• Title/Summary/Keyword: AI experience

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Research related to the development of an age-friendly convergence system using AI

  • LEE, Won ro;CHOI, Junwoo;CHOI, Jeong-Hyun;KANG, Minsoo
    • Korean Journal of Artificial Intelligence
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    • v.10 no.2
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    • pp.1-6
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    • 2022
  • In this paper, the research and development aim to strengthen the digital accessibility of the elderly by developing a kiosk incorporating AI voice recognition technology that can replace the promotional signage currently being installed and spread in the elderly and social welfare centers most frequently used by the digital underprivileged. It was intended to develop a converged system for the use of bulletin board functions, educational functions, and welfare center facilities, and to seek ways to increase the user's digital device experience through direct experience and education. Through interviews and surveys of senior citizens and social welfare centers, it was intended to collect problems and pain Points that the elderly currently experience in the process of using kiosks and apply them to the development process, and improve problems through pilot services. Through this study, it was confirmed that voice recognition technology is 2 to 6 times faster than keyboard input, so it is helpful for the elderly who are not familiar with device operation. However, it is necessary to improve the problem that there is a difference in the accuracy of the recognition rate according to the surrounding environment with noise. Through small efforts such as this study, we hope that the elderly will be a little free from digital alienation.

2023 Survey on User Experience of Artificial Intelligence Software in Radiology by the Korean Society of Radiology

  • Eui Jin Hwang;Ji Eun Park;Kyoung Doo Song;Dong Hyun Yang;Kyung Won Kim;June-Goo Lee;Jung Hyun Yoon;Kyunghwa Han;Dong Hyun Kim;Hwiyoung Kim;Chang Min Park;Radiology Imaging Network of Korea for Clinical Research (RINK-CR)
    • Korean Journal of Radiology
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    • v.25 no.7
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    • pp.613-622
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    • 2024
  • Objective: In Korea, radiology has been positioned towards the early adoption of artificial intelligence-based software as medical devices (AI-SaMDs); however, little is known about the current usage, implementation, and future needs of AI-SaMDs. We surveyed the current trends and expectations for AI-SaMDs among members of the Korean Society of Radiology (KSR). Materials and Methods: An anonymous and voluntary online survey was open to all KSR members between April 17 and May 15, 2023. The survey was focused on the experiences of using AI-SaMDs, patterns of usage, levels of satisfaction, and expectations regarding the use of AI-SaMDs, including the roles of the industry, government, and KSR regarding the clinical use of AI-SaMDs. Results: Among the 370 respondents (response rate: 7.7% [370/4792]; 340 board-certified radiologists; 210 from academic institutions), 60.3% (223/370) had experience using AI-SaMDs. The two most common use-case of AI-SaMDs among the respondents were lesion detection (82.1%, 183/223), lesion diagnosis/classification (55.2%, 123/223), with the target imaging modalities being plain radiography (62.3%, 139/223), CT (42.6%, 95/223), mammography (29.1%, 65/223), and MRI (28.7%, 64/223). Most users were satisfied with AI-SaMDs (67.6% [115/170, for improvement of patient management] to 85.1% [189/222, for performance]). Regarding the expansion of clinical applications, most respondents expressed a preference for AI-SaMDs to assist in detection/diagnosis (77.0%, 285/370) and to perform automated measurement/quantification (63.5%, 235/370). Most respondents indicated that future development of AI-SaMDs should focus on improving practice efficiency (81.9%, 303/370) and quality (71.4%, 264/370). Overall, 91.9% of the respondents (340/370) agreed that there is a need for education or guidelines driven by the KSR regarding the use of AI-SaMDs. Conclusion: The penetration rate of AI-SaMDs in clinical practice and the corresponding satisfaction levels were high among members of the KSR. Most AI-SaMDs have been used for lesion detection, diagnosis, and classification. Most respondents requested KSR-driven education or guidelines on the use of AI-SaMDs.

Development of Artificial Intelligence Education System for K-12 Based on 4P (4P기반의 K-12 대상 인공지능 교육을 위한 교육체계 개발)

  • Ryu, Hyein;Cho, Jungwon
    • Journal of Digital Convergence
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    • v.19 no.1
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    • pp.141-149
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    • 2021
  • Due to the rapid rise of artificial intelligence technology around the world, SW education conducted in elementary and secondary schools is expanding including AI education. Therefore, this study aims to present an AI education system based on 4P(Play, Problem Solving, Product Making, Project) that can be applied from kindergarten to high school. The AI education system presented in this study is designed to be applied in 4P-based Play, Problem Solving, Product Making, and Project 4 stages so that it can be applied by school age and step by step. The level was presented by dividing it into two areas: AI literacy and AI development. In order to verify the validity of the developed AI education system, the Delphi method was applied to 15 experts who had experience in SW education or AI education. The AI education system derived as a result of the verification will be able to contribute to the development of a content system for AI education at each school level in the future.

The Influence of AI Convergence Education on Students' Perception of AI (AI 융합 교육이 초등학생의 AI 인식에 미치는 영향)

  • Lee, Jaeho;Lee, Seunggyu;Lee, Seunghoon
    • Journal of The Korean Association of Information Education
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    • v.25 no.3
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    • pp.483-490
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    • 2021
  • In the era of the fourth industrial revolution, the importance of artificial intelligence(AI) is growing day by day, and there is no disagreement that AI education will bring great innovation in the future. Various attempts are being made to educate the topic of AI, but students who have no experience in AI education recognize AI only as a difficult target. Therefore, in this study, we analyze the changes in students' perception of AI by teaching them using AI. AI convergence education were conducted for 6th grade elementary school students, and pre and post tests were conducted in the form of AI awareness survey questionnaires which included questions such as interest in AI, changes brought by AI, and AI education. As a result, we confirm significant results that suggest the level of awareness of AI has improved through AI education in all factors. AI convergence education requires various AI convergence education programs as a form of education for social needs and future students, and hopefully a design based on this will help realize student centered education.

A Study on the Use of Retailtech and Intention to Accept Technology based on Experiential Marketing (체험마케팅에 기반한 리테일테크 활용과 기술수용의도에 관한 연구)

  • Sangho Lee;Kwangmoon Cho
    • Journal of Internet of Things and Convergence
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    • v.10 no.2
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    • pp.137-148
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    • 2024
  • The purpose of this study is to determine how the use of retailtech technology affects consumers' purchase intention. Furthermore, this study aims to investigate the mediating effects of technology usefulness and ease of use on this influence relationship and whether experiential marketing moderates consumers' purchase intention. The survey was conducted from August 1, 2023 to September 30, 2023, and a total of 257 people participated in the study. For statistical analysis, hierarchical regression analysis, three-stage mediation regression analysis, and hierarchical three-stage controlled regression analysis were conducted to test the hypothesis. The results of the study are as follows. First, it was confirmed that big data-AI utilization, mobile-SNS utilization, live commerce utilization, and IoT utilization affect purchase intention in retail technology utilization. Second, technology usefulness has a mediating effect on IoT utilization, mobile-SNS utilization, and big data-AI utilization. Third, perceived ease of use of technology mediated the effects of IoT utilization, mobile-SNS utilization, live-commerce utilization, and big data-AI utilization. Fourth, escapist experience has a moderating effect on mobile SNS utilization and live commerce utilization. Fifth, esthetic experience has a moderating effect on mobile-SNS utilization and big data-AI utilization. Through this study, we hope that the domestic distribution industry will contribute to national competitiveness by securing the competitive advantage of companies by utilizing new technologies in entering the global market.

A Study on User Switching Intention from Contact Center-oriented to AI Chatbot-Oriented Customer Services (컨택센터 중심에서 인공지능 챗봇 중심 고객 서비스로의 사용자 전환의도에 관한 연구)

  • Ann Seunggyu;Ahn Hyunchul
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.19 no.1
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    • pp.57-76
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    • 2023
  • This study analyzes the factors and effects on the users' intention to switch from contact center-oriented to AI chatbot-oriented customer services by combining Push-Pull-Mooring Model and provides insights for companies considering the adoption of AI chatbots. To test the model, we surveyed users with experience using chatbots at least once across different age groups. Finally, we analyzed 176 cases for the analysis using IBM SPSS Statistics and SmartPLS 4.0. The results of hypotheses testing rejected the hypotheses for variables of inconsistent quality and low availability of push factors and low switching cost of mooring factor while accepting the hypotheses for the tardy response of push factors and all pull factors. Therefore, these findings provide important implications for researchers and practitioners who wish to conduct research or adopt AI chatbots. In conclusion, users do not feel inconvenienced by the contact center-oriented service but also perceive high trust and convenience with AI chatbot-oriented service. However, despite low switching costs, users consider chatbots a complementary tool rather than an alternative. So, companies adopting AI chatbots should consider what features the users expect from AI chatbots and facilitate these features when implementing AI chatbots.

Changes in Perceptions of Science Classes Using Artificial Intelligence among Elementary Teachers Participating in Research School (연구학교 참여 초등교사의 인공지능 활용 과학 수업에 관한 인식 변화)

  • Kim, Tae Ha;Yoon, Hye-Gyoung
    • Journal of Korean Elementary Science Education
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    • v.42 no.3
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    • pp.467-479
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    • 2023
  • For the successful implementation of education using artificial intelligence (AI) in schools, the perception of teachers is important. This study focuses on elementary school teachers and their perception of the need and teaching efficacy of science classes using AI before and after participating in a research school program. The analysis explores four key aspects, namely, learning, teaching, assessment, and communication. The study recruited 24 elementary school teachers from a school designated by the Gangwon Provincial Office of Education to participate in a year-long research school program. The study collected data using pre- and post-program surveys to explore changes in the perception of teachers regarding AI-based science classes. Furthermore, the researchers conducted individual in-depth interviews with four elementary school teachers to investigate the experience factors that influenced the changes in their perception of the aforementioned classes. The main findings were as follows. First, elementary school teachers were positively aware of the need for science classes using AI even prior to their research school experience; this perception remained positive after the research school program. Second, the science teaching efficacy of the elementary school teachers using AI was generally moderate. Even after the research school experience, the study found no statistically significant increase in efficacy in teaching science using AI. Third, by analyzing the necessity-efficacy as quadrants, the study observed that approximately half of the teachers who participated in the research school reported positive changes in learning, teaching, and assessment. Fourth, the study extracted four important experience factors that influenced the perception of the teachers of science classes using AI, namely, personal background and characteristics, personal class practice experience, teacher community activities, and administration and work of school. Furthermore, the study discussed the implications of these results in terms of the operation of research schools and science education using AI in elementary schools.

Application of AI in Marketing Strategy: Insights from Millennials and Generation Z

  • Yooncheong CHO
    • The Journal of Economics, Marketing and Management
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    • v.12 no.1
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    • pp.29-38
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    • 2024
  • Purpose: The purpose of this study is to explore the perceptions of millennials and Generation Z regarding AI applications in marketing, an area that has been rarely explored in previous researches. This study formulated research questions how millennials and Generation Z perceive the impact of brand image, AI-assistant customer service, affective factor, immersive experience, cognitive factor social factor and competitiveness of products and brands on overall attitude through the lens of AI applications in marketing. Additionally, this study also explored the influence of overall attitudes on satisfaction, intention to use, and loyalty towards AI applications. Research design, data and methodology: To gather data, this study employed an online survey conducted in collaboration with a reputable research organization. This study utilized factor analysis, ANOVA, and regression analysis for data analysis. Results: The findings revealed that the impact of brand image, AI-assistant customer service, and competitiveness on attitude demonstrated significance in both millennials and generation Z cohorts. The study identified that cognitive and social factors significantly influenced attitudes among millennials, whereas affective and immersive experiences showed significance in influencing attitudes among Generation Z. Conclusions: The findings offer valuable managerial implications, shedding light on the application of AI in marketing with distinct perspectives between millennials and Generation Z.

Development and Application of AI Education Immersion Course for school autonomous curriculum at Elementary School

  • Soo-Hwan, Lee;Jeong-Rang, Kim
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.1
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    • pp.201-208
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    • 2023
  • As the demand for AI education increases, AI education is actively conducted in the educational field, but it is difficult to internalize AI education due to securing time, difficulty in organizing class contents, and lack of curriculum. As a way to solve this problem, there is a school autonomous course. The school autonomous course allows schools to have autonomy and discretion throughout the curriculum, such as adjusting the number of hours in the subject group and restructuring the use of achievement standards. In this study, in order to enhance AI education, the effect was analyzed by developing and applying an AI education immersion course using a school autonomous curriculum. In the AI education immersion course, students continuously experience AI education in a dense manner within a limited time, so substantial AI education can be achieved. After the AI curriculum, it was found that students' overall AI literacy and self-determination learning motivation improved. It is expected that this study will be able to present a direction to internalize AI education using school autonomous curriculum.

A Study on the Perceptions of SW·AI Education for Elementary and Secondary School Teachers Using Text Mining (텍스트 마이닝을 이용한 초·중등 교사의 SW·AI 교육에 대한 인식 연구)

  • Mihyun Chung;Oakyoung Han;Kapsu Kim;Seungki Shin;Jaehyoun Kim
    • Journal of Internet Computing and Services
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    • v.24 no.6
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    • pp.57-64
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    • 2023
  • This study analyzed the perceptions of elementary and secondary school teachers regarding the importance of SW/AI education in fostering students' fundamental knowledge and the necessity of integrating SW/AI into education. A total of 830 elementary and secondary school teachers were selected as study subjects using the judgment sampling method. The analysis of survey data revealed that elementary and secondary teachers exhibited a strong awareness of the importance and necessity of SW/AI education, irrespective of school characteristics, region, educational experience, or prior involvement in SW and AI education. Nevertheless, the primary reasons for not implementing SW/AI education were identified as excessive workload and a lack of pedagogical expertise. An analysis of opinions on the essential conditions for implementing SW/AI education revealed that workload reduction, budget support, teacher training to enhance teacher competency, content distribution, expansion of subject-linked courses, and dedicated instructional time allocation were the major influencing factors. These findings indicate a significant demand for comprehensive instructional support and teacher capacity-building programs.