• Title/Summary/Keyword: Ai and Data Literacy

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Design to Improve Educational Competency Using ChatGPT

  • Choong Hyong LEE
    • International Journal of Internet, Broadcasting and Communication
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    • v.16 no.1
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    • pp.182-190
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    • 2024
  • Various artificial intelligence neural network models that have emerged since 2014 enable the creation of new content beyond the existing level of information discrimination and withdrawal, and the recent generative artificial intelligences such as ChatGPT and Gall-E2 create and present new information similar to actual data, enabling natural interaction because they create and provide verbal expressions similar to humans, unlike existing chatbots that simply present input content or search results. This study aims to present a model that can improve the ChatGPT communication skills of university students through curriculum research on ChatGPT, which can be participated by students from all departments, including engineering, humanities, society, health, welfare, art, tourism, management, and liberal arts. It is intended to design a way to strengthen competitiveness to embody the practical ability to solve problems through ethical attitudes, AI-related technologies, data management, and composition processes as knowledge necessary to perform tasks in the artificial intelligence era, away from simple use capabilities. It is believed that through creative education methods, it is possible to improve university awareness in companies and to seek industry-academia self-reliant courses.

A Case Study of the Use of Artificial Intelligence in a Problem-Based Learning Program for the Prevention of School Violence (학교폭력 예방을 위한 가정과 AI 기반 문제중심학습 수업 사례연구)

  • Jae Young Shim;Saeeun Choi
    • Human Ecology Research
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    • v.61 no.1
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    • pp.15-28
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    • 2023
  • The aim of this study was to develop, implement, and evaluate the use of Artificial Intelligence in the prevention of violence among middle-school students. The sample for this study consisted of 20 first-year middle-school students who participated in theme selection activities in a free semester program as part of their home economics studies. The data for the study consisted of nine class observation logs, four group activity outputs, 30 class results, an online survey, and in-depth interviews with three students. A program called "R.U.OK" was developed by setting problematic situation for school violence prevention linked to the contents of the Home Economics Education(HEE) curriculum. After the program was implemented, the survey on the students' class satisfaction content elements, with AI-based learning activities and PBL and interest, displayed high points, with an average of 4.0 or higher. Our qualitative analysis produced four significant results. First, students' concerns about school violence had increased and they showed a change in attitude, having more empathy with friends and more interest in their surroundings. Second, digital and AI literacy had improved, and students' interest in digital media learning had increased. Third, there had been an improvement in problem-solving ability in terms of being able to think more critically and independently. Fourth, the results also demonstrated that there had been a positive effect on self-direction and an improved capacity for teamwork. This study was significant in demonstrating the effectiveness of a program for the prevention of school violence based on the use of digital technology in the educational environment.

A Study on ARCS-DEVS-based Programming Learning Methods for SW/AI Basic Liberal Arts Education for Non-majors (비전공자 대상 SW/AI 기초 교양 교육을 위한 ARCS-DEVS 모델 기반의 프로그래밍 학습방법 연구)

  • Han, Youngshin
    • Journal of Korea Multimedia Society
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    • v.25 no.2
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    • pp.311-324
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    • 2022
  • In this paper, we adjusted the feedback and learning materials for each learning based on ARCS motivation which applied DEVS methodology. We designed the ARCS professor-student model that expresses the continuous change in the student's attitude toward the class according to the student's attention, relevance, confidence, and satisfaction. It was applied to computational thinking and data analysis classes Based on the designed model. Before and after class, the students were asked the same question and then analyzed for each part of the ARCS. It was observed that students' perceptions of Attention, Relevance, and Satisfaction were improved except for Confidence. we observed that the students themselves felt that they lacked a lot of confidence compared to other ARS through the analysis. Although, Confidence showed a 13.5% improvement after class but it was about 33% lower than the average of other ARS. However, when it was observed that students' self-confidence was 30% lower than other motivational factors it was confirmed that the part that leads C to a similar level in other ARS is necessary.

Research on a statistics education program utilizing deep learning predictions in high school mathematics (고등학교 수학에서 딥러닝 예측을 이용한 통계교육 프로그램 연구)

  • Hyeseong Jin;Boeuk Suh
    • The Mathematical Education
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    • v.63 no.2
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    • pp.209-231
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    • 2024
  • The education sector is undergoing significant changes due to the Fourth Industrial Revolution and the advancement of artificial intelligence. Particularly, the importance of education based on artificial intelligence is being emphasized. Accordingly, the purpose of this study is to develop a statistics education program using deep learning prediction in high school mathematics and to examine the impact of such statistically problem-solvingcentered statistics education programs on high school students' statistical literacy and computational thinking. To achieve this goal, a statistics education program using deep learning prediction applicable to high school mathematics was developed. The analysis revealed that students' understanding of context improved through experiencing how data was generated and collected. Additionally, they enhanced their comprehension of data variability while exploring and analyzing various datasets. Moreover, they demonstrated the ability to critically analyze data during the process of validating its reliability. In order to analyze the impact of the statistics education program on high school students' computational thinking, a paired sample t-test was conducted, confirming a statistically significant difference in computational thinking between before and after classes (t=-11.657, p<0.001).

A Study on Artificial Intelligence Ethics Perceptions of University Students by Text Mining (텍스트 마이닝으로 살펴본 대학생들의 인공지능 윤리 인식 연구)

  • Yoo, Sujin;Jang, YunJae
    • Journal of The Korean Association of Information Education
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    • v.25 no.6
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    • pp.947-960
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    • 2021
  • In this study, we examine the AI ethics perception of university students to explore the direction of AI ethics education. For this, 83 students wrote their thoughts about 5 discussion topics on online bulletin board. We analyzed it using language networks, one of the text mining techniques. As a result, 62.5% of students spoke the future of the AI society positively. Second, if there is a self-driving car accident, 39.2% of students thought it is the vehicle owner's responsibility at the current level of autonomous driving. Third, invasion of privacy, abuse of technology, and unbalanced information acquisition were cited as dysfunctions of the development of AI. It was mentioned that ethical education for both AI users and developers is required as a way to minimize malfunctions, and institutional preparations should be carried out in parallel. Fourth, only 19.2% of students showed a positive opinion about a society where face recognition technology is universal. Finally, there was a common opinion that when collecting data including personal information, only the part with the consent should be used. Regarding the use of AI without moral standards, they emphasized the ethical literacy of both users and developers. This study is meaningful in that it provides information necessary to design the contents of artificial intelligence ethics education in liberal arts education.

A Study on Development and Effectiveness of the Indicatives for Analysis of the Effects of a Book Sharing Project on pre-schoolers of Supporter' Reading Care in Gyeonggi-do (경기도 책꾸러미 사업을 통한 양육자의 독서육아 효과 분석을 위한 지표개발 및 효과성 연구)

  • Choi, In-Ja;Yoon, Sung-Une;Kim, Soo-Kyoung;Hoang, Gum-Sook;Lee, Sun-Ai
    • Journal of the Korean Society for Library and Information Science
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    • v.56 no.2
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    • pp.133-155
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    • 2022
  • The purpose of this study was to develop the indicatives for the analysis of the effects of Gyeonggi-do Book Sharing Project on pre-schoolers of supporter' reading care and thereby, suggest some data useful to the establishment of a reading culture promotion policy in Gyeonggi-do. Preceding studies and cases were reviewed to analyze the effects of the book-sharing project on pre-schoolers of supporter' reading care and thereby, develop some measurement indicatives, and thus, the indicatives were verified by professionals using the Delphi technique. Then, supporter of 3~5 year-old pre-schoolers were sampled from 7 cities and counties in Gyeonggi-do (Pocheon-si, Yangpyeong-gun, Yeoju-si, Dongducheon-si, Gapyeong-gun, Yeoncheon-gun and Yangju-si) to be divided into control and test groups and thereby, their reading care effect indicatives were compared before and after the test. The theoretical background is theory of family literacy, emergent literacy and parenting efficacy. As a result of developing the indicatives for analysis of pre-schoolers of supporter's reading care effects and comparing them for the sample pre-schoolers of supporter, before and after the test, the book-sharing project was found effective in improving reading care. The most difficult problem in pre-schoolers' earlier reading education involves acquisition of reading habit. So, it is deemed necessary to operate a regular book sharing project involving public organization and homes. As a result of developing the indicatives and analyzing the effects of the book-sharing project, it was confirmed that the project would serve to improve pre-schoolers of support's reading care and therefore, this study seems to provide some ground for the operation of a sustainable book-sharing project to narrow the education divide and promote a book reading culture in Gyeonggi-do.

Design and Application of Artificial Intelligence Experience Education Class for Non-Majors (비전공자 대상 인공지능 체험교육 수업 설계 및 적용)

  • Su-Young Pi
    • Journal of Practical Engineering Education
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    • v.15 no.2
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    • pp.529-538
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    • 2023
  • At the present time when the need for universal artificial intelligence education is expanding and job changes are being made, research and discussion on artificial intelligence liberal arts education for non-majors in universities who experience artificial intelligence as part of their job is insufficient. Although artificial intelligence education courses for non-majors are being operated, they are mainly operated as theory-oriented education on the concepts and principles of artificial intelligence. In order to understand the general concept of artificial intelligence for non-majors, it is necessary to proceed with experiential learning in parallel. Therefore, this study designs artificial intelligence experiential education learning contents of difficulty that can reduce the burden of artificial intelligence classes with interest in learning by considering the characteristics of non-majors. After, we will examine the learning effect of experiential education using App Inventor and the Orange artificial intelligence platform. As a result of analysis based on the learning-related data and survey data collected through the creation of AI-related projects by teams, positive changes in the perception of the need for AI education were found, and AI literacy skills improved. It is expected that it will serve as an opportunity for instructors to lay the groundwork for designing a learning model for artificial intelligence experiential education learning.

Design and Application of App-Inventor-Software Class using Artificial Intelligence (인공지능을 활용한 앱인벤터 소프트웨어 교육 수업 설계 및 적용)

  • Park, Mi Hee;Hu, Kyeong
    • 한국정보교육학회:학술대회논문집
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    • 2021.08a
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    • pp.13-23
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    • 2021
  • This study requires SW education that can adapt to the advent of the fourth industrial revolution and the new normal environment of COVID-19 pandemic. Small and powerful smartphones, which have become a necessity in digital society, are designed and applied to create apps with useful apps or artificial intelligence modules that have been trained with data using the App Inventor program as a good teaching tool. After conducting the class in a blended method that combines face-to-face and non-face methods, the survey questioned the technical and cognitive maturity of artificial intelligence and the pros and cons of blended software classes. We also found changes in career orientation, which is intended to explore SW-related talent occupations that require a lot of demand in terms of national development before and after artificial intelligence classes. Significant results were reached in three of the sub-elements. Even in non-face-to-face situations, it is expected that an app vendor software education program using artificial intelligence will be provided to the actual site.

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Guidelines for big data projects in artificial intelligence mathematics education (인공지능 수학 교육을 위한 빅데이터 프로젝트 과제 가이드라인)

  • Lee, Junghwa;Han, Chaereen;Lim, Woong
    • The Mathematical Education
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    • v.62 no.2
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    • pp.289-302
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    • 2023
  • In today's digital information society, student knowledge and skills to analyze big data and make informed decisions have become an important goal of school mathematics. Integrating big data statistical projects with digital technologies in high school <Artificial Intelligence> mathematics courses has the potential to provide students with a learning experience of high impact that can develop these essential skills. This paper proposes a set of guidelines for designing effective big data statistical project-based tasks and evaluates the tasks in the artificial intelligence mathematics textbook against these criteria. The proposed guidelines recommend that projects should: (1) align knowledge and skills with the national school mathematics curriculum; (2) use preprocessed massive datasets; (3) employ data scientists' problem-solving methods; (4) encourage decision-making; (5) leverage technological tools; and (6) promote collaborative learning. The findings indicate that few textbooks fully align with these guidelines, with most failing to incorporate elements corresponding to Guideline 2 in their project tasks. In addition, most tasks in the textbooks overlook or omit data preprocessing, either by using smaller datasets or by using big data without any form of preprocessing. This can potentially result in misconceptions among students regarding the nature of big data. Furthermore, this paper discusses the relevant mathematical knowledge and skills necessary for artificial intelligence, as well as the potential benefits and pedagogical considerations associated with integrating technology into big data tasks. This research sheds light on teaching mathematical concepts with machine learning algorithms and the effective use of technology tools in big data education.

A Study on the production of Music Content Using Artificial Intelligence Composition Program (인공지능 작곡 프로그램을 활용한 음악 콘텐츠 제작 연구)

  • Park, Dahae
    • Trans-
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    • v.13
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    • pp.35-58
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    • 2022
  • This study predicts the paradigm shift that the development of artificial intelligence technology will bring to the production of music content, and suggests that works created through collaboration between artificial intelligence and humans can have artistic value as finished products. Anyone can easily produce music content using artificial intelligence composition programs, and it has become an opportunity to inspire artists with various attempts and creative ideas. Although artificial intelligence technology provides convenience in human life and benefits a lot in the efficient aspect of work, it is difficult to escape the perception of data-based pattern music in the art field so far. Pattern music with many quantitative elements is not recognized as a complete creation due to the absence of abstract symbolism or meaning pursued by art. However, it predicts that if qualitative elements such as emotions and creativity are given to artificial intelligence music through human collaboration, it can be recognized as a complete work of art. The development of artificial intelligence technology increases access to culture and art from the public, and it can be expected that anyone can enjoy it as well as aesthetic experiences. In addition, various contents can be produced by improving individual digital literacy, and it is an opportunity to share and communicate with others. As such, artificial intelligence technology serves as a medium connecting the public with culture and art, and is narrowing the gap between humans and technology through art activities. Along with this cultural phenomenon, we predict the possibility of research on the production of artificial intelligence music contents with artistic value and the development of various convergence and complex art contents using artificial intelligence technology in the future.