• Title/Summary/Keyword: AI & Digital Education

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Development and Validation of Data Science Education Instructional Model (데이터 과학 교육을 위한 수업모형 개발 및 타당성 검증)

  • Bongchul Kim;Bomsol Kim;Jonghoon Kim
    • Journal of The Korean Association of Information Education
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    • v.26 no.5
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    • pp.417-425
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    • 2022
  • The 'Comprehensive Plan for Nurturing Digital Talents' reported at the Cabinet meeting of the Ministry of Education in August 2022 focuses on qualitative and quantitative expansion of informatics education centered on SW, AI education. With the advent of the era of artificial intelligence, data science education is also drawing attention as a field of informatics education. Data science is originally a field where various studies are fused, and advanced technologies are being used for data analysis, modeling, and machine learning. This study devised a draft of the instructional model of data science education through literature research and analysis of previous studies, and developed a final instructional model through usability test and expert validation.

Research on Improving the Performance of Image based Web Structure Similarity: Combining SSIM and ORB algorithms

  • Seo-Hyuck Lee;Jin-san Kim;Jung-Hwan Kim;Hanjin Lee
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.11
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    • pp.1-10
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    • 2024
  • This study aims to establish a standard to accurately determine the similarity of the results when web pages are generated automatically using AI technology due to the explosive increase in demand for digital business. The YOLO, SSIM, Jaccard, and ORB techniques presented in previous studies related to the existing image similarity evaluation index generally focused on the partial and morphological similarity between the reference and the derived image. However, with the development of more complex and in-depth digital services based on generative AI, the need for comprehensive similarity analysis and determination methods that reflect the context and structure has emerged. Accordingly, this study proposed and verified a method to obtain 'Web Structural Similarity (WSS)' by combining the advantages of SSIM and ORB prior techniques. The research will serve various meaningful implications.

The Effectiveness of Collaborative Learning in SW Education based on Metaverse Platform (메타버스 기반 협력적 소통 SW 교육 프로그램의 효과)

  • Son, Jungmyoung;Lee, Sihoon;Han, Jeonghye
    • Journal of The Korean Association of Information Education
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    • v.26 no.1
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    • pp.11-22
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    • 2022
  • The educational environment, where the change to blended learning and AI convergence education through non-face-to-face is accelerating, is based on the cultivation of digital literacy. This study attempted to verify the effectiveness of future competencies by creating a collaborative SW education program on the metaverse platform that emerged by supplementing the problems through non-face-to-face. Twenty programs on how to design and create software were organized for small-scale elementary classes in the metaverse. In order to verify the effectiveness 4C competency tool presented as future educational competency was selected, and homogeneity test for the experimental group and t-test were conducted. The results showed the SW education programs based on metaverse was effective in improving collaborative communication skills, confirming the possibility of SW education through blended learning.

Impact of Moral Intensity on Moral Behavior in the context of Artificial Intelligence: The Mediating Role of Technology Moral Sense

  • Wen Wu;Xiuqing Huang;Seth Y. Ntim;Yue Shen;Xinyu Li;GuoPeng Wang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.6
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    • pp.1583-1598
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    • 2024
  • With the popularization and application of artificial intelligence technology in daily life, new ethical and moral problems constantly appear in human society. These ethical and moral problems have been associated with people's moral behavior and have become crucial issues. In traditional social situations, researches have proved that moral intensity affects people's moral behavior. However, in the context of applying artificial intelligence technology, the mechanism between moral intensity and moral behavior is unknown. Therefore, this study focuses on the relationship between moral intensity and moral behavior in the context of applying artificial intelligence technology, and introduces a new concept - technology moral sense (TMS) into the theoretical model. Research method: We set various situations of applying artificial intelligence technology and adopt the situational experiment method to analyze the relationship between moral intensity and moral behavior in different application scenarios. The results show that moral intensity has a significant influence on moral behavior, while the technology moral sense performs a mediating function.

The Impact of Usefulness, Ease of Use, and Satisfaction with ChatGPT on the Intention to Use (ChatGPT의 유용성, 용이성, 만족도가 수용 의도에 미치는 영향)

  • Park Hyejin
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.20 no.3
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    • pp.61-70
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    • 2024
  • This study aimed to analyze the impact of perceived usefulness, ease of use, and satisfaction with ChatGPT on the intention to use it. Data were collected through an online survey, and the results showed differences in perceived usefulness, ease of use, and intention to use according to the demographic characteristics of the research subjects. Furthermore, a multiple regression analysis was conducted to examine the impact of ChatGPT's usability, ease of use, and satisfaction on the intention to use. The results indicated statistically significant differences in perceived usefulness, ease of use, and intention to use ChatGPT between students in different academic years. In addition, perceived usefulness, ease of use, and satisfaction with ChatGPT showed a significant positive influence on the intention to use it. This study is significant as it analyzes the intention to use ChatGPT, considering the role of generative AI in digital education and innovative teaching methods in the educational context.

Special Topic: The Impact of ChatGPT in Society, Business, and Academia

  • Kyoung Jun Lee;Taeho Hong;Hyunchul Ahn;Taekyung Kim;Chulmo Koo
    • Asia pacific journal of information systems
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    • v.33 no.4
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    • pp.957-976
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    • 2023
  • ChatGPT has had a significant impact on society, business, and academia by influencing individuals and organizations through knowledge generation and supporting users in locating conversational inquiries and answers. It can transform how people seek answers by combining human-like conversational skills with AI. By eradicating the cumbersome process of selecting from multiple options, users can conduct preliminary research or create optimized solutions. The purpose of this research is to investigate how consumers use ChatGPT and digital transformation, specifically in terms of knowledge development, searching and recommending, and optimizing accessible possibilities. Using many linked theories, we address the potential implications and insights that can be gained from ChatGPT's early stages and its integration with other applications such as robotics, service automation, and the metaverse. Finally, the application of ChatGPT has practical, theoretical, and phenomenological impacts, in addition to improving users' experiences.

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.

Exploration of Teacher Pedagogical Content Knowledge (PCK) and Teacher Educator PCK Characteristics in Future School Science Education

  • Youngsun Kwak;Kyu-dohng Cho
    • Journal of the Korean earth science society
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    • v.44 no.4
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    • pp.331-341
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    • 2023
  • The goal of this study was to examine the PCK required for science teachers and PCK required for university teacher educators in terms of school science knowledge, science teaching and learning, and the role of science educators, which are the main axes of science education in future schools, and to explore the relationship between them. This study is a follow-up to a previous stage of research that explored the prospects for changes in schools in the future (2040-2050) in terms of school knowledge, educational methods, and teacher roles. Based on in-depth interviews, qualitative and semantic network analyses were conducted to derive and compare the characteristics of PCK and PCK. As for the main research results, science teacher PCK in future schools should include expertise in organizing science classes centered on convergence topics, expertise in digital platforms and ICT use, and expertise in building a network of learning communities and resources, as part of the expertise of human teachers differentiated from AI. Teacher educators' PCK includes expertise in the research and development of T-L methods using AI, expertise in the knowledge construction process and practice, and expertise in developing preservice teachers' research competencies. Discussed in the conclusion is the change in teacher PCK and teacher educator PCK with changes in science knowledge, such as convergence-type knowledge and cognition-value integrated knowledge; and the need to emphasize values, attitudes, and ethical judgments for the coexistence of humans and non-humans as school science knowledge in the post-humanism future society.

A Lifelog Posture Estimation Web Program Using Arduino and FSR402 Sensors

  • Ae-Ri Jung;Min-Seok Song;Hyun-Seo Shin;Young-Bok Cho
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.11
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    • pp.251-258
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    • 2024
  • In this paper, we propose a posture correction system using the Arduino FSR402 sensor and Skeleton Keypoint artificial intelligence model. In anticipation of the introduction of AI Digital Textbook (AIDT), which will be fully implemented from 2025 under the 2022 curriculum reform, the need for research to raise awareness of the risk of digital diseases among children and adolescents and to prevent them is emphasized. The proposed system learns the correct posture for each user based on their life log information and helps them maintain good posture by determining whether they are using a smart device correctly and guiding them. In particular, for children and adolescents who experience physical changes, it has the advantage of learning the changed body information from the Skeleton Keypoint artificial intelligence model to guide the appropriate posture, and it can be confirmed that the sensor's measurement value operates normally within the error range (average error 2.53%) in measuring the correct posture for each user.

Digital Transformation: Using D.N.A.(Data, Network, AI) Keywords Generalized DMR Analysis (디지털 전환: D.N.A.(Data, Network, AI) 키워드를 활용한 토픽 모델링)

  • An, Sehwan;Ko, Kangwook;Kim, Youngmin
    • Knowledge Management Research
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    • v.23 no.3
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    • pp.129-152
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    • 2022
  • As a key infrastructure for digital transformation, the spread of data, network, artificial intelligence (D.N.A.) fields and the emergence of promising industries are laying the groundwork for active digital innovation throughout the economy. In this study, by applying the text mining methodology, major topics were derived by using the abstract, publication year, and research field of the study corresponding to the SCIE, SSCI, and A&HCI indexes of the WoS database as input variables. First, main keywords were identified through TF and TF-IDF analysis based on word appearance frequency, and then topic modeling was performed using g-DMR. With the advantage of the topic model that can utilize various types of variables as meta information, it was possible to properly explore the meaning beyond simply deriving a topic. According to the analysis results, topics such as business intelligence, manufacturing production systems, service value creation, telemedicine, and digital education were identified as major research topics in digital transformation. To summarize the results of topic modeling, 1) research on business intelligence has been actively conducted in all areas after COVID-19, and 2) issues such as intelligent manufacturing solutions and metaverses have emerged in the manufacturing field. It has been confirmed that the topic of production systems is receiving attention once again. Finally, 3) Although the topic itself can be viewed separately in terms of technology and service, it was found that it is undesirable to interpret it separately because a number of studies comprehensively deal with various services applied by combining the relevant technologies.