• Journal of Korean Library and Information Science Society
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• v.53 no.1
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• pp.231-263
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• 2022

The understanding and capability to utilize artificial intelligence (AI) incorporated technology has become a required basic skillset for the people living in today's information age, and various members of the university have also increasingly become aware of the need for AI education. Amidst such shifting societal demands, both domestic and international university libraries have recognized the users' need for educational content centered on AI, but a user-centered service that aims to provide personalized recommendations of digital AI educational content is yet to become available. It is critical while the demand for AI education amongst university students is progressively growing that university libraries acquire a clear understanding of user intention towards an AI educational content recommender system and the potential factors contributing to its success. This study intended to ascertain the factors affecting acceptance of such system, using the Extended Technology Acceptance Model with added variables - innovativeness, self-efficacy, social influence, system quality and task-technology fit - in addition to perceived usefulness, perceived ease of use, and intention to use. Quantitative research was conducted via online research surveys for university students, and quantitative research was conducted through written interviews of university librarians. Results show that all groups, regardless of gender, year, or major, have the intention to use the AI-related Educational Content Recommendation System, with the task suitability factor being the most dominant variant to affect use intention. University librarians have also expressed agreement about the necessity of the recommendation system, and presented budget and content quality issues as realistic restrictions of the aforementioned system.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.37-64
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• 2022

As the social acceptance of artificial intelligence increases, the number of cases of applying machine learning methods to companies is also increasing. Technical factors such as accuracy and interpretability have been the main criteria for selecting machine learning methods. However, the success of implementing machine learning also affects management factors such as IT departments, operation departments, leadership, and organizational culture. Unfortunately, there are few integrated studies that understand the success factors of machine learning selection in which technical and management factors are considered together. Therefore, the purpose of this paper is to propose and empirically analyze a technology-management integrated model that combines task-tech fit, IS Success Model theory, and John Rice's algorithm selection process model to understand machine learning selection within the company. As a result of a survey of 240 companies that implemented machine learning, it was found that the higher the algorithm quality and data quality, the higher the algorithm-problem fit was perceived. It was also verified that algorithm-problem fit had a significant impact on the organization's innovation and productivity. In addition, it was confirmed that outsourcing and management support had a positive impact on the quality of the machine learning system and organizational cultural factors such as data-driven management and motivation. Data-driven management and motivation were highly perceived in companies' performance.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.189-217
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• 2023

The metaverse is a virtual world where individuals engage in social, economic, and cultural activities using avatars, which represent an alternate version of oneself within the virtual realm. While the metaverse has garnered global attention recently, research exploring the identity manifested through avatars within the metaverse remains limited. This study investigates the influence of four IT artifact characteristics related to avatar usage in the metaverse-avatar representation, avatar copresence, avatar profiling, and avatar-space interaction-on perceived avatar identity verification. A survey was conducted with 196 experienced users of the Zepeto platform, and hypotheses were tested using structural equation modeling. The analysis results indicate that the use of IT artifacts enabling avatar representation, avatar copresence, and avatar-space interaction has a positive impact on perceived avatar identity verification. This achieved self-verification indirectly influences the satisfaction and subsequent intention to continue using the metaverse. This study contributes to the academic field by empirically verifying the metaverse technological factors that influence the projected identity onto avatars within the metaverse. Furthermore, it is expected to provide effective guidelines for metaverse platform companies in designing and implementing the metaverse.

• The Research Journal of the Costume Culture
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• v.13 no.5 s.58
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• pp.712-728
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• 2005

This study consists of the stimuli of a female model in her twenties with twenty-three different facial make-up and survey on the differences of them for the development of make-up color system, based on the color-sense on the Korean's skin-tone and make-up color, to enforce the efficiency of beauty education. The result of this study and the suggestion is as followed. Firstly, Familiarity, Intelligence, Fitness, Charm, Tradition and Youth were came out as the result of factor analysis of make-up color image perception. Secondly, the stimulus of bare face was evaluated as more familiar and intelligent than the one with image make-up but perceived as unhealthy and not untraditional. Thirdly, skin tone had a big impact on both in lip color that's been applied in monotonous make-up and in image make-up that had been applied in contrastive make-up. Through these results, it is confirmed that the skin tone and make-up colors were influential variables in the research on facial image perception and preference against a female model in her 20s, and also the image test and preference can be changed according to the color contrasts. This research will be used as a basic tool for the development of make-up color applying system with image perception of statics of population variables and preference research. Also it aims to suggest the alternatives to perform the present collage make-up education for more systematic and organized education.

• Journal of Gifted/Talented Education
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• v.5 no.2
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• pp.55-89
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• 1995

Currently Korea encourages gifted highschoolers and junior high schoolers to participate in international achievement contests such as International Olympiads. Participants for these contests are selected nationwide among gifted students in areas of mathematics, physics, chemistry, and others. They go through a series of screening tests and programs. One of the screening processes is Korean Olympiad School, which provides study programs each summer for student-candidates prior to following year's International Olympiads. Approximately 40 students of high schools and junior high schools, in each subject of study, gather at Korean Olympiad Summer School, and they go through intensive study programs during short period of time. Out of 40 candidates, less than 20 students are finally selected to participate in International Olympiads. In this study, a psycho-educational program called "Situatin Coping Training Program" was developed to enhance ahievement motivation for these student-candidates. This study was to see if this tranining program actually improved their cognitive, emotive motivation factors, and to see how this training program affected their achievement level. Training was administered for five days. This training program was found effective for participants to increase self-efficacy, internal locus of control, and anxiety coping. These cognitive and emotive motivation factors, other than intelligence, were found to have positive relationship with achievement level, of which self-efficacy and attribution style of students were found as two best predictors of achievement. This training program was perceived as necessary by participants, and helpful for recovering self-confidence and self-control as well as coping pressure. Suggestions were made that this kind of training program be administered as regular curriculum in preparative study programs such as Korean Olympiads, since cognitive, emotive motivation factors are related with achievement, and furthermore, be utilized in all gifted education programs in Korea. in Korea.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.70-76
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• 2021

The relevance of intelligence involves the definition of such communication systems of PR-management and branding of media channels with the use of social networks, which are already implemented in practice by modern representatives of professional PR product. The purpose of the investigation is to determine the system of implementation of technologies of PR-management and branding of media channels with the use of social networks based on a survey of PR and brand of different media channels on the basis of a survey of brand managers and PR. 980 respondents from Ukraine took part in the survey. The survey was conducted on the Google-forms platform. The results outline a list of the most popular social networks and messengers for the implementation of PR management and branding technologies, including Facebook, Twitter, Google, LinkedIn, Tumblr; Telegram, WhatsApp, Viber, Skype. It is determined that the criteria of branding analysis are informativeness, centralization/distribution, content, feedback intensity. Identified 2 prospects for the development of branding in an interactive media environment (creation of a presentation system; integration of websites of social media and companies in universal centers). The criteria of general importance of the factors influencing the behavioral intention of consumers to use social media channels are presented (satisfaction, accessibility, perceived usefulness, trust, ease of use, attitude, social influence, self-efficacy). The meaning of the content of social media channels (public, informational and communication) is indicated. The practical significance of the study was to present the links between the criteria, development prospects and the values of branding factors.

• Journal of the HCI Society of Korea
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• v.14 no.1
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• pp.35-43
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• 2019

This study examines how interactivity and usage mode of a chatbot interface affects user experience. Chatbot has rapidly been commercialized in accordance with improvements in artificial intelligence and natural language processing. However, most of the researches have focused on the technical aspect to improve the performance of chatbots, and it is necessary to study user experience on a chatbot interface. In this article, we investigated how 'interactivity' of an interface and the 'usage mode' referring to situations of a user affect the satisfaction, flow, and perceived usefulness of a chatbot for exploring user experience. As the result, first, the higher level of interactivity, the higher user experience. Second, usage mode showed interaction effect with interactivity on flow, although it didn't show the main effect. In specific, when interactivity is high in usage mode, flow was the highest rather than other conditions. Thus, for designing better chatbot interfaces, it should be considered to increase the degree of interactivity, and for users to achieve a goal easily through various functions with high interactivity.

• Journal of the HCI Society of Korea
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• v.14 no.2
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• pp.61-69
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• 2019

Recently, as a new ICT trend, emerging chatbots are actively introduced in the field of finance. Chatbot conducts services through the interaction of communication with users. The purpose of this study is to investigate the effect of interaction dialogue type on the efficiency, usability, sensibility and perceived security of financial service chatbot. Based on theoretical considerations, I have divided into closed conversation, open conversation, and mixed conversation type based on the conversation style based on the implementation method of chatbot. Three types of Financial Chatbot prototypes were made and the experiments were conducted after account inquiry, account transfer, Q & A financial task execution. As a result of experimental research analysis, chatbot's interaction dialogue type was found to affect efficiency and usability. Users have shown that the interaction of closed conversations and mixed conversations is an intuitive interface that allows financial services to be easily manipulated without error. This study will be used as a resource to improve the user experience that requires deep understanding of financial chatbot users who should consider both the emotional element of artificial intelligence that provides services through natural conversation and the functional elements that perform financial business can be.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.179-193
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• 2023

research on user-friendly experience design is crucial to reduce resistance and enhance acceptance of robotaxis. This study analyzes the prioritization of design factors in robotaxi systems and provides design guidelines based on user experience. Using the AHP(Analytic Hierarchy Process) technique, users' perceived importance of four primary design factors and sixteen 16 sub-design elements were assessed, and comfort and safety were top priorities. The results showed that the artificial intelligence agent was the most critical design factor, followed by driving guidance information, interior design, and exterior design. These findings offer valuable insights for robotaxi professionals, and could assist in informed decision-making and creating user-centered design guidelines.

• Journal of Information Technology Services
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• v.22 no.3
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• pp.141-165
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• 2023

With the advent of the fourth industrial revolution, technologies such as the Internet of Things, artificial intelligence and cloud computing are developing rapidly, and smart homes enabled by these technologies are rapidly gaining popularity. To gain a competitive advantage in the global market, companies must understand the differences in consumer needs in different countries and cultures and develop corresponding business strategies. Therefore, this study conducts a comparative analysis of consumer reviews of smart homes in South Korea and China. This study collected online reviews of SmartThings, ThinQ, Msmarthom, and MiHome, the four most commonly used smart home apps in Korea and China. The collected review data is divided into satisfied reviews and dissatisfied reviews according to the ratings, and topics are extracted for each review dataset using LDA topic modeling. Next, the extracted topics are classified according to five evaluation factors of Perceived Usefulness, Reachability, Interoperability,Trustness, and Product Brand proposed by previous studies. Then, by comparing the importance of each evaluation factor in the two datasets of satisfaction and dissatisfaction, we find out the factors that affect consumer satisfaction and dissatisfaction, and compare the differences between users in Korea and China. We found Trustness and Reachability are very important factors. Finally, through language network analysis, the relationship between dissatisfied factors is analyzed from a more microscopic level, and improvement plans are proposed to the companies according to the analysis results.