education environment reduces both perceptions of physical distance and psychological distance in interactions. This study aimed to compare PBL activities between in-person and videoconferencing classes, and to investigate social presence and learning satisfaction in a videoconferencing PBL environment. The PBL consisted of six modules for both the first and second years of Chonnam National University Medical School. As social distancing was strengthened, the second class of the fifth module in both years was converted to an online format and the fifth module was excluded. The first four PBL modules were conducted as in-person classes, but the last PBL module was administered via videoconferencing. After the final PBL module, 100 (81.3%) first-year medical students and 90 (79.6%) second-year students were asked to complete a self-administered questionnaire on social presence and learning satisfaction. There were no significant differences in the small group activities of tutorial sessions between in-person and videoconferencing classes. In the online videoconferencing class, students who had favorable attitudes toward the tutors' social role and interactions with peers showed high satisfaction with their learning. In conclusion, online videoconferencing allows students to simultaneously perceive their interactions with others and social presence, even at a distance. Tutors can enhance a sense of online community and collaborative learning as facilitators of online PBL.

• The Journal of Bigdata
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• v.8 no.2
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• pp.15-25
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• 2023

Extreme learning machines (ELMs) are a major analytical method in various prediction fields. ELMs can accurately predict even if the data contains noise or is nonlinear by learning the complex patterns of time series data through optimal learning. This study presents the recent trends of machine learning models that are mainly studied as tools for analyzing online time series data, along with the application characteristics using existing algorithms. In order to efficiently learn large-scale online data that is continuously and explosively generated, it is necessary to have a learning technology that can perform well even in properties that can evolve in various ways. Therefore, this study examines a comprehensive overview of the latest machine learning models applied to big data in the field of time series prediction, discusses the general characteristics of the latest models that learn online data, which is one of the major challenges of machine learning for big data, and how efficiently they can learn and use online time series data for prediction, and proposes alternatives.

• Journal of The Korean Association of Information Education
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• v.22 no.1
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• pp.159-167
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• 2018

In this study, we have developed an online learning community site using Humhub social network software and promote social constructive learning through the questions and answers in subject specific learning groups. By accumulating learning contents which consist of questions and answers about specific topics, learners can acquire knowledge by searching relevant topics and questions and can create and reconstruct knowledge as well as consuming knowledge by participating in self-regulated learning community. We have developed a mathematical editor feature which enables users to enter mathematical expression such as equations and greek characters. Online learning community sites can be used for inquiry based information education.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.476-483
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• 2022

The novel coronavirus pandemic has had a significant impact on society and everyday life. The pandemic imposed a global shutdown leading to many challenges such as the suspension of academic programs at universities. The result of this suspension contributed to the rapid overnight migration of educational activities from traditional face-to-face learning to a virtual environment which until then was unfamiliar to both instructors and students. This study identified the experiences faced by built environment higher education instructors in KwaZulu-Natal, South Africa during this sudden switch to online teaching and learning. This pilot study employed a quantitative research approach to survey instructor experiences on online teaching and learning during a global pandemic. The data was computed and analyzed using IBM Statistical Package for Social Sciences (SPSS) version 27. Descriptive statistics were used to analyze the data collected. The study sample comprised of 20 higher education instructors in the region of the KwaZulu Natal province in South Africa. Findings from the study revealed that instructors faced adaptive challenges with rapidly having to redesign and remodel the mode of academic course delivery and assessments to suit an online platform. Additionally, instructors observed that students faced technological challenges such as connectivity and navigating the online learning management system platforms. The challenges identified by instructors and students can be effectively transformed to opportunities for future learning under the 'new normal'.

• Korean Medical Education Review
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• v.22 no.2
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• pp.144-144
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• 2020

• 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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.3
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• pp.145-152
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• 2015

We consider an online selective-sample learning problem for sequence classification, where the goal is to learn a predictive model using a stream of data samples whose class labels can be selectively queried by the algorithm. Given that there is a limit to the total number of queries permitted, the key issue is choosing the most informative and salient samples for their class labels to be queried. Recently, several aggressive selective-sample algorithms have been proposed under a linear model for static (non-sequential) binary classification. We extend the idea to hidden Markov models for multi-class sequence classification by introducing reasonable measures for the novelty and prediction confidence of the incoming sample with respect to the current model, on which the query decision is based. For several sequence classification datasets/tasks in online learning setups, we demonstrate the effectiveness of the proposed approach.

• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.13-22
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• 2023

The purpose of this paper is to explore the impact of online problem-based learning (PBL) on learners' 4C competencies and learning experience. The results of the study showed that, first, online PBL had a statistically significant effect on learners' problem-solving skills, communication skills, and pre-service teacher efficacy. Second, learners were very satisfied with the online PBL experience and perceived it to be very beneficial to their learning and to themselves as preservice teachers. Third, learners perceived that the real-time video conferencing system and instant messenger were very helpful for successful online PBL. Fourth, regarding the important factors for successful online PBL, the participants in this study perceived that communication and sincerity are very important, and the role of the leader is also important, but personal intimacy among team members is relatively less important. Fifth, learners perceive that instructor feedback is very important for successful online PBL. Finally, the implications of this study are discussed along with suggestions for future research.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.239-248
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• 2023

This study is a descriptive correlation study to identify the relationship among online collaborating learning attitudes, empathy, critical thinking disposition, and sense of community in nursing students in the online learning environment during COVID-19. Data were collected from 129 nursing students. The SPSS/28.0 program was used to analyze the data using descriptive statistics, Pearson's correlation coefficient, independent t-test, one-way ANOVA, Scheffé test, Pearson's correlation analysis, and hierarchical multiple regression. Factors that significantly affect sense of community in nursing students were online collaborating learning attitudes and critical thinking disposition, and the explanatory power was about 42.2%. Based on these results, in order to increase sense of community of nursing students in non-face-to-face learning environment, it is required to strengthen the problem-solving-centered learning method cultivating the online collaborating learning attitude and critical thinking disposition.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.272-275
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• 2022

Large-scale online platforms such as MOOCs-Massive Open Online Courses, which provide a variety of educational contents, have provided a learning environment that allows students to freely access and learn anytime and anywhere. Currently, the proportion of online lectures and home-based learning is increasing, and portfolio or experience-based learning such as bootcamp, field activities, and team project-based group learning are also being actively carried out for educational outcomes. At present, interest in nano or microdegree focused on core technology in units of hours or credits is increasing significantly because such strategic intensive education enables effective learning in terms of continuity and efficiency of education. In an era of large changes in job market due to the reorganization of the industrial structure by new technologies, intensive education in specialized new technology fields such as smart mobility, big data, and artificial intelligence is much more conducive to finding a job. With this reason it is attracting attention as an alternative to lifelong learning are receiving In this paper we propose an educational platform that can efficiently and effectively support the purpose learning for the personalized microdegree education in the online learning era.