• Title/Summary/Keyword: AI Digital Textbook

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Analysis of AI Digital Textbook Keywords Using Text Mining (텍스트 마이닝을 활용한 AI 디지털교과서 키워드 분석)

  • Junhong Min;Mi Ryang Kim
    • Journal of Information Technology Services
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    • v.23 no.5
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    • pp.87-105
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    • 2024
  • This study aims to explore the potential issues and challenges associated with the development, introduction, utilization, and stabilization of AI digital textbook, as well as to identify tasks necessary to address these challenges. We collected and analyzed data from domestic news articles and previous research literature related to "AI digital textbook" to derive key keywords using a comprehensive text analysis approach with Bigkinds and Textom. Through Bigkinds, we conducted keyword trend analysis, associated word analysis, and relationship analysis. Using Textom, we performed keyword frequency analysis, N-gram analysis, TF-IDF(Term Frequency-Inverse Document Frequency) analysis, and network analysis. This approach allowed us to identify the main issues related to the development, implementation, utilization of AI digital textbook and explore the necessary tasks to address these challenges.

Introduction of AI digital textbooks in mathematics: Elementary school teachers' perceptions, needs, and challenges (수학 AI 디지털교과서의 도입: 초등학교 교사가 바라본 인식, 요구사항, 그리고 도전)

  • Kim, Somin;Lee, GiMa;Kim, Hee-jeong
    • Education of Primary School Mathematics
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    • v.27 no.3
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    • pp.199-226
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    • 2024
  • In response to the era of transformation necessitating the introduction of Artificial Intelligence (AI) and digital technologies, educational innovation is undertaken with the implementation of AI digital textbooks in Mathematics, English, and Information subjects by 2025 in Korea. Within this context, this study analyzed the perceptions and needs of elementary school teachers regarding mathematics AI digital textbook. Based on a survey conducted in November 2023, involving 132 elementary school teachers across the country, the analysis revealed that the majority of elementary school teachers had a low perception of the introduction and need for mathematics AI digital textbooks. However, some recognized the potential for personalized learning and effective teaching support. Furthermore, among the core technologies of the AI digital textbook, teachers highly valued the necessity of learning diagnostics and teacher reconfiguration functions and had the most positive perception of their usefulness in math lessons, while their perception of interactivity was relatively low. These findings suggest the need for changing teachers' perceptions through professional development and information provision to ensure the successful adoption and use of mathematics AI digital textbooks. Specifically, providing concrete and practical ways to use the AI digital textbook, exploring alternatives to digital overload, and continuing development and research on core technologies.

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.

An analysis of the use of technology tools in high school mathematics textbooks based (고등학교 수학 교과서의 공학 도구 활용 현황 분석)

  • Oh, Se Jun
    • Communications of Mathematical Education
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    • v.38 no.2
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    • pp.263-286
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    • 2024
  • With the introduction of AI digital textbooks, interest in the use of technology tools in mathematics education is increasing. Technology tools have the advantage of visualizing mathematical concepts and discovering mathematical principles through experimentation and inquiry. The 2015 revised mathematics curriculum in Korea already mentions the use of technology tools, and accordingly, various teaching and learning activities using technology tools are presented in mathematics textbooks. However, there is still a lack of systematic analysis on the types and utilization methods of technology tools presented in textbooks. Therefore, this study analyzed the current status of the use of technology tools presented in high school mathematics textbooks based on the 2015 revised curriculum. To this end, the types of technology tools presented in mathematics textbooks were categorized, and the utilization ratio of each category was investigated. In addition, the utilization patterns of technology tools were analyzed by subject and content area, and the utilization ratio of technology tools according to the type of teaching and learning activities was examined. The results showed that technology tools were used in various types and ratios according to the subject and content area. In particular, technology tools in the symbol-manipulation graphing software category accounted for 58% of the total usage cases, showing the highest proportion. By subject, the use of symbol-manipulation graphing software was prominent in subjects dealing with the analysis area, while the use of dynamic geometry software was relatively high in the geometry area. In terms of teaching and learning activity types, the utilization ratio of auxiliary tool type (49%) and intended inquiry induction type (37%) was high. The results of this study show that technology tools play various roles in mathematics textbooks and provide useful implications for improving mathematics teaching and learning methods using technology tools in the future. Furthermore, it can contribute to the establishment of educational policies related to AI digital textbooks and the development of teacher training programs.