• The Journal of Economics, Marketing and Management
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• v.11 no.6
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• pp.1-8
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• 2023

Purpose: In the era of the Fourth Industrial Revolution, individuals equipped with fundamental understanding and practical skills in artificial intelligence (AI) are essential. This study aimed to validate the effectiveness of AI education for enhancing AI literacy among business major student. Research design, data and methodology: Data for analyzing the effectiveness of the AI Fundamental Education Program for business major students were collected through surveys conducted at the beginning and end of the semester. Structural equation modeling was employed to perform basic statistical analyses regarding gender, grade, and prior software (SW) education duration. To validate the effectiveness of AI education, seven variables - AI interest, AI perception, data analysis/utilization, AI projects, AI literacy, AI self-efficacy, and AI learning persistence - were defined and derived. Results: All seven operationally defined variables showed statistically significant positive changes. The average differences were observed as follows: 0.47 for AI interest, 0.32 for AI perception, 0.37 for data analysis/utilization, 0.27 for AI projects, 0.25 for AI literacy, 0.39 for AI self-efficacy, and 0.41 for AI learning persistence. Statistically, AI interest exhibited the most substantial average difference. Conclusions: Through this study, the applied AI education was confirmed to enhance learners' overall competencies in AI, proving its utility and effectiveness in AI literacy education for business major students. Future research endeavors should build upon these results, focusing on ongoing studies related to AI education programs tailored to learners from diverse academic backgrounds and conducting continuous efficacy evaluations.

• The Mathematical Education
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• v.62 no.3
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• pp.401-416
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• 2023

This study systematically examined the influence of preservice teachers' self-efficacy and AI anxiety, on the intention to use AI programs 'knock-knock! mathematics expedition' in mathematics lessons based on a technology acceptance model. The research model was established with variables including self-efficacy, AI anxiety, perceived ease of use, perceived usefulness, and intention of use from 254 pre-service teachers. The structural relationships and direct and indirect effects between these variables were examined through structural equation modeling. The results indicated that self-efficacy significantly affected perceived ease of use, perceived usefulness, and intention to use. In contrast, AI anxiety did not significantly influence perceived ease of use and perceived usefulness. Perceived ease of use significantly affected perceived usefulness and intention to use and perceived usefulness significantly affected intention to use. The findings offer insights and strategies for encouraging the use of 'knock-knock! mathematics expedition' by preservice teachers in mathematics lessons.

• The Journal of Information Systems
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• v.32 no.4
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• pp.189-210
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• 2023

Purpose This study aims to investigate factors that positively influence the continuous Artificial Intelligence(AI) Learning Continuity of business major students. Design/methodology/approach To evaluate the impact of AI education, a survey was conducted among 119 business-related majors who completed a software/AI course. Frequency analysis was employed to examine the general characteristics of the sample. Furthermore, factor analysis using Varimax rotation was conducted to validate the derived variables from the survey items, and Cronbach's α coefficient was used to measure the reliability of the variables. Findings Positive correlations were observed between business major students' AI Learning Continuity and their AI Interest, AI Awareness, and Data Analysis Capability related to their majors. Additionally, the study identified that AI Project Awareness and AI Literacy Capability play pivotal roles as mediators in fostering AI Learning Continuity. Students who acquired problem-solving skills and related technologies through AI Projects Awareness showed increased motivation for AI Learning Continuity. Lastly, AI Self-Efficacy significantly influences students' AI Learning Continuity.

• Journal of Digital Convergence
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• v.19 no.9
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• pp.201-207
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• 2021

As artificial intelligence gradually expands into jobs, iIt is necessary to nurture talents with AI literacy capabilities required for non-majors. Therefore, in this study, based on the necessity and current status of AI education, AI literacy competency improvement education was conducted for non-majors so that AI learning could be sustainable in relation to future majors. For non-majors at University D, problem-solving solutions through project-based data analysis and visualization were applied over 15 weeks, and the AI ability improvement and effectiveness of learners before and after education were analyzed and verified. As a result, it was possible to confirm a statistically significant level of positive change in the learners' data analysis and utilization ability, AI literacy ability, and AI self-efficacy. In particular, it not only improved the learners' ability to directly utilize public data to analyze and visualize it, but also improved their self-efficacy to solve problems by linking this with the use of AI.

• 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.

• Journal of the Korean Society for information Management
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• v.41 no.1
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• pp.439-463
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• 2024

Recently, there has been a growing demand for school libraries to take on the role of curriculum convergence and content development. This study purposed to develop a program that integrates reading activities and artificial intelligence (AI) education in a middle school library as a platform for convergence education. The program aimed to enhance creative problem-solving skills by integrating an understanding of AI concepts and principles through reading activities related to AI topics. The program, comprising 18 sessions (6 modules), was implemented with 36 first-year students at A Middle School, Gyeonggi-do, in 2022. After implementation, a paired-sample t-test revealed significant improvements in AI learning self-efficacy and creative problem-solving skills. Participants also showed positive attitudes toward class engagement and reading activities. Implications for AI convergence education in connection with school libraries were discussed.

• Journal of the Korean Chemical Society
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• v.68 no.3
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• pp.160-175
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• 2024

The purpose of this study is to examine the effects of a Chemistry I class based on an artificial intelligence (AI) classification model. To achieve this, the research investigated the development and application of a class utilizing an AI classification model in Chemistry I classes conducted at D High School in Gyeongbuk during the first semester of 2023. After selecting the curriculum content and AI tools, and determining the curriculum-AI integration education model as well as AI hardware and software, we developed detailed activities for the program and applied them in actual classes. Following the implementation of the classes, it was confirmed that students' self-efficacy improved in three aspects: chemistry concept formation, AI value perception, and AI-based maker competency. Specifically, the chemistry classes based on text and image classification models had a positive impact on students' self-efficacy for chemistry concept formation, enhanced students' perception of AI value and interest, and contributed to improving students' AI and physical computing abilities. These results demonstrate the positive impact of the Chemistry I class based on an AI classification model on students, providing evidence of its utility in educational settings.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.67-73
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• 2023

The Digital Age calls for improvement of information literacy particularly among children and youth who are vulnerable to cybergrooming. Taking an interdisciplinary approach by leveraging our team's expertise including child and adolescent development, data analytics, and cybersecurity, this study proposes an interactive artificial intelligence (AI)-based preventive simulation program that raises youth knowledge and awareness about the risk of cybergrooming as well as increases resilient self-efficacy in their cybersecurity-relevant skills. The primary purpose of this project is to evaluate the effectiveness of the simulation program on preventing cybergrooming. More specifically, this study is designed to examine developmental changes in self-efficacy of cybersecurity-relevant skills among youth participants as a function of the preventive simulation program. Further, this study will identify risk and protective factors that explain interindividual differences in the ability of children and youth either to fall victim to advances from a cyber predator or to recognize and deter such threats. The preliminary data will help improve the effectiveness of the preventive simulation program as well as the methods of implementation to large groups of youth. The findings from the proposed study will contribute to making specific recommendations to parents, educators, practitioners, and policy makers for the prevention of cybergrooming.

• Journal of Digital Convergence
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• v.19 no.7
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• pp.227-236
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• 2021

This study aims to develop an AI education program for secondary school students to help understand AI and to provide an experience of solving real-life problems by using AI, and to analyze the effectiveness of education. The education program based on the AI education system for K-12 developed in the previous study was composed of a total of 12 lessons by selecting the self-driving cars, which is emerging as a recent issue among real life problems, as the main topic. Classes were conducted for secondary school students who had experience in software education, and the effectiveness of education and class satisfaction were analyzed. As a result of the analysis, it was confirmed that the understanding of AI and the sense of AI efficacy were improved, and the class satisfaction was high in all items such as educational content, fun in class, difficulty of class, and interest in AI. Based on these results, implications for AI education for secondary students were proposed.

• Advanced Industrial SCIence
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• v.3 no.1
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• pp.37-50
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• 2024

This study explored the link between reproductive health knowledge, attitudes, and self-efficacy in young women from Uganda's Luwero district. A survey was conducted on 82 women in the Luwero region from May to July 2016, and the predictive power of knowledge and attitudes toward self-efficacy was evaluated through multiple linear regression analysis. Results showed positive correlations among these factors, with knowledge and attitude predicting self-efficacy. Specifically, understanding healthy puberty habits and valuing women's roles positively influenced self-efficacy for healthy behaviors. These findings emphasize the need to target these aspects in reproductive health education programs, crucial for addressing adolescent pregnancy and related issues in Uganda's rural areas.