• Communications of Mathematical Education
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• v.37 no.4
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• pp.717-736
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• 2023

The purpose of this study is to develop a statistical program using data and artificial intelligence prediction models and apply it to one class in the sixth grade of elementary school to see if it is effective in improving students' statistical literacy. Based on the analysis of problems in today's elementary school statistical education, a total of 15 sessions of the program was developed to encourage elementary students to experience the entire process of statistical problem solving and to make correct predictions by incorporating data, the core in the era of the Fourth Industrial Revolution into AI education. The biggest features of this program are the recognition of the importance of data, which are the key elements of artificial intelligence education, and the collection and analysis activities that take into account context using real-life data provided by public data platforms. In addition, since it consists of activities to predict the future based on data by using engineering tools such as entry and easy statistics, and creating an artificial intelligence prediction model, it is composed of a program focused on the ability to develop communication skills, information processing capabilities, and critical thinking skills. As a result of applying this program, not only did the program positively affect the statistical literacy of elementary school students, but we also observed students' interest, critical inquiry, and mathematical communication in the entire process of statistical problem solving.

• Journal of Practical Engineering Education
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• v.16 no.4
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• pp.415-421
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• 2024

This study is a descriptive research study to understand the relationship between nursing professional intuition, artificial intelligence ethics, and digital health literacy of nursing college students. There was no difference in nursing professional intuition, artificial intelligence ethics, and digital health literacy according to the general characteristics of the subject. In addition, nursing professionals were found to have a significant positive correlation with artificial intelligence ethics consciousness and digital health literacy, and artificial intelligence ethics consciousness was found to have a significant positive correlation with digital health literacy. These results can be used as basic data for preparing educational programs that can strengthen digital health literacy capabilities by cultivating artificial intelligence ethics as well as nursing professionals of nursing college students.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.189-196
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• 2023

This paper analyzes the level of satisfaction of two groups of teachers who were educated about artificial intelligence using App Inventor. The participants were 13 pre-service and 9 in-service elementary school teachers and the data was collected using a questionnaire. As a result of the study, in-service teachers were all more satisfied than pre-service teachers in terms of interest, difficulty, and participation in the education. In addition, the questions investigating whether education helped motivate learning of artificial intelligence and whether there is a willingness to apply it to elementary classes in the future were also more positive for in-service teachers than for pre-service teachers. In general, pre-service teachers had somewhat more negative views than in-service teachers, but they were more positive than in-service teachers in terms of whether the education helped improve their understanding of artificial intelligence and whether they were willing to participate in additional education. Analysis of the Mann-Whitney test to see if there was a significant difference in satisfaction between the two groups showed no significance. This may be because most of the students in the two groups already had block-type or text-type programming experience, so they were able to participate in the education without any special resistance or difficulty with App Inventor, resulting in high levels of satisfaction from both groups. The results of this study can provide basic data for the future development and operation of programs for artificial intelligence education for both pre-service and in-service elementary school teachers.

• Journal of the Health Care and Life Science
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• v.11 no.2
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• pp.181-189
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• 2023

The purpose of this study is a descriptive research study to identify factors affecting nursing students' confidence in performing nursing using artificial intelligence and provide evidence for the development of nursing education programs. Data collected from 245 nursing students were conducted using descriptive statistics, t-test, one way ANOVA, Pearson correlation coefficient, and multiple regression analysis using SPSS/WIN 21.0 program. The reliability of the tool was verified using Cronbach's alpha coefficient. As a result of the study, knowledge of artificial intelligence was 2.52 points, awareness was 3.52 points, attitude of acceptance was 3.74 points, and confidence in nursing performance was 5.47 points. The factors affecting confidence in performing nursing using artificial intelligence were knowledge and attitude, with an explanatory power of 50.8%. Based on the results of this study, basic data can be provided for the development of related curriculum and teaching methods in the future.

• Journal of the Health Care and Life Science
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• v.11 no.1
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• pp.67-77
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• 2023

This paper aims as a prior study to cultivate artificial intelligence professionals at the level of colleges in the future by analyzing healthcare services and technologies using artificial intelligence technology. As artificial intelligence technology is recognized as a key engine or core technology in the future that will create national competitiveness and added value, advanced countries are investing a lot of attention and support in developing technologies as well as human resources at the national level. Korea is also promoting national-level R&D manpower training projects such as AI graduate program support projects, and investing heavily in fostering and securing its own artificial intelligence personnel, mainly by large companies, but there is a lack of artificial intelligence experts. This study analyzes the current status of healthcare services and technologies, industries, and artificial intelligence manpower training using artificial intelligence technology, and proposes directions for fostering artificial intelligence personnel at the level of colleges.

• Convergence Security Journal
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• v.24 no.3
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• pp.33-39
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• 2024

The remarkable advancement of artificial intelligence technology is bringing innovative changes to the field of education. In particular, generative AI models like ChatGPT hold great potential in self-directed programming education due to their natural conversational abilities. This study analyzed the learning effects of using ChatGPT in Scratch classes for non-SW majors. Dividing the classes into those using ChatGPT and those not, and conducting the same evaluations and surveys for the ChatGPT-utilizing group, the results showed that ChatGPT significantly enhanced learning outcomes and the utility of ChatGPT was highly evaluated in advanced learning areas such as understanding Scratch's advanced features and algorithms. This study is significant as it empirically demonstrates the potential of generative AI like ChatGPT as an effective tool in programming education.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.3
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• pp.110-115
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• 2021

With the era of the 4th Industrial Revolution, education on artificial intelligence is one of the important topics. However, since existing education is aimed at knowledge, it is not suitable for developing the active problem-solving ability and AI utilization ability required by artificial intelligence education. To solve this problem, we proposes PBL-based education method in which learners learn in the process of solving the presented problem. The problem presented to the learner is a completed project. This project consists of three types: a classification model, the training data of the classification model, and the block code to be executed according to the classified result. The project works, but each component is designed to perform a low level of operation. In order to solve this problem, the learners can expect to improve their computational thinking skills by finding problems in the project through testing, finding solutions through discussion, and improving to a higher level of operation.

• The Journal of the Convergence on Culture Technology
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• v.10 no.5
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• pp.715-723
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• 2024

The purpose of this study was to identify research trends related to future education through keyword network analysis. To this end, 308 academic papers and master's and doctoral dissertations published from 2000 to 2023 in Korea, and 146 keywords were selected for analysis, divided into 5 periods, and used and analyzed with the Microsoft Excel 365 program and NetMiner 4 program. The results of the study are as follows. First, the publication of future education research has steadily increased since 2000, but has increased significantly since the second half of the 2010s, and the number has exploded in 2021. Second, the number of new keywords that emerged in future education research has increased in recent times, but the frequency of 'future society' keywords appearing in all periods has been high. Third, in future education research results, the number of keywords that simultaneously appear among keywords has increased as time passes, and the contents of keywords that simultaneously have changed in various ways. This study is meaningful in that it suggested the direction of future education by analyzing the past and present of future education with artificial intelligence more than 20 years later.

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.61-67
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• 2021

The purpose of this study is to demonstrate how EFL learners can overcome the limitations of traditional classes and practice communication through the learning activity model. As a research method, it was conducted from March to June 2019 to develop and derive strategies and guidelines through model development, validation, and application. After two validity tests, the model was applied to the experimental group, resulting in an increase of self-direction, engagement, problem-solving, and participation. Moreover the post results showed significant results in all fields, the usefulness of this model was confirmed. However, continuous follow-up research is needed, including the development of software that can easily apply AI related to English learning to classes, and the presentation of convergence activities with more systematic maker education in learning activities.

• Journal of The Korean Association of Information Education
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• v.26 no.4
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• pp.249-263
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• 2022

The purpose of this study is to investigate the effects of assessment by adopting adaptive learning in higher education that are rarely examined in previous studies. In particular, this study applied research questions: 1) How does technical perception, perceived contents and features, and perceived integration of the AI-based adaptive system with lecture affect overall satisfaction, overall effectiveness, overall usefulness, overall motivation for the study, and intention to use it with other classes? 2) How do overall satisfaction, overall effectiveness, overall usefulness, motivation for the class, and intention to use affect loyalty on the AI-based adaptive system? This study conducted online surveys after the completion of the classes adopted AI-based adaptive learning system, ALEKS. This study applied ANOVA, regression, and factor analyses. The results of this study found that perceived integration of the AI-based adaptive learning system with the lectures on overall satisfaction, effectiveness, motivation, and intention to use for other classes showed significant with higher effect size. The results of this study provides implication that the AI-based learning system help improve learning outcomes in graduate level studies. The results provide policy and managerial implications that the AI-based adaptive learning system should improve better customer relationships in higher education.