• Korean Medical Education Review
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• v.19 no.3
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• pp.158-168
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• 2017

There is a more urgent call for educational methods of machine learning in medical education, and therefore, new approaches of teaching and researching machine learning in medicine are needed. This paper presents a case using machine learning through text analysis. Topic modeling of news articles with the keyword 'asbestos' were examined. Two hypotheses were tested using this method, and the process of machine learning of texts is illustrated through this example. Using an automated text analysis method, all the news articles published from January 1, 1990 to November 15, 2016 in South Korea which included 'asbestos' in the title and the body were collected by web scraping. Differences in topics were analyzed by structured topic modelling (STM) and compared by press companies and periods. More articles were found in liberal media outlets. Differences were found in the number and types of topics in the articles according to the partisanship and period. STM showed that the conservative press views asbestos as a personal problem, while the progressive press views asbestos as a social problem. A divergence in the perspective for emphasizing the issues of asbestos between the conservative press and progressive press was also found. Social perspective influences the main topics of news stories. Thus, the patients' uneasiness and pain are not presented by both sources of media. In addition, topics differ between news media sources based on partisanship, and therefore cause divergence in readers' framing. The method of text analysis and its strengths and weaknesses are explained, and an application for the teaching and researching of machine learning in medical education using the methodology of text analysis is considered. An educational method of machine learning in medical education is urgent for future generations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.4
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• pp.991-1000
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• 2015

This paper is studying for New Online Learning Model on Smart digital era. It can expect the result of learning degree on Online Learning Class. Using 7-factors of Online Class's operating policy, make the expectation model by 'decision tree' method. And through applying another class, we can getting a generality. Finally, Over the traditional Online Class model, we can take the real-time status of Online class learning degree. It is useful both students and teacher. It is the one of 'Smart learning Model'.

• Journal of the HCI Society of Korea
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• v.12 no.3
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• pp.5-11
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• 2017

Korean traditional dance has cultural value and is human's cultural heritage. But they are in danger which is caused by lack of bearers and public interest. E-Learning of traditional dance using network technology and digital media can be a solution to extinction problem. The aim of this study is to propose the E-Learning courses and systems for learning traditional dance. E-Learning systems were evaluated in accordance with the HCI (Human Computer Interaction) user evaluation. This study contribute to overcoming distance constraints by offering synchronous E-Learning education system of traditional dance as intangible cultural heritage through new media experience.

• Journal of Korea Multimedia Society
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• v.22 no.8
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• pp.950-959
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• 2019

The purpose of this study was to investigate the effect of integrated teaching and learning method using augmented reality for effective promotion of child - friendly attitude and environmental preservation attitude and explored its applicability. For this purpose, based on the augmented reality fairy tale, we designed an experience - oriented integrated teaching and learning method such as reading book, story - telling, drawing, environmental conservation practice activity. The experimental group was divided into two groups: augmented reality reading fairy tales (A) and children's book reading fairy tales (B). First, interest, immersion, and empathy were higher in the application environment of integrated learning teaching method based on Augmented Reality. Second, there was no difference between the two groups in content understanding. Third, in terms of expressiveness, it was verified that various expressions were expressed in the applying environment of the integrated teaching - learning method based on augmented reality through drawing activities. Fourth, in practice activities, more students were practicing in the augmented reality - based integrated teaching - learning method applied environment, and the number of practice activities of individual students was also confirmed. This study suggests that the application of the integrated teaching and learning method can enhance the effect of education when using the smart teaching media using the augmented reality in early childhood education.

• The Journal of the Korea Contents Association
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• v.15 no.5
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• pp.36-46
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• 2015

The purpose of this study is to investigate the characteristics of diverse contents service of EBS providing on the multi-platform in the era of smart media. This study investigated contents service of EBS in order to seek and suggest EBS's competitiveness in the era of smart media environment. As a result, EBS is providing real-time service, VOD and e-learning, but its current contents service is concentrated on providing e-learning service. This study recommended that EBS need to reinforce contents suitable for various multi-platform uses. It also suggested EBS need to cooperate with diverse webs service and SNS service in order to widen openness of its platform, and to provide not only diverse contents, but also applications by offering mobile and on-demand contents and services. Finally, this study proposed that EBS is needed to move towards a more public and comprehensive media portal.

• Smart Media Journal
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• v.6 no.3
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• pp.41-48
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• 2017

Event detection using social media has been widespread since social network services have been an active communication channel for connecting with others, diffusing news message. Especially, the real-time characteristic of social media has created the opportunity for supporting for real-time applications/systems. Social network such as Twitter is the potential data source to explore useful information by mining messages posted by the user community. This paper proposed a novel system for temporal event detection by analyzing social data. As a result, this information can be used by first responders, decision makers, or news agents to gain insight of the situation. The proposed approach takes advantages of deep learning methods that play core techniques on the main tasks including informative data identifying from a noisy environment and temporal event detection. The former is the responsibility of Convolutional Neural Network model trained from labeled Twitter data. The latter is for event detection supported by Recurrent Neural Network module. We demonstrated our approach and experimental results on the case study of earthquake situations. Our system is more adaptive than other systems used traditional methods since deep learning enables to extract the features of data without spending lots of time constructing feature by hand. This benefit makes our approach adaptive to extend to a new context of practice. Moreover, the proposed system promised to respond to acceptable delay within several minutes that will helpful mean for supporting news channel agents or belief plan in case of disaster events.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.77-85
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• 2020

The purpose of this study is to explore the changing trajectory of using educational media through longitudinal data analysis. We categorize the feature of using educational media as usage for learning, usage for information, and usage for the game. We explore the longitudinal changing patterns of usage for learning, usage for information, and usage for the game by LGM(Longitudinal Growth Modeling). We also find the gender difference between these longitudinal changing trajectories. We used 3,499 samples of KYPS middle school second-grade panel data. We found these results: (a) Both usage for learning and information are statically significant variability in initial level and rate of change. Both of the changing trajectories have increased. (b) Girls have a higher rate of the change both in the usage of learning and information than boys over time. (c) There is a statistically significant individual variability in initial levels and rate of change in the usage of the game over time. (d) Boys have a higher rate of initial value than girls in the usage of games, but there is no significant difference in the rate of changing trajectories.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.59-68
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• 2022

As real-time live streaming broadcasting and non-face-to-face classes are spreading in the Corona era, it is time to take academic interest in online streaming classes. In particular, it is important to clarify why users use online streaming classes. Therefore, this study proposes social presence, interest, convenience of use, and interactivity as characteristics of online streaming classes, and aims to verify how these characteristics affect learning satisfaction and furthermore, recommendation intention. As a result of conducting a survey on 338 Chinese collegestudents, it was found that interactivity, social presence, and interest had a positive effect on learning satisfaction, but the effect of ease did not appear. On the other hand, it was confirmed that learning satisfaction had a positive effect on the online streaming class recommendation intention.

• The Journal of the Korea Contents Association
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• v.17 no.6
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• pp.124-131
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• 2017

In the era of digital media era, the importance of media education has been emphasized by both scholars and audience right related organizations. However, little research has been conducted about the factors may have influence on the intention to participate media education program. Therefore, this study attempted to examine the effect of motivation on both satisfaction and intention of it. For this purpose, this study surveyed the participants from education program offered by two local media center. The results showed that the activity-oriented motivation had effect on both the satisfaction and intention to continuous participation. The results of the current study can be applied to development of the plan for encouraging the continuous learning of media.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.709-713
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• 2009

Recently, a lot of research that applies data acquired from devices such as cameras and RFIDs to context aware services is being performed in the field on Life-Log and the sensor network. A variety of analytical techniques has been proposed to recognize various information from the raw data because video and audio data include a larger volume of information than other sensor data. However, manually watching a huge amount of media data again has been necessary to create supervised data for the update of a class or the addition of a new class because these techniques generally use supervised learning. Therefore, the problem was that applications were able to use only recognition function based on fixed supervised data in most cases. Then, we proposed a method of acquiring supervised data from a video sharing site where users give comments on any video scene because those sites are remarkably popular and, therefore, many comments are generated. In the first step of this method, words with a high utility value are extracted by filtering the comment about the video. Second, the set of feature data in the time series is calculated by applying functions, which extract various feature data, to media data. Finally, our learning system calculates the correlation coefficient by using the above-mentioned two kinds of data, and the correlation coefficient is stored in the DB of the system. Various other applications contain a recognition function that is used to generate collective intelligence based on Web comments, by applying this correlation coefficient to new media data. In addition, flexible recognition that adjusts to a new object becomes possible by regularly acquiring and learning both media data and comments from a video sharing site while reducing work by manual operation. As a result, recognition of not only the name of the seen object but also indirect information, e.g. the impression or the action toward the object, was enabled.