• Journal of The Korean Association of Information Education
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• v.17 no.2
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• pp.115-123
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• 2013

With the rapid growth of mobile technologies, the mobile learning has been gradually considered as a efficient and effective learning form because it breaks the limitations of learning time and space occurring in the traditional classroom learning. Therefore, this research aims how the learners' m-learning efficacy, ubiquity, perceived usefulness, and ease of use predict perceived learning achievement and satisfaction Participants were 144 11th-grade students in A high school in Kyungnam area, Korea. After studying science class using mobile devices, they responded the following surveys: m-learning efficacy, ubiquity, perceived usefulness, ease of use, and satisfaction. Multiple regression analyses with correlation were applied to this study as a data analysis method. Findings of this study include: (a) m-learning efficacy and perceived usefulness predicted learning satisfaction, (b) perceived usefulness and ubiquity predicted perceived learning achievement. These findings imply that m-learning efficacy, perceived usefulness, ubiquity should be valued to enhance learning outcomes in mobile learning class.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.1
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• pp.31-44
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• 2020

Accelerators that invest in early startups, as well as nursery and overall management, have recently emerged as "key players" in the startup ecosystem. This can be proved by the case where the number of domestic accelerators registered in the Korean Ministry of SMEs and Startups has recently reached 208. Accelerators provide the necessary education for early-stage companies, including guidance for a certain period of time, and support startups in ways such as demo days to attract subsequent investment after the seed investment. There is not much research in academia about what factors impact on these accelerators when making investment decisions at the time of seed investment. In this study, we checked the meaning and function of the accelerator and tried to analyze what factors affect on accelerators when making a decision to invest in startups. The research method is based on a literature survey of previous studies on investment decision-making factors of venture capital and angel investors, and a lens model and judgment analysis method through empirical research targeting 43 accelerator investment decision-makers. Empirical analysis shows that accelerators have three of the key factors to consider when choosing the first startup to invest and educate; entrepreneurs' entrepreneurial traits, their product and service expertise and a potential return on success. This will provide an opportunity for early startups to gain strategic access to accelerators when they need money or need a structured educational program. Also, the results obtained through this research will be a kind of guideline for startups to attract accelerators' investment. The significance of this study is that discriminatory evidence was presented on the accelerator determinants of investment, and it would be highly suggestive to startups and related public institutions.

• The Journal of the Korea Contents Association
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• v.19 no.6
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• pp.125-134
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• 2019

The purpose of this study is to explore the direction of decision support for senior citizens living alone by identifying the level of self-determination and desire for decision support. The survey was conducted on 300 elderly people living alone in five districts of Seoul. The analysis results are as follows: First, it has been shown that elderly living alone have thought that it is most important to reflect their decisions when deciding where to live. Second, respondents highly recognized that the need for support decision making as the age group grew. Third, it was found that the factors affecting the perception of the need to support decision-making by senior citizens living alone were age, trust in family and recognition of importance in decision-making. The study suggested the need for a specific, institutionalized system to support decision making for elderly living alone.

• Cartoon and Animation Studies
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• s.47
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• pp.217-239
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• 2017

The purpose of this research is to maximize the core competencies by objectively measuring the Behaviour Patterns of students in Comic-Animation major to understand the difference between individuals and to maximize one's merits which will improve the efficiency in education. Also through this research we could understand which aspects would be affected in both the satisfaction about the major based on Behaviour Patterns and the satisfaction of university life. According to the DISC Patterns, 41.7% of the students in Comic-Animation department shows that they were in Patterns I (Influence). And Patterns S (Steadiness) were 10% which was the lowest percentage in this survey. In the average of the subject's satisfaction aspect, the satisfaction of the professors' suggestion was 3.68 which was the highest. While the satisfaction of the administration service and welfare facility was 2.56 which was the lowest. The satisfaction rate based on DISC Behaviour Patterns shows a significant difference among the satisfaction of the department, the satisfaction of atmosphere in university and the satisfaction of the admin and welfare. Patterns I (Influence) was the highest the satisfaction in the major and the satisfaction of the university life while Patterns C(Criticalness) was the lowest. In particular, the importance of the I (Influence) is the most important factor, but it is essential that there is a slight decrease in the precision and accuracy of the work, and C(Criticalness) is shy and stressed, so they need to give positive communication and accurate advice. It is required to Comic-Animation department professor to analyse students' character based on Behaviour Patterns and a person's pros and cons for the career exploration and the employment consultation in order to have positive affect on employment rate. Also if the department's Behaviour Patterns construction were well utilized, it can improve the success rate of useful leadership and fellowship. it will improve the atmosphere in the department which will decrease the drop-out rate but increase the cohesion in the department which will lead to providing better result in the work and the project.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.227-252
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• 2018

The evolution of instant communication has mirrored the development of the Internet and messenger applications are among the most representative manifestations of instant communication technologies. In messenger applications, senders use emoticons to supplement the emotions conveyed in the text of their messages. The fact that communication via messenger applications is not face-to-face makes it difficult for senders to communicate their emotions to message recipients. Emoticons have long been used as symbols that indicate the moods of speakers. However, at present, emoticon-use is evolving into a means of conveying the psychological states of consumers who want to express individual characteristics and personality quirks while communicating their emotions to others. The fact that companies like KakaoTalk, Line, Apple, etc. have begun conducting emoticon business and sales of related content are expected to gradually increase testifies to the significance of this phenomenon. Nevertheless, despite the development of emoticons themselves and the growth of the emoticon market, no suitable emoticon recommendation system has yet been developed. Even KakaoTalk, a messenger application that commands more than 90% of domestic market share in South Korea, just grouped in to popularity, most recent, or brief category. This means consumers face the inconvenience of constantly scrolling around to locate the emoticons they want. The creation of an emoticon recommendation system would improve consumer convenience and satisfaction and increase the sales revenue of companies the sell emoticons. To recommend appropriate emoticons, it is necessary to quantify the emotions that the consumer sees and emotions. Such quantification will enable us to analyze the characteristics and emotions felt by consumers who used similar emoticons, which, in turn, will facilitate our emoticon recommendations for consumers. One way to quantify emoticons use is metadata-ization. Metadata-ization is a means of structuring or organizing unstructured and semi-structured data to extract meaning. By structuring unstructured emoticon data through metadata-ization, we can easily classify emoticons based on the emotions consumers want to express. To determine emoticons' precise emotions, we had to consider sub-detail expressions-not only the seven common emotional adjectives but also the metaphorical expressions that appear only in South Korean proved by previous studies related to emotion focusing on the emoticon's characteristics. We therefore collected the sub-detail expressions of emotion based on the "Shape", "Color" and "Adumbration". Moreover, to design a highly accurate recommendation system, we considered both emotion-technical indexes and emoticon-emotional indexes. We then identified 14 features of emoticon-technical indexes and selected 36 emotional adjectives. The 36 emotional adjectives consisted of contrasting adjectives, which we reduced to 18, and we measured the 18 emotional adjectives using 40 emoticon sets randomly selected from the top-ranked emoticons in the KakaoTalk shop. We surveyed 277 consumers in their mid-twenties who had experience purchasing emoticons; we recruited them online and asked them to evaluate five different emoticon sets. After data acquisition, we conducted a factor analysis of emoticon-emotional factors. We extracted four factors that we named "Comic", Softness", "Modernity" and "Transparency". We analyzed both the relationship between indexes and consumer attitude and the relationship between emoticon-technical indexes and emoticon-emotional factors. Through this process, we confirmed that the emoticon-technical indexes did not directly affect consumer attitudes but had a mediating effect on consumer attitudes through emoticon-emotional factors. The results of the analysis revealed the mechanism consumers use to evaluate emoticons; the results also showed that consumers' emoticon-technical indexes affected emoticon-emotional factors and that the emoticon-emotional factors affected consumer satisfaction. We therefore designed the emoticon recommendation system using only four emoticon-emotional factors; we created a recommendation method to calculate the Euclidean distance from each factors' emotion. In an attempt to increase the accuracy of the emoticon recommendation system, we compared the emotional patterns of selected emoticons with the recommended emoticons. The emotional patterns corresponded in principle. We verified the emoticon recommendation system by testing prediction accuracy; the predictions were 81.02% accurate in the first result, 76.64% accurate in the second, and 81.63% accurate in the third. This study developed a methodology that can be used in various fields academically and practically. We expect that the novel emoticon recommendation system we designed will increase emoticon sales for companies who conduct business in this domain and make consumer experiences more convenient. In addition, this study served as an important first step in the development of an intelligent emoticon recommendation system. The emotional factors proposed in this study could be collected in an emotional library that could serve as an emotion index for evaluation when new emoticons are released. Moreover, by combining the accumulated emotional library with company sales data, sales information, and consumer data, companies could develop hybrid recommendation systems that would bolster convenience for consumers and serve as intellectual assets that companies could strategically deploy.