• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.524-539
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• 2022

With the advent of generative artificial intelligence technology, it became possible to create a virtual human, and produce a lecture video only with textual information. It is expected that the virtual human will enhance the efficient production of educational contents and the student's entertainment experience and satisfaction. However, there have been still few studies that have demonstrated the process of how virtual human technology reaches students' satisfaction. Therefore, the purpose of this study is to empirically examine whether the human likeness, which is the main characteristic of a virtual human based on Uncanny Valley theory, affects human experience and satisfaction. In particular, human likeness of the Uncanny Valley theory was subdivided into human likeness in the visual and verbal dimensions, and the process of reaching satisfaction was understood based on the experience economy model. In particular, human similarity in Uncanny Valley theory was classified as similarity in the visual and language levels, and the process of reaching satisfaction based on the experiential economic model was analyzed with a partial least squares structure model equation (PLS-SEM). The survey was conducted online for a panel of office workers at a specialized research institution in China. The results indicate that both the visual and verbal human likeness had a positive effect on experience economy factors (education, entertainment, esthetic, escape), and then these experiential factors had a significant effect on satisfaction. The results also provide some suggestions to consider when designing educational contents by virtual human.

• Informatization Policy
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• v.29 no.3
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• pp.82-104
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• 2022

One of the interesting social phenomena in short-form video platforms is the hashtag challenge wherein ordinary users are encouraged to create by imitating short viral videos on a particular theme. Despite the increasing popularity of hashtag challenges, theoretical discussion on related user behavior is still very insufficient. In this study, we attempted to examine the impact of micro-influencers in order to understand users' willingness to participate in hashtag challenges. For this purpose, the para-social interaction theory and imitation behavior literature were adopted as key theoretical basis. In an empirical investigation using 243 survey data from TikTok users, our study found that a user's illusion of intimacy with a micro-influencer (i.e., para-social interaction) had significant positive impact on the intention to participate in a hashtag challenge. This study also showed that the degree of para-social interaction in a short-form video platform was determined by both media content-related factors and media character-related factors (i.e., content attractiveness, physical attractiveness, and attitude homophily). Our work in this study provided significant theoretical and practical implications on how to leverage micro-influencers for the success of hashtag challenges in a short-form video platform.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.25-30
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• 2022

This study is a study on the filter bubble reinforcement phenomenon of SNS recommendation algorithm such as YouTube, which is a characteristic of the Russian-Ukraine war (2022), and the victory or defeat factors of the hybrid war. This war is identified as a hybrid war, and the use of New Media based on the SNS recommendation algorithm is emerging as a factor that determines the outcome of the war beyond political leverage. For this reason, the filter bubble phenomenon goes beyond the dictionary meaning of confirmation bias that limits information exposed to viewers. A YouTube video of Ukrainian President Zelensky encouraging protests in Kyiv garnered 7.02 million views, but Putin's speech only 800,000, which is a evidence that his speech was not exposed to the recommendation algorithm. The war of these SNS recommendation algorithms tends to develop into an algorithm war between the US (YouTube, Twitter, Facebook) and China (TikTok) big tech companies. Influenced by US companies, Ukraine is now able to receive international support, and in Russia, under the influence of Chinese companies, Putin's approval rating is over 80%, resulting in conflicting results. Since this algorithmic empowerment is based on the confirmation bias of public opinion by 'filter bubble', the justification that a new guideline setting for this distortion phenomenon should be presented shortly is drawing attention through this Russia-Ukraine war.

• Journal of The Korean Association For Science Education
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• v.43 no.2
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• pp.59-72
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• 2023

This study analyzed a group interview with six earth science teachers and eight middle school students to find out the evaluations and criteria they use to evaluate VR/AR contents (two virtual reality content and two augmented reality contents) in middle school science digital textbook. The study found the VR/AR contents were evaluated on four criteria as follows: VR/AR media characteristics; technical operation; user interface; and teaching-learning design. The evaluations can be summarized by each criterion. First, regarding VR/AR media characteristics, interesting features of VR/AR contents were considered relatively advantageous compared to other media like videos. However, its shortage of visual presence and inconvenience of using markers were mentioned as shortcomings. Second, in the technical operation criteria, teachers and students found the following conditions as technically challenging: failing to properly operate on a particular OS; huge volumes of contents in the application; and frequent freezing when using the application. Third, poor intuitiveness and lack of flexibility were found as negative aspects in user interface. Fourth, regarding teaching-learning design, the teachers evaluated whether the VR/AR contents delivered scientifically accurate information; whether they incorporated class goals set by teachers; and whether they can help students' inquiry. It turned out teachers gave negative feedbacks on VR/AR contents. The students evaluated VR/AR contents by assessing whether they help them with learning science but concluded they did not regard them necessary in science learning at school. Based on the findings, this study discusses which development direction VR/AR contents should take to be useful in teaching and learning science.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.825-834
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• 2023

The demands of people who purchase fashion products on Internet shopping are gradually increasing, and attempts are being made to provide user-friendly images with 3D contents and web 3D software instead of pictures and videos of products provided. As a reason for this issue, which has emerged as the most important aspect in the fashion web shopping industry, complaints that the product is different when the product is received and the image at the time of purchase has been heightened. As a way to solve this problem, various image processing technologies have been introduced, but there is a limit to the quality of 2D images. In this study, we proposed an automatic conversion technology that converts 2D images into 3D and grafts them to web 3D technology that allows customers to identify products in various locations and reduces the cost and calculation time required for conversion. We developed a system that shoots a mannequin by placing it on a rotating turntable using only 8 cameras. In order to extract only the clothing part from the image taken by this system, markers are removed using U-net, and an algorithm that extracts only the clothing area by identifying the color feature information of the background area and mannequin area is proposed. Using this algorithm, the time taken to extract only the clothes area after taking an image is 2.25 seconds per image, and it takes a total of 144 seconds (2 minutes and 4 seconds) when taking 64 images of one piece of clothing. It can extract 3D objects with very good performance compared to the system.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.133-148
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• 2014

Recently, with the advent of various information channels, the number of has continued to grow. The main cause of this phenomenon can be found in the significant increase of unstructured data, as the use of smart devices enables users to create data in the form of text, audio, images, and video. In various types of unstructured data, the user's opinion and a variety of information is clearly expressed in text data such as news, reports, papers, and various articles. Thus, active attempts have been made to create new value by analyzing these texts. The representative techniques used in text analysis are text mining and opinion mining. These share certain important characteristics; for example, they not only use text documents as input data, but also use many natural language processing techniques such as filtering and parsing. Therefore, opinion mining is usually recognized as a sub-concept of text mining, or, in many cases, the two terms are used interchangeably in the literature. Suppose that the purpose of a certain classification analysis is to predict a positive or negative opinion contained in some documents. If we focus on the classification process, the analysis can be regarded as a traditional text mining case. However, if we observe that the target of the analysis is a positive or negative opinion, the analysis can be regarded as a typical example of opinion mining. In other words, two methods (i.e., text mining and opinion mining) are available for opinion classification. Thus, in order to distinguish between the two, a precise definition of each method is needed. In this paper, we found that it is very difficult to distinguish between the two methods clearly with respect to the purpose of analysis and the type of results. We conclude that the most definitive criterion to distinguish text mining from opinion mining is whether an analysis utilizes any kind of sentiment lexicon. We first established two prediction models, one based on opinion mining and the other on text mining. Next, we compared the main processes used by the two prediction models. Finally, we compared their prediction accuracy. We then analyzed 2,000 movie reviews. The results revealed that the prediction model based on opinion mining showed higher average prediction accuracy compared to the text mining model. Moreover, in the lift chart generated by the opinion mining based model, the prediction accuracy for the documents with strong certainty was higher than that for the documents with weak certainty. Most of all, opinion mining has a meaningful advantage in that it can reduce learning time dramatically, because a sentiment lexicon generated once can be reused in a similar application domain. Additionally, the classification results can be clearly explained by using a sentiment lexicon. This study has two limitations. First, the results of the experiments cannot be generalized, mainly because the experiment is limited to a small number of movie reviews. Additionally, various parameters in the parsing and filtering steps of the text mining may have affected the accuracy of the prediction models. However, this research contributes a performance and comparison of text mining analysis and opinion mining analysis for opinion classification. In future research, a more precise evaluation of the two methods should be made through intensive experiments.

• Journal of The Korean Association For Science Education
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• v.37 no.6
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• pp.1025-1035
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• 2017

The purposes of this study are to analyze the merits and limits of flipped learning by suggesting the ALP model for efficient application and to test the effects of the new ALP model. The process of new model and program development is based on ADDIE in this study. This study consists of two steps. First through literature research on the difficulties of the flipped learning, the elements are extracted to develop new model. Second, these elements were placed according to the teaching and learning flow, which resulted in the procedures. As a result, the ALP model was developed. The ALP model is a new model for applying teaching and learning methods for efficient application of the flipped learning. This model was applied to elementary science classes to test its effects in scientific communication skill. Interviews and cognitive survey were also conducted to collect additional information. The results of this study are as follows: There were various difficulties in flipped learning. Based on literature research results, the ALP model and the science programs for elementary students have been developed. The experimental group showed statistically meaningful improvement in scientific communication skill. The scientific communication skill has two subcategories: the forms and the types. According to the form analysis results, the experimental group showed a statistically meaningful improvement in the form of Table and Picture, but not in the form of Writing and Number. With the same reason given previously, this study confirmed that the application of ALP model improves the students' visual form communication skills such as Table and Picture better than reading form communication skills such as Writing and Number. According to the type analysis results, the experimental group showed a statistically meaningful improvement in "the scientific insistence" type, and "the justification" which is the sub element of "the scientific insistence" type. With this reason, this study suggests that the class applied ALP model gives students more time and opportunities to learn. Though the survey and interviews about the student's awareness of the class with applied the ALP model, this study showed that students actively exchanged their opinions in the class with applied ALP model.

• Journal of Korean Home Economics Education Association
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• v.29 no.1
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• pp.15-33
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• 2017

The purpose of this study was to develop and evaluate a practical problem-based teaching learning process plan for safety in residential environment to raise safety awareness of middle school students. The plan consisting of 4 lessons has been developed and implemented according to the ADDIE model. Various activity materials (26 student's activity sheets and 8 reading texts, and 8 teacher's reading texts) and visual materials (4 sets of pictures & photos and 8 moving pictures) as well as questionnaire were developed for the 4-session lessons. The plans were implemented by the researcher to 4 classes 121 freshmen of M boy's middle school in Kyeongbuk during December 21st to 29th, 2015. Students were highly enjoyed and satisfied with the whole 4-lessons in the aspects such as the level of participation in the lesson, understanding of the contents, adequacy of materials and activities, and usefulness in own's daily life. Students also reported that they were highly aware to practice the contents learned from the lessons in daily family life at home with one's family and recommended to teach the lessons to other schools, too. It can be concluded that the teaching learning process plan for safety in residential environment would raise safety awareness of middle school students through the Home Economics subject.

• Journal of Korean Home Economics Education Association
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• v.29 no.3
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• pp.33-48
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• 2017

The purpose of this research was to analyze the contents of housing teaching learning studies in Home Economics of secondary schools since 2001. The 22 research, drawn from the database 'riss4u', were analyzed in terms of general information of the paper (studied institution & year, implementation & evaluation, subject of study & size) and specific contents of teaching learning plans (theme, curricula & textbooks, methode & # of lessons, resources). The results showed that most studies were reported during the 7th or the 2007 revised curricula period. All, except one doctoral dissertation, were master's theses from a few universities. In all studies, ranging from 2 to 15 lessons, teaching learning plans were implemented and evaluated in the class of the researcher while some were applied in other schools, too. The theme of the teaching learning plans varied but were concentrated on one out of two content elements and two out of six learning elements. The 2007 revised curriculum seems to be an important turning point, not only reinforcing the analyses of the curricular and textbooks in the analyzing stage but also facilitating the use of various methods for the lessons in the developing stage. Practical problem based model was the most frequently adopted, while cooperative learning and ICT served as fundamental although not always mentioned. Various teaching resources such as UCC, reading materials, PPT were developed for the teacher. Activity sheets were the most frequently used for the students, followed by reading materials. Because teaching learning is an essential core of education, teaching learning studies should be more actively conducted and the variety of subject topics, methods and resources should also be obtained by more researchers.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.75-100
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• 2018

Mobile devices have become an important channel for news content usage in our daily life. However, online news content readers' resistance to online news monetization is more serious than other digital content businesses, such as webtoons, music sources, videos, and games. Since major portal sites distribute online news content free of charge to increase their traffics, customers have been accustomed to free news content; hence this makes online news providers more difficult to switch their policies on business models (i.e., monetization policy). As a result, most online news providers are highly dependent on the advertising business model, which can lead to increasing number of false, exaggerated, or sensational advertisements inside the news website to maximize their advertising revenue. To reduce this advertising dependencies, many online news providers had attempted to switch their 'free' readers to 'paid' users, but most of them failed. However, recently, some online news media have been successfully applying the Pay-What-You-Want (PWYW) payment model, which allows readers to voluntarily pay fees for their favorite news content. These successful cases shed some lights to the managers of online news content provider regarding that the PWYW model can serve as an alternative business model. In this study, therefore, we collected 379 online news articles from Ohmynews.com that has been successfully employing the PWYW model, and analyzed the comparative importance of systematic attributes of online news content on readers' voluntary payment. More specifically, we derived the six systematic attributes (i.e., Type of Article Title, Image Stimulation, Article Readability, Article Type, Dominant Emotion, and Article-Image Similarity) and three or four levels within each attribute based on previous studies. Then, we conducted content analysis to measure five attributes except Article Readability attribute, measured by Flesch readability score. Before conducting main content analysis, the face reliabilities of chosen attributes were measured by three doctoral level researchers with 37 sample articles, and inter-coder reliabilities of the three coders were verified. Then, the main content analysis was conducted for two months from March 2017 with 379 online news articles. All 379 articles were reviewed by the same three coders, and 65 articles that showed inconsistency among coders were excluded before employing conjoint analysis. Finally, we examined the comparative importance of those six systematic attributes (Study 1), and levels within each of the six attributes (Study 2) through conjoint analysis with 314 online news articles. From the results of conjoint analysis, we found that Article Readability, Article-Image Similarity, and Type of Article Title are the most significant factors affecting online news readers' voluntary payment. First, it can be interpreted that if the level of readability of an online news article is in line with the readers' level of readership, the readers will voluntarily pay more. Second, the similarity between the content of the article and the image within it enables the readers to increase the information acceptance and to transmit the message of the article more effectively. Third, readers expect that the article title would reveal the content of the article, and the expectation influences the understanding and satisfaction of the article. Therefore, it is necessary to write an article with an appropriate readability level, and use images and title well matched with the content to make readers voluntarily pay more. We also examined the comparative importance of levels within each attribute in more details. Based on findings of two studies, two major and nine minor propositions are suggested for future empirical research. This study has academic implications in that it is one of the first studies applying both content analysis and conjoint analysis together to examine readers' voluntary payment behavior, rather than their intention to pay. In addition, online news content creators, providers, and managers could find some practical insights from this research in terms of how they should produce news content to make readers voluntarily pay more for their online news content.