• Child Health Nursing Research
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• v.29 no.4
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• pp.290-299
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• 2023

Purpose: Artificial intelligence (AI) has had a profound impact on humanity; in particular, chatbots have been designed for interactivity and applied to many aspects of daily life. Chatbots are also regarded as an innovative modality in nursing education. This study aimed to identify nursing students' awareness of using chatbots and factors influencing their usage intention. Methods: This study, which employed a descriptive design using a self-reported questionnaire, was conducted at three university nursing schools located in Seoul, South Korea. The participants were 289 junior and senior nursing students. Data were collected using self-reported questionnaires, both online via a Naver Form and offline. Results: The total mean score of awareness of using chatbots was 3.49±0.61 points out of 5. The mean scores of the four dimensions of awareness of using chatbots were 3.37±0.60 for perceived value, 3.66±0.73 for perceived usefulness, 3.83±0.73 for perceived ease of use, and 3.36±0.87 for intention to use. Significant differences were observed in awareness of using chatbots according to satisfaction with nursing (p<.001), effectiveness of using various methods for nursing education (p<.001), and interest in chatbots (p<.001). The correlations among the four dimensions ranged from .52 to .80. In a hierarchical regression analysis, perceived value (β=.45) accounted for 60.2% of variance in intention to use. Conclusion: The results suggest that chatbots have the potential to be used in nursing education. Further research is needed to clarify the effectiveness of using chatbots in nursing education.

• Journal of the Korea Society of Computer and Information
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• v.29 no.7
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• pp.53-71
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• 2024

Generative Artificial Intelligence (AI) has become the focus of societal attention due to its wide range of applications and profound impact. This paper constructs a comprehensive theoretical model based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), integrating variables such as Personal Innovativeness and Perceived Risk to study the key factors influencing enterprises' adoption of Generative AI. We employed Structural Equation Modeling (SEM) to verify the hypothesized paths and used the Bootstrapping method to test the mediating effect of Behavioral Intention. Additionally, we explored the moderating effect of Perceived Risk through Hierarchical Regression Analysis. The results indicate that Performance Expectancy, Effort Expectancy, Social Influence, Price Value, and Personal Innovativeness have significant positive impacts on Behavioral Intention. Behavioral Intention plays a significant mediating role between these factors and Use Behavior, while Perceived Risk negatively moderates the relationship between Behavioral Intention and Use Behavior. This study provides theoretical and empirical support for how enterprises can effectively adopt Generative AI, offering important practical implications.

• The Journal of the Korea Contents Association
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• v.19 no.9
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• pp.1-10
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• 2019

The purpose of this study is to investigate the influence of exogenous variables on the intention to use AI speaker. An online survey was administrated to 305 AI speaker users in order to examine the effect of the personal characteristics (self-efficacy, innovativeness, suitability, and enjoyment) and social impact (social conformity and social image) on perceived usefulness and easiness. The results indicate that (1) self-efficacy and social conformity have positively effect on perceived easiness; (2) suitability and social image have positively effect on perceived usefulness whereas innovativeness has negatively effect on perceived usefulness; (3) perceived usefulness and perceived easiness have significant effect on the intention to use AI speaker.

• Electronics and Telecommunications Trends
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• v.35 no.5
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• pp.92-101
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• 2020

Artificial intelligence (AI) has become the hottest topic in information and communications technology (ICT) in recent years. Along with the advancement of AI technology, technologies such as big data, cloud, and high-speed wired and wireless communication are being applied to existing media areas in earnest, affecting all parts of the media value chain from content production to consumption. AI technology is now spreading across the media industry faster than any other industry. In the future, the gap between those with and without AI technology will widen, further deepening the polarization of the media ecosystem. Media intelligence, which combines media and AI technologies, is now perceived as essential, not optional. In this paper, we examine the current status of technology development and standardization by major domestic and foreign institutions on how AI is being utilized in the media industry. In addition, we discuss what technology should be developed to lead media intelligence.

• Korean Journal of Childcare and Education
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• v.19 no.2
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• pp.43-59
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• 2023

Objective: This study investigated the differences in preschool children's perceptions of artificial intelligence (AI) and their distribution by latent profiles according to their experience with AI robots in daycare centers. Methods: The participants included 119 five-year-old children, 52 of whom had experience with AI robots in daycare centers and 67 of whom did not. Children's perceptions of AI were measured using the Godspeed scale from Bartneck et al.(2009). Data were analyzed using a t-test, latent profile analysis, and chi-square test. Results: The results showed that compared to the inexperienced group, the experienced group reported lower levels of animacy and perceived intelligence of AI robots, indicating higher levels of AI knowledge and understanding. In addition, the experienced group had a higher probability of belonging to the 'machine recognition' type than 'organism recognition' type, although the difference was not statistically significant. Conclusion/Implications: The findings suggest that experience with AI robots in daycare centers can improve children's AI knowledge and understanding. To further enhance this effect, it is necessary to increase the number of robots put into classrooms, and to consider various teaching media that reflect children's preferences.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.2
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• pp.135-145
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• 2023

ChatGPT is an artificial intelligence-based conversation agent developed by OpenAI using natural language processing technology. In this study, an empirical study was conducted on incumbent teachers on the intention to use the newly emerged Chat GPT. First, we studied how accuracy, entertainment, system accessibility, perceived usefulness, and perceived ease of use affect ChatGPT's acceptance intention. In addition, we analyzed whether perceived usefulness and perceived ease of use differ in the intention to accept depending on the digital technology of teachers. As a result of the study, the suitability of the structural equation model was generally good. Accuracy and entertainment were found to have a significant effect on perceived usefulness, and system accessibility was found to have a significant effect on perceived ease of use. In the analysis of teachers' digital technology control effects, it was found that perceived usefulness and perceived ease of use had a control effect between acceptance intentions. It was found that the group with high digital skills of teachers was strongly intended to accept the service regardless of perceived usefulness and ease of use. In the group with low digital skills of teachers, it is thought that ChatGPT's service shows the acceptance intention only when the perceived usefulness and ease of use are high. Therefore, in the group with low digital technology, it is necessary to seek teaching activities such as the development of instructional models using ChatGPT.

• Education of Primary School Mathematics
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• v.26 no.3
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• pp.163-180
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• 2023

This study aimed to investigate the factors influencing the intentions of elementary school teachers to use artificial intelligence (AI) in mathematics lessons and to identify the essential prerequisites for the effective implementation of AI in mathematics education. To achieve this purpose, we examined the structural relationship between elementary school teachers' TPACK(Technological Pedagogical Content Knowledge) and the TAM(Technology Acceptance Model) using structural equation model. The findings of the study indicated that elementary school teachers' TPACK regarding the use of AI in mathematics instruction had a direct and significant impact on their perceived ease of use and perceived usefulness of AI. In other words, when teachers possessed a higher level of TPACK competency in utilizing AI in mathematics classes, they found it easier to incorporate AI technology and recognized it as a valuable tool to enhance students' mathematics learning experience. In addition, perceived ease of use and perceived usefulness directly influenced the attitudes of elementary school teachers towards the integration of AI in mathematics education. When teachers perceived AI as easy to use in their mathematics lessons, they were more likely to recognize its usefulness and develop a positive attitude towards its application in the classroom. Perceived ease of use, perceived usefulness, and attitude towards AI integration in mathematics classes had a direct impact on the intentions of elementary school teachers to use AI in their mathematics instruction. As teachers perceived AI as easy to use, valuable, and developed a positive attitude towards its incorporation, their intention to utilize AI in mathematics education increased. In conclusion, this study shed light on the factors influencing elementary school teachers' intentions to use AI in mathematics classes. It revealed that teachers' TPACK plays a crucial role in facilitating the integration of AI in mathematics education. Additionally, the study emphasized the significance of enhancing teachers' awareness of the advantages and convenience of using AI in mathematics instruction to foster positive attitudes and intentions towards its implementation. By understanding these factors, educational stakeholders can develop strategies to effectively promote the utilization of AI in mathematics education, ultimately enhancing students' learning outcomes.

• Journal of Gifted/Talented Education
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• v.24 no.5
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• pp.877-892
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• 2014

This Study was to examine whether high school students' autonomy support and beliefs of intelligence ability influence their self-regulated strategies. Of the 600 high school students surveyed from 3 high schools in two metropolitan cities, Korea, 478 completed and returned the questionnaires yielding a total response rate of 79.7%. Among the final sample consisted of 109 gifted students (22.8%), 190 high-achieving non-gifted students (39.7%), and low-achieving non-gifted students (37.4%). Measures of students' perceived autonomy support (i.e. from parents, teacher, peer), beliefs of intelligence ability (i.e. incremental, entity) and self-regulated strategies (i.e. managing environment and behavior, seeking and learning information, maladaptive regulatory behavior). Spearman's rho(${\rho}$) indicated that students' achieving level was positively associated with autonomy support (i.e. parents, teacher), beliefs of intelligence ability (i.e. incremental) and self-regulated strategies (i.e. managing environment and behavior, seeking and learning information). However, students' achieving level was negatively associated with beliefs of intelligence ability (i.e. entity) and self-regulated strategies (i.e. maladaptive regulatory behavior). Hierarchical multiple regression analyses showed that students' perceived autonomy support (i.e. from teacher) and beliefs of intelligence ability (i.e. incremental) were the crucial contributors for enhancing students' self-regulated strategies. Results are discussed in relation to theoretical implications and school settings.

• Electronics and Telecommunications Trends
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• v.35 no.7
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• pp.13-22
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• 2020

There is no denying that computing power has been a crucial driving force behind the development of artificial intelligence today. In addition, artificial intelligence (AI) semiconductors and computing systems are perceived to have promising industrial value in the market along with rapid technological advances. Therefore, success in this field is also meaningful to the nation's growth and competitiveness. In this context, ETRI's AI strategy proposes implementation directions and tasks with the aim of strengthening the technological competitiveness of AI semiconductors and computing systems. The paper contains a brief background of ETRI's AI Strategy #2, research and development trends, and key tasks in four major areas: 1) AI processors, 2) AI computing systems, 3) neuromorphic computing, and 4) quantum computing.

• Knowledge Management Research
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• v.19 no.4
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• pp.99-118
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• 2018

Recently, individuals are interested in a variety of products and services based on artificial intelligence. Among those products and services, an intelligent personal assistants are attracting many attention from IT companies as a next generation platform. Thus, the main purpose of this study is to investigate effects of intelligent personal assistant's benefits on user's value formation and adoption behavior based on Value-based Adoption Model. In addition, the moderating effect of personal innovativeness is examined through empirical analysis. Based on the analysis with the data from actual users, the results show that usefulness, enjoyment, technicality and cost advantage have significant influences on perceived value and correspondingly have an effect on intention to adopt. Personal innovativeness is related to the relationship between perceived value and intention to adopt. These findings may provide important insights to the relevant field regarding the use and spread of intelligent personal assistants.